Inferring undiagnosed sources of COVID‑19 infections using viral genomes
The ongoing COVID‑19 pandemic is believed to be significantly influenced by asymptomatic SARS-CoV-2 patients. Understanding the role that asymptomatic patients play in the spread of the disease is vital for informing testing procedures. This project aims to build a tool to identify asymptomatic or undiagnosed patients by examining infected people around them without the need to directly test them, allowing health authorities to make rapid and better informed decisions. Viral genomes accumulate small changes, mutations, which usually are neutral in terms of disease progression. These can be used to trace transmission networks – individuals within the network will have acquired the disease from a single source and so will share the same variants. Current approaches do not detect utilize all variants especially the low-frequency ones and so rate less robust in building accurate transmission networks, and inferring transmission by asymptomatic carriers. By utilizing our previously developed tools and expertise in inferring HIV transmission networks, we will develop new mathematical models that are able to infer SARS-CoV-2 transmission. The sequencing data needed to map viral transmission will be acquired through a project funded by the Alberta Children’s Hospital Research Institute (ACHRI) and Genome Alberta, which aims to sequence 1,900 COVID‑19 patients. In collaboration with our partner organization, Public Health Laboratory under Alberta Health Services (ProvLab) who performs COVID‑19 diagnostics for the province of Alberta, we will obtain information on asymptomatic patients who have tested positive for the virus, remove them from our data, and then see if we can retrospectively identify them as likely contacts between the symptomatic individuals.. The resulting tools can be extended for use across Canada, and potentially even model future outbreaks of infections diseases in humans, livestock, and wildlife.