21 results on '"Gimma A"'
Search Results
2. Longitudinal social contact data analysis: insights from 2 years of data collection in Belgium during the COVID-19 pandemic
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Loedy, Neilshan, primary, Coletti, Pietro, additional, Wambua, James, additional, Hermans, Lisa, additional, Willem, Lander, additional, Jarvis, Christopher I., additional, Wong, Kerry L. M., additional, Edmunds, W. John, additional, Robert, Alexis, additional, Leclerc, Quentin J., additional, Gimma, Amy, additional, Molenberghs, Geert, additional, Beutels, Philippe, additional, Faes, Christel, additional, and Hens, Niel, additional
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- 2023
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3. Impact of tiered measures on social contact and mixing patterns of in Italy during the second wave of COVID-19
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Tizzani, Michele, primary, De Gaetano, Alessandro, additional, Jarvis, Christopher I., additional, Gimma, Amy, additional, Wong, Kerry, additional, Edmunds, W John, additional, Beutels, Philippe, additional, Hens, Niel, additional, Coletti, Pietro, additional, and Paolotti, Daniela, additional
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- 2023
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4. COVID-19 vaccine hesitancy and social contact patterns in Pakistan: results from a national cross-sectional survey
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Quaife, Matthew, primary, Torres-Rueda, Sergio, additional, Dobreva, Zlatina, additional, van Zandvoort, Kevin, additional, Jarvis, Christopher I., additional, Gimma, Amy, additional, Zulfiqar, Wahaj, additional, Khalid, Muhammad, additional, and Vassall, Anna, additional
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- 2023
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5. COVID-19 vaccine hesitancy and social contact patterns in Pakistan: results from a national cross-sectional survey
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Matthew Quaife, Sergio Torres-Rueda, Zlatina Dobreva, Kevin van Zandvoort, Christopher I. Jarvis, Amy Gimma, Wahaj Zulfiqar, Muhammad Khalid, and Anna Vassall
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Infectious Diseases - Abstract
Background Vaccination is a key tool against COVID-19. However, in many settings it is not clear how acceptable COVID-19 vaccination is among the general population, or how hesitancy correlates with risk of disease acquisition. In this study we conducted a nationally representative survey in Pakistan to measure vaccination perceptions and social contacts in the context of COVID-19 control measures and vaccination programmes. Methods We conducted a vaccine perception and social contact survey with 3,658 respondents across five provinces in Pakistan, between 31 May and 29 June 2021. Respondents were asked a series of vaccine perceptions questions, to report all direct physical and non-physical contacts made the previous day, and a number of other questions regarding the social and economic impact of COVID-19 and control measures. We examined variation in perceptions and contact patterns by geographic and demographic factors. We describe knowledge, experiences and perceived risks of COVID-19. We explored variation in contact patterns by individual characteristics and vaccine hesitancy, and compared to patterns from non-pandemic periods. Results Self-reported adherence to self-isolation guidelines was poor, and 51% of respondents did not know where to access a COVID-19 test. Although 48.1% of participants agreed that they would get a vaccine if offered, vaccine hesitancy was higher than in previous surveys, and greatest in Sindh and Baluchistan provinces and among respondents of lower socioeconomic status. Participants reported a median of 5 contacts the previous day (IQR: 3–5, mean 14.0, 95%CI: 13.2, 14.9). There were no substantial differences in the number of contacts reported by individual characteristics, but contacts varied substantially among respondents reporting more or less vaccine hesitancy. Contacts were highly assortative, particularly outside the household where 97% of men's contacts were with other men. We estimate that social contacts were 9% lower than before the COVID-19 pandemic. Conclusions Although the perceived risk of COVID-19 in Pakistan is low in the general population, around half of participants in this survey indicated they would get vaccinated if offered. Vaccine impact studies which do not account for correlation between social contacts and vaccine hesitancy may incorrectly estimate the impact of vaccines, for example, if unvaccinated people have more contacts.
