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1. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Author: Brauer, M, Roth, GA, Aravkin, AY, Zheng, P, Abate, KH, Abate, YH, Abbafati, C, Abbasgholizadeh, R, Abbasi, MA, Abbasian, M, Abbasifard, M, Abbasi-Kangevari, M, Abd ElHafeez, S, Abd-Elsalam, S, Abdi, P, Abdollahi, M, Abdoun, M, Abdulah, DM, Abdullahi, A, Abebe, M, Abedi, A, Abegaz, TM, Abeldaño Zuñiga, RA, Abiodun, O, Abiso, TL, Aboagye, RG, Abolhassani, H, Abouzid, M, Aboye, GB, Abreu, LG, Abualruz, H, Abubakar, B, Abu-Gharbieh, E, Abukhadijah, HJJ, Aburuz, S, Abu-Zaid, A, Adane, MM, Addo, IY, Addolorato, G, Adedoyin, RA, Adekanmbi, V, Aden, B, Adetunji, JB, Adeyeoluwa, TE, Adha, R, Adibi, A, Adnani, QES, Adzigbli, LA, Afolabi, AA, Afolabi, RF, Afshin, A, Afyouni, S, Afzal, MS, Afzal, S, Agampodi, SB, Agbozo, F, Aghamiri, S, Agodi, A, Agrawal, A, Agyemang-Duah, W, Ahinkorah, BO, Ahmad, A, Ahmad, D, Ahmad, F, Ahmad, N, Ahmad, S, Ahmad, T, Ahmed, A, Ahmed, LA, Ahmed, MB, Ahmed, S, Ahmed, SA, Ajami, M, Akalu, GT, Akara, EM, Akbarialiabad, H, Akhlaghi, S, Akinosoglou, K, Akinyemiju, T, Akkaif, MA, Akkala, S, Akombi-Inyang, B, Al Awaidy, S, Al Hasan, SM, Alahdab, F, AL-Ahdal, TMA, Alalalmeh, SO, Alalwan, TA, Al-Aly, Z, Alam, K, Alam, N, Alanezi, FM, Alanzi, TM, Albakri, A, AlBataineh, MT, Aldhaleei, WA, Aldridge, RW, Alemayohu, MA, Alemu, YM, Al-Fatly, B, Al-Gheethi, AAS, Al-Habbal, K, Alhabib, KF, Alhassan, RK, Ali, A, Ali, BA, Ali, I, Ali, L, Ali, MU, Ali, R, Ali, SSS, Ali, W, Alicandro, G, Alif, SM, Aljunid, SM, Alla, F, Al-Marwani, S, Al-Mekhlafi, HM, Almustanyir, S, Alomari, MA, Alonso, J, Alqahtani, JS, Alqutaibi, AY, Al-Raddadi, RM, Alrawashdeh, A, Al-Rifai, RH, Alrousan, SM, Al-Sabah, SK, Alshahrani, NZ, Altaany, Z, Altaf, A, Al-Tawfiq, JA, Altirkawi, KA, Aluh, DO, Alvis-Guzman, N, Alvis-Zakzuk, NJ, Alwafi, H, Al-Wardat, MS, Al-Worafi, YM, Aly, H, Aly, S, Alzoubi, KH, Al-Zyoud, W, Amaechi, UA, Aman Mohammadi, M, Amani, R, Amiri, S, Amirzade-Iranaq, MH, Ammirati, E, Amu, H, Amugsi, DA, Amusa, GA, Ancuceanu, R, Anderlini, D, Anderson, JA, Andrade, PP, Andrei, CL, Andrei, T, Anenberg, SC, Angappan, D, Angus, C, Anil, A, Anil, S, Anjum, A, Anoushiravani, A, Antonazzo, IC, Antony, CM, Antriyandarti, E, Anuoluwa, BS, Anvari, D, Anvari, S, Anwar, S, Anwar, SL, Anwer, R, Anyabolo, EE, Anyasodor, AE, Apostol, GLC, Arabloo, J, Arabzadeh Bahri, R, Arafat, M, Areda, D, Aregawi, BB, Aremu, A, Armocida, B, Arndt, MB, Ärnlöv, J, Arooj, M, Artamonov, AA, Artanti, KD, Aruleba, IT, Arumugam, A, Asbeutah, AM, Asgary, S, Asgedom, AA, Ashbaugh, C, Ashemo, MY, Ashraf, T, Askarinejad, A, Assmus, M, Astell-Burt, T, Athar, M, Athari, SS, Atorkey, P, Atreya, A, Aujayeb, A, Ausloos, M, Avila-Burgos, L, Awoke, AA, Ayala Quintanilla, BP, Ayatollahi, H, Ayestas Portugal, C, Ayuso-Mateos, JL, Azadnajafabad, S, Azevedo, RMS, Azhar, GS, Azizi, H, Azzam, AY, Backhaus, IL, Badar, M, Badiye, AD, Bagga, A, Baghdadi, S, Bagheri, N, Bagherieh, S, Bahrami Taghanaki, P, Bai, R, Baig, AA, Baker, JL, Bakkannavar, SM, Balasubramanian, M, Baltatu, OC, Bam, K, Bandyopadhyay, S, Banik, B, Banik, PC, Banke-Thomas, A, Bansal, H, Barchitta, M, Bardhan, M, Bardideh, E, Barker-Collo, SL, Bärnighausen, TW, Barone-Adesi, F, Barqawi, HJ, Barrero, LH, Barrow, A, Barteit, S, Basharat, Z, Basiru, A, Basso, JD, Bastan, M-M, Basu, S, Batchu, S, Batra, K, Batra, R, Baune, BT, Bayati, M, Bayileyegn, NS, Beaney, T, Behnoush, AH, Beiranvand, M, Béjot, Y, Bekele, A, Belgaumi, UI, Bell, AW, Bell, ML, Bello, MB, Bello, OO, Belo, L, Beloukas, A, Bendak, S, Bennett, DA, Bennitt, FB, Bensenor, IM, Benzian, H, Beran, A, Berezvai, Z, Bernabe, E, Bernstein, RS, Bettencourt, PJG, Bhagavathula, AS, Bhala, N, Bhandari, D, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Bhat, AN, Bhat, V, Bhatti, GK, Bhatti, JS, Bhatti, MS, Bhatti, R, Bhuiyan, MA, Bhutta, ZA, Bikbov, B, Bishai, JD, Bisignano, C, Biswas, A, Biswas, B, Biswas, RK, Bjørge, T, Boachie, MK, Boakye, H, Bockarie, MJ, Bodolica, V, Bodunrin, AO, Bogale, EK, Bolla, SR, Boloor, A, Bonakdar Hashemi, M, Boppana, SH, Bora Basara, B, Borhany, H, Botero Carvajal, A, Bouaoud, S, Boufous, S, Bourne, R, Boxe, C, Braithwaite, D, Brant, LC, Brar, A, Breitborde, NJK, Breitner, S, Brenner, H, Briko, AN, Britton, G, Brown, CS, Browne, AJ, Brunoni, AR, Bryazka, D, Bulamu, NB, Bulto, LN, Buonsenso, D, Burkart, K, Burns, RA, Busse, R, Bustanji, Y, Butt, NS, Butt, ZA, Caetano dos Santos, FL, Cagney, J, Cahuana-Hurtado, L, Calina, D, Cámera, LA, Campos, LA, Campos-Nonato, IR, Cao, C, Cao, F, Cao, Y, Capodici, A, Cárdenas, R, Carr, S, Carreras, G, Carrero, JJ, Carugno, A, Carvalho, F, Carvalho, M, Castaldelli-Maia, JM, Castañeda-Orjuela, CA, Castelpietra, G, Catalá-López, F, Catapano, AL, Cattaruzza, MS, Caye, A, Cederroth, CR, Cegolon, L, Cenderadewi, M, Cercy, KM, Cerin, E, Chadwick, J, Chakraborty, C, Chakraborty, PA, Chakraborty, S, Chan, JSK, Chan, RNC, Chandan, JS, Chandika, RM, Chaturvedi, P, Chen, A-T, Chen, CS, Chen, H, Chen, MX, Chen, M, Chen, S, Cheng, C-Y, Cheng, ETW, Cherbuin, N, Chi, G, Chichagi, F, Chimed-Ochir, O, Chimoriya, R, Ching, PR, Chirinos-Caceres, JL, Chitheer, A, Cho, WCS, Chong, B, Chopra, H, Chowdhury, R, Christopher, DJ, Chu, D-T, Chukwu, IS, Chung, E, Chung, S-C, Chutiyami, M, Cioffi, I, Cogen, RM, Cohen, AJ, Columbus, A, Conde, J, Corlateanu, A, Cortese, S, Cortesi, PA, Costa, VM, Costanzo, S, Criqui, MH, Cruz, JA, Cruz-Martins, N, Culbreth, GT, da Silva, AG, Dadras, O, Dai, X, Dai, Z, Daikwo, PU, Dalli, LL, Damiani, G, D'Amico, E, D'Anna, L, Darwesh, AM, Das, JK, Das, S, Dash, NR, Dashti, M, Dávila-Cervantes, CA, Davis Weaver, N, Davitoiu, DV, De la Hoz, FP, de la Torre-Luque, A, De Leo, D, Debopadhaya, S, Degenhardt, L, Del Bo', C, Delgado-Enciso, I, Delgado-Saborit, JM, Demoze, CK, Denova-Gutiérrez, E, Dervenis, N, Dervišević, E, Desai, HD, Desai, R, Devanbu, VGC, Dewan, SMR, Dhali, A, Dhama, K, Dhane, AS, Dhimal, ML, Dhimal, M, Dhingra, S, Dhulipala, VR, Dhungana, RR, Dias da Silva, D, Diaz, D, Diaz, LA, Diaz, MJ, Dima, A, Ding, DD, Dinu, M, Djalalinia, S, Do, TC, Do, THP, do Prado, CB, Dodangeh, M, Dohare, S, Dokova, KG, Dong, W, Dongarwar, D, D'Oria, M, Dorostkar, F, Dorsey, ER, Doshi, R, Doshmangir, L, Dowou, RK, Driscoll, TR, Dsouza, AC, Dsouza, HL, Dumith, SC, Duncan, BB, Duraes, AR, Duraisamy, S, Dushpanova, A, Dzianach, PA, Dziedzic, AM, Ebrahimi, A, Echieh, CP, Ed-Dra, A, Edinur, HA, Edvardsson, D, Edvardsson, K, Efendi, F, Eftekharimehrabad, A, Eini, E, Ekholuenetale, M, Ekundayo, TC, El Arab, RA, El Sayed Zaki, M, El-Dahiyat, F, Elemam, NM, Elgar, FJ, ElGohary, GMT, Elhabashy, HR, Elhadi, M, Elmehrath, AO, Elmeligy, OAA, Elshaer, M, Elsohaby, I, Emeto, TI, Esfandiari, N, Eshrati, B, Eslami, M, Esmaeili, SV, Estep, K, Etaee, F, Fabin, N, Fagbamigbe, AF, Fagbule, OF, Fahimi, S, Falzone, L, Fareed, M, Farinha, CSES, Faris, MEM, Faris, PS, Faro, A, Fasina, FO, Fatehizadeh, A, Fauk, NK, Fazylov, T, Feigin, VL, Feng, X, Fereshtehnejad, S-M, Feroze, AH, Ferrara, P, Ferrari, AJ, Ferreira, N, Fetensa, G, Feyisa, BR, Filip, I, Fischer, F, Fitriana, I, Flavel, J, Flohr, C, Flood, D, Flor, LS, Foigt, NA, Folayan, MO, Force, LM, Fortuna, D, Foschi, M, Franklin, RC, Freitas, A, Friedman, SD, Fux, B, G, S, Gaal, PA, Gaihre, S, Gajdács, M, Galali, Y, Gallus, S, Gandhi, AP, Ganesan, B, Ganiyani, MA, Garcia, V, Gardner, WM, Garg, RK, Gautam, RK, Gebi, TG, Gebregergis, MW, Gebrehiwot, M, Gebremariam, TBB, Gebremeskel, TG, Gerema, U, Getacher, L, Getahun, GKA, Getie, M, Ghadirian, F, Ghafarian, S, Ghaffari Jolfayi, A, Ghailan, KY, Ghajar, A, Ghasemi, M, Ghasempour Dabaghi, G, Ghasemzadeh, A, Ghassemi, F, Ghazy, RM, Gholami, A, Gholamrezanezhad, A, Gholizadeh, N, Ghorbani, M, Gil, AU, Gil, GF, Gilbertson, NM, Gill, PS, Gill, TK, Gindaba, EZ, Girmay, A, Glasbey, JC, Gnedovskaya, EV, Göbölös, L, Godinho, MA, Goel, A, Golechha, M, Goleij, P, Golinelli, D, Gomes, NGM, Gopalani, SV, Gorini, G, Goudarzi, H, Goulart, AC, Gouravani, M, Goyal, A, Graham, SM, Grivna, M, Grosso, G, Guan, S-Y, Guarducci, G, Gubari, MIM, Guha, A, Guicciardi, S, Gulati, S, Gulisashvili, D, Gunawardane, DA, Guo, C, Gupta, AK, Gupta, B, Gupta, M, Gupta, R, Gupta, RD, Gupta, S, Gupta, VB, Gupta, VK, Habibzadeh, F, Habibzadeh, P, Hadaro, TS, Hadian, Z, Haep, N, Haghi-Aminjan, H, Haghmorad, D, Hagins, H, Haile, D, Hailu, A, Hajj Ali, A, Halboub, ES, Halimi, A, Hall, BJ, Haller, S, Halwani, R, Hamadeh, RR, Hamdy, NM, Hameed, S, Hamidi, S, Hammoud, A, Hanif, A, Hanifi, N, Haq, ZA, Haque, MR, Harapan, H, Hargono, A, Haro, JM, Hasaballah, AI, Hasan, I, Hasan, MJ, Hasan, SMM, Hasani, H, Hasanian, M, Hashmeh, N, Hasnain, MS, Hassan, A, Hassan, I, Hassan Zadeh Tabatabaei, MS, Hassani, S, Hassanipour, S, Hassankhani, H, Haubold, J, Havmoeller, RJ, Hay, SI, Hebert, JJ, Hegazi, OE, Hegena, TY, Heidari, G, Heidari, M, Helfer, B, Hemmati, M, Henson, CA, Herbert, ME, Herteliu, C, Heuer, A, Hezam, K, Hinneh, TK, Hiraike, Y, Hoan, NQ, Holla, R, Hon, J, Hoque, ME, Horita, N, Hossain, S, Hosseini, SE, Hosseinzadeh, H, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hoven, H, Hsairi, M, Hsu, JM, Hu, C, Huang, J, Huda, MN, Hulland, EN, Hultström, M, Hushmandi, K, Hussain, J, Hussein, NR, Huynh, CK, Huynh, H-H, Ibitoye, SE, Idowu, OO, Ihler, AL, Ikeda, N, Ikuta, KS, Ilesanmi, OS, Ilic, IM, Ilic, MD, Imam, MT, Immurana, M, Inbaraj, LR, Irham, LM, Isa, MA, Islam, MR, Ismail, F, Ismail, NE, Iso, H, Isola, G, Iwagami, M, Iwu, CCD, Iwu-Jaja, CJ, J, V, Jaafari, J, Jacob, L, Jacobsen, KH, Jadidi-Niaragh, F, Jahankhani, K, Jahanmehr, N, Jahrami, H, Jain, A, Jain, N, Jairoun, AA, Jaiswal, A, Jakovljevic, M, Jalilzadeh Yengejeh, R, Jamora, RDG, Jatau, AI, Javadov, S, Javaheri, T, Jayaram, S, Jeganathan, J, Jeswani, BM, Jiang, H, Johnson, CO, Jokar, M, Jomehzadeh, N, Jonas, JB, Joo, T, Joseph, A, Joseph, N, Joshi, V, Joshua, CE, Jozwiak, JJ, Jürisson, M, Kaambwa, B, Kabir, A, Kabir, Z, Kadashetti, V, Kahn, EM, Kalani, R, Kaliyadan, F, Kalra, S, Kamath, R, Kanagasabai, T, Kanchan, T, Kandel, H, Kanmiki, EW, Kanmodi, KK, Kansal, SK, Kapner, DJ, Kapoor, N, Karagiannidis, E, Karajizadeh, M, Karakasis, P, Karanth, SD, Karaye, IM, Karch, A, Karim, A, Karimi, H, Karmakar, S, Kashoo, FZ, Kasraei, H, Kassahun, WD, Kassebaum, NJ, Kassel, MB, Katikireddi, SV, Kauppila, JH, Kawakami, N, Kaydi, N, Kayode, GA, Kazemi, F, Keiyoro, PN, Kemmer, L, Kempen, JH, Kerr, JA, Kesse-Guyot, E, Khader, YS, Khafaie, MA, Khajuria, H, Khalaji, A, Khalil, M, Khalilian, A, Khamesipour, F, Khan, A, Khan, MN, Khan, M, Khan, MJ, Khan, MAB, Khanmohammadi, S, Khatab, K, Khatatbeh, H, Khatatbeh, MM, Khatib, MN, Khavandegar, A, Khayat Kashani, HR, Khidri, FF, Khodadoust, E, Khormali, M, Khorrami, Z, Khosla, AA, Khosrowjerdi, M, Khreis, H, Khusun, H, Kifle, ZD, Kim, K, Kim, MS, Kim, YJ, Kimokoti, RW, Kisa, A, Kisa, S, Knibbs, LD, Knudsen, AKS, Koh, DSQ, Kolahi, A-A, Kompani, F, Kong, J, Koren, G, Korja, M, Korshunov, VA, Korzh, O, Kosen, S, Kothari, N, Koul, PA, Koulmane Laxminarayana, SL, Krishan, K, Krishnamoorthy, V, Krishnamoorthy, Y, Krishnan, B, Krohn, KJ, Kuate Defo, B, Kucuk Bicer, B, Kuddus, MA, Kuddus, M, Kugbey, N, Kuitunen, I, Kulimbet, M, Kulkarni, V, Kumar, A, Kumar, N, Kumar, V, Kundu, S, Kurmi, OP, Kusnali, A, Kusuma, D, Kutluk, T, La Vecchia, C, Ladan, MA, Laflamme, L, Lahariya, C, Lai, DTC, Lal, DK, Lallukka, T, Lám, J, Lan, Q, Lan, T, Landires, I, Lanfranchi, F, Langguth, B, Lansingh, VC, Laplante-Lévesque, A, Larijani, B, Larsson, AO, Lasrado, S, Lauriola, P, Le, H-H, Le, LKD, Le, NHH, Le, TTT, Leasher, JL, Ledda, C, Lee, M, Lee, PH, Lee, SW, Lee, SWH, Lee, YH, LeGrand, KE, Leigh, J, Leong, E, Lerango, TL, Lescinsky, H, Leung, J, Li, M-C, Li, W-Z, Li, W, Li, Y, Li, Z, Ligade, VS, Lim, L-L, Lim, SS, Lin, R-T, Lin, S, Liu, C, Liu, G, Liu, J, Liu, RT, Liu, S, Liu, W, Liu, X, Livingstone, KM, Llanaj, E, Lohiya, A, López-Bueno, R, Lopukhov, PD, Lorkowski, S, Lotufo, PA, Lozano, R, Lubinda, J, Lucchetti, G, Luo, L, lv, H, M Amin, HI, Ma, ZF, Maass, KL, Mabrok, M, Machairas, N, Machoy, M, Mafhoumi, A, Magdy Abd El Razek, M, Maghazachi, AA, Mahadeshwara Prasad, DR, Maharaj, SB, Mahmoud, MA, Mahmoudi, E, Majeed, A, Makram, OM, Makris, KC, Malasala, S, Maled, V, Malhotra, K, Malik, AA, Malik, I, Malinga, LA, Malta, DC, Mamun, AA, Manda, AL, Manla, Y, Mansour, A, Mansouri, B, Mansouri, P, Mansourian, M, Mansournia, MA, Mantovani, LG, Manu, E, Marateb, HR, Maravilla, JC, Marsh, E, Martinez, G, Martinez-Piedra, R, Martini, S, Martins-Melo, FR, Martorell, M, Marx, W, Maryam, S, Mathangasinghe, Y, Mathioudakis, AG, Matozinhos, FP, Mattumpuram, J, Maugeri, A, Maulik, PK, Mayeli, M, Mazidi, M, Mazzotti, A, McGrath, JJ, McKee, M, McKowen, ALW, McLaughlin, SA, McPhail, MA, McPhail, SM, Mechili, EA, Mehmood, A, Mehmood, K, Mehrabani-Zeinabad, K, Mehrabi Nasab, E, Meier, T, Mejia-Rodriguez, F, Mekene Meto, T, Mekonnen, BD, Menezes, RG, Mengist, B, Mensah, GA, Mensah, LG, Mentis, A-FA, Meo, SA, Meretoja, A, Meretoja, TJ, Mersha, AM, Mesfin, BA, Mestrovic, T, Mettananda, KCD, Mettananda, S, Miazgowski, T, Micha, G, Michalek, IM, Micheletti Gomide Nogueira de Sá, AC, Miller, TR, Mirarefin, M, Mirghafourvand, M, Mirica, A, Mirijello, A, Mirrakhimov, EM, Mirshahi, A, Mirzaei, M, Mishra, AK, Mishra, V, Mitchell, PB, Mithra, P, Mittal, C, Moazen, B, Moberg, ME, Mocciaro, G, Mohamadkhani, A, Mohamed, AZ, Mohamed, AI, Mohamed, J, Mohamed, MFH, Mohamed, NS, Mohammadi, E, Mohammadi, S, Mohammadian-Hafshejani, A, Mohammadifard, N, Mohammed, H, Mohammed, M, Mohammed, S, Mokdad, AH, Monasta, L, Mondello, S, Moni, MA, Moodi Ghalibaf, A, Moore, CE, Moradi, M, Moradi, Y, Moraga, P, Morawska, L, Moreira, RS, Morovatdar, N, Morrison, SD, Morze, J, Mosaddeghi Heris, R, Mossialos, E, Motappa, R, Mougin, V, Mousavi, P, Msherghi, A, Mubarik, S, Muccioli, L, Mueller, UO, Mulita, F, Mullany, EC, Munjal, K, Murillo-Zamora, E, Murlimanju, BV, Musina, A-M, Mustafa, G, Muthu, S, Muthupandian, S, Muthusamy, R, Muzaffar, M, Myung, W, Nafei, A, Nagarajan, AJ, Nagaraju, SP, Nagel, G, Naghavi, M, Naghavi, P, Naik, GR, Naik, G, Nainu, F, Nair, TS, Najdaghi, S, Nakhostin Ansari, N, Nanavaty, DP, Nangia, V, Narasimha Swamy, S, Narimani Davani, D, Nascimento, BR, Nascimento, GG, Nashwan, AJ, Natto, ZS, Nauman, J, Navaratna, SNK, Naveed, M, Nayak, BP, Nayak, VC, Ndejjo, R, Nduaguba, SO, Negash, H, Negoi, I, Negoi, RI, Nejadghaderi, SA, Nejjari, C, Nematollahi, MH, Nepal, S, Neupane, S, Ng, M, Nguefack-Tsague, G, Ngunjiri, JW, Nguyen, DH, Nguyen, NNY, Nguyen, PT, Nguyen, VT, Nguyen Tran Minh, D, Niazi, RK, Nicholson, SI, Nie, J, Nikoobar, A, Nikpoor, AR, Ningrum, DNA, Nnaji, CA, Noman, EA, Nomura, S, Noroozi, N, Norrving, B, Noubiap, JJ, Nri-Ezedi, CA, Ntaios, G, Ntsekhe, M, Nunemo, MH, Nurrika, D, Nutor, JJ, Oancea, B, O'Connell, EM, Odetokun, IA, O'Donnell, MJ, Oduro, MS, Ogunfowokan, AA, Ogunkoya, A, Oh, I-H, Okati-Aliabad, H, Okeke, SR, Okekunle, AP, Okonji, OC, Olagunju, AT, Olasupo, OO, Olatubi, MI, Oliveira, AB, Oliveira, GMM, Olorukooba, AA, Olufadewa, II, Olusanya, BO, Olusanya, JO, Oluwafemi, YD, Omar, HA, Omar Bali, A, Omer, GL, Ong, KL, Ong, S, Onwujekwe, OE, Onyedibe, KI, Oppong, AF, Ordak, M, Orish, VN, Ornello, R, Orpana, HM, Ortiz, A, Ortiz-Prado, E, Osman, WMS, Ostroff, SM, Osuagwu, UL, Otoiu, A, Otstavnov, N, Otstavnov, SS, Ouyahia, A, Owolabi, MO, Oyeyemi, IT, Oyeyemi, OT, P A, MP, Pacheco-Barrios, K, Padron-Monedero, A, Padubidri, JR, Pal, PK, Palicz, T, Pan, F, Pan, H-F, Pana, A, Panda, SK, Panda-Jonas, S, Pandey, A, Pandi-Perumal, SR, Pangaribuan, HU, Pantazopoulos, I, Pantea Stoian, AM, Papadopoulou, P, Parent, MC, Parija, PP, Parikh, RR, Park, S, Parsons, N, Pashaei, A, Pasovic, M, Passera, R, Patil, S, Patoulias, D, Patthipati, VS, Paudel, U, Pawar, S, Pazoki Toroudi, H, Peden, AE, Pedersini, P, Peng, M, Pensato, U, Pepito, VCF, Peprah, EK, Peprah, P, Peres, MFP, Perianayagam, A, Perico, N, Perna, S, Pesudovs, K, Petcu, I-R, Petermann-Rocha, FE, Pham, HT, Philip, AK, Phillips, MR, Pickering, BV, Pierannunzio, D, Pigeolet, M, Pigott, DM, Piracha, ZZ, Piradov, MA, 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YF, Wiangkham, T, Wickramasinghe, ND, Wilkerson, C, Willeit, P, Wilson, S, Wong, YJ, Wongsin, U, Wozniak, S, Wu, C, Wu, D, Wu, F, Wu, Z, Xia, J, Xiao, H, Xu, S, Xu, X, Xu, YY, Yadav, MK, Yaghoubi, S, Yamagishi, K, Yang, L, Yano, Y, Yaribeygi, H, Yasufuku, Y, Ye, P, Yesodharan, R, Yesuf, SA, Yezli, S, Yi, S, Yiğit, A, Yigzaw, ZA, Yin, D, Yip, P, Yismaw, MB, Yon, DK, Yonemoto, N, You, Y, Younis, MZ, Yousefi, Z, Yu, C, Yu, Y, Zadey, S, Zadnik, V, Zakham, F, Zaki, N, Zakzuk, J, Zamagni, G, Zaman, SB, Zandieh, GGZ, Zanghì, A, Zar, HJ, Zare, I, Zarimeidani, F, Zastrozhin, MS, Zeng, Y, Zhai, C, Zhang, AL, Zhang, H, Zhang, L, Zhang, M, Zhang, Y, Zhang, Z, Zhang, Z-J, Zhao, H, Zhao, JT, Zhao, X-JG, Zhao, Y, Zhong, C, Zhou, J, Zhou, S, Zhu, B, Zhu, L, Zhu, Z, Ziaeian, B, Ziafati, M, Zielińska, M, Zimsen, SRM, Zoghi, G, Zoller, T, Zumla, A, Zyoud, SH, Murray, CJL, and Gakidou, E
Published: 2024

2. Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Author: Naghavi, M, Ong, KL, Aali, A, Ababneh, HS, Abate, YH, Abbafati, C, Abbasgholizadeh, R, Abbasian, M, Abbasi-Kangevari, M, Abbastabar, H, Abd ElHafeez, S, Abdelmasseh, M, Abd-Elsalam, S, Abdelwahab, A, Abdollahi, M, Abdollahifar, M-A, Abdoun, M, Abdulah, DM, Abdullahi, A, Abebe, M, Abebe, SS, Abedi, A, Abegaz, KH, Abhilash, ES, Abidi, H, Abiodun, O, Aboagye, RG, Abolhassani, H, Abolmaali, M, Abouzid, M, Aboye, GB, Abreu, LG, Abrha, WA, Abtahi, D, Abu Rumeileh, S, Abualruz, H, Abubakar, B, Abu-Gharbieh, E, Abu-Rmeileh, NME, Aburuz, S, Abu-Zaid, A, Accrombessi, MMK, Adal, TG, Adamu, AA, Addo, IY, Addolorato, G, Adebiyi, AO, Adekanmbi, V, Adepoju, AV, Adetunji, CO, Adetunji, JB, Adeyeoluwa, TE, Adeyinka, DA, Adeyomoye, OI, Admass, BAA, Adnani, QES, Adra, S, Afolabi, AA, Afzal, MS, Afzal, S, Agampodi, SB, Agasthi, P, Aggarwal, M, Aghamiri, S, Agide, FD, Agodi, A, Agrawal, A, Agyemang-Duah, W, Ahinkorah, BO, Ahmad, A, Ahmad, D, Ahmad, F, Ahmad, MM, Ahmad, S, Ahmad, T, Ahmadi, K, Ahmadzade, AM, Ahmed, A, Ahmed, H, Ahmed, LA, Ahmed, MS, Ahmed, MB, Ahmed, SA, Ajami, M, Aji, B, Akara, EM, Akbarialiabad, H, Akinosoglou, K, Akinyemiju, T, Akkaif, MA, Akyirem, S, Al Hamad, H, Al Hasan, SM, Alahdab, F, Alalalmeh, SO, Alalwan, TA, Al-Aly, Z, Alam, K, Alam, M, Alam, N, Al-amer, RM, Alanezi, FM, Alanzi, TM, Al-Azzam, S, Albakri, A, Albashtawy, M, AlBataineh, MT, Alcalde-Rabanal, JE, Aldawsari, KA, Aldhaleei, WA, Aldridge, RW, Alema, HB, Alemayohu, MA, Alemi, S, Alemu, YM, Al-Gheethi, AAS, Alhabib, KF, Alhalaiqa, FAN, Al-Hanawi, MK, Ali, A, Ali, L, Ali, MU, Ali, R, Ali, S, Ali, SSS, Alicandro, G, Alif, SM, Alikhani, R, Alimohamadi, Y, Aliyi, AA, Aljasir, MAM, Aljunid, SM, Alla, F, Allebeck, P, Al-Marwani, S, Al-Maweri, SAA, Almazan, JU, Al-Mekhlafi, HM, Almidani, L, Almidani, O, Alomari, MA, Al-Omari, B, Alonso, J, Alqahtani, JS, Alqalyoobi, S, Alqutaibi, AY, Al-Sabah, SK, Altaany, Z, Altaf, A, Al-Tawfiq, JA, Altirkawi, KA, Aluh, DO, Alvis-Guzman, N, Alwafi, H, Al-Worafi, YM, Aly, H, Aly, S, Alzoubi, KH, Amani, R, Amare, AT, Amegbor, PM, Ameyaw, EK, Amin, TT, Amindarolzarbi, A, Amiri, S, Amirzade-Iranaq, MH, Amu, H, Amugsi, DA, Amusa, GA, Ancuceanu, R, Anderlini, D, Anderson, DB, Andrade, PP, Andrei, CL, Andrei, T, Angus, C, Anil, A, Anil, S, Anoushiravani, A, Ansari, H, Ansariadi, A, Ansari-Moghaddam, A, Antony, CM, Antriyandarti, E, Anvari, D, Anvari, S, Anwar, S, Anwar, SL, Anwer, R, Anyasodor, AE, Aqeel, M, Arab, JP, Arabloo, J, Arafat, M, Aravkin, AY, Areda, D, Aremu, A, Aremu, O, Ariffin, H, Arkew, M, Armocida, B, Arndt, MB, Ärnlöv, J, Arooj, M, Artamonov, AA, Arulappan, J, Aruleba, RT, Arumugam, A, Asaad, M, Asadi-Lari, M, Asgedom, AA, Asghariahmadabad, M, Asghari-Jafarabadi, M, Ashraf, M, Aslani, A, Astell-Burt, T, Athar, M, Athari, SS, Atinafu, BTT, Atlaw, HW, Atorkey, P, Atout, MMW, Atreya, A, Aujayeb, A, Ausloos, M, Avan, A, Awedew, AF, Aweke, AM, Ayala Quintanilla, BP, Ayatollahi, H, Ayuso-Mateos, JL, Ayyoubzadeh, SM, Azadnajafabad, S, Azevedo, RMS, Azzam, AY, B, DB, Babu, AS, Badar, M, Badiye, AD, Baghdadi, S, Bagheri, N, Bagherieh, S, Bah, S, Bahadorikhalili, S, Bahmanziari, N, Bai, R, Baig, AA, Baker, JL, Bako, AT, Bakshi, RK, Balakrishnan, S, Balasubramanian, M, Baltatu, OC, Bam, K, Banach, M, Bandyopadhyay, S, Banik, PC, Bansal, H, Bansal, K, Barbic, F, Barchitta, M, Bardhan, M, Bardideh, E, Barker-Collo, SL, Bärnighausen, TW, Barone-Adesi, F, Barqawi, HJ, Barrero, LH, Barrow, A, Barteit, S, Barua, L, Basharat, Z, Bashiri, A, Basiru, A, Baskaran, P, Basnyat, B, Bassat, Q, Basso, JD, Basting, AVL, Basu, S, Batra, K, Baune, BT, Bayati, M, Bayileyegn, NS, Beaney, T, Bedi, N, Beghi, M, Behboudi, E, Behera, P, Behnoush, AH, Behzadifar, M, Beiranvand, M, Bejarano Ramirez, DF, Béjot, Y, Belay, SA, Belete, CM, Bell, ML, Bello, MB, Bello, OO, Belo, L, Beloukas, A, Bender, RG, Bensenor, IM, Beran, A, Berezvai, Z, Berhie, AY, Berice, BN, Bernstein, RS, Bertolacci, GJ, Bettencourt, PJG, Beyene, KA, Bhagat, DS, 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RG, Cramer, KM, Criqui, MH, Cruz-Martins, N, Cuadra-Hernández, SM, Culbreth, GT, Cullen, P, Cunningham, M, Curado, MP, Dadana, S, Dadras, O, Dai, S, Dai, X, Dai, Z, Dalli, LL, Damiani, G, Darega Gela, J, Das, JK, Das, S, Dascalu, AM, Dash, NR, Dashti, M, Dastiridou, A, Davey, G, Dávila-Cervantes, CA, Davis Weaver, N, Davletov, K, De Leo, D, de Luca, K, Debele, AT, Debopadhaya, S, Degenhardt, L, Dehghan, A, Deitesfeld, L, Del Bo', C, Delgado-Enciso, I, Demessa, BH, Demetriades, AK, Deng, K, Deng, X, Denova-Gutiérrez, E, Deravi, N, Dereje, N, Dervenis, N, Dervišević, E, Des Jarlais, DC, Desai, HD, Desai, R, Devanbu, VGC, Dewan, SMR, Dhali, A, Dhama, K, Dhimal, M, Dhingra, S, Dhulipala, VR, Dias da Silva, D, Diaz, D, Diaz, MJ, Dima, A, Ding, DD, Ding, H, Dinis-Oliveira, RJ, Dirac, MA, Djalalinia, S, Do, THP, do Prado, CB, Doaei, S, Dodangeh, M, Dohare, S, Dokova, KG, Dolecek, C, Dominguez, R-MV, Dong, W, Dongarwar, D, D'Oria, M, Dorostkar, F, Dorsey, ER, dos Santos, WM, Doshi, R, 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Zhu, L, Ziafati, M, Zielińska, M, Zitoun, OA, Zoladl, M, Zou, Z, Zuhlke, LJ, Zumla, A, Zweck, E, Zyoud, SH, Wool, EE, and Murray, CJL
Published: 2024

3. Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Author: Vollset, SE, Ababneh, HS, Abate, YH, Abbafati, C, Abbasgholizadeh, R, Abbasian, M, Abbastabar, H, Abd Al Magied, AHA, Abd ElHafeez, S, Abdelkader, A, Abdelmasseh, M, Abd-Elsalam, S, Abdi, P, Abdollahi, M, Abdoun, M, Abdullahi, A, Abebe, M, Abiodun, O, Aboagye, RG, Abolhassani, H, Abouzid, M, Aboye, GB, Abreu, LG, Absalan, A, Abualruz, H, Abubakar, B, Abukhadijah, HJJ, Addolorato, G, Adekanmbi, V, Adetunji, CO, Adetunji, JB, Adeyeoluwa, TE, Adha, R, Adhikary, RK, Adnani, QES, Adzigbli, LA, Afrashteh, F, Afzal, MS, Afzal, S, Agbozo, F, Agodi, A, Agrawal, A, Agyemang-Duah, W, Ahinkorah, BO, Ahlstrom, AJ, Ahmad, A, Ahmad, F, Ahmad, MM, Ahmad, S, Ahmed, A, Ahmed, H, Ahmed, S, Ahmed, SA, Akinosoglou, K, Akkaif, MA, Akrami, AE, Akter, E, Al Awaidy, S, Al Hasan, SM, Al Mosa, AS, Al Ta'ani, O, Al Zaabi, OAM, Alahdab, F, Alajlani, MM, Al-Ajlouni, Y, Alalalmeh, SO, Al-Aly, Z, Alam, K, Alam, N, Alam, T, Alam, Z, Al-amer, RM, Alanezi, FM, Alanzi, TM, Albakri, A, Aldhaleei, WA, Aldridge, RW, Alemohammad, SY, Alemu, YM, Al-Gheethi, AAS, Al-Hanawi, MK, Ali, A, Ali, I, Ali, MU, Ali, R, Ali, SSS, Ali, VE, Ali, W, Al-Ibraheem, A, Alicandro, G, Alif, SM, Aljunid, SM, Alla, F, Almazan, JU, Al-Mekhlafi, HM, Alqutaibi, AY, Alrawashdeh, A, Alrousan, SM, Al-Sabah, SK, Alsabri, MA, Altaany, Z, Al-Tammemi, AB, Al-Tawfiq, JA, Altirkawi, KA, Aluh, DO, Alvis-Guzman, N, Al-Wardat, MS, Al-Worafi, YM, Aly, H, Alyahya, MS, Alzoubi, KH, Al-Zyoud, W, Amani, R, Ameyaw, EK, Amin, TT, Amindarolzarbi, A, Amiri, S, Amirzade-Iranaq, MH, Amu, H, Amugsi, DA, Ancuceanu, R, Anderlini, D, Anderson, DB, Andrade, PP, Andrei, CL, Andrei, T, Andrews, EA, Anil, A, Anil, S, Anoushiravani, A, Antony, CM, Antriyandarti, E, Anuoluwa, BS, Anvari, S, Anyasodor, AE, Appiah, F, Aquilano, M, Arab, JP, Arabloo, J, Arafa, EA, Arafat, M, Aravkin, AY, Ardekani, A, Areda, D, Aregawi, BB, Aremu, A, Ariffin, H, Arkew, M, Armani, K, Artamonov, AA, Arumugam, A, Asghari-Jafarabadi, M, Ashbaugh, C, Astell-Burt, T, Athari, SS, 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Silva, AG, Dadras, O, Dai, X, Dai, Z, Dalton, BE, Damiani, G, Dandona, L, Dandona, R, Das, JK, Das, S, Dash, NR, Davletov, K, De la Hoz, FP, De Leo, D, Debopadhaya, S, Delgado-Enciso, I, Denova-Gutiérrez, E, Dervenis, N, Desai, HD, Devanbu, VGC, Dewan, SMR, Dhama, K, Dhane, AS, Dhingra, S, Dias da Silva, D, Diaz, D, Diaz, LA, Diaz, MJ, Dima, A, Ding, DD, Do, THP, do Prado, CB, Dodangeh, M, Doegah, PT, Dohare, S, Dong, W, D'Oria, M, Doshi, R, Dowou, RK, Dsouza, HL, Dsouza, V, Dube, J, Dumith, SC, Duncan, BB, Duraes, AR, Duraisamy, S, Durojaiye, OC, Dushpanova, A, Dutta, S, Dzianach, PA, Dziedzic, AM, Eboreime, E, Ebrahimi, A, Ebrahimi Kalan, M, Edinur, HA, Efendi, F, Eikemo, TA, Eini, E, Ekundayo, TC, El Arab, RA, El Sayed, I, Elamin, O, Elemam, NM, ElGohary, GMT, Elhadi, M, Elmeligy, OAA, Elmoselhi, AB, Elshaer, M, Elsohaby, I, Eltahir, ME, Emeto, TI, Eshrati, B, Eslami, M, Esmaeili, Z, Fabin, N, Fagbamigbe, AF, Fagbule, OF, Falzone, L, Fareed, M, Farinha, CSES, Faris, MEM, Faro, A, Fasihi, K, Fatehizadeh, A, Fauk, NK, Fazylov, T, Feigin, VL, Fekadu, G, Feng, X, Fereshtehnejad, S-M, Ferrara, P, Ferreira, N, Firew, BS, Fischer, F, Fitriana, I, Flavel, J, Flor, LS, Folayan, MO, Foley, KM, Fonzo, M, Force, LM, Foschi, M, Freitas, A, Fridayani, NKY, Fukutaki, KG, Furtado, JM, Fux, B, Gaal, PA, Gadanya, MA, Gallus, S, Ganesan, B, Ganiyani, MA, Gautam, RK, Gebi, TG, Gebregergis, MW, Gebrehiwot, M, Getacher, L, Getahun, GKA, Gething, PW, Ghadimi, DJ, Ghadirian, F, Ghafarian, S, Ghailan, KY, Ghasemi, M, Ghasempour Dabaghi, G, Ghazy, RM, Ghoba, S, Gholami, E, Gholamrezanezhad, A, Gholizadeh, N, Ghorbani, M, Ghorbani Vajargah, P, Ghotbi, E, Gil, AU, Gill, TK, Girmay, A, Glasbey, JC, Glushkova, EV, Gnedovskaya, EV, Göbölös, L, Goldust, M, Goleij, P, Golinelli, D, Gopalani, SV, Goulart, AC, Gouravani, M, Goyal, A, Grivna, M, Grosso, G, Guarducci, G, Gubari, MIM, Guicciardi, S, Guimarães, RA, Gulati, S, Gulisashvili, D, Gunawardane, DA, Guo, C, Gupta, AK, Gupta, R, Gupta, S, Gupta, VK, Haakenstad, A, Hadi, NR, Haep, N, Hafiz, A, Haghmorad, D, Haile, D, Hajj Ali, A, Haj-Mirzaian, A, Halboub, ES, Haller, S, Halwani, R, Hamagharib Abdullah, K, Hamdy, NM, Hamoudi, R, Hanifi, N, Hankey, GJ, Haq, ZA, Haque, MR, Harapan, H, Hargono, A, Haro, JM, Hasaballah, AI, Hasan, SMM, Hasanian, M, Hasnain, MS, Hassan, A, Haubold, J, Hay, SI, Hebert, JJ, Hegazi, OE, Heidari, M, Hemmati, M, Henson, CA, Herrera-Serna, BY, Herteliu, C, Heydari, M, Hezam, K, Hidayana, I, Hiraike, Y, Hoan, NQ, Holla, R, Hoogar, P, Horita, N, Hossain, MM, Hosseinzadeh, H, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hu, C, Huang, J, Hultström, M, Hundie, TG, Hunt, AJ, Hushmandi, K, Hussain, J, Hussain, MA, Hussein, NR, Huynh, H-H, Hwang, B-F, Ibitoye, SE, Iftikhar, PM, Ikiroma, AI, Ikwegbue, PC, Ilic, IM, Ilic, MD, Immurana, M, Isa, MA, Islam, MR, Islam, SMS, Ismail, F, Ismail, NE, Isola, G, Iwagami, M, Iyamu, IO, Jacob, L, Jacobsen, KH, Jafarinia, M, Jahankhani, K, Jahanmehr, N, Jain, N, Jairoun, AA, Jakhmola Mani, DR, Jamil, S, Jamora, RDG, Jatau, AI, Javadov, S, Javaheri, T, Jayaram, S, Jee, SH, Jeganathan, J, Jiang, H, Jokar, M, Jonas, JB, Joseph, N, Joshua, CE, Jürisson, M, K, V, Kabir, A, Kabir, Z, Kadashetti, V, Kalankesh, LR, Kalra, S, Kamath, A, Kamath, R, Kamireddy, A, Kanaan, M, Kanchan, T, Kanmiki, EW, Kanmodi, KK, Kansal, SK, Karim, A, Karkhah, S, Kashoo, FZ, Kasraei, H, Kassel, MB, Katikireddi, SV, Kauppila, JH, Kaur, H, Kayode, GA, Kazemi, F, Kazemian, S, Kebede, F, Kendal, ES, Kesse-Guyot, E, Khademvatan, S, Khajuria, H, Khalaji, A, Khalid, A, Khalid, N, Khalilian, A, Khamesipour, F, Khan, F, Khan, MJ, Khan, MAB, Khanmohammadi, S, Khatab, K, Khatatbeh, H, Khatatbeh, MM, Khatib, MN, Khayat Kashani, HR, Kheirallah, KA, Khokhar, M, Khormali, M, Khorrami, Z, Khosla, AA, Khosravi, M, Khosrowjerdi, M, Khubchandani, J, Kifle, ZD, Kim, G, Kim, JS, Kim, MS, Kim, YJ, Kimokoti, RW, Kisa, A, Kisa, S, Knibbs, LD, Knudsen, AKS, Kochhar, S, Kolahi, A-A, Kompani, F, Koren, G, Korzh, O, Krishan, K, Krishna, V, Krishnamoorthy, V, Kucuk Bicer, B, Kuddus, MA, Kuddus, M, Kuitunen, I, Kujan, O, Kulimbet, M, Kulkarni, V, Kumar, GA, Kumar, H, Kumar, N, Kumar, R, Kumar, V, Kundu, A, Kusuma, D, Kyei-Arthur, F, Kytö, V, Kyu, HH, La Vecchia, C, Lacey, B, Ladan, MA, Laflamme, L, Lahariya, C, Lai, DTC, Lalloo, R, Lallukka, T, Lám, J, Lan, Q, Lan, T, Landires, I, Lanfranchi, F, Langguth, B, Lansingh, VC, Laplante-Lévesque, A, Larijani, B, Larsson, AO, Lasrado, S, Lauriola, P, Lawlor, HR, Le, H-H, Le, LKD, Le, NHH, Le, TTT, Le, TDT, Leasher, JL, Lee, DW, Lee, M, Lee, PH, Lee, S-W, Lee, SW, Lee, SWH, Lee, YH, Leigh, J, Leong, E, Li, M-C, Libra, M, Ligade, VS, Lim, L-L, Lim, SS, Limenh, LW, Lindholm, D, Lindstedt, PA, Listl, S, Liu, G, Liu, S, Liu, X, Llanaj, E, López-Bueno, R, López-Gil, JF, Loreche, AM, Lotufo, PA, Lozano, R, Lubinda, J, Lucchetti, G, Luo, L, Lusk, JB, Lv, L, M Amin, HI, Ma, ZF, Maass, KL, Machairas, N, Machoy, M, Madureira-Carvalho, ÁM, Magdy Abd El 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Published: 2024

4. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Author: Ferrari, AJ, Santomauro, DF, Aali, A, Abate, YH, Abbafati, C, Abbastabar, H, Abd ElHafeez, S, Abdelmasseh, M, Abd-Elsalam, S, Abdollahi, A, Abdullahi, A, Abegaz, KH, Abeldaño Zuñiga, RA, Aboagye, RG, Abolhassani, H, Abreu, LG, Abualruz, H, Abu-Gharbieh, E, Abu-Rmeileh, NME, Ackerman, IN, Addo, IY, Addolorato, G, Adebiyi, AO, Adepoju, AV, Adewuyi, HO, Afyouni, S, Afzal, S, Agodi, A, Ahmad, A, Ahmad, D, Ahmad, F, Ahmad, S, Ahmed, A, Ahmed, LA, Ahmed, MB, Ajami, M, Akinosoglou, K, Akkaif, MA, Al Hasan, SM, Alalalmeh, SO, Al-Aly, Z, Albashtawy, M, Aldridge, RW, Alemu, MD, Alemu, YM, Alene, KA, Al-Gheethi, AAS, Alharrasi, M, Alhassan, RK, Ali, MU, Ali, R, Ali, SSS, Alif, SM, Aljunid, SM, Al-Marwani, S, Almazan, JU, Alomari, MA, Al-Omari, B, Altaany, Z, Alvis-Guzman, N, Alvis-Zakzuk, NJ, Alwafi, H, Al-Wardat, MS, Al-Worafi, YM, Aly, S, Alzoubi, KH, Amare, AT, Amegbor, PM, Ameyaw, EK, Amin, TT, Amindarolzarbi, A, Amiri, S, Amugsi, DA, Ancuceanu, R, Anderlini, D, Anderson, DB, Andrade, PP, Andrei, CL, Ansari, H, Antony, CM, Anwar, S, Anwar, SL, Anwer, R, Anyanwu, PE, Arab, JP, Arabloo, J, Arafat, M, Araki, DT, Aravkin, AY, Arkew, M, Armocida, B, Arndt, MB, Arooj, M, Artamonov, AA, Aruleba, RT, Arumugam, A, Ashbaugh, C, Ashemo, MY, Ashraf, M, Asika, MO, Askari, E, Astell-Burt, T, Athari, SS, Atorkey, P, Atout, MMW, Atreya, A, Aujayeb, A, Ausloos, M, Avan, A, Awotidebe, AW, Awuviry-Newton, K, Ayala Quintanilla, BP, Ayuso-Mateos, JL, Azadnajafabad, S, Azevedo, RMS, Babu, AS, Badar, M, Badiye, AD, Baghdadi, S, Bagheri, N, Bah, S, Bai, R, Baker, JL, Bakkannavar, SM, Bako, AT, Balakrishnan, S, Bam, K, Banik, PC, Barchitta, M, Bardhan, M, Bardideh, E, Barker-Collo, SL, Barqawi, HJ, Barrow, A, Barteit, S, Barua, L, Bashiri Aliabadi, S, Basiru, A, Basu, S, Bathini, PP, Batra, K, Baune, BT, Bayileyegn, NS, Behnam, B, Behnoush, AH, Beiranvand, M, Bejarano Ramirez, DF, Bell, ML, Bello, OO, Beloukas, A, Bensenor, IM, Berezvai, Z, Bernabe, E, Bernstein, RS, Bettencourt, PJG, Bhagavathula, AS, Bhala, N, Bhandari, D, Bhargava, A, Bhaskar, S, Bhat, V, Bhatti, GK, Bhatti, JS, Bhatti, MS, Bhatti, R, Bhutta, ZA, Bikbov, B, Bishai, JD, Bisignano, C, Bitra, VR, Bjørge, T, Bodolica, V, Bodunrin, AO, Bogale, EK, Bonakdar Hashemi, M, Bonny, A, Bora Basara, B, Borhany, H, Boxe, C, Brady, OJ, Bragazzi, NL, Braithwaite, D, Brant, LC, Brauer, M, Breitner, S, Brenner, H, Brown, J, Brugha, T, Bulamu, NB, Buonsenso, D, Burkart, K, Burns, RA, Busse, R, Bustanji, Y, Butt, ZA, Byun, J, Caetano dos Santos, FL, Calina, D, Cámera, LA, Campos-Nonato, IR, Cao, C, Capodici, A, Carr, S, Carreras, G, Carugno, A, Carvalho, M, Castaldelli-Maia, JM, Castañeda-Orjuela, CA, Castelpietra, G, Catapano, AL, Cattaruzza, MS, Caye, A, Cegolon, L, Cembranel, F, Cenderadewi, M, Cerin, E, Chakraborty, PA, Chan, JSK, Chan, RNC, Chandika, RM, Chandrasekar, EK, Charalampous, P, Chattu, VK, Chatzimavridou-Grigoriadou, V, Chen, AW, Chen, A-T, Chen, CS, Chen, H, Chen, NM, Cheng, ETW, Chimed-Ochir, 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Nguyen, DH, Nguyen, HQ, Niazi, RK, Nikolouzakis, TK, Nikoobar, A, Nikoomanesh, F, Nikpoor, AR, Nnaji, CA, Nnyanzi, LA, Noman, EA, Nomura, S, Norrving, B, Nri-Ezedi, CA, Ntaios, G, Ntsekhe, M, Nurrika, D, Nzoputam, CI, Nzoputam, OJ, Oancea, B, Odetokun, IA, O'Donnell, MJ, Oguntade, AS, Oguta, JO, Okati-Aliabad, H, Okeke, SR, Okekunle, AP, Okonji, OC, Olagunju, AT, Olasupo, OO, Olatubi, MI, Oliveira, GMM, Olufadewa, II, Olusanya, BO, Olusanya, JO, Omar, HA, Omer, GL, Omonisi, AEE, Onie, S, Onwujekwe, OE, Ordak, M, Orish, VN, Ortega-Altamirano, DV, Ortiz, A, Ortiz-Brizuela, E, Osman, WMS, Ostroff, SM, Osuagwu, UL, Otoiu, A, Otstavnov, N, Otstavnov, SS, Ouyahia, A, Ouyang, G, Owolabi, MO, P A, MP, Padron-Monedero, A, Padubidri, JR, Palicz, T, Palladino, C, Pan, F, Pandi-Perumal, SR, Pangaribuan, HU, Panos, GD, Panos, LD, Pantea Stoian, AM, Pardhan, S, Parikh, RR, Pashaei, A, Pasovic, M, Passera, R, Patel, J, Patel, SK, Patil, S, Patoulias, D, Patthipati, VS, Pawar, S, Pazoki Toroudi, H, Pease, SA, Peden, AE, Pedersini, P, Peng, M, Pensato, U, Pepito, VCF, Peprah, EK, Peprah, P, Perdigão, J, Pereira, MO, Perianayagam, A, Perico, N, Pesudovs, K, Petermann-Rocha, FE, Petri, WA, Pham, HT, Philip, AK, Phillips, MR, Pigeolet, M, Pigott, DM, Pillay, JD, Piracha, ZZ, Pirouzpanah, S, Plass, D, Plotnikov, E, Poddighe, D, Polinder, S, Postma, MJ, Pourtaheri, N, Prada, SI, Pradhan, PMS, Prakash, V, Prasad, M, Prates, EJS, Priscilla, T, Pritchett, N, Puri, P, Puvvula, J, Qasim, NH, Qattea, I, Qazi, AS, Qian, G, Rabiee Rad, M, Radhakrishnan, RA, Radhakrishnan, V, Raeisi Shahraki, H, Rafferty, Q, Raggi, A, Raghav, PR, Rahim, MJ, Rahman, MM, Rahman, MHU, Rahman, M, Rahman, MA, Rahmani, S, Rahmanian, M, Rahmawaty, S, Rajaa, S, Ramadan, MM, Ramasamy, SK, Ramasubramani, P, Ramazanu, S, Rana, K, Ranabhat, CL, Rancic, N, Rane, A, Rao, CR, Rao, K, Rao, M, Rao, SJ, Rashidi, M-M, Rathnaiah Babu, G, Rauniyar, SK, Rawaf, DL, Rawaf, S, Razo, C, Reddy, MMRK, Redwan, EMM, Reifels, L, Reiner Jr, 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Unsworth, CA, Upadhyay, E, Urso, D, Usman, JS, Vahabi, SM, Vaithinathan, AG, Van den Eynde, J, Varga, O, Varma, RP, Vart, P, Vasankari, TJ, Vasic, M, Vaziri, S, Vellingiri, B, Venketasubramanian, N, Veroux, M, Verras, G-I, Vervoort, D, Villafañe, JH, Violante, FS, Vlassov, V, Vollset, SE, Volovat, SR, Vongpradith, A, Waheed, Y, Wang, C, Wang, F, Wang, N, Wang, S, Wang, Y, Wang, Y-P, Ward, P, Wassie, EG, Weaver, MR, Weerakoon, KG, Weintraub, RG, Weiss, DJ, Weldemariam, AH, Wells, KM, Wen, YF, Whisnant, JL, Whiteford, HA, Wiangkham, T, Wickramasinghe, DP, Wickramasinghe, ND, Wilandika, A, Wilkerson, C, Willeit, P, Wimo, A, Woldegebreal, DH, Wolf, AW, Wong, YJ, Woolf, AD, Wu, C, Wu, F, Wu, X, Wu, Z, Wulf Hanson, S, Xia, Y, Xiao, H, Xu, X, Xu, YY, Yadav, L, Yadollahpour, A, Yaghoubi, S, Yamagishi, K, Yang, L, Yano, Y, Yao, Y, Yaribeygi, H, Yazdanpanah, MH, Ye, P, Yehualashet, SS, Yesuf, SA, Yezli, S, Yiğit, A, Yiğit, V, Yigzaw, ZA, Yismaw, Y, Yon, DK, Yonemoto, N, Younis, MZ, Yu, C, Yu, Y, Yusuf, H, Zahid, MH, Zakham, F, Zaki, L, Zaki, N, Zaman, BA, Zamora, N, Zand, R, Zandieh, GGZ, Zar, HJ, Zarrintan, A, Zastrozhin, MS, Zhang, H, Zhang, N, Zhang, Y, Zhao, H, Zhong, C, Zhong, P, Zhou, J, Zhu, Z, Ziafati, M, Zielińska, M, Zimsen, SRM, Zoladl, M, Zumla, A, Zyoud, SH, Vos, T, and Murray, CJL
Published: 2024

