179 results on '"Reid SW"'
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2. Profiling training preparation in young Australian Thoroughbred racehorses
- Author
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Cogger, N, primary, Perkins, N, additional, Hodgson, DR, additional, Reid, SW, additional, and Evans, DL, additional
- Published
- 2008
- Full Text
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3. HLA class I binding motifs derived from random peptide libraries differ at the COOH terminus from those of eluted peptides
- Author
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Davenport, MP, Smith, KJ, Barouch, D, Reid, SW, Bodnar, WM, Willis, AC, Hunt, DF, Hill, AVS, Davenport, MP, Smith, KJ, Barouch, D, Reid, SW, Bodnar, WM, Willis, AC, Hunt, DF, and Hill, AVS
- Abstract
Recombinant HLA-A2, HLA-B8, or HLA-B53 heavy chain produced in Escherichia coli was combined with recombinant β2-microglobulin (β2m) and a pool of randomly synthesised nonamer peptides. This mixture was allowed to refold to form stable major histocompatibility complex (MHC) class I complexes, which were then purified by gel filtration chromatography. The peptides bound to the MHC class I molecules were subsequently eluted and sequenced as a pool. Peptide binding motifs for these three MHC class I molecules were derived and compared with previously described motifs derived from analysis of naturally processed peptides eluted from the surface of cells. This comparison indicated that the peptides bound by the recombinant MHC class I molecules showed a similar motif to naturally processed and presented peptides, with the exception of the peptide COOH terminus. Whereas the motifs derived from naturally processed peptides eluted from HLA-A2 and HLA-B8 indicated a strong preference for hydrophobic amino acids at the COOH terminus, this preference was not observed in our studies. We propose that this difference reflects the effects of processing or transport on the peptide repertoire available for binding to MHC class I molecules in vivo.
- Published
- 1997
4. Geographic determinants of reported human Campylobacter infections in Scotland.
- Author
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Bessell PR, Matthews L, Smith-Palmer A, Rotariu O, Strachan NJ, Forbes KJ, Cowden JM, Reid SW, Innocent GT, Bessell, Paul R, Matthews, Louise, Smith-Palmer, Alison, Rotariu, Ovidiu, Strachan, Norval J C, Forbes, Ken J, Cowden, John M, Reid, Stuart W J, and Innocent, Giles T
- Abstract
Background: Campylobacteriosis is the leading cause of bacterial gastroenteritis in most developed countries. People are exposed to infection from contaminated food and environmental sources. However, the translation of these exposures into infection in the human population remains incompletely understood. This relationship is further complicated by differences in the presentation of cases, their investigation, identification, and reporting; thus, the actual differences in risk must be considered alongside the artefactual differences.Methods: Data on 33,967 confirmed Campylobacter infections in mainland Scotland between 2000 and 2006 (inclusive) that were spatially referenced to the postcode sector level were analysed. Risk factors including the Carstairs index of social deprivation, the easting and northing of the centroid of the postcode sector, measures of livestock density by species and population density were tested in univariate screening using a non-spatial generalised linear model. The NHS Health Board of the case was included as a random effect in this final model. Subsequently, a spatial generalised linear mixed model (GLMM) was constructed and age-stratified sensitivity analysis was conducted on this model.Results: The spatial GLMM included the protective effects of the Carstairs index (relative risk (RR) = 0.965, 95% Confidence intervals (CIs) = 0.959, 0.971) and population density (RR = 0.945, 95% CIs = 0.916, 0.974. Following stratification by age group, population density had a significant protective effect (RR = 0.745, 95% CIs = 0.700, 0.792) for those under 15 but not for those aged 15 and older (RR = 0.982, 95% CIs = 0.951, 1.014). Once these predictors have been taken into account three NHS Health Boards remain at significantly greater risk (Grampian, Highland and Tayside) and two at significantly lower risk (Argyll and Ayrshire and Arran).Conclusions: The less deprived and children living in rural areas are at the greatest risk of being reported as a case of Campylobacter infection. However, this analysis cannot differentiate between actual risk and heterogeneities in individual reporting behaviour; nevertheless this paper has demonstrated that it is possible to explain the pattern of reported Campylobacter infections using both social and environmental predictors. [ABSTRACT FROM AUTHOR]- Published
- 2010
- Full Text
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5. Constraints on dark photon dark matter using data from LIGO's and Virgo's third observing run
- Author
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Abbott, R., Abbott, T. D., Acernese, F., Ackley, K., Adams, C., Adhikari, N., Adhikari, R. X., Adya, V. B., Affeldt, C., Agarwal, D., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Allocca, A., Altin, P. A., Amato, A., Ananyeva, A., Anderson, S. B., Anderson, W. G., Ando, M., Andrade, T., Andres, N., Angelova, V, Ansoldi, S., Antelis, J. M., Antier, S., Appert, S., Arai, Koji, Arai, Koya, Arai, Y., Araki, S., Araya, A., Araya, M. C., Areeda, J. S., Arene, M., Aritomi, N., Arnaud, N., Aronson, S. M., Arun, K. G., Asada, H., Asali, Y., Ashton, G., Aso, Y., Assiduo, M., Aston, S. M., Astone, P., Aubin, F., Austin, C., Babak, S., Badaracco, F., Bader, M. K. M., Badger, C., Bae, S., Bae, Y., Baer, A. M., Bagnasco, S., Bai, Y., Baiotti, L., Baird, J., Bajpai, R., Ball, M., Ballardin, G., Ballmer, S. W., Balsamo, A., Baltus, G., Banagiri, S., Bankar, D., Barayoga, J. C., Barbieri, C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Barton, M. A., Bartos, I, Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Baylor, A. C., Bazzan, M., Becsy, B., Bedakihale, V. M., Bejger, M., Belahcene, I, Benedetto, V, Beniwal, D., Bennett, T. F., Bentley, J. D., Benyaala, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Are, R., Bhardwaj, U., Bhattacharjee, D., Bhaumik, S., Bilenko, I. A., Billingsley, G., Bini, S., Birney, R., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Biswas, B., Bitossi, M., Bizouard, M-A, Blackburn, J. K., Blair, C. D., Blair, D. G., Blair, R. M., Bobba, F., Bode, N., Boer, M., Bogaert, G., Boldrini, M., Bonavena, L. D., Bondu, F., Bonilla, E., Bonn, Booker, P., Boom, B. A., Bork, R., Boschi, V, Bose, N., Bose, S., Bossilkov, V, Boudart, V, Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. R., Bramley, A., Branch, A., Branchesi, M., Brau, J. E., Breschi, M., Briant, T., Briggs, J. H., Brillet, A., Brinkmann, M., Brockill, P., Brooks, A. F., Brooks, J., Brown, D. D., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bulik, T., Bulten, H. J., Buonanno, A., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Cadonati, L., Cagnoli, G., Cahillane, C., Calderon Bustillo, J., Callaghan, J. D., Callister, T. A., Calloni, E., Cameron, J., Camp, J. B., Canepa, M., Canevarolo, S., Cannavacciuolo, M., Cannon, K. C., Cao, H., Cao, Z., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlin, J. B., Carney, M. F., Carpinelli, M., Carrillo, G., Carullo, G., Carver, T. L., Diaz, J. Casanueva, Casentini, C., Castaldi, G., Caudill, S., Cavaglia, M., Cavalier, F., Cavalieri, R., Ceasar, M., Cella, G., Cerda-Duran, P., Cesarini, E., Chaibi, W., Chakravarti, K., Subrahmanya, S. Chalathadka, Champion, E., Chan, C-H, Chan, C., Chan, C. L., Chan, K., Chan, M., Ra, K., Chanial, P., Chao, S., Charlton, P., Chase, E. A., Chass, e-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, C., Chen, H. Y., Chen, J., Chen, K., Chen, X., Chen, Y-B, Chen, Y-R, Chen, Z., Cheng, H., Cheong, C. K., Cheung, H. Y., Chia, H. Y., Chiadini, F., Chiang, C-Y, Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Cho, G., Cho, H. S., Choudhary, R. K., Choudhary, S., Christensen, N., Chu, H., Chu, Q., Chu, Y-K, Chua, S., Chung, K. W., Ciani, G., Ciecielag, P., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Cipriano, F., Cirone, A., Clara, F., Clark, E. N., Clark, J. A., Clarke, L., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Codazzo, E., Cohadon, P-F, Cohen, D. E., Cohen, L., Colleoni, M., Collette, C. G., Colombo, A., Colpi, M., Compton, C. M., Constancio, J, R., Conti, L., Cooper, S. J., Corban, P., Corbitt, T. R., Cordero-Carrion, I, Corezzi, S., Corley, K. R., Cornish, N., Corre, D., Corsi, A., Cortese, S., Costa, C. A., Cotesta, R., Coughlin, M. W., Coulon, J-P, Countryman, S. T., Cousins, B., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, D. C., Coyne, R., Creighton, J. D. E., Creighton, T. D., Criswell, A. W., Croquette, M., Crowder, S. G., Cudell, J. R., Cullen, T. J., Cumming, A., Cummings, R., Cunningham, L., Cuoco, E., Dabadie, P., Dal Canton, T., Dall'Osso, S., Dalya, G., Dana, A., Daneshgaranbajastani, L. M., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darsow-Fromm, C., Dasgupta, A., Datrier, L. E. H., Datta, S., Dattilo, V, Dave, I, Davier, M., Davies, G. S., Davis, D., Davis, M. C., Daw, E. J., Dean, R., Debra, D., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deleglise, S., Del Favero, V, De Lillo, F., De Lillo, N., Del Pozzo, W., Demarchi, L. M., De Matteis, F., D'Emilio, V, Demos, N., Dent, T., Depasse, A., De Pietri, R., De Rosa, R., De Rossi, C., Desalvo, R., De Simone, R., Dhur, Har, S., Diaz, M. C., Diaz-Ortiz, Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giorgio, C., Di Giovanni, F., Di Giovanni, M., Di Girolamo, T., Di Lieto, A., Ding, B., Di Pace, S., Di Palma, I, Di Renzo, F., Divakarla, A. K., Dmitriev, A., Doctor, Z., D'Onofrio, L., Donovan, F., Dooley, K. L., Doravari, S., Dorrington, I, Drago, M., Driggers, J. C., Drori, Y., Ducoin, J-G, Dupej, P., Durante, O., D'Urso, D., Duverne, P-A, Dwyer, S. E., Eassa, C., Easter, P. J., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eguchi, S., Eichholz, J., Eikenberry, S. S., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Engelby, E., Enomoto, Y., Errico, L., Essick, R. C., Estelles, H., Estevez, D., Etienne, Z., Etzel, T., Evans, M., Evans, T. M., Ewing, B. E., Fafone, V, Fair, H., Fairhurst, S., Farah, A. M., Farinon, S., Farr, B., Farr, W. M., Farrow, N. W., Fauchon-Jones, E. J., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Fenyvesi, E., Ferguson, D. L., Fern, ez-Galiana, A., Ferrante, I, Ferreira, T. A., Fidecaro, F., Figura, P., Fiori, I, Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V, Flaminio, R., Floden, E., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franke, A., Frasca, S., Frasconi, F., Frederick, C., Freed, J. P., Frei, Z., Freise, A., Frey, R., Fritschel, P., Frolov, V. V., Fronze, G. G., Fujii, Y., Fujikawa, Y., Fukunaga, M., Fukushima, M., Fulda, P., Fyffe, M., Gabbard, H. A., Gadre, B. U., Gair, J. R., Gais, J., Galaudage, S., Gamba, R., Ganapathy, D., Ganguly, A., Gao, D., Gaonkar, S. G., Garaventa, B., Garcia-Nunez, C., Garcia-Quiros, C., Garufi, F., Gateley, B., Gaudio, S., Gayathri, V, G-G, Ge, Gemme, G., Gennai, A., George, J., Gerberding, O., Gergely, L., Gewecke, P., Ghonge, S., Ghosh, Abhirup, Ghosh, Archisman, Ghosh, Shaon, Ghosh, Shrobana, Giacomazzo, B., Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gier, C., Giesler, M., Giri, P., Gissi, F., Glanzer, J., Gleckl, A. E., Godwin, P., Goetz, E., Goetz, R., Gohlke, N., Goncharov, B., Gonzalez, G., Gopakumar, A., Gosselin, M., Gouaty, R., Gould, D. W., Grace, B., Grado, A., Granata, M., Granata, V, Grant, A., Gras, S., Grassia, P., Gray, C., Gray, R., Greco, G., Green, A. C., Green, R., Gretarsson, A. M., Gretarsson, E. M., Griffith, D., Griffiths, W., Griggs, H. L., Grignani, G., Grimaldi, A., Grimm, S. J., Grote, H., Grunewald, S., Gruning, P., Guerra, D., Guidi, G. M., Guimaraes, A. R., Guixe, G., Gulati, H. K., Guo, H-K, Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, P., Gustafson, E. K., Gustafson, R., Guzman, F., Ha, S., Haegel, L., Hagiwara, A., Haino, S., Halim, O., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W-B, Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O., Hansen, H., Hansen, T. J., Hanson, J., Harder, T., Hardwick, T., Haris, K., Harms, J., Harry, G. M., Harry, I. W., Hartwig, D., Hasegawa, K., Haskell, B., Hasskew, R. K., Haster, C-J, Hattori, K., Haughian, K., Hayakawa, H., Hayama, K., Hayes, F. J., Healy, J., Heidmann, A., Heidt, A., Heintze, M. C., Heinze, J., Heinzel, J., Heitmann, H., Hellman, F., Hello, P., Helmling-Cornell, A. F., Hemming, G., Hendry, M., Heng, I. S., Hennes, E., Hennig, J., Hennig, M. H., Hern, A. G., Ez, Vivanco, F. Hern, Heurs, M., Hild, S., Hill, P., Himemoto, Y., Hines, A. S., Hiranuma, Y., Hirata, N., Hirose, E., Hochheim, S., Hofman, D., Hohmann, J. N., Holcomb, D. G., Holl, N. A., Hollows, I. J., Holmes, Z. J., Holt, K., Holz, D. E., Hong, Z., Hopkins, P., Hough, J., Hourihane, S., Howell, E. J., Hoy, C. G., Hoyl, Hreibi, A., Hsieh, B-H, Hsu, Y., Huang, G-Z, Huang, H-Y, Huang, P., Huang, Y-C, Huang, Y-J, Huang, Y., Hubner, M. T., Huddart, A. D., Hughey, B., Hui, D. C. Y., Hui, V, Husa, S., Huttner, S. H., Huxford, R., Huynh-Dinh, T., Ide, S., Idzkowski, B., Iess, A., Ikenoue, B., Imam, S., Inayoshi, K., Ingram, C., Inoue, Y., Ioka, K., Isi, M., Isleif, K., Ito, K., Itoh, Y., Iyer, B. R., Izumi, K., Jaberianhamedan, V, Jacqmin, T., Jadhav, S. J., Jadhav, S. P., James, A. L., Jan, A. Z., Jani, K., Janquart, J., Janssens, K., Janthalur, N. N., Jaranowski, P., Jariwala, D., Jaume, R., Jenkins, A. C., Jenner, K., Jeon, C., Jeunon, M., Jia, W., Jin, H-B, Johns, G. R., Jones, A. W., Jones, I, Jones, J. D., Jones, P., Jones, R., Jonker, R. J. G., Ju, L., Jung, P., Jung, K., Junker, J., Juste, V, Kaihotsu, K., Kajita, T., Kakizaki, M., Kalaghatgi, Kalogera, V, Kamai, B., Kamiizumi, M., K, A, N., Hasamy, S., Kang, G., Kanner, J. B., Kao, Y., Kapadia, S. J., Kapasi, D. P., Karat, S., Karathanasis, C., Karki, S., Kashyap, R., Kasprzack, M., Kastaun, W., Katsanevas, S., Katsavounidis, E., Katzman, W., Kaur, T., Kawabe, K., Kawaguchi, K., Kawai, N., Kawasaki, T., Kefelian, F., Keitel, D., Key, J. S., Khadka, S., Khalili, F. Y., Khan, S., Khazanov, E. A., Khetan, N., Khursheed, M., Kijbunchoo, N., Kim, C., Kim, J. C., Kim, J., Kim, K., Kim, W. S., Kim, Y-M, Kimball, C., Kimura, N., Kinley-Hanlon, M., Kirchhoff, R., Kissel, J. S., Kita, N., Kitazawa, H., Kleybolte, L., Klimenko, S., Knee, A. M., Knowles, T. D., Knyazev, E., Koch, P., Koekoek, G., Kojima, Y., Kokeyama, K., Koley, S., Kolitsidou, P., Kolstein, M., Komori, K., Kondrashov, V, Kong, A. K. H., Kontos, A., Koper, N., Korobko, M., Kotake, K., Kovalam, M., Kozak, D. B., Kozakai, C., Kozu, R., Kringel, V, Krishnendu, Krolak, A., Kuehn, G., Kuei, F., Kuijer, P., Kumar, A., Kumar, P., Kumar, Rahul, Kumar, Rakesh, Kume, J., Kuns, K., Kuo, C., Kuo, H-S, Kuromiya, Y., Kuroyanagi, S., Kusayanagi, K., Kuwahara, S., Kwak, K., Lagabbe, P., Laghi, D., Lal, E, E., Lam, T. L., Lamberts, A., L, Ry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., La