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- 2023
6. Dynamics of non-household contacts during the COVID-19 pandemic in 2020 and 2021 in the Netherlands
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Backer, Jantien A., primary, Bogaardt, Laurens, additional, Beutels, Philippe, additional, Coletti, Pietro, additional, Edmunds, W. John, additional, Gimma, Amy, additional, van Hagen, Cheyenne C. E., additional, Hens, Niel, additional, Jarvis, Christopher I., additional, Vos, Eric R. A., additional, Wambua, James, additional, Wong, Denise, additional, van Zandvoort, Kevin, additional, and Wallinga, Jacco, additional
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- 2023
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7. Pregnancy during COVID-19: social contact patterns and vaccine coverage of pregnant women from CoMix in 19 European countries
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Wong, Kerry L. M., Gimma, Amy, Paixao, Enny S., Paolotti, Daniela, Karch, André, Jäger, Veronika, Baruch, Joaquin, Melillo, Tanya, Hudeckova, Henrieta, Rosinska, Magdalena, Niedzwiedzka-Stadnik, Marta, Fischer, Krista, Vorobjov, Sigrid, Sõnajalg, Hanna, Althaus, Christian, Low, Nicola, Reichmuth, Martina, Auranen, Kari, Nurhonen, Markku, Petrović, Goranka, Makaric, Zvjezdana Lovric, Namorado, Sónia, Caetano, Constantino, Santos, Ana João, Röst, Gergely, Oroszi, Beatrix, Karsai, Márton, Fafangel, Mario, Klepac, Petra, Kranjec, Natalija, Vilaplana, Cristina, Casabona, Jordi, Faes, Christel, Beutels, Philippe, Hens, Niel, Jarvis, Christopher I., Edmunds, W. John, CoMix Europe Working Group, Wong, Kerry L. M., Gimma, Amy, Paixao, Enny S., FAES, Christel, Beutels, Philippe, HENS, Niel, Jarvis, Christopher I., Edmunds, W. John, and CoMix Europe Working Group
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COVID-19 Vaccines ,Lockdowns ,Confinamento ,Social contact ,Pregnancy ,Contactos Sociais ,Humans ,Pandemics ,Vaccines ,Science & Technology ,Contact survey ,Social Contact ,Contact Survey ,Vaccination ,Cuidados de Saúde ,Obstetrics & Gynecology ,COVID-19 ,Obstetrics and Gynecology ,Europe ,Pregnancy, COVID-19, Contact survey, Social contact, Lockdowns, Europe ,Gravidez ,Female ,Pregnant Women ,Human medicine ,Determinantes da Saúde e da Doença ,Europa ,Life Sciences & Biomedicine ,Vaccine - Abstract
CoMix Europe Working Group: Daniela Paolotti, André Karch, Veronika Jäger, Joaquin Baruch, Tanya Melillo, Henrieta Hudeckova, Magdalena Rosinska, Marta Niedzwiedzka-Stadnik, Krista Fischer, Sigrid Vorobjov, Hanna Sõnajalg, Christian Althaus, Nicola Low, Martina Reichmuth, Kari Auranen, Markku Nurhonen, Goranka Petrović, Zvjezdana Lovric Makaric, Sónia Namorado, Constantino Caetano, Ana João Santos, Gergely Röst, Beatrix Oroszi, Márton Karsai, Mario Fafangel, Petra Klepac, Natalija Kranjec, Cristina Vilaplana, Jordi Casabona. CoMix Europe Working Group: Sónia Namorado, Constantino Caetano, and Ana João Santos (Department of Epidemiology, National Institute of Health Dr Ricardo Jorge, Portugal) Background: Evidence and advice for pregnant women evolved during the COVID-19 pandemic. We studied social contact behaviour and vaccine uptake in pregnant women between March 2020 and September 2021 in 19 European countries. Methods: In each country, repeated online survey data were collected from a panel of nationally-representative participants. We calculated the adjusted mean number of contacts reported with an individual-level generalized additive mixed model, modelled using the negative binomial distribution and a log link function. Mean proportion of people in isolation or quarantine, and vaccination coverage by pregnancy status and gender were calculated using a clustered bootstrap. Findings: We recorded 4,129 observations from 1,041 pregnant women, and 115,359 observations from 29,860 non-pregnant individuals aged 18-49. Pregnant women made slightly fewer contacts (3.6, 95%CI = 3.5-3.7) than non-pregnant women (4.0, 95%CI = 3.9-4.0), driven by fewer work contacts but marginally more contacts in non-essential social settings. Approximately 15-20% pregnant and 5% of non-pregnant individuals reported to be in isolation and quarantine for large parts of the study period. COVID-19 vaccine coverage was higher in pregnant women than in non-pregnant women between January and April 2021. Since May 2021, vaccination in non-pregnant women began to increase and surpassed that in pregnant women. Interpretation: Limited social contact to avoid pathogen exposure during the COVID-19 pandemic has been a challenge to many, especially women going through pregnancy. More recognition of maternal social support desire is needed in the ongoing pandemic. As COVID-19 vaccination continues to remain an important pillar of outbreak response, strategies to promote correct information can provide reassurance and facilitate informed pregnancy vaccine decisions in this vulnerable group. HPRU in Modelling & Health Economics,NIHR200908,European Union’s Horizon 2020 research and innovation programme,EpiPose 101003688,TransMID 682540,TransMID 682540,TransMID 682540,EpiPose 101003688,Wellcome Trust,213589/Z/18/Z,National Institute for Health Research,CV220-088—COMIX,CV220-088—COMIX,CV220-088— COMIX,Global Challenges Research Fund,ES/P010873/1,Medical Research Council,MC_PC_19065,NIHR,PR-OD-1017-20002 HPRU in Modelling & Health Economics (NIHR200908: KLMW); European Union Horizon 2020 research and innovation programme – (EpiPose 101,003,688: AG, WJE). Wellcome Trust (213,589/Z/18/Z: ESP). European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (TransMID 682,540: CF, PN, NH). This research was partly funded by the Global Challenges Research Fund (GCRF) project RECAP managed through RCUK and ESRC (ES/P010873/1: CIJ). NIHR (PR-OD-1017–20,002: WJE) UK MRC (MC_PC_19065—Covid 19: Understanding the dynamics and drivers of the COVID-19 epidemic using real-time outbreak analytics: WJE). info:eu-repo/semantics/publishedVersion