5. On the structural equivalence of coresidents and the measurement of village social structure

Author: Simpson, CR
Subjects: 050402 sociology, Emotional support, Sociology and Political Science, 05 social sciences, Adult population, General Social Sciences, Census, Indigenous, 0506 political science, Personal network, Social support, Interpersonal ties, 0504 sociology, Anthropology, 050602 political science & public administration, Sociology, Equivalence (measure theory), Social psychology, General Psychology
Abstract: Researchers in the social and biomedical sciences regularly measure networks spanning entire villages in low- and middle-income countries by documenting the social contacts of just one or two representatives from participating households. This “lean” approach to network measurement is cost-effective compared to a sociometric census of a village’s adult population. However, it implicitly assumes that interviewed and non-interviewed coresidents are structurally equivalent — i.e., directly connected to the same network members in the same fashion. Drawing from research on multilevel networks and intra-household heterogeneity, here I argue that this assumption is unlikely to hold for the personal social ties typically of interest to field researchers (i.e., friends and other preferred sources and targets of material, informational and emotional support). I substantiate my claim with an exploratory case study on the similarity of coresidents’ incoming and outgoing ties using data documenting unrestricted roster-based reports on the provision of tangible aid amongst all adult residents of a remote village of indigenous horticulturalists in Nicaragua (108 adults; 32 nuclear-family households). Results indicate that coresidents markedly deviate from structural equivalence and its generalisation in the form of stochastic equivalence (i.e., similar probabilities of being directly connected to the same network members in the same fashion). All in all, it is ill-advised to assume that the personal network of any one coresident, or, more generally, the manner in which a coresident tends to send and receive their personal ties, is representative of their household.
Published: 2022

6. Genomic epidemiology reveals transmission patterns and dynamics of SARS-CoV-2 in Aotearoa New Zealand

Author: Geoghegan, JL, Ren, X, Storey, M, Hadfield, J, Jelley, L, Jefferies, S, Sherwood, J, Paine, S, Huang, S, Douglas, J, Mendes, FK, Sporle, A, Baker, MG, Murdoch, DR, French, N, Simpson, CR, Welch, D, Drummond, AJ, Holmes, EC, Duchene, S, de Ligt, J, Geoghegan, JL, Ren, X, Storey, M, Hadfield, J, Jelley, L, Jefferies, S, Sherwood, J, Paine, S, Huang, S, Douglas, J, Mendes, FK, Sporle, A, Baker, MG, Murdoch, DR, French, N, Simpson, CR, Welch, D, Drummond, AJ, Holmes, EC, Duchene, S, and de Ligt, J
Abstract: New Zealand, a geographically remote Pacific island with easily sealable borders, implemented a nationwide 'lockdown' of all non-essential services to curb the spread of COVID-19. Here, we generate 649 SARS-CoV-2 genome sequences from infected patients in New Zealand with samples collected during the 'first wave', representing 56% of all confirmed cases in this time period. Despite its remoteness, the viruses imported into New Zealand represented nearly all of the genomic diversity sequenced from the global virus population. These data helped to quantify the effectiveness of public health interventions. For example, the effective reproductive number, Re of New Zealand's largest cluster decreased from 7 to 0.2 within the first week of lockdown. Similarly, only 19% of virus introductions into New Zealand resulted in ongoing transmission of more than one additional case. Overall, these results demonstrate the utility of genomic pathogen surveillance to inform public health and disease mitigation.
Published: 2020

7. Farm size shapes friend choice amongst rice producers in China: some evidence for the theory of network ecology

Author: Simpson, CR
Subjects: Transitive relation, 050402 sociology, Sociology and Political Science, Ecology, media_common.quotation_subject, 05 social sciences, General Social Sciences, Network science, Social relation, 0506 political science, Friendship, 0504 sociology, Agricultural land, Anthropology, Reciprocity (network science), 050602 political science & public administration, China, General Psychology, media_common
Abstract: Multiple dynamics jointly determine who we befriend, however, researchers have failed to systematically assess which processes matter most under different circumstances. Here I draw on observations around how the demands of paddy rice cultivation shape social interaction to demonstrate that the relative importance of reciprocity, transitivity and generalised exchange to who rice producers choose as friends varies with the amount of agricultural land under their control. In doing so, I use unique data on farm size and friendship amongst 4713 rice-growing smallholders in 162 rural villages in Jiangxi, China along with a new technique for measuring the relative importance of effects in Stochastic Actor-Oriented Models. In line with the micro-level component of the recently advanced “theory of network ecology”, results suggest that features of an individual’s proximal environment can powerfully moderate the relative expression of network-formation mechanisms such that for some individuals, a dynamic may be expected to hold substantial sway over the process of choosing social contacts and, for others, no sway at all.
Published: 2019

8. P133 Safety and effectiveness of influenza vaccines in people with asthma: a systematic review and meta-analysis

Author: Vasileiou, E, primary, Sheikh, A, additional, Butler, C, additional, Ferkh, K El, additional, and Simpson, CR, additional
Published: 2016
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9. Projecting the COPD population and costs in England and Scotland: 2011 to 2030

Author: McLean, S, Hoogendoorn - Lips, Martine, Hoogenveen, RT, Feenstra, TL (Talitha), Wild, S, Simpson, CR, Rutten - van Molken, Maureen, Sheikh, A (Aziz), McLean, S, Hoogendoorn - Lips, Martine, Hoogenveen, RT, Feenstra, TL (Talitha), Wild, S, Simpson, CR, Rutten - van Molken, Maureen, and Sheikh, A (Aziz)
Published: 2016

10. Protocol for a systematic review and individual patient data meta-analysis of prognostic factors of foot ulceration in people with diabetes: the international research collaboration for the prediction of diabetic foot ulcerations (PODUS)

Author: Crawford, F, Anandan, C, Chappell, FM, Murray, GD, Price, JF, Sheikh, A, Simpson, CR, Maxwell, M, Stansby, GP, Young, MJ, Abbott, CA, Boulton, AJM, Boyko, EJ, Kastenbauer, T, Leese, GP, Monami, M, Monteiro-Soares, M, Rith-Najarian, SJ, Veves, A, Coates, N, Jeffcoate, WJ, Leech, N, Fahey, T, Tierney, J, Crawford, F, Anandan, C, Chappell, FM, Murray, GD, Price, JF, Sheikh, A, Simpson, CR, Maxwell, M, Stansby, GP, Young, MJ, Abbott, CA, Boulton, AJM, Boyko, EJ, Kastenbauer, T, Leese, GP, Monami, M, Monteiro-Soares, M, Rith-Najarian, SJ, Veves, A, Coates, N, Jeffcoate, WJ, Leech, N, Fahey, T, and Tierney, J
Abstract: Background Diabetes–related lower limb amputations are associated with considerable morbidity and mortality and are usually preceded by foot ulceration. The available systematic reviews of aggregate data are compromised because the primary studies report both adjusted and unadjusted estimates. As adjusted meta-analyses of aggregate data can be challenging, the best way to standardise the analytical approach is to conduct a meta-analysis based on individual patient data (IPD). There are however many challenges and fundamental methodological omissions are common; protocols are rare and the assessment of the risk of bias arising from the conduct of individual studies is frequently not performed, largely because of the absence of widely agreed criteria for assessing the risk of bias in this type of review. In this protocol we propose key methodological approaches to underpin our IPD systematic review of prognostic factors of foot ulceration in diabetes. Review questions; 1. What are the most highly prognostic factors for foot ulceration (i.e. symptoms, signs, diagnostic tests) in people with diabetes? 2. Can the data from each study be adjusted for a consistent set of adjustment factors? 3. Does the model accuracy change when patient populations are stratified according to demographic and/or clinical characteristics? Methods MEDLINE and EMBASE databases from their inception until early 2012 were searched and the corresponding authors of all eligible primary studies invited to contribute their raw data. We developed relevant quality assurance items likely to identify occasions when study validity may have been compromised from several sources. A confidentiality agreement, arrangements for communication and reporting as well as ethical and governance considerations are explained. We have agreement from the corresponding authors of all studies which meet the eligibility criteria and they collectively possess data from more than 17000 patients. We propose, as a provisional
Published: 2013

11. Seasonal Influenza Vaccine Effectiveness (SIVE): an observational retrospective cohort study – exploitation of a unique community-based national-linked database to determine the effectiveness of the seasonal trivalent influenza vaccine

Author: Simpson, CR, primary, Lone, N, additional, Kavanagh, K, additional, Ritchie, LD, additional, Robertson, C, additional, Sheikh, A, additional, and McMenamin, J, additional
Published: 2013
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12. Vaccine effectiveness in pandemic influenza – primary care reporting (VIPER): an observational study to assess the effectiveness of the pandemic influenza A (H1N1)v vaccine.

Author: Simpson, CR, primary, Ritchie, LD, additional, Robertson,, C, additional, Sheikh, A, additional, and McMenamin, J, additional
Published: 2010
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13. Epidemiology and disease burden from allergic disease in Scotland: analyses of national databases

Author: Anandan, C, primary, Gupta, R, additional, Simpson, CR, additional, Fischbacher, C, additional, and Sheikh, A, additional
Published: 2009
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14. A retrospective observational study comparing rescue medication use in children on combined versus separate long-acting beta-agonists and corticosteroids.

Author: Elkout H, McLay JS, Simpson CR, Helms PJ, Elkout, H, McLay, J S, Simpson, C R, and Helms, P J
Abstract: Background: Data on the efficacy and safety of long-acting β2-agonists (LABA) in children are limited, and current guidelines recommend that LABA always be used with inhaled corticosteroids (ICS).Objective: To compare asthma control, assessed by rescue medications use, in children prescribed LABA and ICS as a fixed-dose combination (LABA/ICS) or concurrently via separate inhalers (LABA+ICS).Methods: Retrospective observational study of asthma medication prescribed to children aged 0-18 years registered with 40 primary care practices for the years 2002-6. Asthma control, reflected by requirement for oral corticosteroids (OCS) and/or six or more short-acting β2-agonist (SABA) canisters per year, was assessed for children prescribed LABA/ICS or LABA+ICS.Results: 10,454 (8%) of all registered children received at least one prescription for asthma medication over the study period. Prescribing of LABA/ICS increased significantly, with a concomitant decrease in prescribing of LABA+ICS. Use of OCS increased by 60%, with the lowest use in children prescribed only SABA and highest use in those prescribed LABA. Children prescribed LABA/ICS were significantly less likely than those prescribed LABA+ICS to require OCS rescue therapy and or >6 SABA inhalers a year (OR 1.6; 95% CI 1.1 to 2.2; p=0.04 and OR 1.7; 95% CI 1.1 to 2.5; p=0.005, respectively, for the years 2005-6).Conclusions: The results of this retrospective observational study suggest that children prescribed fixed-dose LABA-and-ICS combination devices achieve better asthma control, as reflected in reduced requirements for SABA and reduced courses of OCS than equivalent doses in separate devices. [ABSTRACT FROM AUTHOR]
Published: 2010
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15. Five year prognosis in patients with angina identified in primary care: incident cohort study.

Author: Buckley BS, Simpson CR, McLernon DJ, Murphy AW, and Hannaford PC
Published: 2009

16. Long-term trends in first hospitalization for heart failure and subsequent survival between 1986 and 2003: a population study of 5.1 million people.

Author: Jhund PS, Macintyre K, Simpson CR, Lewsey JD, Stewart S, Redpath A, Chalmers JW, Capewell S, and McMurray JJ
Published: 2009
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17. The effect of the UK incentive-based contract on the management of patients with coronary heart disease in primary care.

Author: McGovern MP, Boroujerdi MA, Taylor MW, Williams DJ, Hannaford PC, Lefevre KE, and Simpson CR
Abstract: Background. The new General Medical Services (nGMS) contract was introduced in April 2004 to improve care of chronic diseases such as coronary heart disease (CHD) and reduce differences in treatment between patient subgroups. Objective. To determine whether the recording of CHD-related health indicators and prescribing of medicines have increased following the introduction of the nGMS contract and whether differences in the treatment of patients of differing age, gender and deprivation have been affected. Methods. A serial cross-sectional study carried out with 310 general practices in Scotland. The subjects were patients with CHD as identified by their GP. Main outcome measures were the recording of CHD-related health indicators and prescribing of medicines at pre- and post-contract time points (covariates: gender, age, co-morbidity, deprivation and practice size). Results. The recording of CHD-related quality indicators and prescribing increased dramatically (mean absolute increase of 17.1%) after the introduction of the nGMS contract. Post-contract, disparities between patient subgroups, continued for certain components of care. Women were less likely to be recorded than men in 9 of 11 components of care, with older patients (7 of 11 components of care) and the most deprived (4 of 11 components of care) also less likely to have a record than the youngest and least deprived, respectively. Conclusion. The introduction of the new contract was associated with a dramatic rise in the recording of CHD-related quality indicators. However, not all the population benefited equally for certain aspects of care. [ABSTRACT FROM AUTHOR]
Published: 2008

18. Are different groups of patients with stroke more likely to be excluded from the new UK general medical services contract? A cross-sectional retrospective analysis of a large primary care population.

Author: Simpson CR, Hannaford PC, McGovern M, Taylor MW, Green PN, Lefevre K, and Williams DJ
Abstract: BACKGROUND: In April 2004, an incentive based contract was introduced to UK primary care. An important element of the new contract is the ability to exclude individuals from quality indicators for a variety of reasons (known as 'exception reporting'). Exception of patients with stroke or TIA from the recording and achievement of quality indicators may have important consequences in terms of stroke recurrence and mortality. METHODS: A cross-sectional retrospective analysis of anonymised patient data was performed using 312 Scottish primary care practices. RESULTS: Patients recorded as unsuitable for inclusion in the contract were more likely to be female (odds ratio (OR) 1.51, 95% confidence interval (CI) 1.36-1.68), older (>75 years:OR 3.15, 95%CI 2.69-3.69), and have dementia (OR 4.40, 95%CI 3.57-5.43) when compared to those patients without such a code. Patients were less likely to be older (>75 years:OR 0.70, 95%CI 0.56-0.87) and were more likely to be from the most deprived areas of Scotland (Quintile 5: OR 2.02, 95%CI 1.50-2.70) if they refused to attend for review or did not reply to letters asking for attendance at primary care clinics. Patients with multiple co-morbidities were more likely to have exclusions for achieving diagnostic clinical targets such as cholesterol control (3 or more co-morbidities: OR 3.37, 95%CI 2.50-4.50). CONCLUSION: Scottish practices have appeared to use exception reporting appropriately by excluding patients who are older or have dementia. However, younger or more socio-economically deprived patients were more likely to be recorded as having refused to attend for review or not replying to letters asking for attendance at primary care clinics. It is important for primary care practices to identify and monitor these individuals so that all patients fully benefit from the implementation of an incentive based contract and receive appropriate clinical care to prevent stroke recurrence, further disability and mortality. [ABSTRACT FROM AUTHOR]
Published: 2007

19. Effect of the UK incentive-based contract on the management of patients with stroke in primary care.

Author: Simpson CR, Hannaford PC, Lefevre K, Williams D, Simpson, Colin R, Hannaford, Philip C, Lefevre, Karen, and Williams, David
Published: 2006
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20. Evidence for age and sex differences in the secondary prevention of stroke in Scottish primary care.