Rosa, I, Lartaux-Vollard, A., Lasky, P. D., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., Leavey, S., Lecoeuche, Y. K., Lee, H. K., Lee, H. M., Lee, H. W., Lee, J., Lee, K., Lee, R., Lehmann, J., Lemaitre, A., Leonardi, M., Leroy, N., Letendre, N., Levesque, C., Levin, Y., Leviton, J. N., Leyde, K., A. K. Y., Li, Li, B., Li, J., K. L., Li, T. G. F., Li, Li, X., Lin, C-Y, Lin, F-K, Lin, F-L, Lin, H. L., Lin, L. C-C, Linde, F., Linker, S. D., Linley, J. N., Littenberg, T. B., Liu, G. C., Liu, J., Liu, K., Liu, X., Llamas, F., Llorens-Monteagudo, M., R. K. L., Lo, Lockwood, A., London, L. T., Longo, A., Lopez, D., Portilla, M. Lopez, Lorenzini, M., Loriette, V, Lorm, Losurdo, G., Lott, T. P., Lough, J. D., Lousto, C. O., Lovelace, G., Lucaccioni, J. F., Luck, H., Lumaca, D., Lundgren, A. P., Luo, L-W, Lynam, J. E., Macas, R., Macinnis, M., Macleod, D. M., Macmillan, I. A. O., Macquet, A., I. Magana, Ez, Magazzu, C., Magee, R. M., Maggiore, R., Magnozzi, M., Mahesh, S., Majorana, E., Makarem, C., Maksimovic, I, Maliakal, S., Malik, A., Man, N., M, Ic, V, Mangano, V, Mango, J. L., Mansell, G. L., Manske, M., Mantovani, M., Mapelli, M., Marchesoni, F., Marchio, M., Marion, F., Mark, Z., Marka, S., Marka, Z., Markakis, C., Markosyan, A. S., Markowitz, A., Maros, E., Marquina, A., Marsat, S., Martelli, F., Martin, I. W., Martin, R. M., Martinez, M., Martinez, V. A., Martinez, V, Martinovic, K., Martynov, Marx, E. J., Masalehdan, H., Mason, K., Massera, E., Masserot, A., Massinger, T. J., Masso-Reid, M., Mastrogiovanni, S., Matas, A., Mateu-Lucena, M., Matichard, F., Matiushechkina, M., Mavalvala, N., Mccann, J. J., Mccarthy, R., Mcclell, D. E., Mcclincy, P. K., Mccormick, S., Mcculler, L., Mcghee, Mcguire, S. C., Mcisaac, C., Mciver, J., Mcrae, T., Mcwilliams, S. T., Meacher, D., Mehmet, M., Mehta, A. K., Meijer, Q., Melatos, A., Melchor, D. A., Mendell, G., Menendez-Vazquez, A., Menoni, C. S., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Merritt, J. D., Merzougui, M., Meshkov, S., Messenger, C., Messick, C., Meyers, P. M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I, Michel, C., Michimura, Y., Middleton, H., Milano, L., Miller, A. L., Miller, A., Miller, B., Millhouse, M., Mills, J. C., Milotti, E., Minazzoli, O., Minenkov, Y., Mio, N., Mir, Ll M., Miravet-Tenes, M., Mishra, C., Mishra, T., Mistry, T., Mitra, S., Mitrofanov, V. P., Mitselmakher, G., Mittleman, R., Miyakawa, O., Miyamoto, A., Miyazaki, Y., Miyo, K., Miyoki, S., Geoffrey, Mo, Moguel, E., Mogushi, K., Mohapatra, S. R. P., Mohite, S. R., Molina, I, Molina-Ruiz, M., Mondin, M., Montani, M., Moore, C. J., Moraru, D., Morawski, F., More, A., Moreno, C., Moreno, G., Mori, Y., Morisaki, S., Moriwaki, Y., Mours, B., Mow-Lowry, C. M., Mozzon, S., Muciaccia, F., Mukherjee, Arunava, Mukherjee, D., Mukherjee, Soma, Mukherjee, Subroto, Mukherjee, Suvodip, Mukund, N., Mullavey, A., Munch, J., Muniz, E. A., Murray, P. G., Musenich, R., Muusse, S., Nadji, S. L., Nagano, K., Nagano, S., Nagar, A., Nakamura, K., Nakano, H., Nakano, M., Nakashima, R., Nakayama, Y., Napolano, V, Nardecchia, I, Narikawa, T., Naticchioni, L., Nayak, B., Nayak, R. K., Negishi, R., Neil, B. F., Neilson, J., Nelemans, G., Nelson, T. J. N., Nery, M., Neubauer, P., Neunzert, A., K. Y., Ng, S. W. S., Ng, Nguyen, C., Nguyen, P., Nguyen, T., Quynh, L. Nguyen, W-T, Ni, Nichols, S. A., Nishizawa, A., Nissanke, S., Nitoglia, E., Nocera, F., Norman, M., North, C., Nozaki, S., Nuttall, L. K., Oberling, J., O'Brien, B. D., Obuchi, Y., O'Dell, J., Oelker, E., Ogaki, W., Oganesyan, G., J. J., Oh, Oh, K., S. H., Oh, Ohashi, M., Ohishi, N., Ohkawa, M., Ohme, F., Ohta, H., Okada, M. A., Okutani, Y., Okutomi, K., Olivetto, C., Oohara, K., Ooi, C., Oram, R., O'Reilly, B., Ormiston, R. G., Ormsby, N. D., Ortega, L. F., O'Shaughnessy, R., O'Shea, E., Oshino, S., Ossokine, S., Osthelder, C., Otabe, S., Ottaway, D. J., Overmier, H., Pace, A. E., Pagano, G., Page, M. A., Pagliaroli, G., Pai, A., Pai, S. A., Palamos, J. R., Palashov, O., Palomba, C., Pan, H., Pan, K., P, P. K., A, Pang, H., Pang, P. T. H., Pankow, C., Pannarale, F., Pant, B. C., Panther, F. H., Paoletti, F., Paoli, A., Paolone, A., Parisi, A., Park, H., Park, J., Parker, W., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passuello, D., Patel, M., Pathak, M., Patricelli, B., Patron, A. S., Patrone, S., Paul, S., Payne, E., Pedraza, M., Pegoraro, M., Pele, A., Arellano, F. E. Pena, Penn, S., Perego, A., Pereira, A., Pereira, T., Perez, C. J., Perigois, C., Perkins, C. C., Perreca, A., Perries, S., Petermann, J., Petterson, D., Pfeiffer, H. P., Pham, K. A., Phukon, K. S., Piccinni, O. J., Pichot, M., Piendibene, M., Piergiovanni, F., Pierini, L., Pierro, V, Pillant, G., Pillas, M., Pilo, F., Pinard, L., Pinto, I. M., Pinto, M., Piotrzkowski, K., Pirello, M., Pitkin, M. D., Placidi, E., Planas, L., Plastino, W., Pluchar, C., Poggiani, R., Polini, E., Pong, D. Y. T., Ponrathnam, S., Popolizio, P., Porter, E. K., Poulton, R., Powell, J., Pracchia, M., Pradier, T., Prajapati, A. K., Prasai, K., Prasanna, R., Pratten, G., Principe, M., Prodi, G. A., Prokhorov, L., Prosposito, P., Prudenzi, L., Puecher, A., Punturo, M., Puosi, F., Puppo, P., Purrer, M., Qi, H., Quetschke, V, Quitzow-James, R., Raab, F. J., Raaijmakers, G., Radkins, H., Radulesco, N., Raffai, P., Rail, S. X., Raja, S., Rajan, C., Ramirez, K. E., Ramirez, T. D., Ramos-Buades, A., Rana, J., Rapagnani, P., Rapol, U. D., Ray, A., Raymond, V, Raza, N., Razzano, M., Read, J., Rees, L. A., Regimbau, T., Rei, L., Reid, S., Reid, S. W., Reitze, D. H., Relton, P., Renzini, A., Rettegno, P., Rezac, M., Ricci, F., Richards, D., Richardson, J. W., Richardson, L., Riemenschneider, G., Riles, K., Rinaldi, S., Rink, K., Rizzo, M., Robertson, N. A., Robie, R., Robinet, F., Rocchi, A., Rodriguez, S., Roll, Rollins, J. G., Romanelli, M., Romano, R., Romel, C. L., Romero-Rodriguez, A., Romero-Shaw, I. M., Romie, J. H., Ronchini, S., Rosa, L., Rose, C. A., Ross, M. P., Rowan, S., Rowlinson, S. J., Roy, S., Roy, Santosh, Roy, Soumen, Rozza, D., Ruggi, P., Ryan, K., Sachdev, S., Sadecki, T., Sadiq, J., Sago, N., Saito, S., Saito, Y., Sakai, K., Sakai, Y., Sakellariadou, M., Sakuno, Y., Salafia, O. S., Salconi, L., Saleem, M., Salemi, F., Samajdar, A., Sanchez, E. J., Sanchez, J. H., Sanchez, L. E., Sanchis-Gual, N., S, Ers, J. R., Sanuy, A., Saravanan, T. R., Sarin, N., Sassolas, B., Satari, H., Sathyaprakash, B. S., Sato, S., Sato, T., Sauter, O., Savage, R. L., Sawada, T., Sawant, D., Sawant, H. L., Sayah, S., Schaetzl, D., Scheel, M., Scheuer, J., Schiworski, M., Schmidt, P., Schmidt, S., Schnabel, R., Schneewind, M., Schofield, R. M. S., Schoenbeck, A., Schulte, B. W., Schutz, B. F., Schwartz, E., Scott, J., Scott, S. M., Seglar-Arroyo, M., Sekiguchi, T., Sekiguchi, Y., Sellers, D., Sengupta, A. S., Sentenac, D., Seo, E. G., Sequino, V, Sergeev, A., Setyawati, Y., Shaffer, T., Shahriar, M. S., Shams, B., Shao, L., Sharma, A., Sharma, P., Shawhan, P., Shcheblanov, N. S., Shibagaki, S., Shikauchi, M., Shimizu, R., Shimoda, T., Shimode, K., Shinkai, H., Shishido, T., Shoda, A., Shoemaker, D. H., Shoemaker, D. M., Shyamsundar, S., Sieniawska, M., Sigg, D., Singer, L. P., Singh, D., Singh, N., Singha, A., Sintes, A. M., Sipala, V, Skliris, V, Slagmolen, B. J. 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L., Ushiba, T., Utina, A., Vahlbruch, H., Vajente, G., Vajpeyi, A., Valdes, G., Valentini, M., Valsan, V., van Bakel, N., van Beuzekom, M., van den Br, J. F. J., Van den Broeck, C., er-Hyde, D. C., van der Schaaf, L., Van, Heijningen, Vanosky, J., van Putten, M. H. P. M., van Remortel, N., Vardaro, M., Vargas, A. F., Varma, V., Vasuth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venneberg, J., Venugopalan, G., Verkindt, D., Verma, P., Verma, Y., Veske, D., Vetrano, F., Vicere, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Villa-Ortega, V., Vinet, J-Y, Virtuoso, A., Vitale, S., Vo, T., Vocca, H., von Reis, E. R. G., von Wrangel, J. S. A., Vorvick, C., Vyatchanin, S. P., Wade, L. E., Wade, M., Wagner, K. J., Walet, R. C., Walker, M., Wallace, G. S., Wallace, L., Walsh, S., Wang, J., Wang, J. Z., Wang, W. H., Ward, R. L., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watchi, J., Weaver, B., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Weller, C. M., Wellmann, F., Wen, L., Wessels, P., Wette, K., Whelan, J. T., White, D. D., Whiting, B. F., Whittle, C., Wilken, D., Williams, D., Williams, M. J., Williamson, A. R., Willis, J. L., Willke, B., Wilson, D. J., Winkler, W., Wipf, C. C., Wlodarczyk, T., Woan, G., Woehler, J., Wofford, J. K., Wong, I. C. F., Wu, C., D. S., Wu, Wu, H., Wu, S., Wysocki, D. M., Xiao, L., W-R, Xu, Yamada, T., Yamamoto, H., Yamamoto, Kazuhiro, Yamamoto, Kohei, Yamamoto, T., Yamashita, K., Yamazaki, R., Yang, F. W., Yang, L., Yang, Y., Yang, Yang, Yang, Z., Yap, M. J., Yeeles, D. W., Yelikar, A. B., Ying, M., Yokogawa, K., Yokoyama, J., Yokozawa, T., Yoo, J., Yoshioka, T., Hang, Yu, Haocun, Yu, Yuzurihara, H., Zanolin, M., Zeidler, S., Zelenova, T., Zendri, J-P, Zevin, M., Zhan, M., Zhang, H., Zhang, J., Zhang, L., Zhang, T., Zhang, Y., Zhao, C., Zhao, G., Zhao, Y., Zhao, Yue, Zhou, R., Zhou, Z., Zhu, X. J., Zhu, Z-H, Zucker, M. 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D., Acernese, F., Ackley, K., Adams, C., Adhikari, N., Adhikari, R. X., Adya, V. B., Affeldt, C., Agarwal, D., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Allocca, A., Altin, P. A., Amato, A., Anand, C., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Ando, M., Andrade, T., Andres, N., Andric, T., Angelova, S. V., Ansoldi, S., Antelis, J. M., Antier, S., Appert, S., Arai, K., Arai, Y., Araki, S., Araya, A., Araya, M. C., Areeda, J. S., Arene, M., Aritomi, N., Arnaud, N., Aronson, S. M., Arun, K. G., Asada, H., Asali, Y., Ashton, G., Aso, Y., Assiduo, M., Aston, S. M., Astone, P., Aubin, F., Austin, C., Babak, S., Badaracco, F., Bader, M. K. M., Badger, C., Bae, S., Bae, Y., Baer, A. M., Bagnasco, S., Bai, Y., Baiotti, L., Baird, J., Bajpai, R., Ball, M., Ballardin, G., Ballmer, S. W., Balsamo, A., Baltus, G., Banagiri, S., Bankar, D., Barayoga, J. C., Barbieri, C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Barton, M. A., Bartos, I., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Baylor, A. C., Bazzan, M., Becsy, B., Bedakihale, V. M., Bejger, M., Belahcene, I., Benedetto, V., Beniwal, D., Bennett, T. F., Bentley, J. D., Benyaala, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bhandare, R., Bhardwaj, U., Bhattacharjee, D., Bhaumik, S., Bilenko, I. A., Billingsley, G., Bini, S., Birney, R., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Biswas, B., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blair, C. D., Blair, D. G., Blair, R. M., Bobba, F., Bode, N., Boer, M., Bogaert, G., Boldrini, M., Bonavena, L. D., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., Boom, B. A., Bork, R., Boschi, V., Bose, N., Bose, S., Bossilkov, V., Boudart, V., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. 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L., Chan, K., Chan, M., Chandra, K., Chanial, P., Chao, S., Charlton, P., Chase, E. A., Chassande-Mottin, E., Chatterjee, C., Chatterjee, D., Chaturvedi, M., Chaty, S., Chen, C., Chen, H. Y., Chen, J., Chen, K., Chen, X., Chen, Y. -B., Chen, Y. -R., Chen, Z., Cheng, H., Cheong, C. K., Cheung, H. Y., Chia, H. Y., Chiadini, F., Chiang, C. -Y., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Cho, G., Cho, H. S., Choudhary, R. K., Choudhary, S., Christensen, N., Chu, H., Chu, Q., Chu, Y. -K., Chua, S., Chung, K. W., Ciani, G., Ciecielag, P., Cieslar, M., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Cipriano, F., Cirone, A., Clara, F., Clark, E. N., Clark, J. A., Clarke, L., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Codazzo, E., Cohadon, P. -F., Cohen, D. E., Cohen, L., Colleoni, M., Collette, C. G., Colombo, A., Colpi, M., Compton, C. M., Constancio, M., Conti, L., Cooper, S. J., Corban, P., Corbitt, T. R., Cordero-Carrion, I., Corezzi, S., Corley, K. 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S., Taranto, C., Tasson, J. D., Telada, S., Tenorio, R., Terhune, J. E., Terkowski, L., Thirugnanasambandam, M. P., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tiwari, S., Tiwari, V., Toivonen, A. M., Toland, K., Tolley, A. E., Tomaru, T., Tomigami, Y., Tomura, T., Tonelli, M., Torres-Forne, A., Torrie, C. I., E Melo, I. T., Toyra, D., Trapananti, A., Travasso, F., Traylor, G., Trevor, M., Tringali, M. C., Tripathee, A., Troiano, L., Trovato, A., Trozzo, L., Trudeau, R. J., Tsai, D. S., Tsai, D., Tsang, K. W., Tsang, T., Tsao, J. -S., Tse, M., Tso, R., Tsubono, K., Tsuchida, S., Tsukada, L., Tsuna, D., Tsutsui, T., Tsuzuki, T., Turbang, K., Turconi, M., Tuyenbayev, D., Ubhi, A. S., Uchikata, N., Uchiyama, T., Udall, R. P., Ueda, A., Uehara, T., Ueno, K., Ueshima, G., Uraguchi, F., Urban, A. L., Ushiba, T., Utina, A., Vahlbruch, H., Vajente, G., Vajpeyi, A., Valdes, G., Valentini, M., Valsan, V., Van Bakel, N., Van Beuzekom, M., Van Den Brand, J. F. J., Van Den Broeck, C., Vander-Hyde, D. C., Van Der Schaaf, L., Van Heijningen, J. V., Vanosky, J., Van Putten, M. H. P. M., Van Remortel, N., Vardaro, M., Vargas, A. F., Varma, V., Vasuth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venneberg, J., Venugopalan, G., Verkindt, D., Verma, P., Verma, Y., Veske, D., Vetrano, F., Vicere, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Villa-Ortega, V., Vinet, J. -Y., Virtuoso, A., Vitale, S., Vo, T., Vocca, H., Von Reis, E. R. G., Von Wrangel, J. S. A., Vorvick, C., Vyatchanin, S. P., Wade, L. E., Wade, M., Wagner, K. J., Walet, R. C., Walker, M., Wallace, G. S., Wallace, L., Walsh, S., Wang, J., Wang, J. Z., Wang, W. H., Ward, R. L., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watchi, J., Weaver, B., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Weller, C. M., Wellmann, F., Wen, L., Wessels, P., Wette, K., Whelan, J. T., White, D. D., Whiting, B. F., Whittle, C., Wilken, D., Williams, D., Williams, M. J., Williamson, A. R., Willis, J. L., Willke, B., Wilson, D. J., Winkler, W., Wipf, C. C., Wlodarczyk, T., Woan, G., Woehler, J., Wofford, J. K., Wong, I. C. F., Wu, C., Wu, D. S., Wu, H., Wu, S., Wysocki, D. M., Xiao, L., Xu, W. -R., Yamada, T., Yamamoto, H., Yamamoto, K., Yamamoto, T., Yamashita, K., Yamazaki, R., Yang, F. W., Yang, L., Yang, Y., Yang, Z., Yap, M. J., Yeeles, D. W., Yelikar, A. B., Ying, M., Yokogawa, K., Yokoyama, J., Yokozawa, T., Yoo, J., Yoshioka, T., Yu, H., Yuzurihara, H., Zadrozny, A., Zanolin, M., Zeidler, S., Zelenova, T., Zendri, J. -P., Zevin, M., Zhan, M., Zhang, H., Zhang, J., Zhang, L., Zhang, T., Zhang, Y., Zhao, C., Zhao, G., Zhao, Y., Zhou, R., Zhou, Z., Zhu, X. J., Zhu, Z. -H., Zucker, M. E., Zweizig, J., Andrić, T., Arai, Koji, Arai, Koya, Arène, M., Bécsy, B., Bustillo, J. Calderón, Diaz, J. Casanueva, Cavaglià, M., Cerdá-Durán, P., Subrahmanya, S. Chalathadka, Chatterjee, Debarati, Chatterjee, Deep, Chiang, C-Y., Chu, Y-K., Cieślar, M., Cordero-Carrión, I., Curyło, M., Canton, T. Dal, Dall’Osso, S., Dálya, G., D’Angelo, B., D’Antonio, S., Deléglise, S., D’Emilio, V., Díaz, M. C., D’Onofrio, L., D’Urso, D., Estellés, H., Fronzé, G. G., García-Núñez, C., García-Quirós, C., Ghosh, Abhirup, Ghosh, Archisman, Ghosh, Shaon, Ghosh, Shrobana, González, G., Guixé, G., Gupta, Anchal, Gupta, Anuradha, Vivanco, F. Hernandez, Hsieh, B-H., Huang, G-Z., Huang, H-Y., Huang, Y-C., Hübner, M. T., Kéfélian, F., Królak, A., Kumar, Rahul, Kumar, Rakesh, Kuo, H-S., Lemaître, A., Lin, C-Y., Lin, F-K., Lin, F-L., Portilla, M. Lopez, Lück, H., Hernandez, I. Magaña, Magazzù, C., Márka, S., Márka, Z., Mir, Ll. M., Miravet-Tenés, M., Mo, Geoffrey, Mukherjee, Arunava, Mukherjee, Soma, Mukherjee, Subroto, Mukherjee, Suvodip, Muñiz, E. A., Quynh, L. Nguyen, O’Brien, B. D., O’Dell, J., O’Reilly, B., O’Shaughnessy, R., O’Shea, E., Arellano, F. E. Peña, Périgois, C., Perriès, S., Pinto, I. M., Pürrer, M., Romero-Rodríguez, A., Rosińska, D., Roy, Santosh, Roy, Soumen, Schönbeck, A., Suzuki, Takamasa, Suzuki, Toshikazu, Szczepańczyk, M. J., Tanaka, Kazuyuki, Tanaka, Kenta, Tanaka, Taiki, Tanaka, Takahiro, Martin, E. N. Tapia San, Martín, E. N. Tapia San, Tiwari, Shubhanshu, Tiwari, Srishti, Torres-Forné, A., e Melo, I. Tosta, Töyrä, D., Tsao, J-S., van Bakel, N., van Beuzekom, M., van den Brand, J. F. J., van der Schaaf, L., van Heijningen, J. V., van Putten, M. H. P. M., van Remortel, N., Vasúth, M., Viceré, A., von Reis, E. R. G., von Wrangel, J. S. A., Weßels, P., Xu, W-R., Yamamoto, Kazuhiro, Yamamoto, Kohei, Yang, Yang, Yu, Hang, Yu, Haocun, Zadrożny, A., Zhao, Yue, Other Research IHEF (IoP, FNWI), High Energy Astrophys. & Astropart. Phys (API, FNWI), Astroparticle Physics (IHEF, IoP, FNWI), Gravitation and