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- 2022
8. Characterising social contacts under COVID-19 control measures in Africa
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Zlatina Dobreva, Amy Gimma, Hana Rohan, Benjamin Djoudalbaye, Akhona Tshangela, Christopher I. Jarvis, Kevin van Zandvoort, and Matthew Quaife
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Adult ,Male ,Cross-Sectional Studies ,SARS-CoV-2 ,Communicable Disease Control ,COVID-19 ,Humans ,Nigeria ,Female ,General Medicine ,Pandemics - Abstract
Background Early in the COVID-19 pandemic, countries adopted non-pharmaceutical interventions (NPIs) such as lockdowns to limit SARS-CoV-2 transmission. Social contact studies help measure the effectiveness of NPIs and estimate parameters for modelling SARS-CoV-2 transmission. However, few contact studies have been conducted in Africa. Methods We analysed nationally representative cross-sectional survey data from 19 African Union Member States, collected by the Partnership for Evidence-based Responses to COVID-19 (PERC) via telephone interviews at two time points (August 2020 and February 2021). Adult respondents reported contacts made in the previous day by age group, demographic characteristics, and their attitudes towards COVID-19. We described mean and median contacts across these characteristics and related contacts to Google Mobility reports and the Oxford Government Response Stringency Index for each country at the two time points. Results Mean reported contacts varied across countries with the lowest reported in Ethiopia (9, SD=16, median = 4, IQR = 8) in August 2020 and the highest in Sudan (50, SD=53, median = 33, IQR = 40) in February 2021. Contacts of people aged 18–55 represented 50% of total contacts, with most contacts in household and work or study settings for both surveys. Mean contacts increased for Ethiopia, Ghana, Liberia, Nigeria, Sudan, and Uganda and decreased for Cameroon, the Democratic Republic of Congo (DRC), and Tunisia between the two time points. Men had more contacts than women and contacts were consistent across urban or rural settings (except in Cameroon and Kenya, where urban respondents had more contacts than rural ones, and in Senegal and Zambia, where the opposite was the case). There were no strong and consistent variations in the number of mean or median contacts by education level, self-reported health, perceived self-reported risk of infection, vaccine acceptance, mask ownership, and perceived risk of COVID-19 to health. Mean contacts were correlated with Google mobility (coefficient 0.57, p=0.051 and coefficient 0.28, p=0.291 in August 2020 and February 2021, respectively) and Stringency Index (coefficient −0.12, p = 0.304 and coefficient −0.33, p=0.005 in August 2020 and February 2021, respectively). Conclusions These are the first COVID-19 social contact data collected for 16 of the 19 countries surveyed. We find a high reported number of daily contacts in all countries and substantial variations in mean contacts across countries and by gender. Increased stringency and decreased mobility were associated with a reduction in the number of contacts. These data may be useful to understand transmission patterns, model infection transmission, and for pandemic planning.
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- 2022
9. Characterising social contacts under COVID-19 control measures in Africa
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Dobreva, Zlatina, primary, Gimma, Amy, additional, Rohan, Hana, additional, Djoudalbaye, Benjamin, additional, Tshangela, Akhona, additional, Jarvis, Christopher I., additional, van Zandvoort, Kevin, additional, and Quaife, Matthew, additional
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- 2022
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10. The impact of COVID-19 vaccination in prisons in England and Wales: a metapopulation model
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McCarthy, Ciara V., O’Mara, Oscar, van Leeuwen, Edwin, Sherratt, Katharine, Abbas, Kaja, Wong, Kerry LM, Atkins, Katherine E., Lowe, Rachel, Meakin, Sophie R, Davies, Nicholas G., Russell, Timothy W, O’Reilly, Kathleen, Hué, Stéphane, Finch, Emilie, Villabona-Arenas, C Julian, Edmunds, W John, Jafari, Yalda, Tully, Damien C, Bosse, Nikos I, Pearson, Carl A B, Hodgson, David, Kucharski, Adam J, Medley, Graham, Liu, Yang, Procter, Simon R, Waites, William, Abbott, Sam, Barnard, Rosanna C, Sun, Fiona Yueqian, Gibbs, Hamish P, Eggo, Rosalind M, Chapman, Lloyd A C, Flasche, Stefan, Endo, Akira, Mee, Paul, Munday, James D, Koltai, Mihaly, Gimma, Amy, Jarvis, Christopher I, Quaife, Matthew, Clifford, Samuel, Funk, Sebastian, Prem, Kiesha, Knight, Gwenan M, Pung, Rachael, Brady, Oliver, Quilty, Billy J, Jit, Mark, and Sandmann, Frank
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Public health ,COVID-19 Vaccines ,Wales ,Mathematical model ,England ,SARS-CoV-2 ,Prisons ,Vaccination ,Public Health, Environmental and Occupational Health ,Humans ,COVID-19 ,Middle Aged - Abstract