Author: Simpson CR, Wilson C, Hannaford PC, Williams D, Simpson, C R, Wilson, C, Hannaford, P C, and Williams, D
Published: 2005
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21. Effectiveness of COVID-19 vaccines against hospitalisation, death and infection over time in Aotearoa New Zealand: a retrospective cohort study.

Author: Mbinta JF, Sporle AA, Sheppard J, Su'a-Tavila A, Nguyen BP, French N, and Simpson CR
Subjects: Humans, New Zealand epidemiology, Retrospective Studies, Male, Female, Middle Aged, Adult, Aged, Vaccine Efficacy, Immunization, Secondary, Young Adult, Proportional Hazards Models, COVID-19 prevention & control, COVID-19 mortality, COVID-19 epidemiology, COVID-19 Vaccines administration & dosage, Hospitalization statistics & numerical data, SARS-CoV-2 immunology
Abstract: Aims: This study aimed to evaluate the effectiveness of COVID-19 vaccines in preventing COVID-19 outcomes when the Omicron variant was predominant in Aotearoa New Zealand., Methods: We conducted a retrospective cohort study using routinely available data (8 December 2020-28 February 2023). We evaluated the vaccine effectiveness (VE) of COVID-19 vaccines using the Cox proportional-hazards model, adjusting for covariates., Results: The VE against COVID-19 hospitalisation (VEH) for the second booster dose compared to no vaccination was found to be 81.8% (95% confidence interval [95% CI]: 73.6-87.5) after 1 month post-vaccination. After 4 months, VEH was 72.2% (95% CI: 58.5-81.4), and after 6 months VEH was 49.0% (95% CI: 7.9-71.8). Similarly, VEH decreased after the first booster dose (1-month VEH=81.6% [95% CI: 75.6-86.1]; 2 months VEH=74.7% [95% CI: 68.2-79.9]; and 6 months VEH=57.4% [95% CI: 45.8-66.6]). VE against COVID-19 death (VED) was 92.9% (95% CI: 82.1-97.2) 2 months after the first booster vaccination, with VED being sustained until months 5 and 6 (VED=87.2%; 95% CI: 67.4-94.9). The VE after the second dose of the vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (VEI) (real-time polymerase chain reaction [RT-PCR]) was sustained at 5 months post-vaccination (40.6%; 95% CI: 25.6-52.5)., Conclusion: We provide a comprehensive quantification of both VE and VE waning. These findings can guide policymakers to help evaluate the COVID-19 vaccination programme and minimise the effect of future COVID-19 in Aotearoa New Zealand., Competing Interests: This work was supported by the Ministry of Health, Aotearoa New Zealand (reference: PROP–053). The sponsors of the study had no role in the design, data collection, data analysis, data interpretation or the writing of this report. There was no input to the methodology and results by any commercial entity. CR Simpson, AA Sporle, J Shephard, A Su’a-Tavila, BP Nguyen and N French report support for the present manuscript from the Ministry of Health (NZ). CR Simpson reports funding from MBIE (NZ), HRC (NZ), Ministry of Health (NZ), MRC (UK) and CSO (UK), leadership or fiduciary role in other board, society, committee or advocacy group, paid or unpaid with the New Zealand Government Data Ethics Advisory Group as the Chair, outside the submitted work. N French reports grants and consulting fees from MBIE (NZ), the Ministry for Primary Industries, the Ministry of Health (NZ), HRC (NZ), Te Niwha, UK Fleming Fund, Operational Solutions for Primary Industries, the Institute of Environmental Science and Research, and International Commission on Microbial Specifications for Foods, outside the submitted work. BP Nguyen reports grants from MBIE (NZ), and HRC (NZ), outside the submitted work. The remaining authors declare no competing interests., (© PMA.)
Published: 2024
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22. Cross-country assessment of the unique contributions of psychological factors to vaccination: Perspectives on the COVID-19 pandemic.

Author: Adu P, Popoola T, Iqbal N, Roemer A, Collings S, Aspin C, Medvedev ON, and Simpson CR
Abstract: We have identified the most relevant and significant psychological factors in relation to COVID-19 vaccination attitudes in Ghana, Germany, New Zealand and India. This study recruited 1822 participants from the general populations of India ( n = 411), New Zealand ( n = 413), Ghana ( n = 523) and Germany ( n = 475) to participate in a cross-sectional online survey. After controlling for the country of residence, individual psychological factors played a significant role in shaping attitudes towards COVID-19 vaccination. The results also revealed strong direct predictors that explained significant portions of the variance in the COVID-19 vaccination attitudes. Positive affect emerged as the strongest contributor in Ghana (7%), while self-compassion strongly influenced COVID-19 vaccination attitudes in India (66%). Dispositional optimism was the strongest predictor in New Zealand (5%). In Germany, compassion towards others was the strongest positive predictor (2%), while psychological distress had a strong negative impact (3%). Results highlight the importance of promoting emotional well-being to enhance vaccination coverage., Competing Interests: Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Published: 2024
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23. Risk of winter hospitalisation and death from acute respiratory infections in Scotland: national retrospective cohort study.

Author: Shi T, Millington T, Robertson C, Jeffrey K, Katikireddi SV, McCowan C, Simpson CR, Woolford L, Daines L, Kerr S, Swallow B, Fagbamigbe A, Vallejos CA, Weatherill D, Jayacodi S, Marsh K, McMenamin J, Rudan I, Ritchie LD, Mueller T, Kurdi A, and Sheikh A
Subjects: Humans, Scotland epidemiology, Retrospective Studies, Child, Male, Female, Adolescent, Child, Preschool, Adult, Aged, Risk Factors, Middle Aged, Young Adult, Aged, 80 and over, Acute Disease, Proportional Hazards Models, Infant, Respiratory Tract Infections epidemiology, Respiratory Tract Infections mortality, Hospitalization statistics & numerical data, Seasons
Abstract: Objectives: We undertook a national analysis to characterise and identify risk factors for acute respiratory infections (ARIs) resulting in hospitalisation during the winter period in Scotland., Design: A population-based retrospective cohort analysis., Setting: Scotland., Participants: The study involved 5.4 million residents in Scotland., Main Outcome Measures: Cox proportional hazard models were used to estimate adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for the association between risk factors and ARI hospitalisation., Results: Between 1 September 2022 and 31 January 2023, there were 22,284 (10.9% of 203,549 with any emergency hospitalisation) ARI hospitalisations (1759 in children and 20,525 in adults) in Scotland. Compared with the reference group of children aged 6-17 years, the risk of ARI hospitalisation was higher in children aged 3-5 years (aHR = 4.55; 95% CI: 4.11-5.04). Compared with those aged 25-29 years, the risk of ARI hospitalisation was highest among the oldest adults aged ≥80 years (aHR = 7.86; 95% CI: 7.06-8.76). Adults from more deprived areas (most deprived vs. least deprived, aHR = 1.64; 95% CI: 1.57-1.72), with existing health conditions (≥5 vs. 0 health conditions, aHR = 4.84; 95% CI: 4.53-5.18) or with history of all-cause emergency admissions (≥6 vs. 0 previous emergency admissions, aHR = 7.53; 95% CI: 5.48-10.35) were at a higher risk of ARI hospitalisations. The risk increased by the number of existing health conditions and previous emergency admission. Similar associations were seen in children., Conclusions: Younger children, older adults, those from more deprived backgrounds and individuals with greater numbers of pre-existing conditions and previous emergency admission were at increased risk for winter hospitalisations for ARI.
Published: 2024
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24. Association between antibody responses post-vaccination and severe COVID-19 outcomes in Scotland.

Author: Macdonald C, Palmateer N, McAuley A, Lindsay L, Hasan T, Hameed SS, Hall E, Jeffrey K, Grange Z, Gousias P, Mavin S, Jarvis L, Cameron JC, Daines L, Tibble H, Simpson CR, McCowan C, Katikireddi SV, Rudan I, Fagbamigbe AF, Ritchie L, Swallow B, Moss P, Robertson C, Sheikh A, and Murray J
Abstract: Several population-level studies have described individual clinical risk factors associated with suboptimal antibody responses following COVID-19 vaccination, but none have examined multimorbidity. Others have shown that suboptimal post-vaccination responses offer reduced protection to subsequent SARS-CoV-2 infection; however, the level of protection from COVID-19 hospitalisation/death remains unconfirmed. We use national Scottish datasets to investigate the association between multimorbidity and testing antibody-negative, examining the correlation between antibody levels and subsequent COVID-19 hospitalisation/death among double-vaccinated individuals. We found that individuals with multimorbidity ( ≥ five conditions) were more likely to test antibody-negative post-vaccination and 13.37 [6.05-29.53] times more likely to be hospitalised/die from COVID-19 than individuals without conditions. We also show a dose-dependent association between post-vaccination antibody levels and COVID-19 hospitalisation or death, with those with undetectable antibody levels at a significantly higher risk (HR 9.21 [95% CI 4.63-18.29]) of these serious outcomes compared to those with high antibody levels., (© 2024. The Author(s).)
Published: 2024
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25. Prevalence and risk factors for long COVID among adults in Scotland using electronic health records: a national, retrospective, observational cohort study.

Author: Jeffrey K, Woolford L, Maini R, Basetti S, Batchelor A, Weatherill D, White C, Hammersley V, Millington T, Macdonald C, Quint JK, Kerr R, Kerr S, Shah SA, Rudan I, Fagbamigbe AF, Simpson CR, Katikireddi SV, Robertson C, Ritchie L, Sheikh A, and Daines L
Abstract: Background: Long COVID is a debilitating multisystem condition. The objective of this study was to estimate the prevalence of long COVID in the adult population of Scotland, and to identify risk factors associated with its development., Methods: In this national, retrospective, observational cohort study, we analysed electronic health records (EHRs) for all adults (≥18 years) registered with a general medical practice and resident in Scotland between March 1, 2020, and October 26, 2022 (98-99% of the population). We linked data from primary care, secondary care, laboratory testing and prescribing. Four outcome measures were used to identify long COVID: clinical codes, free text in primary care records, free text on sick notes, and a novel operational definition. The operational definition was developed using Poisson regression to identify clinical encounters indicative of long COVID from a sample of negative and positive COVID-19 cases matched on time-varying propensity to test positive for SARS-CoV-2. Possible risk factors for long COVID were identified by stratifying descriptive statistics by long COVID status., Findings: Of 4,676,390 participants, 81,219 (1.7%) were identified as having long COVID. Clinical codes identified the fewest cases (n = 1,092, 0.02%), followed by free text (n = 8,368, 0.2%), sick notes (n = 14,469, 0.3%), and the operational definition (n = 64,193, 1.4%). There was limited overlap in cases identified by the measures; however, temporal trends and patient characteristics were consistent across measures. Compared with the general population, a higher proportion of people with long COVID were female (65.1% versus 50.4%), aged 38-67 (63.7% versus 48.9%), overweight or obese (45.7% versus 29.4%), had one or more comorbidities (52.7% versus 36.0%), were immunosuppressed (6.9% versus 3.2%), shielding (7.9% versus 3.4%), or hospitalised within 28 days of testing positive (8.8% versus 3.3%%), and had tested positive before Omicron became the dominant variant (44.9% versus 35.9%). The operational definition identified long COVID cases with combinations of clinical encounters (from four symptoms, six investigation types, and seven management strategies) recorded in EHRs within 4-26 weeks of a positive SARS-CoV-2 test. These combinations were significantly (p < 0.0001) more prevalent in positive COVID-19 patients than in matched negative controls. In a case-crossover analysis, 16.4% of those identified by the operational definition had similar healthcare patterns recorded before testing positive., Interpretation: The prevalence of long COVID presenting in general practice was estimated to be 0.02-1.7%, depending on the measure used. Due to challenges in diagnosing long COVID and inconsistent recording of information in EHRs, the true prevalence of long COVID is likely to be higher. The operational definition provided a novel approach but relied on a restricted set of symptoms and may misclassify individuals with pre-existing health conditions. Further research is needed to refine and validate this approach., Funding: Chief Scientist Office (Scotland), Medical Research Council, and BREATHE., Competing Interests: AS reports grants from HDRUK, NIHR, MRC, ICSF, and CSO during the conduct of the study; and being a Member of the Scottish Government's CMO COVID-19 Advisory Group and Standing Committee on Pandemics. CR reports support from PHS, CSO and MRC; and being a Member of SPI-M, Scottish Government Scientific Advisory Committee, MHRA Covid vaccine benefit and risk expert working group. CS reports grants from MBIE (New Zealand), Ministry of Health (New Zealand), and HRC (New Zealand). JKQ reports grants from MRC, HDR UK, GlaxoSmithKline, BI, Asthma + Lung UK, and AstraZeneca and consulting fees from GlaxoSmithKline, Evidera, AstraZeneca, Insmed. SVK reports grants from CSO and MRC. All other authors declare no competing interests., (© 2024 Published by Elsevier Ltd.)
Published: 2024
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26. Quality of ethnicity data within Scottish health records and implications of misclassification for ethnic inequalities in severe COVID-19: a national linked data study.

Author: Amele S, McCabe R, Kibuchi E, Pearce A, Hainey K, Demou E, Irizar P, Kapadia D, Taylor H, Nazroo J, Bécares L, Buchanan D, Henery P, Jayacodi S, Woolford L, Simpson CR, Sheikh A, Jeffrey K, Shi T, Daines L, Tibble H, Almaghrabi F, Fagbamigbe AF, Kurdi A, Robertson C, Pattaro S, and Katikireddi SV
Subjects: Humans, State Medicine, Semantic Web, Scotland epidemiology, Ethnicity, COVID-19
Abstract: Background: We compared the quality of ethnicity coding within the Public Health Scotland Ethnicity Look-up (PHS-EL) dataset, and other National Health Service datasets, with the 2011 Scottish Census., Methods: Measures of quality included the level of missingness and misclassification. We examined the impact of misclassification using Cox proportional hazards to compare the risk of severe coronavirus disease (COVID-19) (hospitalization & death) by ethnic group., Results: Misclassification within PHS-EL was higher for all minority ethnic groups [12.5 to 69.1%] compared with the White Scottish majority [5.1%] and highest in the White Gypsy/Traveller group [69.1%]. Missingness in PHS-EL was highest among the White Other British group [39%] and lowest among the Pakistani group [17%]. PHS-EL data often underestimated severe COVID-19 risk compared with Census data. e.g. in the White Gypsy/Traveller group the Hazard Ratio (HR) was 1.68 [95% Confidence Intervals (CI): 1.03, 2.74] compared with the White Scottish majority using Census ethnicity data and 0.73 [95% CI: 0.10, 5.15] using PHS-EL data; and HR was 2.03 [95% CI: 1.20, 3.44] in the Census for the Bangladeshi group versus 1.45 [95% CI: 0.75, 2.78] in PHS-EL., Conclusions: Poor quality ethnicity coding in health records can bias estimates, thereby threatening monitoring and understanding ethnic inequalities in health., (© The Author(s) 2023. Published by Oxford University Press on behalf of Faculty of Public Health.)
Published: 2024
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27. Caveats in reporting of national vaccine uptake.

Author: Millington T, Morrison K, Jeffrey K, Sullivan C, Kurdi A, Fagbamigbe AF, Swallow B, Shi T, Shah SA, Kerr S, Simpson CR, Ritchie LD, Robertson C, Sheikh A, and Rudan I
Subjects: Humans, Influenza Vaccines, Influenza, Human prevention & control
Abstract: Competing Interests: Disclosure of interest: The authors completed the ICMJE Disclosure of Interest Form (available upon request from the corresponding author) and disclose the following activities and/or relationships: AS and CR were members of the Scottish Government’s CMO COVID-19 Advisory Group and the NERVTAG’s risk stratification subgroup. CR is a member of SPI-M and MHRA vaccine Benefit and Risk Expert Working Group. AS was a member of AstraZeneca’s Thrombotic Thrombocytopenic Advisory Group and is a member of the Scottish Government’s Standing Committee on Pandemics. IR is the adviser to the Government of the Republic of Croatia for COVID-19. All these roles are unremunerated. IR is the co-Editor-in-Chief of the Journal of Global Health.
Published: 2024
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28. Critical success index or F measure to validate the accuracy of administrative healthcare data identifying epilepsy in deceased adults in Scotland.

