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1. Global burden of bacterial antimicrobial resistance 1990–2021: a systematic analysis with forecasts to 2050

Author

Naghavi, M, Vollset, SE, Ikuta, KS, Swetschinski, LR, Gray, AP, Wool, EE, Robles Aguilar, G, Mestrovic, T, Smith, G, Han, C, Hsu, RL, Azzam, AY, Babaei, M, Babin, F-X, Badar, M, Baig, AA, Bajcetic, M, Baker, S, Bardhan, M, Barqawi, HJ, Basharat, Z, Chalek, J, Basiru, A, Bastard, M, Basu, S, Bayleyegn, NS, Belete, MA, Bello, OO, Beloukas, A, Berkley, JA, Bhagavathula, AS, Bhaskar, S, Araki, DT, Bhuyan, SS, Bielicki, JA, Briko, NI, Brown, CS, Browne, AJ, Buonsenso, D, Bustanji, Y, Carvalheiro, CG, Castañeda-Orjuela, CA, Cenderadewi, M, Chung, E, Chadwick, J, Chakraborty, S, Chandika, RM, Chandy, S, Chansamouth, V, Chattu, VK, Chaudhary, AA, Ching, PR, Chopra, H, Chowdhury, FR, Raggi, C, Chu, D-T, Chutiyami, M, Cruz-Martins, N, da Silva, AG, Dadras, O, Dai, X, Darcho, SD, Das, S, De la Hoz, FP, Dekker, DM, Gershberg Hayoon, A, Dhama, K, Diaz, D, Dickson, BFR, Djorie, SG, Dodangeh, M, Dohare, S, Dokova, KG, Doshi, OP, Dowou, RK, Dsouza, HL, Davis Weaver, N, Dunachie, SJ, Dziedzic, AM, Eckmanns, T, Ed-Dra, A, Eftekharimehrabad, A, Ekundayo, TC, El Sayed, I, Elhadi, M, El-Huneidi, W, Elias, C, Lindstedt, PA, Ellis, SJ, Elsheikh, R, Elsohaby, I, Eltaha, C, Eshrati, B, Eslami, M, Eyre, DW, Fadaka, AO, Fagbamigbe, AF, Fahim, A, Smith, AE, Fakhri-Demeshghieh, A, Fasina, FO, Fasina, MM, Fatehizadeh, A, Feasey, NA, Feizkhah, A, Fekadu, G, Fischer, F, Fitriana, I, Forrest, KM, Altay, U, Fortuna Rodrigues, C, Fuller, JE, Gadanya, MA, Gajdács, M, Gandhi, AP, Garcia-Gallo, EE, Garrett, DO, Gautam, RK, Gebregergis, MW, Gebrehiwot, M, Bhattacharjee, NV, Gebremeskel, TG, Geffers, C, Georgalis, L, Ghazy, RM, Golechha, M, Golinelli, D, Gordon, M, Gulati, S, Gupta, RD, Gupta, S, Giannakis, K, Gupta, VK, Habteyohannes, AD, Haller, S, Harapan, H, Harrison, ML, Hasaballah, AI, Hasan, I, Hasan, RS, Hasani, H, Haselbeck, AH, Fell, F, Hasnain, MS, Hassan, II, Hassan, S, Hassan Zadeh Tabatabaei, MS, Hayat, K, He, J, Hegazi, OE, Heidari, M, Hezam, K, Holla, R, McManigal, B, Holm, M, Hopkins, H, Hossain, MM, Hosseinzadeh, M, Hostiuc, S, Hussein, NR, Huy, LD, Ibáñez-Prada, ED, Ikiroma, A, Ilic, IM, Ekapirat, N, Islam, SMS, Ismail, F, Ismail, NE, Iwu, CD, Iwu-Jaja, CJ, Jafarzadeh, A, Jaiteh, F, Jalilzadeh Yengejeh, R, Jamora, RDG, Javidnia, J, Mendes, JA, Jawaid, T, Jenney, AWJ, Jeon, HJ, Jokar, M, Jomehzadeh, N, Joo, T, Joseph, N, Kamal, Z, Kanmodi, KK, Kantar, RS, Runghien, T, Kapisi, JA, Karaye, IM, Khader, YS, Khajuria, H, Khalid, N, Khamesipour, F, Khan, A, Khan, MJ, Khan, MT, Khanal, V, Srimokla, O, Khidri, FF, Khubchandani, J, Khusuwan, S, Kim, MS, Kisa, A, Korshunov, VA, Krapp, F, Krumkamp, R, Kuddus, M, Kulimbet, M, Abdelkader, A, Kumar, D, Kumaran, EAP, Kuttikkattu, A, Kyu, HH, Landires, I, Lawal, BK, Le, TTT, Lederer, IM, Lee, M, Lee, SW, Abd-Elsalam, S, Lepape, A, Lerango, TL, Ligade, VS, Lim, C, Lim, SS, Limenh, LW, Liu, C, Liu, X, Loftus, MJ, Aboagye, RG, M Amin, HI, Maass, KL, Maharaj, SB, Mahmoud, MA, Maikanti-Charalampous, P, Makram, OM, Malhotra, K, Malik, AA, Mandilara, GD, Marks, F, Abolhassani, H, Martinez-Guerra, BA, Martorell, M, Masoumi-Asl, H, Mathioudakis, AG, May, J, McHugh, TA, Meiring, J, Meles, HN, Melese, A, Melese, EB, Abualruz, H, Minervini, G, Mohamed, NS, Mohammed, S, Mohan, S, Mokdad, AH, Monasta, L, Moodi Ghalibaf, A, Moore, CE, Moradi, Y, Mossialos, E, Abubakar, U, Mougin, V, Mukoro, GD, Mulita, F, Muller-Pebody, B, Murillo-Zamora, E, Musa, S, Musicha, P, Musila, LA, Muthupandian, S, Nagarajan, AJ, Abukhadijah, HJ, Naghavi, P, Nainu, F, Nair, TS, Najmuldeen, HHR, Natto, ZS, Nauman, J, Nayak, BP, Nchanji, GT, Ndishimye, P, Negoi, I, Aburuz, S, Negoi, RI, Nejadghaderi, SA, Nguyen, QP, Noman, EA, Nwakanma, DC, O'Brien, S, Ochoa, TJ, Odetokun, IA, Ogundijo, OA, Ojo-Akosile, TR, Abu-Zaid, A, Okeke, SR, Okonji, OC, Olagunju, AT, Olivas-Martinez, A, Olorukooba, AA, Olwoch, P, Onyedibe, KI, Ortiz-Brizuela, E, Osuolale, O, Ounchanum, P, Achalapong, S, Oyeyemi, OT, P