Background High incidence of cases and deaths due to coronavirus disease 2019 (COVID-19) have been reported in prisons worldwide. This study aimed to evaluate the impact of different COVID-19 vaccination strategies in epidemiologically semi-enclosed settings such as prisons, where staff interact regularly with those incarcerated and the wider community. Methods We used a metapopulation transmission-dynamic model of a local prison in England and Wales. Two-dose vaccination strategies included no vaccination, vaccination of all individuals who are incarcerated and/or staff, and an age-based approach. Outcomes were quantified in terms of COVID-19-related symptomatic cases, losses in quality-adjusted life-years (QALYs), and deaths. Results Compared to no vaccination, vaccinating all people living and working in prison reduced cases, QALY loss and deaths over a one-year period by 41%, 32% and 36% respectively. However, if vaccine introduction was delayed until the start of an outbreak, the impact was negligible. Vaccinating individuals who are incarcerated and staff over 50 years old averted one death for every 104 vaccination courses administered. All-staff-only strategies reduced cases by up to 5%. Increasing coverage from 30 to 90% among those who are incarcerated reduced cases by around 30 percentage points. Conclusions The impact of vaccination in prison settings was highly dependent on early and rapid vaccine delivery. If administered to both those living and working in prison prior to an outbreak occurring, vaccines could substantially reduce COVID-19-related morbidity and mortality in prison settings.
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- 2022
11. The influence of risk perceptions on close contact frequency during the SARS-CoV-2 pandemic
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Wambua, James, primary, Hermans, Lisa, additional, Coletti, Pietro, additional, Verelst, Frederik, additional, Willem, Lander, additional, Jarvis, Christopher I., additional, Gimma, Amy, additional, Wong, Kerry L. M., additional, Lajot, Adrien, additional, Demarest, Stefaan, additional, Edmunds, W. John, additional, Faes, Christel, additional, Beutels, Philippe, additional, and Hens, Niel, additional
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- 2022
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12. A method for small-area estimation of population mortality in settings affected by crises
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Checchi, Francesco, primary, Testa, Adrienne, additional, Gimma, Amy, additional, Koum-Besson, Emilie, additional, and Warsame, Abdihamid, additional
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- 2022
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13. Predicted norovirus resurgence in 2021–2022 due to the relaxation of nonpharmaceutical interventions associated with COVID-19 restrictions in England: a mathematical modeling study
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O’Reilly, Kathleen M., primary, Sandman, Frank, additional, Allen, David, additional, Jarvis, Christopher I., additional, Gimma, Amy, additional, Douglas, Amy, additional, Larkin, Lesley, additional, Wong, Kerry L. M., additional, Baguelin, Marc, additional, Baric, Ralph S., additional, Lindesmith, Lisa C., additional, Goldstein, Richard A., additional, Breuer, Judith, additional, and Edmunds, W. John, additional
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- 2021
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14. Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data
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Munday, James D, Jarvis, Christopher I, Gimma, Amy, Wong, Kerry LM, van Zandvoort, Kevin, CMMID COVID-19 Working Group, Funk, Sebastian, and Edmunds, W John
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genetic structures ,education - Abstract
BACKGROUND: Schools were closed in England on 4 January 2021 as part of increased national restrictions to curb transmission of SARS-CoV-2. The UK government reopened schools on 8 March. Although there was evidence of lower individual-level transmission risk amongst children compared to adults, the combined effects of this with increased contact rates in school settings and the resulting impact on the overall transmission rate in the population were not clear. METHODS: We measured social contacts of > 5000 participants weekly from March 2020, including periods when schools were both open and closed, amongst other restrictions. We combined these data with estimates of the susceptibility and infectiousness of children compared with adults to estimate the impact of reopening schools on the reproduction number. RESULTS: Our analysis indicates that reopening all schools under the same measures as previous periods that combined lockdown with face-to-face schooling would be likely to increase the reproduction number substantially. Assuming a baseline of 0.8, we estimated a likely increase to between 1.0 and 1.5 with the reopening of all schools or to between 0.9 and 1.2 reopening primary or secondary schools alone. CONCLUSION: Our results suggest that reopening schools would likely halt the fall in cases observed between January and March 2021 and would risk a return to rising infections, but these estimates relied heavily on the latest estimates or reproduction number and the validity of the susceptibility and infectiousness profiles we used at the time of reopening.