Astroparticle Physics Amsterdam, IoP (FNWI), The LIGO Scientific Collaboration, The Virgo Collaboration, The KAGRA Collaboration, Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-École Nationale Supérieure des Sciences Appliquées et de Technologie (ENSSAT)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Université de Strasbourg (UNISTRA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), RS: FSE Grav. waves and fundamental physics, Grav. waves and fundamental physics, RS: FSE MSP, Abbott, R, Abbott, Td, Acernese, F, Ackley, K, Adams, C, Adhikari, N, Adhikari, Rx, Adya, Vb, Affeldt, C, Agarwal, D, Agathos, M, Agatsuma, K, Aggarwal, N, Aguiar, Od, Aiello, L, Ain, A, Ajith, P, Akutsu, T, Albanesi, S, Allocca, A, Altin, Pa, Amato, A, Anand, C, Anand, S, Ananyeva, A, Anderson, Sb, Anderson, Wg, Ando, M, Andrade, T, Andres, N, Angelova, Sv, Ansoldi, S, Antelis, Jm, Antier, S, Appert, S, Arai, K, Arai, Y, Araki, S, Araya, A, Araya, Mc, Areeda, J, Arene, M, Aritomi, N, Arnaud, N, Aronson, Sm, Arun, Kg, Asada, H, Asali, Y, Ashton, G, Aso, Y, Assiduo, M, Aston, Sm, Astone, P, Aubin, F, Austin, C, Babak, S, Badaracco, F, Bader, Mkm, Badger, C, Bae, S, Bae, Y, Baer, Am, Bagnasco, S, Bai, Y, Baiotti, L, Baird, J, Bajpai, R, Ball, M, Ballardin, G, Ballmer, Sw, Balsamo, A, Baltus, G, Banagiri, S, Bankar, D, Barayoga, Jc, Barbieri, C, Barish, Bc, Barker, D, Barneo, P, Barone, F, Barr, B, Barsotti, L, Barsuglia, M, Barta, D, Bartlett, J, Barton, Ma, Bartos, I, Bassiri, R, Basti, A, Bawaj, M, Bayley, Jc, Baylor, Ac, Bazzan, M, Becsy, B, Bedakihale, Vm, Bejger, M, Belahcene, I, Benedetto, V, Beniwal, D, Bennett, Tf, Bentley, Jd, Benyaala, M, Bergamin, F, Berger, Bk, Bernuzzi, S, Bersanetti, D, Bertolini, A, Betzwieser, J, Beveridge, D, Bhandare, R, Bhardwaj, U, Bhattacharjee, D, Bhaumik, S, Bilenko, Ia, Billingsley, G, Bini, S, Birney, R, Birnholtz, O, Biscans, S, Bischi, M, Biscoveanu, S, Bisht, A, Biswas, B, Bitossi, M, Bizouard, Ma, Blackburn, Jk, Blair, Cd, Blair, Dg, Blair, Rm, Bobba, F, Bode, N, Boer, M, Bogaert, G, Boldrini, M, Bonavena, Ld, Bondu, F, Bonilla, E, Bonnand, R, Booker, P, Boom, Ba, Bork, R, Boschi, V, Bose, N, Bose, S, Bossilkov, V, Boudart, V, Bouffanais, Y, Bozzi, A, Bradaschia, C, Brady, Pr, Bramley, A, Branch, A, Branchesi, M, Brau, Je, Breschi, M, Briant, T, Briggs, Jh, Brillet, A, Brinkmann, M, Brockill, P, Brooks, Af, Brooks, J, Brown, Dd, Brunett, S, Bruno, G, Bruntz, R, Bryant, J, Bulik, T, Bulten, Hj, Buonanno, A, Buscicchio, R, Buskulic, D, Buy, C, Byer, Rl, Cadonati, L, Cagnoli, G, Cahillane, C, Bustillo, Jc, Callaghan, Jd, Callister, Ta, Calloni, E, Cameron, J, Camp, Jb, Canepa, M, Canevarolo, S, Cannavacciuolo, M, Cannon, Kc, Cao, H, Cao, Z, Capocasa, E, Capote, E, Carapella, G, Carbognani, F, Carlin, Jb, Carney, Mf, Carpinelli, M, Carrillo, G, Carullo, G, Carver, Tl, Diaz, Jc, Casentini, C, Castaldi, G, Caudill, S, Cavaglia, M, Cavalier, F, Cavalieri, R, Ceasar, M, Cella, G, Cerda-Duran, P, Cesarini, E, Chaibi, W, Chakravarti, K, Subrahmanya, Sc, Champion, E, Chan, Ch, Chan, C, Chan, Cl, Chan, K, Chan, M, Chandra, K, Chanial, P, Chao, S, Charlton, P, Chase, Ea, Chassande-Mottin, E, Chatterjee, C, Chatterjee, D, Chaturvedi, M, Chaty, S, Chen, C, Chen, Hy, Chen, J, Chen, K, Chen, X, Chen, Yb, Chen, Yr, Chen, Z, Cheng, H, Cheong, Ck, Cheung, Hy, Chia, Hy, Chiadini, F, Chiang, Cy, Chiarini, G, Chierici, R, Chincarini, A, Chiofalo, Ml, Chiummo, A, Cho, G, Cho, H, Choudhary, Rk, Choudhary, S, Christensen, N, Chu, H, Chu, Q, Chu, Yk, Chua, S, Chung, Kw, Ciani, G, Ciecielag, P, Cifaldi, M, Ciobanu, Aa, Ciolfi, R, Cipriano, F, Cirone, A, Clara, F, Clark, En, Clark, Ja, Clarke, L, Clearwater, P, Clesse, S, Cleva, F, Coccia, E, Codazzo, E, Cohadon, Pf, Cohen, De, Cohen, L, Colleoni, M, Collette, Cg, Colombo, A, Colpi, M, Compton, Cm, Constancio, M, Conti, L, Cooper, Sj, Corban, P, Corbitt, Tr, Cordero-Carrion, I, Corezzi, S, Corley, Kr, Cornish, N, Corre, D, Corsi, A, Cortese, S, Costa, Ca, Cotesta, R, Coughlin, Mw, Coulon, Jp, Countryman, St, Cousins, B, Couvares, P, Coward, Dm, Cowart, Mj, Coyne, Dc, Coyne, R, Creighton, Jde, Creighton, Td, Criswell, Aw, Croquette, M, Crowder, Sg, Cudell, Jr, Cullen, Tj, Cumming, A, Cummings, R, Cunningham, L, Cuoco, E, Dabadie, P, Dal Canton, T, Dall'Osso, S, Dalya, G, Dana, A, Daneshgaranbajastani, Lm, D'Angelo, B, Danilishin, S, D'Antonio, S, Danzmann, K, Darsow-Fromm, C, Dasgupta, A, Datrier, Leh, Datta, S, Dattilo, V, Dave, I, Davier, M, Davies, G, Davis, D, Davis, Mc, Daw, Ej, Dean, R, Debra, D, Deenadayalan, M, Degallaix, J, De Laurentis, M, Deleglise, S, Del Favero, V, De Lillo, F, De Lillo, N, Del Pozzo, W, Demarchi, Lm, De Matteis, F, D'Emilio, V, Demos, N, Dent, T, Depasse, A, De Pietri, R, De Rosa, R, De Rossi, C, Desalvo, R, De Simone, R, Dhurandhar, S, Diaz, Mc, Diaz-Ortiz, M, Didio, Na, Dietrich, T, Di Fiore, L, Di Fronzo, C, Di Giorgio, C, Di Giovanni, F, Di Giovanni, M, Di Girolamo, T, Di Lieto, A, Ding, B, Di Pace, S, Di Palma, I, Di Renzo, F, Divakarla, Ak, Dmitriev, A, Doctor, Z, D'Onofrio, L, Donovan, F, Dooley, Kl, Doravari, S, Dorrington, I, Drago, M, Driggers, Jc, Drori, Y, Ducoin, Jg, Dupej, P, Durante, O, D'Urso, D, Duverne, Pa, Dwyer, Se, Eassa, C, Easter, Pj, Ebersold, M, Eckhardt, T, Eddolls, G, Edelman, B, Edo, Tb, Edy, O, Effler, A, Eguchi, S, Eichholz, J, Eikenberry, S, Eisenmann, M, Eisenstein, Ra, Ejlli, A, Engelby, E, Enomoto, Y, Errico, L, Essick, Rc, Estelles, H, Estevez, D, Etienne, Z, Etzel, T, Evans, M, Evans, Tm, Ewing, Be, Fafone, V, Fair, H, Fairhurst, S, Farah, Am, Farinon, S, Farr, B, Farr, Wm, Farrow, Nw, Fauchon-Jones, Ej, Favaro, G, Favata, M, Fays, M, Fazio, M, Feicht, J, Fejer, Mm, Fenyvesi, E, Ferguson, Dl, Fernandez-Galiana, A, Ferrante, I, Ferreira, Ta, Fidecaro, F, Figura, P, Fiori, I, Fishbach, M, Fisher, Rp, Fittipaldi, R, Fiumara, V, Flaminio, R, Floden, E, Fong, H, Font, Ja, Fornal, B, Forsyth, Pwf, Franke, A, Frasca, S, Frasconi, F, Frederick, C, Freed, Jp, Frei, Z, Freise, A, Frey, R, Fritschel, P, Frolov, Vv, Fronze, Gg, Fujii, Y, Fujikawa, Y, Fukunaga, M, Fukushima, M, Fulda, P, Fyffe, M, Gabbard, Ha, Gadre, Bu, Gair, Jr, Gais, J, Galaudage, S, Gamba, R, Ganapathy, D, Ganguly, A, Gao, D, Gaonkar, Sg, Garaventa, B, Garcia-Nunez, C, Garcia-Quiros, C, Garufi, F, Gateley, B, Gaudio, S, Gayathri, V, Ge, Gg, Gemme, G, Gennai, A, George, J, Gerberding, O, Gergely, L, Gewecke, P, Ghonge, S, Ghosh, A, Ghosh, S, Giacomazzo, B, Giacoppo, L, Giaime, Ja, Giardina, Kd, Gibson, Dr, Gier, C, Giesler, M, Giri, P, Gissi, F, Glanzer, J, Gleckl, Ae, Godwin, P, Goetz, E, Goetz, R, Gohlke, N, Goncharov, B, Gonzalez, G, Gopakumar, A, Gosselin, M, Gouaty, R, Gould, Dw, Grace, B, Grado, A, Granata, M, Granata, V, Grant, A, Gras, S, Grassia, P, Gray, C, Gray, R, Greco, G, Green, Ac, Green, R, Gretarsson, Am, Gretarsson, Em, Griffith, D, Griffiths, W, Griggs, Hl, Grignani, G, Grimaldi, A, Grimm, Sj, Grote, H, Grunewald, S, Gruning, P, Guerra, D, Guidi, Gm, Guimaraes, Ar, Guixe, G, Gulati, Hk, Guo, Hk, Guo, Y, Gupta, A, Gupta, P, Gustafson, Ek, Gustafson, R, Guzman, F, Ha, S, Haegel, L, Hagiwara, A, Haino, S, Halim, O, Hall, Ed, Hamilton, Ez, Hammond, G, Han, Wb, Haney, M, Hanks, J, Hanna, C, Hannam, Md, Hannuksela, O, Hansen, H, Hansen, Tj, Hanson, J, Harder, T, Hardwick, T, Haris, K, Harms, J, Harry, Gm, Harry, Iw, Hartwig, D, Hasegawa, K, Haskell, B, Hasskew, Rk, Haster, Cj, Hattori, K, Haughian, K, Hayakawa, H, Hayama, K, Hayes, Fj, Healy, J, Heidmann, A, Heidt, A, Heintze, Mc, Heinze, J, Heinzel, J, Heitmann, H, Hellman, F, Hello, P, Helmling-Cornell, Af, Hemming, G, Hendry, M, Heng, I, Hennes, E, Hennig, J, Hennig, Mh, Hernandez, Ag, Vivanco, Fh, Heurs, M, Hild, S, Hill, P, Himemoto, Y, Hines, A, Hiranuma, Y, Hirata, N, Hirose, E, Hochheim, S, Hofman, D, Hohmann, Jn, Holcomb, Dg, Holland, Na, Hollows, Ij, Holmes, Zj, Holt, K, Holz, De, Hong, Z, Hopkins, P, Hough, J, Hourihane, S, Howell, Ej, Hoy, Cg, Hoyland, D, Hreibi, A, Hsieh, Bh, Hsu, Y, Huang, Gz, Huang, Hy, Huang, P, Huang, Yc, Huang, Yj, Huang, Y, Hubner, Mt, Huddart, Ad, Hughey, B, Hui, Dcy, Hui, V, Husa, S, Huttner, Sh, Huxford, R, Huynh-Dinh, T, Ide, S, Idzkowski, B, Iess, A, Ikenoue, B, Imam, S, Inayoshi, K, Ingram, C, Inoue, Y, Ioka, K, Isi, M, Isleif, K, Ito, K, Itoh, Y, Iyer, Br, Izumi, K, Jaberianhamedan, V, Jacqmin, T, Jadhav, Sj, Jadhav, Sp, James, Al, Jan, Az, Jani, K, Janquart, J, Janssens, K, Janthalur, Nn, Jaranowski, P, Jariwala, D, Jaume, R, Jenkins, Ac, Jenner, K, Jeon, C, Jeunon, M, Jia, W, Jin, Hb, Johns, Gr, Jones, Aw, Jones, Di, Jones, Jd, Jones, P, Jones, R, Jonker, Rjg, Ju, L, Jung, P, Jung, K, Junker, J, Juste, V, Kaihotsu, K, Kajita, T, Kakizaki, M, Kalaghatgi, Cv, Kalogera, V, Kamai, B, Kamiizumi, M, Kanda, N, Kandhasamy, S, Kang, G, Kanner, Jb, Kao, Y, Kapadia, Sj, Kapasi, Dp, Karat, S, Karathanasis, C, Karki, S, Kashyap, R, Kasprzack, M, Kastaun, W, Katsanevas, S, Katsavounidis, E, Katzman, W, Kaur, T, Kawabe, K, Kawaguchi, K, Kawai, N, Kawasaki, T, Kefelian, F, Keitel, D, Key, J, Khadka, S, Khalili, Fy, Khan, S, Khazanov, Ea, Khetan, N, Khursheed, M, Kijbunchoo, N, Kim, C, Kim, Jc, Kim, J, Kim, K, Kim, W, Kim, Ym, Kimball, C, Kimura, N, Kinley-Hanlon, M, Kirchhoff, R, Kissel, J, Kita, N, Kitazawa, H, Kleybolte, L, Klimenko, S, Knee, Am, Knowles, Td, Knyazev, E, Koch, P, Koekoek, G, Kojima, Y, Kokeyama, K, Koley, S, Kolitsidou, P, Kolstein, M, Komori, K, Kondrashov, V, Kong, Akh, Kontos, A, Koper, N, Korobko, M, Kotake, K, Kovalam, M, Kozak, Db, Kozakai, C, Kozu, R, Kringel, V, Krishnendu, Nv, Krolak, A, Kuehn, G, Kuei, F, Kuijer, P, Kumar, A, Kumar, P, Kumar, R, Kume, J, Kuns, K, Kuo, C, Kuo, H, Kuromiya, Y, Kuroyanagi, S, Kusayanagi, K, 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coupling: (dark matter baryon) ,Nuclear and High Energy Physics ,data analysis method ,Cosmology and Nongalactic Astrophysics (astro-ph.CO) ,gr-qc ,Astronomy ,Astrophysics::High Energy Astrophysical Phenomena ,FOS: Physical sciences ,detector: noise ,General Relativity and Quantum Cosmology (gr-qc) ,Astrophysics::Cosmology and Extragalactic Astrophysics ,Astronomy & Astrophysics ,dark matter: direct detection ,coupling: minimal ,General Relativity and Quantum Cosmology ,dark matter ,Physics, Particles & Fields ,gravitational wave detectors ,High Energy Physics - Phenomenology (hep-ph) ,Fourier transformation ,correlation function ,LIGO ,gravitational wave ,QC ,QB ,Settore FIS/01 ,Science & Technology ,mirror: oscillation ,Physics ,gravitational radiation ,tachyon: stability ,hep-ph ,field theory: scalar ,detector: sensitivity ,High Energy Physics - Phenomenology ,cosmic string: decay ,VIRGO ,Physics and Astronomy ,[PHYS.HPHE]Physics [physics]/High Energy Physics - Phenomenology [hep-ph] ,Physical Sciences ,astro-ph.CO ,[PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc] ,gravitational radiation detector: interferometer ,[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph] ,Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
LIGO Scientific Collaboration - Virgo Collaboration - KAGRA Collaboration: Abbott, R. et al., We present a search for dark photon dark matter that could couple to gravitational-wave interferometers using data from Advanced LIGO and Virgo’s third observing run. To perform this analysis, we use two methods, one based on cross-correlation of the strain channels in the two nearly aligned LIGO detectors, and one that looks for excess power in the strain channels of the LIGO and Virgo detectors. The excess power method optimizes the Fourier transform coherence time as a function of frequency, to account for the expected signal width due to Doppler modulations. We do not find any evidence of dark photon dark matter with a mass between mA∼10−14–10−11 eV/c2, which corresponds to frequencies between 10–2000 Hz, and therefore provide upper limits on the square of the minimum coupling of dark photons to baryons, i.e., U(1)B dark matter. For the cross-correlation method, the best median constraint on the squared coupling is ∼1.31×10−47 at mA∼4.2×10−13eV/c2; for the other analysis, the best constraint is ∼2.4×10−47 at mA∼5.7×10−13eV/c2. These limits improve upon those obtained in direct dark matter detection experiments by a factor of ∼100 for mA∼[2–4]×10−13eV/c2, and are, in absolute terms, the most stringent constraint so far in a large mass range mA∼2×10−13–8×10−12eV/c2., This material is based upon work supported by NSF’s LIGO Laboratory which is a major facility fully funded by the National Science Foundation. The authors also gratefully acknowledge the support of the Science and Technology Facilities Council (STFC) of the United Kingdom, the Max-Planck-Society (MPS), and the State of Niedersachsen/ Germany for support of the construction of Advanced LIGO and construction and operation of the GEO600 detector. Additional support for Advanced LIGO was provided by the Australian Research Council. The authors gratefully acknowledge the Italian Istituto Nazionale di Fisica Nucleare (INFN), the French Centre National de la Recherche Scientifique (CNRS) and the Netherlands Organization for Scientific Research, for the construction and operation of the Virgo detector and the creation and support of the EGO consortium. The authors also gratefully acknowledge research support fromthese agencies as well as by the Council of Scientific and Industrial Research of India, the Department of Science and Technology, India, the Science & Engineering Research Board (SERB), India, the Ministry of Human Resource Development, India, the Spanish Agencia Estatal de Investigación, the Vicepresidencia i Conselleria d’Innovació, Recerca i Turisme and the Conselleria d’Educació i Universitat del Govern de les Illes Balears, the Conselleria d’Innovació, Universitats, Ciencia i Societat Digital de la Generalitat Valenciana and the CERCA Programme Generalitat de Catalunya, Spain, the National Science Centre of Poland and the Foundation for Polish Science (FNP), the Swiss National Science Foundation (SNSF), the Russian Foundation for Basic Research, the Russian Science Foundation, the European Commission, the European Regional Development Funds (ERDF), the Royal Society, the Scottish Funding Council, the Scottish Universities Physics Alliance, the Hungarian Scientific Research Fund (OTKA), the French Lyon Institute of Origins (LIO), the Belgian Fonds de la Recherche Scientifique (FRS-FNRS), Actions de Recherche Concert´ees (ARC) and Fonds Wetenschappelijk Onderzoek—Vlaanderen (FWO), Belgium, the Paris Île-de-France Region, the National Research, Development and Innovation Office Hungary (NKFIH), the National Research Foundation of Korea, the Natural Science and Engineering Research Council Canada, Canadian Foundation for Innovation (CFI), the Brazilian Ministry of Science, Technology, and Innovations, the International Center for Theoretical Physics South American Institute for Fundamental Research (ICTPSAIFR), the Research Grants Council of Hong Kong, the National Natural Science Foundation of China (NSFC), the Leverhulme Trust, the Research Corporation, the Ministry of Science and Technology (MOST), Taiwan, the United States Department of Energy, and the Kavli Foundation. The authors gratefully acknowledge the support of the NSF, STFC, INFN and CNRS for provision of computational resources. This work was supported by MEXT, JSPS Leading-edge Research Infrastructure Program, JSPS Grant-in-Aid for Specially Promoted Research 26000005, JSPS Grant-in-Aid for Scientific Research on Innovative Areas 2905: No. JP17H06358, No. JP17H06361 and No. JP17H06364, JSPS Core-to-Core Program A. Advanced Research Networks, JSPS Grant-in-Aid for Scientific Research (S) No. 17H06133, the joint research program of the Institute forCosmic Ray Research, University of Tokyo, National Research Foundation (NRF) and Computing Infrastructure Project of KISTI-GSDC in Korea, Academia Sinica (AS), AS Grid Center (ASGC) and the Ministry of Science and Technology (MoST) in Taiwan under grants including AS-CDA-105-M06, Advanced Technology Center (ATC) of NAOJ, and Mechanical Engineering Center of KEK.
