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. 2020 Sep 24;8(1):nwaa246.
doi: 10.1093/nsr/nwaa246. eCollection 2021 Jan.

On the founder effect in COVID-19 outbreaks: how many infected travelers may have started them all?

Affiliations

On the founder effect in COVID-19 outbreaks: how many infected travelers may have started them all?

Yongsen Ruan et al. Natl Sci Rev. .

Abstract

How many incoming travelers (I0 at time 0, equivalent to the 'founders' in evolutionary genetics) infected with SARS-CoV-2 who visit or return to a region could have started the epidemic of that region? I0 would be informative about the initiation and progression of epidemics. To obtain I0 , we analyze the genetic divergence among viral populations of different regions. By applying the 'individual-output' model of genetic drift to the SARS-CoV-2 diversities, we obtain I0 < 10, which could have been achieved by one infected traveler in a long-distance flight. The conclusion is robust regardless of the source population, the continuation of inputs (It for t > 0) or the fitness of the variants. With such a tiny trickle of human movement igniting many outbreaks, the crucial stage of repressing an epidemic in any region should, therefore, be the very first sign of local contagion when positive cases first become identifiable. The implications of the highly 'portable' epidemics, including their early evolution prior to any outbreak, are explored in the companion study (Ruan et al., personal communication).

Keywords: COVID-19; SARS-CoV-2; founder effect; genetic drift; population genetics.

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Figures

Figure 1.
Figure 1.
Schematic diagram of viral population divergence among regions. In G0 (generation 0), I0 = 8 and infected individuals arrive in regions 1–3 with 3, 5 and 7 of them, respectively, carrying the L-type virus. In the beginning, genetic drift is particularly strong and the frequency of L fluctuates as modeled by the Branching Process. G8 is about 5 weeks after the first arrival when the data are collected. After G8, the fluctuation is greatly dampened due to the large population size. In the later stage (after G20), even weak selection could drive gene frequency toward the fixation of the more contagious genotype. Regions 4–6 are not independent samples and are not included in the analysis (see Data of the main text).
Figure 2.
Figure 2.
The pairwise Fst distribution from the two datasets of Table 1. Fst is calculated by Equation (5). Given 10 regions, there are 45 (= 10 × 9/2) pairwise comparisons.
Figure 3.
Figure 3.
The Fst distribution at G20. For each parameter set of (I0, T, X0, s), we repeat the simulations 100 times. For all panels, I0 = 10, s = 0. Panel A–D, T = 20 and X0 ranges from 0.1 to 0.7. Panel E–H, X0 = 0.7, T ranges from 0 to 20. These eight panels show that neither X0 nor T would impact the Fst distribution much.
Figure 4.
Figure 4.
Comparisons between data and simulations with various I0 values. For all panels, s = 0 (no selection), X0 = 0.7 and T = 0. The value of I0 is shown next to each panel. Panel (A, C and E): the frequency of L type over time (100 repeats), the average is showed by the orange dotted line. Panel (B and D): Fst distribution; the simulation results are in black and the distributions from Dataset II (realistic data) are in orange. Panel (F): like panels B and D but Dataset I is used.
Figure 5.
Figure 5.
Same as Fig. 4 except that (i) s = 0.1 with selection favoring the L type; (ii) X0 = 0.5 so the L type would not reach fixation so quickly.

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