Can long-term COVID-19 vaccination be improved by serological surveillance?: a modeling study for Mozambique

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Abstract Seroprevalence provides an estimate of the population-level susceptibility to infection. In this study, we used a transmission model to examine the potential of using serological surveillance to inform the timing of COVID-19 boosters in Mozambique. We simulated using population-level seroprevalence thresholds as an estimate of the risk of outbreaks to trigger the timing of re-vaccination campaigns among older adults. We compare this approach to a strategy of re-vaccination at fixed time intervals. Vaccinating older adults each time the seroprevalence among older adults falls below 50% and 80% resulted in medians of 20% and 71% reduction in deaths, respectively, and number-needed-to-vaccinate to avert one death (NNT) of 1,499 (2.5 th -97.5 th centile:1,252-1,905) and 3,151 (2,943-3,429), respectively. In comparison, biennial and annual re-vaccination of older adults resulted in medians of 35% and 52% deaths averted, respectively, and NNTs of 1,443 (1,223-1,733) and 1,941 (1,805-2,112), respectively. We conducted sensitivity analysis over a range of antibody waning rates and epidemic scenarios and found that re-vaccination trigger thresholds of 50-60% seroprevalence are most likely to be efficient compared to fixed-time strategies. However, given marginal gains in efficiency even in the best-case scenarios, our results favor the use of simpler fixed-time strategies for long-term control of SARS-CoV-2.

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