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- 2022
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6. All-sky search for gravitational wave emission from scalar boson clouds around spinning black holes in LIGO O3 data
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Abbott, R., Abe, H., Acernese, F., Ackley, K., Adhikari, N., Adhikari, R. X., Adkins, V. K., Adya, V. B., Affeldt, C., Agarwal, D., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Allocca, A., Altin, P. A., Amato, A., Ananyeva, A., Anderson, S. B., Anderson, W. G., Ando, M., Andrade, T., Andres, N., Andres-Carcasona, M., Angelova, V, Ansoldi, S., Antelis, J. M., Antier, S., Apostolatos, T., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Arene, M., Aritomi, N., Arnaud, N., Arogeti, M., Aronson, S. M., Arun, K. G., Asada, H., Asali, Y., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Aubin, F., Aultoneal, K., Austin, C., Babak, S., Badaracco, F., Bader, M. K. M., Badger, C., Bae, S., Bae, Y., Baer, A. M., Bagnasco, S., Bai, Y., Baird, J., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. 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M., Badger, C., Bae, S., Bae, Y., Baer, A. M., Bagnasco, S., Bai, Y., Baird, J., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Balsamo, A., Baltus, G., Banagiri, S., Banerjee, B., Bankar, D., Barayoga, J. C., Barbieri, C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Barton, M. A., Bartos, I., Basak, S., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Becher, B. R., Bécsy, B., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belahcene, I., Benedetto, V., Beniwal, D., Benjamin, M. G., Bennett, T. F., Bentley, J. D., Benyaala, M., Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bhandare, R., Bhandari, A. V., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Bini, S., Birney, R., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Biswas, B., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blair, C. D., Blair, D. G., Blair, R. M., Bobba, F., Bode, N., Boër, M., Bogaert, G., Boldrini, M., Bolingbroke, G. N., Bonavena, L. D., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., Boom, B. A., Bork, R., Boschi, V., Bose, N., Bose, S., Bossilkov, V., Boudart, V., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. R., Bramley, A., Branch, A., Branchesi, M., Brau, J. E., Breschi, M., Briant, T., Briggs, J. H., Brillet, A., Brinkmann, M., Brockill, P., Brooks, A. F., Brooks, J., Brown, D. D., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cadonati, L., Caesar, M., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. 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Shoemaker, D. ???H., Shoemaker, D. ???M., Singer, L. ???P., Singh, M. ???K., Sintes, A. ???M., Slagmolen, B. ???J. ???J., Slaven-Blair, T. ???J., Smith, J. ???R., Smith, R. ???J. ???E., Somala, S. ???N., Spencer, A. ???P., Srivastava, A. ???K., Steer, D. ???A., Stops, D. ???J., Strain, K. ???A., Strang, L. ???C., Strong, M. ???D., Stuver, A. ???L., Suh, H. ???G., Sullivan, A. ???G., Summerscales, T. ???Z., Sutton, P. ???J., Swinkels, B. ???L., Szczepa??czyk, M. ???J., Tait, S. ???C., Talbot, C. ???J., Tanasijczuk, A. ???J., Tanner, D. ???B., Tapia, R. ???D., Tapia San Mart??n, E. ???N., Tasson, J. ???D., Terhune, J. ???E. ???S., Thirugnanasambandam, M. ???P., Thompson, E. ???E., Thompson, J. ???E., Thondapu, S. ???R., Thorne, K. ???A., Toivonen, A. ???M., Tolley, A. ???E., Torres-Forn??, A., Torrie, C. ???I., Tosta e Melo, I., T??yr??, D., Tringali, M. ???C., Trudeau, R. ???J., Tsang, K. ???W., Ubhi, A. ???S., Udall, R. ???P., Unnikrishnan, C. ???S., Urban, A. ???L., van den Brand, J. 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Angelova, Sv, Antelis, Jm, Appavuravther, Ez, Apple, Sk, Araya, Mc, Aronson, Sm, Arun, Kg, Melo, Sad, Aston, Sm, Bader, Mkm, Baer, Am, Ballmer, Sw, Barayoga, Jc, Barish, Bc, Barton, Ma, Bayley, Jc, Becher, Br, Bedakihale, Vm, Benjamin, Mg, Bennett, Tf, Bentley, Jd, Berger, Bk, Bhandari, Av, Bilenko, Ia, Bizouard, Ma, Blackburn, Jk, Blair, Cd, Blair, Dg, Blair, Rm, Bolingbroke, Gn, Bonavena, Ld, Boom, Ba, Brady, Pr, Brau, Je, Briggs, Jh, Brooks, Af, Brown, Dd, Bulten, Hj, Byer, Rl, Davies, Gsc, Bustillo, Jc, Callaghan, Jd, Callister, Ta, Camp, Jb, Cannon, Kc, Carlin, Jb, Carney, Mf, Carver, Tl, Diaz, Jc, Subrahmanya, Sc, Chan, Ch, Chan, Cl, Chang, Ip, Chase, Ea, Chen, Hy, Chen, Yb, Chen, Yr, Cheong, Ck, Cheung, Hy, Chia, Hy, Chiang, Cy, Chiofalo, Ml, Choudhary, Rk, Chu, Yk, Chua, Ssy, Chung, Kw, Ciobanu, Aa, Clark, Ja, Cohadon, Pf, Cohen, De, Collette, Cg, Compton, Cm, Cooper, Sj, Corbitt, Tr, Corley, Kr, Cornish, Nj, Costa, Ca, Coughlin, Mw, Coulon, Jp, Countryman, St, Coward, Dm, Cowart, Mj, Coyne, Dc, Creighton, Jde, Creighton, Td, Criswell, Aw, Crowder, Sg, Cudell, Jr, Cullen, Tj, Dal Canton, T, Datrier, Leh, Davis, Mc, Daw, Ej, Demarchi, Lm, Diaz, Mc, Didio, Na, Divakarla, Ak, Dooley, Kl, Driggers, Jc, Ducoin, Jg, Duverne, Pa, Dwyer, Se, Easter, Pj, Edo, Tb, Eisenstein, Ra, Essick, Rc, Evans, Tm, Ewing, Be, Fan, Pc, Farah, Am, Farr, Wm, Fauchon-Jones, Ej, Fejer, Mm, Ferguson, Dl, Ferreira, Ta, Fisher, Rp, Fong, Hk, Font, Ja, Forsyth, Pwf, Freed, Jp, Frolov, Vv, Fronze, Gg, Gabbard, Ha, Gadre, Bu, Gair, Jr, Gaonkar, Sg, Nunez, Cg, Ge, Gg, Giaime, Ja, Giardina, Kd, Gibson, Dr, Gleckl, Ae, Gould, Dw, Green, Ac, Gretarsson, Am, Gretarsson, Em, Griffiths, Wl, Griggs, Hl, Grimm, Sj, Guidi, Gm, Guimaraes, Ar, Gulati, Hk, Gunny, Am, Guo, Hk, Gupta, Im, Gupta, Sk, Hadiputrawan, Ipw, Hall, Ed, Hamilton, Ez, Han, Wb, Hannam, Md, Hansen, Tj, Harry, Gm, Harry, Iw, Haster, Cj, Hayes, Fj, Heintze, Mc, Helmling-Cornell, Af, Hennig, Mh, Hernandez, Ag, Vivanco, Fh, Hewitt, Al, Ho, Tc, Hohmann, Jn, Holcomb, Dg, Holland, Na, Hollows, Ij, Holmes, Zj, Holz, De, Howell, Ej, Hoy, Cg, Hsieh, Bh, Hsieh, Hf, Huang, Hy, Huang, Yc, Huang, Yj, Huang, Yt, Huang, Yw, Hubner, Mt, Huddart, Ad, Hui, Dcy, Huttner, Sh, Iyer, Br, Jacquet, Pe, Jadhav, Sj, Jadhav, Sp, James, Al, Jan, Az, Janthalur, Nn, Jenkins, Ac, Jin, Hb, Johns, Gr, Jones, Aw, Jones, Di, Kalaghatgi, Cv, Kanner, Jb, Kapadia, Sj, Kapasi, Dp, Khalili, Fy, Khazanov, Ea, Kim, Jc, Kim, Ym, Knee, Am, Knowles, Td, Kong, Akh, Kozak, Db, Krishnendu, Nv, Lam, Tl, Lane, Bb, Lang, Rn, Lasky, Pd, Lecoeuche, Yk, Lee, Hm, Lee, Hw, Legred, In, Leviton, Jn, Li, Aky, Li, Kl, Li, Tgf, Lin, Cy, Lin, Et, Lin, Fk, Lin, Fl, Lin, Hl, Lin, Lcc, Linker, Sd, Linley, Jn, Littenberg, Tb, Liu, Gc, Lo, Rkl, London, Lt, Portilla, Ml, Lott, Tp, Lough, Jd, Lousto, Co, Lucaccioni, Jf, Lundgren, Ap, Luo, Lw, Lynam, Je, Machtinger, Jb, Macleod, Dm, Macmillan, Iao, Hernandez, Im, Magee, Rm, Mansell, Gl, Pina, Dm, Martin, Iw, Martin, Rm, 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- Subjects
Nuclear and High Energy Physics ,gravitational wave emission ,scalar boson clouds ,spinning black holes ,ligo o3 data ,FOS: Physical sciences ,Astronomy & Astrophysics ,Physics, Particles & Fields ,General Relativity and Quantum Cosmology ,Particle dark matter ,QC ,Particle astrophysic ,QB ,astro-ph.HE ,High Energy Astrophysical Phenomena (astro-ph.HE) ,Science & Technology ,Physics ,Classical black hole ,SDG 10 - Reduced Inequalities ,black holes ,Physics and Astronomy ,gravitational waves ,[SDU]Sciences of the Universe [physics] ,Physical Sciences ,Gravitational wave detection ,Gravitational wave source ,Astrophysics - High Energy Astrophysical Phenomena - Abstract
This paper describes the first all-sky search for long-duration, quasi-monochromatic gravitational-wave signals emitted by ultralight scalar boson clouds around spinning black holes using data from the third observing run of Advanced LIGO. We analyze the frequency range from 20~Hz to 610~Hz, over a small frequency derivative range around zero, and use multiple frequency resolutions to be robust towards possible signal frequency wanderings. Outliers from this search are followed up using two different methods, one more suitable for nearly monochromatic signals, and the other more robust towards frequency fluctuations. We do not find any evidence for such signals and set upper limits on the signal strain amplitude, the most stringent being $\approx10^{-25}$ at around 130~Hz. We interpret these upper limits as both an "exclusion region" in the boson mass/black hole mass plane and the maximum detectable distance for a given boson mass, based on an assumption of the age of the black hole/boson cloud system., Comment: 28 pages, 16 figures
- Published
- 2022
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7. Search for Subsolar-Mass Binaries in the First Half of Advanced LIGO's and Advanced Virgo's Third Observing Run.
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Richardson L, Riemenschneider G, Riles K, Rinaldi S, Rink K, Rizzo M, Robertson NA, Robie R, Robinet F, Rocchi A, Rodriguez S, Rolland L, Rollins JG, Romanelli M, Romano R, Romel CL, Romero-Rodríguez A, Romero-Shaw IM, Romie JH, Ronchini S, Rosa L, Rose CA, Rosińska D, Ross MP, Rowan S, Rowlinson SJ, Roy S, Roy S, Roy S, Rozza D, Ruggi P, Ryan K, Sachdev S, Sadecki T, Sadiq J, Sakellariadou M, Salafia OS, Salconi L, Saleem M, Salemi F, Samajdar A, Sanchez EJ, Sanchez JH, Sanchez LE, Sanchis-Gual N, Sanders JR, Sanuy A, Saravanan TR, Sarin N, Sassolas B, Satari H, Sathyaprakash BS, Sauter O, Savage RL, Sawant D, Sawant HL, Sayah S, Schaetzl D, Scheel M, Scheuer J, Schiworski M, Schmidt P, Schmidt S, Schnabel R, Schneewind M, Schofield RMS, Schönbeck A, Schulte BW, Schutz BF, Schwartz E, Scott J, Scott SM, Seglar-Arroyo M, Sellers D, Sengupta AS, Sentenac D, Seo EG, Sequino V, Sergeev A, Setyawati Y, Shaffer T, Shahriar MS, Shams B, Sharma A, Sharma P, Shawhan P, Shcheblanov NS, Shikauchi M, Shoemaker DH, Shoemaker DM, ShyamSundar S, Sieniawska M, Sigg D, Singer LP, Singh D, Singh N, Singha A, Sintes AM, Sipala V, Skliris V, Slagmolen BJJ, Slaven-Blair TJ, Smetana J, Smith JR, Smith RJE, Soldateschi J, Somala SN, Son EJ, Soni K, Soni S, Sordini V, Sorrentino F, Sorrentino N, Soulard R, Souradeep T, Sowell E, Spagnuolo V, Spencer AP, Spera M, Srinivasan R, Srivastava AK, Srivastava V, Staats K, Stachie C, Steer DA, Steinlechner J, Steinlechner S, Stevenson S, Stops DJ, Stover M, Strain KA, Strang LC, Stratta G, Strunk A, Sturani R, Stuver AL, Sudhagar S, Sudhir V, Suh HG, Summerscales TZ, Sun H, Sun L, Sunil S, Sur A, Suresh J, Sutton PJ, Swinkels BL, Szczepańczyk MJ, Szewczyk P, Tacca M, Tait SC, Talbot CJ, Talbot C, Tanasijczuk AJ, Tanner DB, Tao D, Tao L, Martín ENTS, Taranto C, Tasson JD, Tenorio R, Terhune JE, Terkowski L, Thirugnanasambandam MP, Thomas M, Thomas P, Thompson JE, Thondapu SR, Thorne KA, Thrane E, Tiwari S, Tiwari S, Tiwari V, Toivonen AM, Toland K, Tolley AE, Tonelli M, Torres-Forné A, Torrie CI, E Melo IT, Töyrä D, Trapananti A, Travasso F, Traylor G, Trevor M, Tringali MC, Tripathee A, Troiano L, Trovato A, Trozzo L, Trudeau RJ, Tsai DS, Tsai D, Tsang KW, Tse M, Tso R, Tsukada L, Tsuna D, Tsutsui T, Turbang K, Turconi M, Ubhi AS, Udall RP, Ueno K, Unnikrishnan CS, Urban AL, Utina A, Vahlbruch H, Vajente G, Vajpeyi A, Valdes G, Valentini M, Valsan V, van Bakel N, van Beuzekom M, van den Brand JFJ, Van Den Broeck C, Vander-Hyde DC, van der Schaaf L, van Heijningen JV, Vanosky J, van Remortel N, Vardaro M, Vargas AF, Varma V, Vasúth M, Vecchio A, Vedovato G, Veitch J, Veitch PJ, Venneberg J, Venugopalan G, Verkindt D, Verma P, Verma Y, Veske D, Vetrano F, Viceré A, Vidyant S, Viets AD, Vijaykumar A, Villa-Ortega V, Vinet JY, Virtuoso A, Vitale S, Vo T, Vocca H, von Reis ERG, von Wrangel JSA, Vorvick C, Vyatchanin SP, Wade LE, Wade M, Wagner KJ, Walet RC, Walker M, Wallace GS, Wallace L, Walsh S, Wang JZ, Wang WH, Ward RL, Warner J, Was M, Washington NY, Watchi J, Weaver B, Webster SA, Weinert M, Weinstein AJ, Weiss R, Weller CM, Wellmann F, Wen L, Weßels P, Wette K, Whelan JT, White DD, Whiting BF, Whittle C, Wilken D, Williams D, Williams MJ, Williamson AR, Willis JL, Willke B, Wilson DJ, Winkler W, Wipf CC, Wlodarczyk T, Woan G, Woehler J, Wofford JK, Wong ICF, Wu DS, Wysocki DM, Xiao L, Yamamoto H, Yang FW, Yang L, Yang Y, Yang Z, Yap MJ, Yeeles DW, Yelikar AB, Ying M, Yoo J, Yu H, Yu H, Zadrożny A, Zanolin M, Zelenova T, Zendri JP, Zevin M, Zhang J, Zhang L, Zhang T, Zhang Y, Zhao C, Zhao G, Zhao Y, Zhou R, Zhou Z, Zhu XJ, Zimmerman AB, Zucker ME, Zweizig J, Jeong D, and Shandera S
- Abstract
We report on a search for compact binary coalescences where at least one binary component has a mass between 0.2 M_{⊙} and 1.0 M_{⊙} in Advanced LIGO and Advanced Virgo data collected between 1 April 2019 1500 UTC and 1 October 2019 1500 UTC. We extend our previous analyses in two main ways: we include data from the Virgo detector and we allow for more unequal mass systems, with mass ratio q≥0.1. We do not report any gravitational-wave candidates. The most significant trigger has a false alarm rate of 0.14 yr^{-1}. This implies an upper limit on the merger rate of subsolar binaries in the range [220-24200] Gpc^{-3} yr^{-1}, depending on the chirp mass of the binary. We use this upper limit to derive astrophysical constraints on two phenomenological models that could produce subsolar-mass compact objects. One is an isotropic distribution of equal-mass primordial black holes. Using this model, we find that the fraction of dark matter in primordial black holes in the mass range 0.2 M_{⊙}
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- 2022
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8. Self-employment, depression, and older individuals: A cross-country study.