Author: Mbizvo GK, Simpson CR, Duncan SE, Chin RFM, and Larner AJ
Subjects: Adult, Humans, Predictive Value of Tests, Delivery of Health Care, Algorithms, Scotland, Sensitivity and Specificity, Epilepsy diagnosis
Abstract: Background: Methods to undertake diagnostic accuracy studies of administrative epilepsy data are challenged by lack of a way to reliably rank case-ascertainment algorithms in order of their accuracy. This is because it is difficult to know how to prioritise positive predictive value (PPV) and sensitivity (Sens). Large numbers of true negative (TN) instances frequently found in epilepsy studies make it difficult to discriminate algorithm accuracy on the basis of negative predictive value (NPV) and specificity (Spec) as these become inflated (usually >90%). This study demonstrates the complementary value of using weather forecasting or machine learning metrics critical success index (CSI) or F measure, respectively, as unitary metrics combining PPV and sensitivity. We reanalyse data published in a diagnostic accuracy study of administrative epilepsy mortality data in Scotland., Method: CSI was calculated as 1/[(1/PPV) + (1/Sens) - 1]. F measure was calculated as 2.PPV.Sens/(PPV + Sens). CSI and F values range from 0 to 1, interpreted as 0 = inaccurate prediction and 1 = perfect accuracy. The published algorithms were reanalysed using these and their accuracy re-ranked according to CSI in order to allow comparison to the original rankings., Results: CSI scores were conservative (range 0.02-0.826), always less than or equal to the lower of the corresponding PPV (range 39-100%) and sensitivity (range 2-93%). F values were less conservative (range 0.039-0.905), sometimes higher than either PPV or sensitivity, but were always higher than CSI. Low CSI and F values occurred when there was a large difference between PPV and sensitivity, e.g. CSI was 0.02 and F was 0.039 in an instance when PPV was 100% and sensitivity was 2%. Algorithms with both high PPV and sensitivity performed best in terms of CSI and F measure, e.g. CSI was 0.826 and F was 0.905 in an instance when PPV was 90% and sensitivity was 91%., Conclusion: CSI or F measure can combine PPV and sensitivity values into a convenient single metric that is easier to interpret and rank in terms of diagnostic accuracy than trying to rank diagnostic accuracy according to the two measures themselves. CSI or F prioritise instances where both PPV and sensitivity are high over instances where there are large differences between PPV and sensitivity (even if one of these is very high), allowing diagnostic accuracy thresholds based on combined PPV and sensitivity to be determined. Therefore, CSI or F measures may be helpful complementary metrics to report alongside PPV and sensitivity in diagnostic accuracy studies of administrative epilepsy data., Competing Interests: Declarations of interest None of the authors have any conflict of interests to disclose., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)
Published: 2024
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29. External validation of the QCovid 2 and 3 risk prediction algorithms for risk of COVID-19 hospitalisation and mortality in adults: a national cohort study in Scotland.

Author: Kerr S, Millington T, Rudan I, McCowan C, Tibble H, Jeffrey K, Fagbamigbe AF, Simpson CR, Robertson C, Hippisley-Cox J, and Sheikh A
Subjects: Adult, Humans, Cohort Studies, Pandemics, Hospitalization, Scotland epidemiology, Algorithms, COVID-19 epidemiology
Abstract: Objective: The QCovid 2 and 3 algorithms are risk prediction tools developed during the second wave of the COVID-19 pandemic that can be used to predict the risk of COVID-19 hospitalisation and mortality, taking vaccination status into account. In this study, we assess their performance in Scotland., Methods: We used the Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 national data platform consisting of individual-level data for the population of Scotland (5.4 million residents). Primary care data were linked to reverse-transcription PCR virology testing, hospitalisation and mortality data. We assessed the discrimination and calibration of the QCovid 2 and 3 algorithms in predicting COVID-19 hospitalisations and deaths between 8 December 2020 and 15 June 2021., Results: Our validation dataset comprised 465 058 individuals, aged 19-100. We found the following performance metrics (95% CIs) for QCovid 2 and 3: Harrell's C 0.84 (0.82 to 0.86) for hospitalisation, and 0.92 (0.90 to 0.94) for death, observed-expected ratio of 0.24 for hospitalisation and 0.26 for death (ie, both the number of hospitalisations and the number of deaths were overestimated), and a Brier score of 0.0009 (0.00084 to 0.00096) for hospitalisation and 0.00036 (0.00032 to 0.0004) for death., Conclusions: We found good discrimination of the QCovid 2 and 3 algorithms in Scotland, although performance was worse in higher age groups. Both the number of hospitalisations and the number of deaths were overestimated., Competing Interests: Competing interests: JH-C reports grants from MRC, grants from Wellcome Trust, grants from NIHR, during the conduct of the study; JH-C is a founder and shareholder of ClinRisk and was its medical director until 31 May 2019. ClinRisk produces open and closed source software to implement clinical risk algorithms (outside this work) into clinical computer systems. JH-C was chair of the NERVTAG risk stratification subgroup and a member of SAGE COVID-19 groups and the NHS group advising on prioritisation of use of monoclonal antibodies in COVID-19 infection. AS reports grants from NIHR, grants from MRC, grants from HDR UK, during the conduct of the study. All other authors report no conflict of interest., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)
Published: 2023
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30. Long term effectiveness of live herpes zoster vaccine.

Author: Mbinta JF and Simpson CR
Subjects: Humans, Vaccines, Attenuated, Vaccination, Herpes Zoster Vaccine, Herpes Zoster prevention & control
Abstract: Competing Interests: Competing interests: The BMJ has judged that there are no disqualifying financial ties to commercial companies. The authors declare the following other interests: CRS reports research grants paid to his institution from UK Research and Innovation, the UK Medical Research Council, the UK National Institute for Health Research, the New Zealand Ministry of Business, Innovation and Employment, the Health Research Council of New Zealand, the New Zealand Ministry of Health, and the UK Chief Scientist Office, all outside of the submitted work. CRS also reports a leadership or fiduciary role in other boards, societies, committees, or advocacy groups, paid or unpaid, with the New Zealand Government Chief Data Steward’s Data Ethics Advisory Group. JM reports none. Further details of The BMJ policy on financial interests is here: https://www.bmj.com/sites/default/files/attachments/resources/2016/03/16-current-bmj-education-coi-form.pdf.
Published: 2023
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31. Developing the EAVE III platform for future health crises.

Author: Simpson CR, Robertson C, McMenamin J, Ritchie LD, and Sheikh A
Subjects: Animals, Humans, Anopheles, Insecticides
Abstract: Competing Interests: CRS reports research grants paid to his institution to support the present manuscript from UK Research and Innovation, the UK Medical Research Council, and the UK National Institute for Health Research and reports research grants paid to his institution from the New Zealand Ministry of Business, Innovation and Employment, the Health Research Council of New Zealand, the New Zealand Ministry of Health, and the UK Chief Scientist Office, all outside the submitted work. CRS also reports a leadership or fiduciary role in other boards, societies, committees, or advocacy groups, paid or unpaid, with the New Zealand Government Chief Data Steward's Data Ethics Advisory Group. CR reports research grants paid to his institution to support the present manuscript from PHS, the UK Medical Research Council, and the Chief Scientist Office Scotland and a leadership or fiduciary role in other boards, societies, committees, or advocacy groups, paid or unpaid, with the Scientific Pandemic Infections Group on Modelling, the Scottish Government Scientific Advisory Committee, the Medicines and Healthcare Products Regulatory Agency COVID Vaccine Benefit and Risk Expert Working Group, and the International Breast Cancer Study Group Data Safety Monitoring Group. JMM reports research grants paid to his institution from the UK Medical Research Council, outside the submitted work, and a leadership or fiduciary role in other boards, societies, committees, or advocacy groups, paid or unpaid, with the Scottish Government Chief Medical Officer's COVID-19 Advisory Group, the New and Emerging Respiratory Virus Threats Advisory Group, and the Scientific Advisory Group for Emergencies (observer). LDR reports a leadership or fiduciary role in boards, societies, committees, or advocacy groups, paid or unpaid, with the Scottish Government as a part-time medical advisor (seconded from University of Aberdeen). AS reports research grants paid to his institution from UK Research and Innovation and the UK National Institute for Health Research, outside the submitted work; participation on a Data Safety Monitoring Board or Advisory Board with AstraZeneca, outside the submitted work; and a leadership or fiduciary role in other boards, societies, committees, or advocacy groups, paid or unpaid, with the UK and Scottish Government COVID-19 advisory groups and the Scottish Standing Committee on Pandemic Preparedness.
Published: 2023
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32. Ethnic inequalities in positive SARS-CoV-2 tests, infection prognosis, COVID-19 hospitalisations and deaths: analysis of 2 years of a record linked national cohort study in Scotland.

Author: Amele S, Kibuchi E, McCabe R, Pearce A, Henery P, Hainey K, Fagbamigbe AF, Kurdi A, McCowan C, Simpson CR, Dibben C, Buchanan D, Demou E, Almaghrabi F, Anghelescu G, Taylor H, Tibble H, Rudan I, Nazroo J, Bécares L, Daines L, Irizar P, Jayacodi S, Pattaro S, Sheikh A, and Katikireddi SV
Subjects: Humans, Cohort Studies, SARS-CoV-2, Minority Groups, Hospitalization, Scotland epidemiology, Prognosis, Ethnicity, COVID-19 diagnosis
Abstract: Background: This study aims to estimate ethnic inequalities in risk for positive SARS-CoV-2 tests, COVID-19 hospitalisations and deaths over time in Scotland., Methods: We conducted a population-based cohort study where the 2011 Scottish Census was linked to health records. We included all individuals ≥ 16 years living in Scotland on 1 March 2020. The study period was from 1 March 2020 to 17 April 2022. Self-reported ethnic group was taken from the census and Cox proportional hazard models estimated HRs for positive SARS-CoV-2 tests, hospitalisations and deaths, adjusted for age, sex and health board. We also conducted separate analyses for each of the four waves of COVID-19 to assess changes in risk over time., Findings: Of the 4 358 339 individuals analysed, 1 093 234 positive SARS-CoV-2 tests, 37 437 hospitalisations and 14 158 deaths occurred. The risk of COVID-19 hospitalisation or death among ethnic minority groups was often higher for White Gypsy/Traveller (HR 2.21, 95% CI (1.61 to 3.06)) and Pakistani 2.09 (1.90 to 2.29) groups compared with the white Scottish group. The risk of COVID-19 hospitalisation or death following confirmed positive SARS-CoV-2 test was particularly higher for White Gypsy/Traveller 2.55 (1.81-3.58), Pakistani 1.75 (1.59-1.73) and African 1.61 (1.28-2.03) individuals relative to white Scottish individuals. However, the risk of COVID-19-related death following hospitalisation did not differ. The risk of COVID-19 outcomes for ethnic minority groups was higher in the first three waves compared with the fourth wave., Interpretation: Most ethnic minority groups were at increased risk of adverse COVID-19 outcomes in Scotland, especially White Gypsy/Traveller and Pakistani groups. Ethnic inequalities persisted following community infection but not following hospitalisation, suggesting differences in hospital treatment did not substantially contribute to ethnic inequalities., Competing Interests: Competing interests: SVK was cochair of the Scottish Government’s Expert Reference Group on Ethnicity and COVID-19 and a member of the Scientific Advisory Group on Emergencies subgroup on ethnicity., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)
Published: 2023
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33. Understanding and reporting odds ratios as rate-ratio estimates in case-control studies.

Author: Kerr S, Greenland S, Jeffrey K, Millington T, Bedston S, Ritchie L, Simpson CR, Fagbamigbe AF, Kurdi A, Robertson C, Sheikh A, and Rudan I
Subjects: Humans, Case-Control Studies, Odds Ratio, Research Personnel
Abstract: Background: We noted that there remains some confusion in the health-science literature on reporting sample odds ratios as estimated rate ratios in case-control studies., Methods: We recap historical literature that definitively answered the question of when sample odds ratios (ORs) from a case-control study are consistent estimators for population rate ratios. We use numerical examples to illustrate the magnitude of the disparity between sample ORs in a case-control study and population rate ratios when sufficient conditions for them to be equal are not satisfied., Results: We stress that in a case-control study, sampling controls from those still at risk at the time of outcome event of the index case is not sufficient for a sample OR to be a consistent estimator for an intelligible rate ratio. In such studies, constancy of the exposure prevalence together with constancy of the hazard ratio (HR) (i.e., the instantaneous rate ratio) over time is sufficient for this result if sampling time is not controlled; if time is controlled, constancy of the HR will suffice. We present numerical examples to illustrate how failure to satisfy these conditions adds a small systematic error to sample ORs as estimates of population rate ratios., Conclusions: We recommend that researchers understand and critically evaluate all conditions used to interpret their estimates as consistent for a population parameter in case-control studies., Competing Interests: Disclosure of interest: The authors completed the ICMJE Disclosure of Interest Form (available upon request from the corresponding author) and declare the following activities and relationships: AS and CR are members of the Scottish Government’s CMO COVID-19 Advisory Group. IR is a member of the Croatian Government’s Scientific Committee on COVID-19 and co-Editor-in-Chief of the Journal of Global Health. AS and CR are members of NERVTAG’s risk stratification subgroup. CR is a member of SPI-M. AS is a member of AstraZeneca’s Thrombotic Thrombocytopenic Advisory Group and the Scottish Government’s Standing Committee on Pandemics. All roles are unremunerated. All other co-authors report no conflict of interests., (Copyright © 2023 by the Journal of Global Health. All rights reserved.)
Published: 2023
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34. Predictors of incomplete COVID-19 vaccine schedule among adults in Scotland: Two retrospective cohort analyses of the primary schedule and third dose.

Author: Morrison K, Cullen L, James AB, Chua V, Sullivan C, Robertson C, Carruthers J, Wood R, Jeffrey K, MacDonald C, Shah SA, Rudan I, Simpson CR, McCowan C, Vittal Katikireddi S, Grange Z, Ritchie L, and Sheikh A
Subjects: Female, Pregnancy, Adult, Humans, Adolescent, Retrospective Studies, SARS-CoV-2, Scotland epidemiology, COVID-19 Vaccines, COVID-19 epidemiology, COVID-19 prevention & control
Abstract: Background: Vaccination continues to be the key public health measure for preventing severe COVID-19 outcomes. Certain groups may be at higher risk of incomplete vaccine schedule, which may leave them vulnerable to COVID-19 hospitalisation and death., Aim: To identify the sociodemographic and clinical predictors for not receiving a scheduled COVID-19 vaccine after previously receiving one., Methods: We conducted two retrospective cohort studies with ≥3.7 million adults aged ≥18 years in Scotland. Multivariable logistic regression was used to estimate adjusted odds ratios (aOR) of not receiving a second, and separately a third dose between December 2020 and May 2022. Independent variables included sociodemographic and clinical factors., Results: Of 3,826,797 people in the study population who received one dose, 3,732,596 (97.5%) received two doses, and 3,263,153 (86.5%) received all doses available during the study period. The most strongly associated predictors for not receiving the second dose were: being aged 18-29 (reference: 50-59 years; aOR:4.26; 95% confidence interval (CI):4.14-4.37); hospitalisation due to a potential vaccine related adverse event of special interest (AESI) (reference: not having a potential AESI, aOR:3.78; 95%CI: 3.29-4.35); and living in the most deprived quintile (reference: least deprived quintile, aOR:3.24; 95%CI: 3.16-3.32). The most strongly associated predictors for not receiving the third dose were: being 18-29 (reference: 50-59 years aOR:4.44; 95%CI: 4.38-4.49), living in the most deprived quintile (reference: least deprived quintile aOR:2.56; 95%CI: 2.53-2.59), and Black, Caribbean, or African ethnicity (reference: White ethnicity aOR:2.38; 95%CI: 2.30-2.46). Pregnancy, previous vaccination with mRNA-1273, smoking history, individual and household severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positivity, and having an unvaccinated adult in the household were also associated with incomplete vaccine schedule., Conclusion: We observed several risk factors that predict incomplete COVID-19 vaccination schedule. Vaccination programmes must take immediate action to ensure maximum uptake, particularly for populations vulnerable to severe COVID-19 outcomes., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)
Published: 2023
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35. Neonatal and maternal outcomes following SARS-CoV-2 infection and COVID-19 vaccination: a population-based matched cohort study.

Author: Lindsay L, Calvert C, Shi T, Carruthers J, Denny C, Donaghy J, Hopcroft LEM, Hopkins L, Goulding A, McLaughlin T, Moore E, Taylor B, Bhaskaran K, Katikireddi SV, McCabe R, McCowan C, Simpson CR, Robertson C, Sheikh A, Wood R, and Stock SJ
Subjects: Adult, Female, Humans, Infant, Newborn, Pregnancy, Cohort Studies, COVID-19 pathology, COVID-19 Vaccines adverse effects, Pregnancy Complications, Infectious pathology, Pregnancy Outcome
Abstract: Understanding the impact of SARS-CoV-2 infection and COVID-19 vaccination in pregnancy on neonatal and maternal outcomes informs clinical decision-making. Here we report a national, population-based, matched cohort study to investigate associations between SARS-CoV-2 infection and, separately, COVID-19 vaccination just before or during pregnancy and the risk of adverse neonatal and maternal outcomes among women in Scotland with a singleton pregnancy ending at ≥20 weeks gestation. Neonatal outcomes are stillbirth, neonatal death, extended perinatal mortality, preterm birth (overall, spontaneous, and provider-initiated), small-for-gestational age, and low Apgar score. Maternal outcomes are admission to critical care or death, venous thromboembolism, hypertensive disorders of pregnancy, and pregnancy-related bleeding. We use conditional logistic regression to derive odds ratios adjusted for socio-demographic and clinical characteristics (aORs). We find that infection is associated with an increased risk of preterm (aOR=1.36, 95% Confidence Interval [CI] = 1.16-1.59) and very preterm birth (aOR = 1.90, 95% CI 1.20-3.02), maternal admission to critical care or death (aOR=1.72, 95% CI = 1.39-2.12), and venous thromboembolism (aOR = 2.53, 95% CI = 1.47-4.35). We find no evidence of increased risk for any of our outcomes following vaccination. These data suggest SARS-CoV-2 infection during pregnancy is associated with adverse neonatal and maternal outcomes, and COVID-19 vaccination remains a safe way for pregnant women to protect themselves and their babies against infection., (© 2023. Springer Nature Limited.)
Published: 2023
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36. Herpes zoster vaccine safety in the Aotearoa New Zealand population: a self-controlled case series study.