A, MP, Paredes, JL, Parikh, RR, Patel, J, Patil, S, Pawar, S, Peleg, AY, Peprah, P, Perdigão, J, Addo, IY, Perrone, C, Petcu, I-R, Phommasone, K, Piracha, ZZ, Poddighe, D, Pollard, AJ, Poluru, R, Ponce-De-Leon, A, Puvvula, J, Qamar, FN, Adekanmbi, V, Qasim, NH, Rafai, CD, Raghav, P, Rahbarnia, L, Rahim, F, Rahimi-Movaghar, V, Rahman, M, Rahman, MA, Ramadan, H, Ramasamy, SK, Adeyeoluwa, TE, Ramesh, PS, Ramteke, PW, Rana, RK, Rani, U, Rashidi, M-M, Rathish, D, Rattanavong, S, Rawaf, S, Redwan, EMM, Reyes, LF, Adnani, QES, Roberts, T, Robotham, JV, Rosenthal, VD, Ross, AG, Roy, N, Rudd, KE, Sabet, CJ, Saddik, BA, Saeb, MR, Saeed, U, Adzigbli, LA, Saeedi Moghaddam, S, Saengchan, W, Safaei, M, Saghazadeh, A, Saheb Sharif-Askari, N, Sahebkar, A, Sahoo, SS, Sahu, M, Saki, M, Salam, N, Afzal, MS, Saleem, Z, Saleh, MA, Samodra, YL, Samy, AM, Saravanan, A, Satpathy, M, Schumacher, AE, Sedighi, M, Seekaew, S, Shafie, M, Afzal, S, Shah, PA, Shahid, S, Shahwan, MJ, Shakoor, S, Shalev, N, Shamim, MA, Shamshirgaran, MA, Shamsi, A, Sharifan, A, Shastry, RP, Agodi, A, Shetty, M, Shittu, A, Shrestha, S, Siddig, EE, Sideroglou, T, Sifuentes-Osornio, J, Silva, LMLR, Simões, EAF, Simpson, AJH, Singh, A, Ahlstrom, AJ, Singh, S, Sinto, R, Soliman, SSM, Soraneh, S, Stoesser, N, Stoeva, TZ, Swain, CK, Szarpak, L, T Y, SS, Tabatabai, S, Ahmad, A, Tabche, C, Taha, ZM-A, Tan, K-K, Tasak, N, Tat, NY, Thaiprakong, A, Thangaraju, P, Tigoi, CC, Tiwari, K, Tovani-Palone, MR, Ahmad, S, Tran, TH, Tumurkhuu, M, Turner, P, Udoakang, AJ, Udoh, A, Ullah, N, Ullah, S, Vaithinathan, AG, Valenti, M, Vos, T, Ahmad, T, Vu, HTL, Waheed, Y, Walker, AS, Walson, JL, Wangrangsimakul, T, Weerakoon, KG, Wertheim, HFL, Williams, PCM, Wolde, AA, Wozniak, TM, Ahmadi, A, Wu, F, Wu, Z, Yadav, MKK, Yaghoubi, S, Yahaya, ZS, Yarahmadi, A, Yezli, S, Yismaw, YE, Yon, DK, Yuan, C-W, Ahmed, A, Yusuf, H, Zakham, F, Zamagni, G, Zhang, H, Zhang, Z-J, Zielińska, M, Zumla, A, Zyoud, SHH, Zyoud, SH, Hay, SI, Ahmed, H, Stergachis, A, Sartorius, B, Cooper, BS, Dolecek, C, Murray, CJL, Ahmed, I, Ahmed, M, Ahmed, S, Ahmed, SA, Akkaif, MA, Al Awaidy, S, Al Thaher, Y, Alalalmeh, SO, AlBataineh, MT, Aldhaleei, WA, Al-Gheethi, AAS, Alhaji, NB, Ali, A, Ali, L, Ali, SS, Ali, W, Allel, K, Al-Marwani, S, Alrawashdeh, A, Altaf, A, Al-Tammemi, AB, Al-Tawfiq, JA, Alzoubi, KH, Al-Zyoud, WA, Amos, B, Amuasi, JH, Ancuceanu, R, Andrews, JR, Anil, A, Anuoluwa, IA, Anvari, S, Anyasodor, AE, Apostol, GLC, Arabloo, J, Arafat, M, Aravkin, AY, Areda, D, Aremu, A, Artamonov, AA, Ashley, EA, Asika, MO, Athari, SS, Atout, MMW, Awoke, T, Azadnajafabad, S, Azam, JM, Aziz, S, Naghavi, M, Vollset, SE, Ikuta, KS, Swetschinski, LR, Gray, AP, Wool, EE, Robles Aguilar, G, Mestrovic, T, Smith, G, Han, C, Hsu, RL, Azzam, AY, Babaei, M, Babin, F-X, Badar, M, Baig, AA, Bajcetic, M, Baker, S, Bardhan, M, Barqawi, HJ, Basharat, Z, Chalek, J, Basiru, A, Bastard, M, Basu, S, Bayleyegn, NS, Belete, MA, Bello, OO, Beloukas, A, Berkley, JA, Bhagavathula, AS, Bhaskar, S, Araki, DT, Bhuyan, SS, Bielicki, JA, Briko, NI, Brown, CS, Browne, AJ, Buonsenso, D, Bustanji, Y, Carvalheiro, CG, Castañeda-Orjuela, CA, Cenderadewi, M, Chung, E, Chadwick, J, Chakraborty, S, Chandika, RM, Chandy, S, Chansamouth, V, Chattu, VK, Chaudhary, AA, Ching, PR, Chopra, H, Chowdhury, FR, Raggi, C, Chu, D-T, Chutiyami, M, Cruz-Martins, N, da Silva, AG, Dadras, O, Dai, X, Darcho, SD, Das, S, De la Hoz, FP, Dekker, DM, Gershberg Hayoon, A, Dhama, K, Diaz, D, Dickson, BFR, Djorie, SG, Dodangeh, M, Dohare, S, Dokova, KG, Doshi, OP, Dowou, RK, Dsouza, HL, Davis Weaver, N, Dunachie, SJ, Dziedzic, AM, Eckmanns, T, Ed-Dra, A, Eftekharimehrabad, A, Ekundayo, TC, El Sayed, I, Elhadi, M, El-Huneidi, W, Elias, C, Lindstedt, PA, Ellis, SJ, Elsheikh, R, Elsohaby, I, Eltaha, C, Eshrati, B, Eslami, M, Eyre, DW, Fadaka, AO, Fagbamigbe, AF, Fahim, A, Smith, AE, Fakhri-Demeshghieh, A, Fasina, FO, Fasina, MM, Fatehizadeh, A, Feasey, NA, Feizkhah, A, Fekadu, G, Fischer, F, Fitriana, I, Forrest, KM, Altay, U, Fortuna Rodrigues, C, Fuller, JE, Gadanya, MA, Gajdács, M, Gandhi, AP, Garcia-Gallo, EE, Garrett, DO, Gautam, RK, Gebregergis, MW, Gebrehiwot, M, Bhattacharjee, NV, Gebremeskel, TG, Geffers, C, Georgalis, L, Ghazy, RM, Golechha, M, Golinelli, D, Gordon, M, Gulati, S, Gupta, RD, Gupta, S, Giannakis, K, Gupta, VK, Habteyohannes, AD, Haller, S, Harapan, H, Harrison, ML, Hasaballah, AI, Hasan, I, Hasan, RS, Hasani, H, Haselbeck, AH, Fell, F, Hasnain, MS, Hassan, II, Hassan, S, Hassan Zadeh Tabatabaei, MS, Hayat, K, He, J, Hegazi, OE, Heidari, M, Hezam, K, Holla, R, McManigal, B, Holm, M, Hopkins, H, Hossain, MM, Hosseinzadeh, M, Hostiuc, S, Hussein, NR, Huy, LD, Ibáñez-Prada, ED, Ikiroma, A, Ilic, IM, Ekapirat, N, Islam, SMS, Ismail, F, Ismail, NE, Iwu, CD, Iwu-Jaja, CJ, Jafarzadeh, A, Jaiteh, F, Jalilzadeh