Population Enumeration and Household Utilization Survey Methods in the Enterics for Global Health (EFGH): Shigella Surveillance Study

Ryan Dodd, Alex O. Awuor, Paul F. Garcia Bardales, Farhana Khanam, Donnie Mategula, Uma Onwuchekwa, Golam Sarwar, Mohammad Tahir Yousafzai, Naveed Ahmed, Hannah E. Atlas, Md Amirul Islam Bhuiyan, Josh M. Colston, Bakary Conteh, Manan Diawara, Nasrin Dilruba, Sarah Elwood, Irum Fatima, Erika Feutz, Sean R. Galagan, Shahinur HaqueMd Taufiqul Islam, Mehrab Karim, Belali Keita, Margaret N. Kosek, Karen L. Kotloff, Clement Lefu, Mamadou Mballow, Maureen Ndalama, Latif Ndeketa, Billy Ogwel, Caleb Okonji, Maribel Paredes Olortegui, Patricia B. Pavlinac, Tackeshy Pinedo Vasquez, James A. Platts-Mills, Firdausi Qadri, Sonia Qureshi, Elizabeth T. Rogawski McQuade, Shazia Sultana, Moussa Oumar Traore, Nigel A. Cunliffe, M. Jahangir Hossain, Richard Omore, Farah Naz Qamar, Milagritos D. Tapia, Pablo Peñataro Yori, K. Zaman, Christine J. McGrath

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)S17-S24
JournalOpen Forum Infectious Diseases
Volume11
Issue numberSupplement_1
DOIs
Publication statusPublished - 1 Mar 2024

Keywords

  • EFGH
  • healthcare utilization survey
  • hybrid surveillance design
  • population enumeration
  • Shigella

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