An International Spatial Analysis of Welfare Spending’s Influence on Measles

BACKGROUND: National welfare policies have the potential to influence population health. Yet, no research has investigated the influence that welfare spending levels have on primary prevention interventions.

METHODS: This study uses generalized linear mixed model Bayesian analysis to explore how welfare spending influences the relationship between measles counts and measles vaccination rates at a national level. Furthermore, models include random effects to account for the nested structure of countries within regions. A conditional autoregressive model was also developed to test for the influence of spatial relationships among the variables of interest.

RESULTS: Analysis of the Bayesian Information Criterion (BIC) indicated that the non-spatial model (BIC=19743.090) was preferred over the spatial model (BIC = 24225.730). The final model found that both the first dose of measles vaccine (B = -0.835, 95% Cr. I. = -0.975, -0.699), public social protection (B = -0.936, 95% Cr. I. = -1.132, -0.744), and their interaction (B = -0.239, 95% Cr. I. -0.319, -0.156) had a negative influence on national measles counts.

CONCLUSIONS: This finding indicates that welfare spending may enhance primary prevention interventions, like measles vaccination.