Measuring coverage in MNCH: design, implementation, and interpretation challenges associated with tracking vaccination coverage using household surveys

PLoS Med. 2013;10(5):e1001404. doi: 10.1371/journal.pmed.1001404. Epub 2013 May 7.

Abstract

Vaccination coverage is an important public health indicator that is measured using administrative reports and/or surveys. The measurement of vaccination coverage in low- and middle-income countries using surveys is susceptible to numerous challenges. These challenges include selection bias and information bias, which cannot be solved by increasing the sample size, and the precision of the coverage estimate, which is determined by the survey sample size and sampling method. Selection bias can result from an inaccurate sampling frame or inappropriate field procedures and, since populations likely to be missed in a vaccination coverage survey are also likely to be missed by vaccination teams, most often inflates coverage estimates. Importantly, the large multi-purpose household surveys that are often used to measure vaccination coverage have invested substantial effort to reduce selection bias. Information bias occurs when a child's vaccination status is misclassified due to mistakes on his or her vaccination record, in data transcription, in the way survey questions are presented, or in the guardian's recall of vaccination for children without a written record. There has been substantial reliance on the guardian's recall in recent surveys, and, worryingly, information bias may become more likely in the future as immunization schedules become more complex and variable. Finally, some surveys assess immunity directly using serological assays. Sero-surveys are important for assessing public health risk, but currently are unable to validate coverage estimates directly. To improve vaccination coverage estimates based on surveys, we recommend that recording tools and practices should be improved and that surveys should incorporate best practices for design, implementation, and analysis.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Child
  • Child Health Services / trends*
  • Child, Preschool
  • Data Interpretation, Statistical
  • Developing Countries*
  • Family Characteristics
  • Global Health
  • Health Care Surveys / trends*
  • Health Services Accessibility / trends
  • Health Services Research / methods
  • Health Services Research / trends*
  • Humans
  • Immunization Schedule
  • Infant
  • Infant, Newborn
  • Patient Acceptance of Health Care
  • Program Evaluation
  • Reproducibility of Results
  • Research Design
  • Sample Size
  • Selection Bias
  • Socioeconomic Factors
  • Surveys and Questionnaires
  • Time Factors
  • Vaccination / trends*

Grants and funding

FTC and DAR were contracted by The Bill & Melinda Gates Foundation to undertake this work. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The views expressed in this paper are those of the individual authors and not necessarily those of the US Food and Drug Administration.