Yengejeh, R, Jamora, RDG, Javidnia, J, Mendes, JA, Jawaid, T, Jenney, AWJ, Jeon, HJ, Jokar, M, Jomehzadeh, N, Joo, T, Joseph, N, Kamal, Z, Kanmodi, KK, Kantar, RS, Runghien, T, Kapisi, JA, Karaye, IM, Khader, YS, Khajuria, H, Khalid, N, Khamesipour, F, Khan, A, Khan, MJ, Khan, MT, Khanal, V, Srimokla, O, Khidri, FF, Khubchandani, J, Khusuwan, S, Kim, MS, Kisa, A, Korshunov, VA, Krapp, F, Krumkamp, R, Kuddus, M, Kulimbet, M, Abdelkader, A, Kumar, D, Kumaran, EAP, Kuttikkattu, A, Kyu, HH, Landires, I, Lawal, BK, Le, TTT, Lederer, IM, Lee, M, Lee, SW, Abd-Elsalam, S, Lepape, A, Lerango, TL, Ligade, VS, Lim, C, Lim, SS, Limenh, LW, Liu, C, Liu, X, Loftus, MJ, Aboagye, RG, M Amin, HI, Maass, KL, Maharaj, SB, Mahmoud, MA, Maikanti-Charalampous, P, Makram, OM, Malhotra, K, Malik, AA, Mandilara, GD, Marks, F, Abolhassani, H, Martinez-Guerra, BA, Martorell, M, Masoumi-Asl, H, Mathioudakis, AG, May, J, McHugh, TA, Meiring, J, Meles, HN, Melese, A, Melese, EB, Abualruz, H, Minervini, G, Mohamed, NS, Mohammed, S, Mohan, S, Mokdad, AH, Monasta, L, Moodi Ghalibaf, A, Moore, CE, Moradi, Y, Mossialos, E, Abubakar, U, Mougin, V, Mukoro, GD, Mulita, F, Muller-Pebody, B, Murillo-Zamora, E, Musa, S, Musicha, P, Musila, LA, Muthupandian, S, Nagarajan, AJ, Abukhadijah, HJ, Naghavi, P, Nainu, F, Nair, TS, Najmuldeen, HHR, Natto, ZS, Nauman, J, Nayak, BP, Nchanji, GT, Ndishimye, P, Negoi, I, Aburuz, S, Negoi, RI, Nejadghaderi, SA, Nguyen, QP, Noman, EA, Nwakanma, DC, O'Brien, S, Ochoa, TJ, Odetokun, IA, Ogundijo, OA, Ojo-Akosile, TR, Abu-Zaid, A, Okeke, SR, Okonji, OC, Olagunju, AT, Olivas-Martinez, A, Olorukooba, AA, Olwoch, P, Onyedibe, KI, Ortiz-Brizuela, E, Osuolale, O, Ounchanum, P, Achalapong, S, Oyeyemi, OT, P A, MP, Paredes, JL, Parikh, RR, Patel, J, Patil, S, Pawar, S, Peleg, AY, Peprah, P, Perdigão, J, Addo, IY, Perrone, C, Petcu, I-R, Phommasone, K, Piracha, ZZ, Poddighe, D, Pollard, AJ, Poluru, R, Ponce-De-Leon, A, Puvvula, J, Qamar, FN, Adekanmbi, V, Qasim, NH, Rafai, CD, Raghav, P, Rahbarnia, L, Rahim, F, Rahimi-Movaghar, V, Rahman, M, Rahman, MA, Ramadan, H, Ramasamy, SK, Adeyeoluwa, TE, Ramesh, PS, Ramteke, PW, Rana, RK, Rani, U, Rashidi, M-M, Rathish, D, Rattanavong, S, Rawaf, S, Redwan, EMM, Reyes, LF, Adnani, QES, Roberts, T, Robotham, JV, Rosenthal, VD, Ross, AG, Roy, N, Rudd, KE, Sabet, CJ, Saddik, BA, Saeb, MR, Saeed, U, Adzigbli, LA, Saeedi Moghaddam, S, Saengchan, W, Safaei, M, Saghazadeh, A, Saheb Sharif-Askari, N, Sahebkar, A, Sahoo, SS, Sahu, M, Saki, M, Salam, N, Afzal, MS, Saleem, Z, Saleh, MA, Samodra, YL, Samy, AM, Saravanan, A, Satpathy, M, Schumacher, AE, Sedighi, M, Seekaew, S, Shafie, M, Afzal, S, Shah, PA, Shahid, S, Shahwan, MJ, Shakoor, S, Shalev, N, Shamim, MA, Shamshirgaran, MA, Shamsi, A, Sharifan, A, Shastry, RP, Agodi, A, Shetty, M, Shittu, A, Shrestha, S, Siddig, EE, Sideroglou, T, Sifuentes-Osornio, J, Silva, LMLR, Simões, EAF, Simpson, AJH, Singh, A, Ahlstrom, AJ, Singh, S, Sinto, R, Soliman, SSM, Soraneh, S, Stoesser, N, Stoeva, TZ, Swain, CK, Szarpak, L, T Y, SS, Tabatabai, S, Ahmad, A, Tabche, C, Taha, ZM-A, Tan, K-K, Tasak, N, Tat, NY, Thaiprakong, A, Thangaraju, P, Tigoi, CC, Tiwari, K, Tovani-Palone, MR, Ahmad, S, Tran, TH, Tumurkhuu, M, Turner, P, Udoakang, AJ, Udoh, A, Ullah, N, Ullah, S, Vaithinathan, AG, Valenti, M, Vos, T, Ahmad, T, Vu, HTL, Waheed, Y, Walker, AS, Walson, JL, Wangrangsimakul, T, Weerakoon, KG, Wertheim, HFL, Williams, PCM, Wolde, AA, Wozniak, TM, Ahmadi, A, Wu, F, Wu, Z, Yadav, MKK, Yaghoubi, S, Yahaya, ZS, Yarahmadi, A, Yezli, S, Yismaw, YE, Yon, DK, Yuan, C-W, Ahmed, A, Yusuf, H, Zakham, F, Zamagni, G, Zhang, H, Zhang, Z-J, Zielińska, M, Zumla, A, Zyoud, SHH, Zyoud, SH, Hay, SI, Ahmed, H, Stergachis, A, Sartorius, B, Cooper, BS, Dolecek, C, Murray, CJL, Ahmed, I, Ahmed, M, Ahmed, S, Ahmed, SA, Akkaif, MA, Al Awaidy, S, Al Thaher, Y, Alalalmeh, SO, AlBataineh, MT, Aldhaleei, WA, Al-Gheethi, AAS, Alhaji, NB, Ali, A, Ali, L, Ali, SS, Ali, W, Allel, K, Al-Marwani, S, Alrawashdeh, A, Altaf, A, Al-Tammemi, AB, Al-Tawfiq, JA, Alzoubi, KH, Al-Zyoud, WA, Amos, B, Amuasi, JH, Ancuceanu, R, Andrews, JR, Anil, A, Anuoluwa, IA, Anvari, S, Anyasodor, AE, Apostol, GLC, Arabloo, J, Arafat, M, Aravkin, AY, Areda, D, Aremu, A, Artamonov, AA, Ashley, EA, Asika, MO, Athari, SS, Atout, MMW, Awoke, T, Azadnajafabad, S, Azam, JM, and Aziz, S