Author: Mbinta JF, Wang AX, Nguyen BP, Paynter J, Awuni PMA, Pine R, Sporle AA, Bowe S, and Simpson CR
Subjects: Adult, Humans, New Zealand epidemiology, Research Design, Herpes Zoster Vaccine adverse effects, Herpes Zoster epidemiology, Herpes Zoster prevention & control, Stroke drug therapy
Abstract: In Aotearoa New Zealand, zoster vaccine live is used for the prevention of zoster and associated complications in adults. This study assessed the risk of pre-specified serious adverse events following zoster vaccine live immunisation among adults in routine clinical practice. We conducted a self-controlled case series study using routinely collected national data. We compared the incidence of serious adverse events during the at-risk period with the control period. Rate ratios were estimated using Conditional Poisson regression models. Falsification outcomes analyses were used to evaluate biases in our study population. From April 2018 to July 2021, 278,375 received the vaccine. The rate ratio of serious adverse events following immunisation was 0·43 (95% confidence interval [CI]: 0·37-0·50). There was no significant increase in the risk of cerebrovascular accidents, acute myocardial infarction, acute pericarditis, acute myocarditis, and Ramsay-Hunt Syndrome. The herpes zoster vaccine is safe in adults in Aotearoa New Zealand., (© 2023. The Author(s).)
Published: 2023
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37. Confirmed SARS-CoV-2 infection in Scottish neonates 2020-2022: a national, population-based cohort study.

Author: Goulding A, McQuaid F, Lindsay L, Agrawal U, Auyeung B, Calvert C, Carruthers J, Denny C, Donaghy J, Hillman S, Hopcroft L, Hopkins L, McCowan C, McLaughlin T, Moore E, Ritchie L, Simpson CR, Taylor B, Fenton L, Pollock L, Gale C, Kurinczuk JJ, Robertson C, Sheikh A, Stock S, and Wood R
Subjects: Pregnancy, Infant, Newborn, Infant, Child, Humans, Female, SARS-CoV-2, Cohort Studies, Scotland epidemiology, Pregnancy Outcome epidemiology, COVID-19 diagnosis, COVID-19 epidemiology, Pregnancy Complications, Infectious epidemiology, Pregnancy Complications, Infectious diagnosis
Abstract: Objectives: To examine neonates in Scotland aged 0-27 days with SARS-CoV-2 infection confirmed by viral testing; the risk of confirmed neonatal infection by maternal and infant characteristics; and hospital admissions associated with confirmed neonatal infections., Design: Population-based cohort study., Setting and Population: All live births in Scotland, 1 March 2020-31 January 2022., Results: There were 141 neonates with confirmed SARS-CoV-2 infection over the study period, giving an overall infection rate of 153 per 100 000 live births (141/92 009, 0.15%). Among infants born to women with confirmed infection around the time of birth, the confirmed neonatal infection rate was 1812 per 100 000 live births (15/828, 1.8%). Two-thirds (92/141, 65.2%) of neonates with confirmed infection had an associated admission to neonatal or (more commonly) paediatric care. Six of these babies (6/92, 6.5%) were admitted to neonatal and/or paediatric intensive care; however, none of these six had COVID-19 recorded as their main diagnosis. There were no neonatal deaths among babies with confirmed infection., Implications and Relevance: Confirmed neonatal SARS-CoV-2 infection was uncommon over the first 23 months of the pandemic in Scotland. Secular trends in the neonatal confirmed infection rate broadly followed those seen in the general population, although at a lower level. Maternal confirmed infection at birth was associated with an increased risk of neonatal confirmed infection. Two-thirds of neonates with confirmed infection had an associated admission to hospital, with resulting implications for the baby, family and services, although their outcomes were generally good. Ascertainment of confirmed infection depends on the extent of testing, and this is likely to have varied over time and between groups: the extent of unconfirmed infection is inevitably unknown., Competing Interests: Competing interests: CG and JJK are lead investigators for the British Paediatric Surveillance Unit study 'Neonatal complications of COVID-19' and coinvestigators for the 'SARS-CoV-2 infection in neonates or in pregnancy: outcomes at 18 months (SINEPOST)' study., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)
Published: 2023
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38. Case-control study developing Scottish Epilepsy Deaths Study Score to predict epilepsy-related death.

Author: Mbizvo GK, Schnier C, Simpson CR, Duncan SE, and Chin RFM
Subjects: Adult, Humans, Male, Middle Aged, Case-Control Studies, Risk Factors, Scotland epidemiology, Epilepsy, Epilepsy, Generalized
Abstract: This study aimed to develop a risk prediction model for epilepsy-related death in adults. In this age- and sex-matched case-control study, we compared adults (aged ≥16 years) who had epilepsy-related death between 2009 and 2016 to living adults with epilepsy in Scotland. Cases were identified from validated administrative national datasets linked to mortality records. ICD-10 cause-of-death coding was used to define epilepsy-related death. Controls were recruited from a research database and epilepsy clinics. Clinical data from medical records were abstracted and used to undertake univariable and multivariable conditional logistic regression to develop a risk prediction model consisting of four variables chosen a priori. A weighted sum of the factors present was taken to create a risk index-the Scottish Epilepsy Deaths Study Score. Odds ratios were estimated with 95% confidence intervals (CIs). Here, 224 deceased cases (mean age 48 years, 114 male) and 224 matched living controls were compared. In univariable analysis, predictors of epilepsy-related death were recent epilepsy-related accident and emergency attendance (odds ratio 5.1, 95% CI 3.2-8.3), living in deprived areas (odds ratio 2.5, 95% CI 1.6-4.0), developmental epilepsy (odds ratio 3.1, 95% CI 1.7-5.7), raised Charlson Comorbidity Index score (odds ratio 2.5, 95% CI 1.2-5.2), alcohol abuse (odds ratio 4.4, 95% CI 2.2-9.2), absent recent neurology review (odds ratio 3.8, 95% CI 2.4-6.1) and generalized epilepsy (odds ratio 1.9, 95% CI 1.2-3.0). Scottish Epilepsy Deaths Study Score model variables were derived from the first four listed before, with Charlson Comorbidity Index ≥2 given 1 point, living in the two most deprived areas given 2 points, having an inherited or congenital aetiology or risk factor for developing epilepsy given 2 points and recent epilepsy-related accident and emergency attendance given 3 points. Compared to having a Scottish Epilepsy Deaths Study Score of 0, those with a Scottish Epilepsy Deaths Study Score of 1 remained low risk, with odds ratio 1.6 (95% CI 0.5-4.8). Those with a Scottish Epilepsy Deaths Study Score of 2-3 had moderate risk, with odds ratio 2.8 (95% CI 1.3-6.2). Those with a Scottish Epilepsy Deaths Study Score of 4-5 and 6-8 were high risk, with odds ratio 14.4 (95% CI 5.9-35.2) and 24.0 (95% CI 8.1-71.2), respectively. The Scottish Epilepsy Deaths Study Score may be a helpful tool for identifying adults at high risk of epilepsy-related death and requires external validation., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)
Published: 2023
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39. Using Critical Success Index or Gilbert Skill Score as composite measures of positive predictive value and sensitivity in diagnostic accuracy studies: Weather forecasting informing epilepsy research.

Author: Mbizvo GK, Bennett KH, Simpson CR, Duncan SE, Chin RFM, and Larner AJ
Subjects: Humans, Predictive Value of Tests, Forecasting, Weather, Sensitivity and Specificity, Epilepsy diagnosis
Abstract: The Critical Success Index (CSI) and Gilbert Skill score (GS) are verification measures that are commonly used to check the accuracy of weather forecasting. In this article, we propose that they can also be used to simplify the joint interpretation of positive predictive value (PPV) and sensitivity estimates across diagnostic accuracy studies of epilepsy data. This is because CSI and GS each provide a single measure that takes the weather forecasting equivalent of PPV and sensitivity into account. We have re-analysed data from our recent systematic review of diagnostic accuracy studies of administrative epilepsy data using CSI and GS. We summarise the results and benefits of this approach., (© 2023 International League Against Epilepsy.)
Published: 2023
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40. Simple Technique for Microscopic Evaluation of Active Cellular Invasion into 3D Hydrogel Constructs.

Author: Simpson CR, Cavanagh BL, Kelly HM, and Murphy CM
Subjects: Cell Culture Techniques methods, Cell Differentiation, Hydrogels, Tissue Engineering methods
Abstract: Materials that are evaluated for bioengineering purposes are carefully tested to evaluate cellular interactions with respect to biocompatibility and in some cases cell differentiation. A key perspective that is often considered is the ability for decellularized synthetic or natural based matrices to facilitate cell migration or tissue ingrowth. Current methods of measuring cell migration range from simple scratch assays to Boyden chamber inserts and fluorescent imaging of seeded spheroids. Many of these methods require tissue processing for histological analysis and fixing and staining for imaging, which can be difficult and dependent on the stability of the hydrogel subject. Herein we present a simple platform that can be manufactured using 3D printing and easily applied to in vitro cell culture, allowing the researcher to image live cellular migration into a cellular materials. We found this to be an adaptable, cheap, and replicable technique to evaluate cellular interaction that has applications in the research and development of hydrogels for tissue engineering purposes.
Published: 2023
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41. Implications for COVID-19 vaccine uptake: A systematic review.

Author: Adu P, Poopola T, Medvedev ON, Collings S, Mbinta J, Aspin C, and Simpson CR
Subjects: Humans, COVID-19 Vaccines, Vaccination, Vaccination Coverage, China, COVID-19 prevention & control, Vaccines
Abstract: Background: Globally, increasing coronavirus disease (COVID-19) vaccination coverage remains a major public health concern in the face of high rates of COVID-19 hesitancy among the general population. We must understand the impact of the determinants of COVID-19 vaccine uptake when designing national vaccination programmes. We aimed to synthesise nationwide evidence regarding COVID-19 infodemics and the demographic, psychological, and social predictors of COVID-19 vaccination uptake., Methods: We systematically searched seven databases between July 2021 and March 2022 to retrieve relevant articles published since COVID-19 was first reported on 31 December 2019 in Wuhan, China. Of the 12,502 peer-reviewed articles retrieved from the databases, 57 met the selection criteria and were included in this systematic review. We explored COVID-19 vaccine uptake determinants before and after the first COVID-19 vaccine roll-out by the Food and Drug Authority (FDA)., Results: Increased COVID-19 vaccine uptake rates were associated with decreased hesitancy. Concerns about COVID-19 vaccine safety, negative side effects, rapid development of the COVID-19 vaccine, and uncertainty about vaccine effectiveness were associated with reluctance to be vaccinated. After the US FDA approval of COVID-19 vaccines, phobia of medical procedures such as vaccine injection and inadequate information about vaccines were the main determinants of COVID-19 vaccine hesitancy., Conclusion: Addressing effectiveness and safety concerns regarding COVID-19 vaccines, as well as providing adequate information about vaccines and the impacts of pandemics, should be considered before implementation of any vaccination programme. Reassuring people about the safety of medical vaccination and using alternative procedures such as needle-free vaccination may help further increase vaccination uptake., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)
Published: 2023
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42. Dynamics of cooperative networks associated with gender among South Indian Tamils.

Author: Simpson CR and Power EA
Subjects: Male, Adult, Animals, Humans, Female, India, Sex Factors, Social Networking, Helping Behavior
Abstract: Helping behaviour is thought to play a major role in the evolution of group-living animals. Yet, it is unclear to what extent human males and human females use the same strategies to secure support. Accordingly, we investigate help-seeking over a 5-year period in relation to gender using data from virtually all adults in two Tamil villages ( N = 782). Simulations of network dynamics (i.e. stochastic actor-oriented models) calibrated to these data broadly indicate that women are more inclined than men to create and maintain supportive bonds via multiple mechanisms of cooperation (e.g. reciprocity, kin bias, friend bias, generalized exchange). However, gender-related differences in the simulated dynamics of help-seeking are modest, vary based on structural position (e.g. out-degree), and do not appear to translate to divergence in the observed structure of respondents' egocentric networks. Findings ultimately suggest that men and women in the two villages are similarly social but channel their sociality differently. This article is part of the theme issue 'Cooperation among women: evolutionary and cross-cultural perspectives'.
Published: 2023
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43. A population-based matched cohort study of major congenital anomalies following COVID-19 vaccination and SARS-CoV-2 infection.

Author: Calvert C, Carruthers J, Denny C, Donaghy J, Hopcroft LEM, Hopkins L, Goulding A, Lindsay L, McLaughlin T, Moore E, Taylor B, Loane M, Dolk H, Morris J, Auyeung B, Bhaskaran K, Gibbons CL, Katikireddi SV, O'Leary M, McAllister D, Shi T, Simpson CR, Robertson C, Sheikh A, Stock SJ, and Wood R
Subjects: Female, Humans, Pregnancy, BNT162 Vaccine, Cohort Studies, SARS-CoV-2 genetics, Vaccination adverse effects, COVID-19 epidemiology, COVID-19 prevention & control, COVID-19 Vaccines adverse effects
Abstract: Evidence on associations between COVID-19 vaccination or SARS-CoV-2 infection and the risk of congenital anomalies is limited. Here we report a national, population-based, matched cohort study using linked electronic health records from Scotland (May 2020-April 2022) to estimate the association between COVID-19 vaccination and, separately, SARS-CoV-2 infection between six weeks pre-conception and 19 weeks and six days gestation and the risk of [1] any major congenital anomaly and [2] any non-genetic major congenital anomaly. Mothers vaccinated in this pregnancy exposure period mostly received an mRNA vaccine (73.7% Pfizer-BioNTech BNT162b2 and 7.9% Moderna mRNA-1273). Of the 6731 babies whose mothers were vaccinated in the pregnancy exposure period, 153 had any anomaly and 120 had a non-genetic anomaly. Primary analyses find no association between any vaccination and any anomaly (adjusted Odds Ratio [aOR] = 1.01, 95% Confidence Interval [CI] = 0.83-1.24) or non-genetic anomalies (aOR = 1.00, 95% CI = 0.81-1.22). Primary analyses also find no association between SARS-CoV-2 infection and any anomaly (aOR = 1.02, 95% CI = 0.66-1.60) or non-genetic anomalies (aOR = 0.94, 95% CI = 0.57-1.54). Findings are robust to sensitivity analyses. These data provide reassurance on the safety of vaccination, in particular mRNA vaccines, just before or in early pregnancy., (© 2023. The Author(s).)
Published: 2023
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44. Is Police Misconduct Contagious? Non-trivial Null Findings from Dallas, Texas.

Author: Simpson CR and Kirk DS
Abstract: Objectives: Understanding if police malfeasance might be "contagious" is vital to identifying efficacious paths to police reform. Accordingly, we investigate whether an officer's propensity to engage in misconduct is associated with her direct, routine interaction with colleagues who have themselves engaged in misbehavior in the past., Methods: Recognizing the importance of analyzing the actual social networks spanning a police force, we use data on collaborative responses to 1,165,136 "911" calls for service by 3475 Dallas Police Department (DPD) officers across 2013 and 2014 to construct daily networks of front-line interaction. And we relate these cooperative networks to reported and formally sanctioned misconduct on the part of the DPD officers during the same time period using repeated-events survival models., Results: Estimates indicate that the risk of a DPD officer engaging in misconduct is not associated with the disciplined misbehavior of her ad hoc, on-the-scene partners. Rather, a greater risk of misconduct is associated with past misbehavior, officer-specific proneness, the neighborhood context of patrol, and, in some cases, officer race, while departmental tenure is a mitigating factor., Conclusions: Our observational findings-based on data from one large police department in the United States-ultimately suggest that actor-based and ecological explanations of police deviance should not be summarily dismissed in favor of accounts emphasizing negative socialization, where our study design also raises the possibility that results are partly driven by unobserved trait-based variation in the situations that officers find themselves in. All in all, interventions focused on individual officers, including the termination of deviant police, may be fruitful for curtailing police misconduct-where early interventions focused on new offenders may be key to avoiding the escalation of deviance., (© The Author(s) 2022.)
Published: 2023
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45. Pregnancy outcomes after SARS-CoV-2 infection in periods dominated by delta and omicron variants in Scotland: a population-based cohort study.

