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Using social contact data to improve the overall effect estimate of a cluster-randomized influenza vaccination program in Senegal
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1 2022
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Source: J R Stat Soc Ser C Appl Stat. 71(1):70-90
[PDF-1.24 MB]
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Alternative Title:J R Stat Soc Ser C Appl Stat
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Description:This study estimates the overall effect of two influenza vaccination programs consecutively administered in a cluster-randomized trial in western Senegal over the course of two influenza seasons from 2009-2011. We apply cutting-edge methodology combining social contact data with infection data to reduce bias in estimation arising from contamination between clusters. Our time-varying estimates reveal a reduction in seasonal influenza from the intervention and a nonsignificant increase in H1N1 pandemic influenza. We estimate an additive change in overall cumulative incidence (which was 6.13% in the control arm) of -0.68 percentage points during Year 1 of the study (95% CI: -2.53, 1.18). When H1N1 pandemic infections were excluded from analysis, the estimated change was -1.45 percentage points and was significant (95% CI, -2.81, -0.08). Because cross-cluster contamination was low (0-3% of contacts for most villages), an estimator assuming no contamination was only slightly attenuated (-0.65 percentage points). These findings are encouraging for studies carefully designed to minimize spillover. Further work is needed to estimate contamination - and its effect on estimation - in a variety of settings.
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Pubmed ID:35721226
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Pubmed Central ID:PMC9202735
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Volume:71
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Issue:1
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