Published
2024

2. COVID-19 Pandemic Impacted Food Security and Caused Psychosocial Stress in Selected States of Nigeria.

Author

Bwala DG, Otekunrin OA, Adebowale OO, Fasina MM, Odetokun IA, and Fasina FO

Subjects
Humans, Socioeconomic Factors, Nigeria, Pandemics, Food Supply, Food Security, Stress, Psychological, COVID-19
Abstract

The COVID-19 disease has infected many countries, causing generalized impacts on different income categories. We carried out a survey among households (n = 412) representing different income groups in Nigeria. We used validated food insecurity experience and socio-psychologic tools. Data obtained were analyzed using descriptive and inferential statistics. The earning capacities of the respondents ranged from 145 USD/month for low-income earners to 1945 USD/month for high-income earners. A total of 173 households (42%) ran out of food during the COVID-19 pandemic. All categories of households experienced increasing dependency on the general public and a perception of increasing insecurity, with the high-income earners experiencing the greatest shift. In addition, increasing levels of anger and irritation were experienced among all categories. Of the socio-demographic variables, only gender, educational level of the household head, work hours per day, and family income based on society class were associated ( p < 0.05) with food security and hunger due to the COVID-19 pandemic. Although psychological stress was observed to be greater in the low-income earning group, household heads with medium and high family income were more likely to have satisfactory experiences regarding food security and hunger. It is recommended that socio-economic groups should be mapped and support systems should target each group to provide the needed support in terms of health, social, economic, and mental wellness.

Published
2023
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3. Test positivity - Evaluation of a new metric to assess epidemic dispersal mediated by non-symptomatic cases.

