Screening programs that test only the unvaccinated population have been proposed and implemented to mitigate SARS-CoV-2 spread, implicitly assuming that the unvaccinated population drives transmission. To evaluate this premise and quantify the impact of unvaccinated-only screening programs, we introduce a model for SARS-CoV-2 transmission through which we explore a range of transmission rates, vaccine effectiveness scenarios, rates of prior infection, and screening programs. We find that, as vaccination rates increase, the proportion of transmission driven by the unvaccinated population decreases, such that most community spread is driven by vaccine-breakthrough infections once vaccine coverage exceeds 55% (omicron) or 80% (delta), points which shift lower as vaccine effectiveness wanes. Thus, we show that as vaccination rates increase, the transmission reductions associated with unvaccinated-only screening decline, identifying three distinct categories of impact on infections and hospitalizations. More broadly, these results demonstrate that effective unvaccinated-only screening depends on population immunity, vaccination rates, and variant.

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In populations with mixed vaccination status, testing programs focused on only the unvaccinated population are being enacted to mitigate SARS-CoV-2 spread. However, it is not well understood how viral spread occurs in mixed-status populations, including the possible benefits of unvaccinated-only testing. Here, we analyze a model of SARS-CoV-2 transmission in which a variable fraction of the population is fully vaccinated and unvaccinated individuals are proactively tested for infection, while varying transmission rates, vaccine effectiveness (VE) parameters, and prior infection rates. This analysis reveals principles of viral spread in communities of mixed vaccination status, with implications for testing policies. As vaccination rates increase, the proportions of infections occurring in unvaccinated individuals and the amount of transmission driven by the unvaccinated both decrease, such that at ∼65-75% vaccine coverage, most infections are vaccine breakthroughs, and at ∼76-83% vaccine coverage, most community spread is driven by breakthrough infections, under baseline mRNA VE assumptions. These ranges shift lower with waning VE and higher with boosted VE. In highly vaccinated communities proactive unvaccinated-only testing had little impact on community spread. Instead, the benefits of weekly unvaccinated-only testing were restricted to regimes with high or moderate ongoing transmission due to lower vaccination rates and strongly depended on near-perfect test compliance. By evaluating a wide range of scenarios, this work finds broadly that resources devoted to routine unvaccinated-only testing could be reallocated when vaccine coverage is sufficiently high.

Yellow fever is a viral hemorrhagic fever transmitted by the Aedes aegypti mosquito. It has historically caused thousands of deaths throughout Africa, the Americas, Europe, and the Caribbean and continues to pose threats in Africa and Central and South America. The disease is most detrimental in densely populated areas with warmer climates where individuals have limited access to health care facilities. These conditions are exemplified by the yellow fever epidemic of 1878 in Memphis, Tennessee. The limited medical knowledge, warm climate, and densely populated urban areas greatly contributed to the magnitude of the epidemic that killed thousands. We have developed an ordinary differential equations model to simulate the dynamics of human and mosquito populations during a yellow fever outbreak using historical data. Additionally, we examined the use of insect repellent and vaccination as methods to reduce the severity of the outbreak. We examined the conditions under which the disease-free equilibria are stable for the complete model. We also used uncertainty and sensitivity analyses to quantify the reduction in cumulative infections and deaths due to the use of insect repellent and vaccination among humans.