Modeling and presentation of vaccination coverage estimates using data from household surveys

• Published in: Vaccine Vol. 39; no. 18; pp. 2584 - 2594
• Main Authors: Dong, Tracy Qi, Wakefield, Jon
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Ltd 28.04.2021; Elsevier Limited
• Subjects: Allergy and Immunology; Bayesian analysis; Bayesian model-based geostatistics; Bayesian theory; Censuses; Clusters; Estimates; Geostatistics; Global positioning systems; GPS; health surveys; High-resolution maps; Households; Immunization; Mathematical models; Measles; Modelling; Nigeria; Partial differential equations; Polls & surveys; Random variables; Rural areas; Sampling designs; Small area estimation; Survey sampling; Uncertainty; Vaccination; Vaccination coverage; vaccines; Nigeria; Uncertainty; Vaccination coverage; Bayesian model-based geostatistics; Small area estimation; Survey sampling; High-resolution maps
• DOI: 10.1016/j.vaccine.2021.03.007
• ISSN: 0264-410X; 1873-2518

•Modeling survey stratification and clustering improves coverage estimation.•High-resolution coverage maps based on survey data often have large uncertainties.•Visualizing posterior distributions of coverage estimates help reveal uncertainties.•A new presentation method is proposed to compare and control overall map precision. It is becoming increasingly popular to produce high-resolution maps of vaccination coverage by fitting Bayesian geostatistical models to data from household surveys. Usually, the surveys adopt a stratified cluster sampling design. We discuss a number of crucial choices with respect to two key aspects of the map production process: the acknowledgement of the survey design in modeling, and the appropriate presentation of estimates and their uncertainties. Specifically, we consider the importance of accounting for urban/rural stratification and cluster-level non-spatial excess variation in survey outcomes, when fitting geostatistical models. We also discuss the trade-off between the geographical scale and precision of model-based estimates, and demonstrate visualization methods for mapping and ranking that emphasize the probabilistic interpretation of results. A novel approach to coverage map presentation is proposed to allow comparison and control of the overall map uncertainty. We use measles vaccination coverage in Nigeria as a motivating example and illustrate the different issues using data from the 2018 Nigeria Demographic and Health Survey.