Speaker
Description
As SARS-CoV-2 has transitioned from a novel pandemic-causing pathogen into an established (but incorrigible) member of the seasonal respiratory virus community, its evolutionary imperative has changed from transmitting between hosts as efficiently as possible to the more subtle task of immune evasion, whereby it may persist in human populations for the foreseeable future. Consequently post-acute sequelae of COVID-19 (PASC, colloquially ``long COVID'') will also continue to accrue, but exactly what the long-term burden is likely to be in human populations remains unclear. Still less obvious is the manner in which vaccination might shape future scenarios. In the framework of Living Evidence Synthesis, we developed simple compartmental models of COVID-19/PASC epidemiology which account for characteristics like the efficacy of immunity against reinfection, altered susceptibility to PASC between immunologically-naive and immunologically-trained individuals, and generalized duration of sequelae. We use the model to identify areas of uncertainty that have the most impact on PASC prevalence.
Because the emergence of new variants through mechanisms like immune escape produces apparent changes in traits such as vaccine efficacy, we account for evolution in the virus by treating parameters fed into the model as dynamic. We synthesize data on selection coefficients of variants to identify the direction and speed of changes to parameters over time. To predict how PASC dynamics are likely to respond to viral evolution, we simulate different tradeoffs among the most influential parameters. In doing so, we partition different evolutionary scenarios among futures with low or high PASC. The rapid emergence, ongoing high prevalence, and relentless evolution in SARS-CoV-2 implies the dynamics of PASC could remain persistently variable as the pandemic recedes further into the past.