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- 2021
15. Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England
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Leclerc, QJ, Fuller, NM, Keogh, RH, Diaz-Ordaz, K, Sekula, R, Semple, MG, Baillie, JK, Openshaw, PJM, Carson, G, Alex, B, Bach, B, Barclay, WS, Bogaert, D, Chand, M, Cooke, GS, Docherty, AB, Dunning, J, da Silva Filipe, A, Fletcher, T, Green, CA, Harrison, EM, Hiscox, JA, Ho, AYW, Horby, PW, Ijaz, S, Khoo, S, Klenerman, P, Law, A, Lim, WS, Mentzer, AJ, Merson, L, Meynert, AM, Noursadeghi, M, Moore, SC, Palmarini, M, Paxton, WA, Pollakis, G, Price, N, Rambaut, A, Robertson, DL, Russell, CD, Sancho-Shimizu, V, Scott, JT, de Silva, T, Sigfrid, L, Solomon, T, Sriskandan, S, Stuart, D, Summers, C, Tedder, RS, Thomson, EC, Thompson, AAR, Thwaites, RS, Turtle, LCW, Zambon, M, Hardwick, H, Donohue, C, Lyons, R, Griffiths, F, Oosthuyzen, W, Norman, L, Pius, R, Drake, TM, Fairfield, CJ, Knight, S, Mclean, KA, Murphy, D, Shaw, CA, Dalton, J, Lee, J, Plotkin, D, Girvan, M, Saviciute, E, Roberts, S, Harrison, J, Marsh, L, Connor, M, Halpin, S, Jackson, C, Gamble, C, Petersen, C, Mullaney, S, Leeming, G, Wham, M, Clohisey, S, Hendry, R, Scott-Brown, J, Greenhalf, W, Shaw, V, McDonald, S, Keating, S, Ahmed, KA, Armstrong, JA, Ashworth, M, Asiimwe, IG, Bakshi, S, Barlow, SL, Booth, L, Brennan, B, Bullock, K, Catterall, BWA, Clark, JJ, Clarke, EA, Cole, S, Cooper, L, Cox, H, Davis, C, Dincarslan, O, Dunn, C, Dyer, P, Elliott, A, Evans, A, Finch, L, Fisher, LWS, Foster, T, Garcia-Dorival, I, Gunning, P, Hartley, C, Ho, A, Jensen, RL, Jones, CB, Jones, TR, Khandaker, S, King, K, Kiy, RT, Koukorava, C, Lake, A, Lant, S, Latawiec, D, Lavelle-Langham, L, Lefteri, D, Lett, L, Livoti, LA, Mancini, M, McEvoy, L, McLauchlan, J, Metelmann, S, Miah, NS, Middleton, J, Mitchell, J, Murphy, EG, Penrice-Randal, R, Pilgrim, J, Prince, T, Reynolds, W, Ridley, PM, Sales, D, Shaw, VE, Shears, RK, Small, B, Subramaniam, KS, Szemiel, A, Taggart, A, Tanianis-Hughes, J, Thomas, J, Trochu, E, van Tonder, L, Wilcock, E, Zhang, JE, Adeniji, K, Agranoff, D, Agwuh, K, Ail, D, Alegria, A, Angus, B, Ashish, A, Atkinson, D, Bari, S, Barlow, G, Barnass, S, Barrett, N, Bassford, C, Baxter, D, Beadsworth, M, Bernatoniene, J, Berridge, J, Best, N, Bothma, P, Brealey, D, Brittain-Long, R, Bulteel, N, Burden, T, Burtenshaw, A, Caruth, V, Chadwick, D, Chambler, D, Chee, N, Child, J, Chukkambotla, S, Clark, T, Collini, P, Cosgrove, C, Cupitt, J, Cutino-Moguel, M-T, Dark, P, Dawson, C, Dervisevic, S, Donnison, P, Douthwaite, S, DuRand, I, Dushianthan, A, Dyer, T, Evans, C, Eziefula, C, Fegan, C, Finn, A, Fullerton, D, Garg, S, Garg, A, Gkrania-Klotsas, E, Godden, J, Goldsmith, A, Graham, C, Hardy, E, Hartshorn, S, Harvey, D, Havalda, P, Hawcutt, DB, Hobrok, M, Hodgson, L, Hormis, A, Jacobs, M, Jain, S, Jennings, P, Kaliappan, A, Kasipandian, V, Kegg, S, Kelsey, M, Kendall, J, Kerrison, C, Kerslake, I, Koch, O, Koduri, G, Koshy, G, Laha, S, Laird, S, Larkin, S, Leiner, T, Lillie, P, Limb, J, Linnett, V, Little, J, MacMahon, M, MacNaughton, E, Mankregod, R, Masson, H, Matovu, E, McCullough, K, McEwen, R, Meda, M, Mills, G, Minton, J, Mirfenderesky, M, Mohandas, K, Mok, Q, Moon, J, Moore, E, Morgan, P, Morris, C, Mortimore, K, Moses, S, Mpenge, M, Mulla, R, Murphy, M, Nagel, M, Nagarajan, T, Nelson, M, Otahal, I, Pais, M, Panchatsharam, S, Paraiso