Author: Stock SJ, Moore E, Calvert C, Carruthers J, Denny C, Donaghy J, Hillman S, Hopcroft LEM, Hopkins L, Goulding A, Lindsay L, McLaughlin T, Taylor B, Auyeung B, Katikireddi SV, McCowan C, Ritchie LD, Rudan I, Simpson CR, Robertson C, Sheikh A, and Wood R
Subjects: Infant, Newborn, Pregnancy, Female, Humans, SARS-CoV-2, Pregnancy Outcome epidemiology, Cohort Studies, Stillbirth epidemiology, COVID-19 Vaccines, COVID-19, Premature Birth epidemiology, Pregnancy Complications, Infectious epidemiology
Abstract: Background: Evidence suggests that the SARS-CoV-2 omicron (B.1·1.529) is associated with lower risks of adverse outcomes than the delta (B.1.617.2) variant among the general population. However, little is known about outcomes after omicron infection in pregnancy. We aimed to assess and compare short-term pregnancy outcomes after SARS-CoV-2 delta and omicron infection in pregnancy., Methods: We did a national population-based cohort study of women who had SARS-CoV-2 infection in pregnancy between May 17, 2021, and Jan 31, 2022. The primary maternal outcome was admission to critical care within 21 days of infection or death within 28 days of date of infection. Pregnancy outcomes were preterm birth and stillbirth within 28 days of infection. Neonatal outcomes were death within 28 days of birth, and low Apgar score (<7 of 10, for babies born at term) or neonatal SARS-CoV-2 infection in births occurring within 28 days of maternal infection. We used periods when variants were dominant in the general Scottish population, based on 50% or more of cases being S-gene positive (delta variant, from May 17 to Dec 14, 2021) or S-gene negative (omicron variant, from Dec 15, 2021, to Jan 31, 2022) as surrogates for variant infections. Analyses used logistic regression, adjusting for maternal age, deprivation quintile, ethnicity, weeks of gestation, and vaccination status. Sensitivity analyses included restricting the analysis to those with first confirmed SARS-CoV-2 infection and using periods when delta or omicron had 90% or more predominance., Findings: Between May 17, 2021, and Jan 31, 2022, there were 9923 SARS-CoV-2 infections in 9823 pregnancies, in 9817 women in Scotland. Compared with infections in the delta-dominant period, SARS-CoV-2 infections in pregnancy in the omicron-dominant period were associated with lower maternal critical care admission risk (0·3% [13 of 4968] vs 1·8% [89 of 4955]; adjusted odds ratio 0·25, 95% CI 0·14-0·44) and lower preterm birth within 28 days of infection (1·8% [37 of 2048] vs 4·2% [98 of 2338]; 0·57, 95% CI 0·38-0·87). There were no maternal deaths within 28 days of infection. Estimates of low Apgar scores were imprecise due to low numbers (5 [1·2%] of 423 with omicron vs 11 [2·1%] of 528 with delta, adjusted odds ratio 0·72, 0·23-2·32). There were fewer stillbirths in the omicron-dominant period than in the delta-dominant period (4·3 [2 of 462] per 1000 births vs 20·3 [13 of 639] per 1000) and no neonatal deaths during the omicron-dominant period (0 [0 of 460] per 1000 births vs 6·3 [4 of 626] per 1000 births), thus numbers were too small to support adjusted analyses. Rates of neonatal infection were low in births within 28 days of maternal SARS-CoV-2 infection, with 11 cases of neonatal SARS-CoV-2 in the delta-dominant period, and 1 case in the omicron-dominant period. Of the 15 stillbirths, 12 occurred in women who had not received two or more doses of COVID-19 vaccination at the time of SARS-CoV-2 infection in pregnancy. All 12 cases of neonatal SARS-CoV-2 infection occurred in women who had not received two or more doses of vaccine at the time of maternal infection. Findings in sensitivity analyses were similar to those in the main analyses., Interpretation: Pregnant women infected with SARS-CoV-2 were substantially less likely to have a preterm birth or maternal critical care admission during the omicron-dominant period than during the delta-dominant period., Funding: Wellcome Trust, Tommy's charity, Medical Research Council, UK Research and Innovation, Health Data Research UK, National Core Studies-Data and Connectivity, Public Health Scotland, Scottish Government Health and Social Care, Scottish Government Chief Scientist Office, National Research Scotland., Competing Interests: Declaration of interests AS and CR were members of the Scottish Government's COVID-19 Advisory Group and are members of the New and Emerging Respiratory Virus Threats Advisory Group risk stratification subgroup and the Scottish Government's Committee on Pandemic Preparedness (unremunerated roles). CR is a member of the Scientific Pandemic Influenza Group on Modelling (unremunerated role). AS is a member of AstraZeneca's Thrombotic Thrombocytopenic Advisory Group (unremunerated role). SVK was co-chair of Scottish Government's Expert Reference Group on Ethnicity and COVID-19 (unremunerated role). All other authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)
Published: 2022
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46. Studying the Long-term Impact of COVID-19 in Kids (SLICK). Healthcare use and costs in children and young people following community-acquired SARS-CoV-2 infection: protocol for an observational study using linked primary and secondary routinely collected healthcare data from England, Scotland and Wales.

Author: Swann OV, Lone NI, Harrison EM, Tomlinson LA, Walker AJ, Seaborne MJ, Pollock L, Farrell J, Hall PS, Seth S, Williams TC, Preston J, Ainsworth JS, Semple FF, Baillie JK, Katikireddi SV, Akbari A, Lyons R, Simpson CR, Semple MG, Goldacre B, Brophy S, Sheikh A, and Docherty AB
Subjects: Child, Humans, Adolescent, SARS-CoV-2, COVID-19 Testing, Cohort Studies, Wales epidemiology, Delivery of Health Care, Observational Studies as Topic, COVID-19 epidemiology
Abstract: Introduction: SARS-CoV-2 infection rarely causes hospitalisation in children and young people (CYP), but mild or asymptomatic infections are common. Persistent symptoms following infection have been reported in CYP but subsequent healthcare use is unclear. We aim to describe healthcare use in CYP following community-acquired SARS-CoV-2 infection and identify those at risk of ongoing healthcare needs., Methods and Analysis: We will use anonymised individual-level, population-scale national data linking demographics, comorbidities, primary and secondary care use and mortality between 1 January 2019 and 1 May 2022. SARS-CoV-2 test data will be linked from 1 January 2020 to 1 May 2022. Analyses will use Trusted Research Environments: OpenSAFELY in England, Secure Anonymised Information Linkage (SAIL) Databank in Wales and Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 in Scotland (EAVE-II). CYP aged ≥4 and <18 years who underwent SARS-CoV-2 reverse transcription PCR (RT-PCR) testing between 1 January 2020 and 1 May 2021 and those untested CYP will be examined.The primary outcome measure is cumulative healthcare cost over 12 months following SARS-CoV-2 testing, stratified into primary or secondary care, and physical or mental healthcare. We will estimate the burden of healthcare use attributable to SARS-CoV-2 infections in the 12 months after testing using a matched cohort study of RT-PCR positive, negative or untested CYP matched on testing date, with adjustment for confounders. We will identify factors associated with higher healthcare needs in the 12 months following SARS-CoV-2 infection using an unmatched cohort of RT-PCR positive CYP. Multivariable logistic regression and machine learning approaches will identify risk factors for high healthcare use and characterise patterns of healthcare use post infection., Ethics and Dissemination: This study was approved by the South-Central Oxford C Health Research Authority Ethics Committee (13/SC/0149). Findings will be preprinted and published in peer-reviewed journals. Analysis code and code lists will be available through public GitHub repositories and OpenCodelists with meta-data via HDR-UK Innovation Gateway., Competing Interests: Competing interests: OVS reports an institutional payment from HDR-UK/Alan Turing for work on this study. LAT reports institutional contracts with UKRI, NIHR, MRC, institutional consulting fees from Bayer, support to attend MHRA meetings and unpaid membership of two non-industry funded trial advisory committees. MJS reports an institutional payment from HDR-UK/Alan Turing for work on this study. CRS reports institutional grants from MBIE, HRC and MRC. SVK reports funding from NRS, MRC and the Scottish Government Chief Scientist Office. He was co-chair of the Scottish Government’s Expert Reference Group on Ethnicity and COVID-19 and a member of the UK Scientific Advisory Group on Emergencies subgroup on ethnicity. MGS reports grants from NIHR, MRC and Health Protection Research Unit in Emerging & Zoonotic Infections, University of Liverpool. He also reports a role as Independent external and non-remunerated member of Pfizer’s External Data Monitoring Committee for their mRNA vaccine program. He is Chair of Infectious Disease Scientific Advisory Board for Integrum Scientific LLC, Greensboro, NC, USA and director of MedEx Solutions Ltd. He reports minority stock ownership for Integrum Scientific LLC, Greensboro, NC, USA and majority stock ownership for MedEx Solutions Ltd. He also reports a gift from Chiesi Farmaceutici SPA to his institution of a clinical trial investigational medicinal product without encumbrance and distribution of same to trial sites. He is also a non-remunerated independent member of HMG UK Scientific Advisory Group for Emergencies (SAGE, COVID-19 Response) and HMG UK New Emerging Respiratory Virus Threats Advisory Group (NERVTAG). SB has received an institutional payment from HDR-UK/Alan Turing funding UOE Ref: 11563729 for work on this study. She also reports institutional payments from MRC, Welsh Government and NIHR. She is a member of the Population and Systems Medicine MRC board. AS reports an institutional payment from HDR-UK/Alan Turing and research grants for EAVE II and BREATHE Hub. He also reports non-remunerated positions on AstraZeneca’s Thrombotic Thrombocytopenic Taskforce and Scottish and UK Government Advisory Committees. RAL is a member of the Welsh Government COVID-19 Technical Advisory Group. BG has received research funding from HDRUK, the Laura and John Arnold Foundation, the Wellcome Trust, the NIHR Oxford Biomedical Research Centre, the NHS National Institute for Health Research School of Primary Care Research, the Mohn-Westlake Foundation, the Good Thinking Foundation, the Health Foundation, and the World Health Organisation; he also receives personal income from speaking and writing for lay audiences on the misuse of science., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)
Published: 2022
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47. Impact on emergency and elective hospital-based care in Scotland over the first 12 months of the pandemic: interrupted time-series analysis of national lockdowns.

Author: Shah SA, Mulholland RH, Wilkinson S, Katikireddi SV, Pan J, Shi T, Kerr S, Agrawal U, Rudan I, Simpson CR, Stock SJ, Macleod J, Murray JL, McCowan C, Ritchie L, Woolhouse M, and Sheikh A
Subjects: Child, Humans, Infant, Newborn, Infant, Child, Preschool, Adolescent, Pandemics, State Medicine, Communicable Disease Control, Hospitals, Scotland epidemiology, Emergency Service, Hospital, Patient Admission, COVID-19 epidemiology
Abstract: Objectives: COVID-19 has resulted in the greatest disruption to National Health Service (NHS) care in its over 70-year history. Building on our previous work, we assessed the ongoing impact of pandemic-related disruption on provision of emergency and elective hospital-based care across Scotland over the first year of the pandemic., Design: We undertook interrupted time-series analyses to evaluate the impact of ongoing pandemic-related disruption on hospital NHS care provision at national level and across demographics and clinical specialties spanning the period 29 March 2020-28 March 2021., Setting: Scotland, UK., Participants: Patients receiving hospital care from NHS Scotland., Main Outcome Measures: We used the percentage change of accident and emergency attendances, and emergency and planned hospital admissions during the pandemic compared to the average admission rate for equivalent weeks in 2018-2019., Results: As restrictions were gradually lifted in Scotland after the first lockdown, hospital-based admissions increased approaching pre-pandemic levels. Subsequent tightening of restrictions in September 2020 were associated with a change in slope of relative weekly admissions rate: -1.98% (-2.38, -1.58) in accident and emergency attendance, -1.36% (-1.68, -1.04) in emergency admissions and -2.31% (-2.95, -1.66) in planned admissions. A similar pattern was seen across sex, socioeconomic status and most age groups, except children (0-14 years) where accident and emergency attendance, and emergency admissions were persistently low over the study period., Conclusions: We found substantial disruption to urgent and planned inpatient healthcare provision in hospitals across NHS Scotland. There is the need for urgent policy responses to address continuing unmet health needs and to ensure resilience in the context of future pandemics.
Published: 2022
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48. Vaccine effectiveness of two-dose BNT162b2 against symptomatic and severe COVID-19 among adolescents in Brazil and Scotland over time: a test-negative case-control study.

Author: Florentino PTV, Millington T, Cerqueira-Silva T, Robertson C, de Araújo Oliveira V, Júnior JBS, Alves FJO, Penna GO, Vital Katikireddi S, Boaventura VS, Werneck GL, Pearce N, McCowan C, Sullivan C, Agrawal U, Grange Z, Ritchie LD, Simpson CR, Sheikh A, Barreto ML, Rudan I, Barral-Netto M, and Paixão ES
Subjects: Humans, Adolescent, Brazil epidemiology, Case-Control Studies, BNT162 Vaccine, Vaccine Efficacy, SARS-CoV-2, COVID-19 epidemiology, COVID-19 prevention & control
Abstract: Background: Little is known about vaccine effectiveness over time among adolescents, especially against the SARS-CoV-2 omicron (B.1.1.529) variant. This study assessed the associations between time since two-dose vaccination with BNT162b2 and the occurrence of symptomatic SARS-CoV-2 infection and severe COVID-19 among adolescents in Brazil and Scotland., Methods: We did test-negative, case-control studies in adolescents aged 12-17 years with COVID-19-related symptoms in Brazil and Scotland. We linked records of SARS-CoV-2 RT-PCR and antigen tests to national vaccination and clinical records. We excluded tests from individuals who did not have symptoms, were vaccinated before the start of the national vaccination programme, received vaccines other than BNT162b2 or a SARS-CoV-2 booster dose of any kind, or had an interval between their first and second dose of fewer than 21 days. Additionally, we excluded negative SARS-CoV-2 tests recorded within 14 days of a previous negative test, negative tests recorded within 7 days after a positive test, any test done within 90 days after a positive test, and tests with missing sex and location information. Cases (SARS-CoV-2 test-positive adolescents) and controls (test-negative adolescents) were drawn from a sample of individuals in whom tests were collected within 10 days of symptom onset. We estimated the adjusted odds ratio and vaccine effectiveness against symptomatic COVID-19 for both countries and against severe COVID-19 (hospitalisation or death) for Brazil across fortnightly periods., Findings: We analysed 503 776 tests from 2 948 538 adolescents in Brazil between Sept 2, 2021, and April 19, 2022, and 127 168 tests from 404 673 adolescents in Scotland between Aug 6, 2021, and April 19, 2022. Vaccine effectiveness peaked at 14-27 days after the second dose in both countries during both waves, and was significantly lower against symptomatic infection during the omicron-dominant period in Brazil (64·7% [95% CI 63·0-66·3]) and in Scotland (82·6% [80·6-84·5]), than it was in the delta-dominant period (80·7% [95% CI 77·8-83·3] in Brazil and 92·8% [85·7-96·4] in Scotland). Vaccine efficacy started to decline from 27 days after the second dose for both countries, reducing to 5·9% (95% CI 2·2-9·4) in Brazil and 50·6% (42·7-57·4) in Scotland at 98 days or more during the omicron-dominant period. In Brazil, protection against severe disease remained above 80% from 28 days after the second dose and was 82·7% (95% CI 68·8-90·4) at 98 days or more after receiving the second dose., Interpretation: We found waning vaccine protection of BNT162b2 against symptomatic COVID-19 infection among adolescents in Brazil and Scotland from 27 days after the second dose. However, protection against severe COVID-19 outcomes remained high at 98 days or more after the second dose in the omicron-dominant period. Booster doses for adolescents need to be considered., Funding: UK Research and Innovation (Medical Research Council), Scottish Government, Health Data Research UK BREATHE Hub, Fiocruz, Fazer o Bem Faz Bem programme, Brazilian National Research Council, and Wellcome Trust., Translation: For the Portuguese translation of the abstract see Supplementary Materials section., Competing Interests: Declaration of interests MB-N reports grants from the Fazer o Bem Faz Bem programme from JBS SA. VdAO, VSB, MLB, and MB-N are employees of Fiocruz, a federal public institution that manufactures Vaxzevria in Brazil through a full technology transfer agreement with AstraZeneca. Fiocruz allocates all its manufactured products to the Ministry of Health for public health use. SVK was Co-Chair of the Scottish Government's Expert Reference Group on Ethnicity and COVID-19 and a member of the UK Government's Scientific Advisory Group on Emergencies subgroup on ethnicity. IR is a member of the Scientific Advisory Committee of the Government of Croatia and co-Editor-in-Chief of the Journal of Global Health. CRS declares funding from the Medical Research Council, the National Institute for Health Research, the Chief Scientist Office, and the New Zealand Ministry for Business, Innovation and Employment and Health Research Council during the conduct of this study. CR declares he is a Member of SPI-M, Scottish Government Scientific Advisory Committee, MHRA COVID-19 vaccine benefit and risk expert working group. AS declares that he is a member of the UK and Scottish Governments COVID-19 Advisory Boards and Astra-Zeneca's Thrombotic Thrombocytopenic Taskforce. IR is Co-Editor-in-Chief of the Journal of Global Health and President of the International Society of Global Health. All other authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)
Published: 2022
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49. A population-based matched cohort study of early pregnancy outcomes following COVID-19 vaccination and SARS-CoV-2 infection.

Author: Calvert C, Carruthers J, Denny C, Donaghy J, Hillman S, Hopcroft LEM, Hopkins L, Goulding A, Lindsay L, McLaughlin T, Moore E, Pan J, Taylor B, Almaghrabi F, Auyeung B, Bhaskaran K, Gibbons CL, Katikireddi SV, McCowan C, Murray J, O'Leary M, Ritchie LD, Shah SA, Simpson CR, Robertson C, Sheikh A, Stock SJ, and Wood R
Subjects: Female, Humans, Pregnancy, Cohort Studies, Pregnancy Outcome, SARS-CoV-2, Vaccination, Abortion, Spontaneous epidemiology, COVID-19 epidemiology, COVID-19 prevention & control, COVID-19 Vaccines adverse effects, Influenza, Human prevention & control, Pregnancy, Ectopic
Abstract: Data on the safety of COVID-19 vaccines in early pregnancy are limited. We conducted a national, population-based, matched cohort study assessing associations between COVID-19 vaccination and miscarriage prior to 20 weeks gestation and, separately, ectopic pregnancy. We identified women in Scotland vaccinated between 6 weeks preconception and 19 weeks 6 days gestation (for miscarriage; n = 18,780) or 2 weeks 6 days gestation (for ectopic; n = 10,570). Matched, unvaccinated women from the pre-pandemic and, separately, pandemic periods were used as controls. Here we show no association between vaccination and miscarriage (adjusted Odds Ratio [aOR], pre-pandemic controls = 1.02, 95% Confidence Interval [CI] = 0.96-1.09) or ectopic pregnancy (aOR = 1.13, 95% CI = 0.92-1.38). We undertook additional analyses examining confirmed SARS-CoV-2 infection as the exposure and similarly found no association with miscarriage or ectopic pregnancy. Our findings support current recommendations that vaccination remains the safest way for pregnant women to protect themselves and their babies from COVID-19., (© 2022. The Author(s).)
Published: 2022
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50. Cohort Profile: The COVID-19 in Pregnancy in Scotland (COPS) dynamic cohort of pregnant women to assess effects of viral and vaccine exposures on pregnancy.

Author: Stock SJ, Carruthers J, Denny C, Donaghy J, Goulding A, Hopcroft LEM, Hopkins L, Mulholland R, Agrawal U, Auyeung B, Katikireddi SV, McCowan C, Murray J, Robertson C, Sheikh A, Shi T, Simpson CR, Vasileiou E, and Wood R
Subjects: Female, Humans, Pregnancy, Pregnant Women, SARS-CoV-2, Vaccination, COVID-19 prevention & control, Pregnancy Complications, Infectious epidemiology, Pregnancy Complications, Infectious prevention & control, Vaccines
Published: 2022
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