People-centred surveillance: a narrative review of community-based surveillance among crisis-affected populations. Issue 10 (October 2020)

• Record Type: Journal Article
• Authors: Ratnayake, Ruwan; Tammaro, Meghan; Tiffany, Amanda; Kongelf, Anine; Polonsky, Jonathan A; McClelland, Amanda
• Is Part Of: Lancet. Volume 4:Issue 10(2020)
• Page Start: e483
• Page End: e495
• Publication Date: 2020-10
• Subjects: Global environmental change -- Periodicals; Climatic changes -- Government policy -- Periodicals; Ecology -- Periodicals; Human ecology -- Periodicals; Public health administration -- Periodicals; 304.2
• DOI: 10.1016/S2542-5196(20)30221-7
• Languages: English
• ISSNs: 2542-5196

Abstract

Abstract : Summary: Outbreaks of disease in settings affected by crises grow rapidly due to late detection and weakened public health systems. Where surveillance is underfunctioning, community-based surveillance can contribute to rapid outbreak detection and response, a core capacity of the International Health Regulations. We reviewed articles describing the potential for community-based surveillance to detect diseases of epidemic potential, outbreaks, and mortality among populations affected by crises. Surveillance objectives have included the early warning of outbreaks, active case finding during outbreaks, case finding for eradication programmes, and mortality surveillance. Community-based surveillance can provide sensitive and timely detection, identify valid signals for diseases with salient symptoms, and provide continuity in remote areas during cycles of insecurity. Effectiveness appears to be mediated by operational requirements for continuous supervision of large community networks, verification of a large number of signals, and integration of community-based surveillance within the routine investigation and response infrastructure. Similar to all community health systems, community-based surveillance requires simple design, reliable supervision, and early and routine monitoring and evaluation to ensure data validity. Research priorities include the evaluation of syndromic case definitions, electronic data collection for community members, sentinel site designs, and statistical techniques to counterbalance false positive signals.