, H, Patel, B, Pattison, N, Pepperell, J, Peters, M, Phull, M, Pintus, S, Pooni, JS, Post, F, Price, D, Prout, R, Rae, N, Reschreiter, H, Reynolds, T, Richardson, N, Roberts, M, Roberts, D, Rose, A, Rousseau, G, Ryan, B, Saluja, T, Shah, A, Shanmuga, P, Sharma, A, Shawcross, A, Sizer, J, Shankar-Hari, M, Smith, R, Snelson, C, Spittle, N, Staines, N, Stambach, T, Stewart, R, Subudhi, P, Szakmany, T, Tatham, K, Thompson, C, Thompson, R, Tridente, A, Tupper-Carey, D, Twagira, M, Ustianowski, A, Vallotton, N, Vincent-Smith, L, Visuvanathan, S, Vuylsteke, A, Waddy, S, Wake, R, Walden, A, Welters, I, Whitehouse, T, Whittaker, P, Whittington, A, Wijesinghe, M, Williams, M, Wilson, L, Wilson, S, Winchester, S, Wiselka, M, Wolverson, A, Wooton, DG, Workman, A, Yates, B, Young, P, Quaife, M, Jarvis, CI, Meakin, SR, Quilty, BJ, Prem, K, Villabona-Arenas, CJ, Sun, FY, Abbas, K, Auzenbergs, M, Gimma, A, Tully, DC, Sherratt, K, Rosello, A, Davies, NG, Liu, Y, Lowe, R, Gibbs, HP, Waterlow, NR, Edmunds, WJ, Simons, D, Medley, G, Munday, JD, Flasche, S, Sandmann, FG, Showering, A, Eggo, RM, Chan, Y-WD, Pearson, CAB, Kucharski, AJ, Foss, AM, Russell, TW, Bosse, NI, Jit, M, Abbott, S, Williams, J, Endo, A, Clifford, S, Gore-Langton, GR, Klepac, P, Brady, O, Hellewell, J, Funk, S, van Zandvoort, K, Barnard, RC, Nightingale, ES, Jombart, T, Atkins, KE, Procter, SR, and Knight, GM
- Abstract
Background\ud \ud Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient’s “bed pathway” - the sequence of transfers of individual patients between bed types during a hospital stay. In this study, we characterise these pathways, and their impact on predicted hospital bed occupancy.\ud \ud \ud \ud Methods\ud \ud We obtained data from University College Hospital (UCH) and the ISARIC4C COVID-19 Clinical Information Network (CO-CIN) on hospitalised patients with COVID-19 who required care in general ward or critical care (CC) beds to determine possible bed pathways and LoS. We developed a discrete-time model to examine the implications of using either bed pathways or only average LoS by bed type to forecast bed occupancy. We compared model-predicted bed occupancy to publicly available bed occupancy data on COVID-19 in England between March and August 2020.\ud \ud \ud \ud Results\ud \ud In both the UCH and CO-CIN datasets, 82% of hospitalised patients with COVID-19 only received care in general ward beds. We identified four other bed pathways, present in both datasets: “Ward, CC, Ward”, “Ward, CC”, “CC” and “CC, Ward”. Mean LoS varied by bed type, pathway, and dataset, between 1.78 and 13.53 days.\ud \ud \ud \ud For UCH, we found that using bed pathways improved the accuracy of bed occupancy predictions, while only using an average LoS for each bed type underestimated true bed occupancy. However, using the CO-CIN LoS dataset we were not able to replicate past data on bed occupancy in England, suggesting regional LoS heterogeneities.\ud \ud \ud \ud Conclusions\ud \ud We identified five bed pathways, with substantial variation in LoS by bed type, pathway, and geography. This might be caused by local differences in patient characteristics, clinical care strategies, or resource availability, and suggests that national LoS averages may not be appropriate for local forecasts of bed occupancy for COVID-19.\ud \ud \ud \ud Trial registration\ud \ud The ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR.