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Patel PC, Reid SW, and Wolfe MT
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- Aged, Employment, Europe, Female, Health Status, Humans, Male, Middle Aged, Retirement, Depression epidemiology, Quality of Life
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Background: Self-employment has become an increasingly popular occupational choice, and there are substantial mental health and well-being benefits that can accrue for individuals who remain active and engaged later in life. In this study, we examine the association between reduced depression symptoms and self-employment in aging workers., Methods: Drawing from The Survey of Health, Ageing and Retirement in Europe (SHARE) data, our study examines a longitudinal sample of 35,717 individuals aged 50 years or older., Results: Our results indicate that self-employment is negatively associated with depression among aging workers. Additionally, we find that this relationship weakens as aging self-employed individuals grow older, and that gender moderates this relationship such that older female self-employed individuals report lower depression symptoms than their male counterparts., Limitations: Our sample is limited to European workers aged 50 years and older, and as such might have limited generalizability to younger self-employed individuals from other geographic regions. Moreover, although we control for factors that could play a role in the association between depression symptoms and self-employment (e.g. quality of life, personality traits, etc.), additional research will be needed in order to determine the potential mediating and moderating roles such factors might have on this relationship., Conclusions: The results we present demonstrate the important and nuanced nature between self-employment and depression symptoms in aging workers. These findings call to light the need to continue to foster and develop systems and programs that help to facilitate self-employment for individuals as they transition into older ages., Competing Interests: Declaration of Competing Interest The authors state that there are no known conflicts of interest regarding the completion and publication of this research study., (Published by Elsevier B.V.)
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- 2020
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9. Gastric dilatation and enterotoxemia in ten captive felids.
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Anderson KM, Garner MM, Clyde VL, Volle KA, Ialeggio DM, Reid SW, Hobbs JK, and Wolf KN
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- Animals, Animals, Zoo, Diagnosis, Differential, Enterotoxemia complications, Enterotoxemia diagnostic imaging, Female, Gastric Dilatation complications, Gastric Dilatation diagnosis, Gastric Dilatation diagnostic imaging, Male, Enterotoxemia diagnosis, Felidae, Gastric Dilatation veterinary
- Abstract
CASE DESCRIPTION 10 large felids at 8 facilities were determined or suspected to have developed gastric dilatation with or without enterotoxemia over a 20-year period. Four felids were found dead with no premonitory signs. CLINICAL FINDINGS 4 felids (2 male snow leopards [Uncia uncia], 1 male Amur tiger [Panthera tigris altaica], and 1 male Sumatran tiger [Panthera tigris sumatrae]) were found dead or died before they could be evaluated. Six felids had hematemesis (1 male and 1 female African lion [Panthera leo] and 1 male jaguar [Panthera onca]) or abdominal distention and signs of lethargy with or without vomiting (1 male African lion, 1 male Malayan tiger [Panthera tigris jacksoni], and 1 female Sumatran tiger). Gastric dilatation was radiographically and surgically confirmed in the male Malayan and female Sumatran tigers and the jaguar. TREATMENT AND OUTCOME In 3 felids with an antemortem diagnosis, the gastric dilatation resolved with decompressive laparotomy but then recurred in 1 felid, which subsequently died. Three others died at various points during hospitalization. Although Clostridium perfringens type A was recovered from 3 of the 5 felids for which microbial culture was performed, and 2 felids had a recent increase in the amount fed, no single factor was definitively identified that might have incited or contributed to the gastric dilatation. CLINICAL RELEVANCE Gastric dilatation was a life-threatening condition in the large felids of this report, causing sudden death or clinical signs of hematemesis, abdominal distention, or vomiting. Even with rapid diagnosis and surgical decompression, the prognosis was poor. Research is needed into the factors that contribute to this emergent condition in large felids so that preventive measures might be taken.
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- 2018
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10. Detection of Rare Antimicrobial Resistance Profiles by Active and Passive Surveillance Approaches.
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Mather AE, Reeve R, Mellor DJ, Matthews L, Reid-Smith RJ, Dutil L, Haydon DT, and Reid SW
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- Animals, Anti-Bacterial Agents pharmacology, Anti-Bacterial Agents therapeutic use, Microbial Sensitivity Tests, Models, Theoretical, Population Surveillance, Salmonella drug effects, Salmonella Infections, Animal drug therapy, Swine, Drug Resistance, Bacterial, Salmonella enterica drug effects
- Abstract
Antimicrobial resistance (AMR) surveillance systems are generally not specifically designed to detect emerging resistances and usually focus primarily on resistance to individual drugs. Evaluating the diversity of resistance, using ecological metrics, allows the assessment of sampling protocols with regard to the detection of rare phenotypes, comprising combinations of resistances. Surveillance data of phenotypic AMR of Canadian poultry Salmonella Heidelberg and swine Salmonella Typhimurium var. 5- were used to contrast active (representative isolates derived from healthy animals) and passive (diagnostic isolates) surveillance and assess their suitability for detecting emerging resistance patterns. Although in both datasets the prevalences of resistance to individual antimicrobials were not significantly different between the two surveillance systems, analysis of the diversity of entire resistance phenotypes demonstrated that passive surveillance of diagnostic isolates detected more unique phenotypes. Whilst the most appropriate surveillance method will depend on the relevant objectives, under the conditions of this study, passive surveillance of diagnostic isolates was more effective for the detection of rare and therefore potentially emerging resistance phenotypes.
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- 2016
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11. Clinical Research Abstracts of the British Equine Veterinary Association Congress 2015.
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Getachew MA, Innocent G, Reid SW, Burden F, and Love S
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Reasons for Performing Study: Although fasciolosis is an important livestock disease worldwide, the public health importance of human fasciolosis has increased in recent years and it is recognised as an important re-emerging zoonotic disease, its epidemiology and pathogenicity in donkeys, and the epidemiological role they may play have not been determined., Objectives: To investigate the epidemiology and pathogenicity of fasciolosis in donkeys., Study Design: Cross-sectional coprological and retrospective post-mortem study., Methods: Faecal samples collected from 803 randomly selected working donkeys from the central region of Ethiopia were analysed by a sedimentation-centrifugation-flotation technique. Further data on liver-flukes and associated pathologies were obtained by routine post mortem examinations of 112 donkeys, subjected to euthanasia on welfare grounds or died. Data were analysed using a generalised linear model and multivariate binary logistic regression in R statistical package with significance level of statistical tests set at P<0.05., Results: Infection prevalences of 44.4% and 41.9% were obtained in coprologically and post mortem examined donkeys, respectively, irrespective of their age. Both Fasciola hepatica and Fasciola gigantica were identified with the mean infection intensity of 30 flukes. Older donkeys (≥8 years) were found harbouring a significantly higher worm burden (P<0.0001). Gross and histopathologies of hyperplasia and thickening of the bile ducts, fibrosis of large portal areas and irregular bile duct proliferation and hypertrophy were noted., Conclusions: The high infection prevalence of fasciolosis and the associated hepatic pathologies in working donkeys shows not only the susceptibility of donkeys and the impact it has on their health, but also indicates the important role they can play in the epidemiology of both livestock and human fasciolosis. These further demonstrate the need for these animals to be considered in the overall epidemiological studies and for sound control strategies and prevention of fasciolosis. Ethical animal research: The research underwent ethical review and the use of animals was approved by the Directors of The Donkey Sanctuary. Consent of the owners was obtained to use their animals., Source of Funding: The Donkey Sanctuary. Competing interests: None declared., (© 2015 The Author(s). Equine Veterinary Journal © 2015 EVJ Ltd.)
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- 2015
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12. A metapopulation model for highly pathogenic avian influenza: implications for compartmentalization as a control measure.
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Nickbakhsh S, Matthews L, Reid SW, and Kao RR
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- Animals, Disease Outbreaks prevention & control, Disease Outbreaks veterinary, Influenza in Birds epidemiology, United Kingdom epidemiology, Communicable Disease Control methods, Influenza in Birds prevention & control, Models, Biological, Poultry
- Abstract
Although the compartmentalization of poultry industry components has substantial economic implications, and is therefore a concept with huge significance to poultry industries worldwide, the current requirements for compartment status are generic to all OIE member countries. We examined the consequences for potential outbreaks of highly pathogenic avian influenza in the British poultry industry using a metapopulation modelling framework. This framework was used to assess the effectiveness of compartmentalization relative to zoning control, utilizing empirical data to inform the structure of potential epidemiological contacts within the British poultry industry via network links and spatial proximity. Conditions were identified where, despite the efficient isolation of poultry compartments through the removal of network-mediated links, spatially mediated airborne spread enabled spillover of infection with nearby premises making compartmentalization a more 'risky' option than zoning control. However, when zoning control did not effectively inhibit long-distance network links, compartmentalization became a relatively more effective control measure than zoning. With better knowledge of likely distance ranges for airborne spread, our approach could help define an appropriate minimum inter-farm distance to provide more specific guidelines for compartmentalization in Great Britain.
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- 2014
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13. Systems approaches to animal disease surveillance and resource allocation: methodological frameworks for behavioral analysis.
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Rich KM, Denwood MJ, Stott AW, Mellor DJ, Reid SW, and Gunn GJ
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- Animals, Decision Making, Animal Diseases, Resource Allocation
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While demands for animal disease surveillance systems are growing, there has been little applied research that has examined the interactions between resource allocation, cost-effectiveness, and behavioral considerations of actors throughout the livestock supply chain in a surveillance system context. These interactions are important as feedbacks between surveillance decisions and disease evolution may be modulated by their contextual drivers, influencing the cost-effectiveness of a given surveillance system. This paper identifies a number of key behavioral aspects involved in animal health surveillance systems and reviews some novel methodologies for their analysis. A generic framework for analysis is discussed, with exemplar results provided to demonstrate the utility of such an approach in guiding better disease control and surveillance decisions.
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- 2013
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14. Predicting the public health benefit of vaccinating cattle against Escherichia coli O157.
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Matthews L, Reeve R, Gally DL, Low JC, Woolhouse ME, McAteer SP, Locking ME, Chase-Topping ME, Haydon DT, Allison LJ, Hanson MF, Gunn GJ, and Reid SW
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- Animals, Bacterial Shedding genetics, Cattle, Escherichia coli Infections prevention & control, Escherichia coli Infections transmission, Feces microbiology, Humans, Models, Immunological, Polymerase Chain Reaction veterinary, Public Health, Risk Assessment, Scotland, Shiga Toxin 2 genetics, Shiga Toxin 2 metabolism, Zoonoses microbiology, Bacterial Vaccines therapeutic use, Cattle Diseases microbiology, Cattle Diseases prevention & control, Escherichia coli Infections veterinary, Escherichia coli O157 pathogenicity, Mass Vaccination veterinary, Zoonoses prevention & control
- Abstract
Identifying the major sources of risk in disease transmission is key to designing effective controls. However, understanding of transmission dynamics across species boundaries is typically poor, making the design and evaluation of controls particularly challenging for zoonotic pathogens. One such global pathogen is Escherichia coli O157, which causes a serious and sometimes fatal gastrointestinal illness. Cattle are the main reservoir for E. coli O157, and vaccines for cattle now exist. However, adoption of vaccines is being delayed by conflicting responsibilities of veterinary and public health agencies, economic drivers, and because clinical trials cannot easily test interventions across species boundaries, lack of information on the public health benefits. Here, we examine transmission risk across the cattle-human species boundary and show three key results. First, supershedding of the pathogen by cattle is associated with the genetic marker stx2. Second, by quantifying the link between shedding density in cattle and human risk, we show that only the relatively rare supershedding events contribute significantly to human risk. Third, we show that this finding has profound consequences for the public health benefits of the cattle vaccine. A naïve evaluation based on efficacy in cattle would suggest a 50% reduction in risk; however, because the vaccine targets the major source of human risk, we predict a reduction in human cases of nearly 85%. By accounting for nonlinearities in transmission across the human-animal interface, we show that adoption of these vaccines by the livestock industry could prevent substantial numbers of human E. coli O157 cases.
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- 2013
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15. Distinguishable epidemics of multidrug-resistant Salmonella Typhimurium DT104 in different hosts.
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Mather AE, Reid SW, Maskell DJ, Parkhill J, Fookes MC, Harris SR, Brown DJ, Coia JE, Mulvey MR, Gilmour MW, Petrovska L, de Pinna E, Kuroda M, Akiba M, Izumiya H, Connor TR, Suchard MA, Lemey P, Mellor DJ, Haydon DT, and Thomson NR
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- Animals, Epidemics, Genome, Bacterial, Humans, Molecular Sequence Data, Phylogeny, Salmonella Infections epidemiology, Salmonella Infections, Animal epidemiology, Salmonella typhimurium drug effects, Salmonella typhimurium genetics, Drug Resistance, Multiple, Bacterial genetics, Host-Pathogen Interactions, Salmonella Infections microbiology, Salmonella Infections, Animal microbiology, Salmonella typhimurium classification, Zoonoses microbiology
- Abstract
The global epidemic of multidrug-resistant Salmonella Typhimurium DT104 provides an important example, both in terms of the agent and its resistance, of a widely disseminated zoonotic pathogen. Here, with an unprecedented national collection of isolates collected contemporaneously from humans and animals and including a sample of internationally derived isolates, we have used whole-genome sequencing to dissect the phylogenetic associations of the bacterium and its antimicrobial resistance genes through the course of an epidemic. Contrary to current tenets supporting a single homogeneous epidemic, we demonstrate that the bacterium and its resistance genes were largely maintained within animal and human populations separately and that there was limited transmission, in either direction. We also show considerable variation in the resistance profiles, in contrast to the largely stable bacterial core genome, which emphasizes the critical importance of integrated genotypic data sets in understanding the ecology of bacterial zoonoses and antimicrobial resistance.
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- 2013
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16. Resistance through a different prism.
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Mather AE, Mellor DJ, and Reid SW
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- Animals, Bacterial Infections drug therapy, Horse Diseases drug therapy, Horses, Anti-Bacterial Agents pharmacology, Bacterial Infections veterinary, Drug Resistance, Bacterial, Horse Diseases microbiology
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- 2013
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17. Implications of within-farm transmission for network dynamics: consequences for the spread of avian influenza.
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Nickbakhsh S, Matthews L, Dent JE, Innocent GT, Arnold ME, Reid SW, and Kao RR
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- Animals, Feces virology, Humans, Influenza in Birds epidemiology, Models, Biological, Poultry, Risk, United Kingdom epidemiology, Agriculture, Disease Outbreaks veterinary, Influenza in Birds transmission
- Abstract
The importance of considering coupled interactions across multiple population scales has not previously been studied for highly pathogenic avian influenza (HPAI) in the British commercial poultry industry. By simulating the within-flock transmission of HPAI using a deterministic S-E-I-R model, and by incorporating an additional environmental class representing infectious faeces, we tracked the build-up of infectious faeces within a poultry house over time. A measure of the transmission risk (TR) was computed for each farm by linking the amount of infectious faeces present each day of an outbreak with data describing the daily on-farm visit schedules for a major British catching company. Larger flocks tended to have greater levels of these catching-team visits. However, where density-dependent contact was assumed, faster outbreak detection (according to an assumed mortality threshold) led to a decreased opportunity for catching-team visits to coincide with an outbreak. For this reason, maximum TR-levels were found for mid-range flock sizes (~25,000-35,000 birds). When assessing all factors simultaneously using multivariable linear regression on the simulated outputs, those related to the pattern of catching-team visits had the largest effect on TR, with the most important movement-related factor depending on the mode of transmission. Using social network analysis on a further database to inform a measure of between-farm connectivity, we identified a large fraction of farms (28%) that had both a high TR and a high potential impact at the between farm level. Our results have counter-intuitive implications for between-farm spread that could not be predicted based on flock size alone, and together with further knowledge of the relative importance of transmission risk and impact, could have implications for improved targeting of control measures., (Copyright © 2013 Elsevier B.V. All rights reserved.)
- Published
- 2013
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18. Identifying the seasonal origins of human campylobacteriosis.
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Strachan NJ, Rotariu O, Smith-Palmer A, Cowden J, Sheppard SK, O'Brien SJ, Maiden MC, Macrae M, Bessell PR, Matthews L, Reid SW, Innocent GT, Ogden ID, and Forbes KJ
- Subjects
- Adolescent, Adult, Age Factors, Aged, Animals, Animals, Wild microbiology, Birds microbiology, Campylobacter Infections epidemiology, Chickens microbiology, Child, Child, Preschool, Humans, Incidence, Middle Aged, Molecular Epidemiology methods, Multilocus Sequence Typing, Rural Population statistics & numerical data, Scotland epidemiology, Seasons, Travel, Urban Population statistics & numerical data, Young Adult, Campylobacter Infections etiology
- Abstract
Human campylobacteriosis exhibits a distinctive seasonality in temperate regions. This paper aims to identify the origins of this seasonality. Clinical isolates [typed by multi-locus sequence typing (MLST)] and epidemiological data were collected from Scotland. Young rural children were found to have an increased burden of disease in the late spring due to strains of non-chicken origin (e.g. ruminant and wild bird strains from environmental sources). In contrast the adult population had an extended summer peak associated with chicken strains. Travel abroad and UK mainland travel were associated with up to 17% and 18% of cases, respectively. International strains were associated with chicken, had a higher diversity than indigenous strains and a different spectrum of MLST types representative of these countries. Integrating empirical epidemiology and molecular subtyping can successfully elucidate the seasonal components of human campylobacteriosis. The findings will enable public health officials to focus strategies to reduce the disease burden.
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- 2013
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19. Field efficacy of praziquantel oral paste against naturally acquired equine cestodes in Ethiopia.
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Getachew AM, Innocent G, Proudman CJ, Trawford A, Feseha G, Reid SW, Faith B, and Love S
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- Administration, Oral, Animals, Antibodies, Helminth blood, Cestode Infections drug therapy, Equidae, Ethiopia, Feces parasitology, Female, Ivermectin administration & dosage, Male, Parasite Egg Count, Treatment Outcome, Anthelmintics administration & dosage, Cestoda drug effects, Cestode Infections veterinary, Ointments administration & dosage, Praziquantel administration & dosage
- Abstract
The efficacy of an oral formulation of praziquantel (Equitape, Horse paste, Fort Dodge) in the reduction of cestode egg counts and serum antibody level against Anoplocephala perfoliata was assessed in 44 donkeys under field conditions. The donkeys were confirmed both by faecal examination and serum antibody assessed by an enzyme-linked immunosorbent assay to have natural infection with tapeworms. The donkeys were randomly allocated into treatment (n = 22) and control (n = 22) groups. The treatment group was treated with both praziquantel and ivermectin (Ivomec, Merial) at a dose rate of 1 mg/kg and 200 μg/kg, respectively while the control group was treated only with ivermectin. Faecal samples were collected before treatment (day-0) and 2, 6, 8, 12, and 16 weeks post-treatment while blood samples were collected before treatment and 8 and 16 weeks after treatment and analysed. The results of the study demonstrated that praziquantel paste was highly effective in reducing cestode eggs in donkeys and had an efficacy of more than 99 % until week 16 (day 112). No cestode egg reappearance by 16 weeks post-treatment in any animal in the treatment group was observed while donkeys in the control group continued shedding cestode eggs. The immunological assay also showed a significant reduction in serum antibody level against A. perfoliata in treated donkeys compared to the control group (p = 0.0001). This marked decrease in serum antibody level indicates reduced risk of cestode-associated colic and other gastrointestinal disorders and clinical diseases. No adverse reactions or clinical effects were encountered in any animal within either group throughout the trial period.
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- 2013
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20. Quantifying the sources of variability in equine faecal egg counts: implications for improving the utility of the method.
