Punya Alahakoon (Oxford) – Tracking West Nile Virus dynamics using viral loads from trapped mosquitoes

West Nile virus (WNV) is a vector-borne pathogen causing major outbreaks of West Nile fever worldwide. Although the transmission is maintained via birds and mosquitoes, human infection is possible.  Routine surveillance of WNV in the USA is performed by trapping mosquitos and testing for the presence of WNV during the transmission season by RT-qPCR testing. Apart from the general binary positive/negative outcome from these tests, they also generate cycle threshold (Ct) values. Motivated by findings from SARS-CoV-2 viral load dynamics in humans, we hypothesised that Ct values observed through routine pooled testing over time are sufficient to provide information on WNV epidemic dynamics. To investigate this, we introduce an agent-based model of mosquitoes and birds to model WNV epidemiological and viral load dynamics. In this model, we embed a within-host model of the viral load kinetics of mosquitoes. We simulate scenarios where mosquitoes are captured through routine surveillance and tested for WNV through pooled RT-qPCR testing, generating synthetic Ct values over time. We compare our model output to real Ct value data collected through WNV pooled testing in Nebraska in 2022 and 2023.