Modeling the evolution of SARS-CoV-2 under non-pharmaceutical interventions

Abstract

Social and behavioral non-pharmaceutical interventions (NPIs), such as mask-wearing, social distancing, and travel restrictions, as well as diagnostic tests, have been broadly implemented in response to the COVID-19 pandemic. Epidemiological models and data analysis affirm that wide adoption of NPIs helps to control the pandemic. However, SARS-CoV-2 has extensively demonstrated its ability to evolve. Therefore, it is crucial to examine how NPIs may affect the evolution of the virus. Such evolution could have important effects on the spread and impact of the pandemic. We used evo-epidemiological models to examine the effect of non-pharmaceutical interventions and testing on two evolutionary trajectories for SARS-CoV-2: attenuation and test evasion. Our results show that when stronger measures are taken, selection may act to reduce virulence. Additionally, the timely application of NPIs could significantly affect the competition between viral strains, favoring reduced virulence. Furthermore, a higher testing rate can select for a test-evasive viral strain, even if that strain is less infectious than the detectable competing strain. Importantly, if a less detectable strain evolves, epidemiological metrics such as confirmed daily cases may distort our assessment of the pandemic. Our results highlight the important implications NPIs can have on the evolution of SARS-CoV-2.

Dynamic governance of the first wave of Covid‐19 in Tunisia: An interoperability analysis

“…In this regard, Banholzer et al ( 2021 ), using a semi‐mechanistic Bayesian hierarchical model, showed that the combination of some nonpharmaceutical interventions leads to a strong reduction in the number of new infections. Furthermore, Gurevich et al ( 2021 ), using evo‐epidemiological model, have shown that the timely application of nonpharmaceutical measures could significantly manage the COVID‐19 crisis and may act to reduce virulence.…”

A Review of Matrix SIR Arino Epidemic Models

“…See Figure 4 Example 6. The SI aps QR model (with asymptomatic, pre-symptomatic, and symptomatic infectious) [37,56] (3.2). See Figure 5; The disease states are i = ( i a , i p , i s , q), and the model is defined by…”

Endogenous viral mutations, evolutionary selection, and containment policy design

“…This paper contributes to the literature on the theoretical modeling (the impact) of viral mutations and-more specifically-COVID-19 variants (e.g., Roche et al 2011;Basurto et al 2021;Buckee et al 2007;Cao et al 2021;Gabler et al 2021;Gurevich et al 2021;Gordo et al 2009;Griffin et al 2020;Halley et al 2021;Marquioni and Aguiar 2021;Pageaud et al 2021;Rella et al 2021;Rüdiger et al 2020;Williams et al 2021). My contribution is to (a) introduce a parsimonious model of endogenous viral evolution capturing both genetic and antigenic variation (i.e., evolving intrinsic and extrinsic fitness, see Smith et al 2004), as well as imperfect cross-immunity, and (b) use this framework to study aggregate dynamics and the direction of viral evolution under varying containment policies.…”

“…It may also, however, be single-peaked, a case in which the species continuously approaches the peak. Gurevich et al (2021) study the evolutionary competition between two distinct strains and find that increased testing favors a test-evasive strain.…”