On the evolutionary epidemiology of SARS-CoV-2

Abstract

There is no doubt that the novel coronavirus SARS-CoV-2 that causes COVID-19 is mutating and thus has the potential to adapt during the current pandemic. Whether this evolution will lead to changes in the transmission, the duration, or the severity of the disease is not clear. This has led to considerable scientific and media debate, from raising alarms about evolutionary change to dismissing it. Here we review what little is currently known about the evolution of SARS-CoV-2 and extend existing evolutionary theory to consider how selection might be acting upon the virus during the COVID-19 pandemic. Although there is currently no definitive evidence that SARS-CoV-2 is undergoing further adaptation, continued evidence-based analysis of evolutionary change is important so that public health measures can be adjusted in response to substantive changes in the infectivity or severity of COVID-19.

Figure 1

Variability among SARS-CoV-2 genomes. Genetic diversity segregating among SARS-CoV-2 genomes (from Nextstrain [8]). Horizontal axis is genomic location and vertical axis is entropy, an information-based measure that highlights sites exhibiting the most genetic variation: (A) at the nucleotide level, (B) at the amino acid level.

Figure 2

Epidemiological model for COVID-19. Susceptible individuals, S, enter the exposed class, E, upon infection after contact with infected individuals (as indicated by dashed curves, with transmission rates β_i). A proportion of new infections, f, remain asymptomatic, A, whereas the remainder become pre-symptomatic, P. The latter eventually progress to the symptomatic stage, I, and die from the disease at rate α (referred to as ‘virulence’). All other individuals eventually recover, R, and are assumed to be immune. Transition rates between disease classes are denoted by κ_i. As shown in the Supplemental Information, selection acting on these traits favors increased transmission and a briefer interval between exposure and infectiousness (red parameters are selected to increase). Selection also favors mutations that keep individuals in the infectious stage longer (green parameters are selected to decrease), including reduced virulence. As long as pre-symptomatic and symptomatic individuals are the major source of new infections, selection also favors a reduction in the proportion of asymptomatic individuals (f).

Figure 3

Simulations of SARS-CoV-2 evolution without pleiotropy. Evolutionary and epidemiological dynamics of a mutation that only affects a single trait, either in the absence (top panels) or presence (bottom) of periodic social distancing. Parameters of the resident virus (r) are chosen to be roughly consistent with available data: β^r_p= 3β^r_I= 10β^r_A = 1, κ^r_E= 0.25, κ^r_P= 1, κ^r_I= 0.2, κ^r_A= 0.11, ƒ^r= 0.2, and α^r= 0.005. This yields a basic reproduction number R^r₀ ≈ 2.3. A mutant allele increases transmission in panels (A) and (E) (all transmission rates multiplied by 1.2), decreases the fraction of asymptomatic cases in panels (B) and (F) (ƒ^m = 0.1), progresses more slowly through the pre-symptomatic stage in panels (C) and (G) (κ^m_P= 0.67), and decreases virulence in panels (D) and (H) (α^m = 0). In the latter case, mutants that reduce mortality do spread, but selection is very weak and the effects are hardly visible. Grey regions indicate periods of effective social distancing (all transmission rates are reduced by 60%). Curves show the numbers of infected (red) and susceptible individuals (blue), measured as a fraction of the initial number of susceptibles, as well as the frequency of the mutation (black). Solid curves are with evolution (dashed are without evolution, for reference). Inset bar chart shows cumulative deaths, with ticks at 1% intervals (pink, without evolution; red, with evolution).

Figure 4

Simulations of SARS-CoV-2 evolution with pleiotropy. Evolutionary and epidemiological dynamics of a mutation with pleiotropic effects on both transmission (all transmission rates multiplied by 1.2) and virulence, either doubling virulence (α^m = 0.01, panels (A) and (C)) or eliminating it (α^m = 0, panels (B) and (D)). See Figure 3 for additional details.