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- 2021
16. SOCRATES-CoMix: a platform for timely and open-source contact mixing data during and in between COVID-19 surges and interventions in over 20 European countries
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Verelst, Frederik, primary, Hermans, Lisa, additional, Vercruysse, Sarah, additional, Gimma, Amy, additional, Coletti, Pietro, additional, Backer, Jantien A., additional, Wong, Kerry L. M., additional, Wambua, James, additional, van Zandvoort, Kevin, additional, Willem, Lander, additional, Bogaardt, Laurens, additional, Faes, Christel, additional, Jarvis, Christopher I., additional, Wallinga, Jacco, additional, Edmunds, W. John, additional, Beutels, Philippe, additional, and Hens, Niel, additional
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- 2021
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17. Implications of the school-household network structure on SARS-CoV-2 transmission under school reopening strategies in England
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Munday, James D., Sherratt, Katharine, Meakin, Sophie, Endo, Akira, Pearson, Carl A. B., Hellewell, Joel, Abbott, Sam, Bosse, Nikos I., Eggo, Rosalind M., Simons, David, O’Reilly, Kathleen, Russell, Timothy W., Lowe, Rachel, Leclerc, Quentin J., Emery, Jon C., Klepac, Petra, Nightingale, Emily S., Quaife, Matthew, van Zandvoort, Kevin, Knight, Gwenan M., Jombart, Thibaut, Villabona-Arenas, C. Julian, Rees, Eleanor M., Diamond, Charlie, Auzenbergs, Megan, Medley, Graham, Foss, Anna M., Gore-Langton, Georgia R., Deol, Arminder K., Jit, Mark, Gibbs, Hamish P., Procter, Simon R., Rosello, Alicia, Jarvis, Christopher I., Liu, Yang, Houben, Rein M. G. J., Hué, Stéphane, Clifford, Samuel, Quilty, Billy J., Gimma, Amy, Tully, Damien C., Sun, Fiona Yueqian, Prem, Kiesha, Atkins, Katherine E., Wallinga, Jacco, Edmunds, W. John, van Hoek, Albert Jan, and Funk, Sebastian
- Subjects
0301 basic medicine ,Economic growth ,2019-20 coronavirus outbreak ,Coronavirus disease 2019 (COVID-19) ,Adolescent ,genetic structures ,Epidemiology ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Science ,education ,General Physics and Astronomy ,Network structure ,Risk Assessment ,General Biochemistry, Genetics and Molecular Biology ,Article ,law.invention ,03 medical and health sciences ,0302 clinical medicine ,law ,Risk Factors ,Pandemic ,Disease Transmission, Infectious ,Humans ,Computational models ,030212 general & internal medicine ,Disease Transmission, Infectious/prevention & control ,England/epidemiology ,Child ,Pandemics ,COVID-19/epidemiology ,Family Characteristics ,Multidisciplinary ,Schools ,SARS-CoV-2 ,SARS-CoV-2/isolation & purification ,COVID-19 ,General Chemistry ,Schools/organization & administration ,030104 developmental biology ,Transmission (mechanics) ,England ,Viral infection ,Child, Preschool ,Business ,Risk assessment ,Disease transmission - Abstract
In early 2020 many countries closed schools to mitigate the spread of SARS-CoV-2. Since then, governments have sought to relax the closures, engendering a need to understand associated risks. Using address records, we construct a network of schools in England connected through pupils who share households. We evaluate the risk of transmission between schools under different reopening scenarios. We show that whilst reopening select year-groups causes low risk of large-scale transmission, reopening secondary schools could result in outbreaks affecting up to 2.5 million households if unmitigated, highlighting the importance of careful monitoring and within-school infection control to avoid further school closures or other restrictions., Many countries have closed schools as part of their COVID-19 response. Here, the authors model SARS-CoV-2 transmission on a network of schools and households in England, and find that risk of transmission between schools is lower if primary schools are open than if secondary schools are open.
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- 2021
18. The practice of evaluating epidemic response in humanitarian and low-income settings: a systematic review
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Abdihamid Warsame, Jillian Murray, Francesco Checchi, and Amy Gimma
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medicine.medical_specialty ,030231 tropical medicine ,MEDLINE ,Epidemic ,lcsh:Medicine ,CINAHL ,Infections ,03 medical and health sciences ,0302 clinical medicine ,Environmental health ,Global health ,Humans ,Medicine ,030212 general & internal medicine ,Epidemics ,Evaluation ,Poverty ,business.industry ,Public health ,Humanitarian ,lcsh:R ,Low-income ,Outbreak ,General Medicine ,Grey literature ,Altruism ,Health equity ,Accountability ,Public Health ,business ,Delivery of Health Care ,Research Article - Abstract
Background Epidemics of infectious disease occur frequently in low-income and humanitarian settings and pose a serious threat to populations. However, relatively little is known about responses to these epidemics. Robust evaluations can generate evidence on response efforts and inform future improvements. This systematic review aimed to (i) identify epidemics reported in low-income and crisis settings, (ii) determine the frequency with which evaluations of responses to these epidemics were conducted, (iii) describe the main typologies of evaluations undertaken and (iv) identify key gaps and strengths of recent evaluation practice. Methods Reported epidemics were extracted from the following sources: World Health Organization Disease Outbreak News (WHO DON), UNICEF Cholera platform, Reliefweb, PROMED and Global Incidence Map. A systematic review for evaluation reports was conducted using the MEDLINE, EMBASE, Global Health, Web of Science, WPRIM, Reliefweb, PDQ Evidence and CINAHL Plus databases, complemented by grey literature searches using Google and Google Scholar. Evaluation records were quality-scored and linked to epidemics based on time and place. The time period for the review was 2010–2019. Results A total of 429 epidemics were identified, primarily in sub-Saharan Africa, the Middle East and Central Asia. A total of 15,424 potential evaluations records were screened, 699 assessed for eligibility and 132 included for narrative synthesis. Only one tenth of epidemics had a corresponding response evaluation. Overall, there was wide variability in the quality, content as well as in the disease coverage of evaluation reports. Conclusion The current state of evaluations of responses to these epidemics reveals large gaps in coverage and quality and bears important implications for health equity and accountability to affected populations. The limited availability of epidemic response evaluations prevents improvements to future public health response. The diversity of emphasis and methods of available evaluations limits comparison across responses and time. In order to improve future response and save lives, there is a pressing need to develop a standardized and practical approach as well as governance arrangements to ensure the systematic conduct of epidemic response evaluations in low-income and crisis settings.