Author

Fasina FO, Salami MA, Fasina MM, Otekunrin OA, Hoogesteijn AL, and Hittner JB

Subjects
Argentina epidemiology, Bolivia epidemiology, COVID-19 prevention & control, COVID-19 Testing trends, Chile epidemiology, Cuba epidemiology, Epidemics prevention & control, Humans, Mexico epidemiology, Mortality trends, Uruguay epidemiology, Asymptomatic Infections epidemiology, COVID-19 diagnosis, COVID-19 epidemiology, COVID-19 Testing methods, COVID-19 Testing standards
Abstract

Epidemic control may be hampered when the percentage of asymptomatic cases is high. Seeking remedies for this problem, test positivity was explored between the first 60 to 90 epidemic days in six countries that reported their first COVID-19 case between February and March 2020: Argentina, Bolivia, Chile, Cuba, Mexico, and Uruguay. Test positivity (TP) is the percentage of test-positive individuals reported on a given day out of all individuals tested the same day. To generate both country-specific and multi-country information, this study was implemented in two stages. First, the epidemiologic data of the country infected last (Uruguay) were analyzed. If at least one TP-related analysis yielded a statistically significant relationship, later assessments would investigate the six countries. The Uruguayan data indicated (i) a positive correlation between daily TP and daily new cases (r = 0.75); (ii) a negative correlation between TP and the number of tests conducted per million inhabitants (TPMI, r = -0.66); and (iii) three temporal stages, which differed from one another in both TP and TPMI medians (p < 0.01) and, together, revealed a negative relationship between TPMI and TP. No significant relationship was found between TP and the number of active or recovered patients. The six countries showed a positive correlation between TP and the number of deaths/million inhabitants (DMI, r = 0.65, p < 0.01). With one exception -a country where isolation was not pursued-, all countries showed a negative correlation between TP and TPMI (r = 0.74). The temporal analysis of country-specific policies revealed four patterns, characterized by: (1) low TPMI and high DMI, (2) high TPMI and low DMI; (3) an intermediate pattern, and (4) high TPMI and high DMI. Findings support the hypothesis that test positivity may guide epidemiologic policy-making, provided that policy-related factors are considered and high-resolution geographical data are utilized., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Published
2021
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4. Knowledge, Attitudes, and Perceptions Associated With Antimicrobial Stewardship Among Veterinary Students: A Multi-Country Survey From Nigeria, South Africa, and Sudan.

Author

Fasina FO, LeRoux-Pullen L, Smith P, Debusho LK, Shittu A, Jajere SM, Adebowale O, Odetokun I, Agbaje M, Fasina MM, Fasanmi OG, van Dyk D, Abubakar MS, Onakpa MM, Ali MG, Yousuf HS, Elmgboul WE, and Sirdar MM

Subjects
Adult, Animals, Cross-Sectional Studies, Health Knowledge, Attitudes, Practice, Humans, Nigeria, Perception, South Africa, Sudan, Young Adult, Antimicrobial Stewardship
Abstract

In African countries, antimicrobial resistance (AMR) issue remains pertinent. Despite this, little efforts have been made to assess the future veterinary prescribers on their knowledge, attitudes and practices (KAP) related to antimicrobial usage. This multi-country survey attempts to explore the KAP of future veterinarians on stewardship of antimicrobial and identify knowledge gaps. Eight veterinary schools participated from Nigeria, Sudan and South Africa. Data regarding perceptions and knowledge were analyzed using Chi-square χ 2 test, Spearman's (Rho) Rank order correlation and factor analysis using principal component factoring extraction method. Fifty-two percent of the study participants were final year veterinary students, respectively, and majority (77.2%) had no previous knowledge of biomedical sciences. Majority age were 22-27 years (24.7 ± 2.8) 79% and multiple career fields post-graduation were preferred. Overall, poor perceptions and knowledge of antimicrobial stewardship were observed with variations among countries and only 36.3% ( n = 123) of the students were confident in their ability to choose the ideal antimicrobial agents for a specific patient/group of animals. The majority of the final year students were confident of their knowledge regarding AMR (68%), making of Gram staining (69.2%) and in choosing the most ideal route for administering a specific antimicrobial (74.7%). The final year students had significantly ( p < 0.05) higher confidence level for knowledge compared with the pre-final year students. Tetracyclines, penicillins, and sulphonamides represent the three most abused veterinary antimicrobials with similar ranking across countries. South African (69.7 ± 20.5) and Sudanese (68.1 ± 15.4) had significantly ( p < 0.0001) higher mean scores compared to the Nigerian students (44.3 ± 6.8) in the student's ability to correctly match some specific antimicrobials against their classes but Nigerian students performed better in ranking antimicrobials. This survey revealed poor to average knowledge of antimicrobial stewardship among veterinary students with significant knowledge gaps across the countries. It is recommended that the relevant regulatory and standardization authorities should make concerted efforts and interventions to regularly review curricula to ensure the delivery of targeted formative and normative training, and improved lectures on antimicrobial usage and stewardship in order to improve the awareness and behaviors of future prescribers. The identified knowledge gaps of veterinary medical students on antimicrobial stewardship must be bridge to safeguard the future., (Copyright © 2020 Fasina, LeRoux-Pullen, Smith, Debusho, Shittu, Jajere, Adebowale, Odetokun, Agbaje, Fasina, Fasanmi, van Dyk, Abubakar, Onakpa, Ali, Yousuf, Elmgboul and Sirdar.)

Published
2020
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5. Where and when to vaccinate? Interdisciplinary design and evaluation of the 2018 Tanzanian anti-rabies campaign.

