A simulation-based method to inform serosurvey designs for estimating the force of infection using existing blood samples

The extent to which dengue virus has been circulating globally and especially in Africa is largely unknown. Testing available blood samples from previous cross-sectional serological surveys offers a convenient strategy to investigate past dengue infections, as such serosurveys provide the ideal data to reconstruct the age-dependent immunity profile of the population and to estimate the average per-capita annual risk of infection: the force of infection (FOI), which is a fundamental measure of transmission intensity.In this study, we present a novel methodological approach to inform the size and age distribution of blood samples to test when samples are acquired from previous surveys. The method was used to inform SERODEN, a dengue seroprevalence survey which is currently being conducted in Ghana among other countries utilizing samples previously collected for a SARS-CoV-2 serosurvey.The method described in this paper can be employed to determine sample sizes and testing strategies for different diseases and transmission settings. The historical circulation of dengue virus is still poorly understood in many parts of the world, and age-stratified seroprevalence surveys can provide the data to quantify population exposure to dengue and its transmission intensity.In this work, we developed a simulation-based method that can be used to identify the sample sizes and age-distribution of the samples needed to obtain informative estimates of dengue force of infection from existing blood samples. We apply this method to data obtained from a SARS-CoV-2 serological survey, previously conducted in three cities in Ghana.The methods and code developed in this paper can be used to design serological surveys for dengue and other pathogens when using existing blood samples with accompanying information on age and location.