Integrating Facility-Based Surveillance with Healthcare Utilization Surveys to Estimate Enteric Fever Incidence: Methods and Challenges

Jason R. Andrews, Caitlin Barkume, Alexander T. Yu, Samir K. Saha, Farah N. Qamar, Denise Garrett, Stephen P. Luby

Research output: Contribution to journalArticlepeer-review

37 Citations (Scopus)

Abstract

Cohort studies and facility-based sentinel surveillance are common approaches to characterizing infectious disease burden, but present trade-offs; cohort studies are resource-intensive and may alter disease natural history, while sentinel surveillance underestimates incidence in the population. Hybrid surveillance, whereby facility-based surveillance is paired with a community-based healthcare utilization assessment, represents an alternative approach to generating population-based disease incidence estimates with moderate resource investments. Here, we discuss this method in the context of the Surveillance for Enteric Fever in Asia Project (SEAP) study. We describe how data are collected and utilized to adjust enteric fever incidence for blood culture sensitivity, facility-based enrollment, and healthcare seeking, incorporating uncertainty in these parameters in the uncertainty around incidence estimates. We illustrate how selection of surveillance sites and their coverage may influence precision and bias, and we identify approaches in the study design and analysis to minimize and control for these biases. Rigorously designed hybrid surveillance systems can be an efficient approach to generating population-based incidence estimates for infectious diseases.

Original languageEnglish
Pages (from-to)S268-S276
JournalJournal of Infectious Diseases
Volume218
DOIs
Publication statusPublished - 10 Nov 2018

Keywords

  • bias
  • enteric fever
  • incidence
  • methods
  • surveillance
  • typhoid

Fingerprint

Dive into the research topics of 'Integrating Facility-Based Surveillance with Healthcare Utilization Surveys to Estimate Enteric Fever Incidence: Methods and Challenges'. Together they form a unique fingerprint.

Cite this