Author

Fasina FO, Mtui-Malamsha N, Mahiti GR, Sallu R, OleNeselle M, Rubegwa B, Makonnen YJ, Kafeero F, Ruheta M, Nonga HE, Swai E, Makungu S, Killewo J, Otieno EG, Lupindu AM, Komba E, Mdegela R, Assenga JK, Bernard J, Hussein M, Marandu W, Warioba J, Kaaya E, Masanja P, Francis G, Kessy VM, Savy J, Choyo H, Ochieng J, Hoogesteijn AL, Fasina MM, and Rivas AL

Subjects
Animals, Cat Diseases prevention & control, Cats, Cost-Benefit Analysis, Dog Diseases prevention & control, Dogs, Female, Humans, Rabies economics, Rabies transmission, Rabies Vaccines economics, Tanzania, Immunization Programs economics, Rabies prevention & control, Rabies Vaccines administration & dosage
Abstract

Objectives: Hoping to improve health-related effectiveness, a two-phase vaccination against rabies was designed and executed in northern Tanzania in 2018, which included geo-epidemiological and economic perspectives., Methods: Considering the local bio-geography and attempting to rapidly establish a protective ring around a city at risk, the first phase intervened on sites surrounding that city, where the population density was lower than in the city at risk. The second phase vaccinated a rural area., Results: No rabies-related case has been reported in the vaccinated areas for over a year post-immunisation; hence, the campaign is viewed as highly cost-effective. Other metrics included: rapid implementation (concluded in half the time spent on other campaigns) and the estimated cost per protected life, which was 3.28 times lower than in similar vaccinations., Conclusions: The adopted design emphasised local bio-geographical dynamics: it prevented the occurrence of an epidemic in a city with a higher demographic density than its surrounding area and it also achieved greater effectiveness than average interventions. These interdisciplinary, policy-oriented experiences have broad and immediate applications in settings of limited and/or time-sensitive (expertise, personnel, and time available to intervene) resources and conditions., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Published
2020
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7. Descriptive analyses and risk of death due to Ebola Virus Disease, West Africa, 2014.

Author

Fasina FO, Adenubi OT, Ogundare ST, Shittu A, Bwala DG, and Fasina MM

Subjects
Africa, Western epidemiology, Female, Humans, Male, Public Health Administration methods, Risk Assessment, Hemorrhagic Fever, Ebola epidemiology, Hemorrhagic Fever, Ebola mortality, Mortality
Abstract

Introduction: Since the first case of Ebola virus disease (EVD) in Guinea in 2013, major outbreaks have been reported in West Africa., Methodology: Cases and fatalities of EVD caused by Zaire Ebola virus (ZEBOV) were evaluated, and the risks of dying in the general population and in healthcare workers were assessed., Results: The case fatality rate estimated for EVD was 76.4% in 20 studies. Cumulative proportion of fatal cases in West Africa was 42.9%, 30.1%, and 64.2% in Liberia, Sierra Leone, and Guinea, respectively. The proportion of total deaths in Liberia, Sierra Leone, and Guinea was 42.5%, 35.8%, and 21.6%, respectively. Healthcare workers were at higher risk of dying compared with the general public, and the same applied to intense transmission countries and to countries with sufficient bed capacities. The declaration of a health emergency "out-of-control" situation by the World Health Organization on 8 August 2014 reduced the risk of death among patients. Factors including deplorable healthcare delivery infrastructure in war-ravaged regions of Africa, the impotence of governments to enforce public health regulations, and the loss of confidence in public healthcare delivery programs were key among others factors that enhanced the spread and magnitude of outbreaks., Conclusions: The findings underscore the need for an overall re-appraisal of the healthcare systems in African countries and the ability to cope with widespread epidemic challenges. Outbreaks like that of Ebola diseases should be handled not just as a medical emergency but also a socio-economic problem with significant negative economic impacts.

Published
2015
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8. Phytochemical analysis and in-vitro anti-African swine fever virus activity of extracts and fractions of Ancistrocladus uncinatus, Hutch and Dalziel (Ancistrocladaceae).

Author

Fasina FO, Olaokun OO, Oladipo OO, Fasina MM, Makinde AA, Heath L, and Bastos AD

Subjects
Animals, Gas Chromatography-Mass Spectrometry, In Vitro Techniques, Plant Bark chemistry, Plant Extracts analysis, Plant Leaves chemistry, Plant Roots chemistry, Plant Stems chemistry, Polymerase Chain Reaction veterinary, Real-Time Polymerase Chain Reaction veterinary, Swine, African Swine Fever drug therapy, African Swine Fever Virus drug effects, Antiviral Agents therapeutic use, Caryophyllaceae chemistry, Phytotherapy veterinary, Plant Extracts therapeutic use
Abstract

Background: African swine fever (ASF), a highly contagious fatal acute haemorrhagic viral disease of pigs currently has no treatment or vaccination protocol and it threatens the pig industry worldwide. Recent outbreaks were managed by farmers with ethnoveterinary preparations with various claims of effectiveness., Results: We identified 35 compounds using GC-MS protocol and ASF virus (NIG 99) was significantly reduced by some extracts and fractions of the plant. However, the plant was poorly extracted by water and cytotoxicity was found to be a major problem with the use of the plant since its extracts also reduced the primary cells used in the assay., Conclusion: It is confirmed that the plant has antiviral potentials against ASF virus and farmers' claims seem to have certain degree of veracity, but finding the best means of exploring the potential of the plant while reducing its cytotoxic effect in-vitro and in-vivo will be necessary.

Published
2013
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9. Assessment of the public knowledge, attitudes, and perceptions of Nigerians regarding preparedness for future pandemics.

