Using Serosurvey Data Triangulation for More Accurate Estimates of Vaccine Coverage: Measured and Modeled Coverage From Pakistan Household Surveys.

Household surveys remain an essential method for estimating vaccine coverage in developing countries. However, the resulting estimates have inevitable and currently unmeasurable information biases due to inaccuracies in recall, low retention of home-based records (HBRs; i.e., vaccination cards), and inaccurate recording of vaccination on HBRs. We developed an innovative method with which to overcome these biases, enhance the validity of survey results, and estimate true vaccine coverage using nested serological assessments of immune markers. We enrolled children aged 12-23 months in vaccine coverage surveys in Karachi, Pakistan, from January to December 2016. Vaccination history was collected through verbal recall by the caregiver and, when available, by HBR. One-third of survey participants were randomly enrolled for serological testing for anti-measles virus immunoglobulin G antibody. We applied Bayesian latent class models to evaluate the misalignment among measles vaccination histories derived by recall, HBRs, and measles serology and estimated true measles vaccine coverage. The model-based estimate of true measles vaccine coverage was 61.1% (95% credible interval: 53.5, 69.4) among all survey participants. The standard estimate of 73.2% (95% confidence interval: 71.3, 75.1) defined by positive recall or HBR documentation substantially overestimated the vaccine coverage. Researchers can correct for information biases using serological assessments in a subsample of survey participants and latent class analytical approaches.

Comparison of three rapid household survey sampling methods for vaccination coverage assessment in a peri-urban setting in Pakistan.

BACKGROUND: Household surveys are an essential tool for vaccine coverage monitoring in developing countries, and the World Health Organization (WHO) Expanded Program on Immunization (EPI) cluster survey design has been a default choice for decades. In response to methodological limitations of the traditional EPI sampling, alternative methods have been proposed, based on modern statistical and geographical techniques. This study compared the coverage estimates and the time efficiency of the EPI sampling design and two alternative methods: the compact segment sampling and innovative grid-based geographical information system (GIS) sampling. METHODS: We conducted a series of equal-sized concurrent prospective vaccine coverage surveys in Karachi, Pakistan, from January to December 2016, using traditional EPI, compact segment and grid-based GIS sampling methods. RESULTS: No differences in vaccine coverage estimates were identified across sampling methods in the peri-urban setting; however, due to stronger clustering effects and correct incorporation of sampling weights, the compact segment [design effect (DEFF) = 2.03] and the grid-based GIS surveys (DEFF = 1.72) had higher design effects and, therefore, appeared to have lower statistical precision than the traditional EPI surveys (DEFF = 1.57). To achieve the same level of apparent precision, data collection activities in the compact segment surveys would require more than twice the implementation time needed compared with the traditional EPI surveys. CONCLUSIONS: The precision of the EPI surveys appeared higher than that of the alternative methods because, under a questionable self-weighting assumption, the estimated design effect did not account for variable sampling weights. The compact segment and grid-based GIS methods were designed to improve randomness and representativeness of sampling households. Although these alternative methods did not result in coverage estimates that differed from the EPI survey results in the peri-urban setting, they have a lower risk of selection bias and therefore may be preferred.