1921
image of A Multicountry Comparison of Three Coverage Evaluation Survey Sampling Methodologies for Neglected Tropical Diseases
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645

Abstract

Coverage evaluation surveys (CESs) are an important complement to routinely reported drug coverage estimates following mass drug administration for neglected tropical diseases (NTDs). Although the WHO recommends the routine use of CESs, they are rarely implemented. Reasons for this low uptake are multifaceted; one is uncertainty on the best sampling method. We conducted a multicountry study to compare the statistical characteristics, cost, time, and complexity of three commonly used CES sampling methods: the Expanded Program on Immunization’s (EPI’s) 30 × 7 cluster survey, a stratified design with systematic sampling within strata to enable lot quality assurance sampling (S-LQAS) decision rules, and probability sampling with segmentation (PSS). The three CES methods were used in Burkina Faso, Honduras, Malawi, and Uganda, and results were compared across the country sites. All three CES methods were found to be feasible. The S-LQAS approach took the least amount of time to complete and, consequently, was the least expensive; however, all three methods cost less than $5,000 per district. The PSS design resulted in an unbiased, equal-probability sample of the target populations. By contrast, the EPI approach had inherent bias related to the selection of households. Because of modifications needed to maintain feasibility, the S-LQAS method also resulted in a non-probability sample with less precision than the other two methods. Given the comparable cost and time of the three sampling methods and the statistical advantages of the PSS method, the PSS method was deemed to be the best for CESs in NTD programs.

[open-access] This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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http://instance.metastore.ingenta.com/content/journals/10.4269/ajtmh.19-0946
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  • Received : 19 Dec 2019
  • Accepted : 25 Jun 2020
  • Published online : 24 Aug 2020
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