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Dodd, Ryan, Awuor, Alex O, Garcia Bardales, Paul F, Khanam, Farhana, Mategula, Donnie, Onwuchekwa, Uma, Sarwar, Golam, Yousafzai, Mohammad Tahir, Ahmed, Naveed, Atlas, Hannah E, Amirul Islam Bhuiyan, Md, Colston, Josh M, Conteh, Bakary, Diawara, Manan, Dilruba, Nasrin, Elwood, Sarah, Fatima, Irum, Feutz, Erika, Galagan, Sean R, Haque, Shahinur, Taufiqul Islam, Md, Karim, Mehrab, Keita, Belali, Kosek, Margaret N, Kotloff, Karen L, Lefu, Clement, Mballow, Mamadou, Ndalama, Maureen, Ndeketa, Latif, Ogwel, Billy, Okonji, Caleb, Paredes Olortegui, Maribel, Pavlinac, Patricia B, Pinedo Vasquez, Tackeshy, Platts-Mills, James A, Qadri, Firdausi, Qureshi, Sonia, Rogawski McQuade, Elizabeth T, Sultana, Shazia, Traore, Moussa Oumar, Cunliffe, Nigel A, Jahangir Hossain, M, Omore, Richard, Qamar, Farah Naz, Tapia, Milagritos D, Peñataro Yori, Pablo, Zaman, K and McGrath, Christine J (2024) 'Population Enumeration and Household Utilization Survey Methods in the Enterics for Global Health (EFGH): Shigella Surveillance Study'. Open Forum Infectious Diseases, Vol 11, Issue Supplement_1, S17-S24.
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Abstract
Background: Accurate estimation of diarrhea incidence from facility-based surveillance requires estimating the population at risk and accounting for case patients who do not seek care. The Enterics for Global Health (EFGH) Shigella surveillance study will characterize population denominators and healthcare-seeking behavior proportions to calculate incidence rates of Shigella diarrhea in children aged 6–35 months across 7 sites in Africa, Asia, and Latin America.
Methods: The Enterics for Global Health (EFGH) Shigella surveillance study will use a hybrid surveillance design, supplementing facility-based surveillance with population-based surveys to estimate population size and the proportion of children with diarrhea brought for care at EFGH health facilities. Continuous data collection over a 24 month period captures seasonality and ensures representative sampling of the population at risk during the period of facility-based enrollments. Study catchment areas are broken into randomized clusters, each sized to be feasibly enumerated by individual field teams.
Conclusions: The methods presented herein aim to minimize the challenges associated with hybrid surveillance, such as poor parity between survey area coverage and facility coverage, population fluctuations, seasonal variability, and adjustments to care-seeking behavior.
| Item Type: | Article |
|---|---|
| Subjects: | WA Public Health > Health Administration and Organization > WA 530 International health administration WA Public Health > Statistics. Surveys > WA 900 Public health statistics WA Public Health > Statistics. Surveys > WA 950 Theory or methods of medical statistics. Epidemiologic methods |
| Faculty: Department: | Clinical Sciences & International Health > Malawi-Liverpool-Wellcome Programme (MLW) |
| Digital Object Identifer (DOI): | https://doi.org/10.1093/ofid/ofae018 |
| SWORD Depositor: | JISC Pubrouter |
| Depositing User: | JISC Pubrouter |
| Date Deposited: | 28 Mar 2024 12:11 |
| Last Modified: | 28 Mar 2024 12:11 |
| URI: | https://archive.lstmed.ac.uk/id/eprint/24262 |
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