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- 2020
19. Changing travel patterns in China during the early stages of the COVID-19 pandemic
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Gibbs, Hamish, Liu, Yang, Pearson, Carl A. B., Jarvis, Christopher I., Grundy, Chris, Quilty, Billy J., Diamond, Charlie, Simons, David, Gimma, Amy, Leclerc, Quentin J., Auzenbergs, Megan, Lowe, Rachel, O’Reilly, Kathleen, Quaife, Matthew, Hellewell, Joel, Knight, Gwenan M., Jombart, Thibaut, Klepac, Petra, Procter, Simon R., Deol, Arminder K., Rees, Eleanor M., Flasche, Stefan, Kucharski, Adam J., Abbott, Sam, Sun, Fiona Yueqian, Endo, Akira, Medley, Graham, Munday, James D., Meakin, Sophie R., Bosse, Nikos I., Edmunds, W. John, Davies, Nicholas G., Prem, Kiesha, Hué, Stéphane, Villabona-Arenas, C. Julian, Nightingale, Emily S., Houben, Rein M. G. J., Foss, Anna M., Tully, Damien C., Emery, Jon C., van Zandvoort, Kevin, Atkins, Katherine E., Rosello, Alicia, Funk, Sebastian, Jit, Mark, Clifford, Samuel, Russell, Timothy W., and Eggo, Rosalind M.
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0301 basic medicine ,Time Factors ,Epidemiology ,General Physics and Astronomy ,Transportation ,0302 clinical medicine ,Health care ,Pandemic ,Computational models ,030212 general & internal medicine ,lcsh:Science ,Holidays ,Travel ,0303 health sciences ,Multidisciplinary ,Geography ,Public Health ,Coronavirus Infections ,Mainland China ,China ,2019-20 coronavirus outbreak ,medicine.medical_specialty ,Coronavirus disease 2019 (COVID-19) ,Science ,Pneumonia, Viral ,Policy and public health in microbiology ,Article ,General Biochemistry, Genetics and Molecular Biology ,Betacoronavirus ,03 medical and health sciences ,Development economics ,medicine ,Humans ,Pandemics ,030304 developmental biology ,Population Density ,SARS-CoV-2 ,business.industry ,Public health ,COVID-19 ,General Chemistry ,030104 developmental biology ,13. Climate action ,lcsh:Q ,Demographic economics ,business ,Delivery of Health Care ,human activities - Abstract
Understanding changes in human mobility in the early stages of the COVID-19 pandemic is crucial for assessing the impacts of travel restrictions designed to reduce disease spread. Here, relying on data from mainland China, we investigate the spatio-temporal characteristics of human mobility between 1st January and 1st March 2020, and discuss their public health implications. An outbound travel surge from Wuhan before travel restrictions were implemented was also observed across China due to the Lunar New Year, indicating that holiday travel may have played a larger role in mobility changes compared to impending travel restrictions. Holiday travel also shifted healthcare pressure related to COVID-19 towards locations with lower healthcare capacity. Network analyses showed no sign of major changes in the transportation network after Lunar New Year. Changes observed were temporary and did not lead to structural reorganisation of the transportation network during the study period., COVID-19-related travel restrictions were imposed in China around the same time as major annual holiday migrations, with unknown combined impacts on mobility patterns. Here, the authors show that restructuring of the travel network in response to restrictions was temporary, whilst holiday-related travel increased pressure on healthcare services with lower capacity.
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- 2020
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20. CoMix: comparing mixing patterns in the Belgian population during and after lockdown
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Coletti, Pietro, primary, Wambua, James, additional, Gimma, Amy, additional, Willem, Lander, additional, Vercruysse, Sarah, additional, Vanhoutte, Bieke, additional, Jarvis, Christopher I., additional, Van Zandvoort, Kevin, additional, Edmunds, John, additional, Beutels, Philippe, additional, and Hens, Niel, additional
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- 2020
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21. The practice of evaluating epidemic response in humanitarian and low-income settings: a systematic review
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Warsame, Abdihamid, primary, Murray, Jillian, additional, Gimma, Amy, additional, and Checchi, Francesco, additional
- Published
- 2020
- Full Text
- View/download PDF
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