Author

Odetokun, Ismail Ayoade, Oniyanda, Oluwatobi, Raza, Ali, Akpabio, Uduak, Musawa, Aliyu Ibrahim, Hambali, Idris Umar, Adamu, Shuaibu Gidado, Oyafajo, Lateefah, Alhaji, Nma Bida, and Fasina, Folorunso Oludayo

Subjects
PREVENTION of epidemics, HEALTH literacy, CROSS-sectional method, SCALE analysis (Psychology), INFLUENZA pandemic, 1918-1919, CRONBACH'S alpha, INTERVIEWING, STATISTICAL sampling, LOGISTIC regression analysis, DRUG resistance in microorganisms, RESIDENTIAL patterns, PUBLIC opinion, PANDEMIC preparedness, DESCRIPTIVE statistics, AGE distribution, CHI-squared test, ODDS ratio, EPIDEMICS, NIGERIANS, INFERENTIAL statistics, ZIKA virus infections, CONFIDENCE intervals, DATA analysis software, EDUCATIONAL attainment
Abstract

Introduction: Pandemics are global health crises that have caused millions of deaths, enormous socio-economic disruptions, and considerable public and global health security consequences. This study assessed Nigerians' knowledge, attitudes, and perceptions regarding preparedness for the next pandemics. Methods: A cross-sectional questionnaire-based national survey was conducted among 1276 respondents in Nigeria to determine public knowledge, attitudes, and perceptions of preparedness for future pandemics. Descriptive and inferential statistics were used for analyses. Results: Of the 1276 respondents to this survey, > 50% had not heard of the Spanish flu and Zika disease. Approximately half (594) of the respondents did not consider antimicrobial resistance a possible cause of future pandemics. Over an average proportion of respondents reported unsatisfactory knowledge (655, 51.3%) and poor perceptions (695, 54.5%) about pandemic preparedness. The respondents' good knowledge and satisfactory attitudes toward pandemic preparedness decreased with age. The respondents' education, age, and state of residence were significantly associated with good knowledge, satisfactory attitudes, and positive perceptions of pandemic preparedness with respondents with tertiary education levels being at least two times more likely to have these positive outcomes. Conclusion: This study revealed serious gaps in Nigerians' knowledge, attitudes, and perceptions of their readiness for upcoming pandemics. To protect Nigerians' health, emphasis should be placed on these issues by all stakeholders, including the government. [ABSTRACT FROM AUTHOR]

Published
2024
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10. Knowledge, attitude and practices of residents toward antimicrobial usage and resistance in Gondar, Northwest Ethiopia.

Author

Dejene, Haileyesus, Birhanu, Rediet, and Tarekegn, Zewdu Seyoum

Subjects
ANTI-infective agents, DRUG resistance, RESIDENTS (Medicine), EDUCATIONAL attainment, CROSS-sectional method
Abstract

Background: Antimicrobials are essential for human and animal health. Drug resistance to an antimicrobial agent follows the introduction of a new antimicrobial agent. Evidence suggests that the public plays an important role in the risk, increase, and spread of antimicrobial resistance. This study aimed to assess the knowledge, attitudes, and practices of the Gondar City residents regarding antimicrobial use and resistance. Methods: A cross-sectional study was conducted from April to July 2021 on 400 randomly selected Gondar city residents using a pretested semi-structured questionnaire. The descriptive and chi-square tests were used to analyse the data. Results: The response rate was one hundred percent. Approximately 75% of respondents were men, with 32% having completed secondary school. Nearly 74% and 35% of participants were married and worked in various government jobs. Furthermore, 48%, 54%, and 50% of respondents, respectively, had moderate knowledge, a positive attitude, and good practice concerning antimicrobial use and resistance. The chi-square analysis revealed a significant (p < 0.05) disparity between knowledge and educational level, marital status, and position in the house. The respondents' attitude levels were also significantly associated (p < 0.05) with their educational level, marital status, occupation, and position in the house. Respondents' practice levels were also significantly associated (p < 0.05) with their educational level and occupation. The study also found a significant relationship between respondents' knowledge and attitude (χ2 = 215.23, p ≤ 0.01), knowledge and practice (χ2 = 147.2, p ≤ 0.01), and attitude and practice (χ2 = 116.03, p ≤ 0.01). Conclusion: This study found that study participants had some misconceptions about antimicrobial use and resistance. As a result, both enforcing antimicrobial regulation and educating people about antimicrobial use are advised. [ABSTRACT FROM AUTHOR]

Published
2022
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11. Diverse non-typhoidal Salmonella serovars with multi-drug resistance potentials isolated from chicken faeces in Ogun State, Nigeria.

Author

Agbaje, M., Awosile, B., Kehinde, O. O., Omoshaba, E. O., Dipeolu, M. A., and Bankole, N. O.

Subjects
MULTIDRUG resistance, SALMONELLA, POULTRY farms, DRUG resistance in microorganisms, CHICKENS, FECES, SALMONELLA diseases
Abstract

This study was carried out in selected poultry farms to determine the prevalence, distribution and antimicrobial resistance patterns in Salmonella serovars in Ogun State, South-western Nigeria. A total of 200 faecal samples were aseptically collected from the four geographical zones of Ogun State, Nigeria. Seventy-eight Salmonella isolates spread across 39 serovars and representing a prevalence of 39% was recovered. Salmonella Urbana (n=7), Salmonella Kingston (n=6) and Salmonella Agama (n=5) serovars were more commonly isolated. Resistance was most common to ciprofloxacin (29.5%; n=23/78). Multi-drug resistance (MDR) was observed in 15.4% (n=12/78) of the isolates spread across 7 serovars: S. Kentucky, S. Telelkebir, S. Virchow, S. Blockley, S. Chomedey, S. Haifa, and S. Isangi. The study showed the diversity of Salmonella serovars and the increasing trend of antimicrobial resistance in poultry farms in Ogun State, Southwestern Nigeria. [ABSTRACT FROM AUTHOR]

Published
2021
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12. Infection Rates and Risk Factors for Infection Among Health Workers During Ebola and Marburg Virus Outbreaks: A Systematic Review.

