Anchoring Convenience Survey Samples to a Baseline Census for Vaccine Coverage Monitoring in Global Health

TL;DR

This study evaluates hybrid anchoring survey methods to improve vaccine coverage estimates in rural Africa, demonstrating their robustness under various bias and response scenarios.

Contribution

It introduces and assesses calibration-weighted and logistic regression-based estimators anchoring surveys to baseline censuses, enhancing vaccine coverage monitoring.

Findings

Estimators maintained low bias (<2%) under high bias scenarios.

Performance improved with increased village sampling proportion.

High accuracy and coverage achieved at OR≤1.2 with moderate response rates.

Abstract

While conducting probabilistic surveys is the gold standard for assessing vaccine coverage, implementing these surveys poses challenges for global health. There is a need for more convenient option that is more affordable and practical. Motivated by childhood vaccine monitoring programs in rural areas of Chad and Niger, we conducted a simulation study to evaluate calibration-weighted design-based and logistic regression-based imputation estimators of the finite-population proportion of MCV1 coverage. These estimators use a hybrid approach that anchors non-probabilistic follow-up survey to probabilistic baseline census to account for selection bias. We explored varying degrees of non-ignorable selection bias (odds ratios from 1.0-1.5), percentage of villages sampled (25-75%), and village-level survey response rate to the follow-up survey (50-80%). Our performance metrics included bias, coverage, and proportion of simulated 95% confidence intervals falling within equivalence margins of 5% and 7.5% (equivalence tolerance). For both adjustment methods, the performance worsened with higher selection bias and lower response rate and generally improved as a larger proportion of villages was sampled. Under the worst scenario with 1.5 OR, 25% village sampled, and 50% survey response rate, both methods showed empirical biases of 2% or less, below 95% coverage, and low equivalence tolerances. In more realistic scenarios, the performance of our estimators showed lower biases and close to 95% coverage. For example, at OR$\leq$1.2, both methods showed high performance, except at the lowest village sampling and participation rates. Our simulations show that a hybrid anchoring survey approach is a feasible survey option for vaccine monitoring.