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Denwood MJ, Love S, Innocent GT, Matthews L, McKendrick IJ, Hillary N, Smith A, and Reid SW
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- Animals, Horse Diseases diagnosis, Horses, Parasite Egg Count methods, Seasons, Feces parasitology, Helminthiasis, Animal diagnosis, Horse Diseases parasitology, Parasite Egg Count veterinary
- Abstract
The faecal egg count (FEC) is the most widely used means of quantifying the nematode burden of horses, and is frequently used in clinical practice to inform treatment and prevention. The statistical process underlying the FEC is complex, comprising a Poisson counting error process for each sample, compounded with an underlying continuous distribution of means between samples. Being able to quantify the sources of variability contributing to this distribution of means is a necessary step towards providing estimates of statistical power for future FEC and FECRT studies, and may help to improve the usefulness of the FEC technique by identifying and minimising unwanted sources of variability. Obtaining such estimates require a hierarchical statistical model coupled with repeated FEC observations from a single animal over a short period of time. Here, we use this approach to provide the first comparative estimate of multiple sources of within-horse FEC variability. The results demonstrate that a substantial proportion of the observed variation in FEC between horses occurs as a result of variation in FEC within an animal, with the major sources being aggregation of eggs within faeces and variation in egg concentration between faecal piles. The McMaster procedure itself is associated with a comparatively small coefficient of variation, and is therefore highly repeatable when a sufficiently large number of eggs are observed to reduce the error associated with the counting process. We conclude that the variation between samples taken from the same animal is substantial, but can be reduced through the use of larger homogenised faecal samples. Estimates are provided for the coefficient of variation (cv) associated with each within animal source of variability in observed FEC, allowing the usefulness of individual FEC to be quantified, and providing a basis for future FEC and FECRT studies., (Copyright © 2012 Elsevier B.V. All rights reserved.)
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- 2012
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21. Equine cestodosis: a sero-epidemiological study of Anoplocephala perfoliata infection in Ethiopia.
- Author
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Getachew AM, Innocent G, Proudman CJ, Trawford A, Feseha G, Reid SW, Faith B, and Love S
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- Animals, Cestode Infections blood, Cestode Infections epidemiology, Enzyme-Linked Immunosorbent Assay, Ethiopia epidemiology, Female, Male, Seroepidemiologic Studies, Cestoda classification, Cestode Infections veterinary, Equidae
- Abstract
A 12/13 kDa antigen, tapeworm ELISA test, developed for use in horses, was used to detect parasite-specific serum antibody, IgG(T), in the serum of donkeys. In a pilot study the 12/13 kDa antigen was tested and proved to detect the antibody, IgG(T), in donkey sera. Blood samples from 797 donkeys, naturally exposed to cestode infection, from four geographical localities were collected and sera were prepared and analysed. There was substantial serological evidence that donkeys were potentially infected with A. perfoliata. A range of ELISA OD values were obtained from the serological assay. Over 26% and 7.5% of the donkeys were moderately and highly infected, respectively, showing at least a 34% sero-prevalence. The rest, 66.1%, were either with low infection intensity or negative for A. perfoliata infection. The risk of infections, both in sero-prevalence and intensity, as determined by ELISA optical density (OD), were highest in the highland areas of Ethiopia where pastures are low-lying and wet, and permanent pasture management is regularly practised. Sex, age and body condition of the donkeys had no significant effect either on prevalence of the infection or on the serum antibody level. These results indicate a risk of intestinal disorders, particularly, colic, associated with A. perfoliata infection in donkeys.
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- 2012
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22. An ecological approach to assessing the epidemiology of antimicrobial resistance in animal and human populations.
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Mather AE, Matthews L, Mellor DJ, Reeve R, Denwood MJ, Boerlin P, Reid-Smith RJ, Brown DJ, Coia JE, Browning LM, Haydon DT, and Reid SW
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- Animals, Humans, Microbial Sensitivity Tests, Phenotype, Salmonella typhimurium isolation & purification, Scotland epidemiology, Anti-Infective Agents pharmacology, Drug Resistance, Bacterial, Salmonella typhimurium drug effects
- Abstract
We examined long-term surveillance data on antimicrobial resistance (AMR) in Salmonella Typhimurium DT104 (DT104) isolates from concurrently sampled and sympatric human and animal populations in Scotland. Using novel ecological and epidemiological approaches to examine diversity, and phenotypic and temporal relatedness of the resistance profiles, we assessed the more probable source of resistance of these two populations. The ecological diversity of AMR phenotypes was significantly greater in human isolates than in animal isolates, at the resolution of both sample and population. Of 5200 isolates, there were 65 resistance phenotypes, 13 unique to animals, 30 unique to humans and 22 were common to both. Of these 22, 11 were identified first in the human isolates, whereas only five were identified first in the animal isolates. We conclude that, while ecologically connected, animals and humans have distinguishable DT104 communities, differing in prevalence, linkage and diversity. Furthermore, we infer that the sympatric animal population is unlikely to be the major source of resistance diversity for humans. This suggests that current policy emphasis on restricting antimicrobial use in domestic animals may be overly simplistic. While these conclusions pertain to DT104 in Scotland, this approach could be applied to AMR in other bacteria-host ecosystems.
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- 2012
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23. Gasterophilosis: a major cause of rectal prolapse in working donkeys in Ethiopia.
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Getachew AM, Innocent G, Trawford AF, Reid SW, and Love S
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- Animals, Diptera classification, Ethiopia epidemiology, Female, Incidence, Larva physiology, Male, Myiasis epidemiology, Myiasis parasitology, Myiasis pathology, Prevalence, Rectal Prolapse epidemiology, Rectal Prolapse parasitology, Rectal Prolapse pathology, Rectum parasitology, Rectum pathology, Retrospective Studies, Seasons, Species Specificity, Diptera physiology, Equidae, Myiasis veterinary, Rectal Prolapse veterinary
- Abstract
A retrospective study was conducted to investigate the cause of rectal prolapse in working donkeys in Ethiopia. Analysis of data on rectal prolapse cases obtained from the Donkey Health and Welfare Project clinic at the School of Veterinary Medicine, Addis Ababa University, from 1995 to 2004 revealed that 83.6% (n = 177) of the cases were associated with Gasterophilus nasalis. The rest 10.7% and 5.7% were associated with work-related (overloading) cause and diarrhoea, respectively. The mean and median numbers of G. nasalis recovered from the rectum of infected donkeys were 66 and 64, respectively, with a range of 2-195. Over 100 G. nasalis larvae were recovered from the rectum of 22% of the donkeys. Circular demarcated ulcer-like and deep circumferential pits or ring-like mucosal lesions were found at the larval attachment sites. G. nasalis infection and the associated rectal prolapse were observed year round. However, the intensity of rectal larval infection and incidence of rectal prolapse were significantly higher during the rainy season (P < 0.01). Age and sex of the donkeys had no significant effect on the intensity of rectal larval infection and incidence of rectal prolapse (P > 0.05).
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- 2012
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24. Using sequence data to identify alternative routes and risk of infection: a case-study of campylobacter in Scotland.
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Bessell PR, Rotariu O, Innocent GT, Smith-Palmer A, Strachan NJ, Forbes KJ, Cowden JM, Reid SW, and Matthews L
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- Adult, Animals, Campylobacter Infections microbiology, Campylobacter jejuni isolation & purification, Child, Child, Preschool, Cluster Analysis, Female, Genotype, Humans, Male, Molecular Epidemiology, Poultry, Ruminants, Scotland epidemiology, Campylobacter Infections epidemiology, Campylobacter Infections transmission, Campylobacter jejuni classification, Campylobacter jejuni genetics, Multilocus Sequence Typing, Zoonoses epidemiology, Zoonoses transmission
- Abstract
Background: Genetic typing data are a potentially powerful resource for determining how infection is acquired. In this paper MLST typing was used to distinguish the routes and risks of infection of humans with Campylobacter jejuni from poultry and ruminant sources, Methods: C. jejuni samples from animal and environmental sources and from reported human cases confirmed between June 2005 and September 2006 were typed using MLST. The STRUCTURE software was used to assign the specific sequence types of the sporadic human cases to a particular source. We then used mixed case-case logistic regression analysis to compare the risk factors for being infected with C. jejuni from different sources., Results: A total of 1,599 (46.3%) cases were assigned to poultry, 1,070 (31.0%) to ruminant and 67 (1.9%) to wild bird sources; the remaining 715 (20.7%) did not have a source that could be assigned with a probability of greater than 0.95. Compared to ruminant sources, cases attributed to poultry sources were typically among adults (odds ratio (OR) = 1.497, 95% confidence intervals (CIs) = 1.211, 1.852), not among males (OR = 0.834, 95% CIs = 0.712, 0.977), in areas with population density of greater than 500 people/km2 (OR = 1.213, 95% CIs = 1.030, 1.431), reported in the winter (OR = 1.272, 95% CIs = 1.067, 1.517) and had undertaken recent overseas travel (OR = 1.618, 95% CIs = 1.056, 2.481). The poultry assigned strains had a similar epidemiology to the unassigned strains, with the exception of a significantly higher likelihood of reporting overseas travel in unassigned strains., Conclusions: Rather than estimate relative risks for acquiring infection, our analyses show that individuals acquire C. jejuni infection from different sources have different associated risk factors. By enhancing our ability to identify at-risk groups and the times at which these groups are likely to be at risk, this work allows public health messages to be targeted more effectively. The rapidly increasing capacity to conduct genetic typing of pathogens makes such traced epidemiological analysis more accessible and has the potential to substantially enhance epidemiological risk factor studies.
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- 2012
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25. Generating social network data using partially described networks: an example informing avian influenza control in the British poultry industry.
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Nickbakhsh S, Matthews L, Bessell PR, Reid SW, and Kao RR
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- Animal Husbandry methods, Animals, Bias, Databases, Factual, Disease Outbreaks prevention & control, Influenza in Birds prevention & control, Influenza in Birds transmission, United Kingdom epidemiology, Disease Outbreaks veterinary, Influenza A Virus, H5N1 Subtype isolation & purification, Influenza in Birds epidemiology, Models, Statistical, Poultry, Social Networking
- Abstract
Background: Targeted sampling can capture the characteristics of more vulnerable sectors of a population, but may bias the picture of population level disease risk. When sampling network data, an incomplete description of the population may arise leading to biased estimates of between-host connectivity. Avian influenza (AI) control planning in Great Britain (GB) provides one example where network data for the poultry industry (the Poultry Network Database or PND), targeted large premises and is consequently demographically biased. Exposing the effect of such biases on the geographical distribution of network properties could help target future poultry network data collection exercises. These data will be important for informing the control of potential future disease outbreaks., Results: The PND was used to compute between-farm association frequencies, assuming that farms sharing the same slaughterhouse or catching company, or through integration, are potentially epidemiologically linked. The fitted statistical models were extrapolated to the Great Britain Poultry Register (GBPR); this dataset is more representative of the poultry industry but lacks network information. This comparison showed how systematic biases in the demographic characterisation of a network, resulting from targeted sampling procedures, can bias the derived picture of between-host connectivity within the network., Conclusions: With particular reference to the predictive modeling of AI in GB, we find significantly different connectivity patterns across GB when network estimates incorporate the more demographically representative information provided by the GBPR; this has not been accounted for by previous epidemiological analyses. We recommend ranking geographical regions, based on relative confidence in extrapolated estimates, for prioritising further data collection. Evaluating whether and how the between-farm association frequencies impact on the risk of between-farm transmission will be the focus of future work.
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- 2011
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26. From phenotype to genotype: a Bayesian solution.
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Denwood MJ, Mather AE, Haydon DT, Matthews L, Mellor DJ, and Reid SW
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- Anti-Bacterial Agents pharmacology, Genes, Bacterial, Genetic Heterogeneity, Genotype, Humans, Markov Chains, Models, Biological, Monte Carlo Method, Phenotype, Salmonella Infections microbiology, Salmonella typhimurium drug effects, Bayes Theorem, Drug Resistance, Multiple, Bacterial, Genetics, Population methods, Genomic Islands drug effects, Salmonella typhimurium genetics
- Abstract
The study of biological systems commonly depends on inferring the state of a 'hidden' variable, such as an underlying genotype, from that of an 'observed' variable, such as an expressed phenotype. However, this cannot be achieved using traditional quantitative methods when more than one genetic mechanism exists for a single observable phenotype. Using a novel latent class Bayesian model, it is possible to infer the prevalence of different genetic elements in a population given a sample of phenotypes. As an exemplar, data comprising phenotypic resistance to six antimicrobials obtained from passive surveillance of Salmonella Typhimurium DT104 are analysed to infer the prevalence of individual resistance genes, as well as the prevalence of a genomic island known as SGI1 and its variants. Three competing models are fitted to the data and distinguished between using posterior predictive p-values to assess their ability to predict the observed number of unique phenotypes. The results suggest that several SGI1 variants circulate in a few fixed forms through the population from which our data were derived. The methods presented could be applied to other types of phenotypic data, and represent a useful and generic mechanism of inferring the genetic population structure of organisms.
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- 2011
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27. Assessing the probability of acquisition of meticillin-resistant Staphylococcus aureus (MRSA) in a dog using a nested stochastic simulation model and logistic regression sensitivity analysis.
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Heller J, Innocent GT, Denwood M, Reid SW, Kelly L, and Mellor DJ
- Subjects
- Animals, Computer Simulation, Dog Diseases transmission, Dogs, Environmental Microbiology, Female, Logistic Models, Male, Methicillin-Resistant Staphylococcus aureus isolation & purification, Risk Assessment, Staphylococcal Infections microbiology, Staphylococcal Infections transmission, Stochastic Processes, Zoonoses, Dog Diseases microbiology, Methicillin-Resistant Staphylococcus aureus pathogenicity, Staphylococcal Infections veterinary
- Abstract
Meticillin-resistant Staphylococcus aureus (MRSA) is an important nosocomial and community-acquired pathogen with zoonotic potential. The relationship between MRSA in humans and companion animals is poorly understood. This study presents a quantitative exposure assessment, based on expert opinion and published data, in the form of a second order stochastic simulation model with accompanying logistic regression sensitivity analysis that aims to define the most important factors for MRSA acquisition in dogs. The simulation model was parameterised using expert opinion estimates, along with published and unpublished data. The outcome of the model was biologically plausible and found to be dominated by uncertainty over variability. The sensitivity analysis, in the form of four separate logistic regression models, found that both veterinary and non-veterinary routes of acquisition of MRSA are likely to be relevant for dogs. The effects of exposure to, and probability of, transmission of MRSA from the home environment were ranked as the most influential predictors in all sensitivity analyses, although it is unlikely that this environmental source of MRSA is independent of alternative sources of MRSA (human and/or animal). Exposure to and transmission from MRSA positive family members were also found to be influential for acquisition of MRSA in pet dogs, along with veterinary clinic attendance and, while exposure to and transmission from the veterinary clinic environment was also found to be influential, it was difficult to differentiate between the importance of independent sources of MRSA within the veterinary clinic. The implementation of logistic regression analyses directly to the input/output relationship within the simulation model presented in this paper represents the application of a variance based sensitivity analysis technique in the area of veterinary medicine and is a useful means of ranking the relative importance of input variables., (Copyright © 2010 Elsevier B.V. All rights reserved.)
- Published
- 2011
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28. The prevalences of Salmonella Genomic Island 1 variants in human and animal Salmonella Typhimurium DT104 are distinguishable using a Bayesian approach.
- Author
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Mather AE, Denwood MJ, Haydon DT, Matthews L, Mellor DJ, Coia JE, Brown DJ, and Reid SW
- Subjects
- Animals, Anti-Bacterial Agents pharmacology, Gene Frequency, Genetic Variation, Humans, Markov Chains, Monte Carlo Method, Salmonella Infections microbiology, Salmonella Infections, Animal microbiology, Salmonella typhimurium classification, Salmonella typhimurium drug effects, Species Specificity, Bayes Theorem, Drug Resistance, Multiple, Bacterial genetics, Genomic Islands genetics, Salmonella typhimurium genetics
- Abstract
Throughout the 1990 s, there was an epidemic of multidrug resistant Salmonella Typhimurium DT104 in both animals and humans in Scotland. The use of antimicrobials in agriculture is often cited as a major source of antimicrobial resistance in pathogenic bacteria of humans, suggesting that DT104 in animals and humans should demonstrate similar prevalences of resistance determinants. Until very recently, only the application of molecular methods would allow such a comparison and our understanding has been hindered by the fact that surveillance data are primarily phenotypic in nature. Here, using large scale surveillance datasets and a novel Bayesian approach, we infer and compare the prevalence of Salmonella Genomic Island 1 (SGI1), SGI1 variants, and resistance determinants independent of SGI1 in animal and human DT104 isolates from such phenotypic data. We demonstrate differences in the prevalences of SGI1, SGI1-B, SGI1-C, absence of SGI1, and tetracycline resistance determinants independent of SGI1 between these human and animal populations, a finding that challenges established tenets that DT104 in domestic animals and humans are from the same well-mixed microbial population.
- Published
- 2011
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29. Putative household outbreaks of campylobacteriosis typically comprise single MLST genotypes.
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Rotariu O, Smith-Palmer A, Cowden J, Bessell PR, Innocent GT, Reid SW, Matthews L, Dallas J, Ogden ID, Forbes KJ, and Strachan NJ
- Subjects
- Adolescent, Adult, Aged, Aged, 80 and over, Campylobacter genetics, Child, Child, Preschool, Cluster Analysis, Family Characteristics, Female, Genotype, Humans, Infant, Male, Middle Aged, Scotland epidemiology, Sequence Analysis, DNA, Young Adult, Bacterial Typing Techniques, Campylobacter classification, Campylobacter isolation & purification, Campylobacter Infections epidemiology, DNA Fingerprinting, Disease Outbreaks, Family Health
- Abstract
During a 15-month period in Scotland a small but important number of human Campylobacter cases (3·2%) arose from 91 putative household outbreaks. Of the 26 outbreaks with known strain composition, 89% were composed of the same MLST which supports the potential use of MLST in public health epidemiology. The number of cases associated with household outbreaks is much larger than general outbreaks and there is some evidence to indicate that there may be secondary transmission, although this is relatively rare.
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- 2010
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30. Associations between the presence of virulence determinants and the epidemiology and ecology of zoonotic Escherichia coli.
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O'Reilly KM, Low JC, Denwood MJ, Gally DL, Evans J, Gunn GJ, Mellor DJ, Reid SW, and Matthews L
- Subjects
- Animals, Bacterial Typing Techniques, Cattle, Cattle Diseases transmission, Escherichia coli classification, Escherichia coli genetics, Escherichia coli isolation & purification, Escherichia coli Infections microbiology, Escherichia coli Infections transmission, Prevalence, Serotyping, Virulence, Adhesins, Bacterial genetics, Cattle Diseases microbiology, Escherichia coli pathogenicity, Escherichia coli Infections veterinary, Escherichia coli Proteins genetics, Shiga Toxin genetics, Virulence Factors genetics
- Abstract
The severity of human infection with pathogenic Escherichia coli depends on two major virulence determinants (eae and stx) that, respectively, produce intimin and Shiga toxin. In cattle, both may enhance colonization, but whether this increases fitness by enhancing cattle-to-cattle transmission in the field is unknown. In E. coli O157, the almost uniform presence of the virulence determinants in cattle isolates prevents comparative analysis. The availability to this study of extensive non-O157 E. coli data, with much greater diversity in carriage of virulence determinants, provides the opportunity to gain insight into their potential impact on transmission. Dynamic models were used to simulate expected prevalence distributions for serogroups O26 and O103. Transmission parameters were estimated by fitting model outputs to prevalence data from Scottish cattle using a Bayesian Markov chain Monte Carlo (MCMC) approach. Despite similar prevalence distributions for O26 and O103, their transmission dynamics were distinct. Serogroup O26 strains appear well adapted to the cattle host. The dynamics are characterized by a basic reproduction ratio (R(0)) of >1 (allowing sustained cattle-to-cattle transmission), a relatively low transmission rate from environmental reservoirs, and substantial association with eae on transmission. The presence of stx(2) was associated with reduced transmission. In contrast, serogroup O103 appears better adapted to the noncattle environment, characterized by an R(0) value of <1 for plausible test sensitivities, a significantly higher transmission rate from noncattle sources than serogroup O26, and an absence of fitness benefits associated with the carriage of eae. Thus, the association of eae with enhanced transmission depends on the E. coli serogroup. Our results suggest that the capacity of E. coli strains to derive fitness benefits from virulence determinants influences the prevalence in the cattle population and the ecology and epidemiology of the host organism.
