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MEASURING COVERAGE IN MNCH: TOTAL SURVEY ERROR AND THE INTERPRETATION OF INTERVENTION COVERAGE ESTIMATES FROM HOUSEHOLD SURVEYS

Wednesday, 12th of June 2013

• MEASURING COVERAGE IN MNCH: TOTAL SURVEY ERROR AND THE INTERPRETATION OF INTERVENTION COVERAGE ESTIMATES FROM HOUSEHOLD SURVEYS

Full text, with figures, is at

http://www.ploscollections.org/article/info%3Adoi%2F10.1371%2Fjournal.pmed.1001386

Abstract

Nationally representative household surveys are increasingly relied upon to measure maternal, newborn, and child health (MNCH) intervention coverage at the population level in low- and middle-income countries. Surveys are the best tool we have for this purpose and are central to national and global decision making. However, all survey point estimates have a certain level of error (total survey error) comprising sampling and non-sampling error, both of which must be considered when interpreting survey results for decision making. In this review, we discuss the importance of considering these errors when interpreting MNCH intervention coverage estimates derived from household surveys, using relevant examples from national surveys to provide context. Sampling error is usually thought of as the precision of a point estimate and is represented by 95% confidence intervals, which are measurable. Confidence intervals can inform judgments about whether estimated parameters are likely to be different from the real value of a parameter. We recommend, therefore, that confidence intervals for key coverage indicators should always be provided in survey reports. By contrast, the direction and magnitude of non-sampling error is almost always unmeasurable, and therefore unknown. Information error and bias are the most common sources of non-sampling error in household survey estimates and we recommend that they should always be carefully considered when interpreting MNCH intervention coverage based on survey data. Overall, we recommend that future research on measuring MNCH intervention coverage should focus on refining and improving survey-based coverage estimates to develop a better understanding of how results should be interpreted and used.

Citation: Eisele TP, Rhoda DA, Cutts FT, Keating J, Ren R, et al. (2013) Measuring Coverage in MNCH: Total Survey Error and the Interpretation of Intervention Coverage Estimates from Household Surveys. PLoS Med 10(5): e1001386. doi:10.1371/journal.pmed.1001386

Academic Editor: Nyovani Madise, Professor of Demography and Social Statistics, University of Southampton, United Kingdom

Published: May 7, 2013

Copyright: © 2013 Eisele et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: No specific funding was received for the writing of this paper. TPE and JK were funded by the Malaria Control and Evaluation Partnership in Africa (MACEPA), a PATH project, from funding from the Bill & Melinda Gates Foundation. This work was conducted under the auspices of the Child Health Epidemiology Reference Group (CHERG) for WHO and UNICEF. CHERG receives financial support from the Bill & Melinda Gates Foundation through their grant to the US Fund for UNICEF. No funders were involved in in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations: AIS, AIDS Indicator Survey/s; DHS, Demographic and Health Survey/s; EPI, Expanded Programme on Immunization; ITN, insecticide-treated mosquito net; LQAS, Lot Quality Assurance Sampling; MICS, Multiple Indicator Cluster Survey/s; MIS, Malaria Indicator Survey/s; MNCH, maternal, newborn, and child health

Provenance: Submitted as part of a sponsored Collection; externally reviewed.

This paper is part of the PLOS Medicine “Measuring Coverage in MNCH” Collection