Spillover
depression, depressed
REGRESSION
A second pre-registered hypothesis is that proximity to households treated with a cash incentive treatment would depress COVID-19 vaccination uptake. The trial design allows us to test this proposition. First, within each non-placebo-treated village cluster, the two-stage random cluster design assigns 25% of individuals to the placebo treatment. For each of the three treatments, we can estimate a cluster-level spillover effectThe ‘depression’ spillover conjecture implies that, on average, the participants receiving a placebo video in cash treatment villages will have lower vaccination rates than participants in placebo-treated villages. Panel A of Extended Data Table Extended Data Table Our second approach to measuring spillover is to survey, in phase III, individuals who received no video interventions. The ‘depression’ spillover conjecture implies that the average reported vaccination rates of non-treated individuals in cash-treated villages will be significantly lower than for those non-treated individuals in placebo-treated villages. Extended Data Table Extended Data Table We surveyed a randomly selected non-treated sample in the post-treatment phase III explicitly to measure spillover effects from the two cash treatments. The results are consistent with those reported for the placebo spillover estimations. There is no evidence that financial incentives to treated individuals depressed the non-treated individuals in the same village. In fact, there is some evidence to suggest that the verified vaccination rates of the non-treated individuals in the low cash treatment arms were positively affected by their proximity to individuals receiving financial incentives for the COVID-19 vaccine. We are sufficiently powered to conclude that this effect likely ranges between about 3% and 20%.The four multi-variable models in Table Spillover samples: odds ratios from regression of vaccine outcomes on treatments and covariatesNote: 95% CIs are reported in parentheses. The CIs are based on standard errors that are clustered at the village level. AIC, Akaike information criterion; SP, spillover.One possible mechanism that facilitates spillover is the proximity of village residents treated with financial incentives to those who were not. We might expect higher levels of spillover in smaller villages where news of cash incentives spread more easily. This suggests that the effect sizes of our spillover metrics would vary by the village’s population size. We interact village population with both sets of spillover metrics: (1) VCash.Health, VCash.HighCash and the VCash.LowCash and (2) VCash.HighCash and VCash.LowCash. Results are reported in Supplementary Table 