Author

Selvaraj, Saranya A, Lee, Karen E, Harrell, Mason, Ivanov, Ivan, and Allegranzi, Benedetta

Subjects
EBOLA virus disease, MARBURG virus disease, VIRAL disease prevention, INDUSTRIAL hygiene, DISEASE outbreaks
Abstract

Background: Infection in health workers (HWs) has characterized outbreaks of Ebola virus disease (EVD) and Marburg virus disease (MVD). We conducted a systematic review to investigate infection and mortality rates and common exposure risks in HWs in EVD and MVD outbreaks.Methods: We searched the EMBASE and PubMed databases to identify articles posted before 27 December 2017, with no language restrictions. Data on the number, frequency, and mortality of HW infection and exposure risks were extracted.Results: Ninety-four articles related to 22 outbreaks were included. HW infections composed 2%-100% of cases in EVD and 5%-50% of cases in MVD outbreaks. Among exposed HWs, 0.6%-92% developed EVD, and 1%-10% developed MVD. HW infection rates were consistent through outbreaks. The most common exposure risk situations were inadequate personal protective equipment and exposure to patients with unrecognized EVD/MVD. Similar risks were reported in past EVD/MVD outbreaks and in the recent outbreak in West Africa.Conclusions: Many outbreaks reported high proportions of infected HWs. Similar HW infection rates and exposure risk factors in both past and recent EVD and MVD outbreaks emphasize the need to improve the implementation of appropriate infection control measures consistently across all healthcare settings. [ABSTRACT FROM AUTHOR]

Published
2018
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13. IoT-based cloud framework to control Ebola virus outbreak.

Author

Sareen, Sanjay, Sood, Sandeep K., and Gupta, Sunil Kumar

Abstract

Ebola is a deadly infectious virus that spreads very quickly through human-to-human transmission and sometimes death. The continuous detection and remote monitoring of infected patients are required in order to prevent the spread of Ebola virus disease (EVD). Healthcare services based on Internet of Things (IoT) and cloud computing technologies are emerging as a more effective and proactive solution which provides remote continuous monitoring of patients. A novel architecture based on Radio Frequency Identification Device (RFID), wearable sensor technology, and cloud computing infrastructure is proposed for the detection and monitoring of Ebola infected patients. The aim of this work is to prevent the spreading of the infection at the early stage of the outbreak. The J48 decision tree is used to evaluate the level of infection in a user depending on his symptoms. RFID is used to automatically sense the close proximity interactions (CPIs) between users. Temporal Network Analysis (TNA) is applied to describe and monitor the current state of the outbreak using the CPI data. The performance and accuracy of our proposed model are evaluated on Amazon EC2 cloud using synthetic data of two million users. Our proposed model provided 94 % accuracy for the classification and 92 % of the resource utilization. [ABSTRACT FROM AUTHOR]

Published
2018
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14. Influence of Referral Pathway on Ebola Virus Disease Case-Fatality Rate and Effect of Survival Selection Bias.

Author

Rudolf, Frauke, Damkjær, Mads, Lunding, Suzanne, de la Cour, Kenn Dornonville, Young, Alyssa, Brooks, Tim, Sesay, Tom, Salam, Alex P., Mishra, Sharmistha, Storgaard, Merete, and Dornonville de la Cour, Kenn

Subjects
EBOLA virus disease, PROGRESSION-free survival, MEDICAL referrals, SELECTION bias (Statistics), MEDICAL centers, EPIDEMICS, HEALTH facilities, MORTALITY, SURVIVAL analysis (Biometry), VIRAL load, RESEARCH bias, RETROSPECTIVE studies
Abstract

Case-fatality rates in Ebola treatment centers (ETCs) varied widely during the Ebola virus disease (EVD) outbreak in West Africa. We assessed the influence of referral pathway on ETC case-fatality rates with a retrospective cohort of 126 patients treated at the Mathaska ETC in Port Loko, Sierra Leone. The patients consisted of persons who had confirmed EVD when transferred to the ETC or who had been diagnosed onsite. The case-fatality rate for transferred patients was 46% versus 67% for patients diagnosed onsite (p = 0.02). The difference was mediated by Ebola viral load at diagnosis, suggesting a survival selection bias. Comparisons of case-fatality rates across ETCs and clinical management strategies should account for potential survival selection bias. [ABSTRACT FROM AUTHOR]

Published
2017
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15. Evaluation of therapeutic potentials of plant extracts against poultry bacteria threatening public health.

Author

Abiala, Moses, Olayiwola, John, Babatunde, Oluwatoyin, Aiyelaagbe, Olapeju, and Akinyemi, Sunday

Subjects
DIAGNOSIS of escherichia coli diseases, PHYTOTHERAPY, THERAPEUTIC use of plant extracts, PSEUDOMONAS diseases, ALTERNATIVE medicine, ANTI-infective agents, BIOLOGICAL assay, CELL separation, DRUG resistance in microorganisms, POULTRY, PUBLIC health, DIAGNOSIS
Abstract

Background: Plant extracts were evaluated on poultry bacteria known to be threatening public health. This is to develop better bio-therapeutic agents from plant origin. Methods: Bacteria were isolated from water, feed, crop, gizzard and faeces of layer chicken. Isolates of interest (Escherichia coli, Salmonella enteritidis, Pseudomonas aeruginosa and Klebsiella oxytoca) were subjected to antibiotic susceptibility test. Resistant strains were further evaluated against different plant extracts in comparison to Meropenem (control) using agar diffusion method. Results: E. coli had the highest occurrence (53 %), followed by P. aeruginosa (25 %) and then S. enteritidis (13 %) while the least was K. oxytoca (9 %). Virtually all the isolates exhibited multi-antibiotic resistance (MAR) with gross resistance to Amoxicillin, Erythromycin and Cefuroxine. P. aeruginosa (75 %), S. enteritidis (75 %) and E. coli (63 %), had the highest MAR. Out of the 11 (100 %) plant extracts evaluated, 7 (64 %) were outstanding and showed varied levels of antibacterial activity. Specifically, methanol extract of Mangifera indica Julie cultivar leaf (MJLM) had the highest antibacterial activity, followed by Euadenia trifoliata stem bark (TB03) and Euadenia eminens leaf (TB05). P. aeruginosa was highly susceptible (81.81 %) to the extracts, followed by S. enteritidis (63.64 %) and then E. coli (27.27 %). Conclusions: MJLM and other extracts have proven to be promising extracts in which to search for bioactive components that can be developed into therapeutic drugs. This may help in the management of antibiotic resistant bacterial isolates from poultry chicken threatening public health. [ABSTRACT FROM AUTHOR]

Published
2016
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