- Published
- 2010
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31. Risk of carcase contamination with Campylobacter in sheep sent for slaughter into an abattoir in Scotland.
- Author
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Garcia AB, Steele WB, Reid SW, and Taylor DJ
- Subjects
- Animals, Campylobacter isolation & purification, Campylobacter Infections epidemiology, Campylobacter Infections prevention & control, Campylobacter Infections transmission, Food Contamination analysis, Food Microbiology, Humans, Logistic Models, Risk Assessment, Risk Factors, Scotland epidemiology, Sheep, Sheep Diseases prevention & control, Sheep Diseases transmission, Zoonoses, Abattoirs, Campylobacter Infections veterinary, Food Contamination prevention & control, Meat microbiology, Sheep Diseases epidemiology
- Abstract
Campylobacter species have been identified as the major cause of acute bacterial enteritis in the UK. However, the epidemiology of campylobacteriosis remains poorly understood. It has been suggested that the role of sheep in the epidemiology of Campylobacter has been underestimated. The objective of the present study was to assess the infection risk of Campylobacter in sheep meat as a potential risk for human campylobacteriosis and to establish any possible associations between the epidemiological factors considered in the study and the presence of Campylobacter on lamb carcases. The prevalence of Campylobacter obtained from faecal samples and swabs from fleeces and carcases was presented in a previous paper. Epidemiological data was collected through questionnaires in order to identify risk factors for the presence of Campylobacter on the carcases and to make recommendations, based on the results obtained, to prevent human campylobacteriosis., ((c) 2010 Elsevier B.V. All rights reserved.)
- Published
- 2010
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32. Epidemiological features of fasciolosis in working donkeys in Ethiopia.
- Author
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Getachew M, Innocent GT, Trawford AF, Reid SW, and Love S
- Subjects
- Animals, Ethiopia epidemiology, Fasciola hepatica isolation & purification, Fascioliasis epidemiology, Feces parasitology, Female, Male, Prevalence, Equidae parasitology, Fascioliasis veterinary
- Abstract
A cross-sectional coprological survey in the tropical regions of Ada, Akaki, Bereh and Boset, and a retrospective post-mortem investigation were conducted to study the epidemiology of fasciolosis in working donkeys in Ethiopia. Faecal samples from 803 donkeys were collected, and the number of liver flukes recovered from 112 donkeys at post-mortem between 1995 and 2004 were analysed. There was a high prevalence of fasciolosis irrespective of the age of the donkeys. The overall prevalence of the infection was 44.4% in coprologically examined donkeys, and the prevalence in the donkeys examined post-mortem was 41.9%. The infection prevalence was significantly higher in Bereh and Ada regions than in Akaki and Boset regions. Bereh with 72.6% and Boset with 21.5% showed a significantly higher and lower infection prevalence, respectively, than the rest of the regions (P<0.001). There was no significant difference between different age groups of donkeys in the infection prevalence (P>0.05) but infection intensity was significantly higher in donkeys 8 years old and above (P<0.0001). Both Fasciola hepatica and Fasciola gigantica were identified., ((c) 2010 Elsevier B.V. All rights reserved.)
- Published
- 2010
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33. Qualitative risk assessment of the acquisition of Meticillin-resistant staphylococcus aureus in pet dogs.
- Author
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Heller J, Kelly L, Reid SW, and Mellor DJ
- Subjects
- Animals, Dogs, Hospitals, Animal, Humans, Methicillin-Resistant Staphylococcus aureus isolation & purification, Risk Assessment, Staphylococcal Infections veterinary
- Abstract
This article presents a qualitative risk assessment of the acquisition of meticillin-resistant Staphylococcus aureus (MRSA) in pet dogs, representing an important first step in the exploration of risk of bidirectional MRSA transfer between dogs and humans. A conceptual model of the seven potential pathways for MRSA acquisition in a dog in any given 24-hour period was developed and the data available to populate that model were considered qualitatively. Humans were found to represent the most important source of MRSA for dogs in both community and veterinary hospital settings. The environment was found to be secondary to humans in terms of importance and other dogs less still. This study highlights some important methodological limitations of a technique that is heavily relied upon for qualitative risk assessments and applies a novel process, the use of relative risk ranking, to enable the generation of a defensible output using a matrix combination approach. Given the limitations of the prescribed methods as applied to the problem under consideration, further validation, or repudiation, of the findings contained herein is called for using a subsequent quantitative assessment.
- Published
- 2010
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34. Comparison of three alternative methods for analysis of equine Faecal Egg Count Reduction Test data.
- Author
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Denwood MJ, Reid SW, Love S, Nielsen MK, Matthews L, McKendrick IJ, and Innocent GT
- Subjects
- Animals, Helminthiasis, Animal epidemiology, Horses, Netherlands epidemiology, Parasite Egg Count methods, Anthelmintics therapeutic use, Feces parasitology, Helminthiasis, Animal drug therapy, Horse Diseases drug therapy, Parasite Egg Count veterinary
- Abstract
The Faecal Egg Count Reduction Test (FECRT) is the most widely used method of assessing the efficacy of anthelmintics, and is the only in vivo technique currently approved for use with horses. Equine Faecal Egg Count (FEC) data are frequently characterised by a low mean, high variability, small sample size and frequent zero count observations. Accurate analysis of the data therefore depends on the use of an appropriate statistical technique. Analyses of simulated FECRT data by methods based on calculation of the empirical mean and variance, non-parametric bootstrapping, and Markov chain Monte Carlo (MCMC) are compared. The MCMC method consistently outperformed the other methods, independently of the distribution from which the data were generated. Bootstrapping produced notional 95% confidence intervals containing the true parameter as little as 40% of the time with sample sizes of less than 50. Analysis of equine FECRT data yielded inconclusive results in 53 of 63 (84%) datasets, suggesting that the routine use of prior sample size calculations should be adopted to ensure sufficient data are collected. The authors conclude that computationally intensive parametric methods such as MCMC be used for analysis of FECRT data with sample sizes of less than 50, in order to avoid erroneous inference about the true efficacy of anthelmintics in the field.
- Published
- 2010
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35. Gastrointestinal parasites of working donkeys of Ethiopia.
- Author
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Getachew M, Trawford A, Feseha G, and Reid SW
- Subjects
- Animals, Ethiopia epidemiology, Feces parasitology, Female, Gastrointestinal Diseases epidemiology, Gastrointestinal Diseases parasitology, Helminthiasis, Animal epidemiology, Male, Parasite Egg Count veterinary, Prevalence, Retrospective Studies, Equidae parasitology, Gastrointestinal Diseases veterinary, Helminthiasis, Animal parasitology, Helminths isolation & purification
- Abstract
The general prevalence and population composition of gastrointestinal and pulmonary helminths of working donkeys were studied. For the purpose 2935 working donkeys were coprologically examined for nematode and cestode, and 215 donkeys for trematode infections. Seven donkeys that died due to various health problems or were euthanased on a welfare ground were necropsied and the parasites were recovered and identified to the species level. The study was conducted during the periods 1996-1999.Coprological examination revealed 99% strongyle, 80% Fasciola, 51% Parascaris, 30% Gastrodiscus, 11% Strongyloides westeri, 8% cestodes and 2% Oxyuris equi infection prevalence. Over 55% of donkeys had more than 1000 eggs per gram of faeces (epg). Forty two different species of parasites consisting of 33 nematodes, 3 trematodes, 3 cestodes and 3 arthropod larvae were identified from postmortem examined donkeys. Among the nematodes 17 species of Cyathostominae and 7 species of Strongylinae were identified. Other parasites identified include, Habronema muscae, Draschia megastoma, Trichostrongylus axei, Strongyloides westeri, Anoplocephala perfoliata, Anoplocephala magna, Anoplocephaloides (Paranoplocephala) mamillana, Parascaris equorum, Fasciola hepatica, Fasciola gigantica, Gastrodiscus aegyptiacus, Dictyocaulus arnfieldi, Oxyuris equi, Probstmayria vivipara, Gasterophilus intestinalis, Gasterophilus nasalis, Rhinoestrus uzbekistanicus and Setaria equina. This study revealed that working donkeys in Ethiopia are infected with a range of helminths and arthropod larvae, which are representatives of the important pathogenic parasites found in equids worldwide.
- Published
- 2010
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36. Temporal and spatial patterns of bovine Escherichia coli O157 prevalence and comparison of temporal changes in the patterns of phage types associated with bovine shedding and human E. coli O157 cases in Scotland between 1998-2000 and 2002-2004.
- Author
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Pearce MC, Chase-Topping ME, McKendrick IJ, Mellor DJ, Locking ME, Allison L, Ternent HE, Matthews L, Knight HI, Smith AW, Synge BA, Reilly W, Low JC, Reid SW, Gunn GJ, and Woolhouse ME
- Subjects
- Animal Husbandry, Animals, Bacteriophage Typing, Cattle, Cattle Diseases microbiology, Disease Reservoirs veterinary, Escherichia coli Infections microbiology, Escherichia coli O157 classification, Humans, Incidence, Prevalence, Scotland epidemiology, Bacterial Shedding, Cattle Diseases epidemiology, Escherichia coli Infections epidemiology, Escherichia coli Infections veterinary, Escherichia coli O157 genetics
- Abstract
Background: Escherichia coli O157 is an important cause of acute diarrhoea, haemorrhagic colitis and, especially in children, haemolytic uraemic syndrome (HUS). Incidence rates for human E. coli O157 infection in Scotland are higher than most other United Kingdom, European and North American countries. Cattle are considered the main reservoir for E. coli O157. Significant associations between livestock related exposures and human infection have been identified in a number of studies., Results: Animal Studies: There were no statistically significant differences (P = 0.831) in the mean farm-level prevalence between the two studies (SEERAD: 0.218 (95%CI: 0.141-0.32); IPRAVE: 0.205 (95%CI: 0.135-0.296)). However, the mean pat-level prevalence decreased from 0.089 (95%CI: 0.075-0.105) to 0.040 (95%CI: 0.028-0.053) between the SEERAD and IPRAVE studies respectively (P < 0.001). Highly significant (P < 0.001) reductions in mean pat-level prevalence were also observed in the spring, in the North East and Central Scotland, and in the shedding of phage type (PT) 21/28. Human Cases: Contrasting the same time periods, there was a decline in the overall comparative annual reported incidence of human cases as well as in all the major PT groups except 'Other' PTs. For both cattle and humans, the predominant phage type between 1998 and 2004 was PT21/28 comprising over 50% of the positive cattle isolates and reported human cases respectively. The proportion of PT32, however, was represented by few (<5%) of reported human cases despite comprising over 10% of cattle isolates. Across the two studies there were differences in the proportion of PTs 21/28, 32 and 'Other' PTs in both cattle isolates and reported human cases; however, only differences in the cattle isolates were statistically significant (P = 0.002)., Conclusion: There was no significant decrease in the mean farm-level prevalence of E. coli O157 between 1998 and 2004 in Scotland, despite significant declines in mean pat-level prevalence. Although there were declines in the number of human cases between the two study periods, there is no statistically significant evidence that the overall rate (per 100,000 population) of human E. coli O157 infections in Scotland over the last 10 years has altered. Comparable patterns in the distribution of PTs 21/28 and 32 between cattle and humans support a hypothesized link between the bovine reservoir and human infections. This emphasizes the need to apply and improve methods to reduce bovine shedding of E. coli O157 in Scotland where rates appear higher in both cattle and human populations, than in other countries.
- Published
- 2009
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37. Exploiting strain diversity to expose transmission heterogeneities and predict the impact of targeting supershedding.
- Author
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Matthews L, Reeve R, Woolhouse ME, Chase-Topping M, Mellor DJ, Pearce MC, Allison LJ, Gunn GJ, Low JC, and Reid SW
- Subjects
- Animals, Bacterial Load, Bacterial Shedding, Cattle, Cattle Diseases epidemiology, Coliphages isolation & purification, Cross-Sectional Studies, Escherichia coli Infections epidemiology, Monte Carlo Method, Scotland epidemiology, Cattle Diseases microbiology, Cattle Diseases transmission, Coliphages pathogenicity, Escherichia coli Infections microbiology, Escherichia coli Infections transmission, Escherichia coli O157 pathogenicity
- Abstract
When a few individuals generate disproportionately many secondary cases, targeted interventions can theoretically lead to highly efficient control of the spread of infection. Practical exploitation of heterogeneous transmission requires the sources of variability to be quantified, yet it is unusual to have empirical data of sufficient resolution to distinguish their effects. Here, we exploit extensive data on pathogen shedding densities and the distribution of cases, collected from the same population within the same spatio-temporal window, to expose the comparative epidemiology of independent Escherichia coli O157 strains. For this zoonotic pathogen, which exhibits high-density shedding (supershedding) and heterogeneous transmission in its cattle reservoir, whether targeting supershedding could be an effective control depends critically on the proposed link between shedding density and transmissibility. We substantiate this link by showing that our supershedder strain has nearly triple the R(0) of our non-supershedder strain. We show that observed transmission heterogeneities are strongly driven by superspreading in addition to supershedding, but that for the supershedder strain, the dominant strain in our study population, there remains sufficient heterogeneity in contribution to R(0) from different shedding densities to allow exploitation for control. However, in the presence of substantial within-host variability, our results indicate that rather than seek out supershedders themselves, the most effective controls would directly target the phenomenon of pathogen supershedding with the aim of interrupting or preventing high shedding densities. In this system, multiple sources of heterogeneity have masked the role of shedding densities-our potential targets for control. This analysis demonstrates the critical importance of disentangling the effects of multiple sources of heterogeneity when designing targeted interventions., (Copyright © 2009 Elsevier B.V. All rights reserved.)
- Published
- 2009
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38. Prevalence and distribution of meticillin-resistant Staphylococcus aureus within the environment and staff of a university veterinary clinic.
- Author
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Heller J, Armstrong SK, Girvan EK, Reid SW, Moodley A, and Mellor DJ
- Subjects
- Animal Technicians, Animals, Bacterial Toxins isolation & purification, Exotoxins isolation & purification, Genotype, Humans, Leukocidins isolation & purification, Methicillin-Resistant Staphylococcus aureus genetics, Microbial Sensitivity Tests, Nasal Mucosa microbiology, Prevalence, Schools, Veterinary, Scotland, Veterinarians, Environmental Exposure analysis, Environmental Microbiology, Hospitals, Animal, Methicillin-Resistant Staphylococcus aureus isolation & purification
- Abstract
Objectives: To characterise the distribution of meticillin-resistant Staphylococcus aureus within the environment of a university small animal hospital and compare this with the distribution among staff., Methods: Samples were collected from 140 environmental sites and the anterior nares of 64 staff members at the University of Glasgow Small Animal Hospital on a single day (d1). Sixty of the environmental sites were resampled 14 days later (d14)., Results: Meticillin-resistant S aureus was isolated from two of 140 (1.4 per cent; 95 per cent confidence interval: 1.7 to 5.1) environmental sites on d1 and one of 60 (1.7 per cent; 95 per cent confidence interval: 0.4 to 8.9) on d14. Two of the 64 staff sampled were positive for meticillin-resistant S aureus (3.1 per cent; 95 per cent confidence interval: 0.4 to 8.4)., Clinical Significance: A lower prevalence of meticillin-resistant S aureus was observed in the environment than previously reported. The location, relatedness between isolates and the presence of Panton-Valentine leucocidin indicates that the source of the environmental meticillin-resistant S aureus was most likely to have been human rather than animal in these cases. This study presents important information regarding the potential source and distribution of meticillin-resistant S aureus within veterinary hospital environments and highlights potential variability of prevalence of meticillin-resistant S aureus within and between veterinary institutions.
- Published
- 2009
- Full Text
- View/download PDF
39. Isolation, microinjection and transfer of mouse blastocysts.
- Author
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Reid SW and Tessarollo L
- Subjects
- Animals, Blastocyst, Embryonic Stem Cells cytology, Female, Mice, Mice, Inbred C57BL, Microinjections methods, Micromanipulation, Embryo Transfer
- Abstract
Genetically modified mice by means of homologous recombination in embryonic stem (ES) cells are generated by injection of manipulated ES cells into recipient blastocysts. The injected blastocysts, following reintroduction into recipient foster mice, will produce chimeric mice in which the manipulated ES cells populate the germline and transmit the induced mutation to the offspring. Crossing of the chimeras' offspring bearing the targeted mutation in heterozygosis will ultimately produce mice homozygous for the specific genetic mutation. Here we describe the steps and procedures required to generate the chimeric mice leading to the transfer of a genetic mutation to the mouse germline.
- Published
- 2009
- Full Text
- View/download PDF
40. A survey of seasonal patterns in strongyle faecal worm egg counts of working equids of the central midlands and lowlands, Ethiopia.
- Author
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Getachew M, Feseha G, Trawford A, and Reid SW
- Subjects
- Animals, Ethiopia epidemiology, Feces parasitology, Female, Linear Models, Male, Parasite Egg Count veterinary, Prevalence, Seasons, Strongylida Infections epidemiology, Strongylida Infections parasitology, Equidae parasitology, Strongylida Infections veterinary, Strongyloidea growth & development
- Abstract
A study was conducted for two consecutive years (1998-1999) to determine the seasonal patterns of strongyle infection in working donkeys of Ethiopia. For the purpose 2385 donkeys from midland and lowland areas were examined for the presence of parasitic ova. A hundred percent prevalence of strongyle infection with similar seasonal pattern of strongyle faecal worm egg output was obtained in all study areas. However, seasonal variations in the number of strongyle faecal worm egg output were observed in all areas. The highest mean faecal worm egg outputs were recorded during the main rainy season (June to October) in both years in all areas. Although an increase in the mean strongyle faecal egg output was obtained in the short rainy season (March-April) followed by a drop in the short dry season (May), there was no statistically significant difference between the short rainy season and long dry season (Nov-Feb) (P > 0.05). A statistically significant difference however, was obtained between the main rainy season and short rainy season, and between the main rainy season and dry season (P < 0.05). Based on the results obtained it is suggested that the most economical and effective control of strongyles can be achieved by strategic deworming programme during the hot dry pre-main rainy season (May), when the herbage coverage is scarce and helminthologically 'sterile', and the arrested development of the parasites is suppose to be terminating. This could insure the greatest proportion of the existing worm population to be exposed to anthelmintic and also reduces pasture contamination and further infection in the subsequent wet season.
- Published
- 2008
- Full Text
- View/download PDF
41. Factors associated with cross-contamination of hides of Scottish cattle by Escherichia coli O157.
- Author
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Mather AE, Reid SW, McEwen SA, Ternent HE, Reid-Smith RJ, Boerlin P, Taylor DJ, Steele WB, Gunn GJ, and Mellor DJ
- Subjects
- Abattoirs, Animals, Bacteriophage Typing, Cattle, Escherichia coli Infections etiology, Escherichia coli O157 metabolism, Regression Analysis, Risk Factors, Scotland, Shiga Toxins biosynthesis, Escherichia coli Infections veterinary, Escherichia coli O157 classification, Escherichia coli O157 isolation & purification, Food Contamination, Food Microbiology, Skin microbiology
- Abstract
The putative source of hide contamination for 236 cattle in Scotland followed from the farm through to slaughter was determined using phage and verocytotoxin type data. The majority of cattle (84%) were found to have subtypes of Escherichia coli O157 on their hide that had not been found previously in any animal from the farm of origin, strongly suggesting that contamination occurred once animals had left the farm of origin. Using logistic regression analysis, several variables and factors were found to be strongly associated (P < 0.01) with cross-contamination of cattle hides at the univariate level; commercial transport to slaughter, transport with other animals, use of a crush, line automation, and increasing slaughterhouse throughput were all risk factors, while feeding hay in lairage, processing an animal earlier in a slaughter cohort, and cleaning the landing area poststunning were protective. In the multivariable model, with the slaughterhouse and the farm group included as random effects, factors associated with the cross-contamination of cattle hides were identified. Transport to the slaughterhouse by a commercial hauler had a borderline-significant association with increased odds of an animal having a cross-contaminated hide (odds ratio [OR] [95% confidence interval (CI)] = 5.7 [0.99, 33.0]; P = 0.05). At the slaughterhouse, providing hay to cattle waiting in lairage (OR [95% CI] = 0.04 [<0.01, 1.04]; P = 0.05) and cleaning the landing area (OR [95% CI] = 0.03 [<0.01, 1.15,]; P = 0.06) also had a borderline-significant association with decreased odds of an animal having a cross-contaminated hide. Although the prevalence of carcass contamination remains very low, targeted intervention at the preslaughter stage may have the potential to reduce further the risk to public health.
- Published
- 2008
- Full Text
- View/download PDF
42. The distribution of the pathogenic nematode Nematodirus battus in lambs is zero-inflated.
- Author
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Denwood MJ, Stear MJ, Matthews L, Reid SW, Toft N, and Innocent GT
- Subjects
- Animals, Bayes Theorem, Female, Male, Markov Chains, Monte Carlo Method, Nematode Infections epidemiology, Parasite Egg Count veterinary, Scotland, Sheep parasitology, Sheep Diseases epidemiology, Nematode Infections veterinary, Sheep Diseases parasitology
- Abstract
Understanding the frequency distribution of parasites and parasite stages among hosts is essential for efficient experimental design and statistical analysis, and is also required for the development of sustainable methods of controlling infection. Nematodirus battus is one of the most important organisms that infect sheep but the distribution of parasites among hosts is unknown. An initial analysis indicated a high frequency of animals without N. battus and with zero egg counts, suggesting the possibility of a zero-inflated distribution. We developed a Bayesian analysis using Markov chain Monte Carlo methods to estimate the parameters of the zero-inflated negative binomial distribution. The analysis of 3000 simulated data sets indicated that this method out-performed the maximum likelihood procedure. Application of this technique to faecal egg counts from lambs in a commercial upland flock indicated that N. battus counts were indeed zero-inflated. Estimating the extent of zero-inflation is important for effective statistical analysis and for the accurate identification of genetically resistant animals.
- Published
- 2008
- Full Text
- View/download PDF
43. The aetiology of spinal deformity in Atlantic salmon, Salmo salar L.: influence of different commercial diets on the incidence and severity of the preclinical condition in salmon parr under two contrasting husbandry regimes.
- Author
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Sullivan M, Reid SW, Ternent H, Manchester NJ, Roberts RJ, Stone DA, and Hardy RW
- Subjects
- Animal Feed, Animals, Fish Diseases diagnostic imaging, Fish Diseases metabolism, Multivariate Analysis, Phosphorus, Dietary metabolism, Radiography, Spinal Diseases diagnostic imaging, Spinal Diseases etiology, Spinal Diseases metabolism, Animal Husbandry methods, Fish Diseases etiology, Oncorhynchus mykiss, Phosphorus, Dietary administration & dosage, Salmo salar, Spinal Diseases veterinary
- Abstract
A large-scale trial of the effect of different commercial diets on the incidence of preclinical spinal deformation, as assessed by radiography, and the influence of two contrasting rearing systems was carried out. Two sets of three populations of Atlantic salmon, each of 20 000 first feeding fry of identical hatchery origin, created from equal numbers of eggs from 15 different families, were reared under commercial conditions on two different farms. Three commercial (closed formula) extruded fish meal-based diets were used in this study (diets A, B & C). Each diet was fed to one population of 20 000 fish at each site. Fish were fed a percentage of their body weight per day, with feeding rates set at commercial levels, based on water temperature, day length and fish biomass. Additional hand feeding was used to ensure satiation in all tanks. Fish in each tank were bulk-weighed and counted at the beginning and at 2-week intervals throughout the study. The fish were grown for 30 weeks. In addition, phosphorus (P) digestibility was evaluated by in-feed absorption testing in rainbow trout. The morphology of the radiographic lesions conformed to those described previously. Statistical analysis using multivariate regression analysis showed that date of sampling, site and diet were all statistically significant (P < 0.001) on univariable analysis. Farm A had significantly more affected fish than farm B (P < 0.001), which may have been attributable to variation in dissolved oxygen levels. The available dietary P levels were low in each diet. The number of fish affected in the group of fish being fed diet B was significantly lower than in the groups being fed diets A or C (P < 0.001). It appears most likely that the occurrence of preclinical radiographically apparent defects in parr which are believed to lead to the condition known as 'spinal deformity' is predominantly caused by a deficiency of available dietary P in first-feeding fry. The availability of dietary P may also vary considerably between diets formulated using different ingredients. Phytate-P associated with plant ingredients may affect the availability of P as well as other essential dietary nutrients. Additionally, diets for the production of salmonids in fresh water are currently formulated to keep P effluent to a minimum compatible with healthy spinal development. These various factors combine to make it crucial that small Atlantic salmon, especially first-feeding fry, are provided with carefully formulated diets fortified to an adequate level with a high quality source of available P.
- Published
- 2007
- Full Text
- View/download PDF
44. Elapid snake envenomation in dogs in New South Wales: a review.
- Author
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Heller J, Mellor DJ, Hodgson JL, Reid SW, Hodgson DR, and Bosward KL
- Subjects
- Animals, Diagnosis, Differential, Dog Diseases drug therapy, Dog Diseases pathology, Dogs, Elapid Venoms antagonists & inhibitors, New South Wales epidemiology, Snake Bites diagnosis, Snake Bites drug therapy, Snake Bites pathology, Species Specificity, Antivenins therapeutic use, Dog Diseases diagnosis, Elapid Venoms adverse effects, Elapidae, Snake Bites veterinary
- Abstract
Elapid snake envenomation in dogs is a commonly occurring yet poorly described clinical entity. Twelve species of dangerously venomous elapid snakes are found in New South Wales that are capable of causing disease in dogs. Geographical distribution of these species varies, as does their venom composition and systemic envenomation syndromes produced in target species. Elapid venom may be divided into the components of prothrombin activating enzymes, lipases and peptidic neurotoxins. Each species of elapid snake may possess venom components that fit any or all of these classifications. The action of these venom components may result in neurotoxic (pre-synaptic and post-synaptic), haemotoxic (red-cell destruction and coagulation disturbance), cardiovascular, myotoxic and secondary nephrotoxic effects. Marked variability may occur in venom composition between and within snake species, resulting in varying toxicity between species and also potentially unreliable clinical syndromes following envenomation. The existence of certain components consistently within the venom of each snake species allows the broad definition of basic pathological processes and clinicopathological changes resulting from snake species-specific envenomation and these are discussed. Diagnosis of snake envenomation is unreliable if based on clinical signs alone and the use of these signs in conjunction with history, physical examination and laboratory investigation, including snake venom detection kits, is recommended. Treatment of systemic envenomation should be undertaken with initial effective first aid and subsequent administration of snake species-specific antivenom.
- Published
- 2007
- Full Text
- View/download PDF
45. Risk factors for hide contamination of Scottish cattle at slaughter with Escherichia coli O157.
- Author
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Mather AE, Innocent GT, McEwen SA, Reilly WJ, Taylor DJ, Steele WB, Gunn GJ, Ternent HE, Reid SW, and Mellor DJ
- Subjects
- Animal Husbandry, Animals, Logistic Models, Models, Biological, Odds Ratio, Risk Factors, Scotland, Abattoirs, Cattle microbiology, Escherichia coli O157 isolation & purification, Food Contamination, Food Handling methods, Skin microbiology
- Abstract
In the slaughter processing of cattle, contaminated hides have been identified as one of the major sources of Escherichia coli O157 carcase contamination. Logistic regression analysis was applied to data collected in a large scale study in Scotland involving 222 cattle forming 34 groups sent for slaughter from 30 farms to 10 slaughterhouses. Aspects of individual animal characteristics, farm management practices and slaughterhouse features were examined to identify potential risk factors for hide contamination at harvest. Two models were developed, the first in which slaughterhouse was modelled as a fixed effect, and a second model where slaughterhouse and farm groups were modelled as random effects. In the first model, there was a significantly increased risk of a carcase testing positive for E. coli O157 on the hide if either the hide of the carcase immediately before or after it on the line was contaminated (OR 3.6; 95% CI: 1.4-9.9). If both adjacent carcases had contaminated hides, the odds ratio for the study carcase having a contaminated hide rose to 11.5 (95% CI: 4.4-32.5). If animals were held in lairage, receiving hay as feed appeared to have a protective effect on hide contamination. Transportation to the slaughterhouse by haulier, as opposed to transport by the farmer, was associated with a 5.4 increase in the odds of E. coli O157 contamination. The use of a crush in the lairage, often employed when reading ear tags, was also found to significantly increase the odds of hide contamination with E. coli O157. In the second model, the inclusion of slaughterhouse and farm group as random effects resulted in two of the previously identified factors being associated with hide contamination. If at least one of the adjacent carcases on the line had a contaminated hide, the associated odds ratio was 6.6 (95% CI: 2.8-15.9), which rose to 22.7 (95% CI: 9.3-55.5) if both adjacent hides were contaminated. Receiving hay in lairage was found to be important to the model, although not significant in itself (OR 0.005; 95% CI: 1.2e(-6)-20.7). These results suggest that modifiable risk factors for hide contamination exist. However, in order best to reduce the prevalence of hide contamination at slaughter, individual slaughterhouse risk assessment and intervention strategies are appropriate.
- Published
- 2007
- Full Text
- View/download PDF
46. A survey of horse owners in Great Britain regarding horses in their care. Part 2: Risk factors for recurrent airway obstruction.
- Author
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Hotchkiss JW, Reid SW, and Christley RM
- Subjects
- Age Factors, Air Pollutants adverse effects, Animals, Cluster Analysis, Female, Horses, Logistic Models, Lung Diseases, Obstructive epidemiology, Male, Multivariate Analysis, Prevalence, Recurrence, Respiratory Tract Infections complications, Respiratory Tract Infections epidemiology, Risk Factors, Seasons, Surveys and Questionnaires, United Kingdom epidemiology, Animal Husbandry methods, Horse Diseases epidemiology, Lung Diseases, Obstructive veterinary, Respiratory Tract Infections veterinary
- Abstract
Reasons for Performing Study: Recurrent airway obstruction (RAO) is a commonly encountered respiratory condition of horses. Despite this, the epidemiology of this predominately manageable and reversible disease in Great Britain has been largely ignored., Objectives: To estimate the prevalence of RAO in the general horse population of Great Britain and to investigate possible risk factors for RAO associated with management or early life., Methods: Horse owners were surveyed using a self-administered postal questionnaire that contained a risk-screening questionnaire (RSQ) designed to identify horses with RAO. These owners were randomly selected, following geographical stratification, using 2-stage cluster sampling of veterinary practices and their clients. Multilevel, multivariable logistic regression models were used to investigate risk factors for RAO in the selected horse population., Results: The estimated true prevalence of RAO in the selected horse population was 14.0% (95%CI 10.7-17.4%). Risk factors for RAO identified in a general horse management logistic regression model included increasing age and exposure to an urbanised environment. Recurrent airway obstruction has long been associated with mature horses while the association with an urbanised environment could be related to different management practices in these areas or possibly air pollution could be involved. The second model associated exposure to hay and respiratory infection in early life with a horse having RAO in later life. Challenges to the respiratory system in early life may be involved in the development of this disease., Conclusions and Potential Relevance: Recurrent airway obstruction is a significant health problem in the horse population of Great Britain. This form of epidemiological investigation highlights potential risk factors for the disease.
- Published
- 2007
- Full Text
- View/download PDF
47. A survey of horse owners in Great Britain regarding horses in their care. Part 1: Horse demographic characteristics and management.
- Author
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Hotchkiss JW, Reid SW, and Christley RM
- Subjects
- Animal Feed, Animal Husbandry standards, Animals, Cluster Analysis, Data Collection, Demography, Female, Housing, Animal standards, Male, Ownership statistics & numerical data, Seasons, Surveys and Questionnaires, United Kingdom, Veterinary Medicine standards, Animal Husbandry methods, Horses physiology, Veterinary Medicine methods
- Abstract
Reasons for Performing Study: Information is scarce as to how horses are kept and managed in the general horse population of Great Britain., Objectives: To characterise the demographics of horses in Great Britain and assess their care (with particular reference to the respiratory system)., Methods: Horse owners were surveyed using a self-administered postal questionnaire. These owners were selected randomly, following geographical stratification, using 2-stage cluster sampling of veterinary practices and their clients., Results: The overall response proportion to the survey was 68.2%. An investigation of nonresponse bias detected minimal differences between responders and nonresponders. A summary of the demographic characteristics, feeding and management of horses in a sample of the general population of Great Britain is presented., Conclusions and Potential Relevance: Horses are kept under a great variety of conditions with some potentially exposed to high concentrations of organic dusts associated with stabling. This information is relevant to their health and welfare.
- Published
- 2007
- Full Text
- View/download PDF
48. Assessing the convergence of Markov Chain Monte Carlo methods: an example from evaluation of diagnostic tests in absence of a gold standard.
- Author
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Toft N, Innocent GT, Gettinby G, and Reid SW
- Subjects
- Algorithms, Animal Diseases epidemiology, Animals, Bayes Theorem, Diagnosis, Differential, Markov Chains, Monte Carlo Method, Reproducibility of Results, Sensitivity and Specificity, Animal Diseases diagnosis, Models, Biological, Models, Statistical, Software
- Abstract
The accessibility of Markov Chain Monte Carlo (MCMC) methods for statistical inference have improved with the advent of general purpose software. This enables researchers with limited statistical skills to perform Bayesian analysis. Using MCMC sampling to do statistical inference requires convergence of the MCMC chain to its stationary distribution. There is no certain way to prove convergence; it is only possible to ascertain when convergence definitely has not been achieved. These methods are rather subjective and not implemented as automatic safeguards in general MCMC software. This paper considers a pragmatic approach towards assessing the convergence of MCMC methods illustrated by a Bayesian analysis of the Hui-Walter model for evaluating diagnostic tests in the absence of a gold standard. The Hui-Walter model has two optimal solutions, a property which causes problems with convergence when the solutions are sufficiently close in the parameter space. Using simulated data we demonstrate tools to assess the convergence and mixing of MCMC chains using examples with and without convergence. Suggestions to remedy the situation when the MCMC sampler fails to converge are given. The epidemiological implications of the two solutions of the Hui-Walter model are discussed.
- Published
- 2007
- Full Text
- View/download PDF
49. Incisional complications following exploratory celiotomy: does an abdominal bandage reduce the risk?
- Author
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Smith LJ, Mellor DJ, Marr CM, Reid SW, and Mair TS
- Subjects
- Animals, Colic mortality, Colic surgery, Female, Horse Diseases mortality, Horses, Laparotomy adverse effects, Laparotomy methods, Male, Multivariate Analysis, Postoperative Complications epidemiology, Postoperative Complications prevention & control, Risk Factors, Time Factors, Treatment Outcome, Bandages veterinary, Colic veterinary, Horse Diseases surgery, Laparotomy veterinary, Postoperative Complications veterinary
- Abstract
Reasons for Performing Study: Post operative complications following exploratory laparotomy can be potentially life-threatening, increase post operative morbidity and result in an increase in the length of hospitalisation of the affected individual. No study has evaluated the efficacy of specific strategies to reduce the incidence of post operative incisional complications., Hypothesis: The use of an abdominal bandage following colic surgery through a celiotomy incision would significantly reduce the prevalence of post operative incisional complications., Methods: A controlled, randomised clinical trial to test the hypothesis was devised. Horses eligible for inclusion in the study were assigned randomly either to the study or control group following recovery from general anaesthesia. Any post operative incisional complications occurring during hospitalisation were recorded. Long-term follow-up was obtained via telephone questionnaires. Absolute risk reduction (ARR) and number needed to treat (NNT) were calculated. Multivariable analyses were conducted for all outcomes of interest., Results: There was an ARR of the likelihood of developing a post operative incisional complication of 45% when using compared to not using an abdominal bandage in the post operative period. Therefore, it would be necessary to treat 2.2 horses with an abdominal bandage in order to prevent one horse developing any post operative incisional complications., Conclusions: Although incisional complications continue to be a problem following an exploratory celiotomy for colic, the proportion of horses affected was significantly reduced by use of a bandage., Potential Relevance: Using an abdominal bandage following an exploratory laparotomy may help reduce the prevalence of post operative incisional complications, and prevent the development of potentially life-threatening complications.
- Published
- 2007
- Full Text
- View/download PDF
50. Construction and validation of a risk-screening questionnaire for the investigation of recurrent airway obstruction in epidemiological studies of horse populations in Great Britain.
- Author
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Hotchkiss JW, Reid SW, and Christley R
- Subjects
- Airway Obstruction diagnosis, Airway Obstruction epidemiology, Animals, Case-Control Studies, Delphi Technique, Female, Horse Diseases diagnosis, Horses, Humans, Male, ROC Curve, Recurrence, Risk Factors, Sensitivity and Specificity, United Kingdom epidemiology, Airway Obstruction veterinary, Horse Diseases epidemiology, Surveys and Questionnaires standards
- Abstract
Recurrent airway obstruction (RAO) is an environmental respiratory disease affecting horses. A risk-screening questionnaire (RSQ) for RAO would provide a useful tool to investigate the epidemiology of the disease in horses; our aim in this study was to construct and validate such an instrument. Guidance for what questions to include in the RSQ came from three processes: a review of the scientific literature, a survey of equine practitioners in the UK and a consultation with 19 experts using a modified Delphi technique. The latter consultation consisted of two rounds; agreement amongst the experts increased between the rounds. The quantitative outputs provided estimates of the probabilities of a horse having RAO for each particular piece of historical information or clinical sign. The RSQ for RAO was a short questionnaire for completion by horse owners regarding the horse, its health and its management. The likelihood of a horse having RAO (the RAO score) was calculated from a completed RSQ by combining the relevant estimated probabilities. The RSQ was validated against a reference standard of a veterinary diagnosis including respiratory cytology. This was achieved by inviting veterinary surgeons (residing in Great Britain who had taken part in the practitioner survey, and who had indicated that they used respiratory cytology in the diagnosis of respiratory cases) to participate. During 2003 and 2004 these veterinary surgeons returned RSQs for 40 cases that underwent investigation of the respiratory tract and 40 controls; 18 of the cases were given a final diagnosis of RAO. A receiver-operating characteristic (ROC) curve was used to select a positive cut-off of 0.87 for the RSQ for RAO. This suggested that the RSQ had a sensitivity of 0.83 (95% confidence interval=0.59-0.96) and specificity of 0.85 (0.74-0.93) for the diagnosis of apparent RAO (compared to all other diagnoses).
- Published
- 2006
- Full Text
- View/download PDF
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