We have come a long way since the start of the COVID-19 pandemic—from hoarding toilet paper and wiping down groceries to sending our children back to school and vaccinating billions. Over this period, the global community of epidemiologists and evolutionary biologists has also come a long way in understanding the complex and changing dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19. In this Review, we retrace our steps through the questions that this community faced as the pandemic unfolded. We focus on the key roles that mathematical modeling and quantitative analyses of empirical data have played in allowing us to address these questions and ultimately to better understand and control the pandemic.

Full genome sequences are increasingly used to track the geographic spread and transmission dynamics of viral pathogens. Here, with a focus on Israel, we sequenced 212 SARS-CoV-2 sequences and use them to perform a comprehensive analysis to trace the origins and spread of the virus. A phylogenetic analysis including thousands of globally sampled sequences allowed us to infer multiple independent introductions into Israel, followed by local transmission. Returning travelers from the U.S. contributed dramatically more to viral spread relative to their proportion in incoming infected travelers. Using phylodynamic analysis, we estimated that the basic reproduction number of the virus was initially around ~2.0-2.6, dropping by two-thirds following the implementation of social distancing measures. A comparison between reported and model-estimated case numbers indicated high levels of transmission heterogeneity in SARS-CoV-2 spread, with between 1-10% of infected individuals resulting in 80% of secondary infections. Overall, our findings underscore the ability of this virus to efficiently transmit between and within countries, as well as demonstrate the effectiveness of social distancing measures for reducing its spread.

Whole genome sequencing in conjunction with traditional epidemiology has been used to reconstruct transmission networks of Mycobacterium tuberculosis during outbreaks. Given its low mutation rate, genetic diversity within M. tuberculosis outbreaks can be extremely limited – making it difficult to determine precisely who transmitted to whom. In addition to consensus SNPs (cSNPs), examining heterogeneous alleles (hSNPs) has been proposed to improve resolution. However, few studies have examined the potential biases in detecting these hSNPs. Here, we analysed genome sequence data from 25 specimens from British Columbia, Canada. Specimens were sequenced to a depth of 112–296×. We observed biases in read depth, base quality, strand distribution and read placement where possible hSNPs were initially identified, so we applied conservative filters to reduce false positives. Overall, there was phylogenetic concordance between the observed 2542 cSNP and 63 hSNP loci. Furthermore, we identified hSNPs shared exclusively by epidemiologically linked patients, supporting their use in transmission inferences. We conclude that hSNPs may add resolution to transmission networks, particularly where the overall genetic diversity is low.

248 words 17 Importance: 135 words 18 Main text: 4,747 words 19 Importance 39The evolution of influenza virus, in terms of single nucleotide variants and the reassortment of 40 gene segments, has been studied in detail. However, influenza is known to generate defective 41 viral genomes (DVGs) during replication, and little is known about how these genomes evolve 42 both within hosts and at the population level. Studies in animal models have indicated that 43 prophylactically or therapeutically administered DVGs can impact patterns of disease 44 progression. However, the formation of naturally-occurring DVGs, their evolutionary dynamics, 45and their contribution to disease severity in human hosts is not well understood. Here, we 46 identify the formation of de novo DVGs in samples from human challenge studies throughout the 47 course of infection. We analyze their evolutionary trajectories, revealing the important role of 48 genetic drift in shaping DVG populations during acute infections with well-adapted viral strains. 49 of the samples analyzed and were most common in the PB2, PB1, and PA gene segments. A 73 limitation of this study, however, is that it offered only a cross-sectional view of IAV DVG 74 populations. While it has been shown that Sendai virus DVG populations expand during the first 75 12 hours of infection in a mouse model (25), the evolution of IAV DVG populations within a 76 human host over the course of an infection has not been well characterized. 77Here, we report an analysis of IAV DVG populations identified from deep sequencing 78 data taken over the course of infection during two longitudinal human challenge studies with 79 different treatment cohorts. We observe the generation of de novo DVGs in nearly all subjects, 80 primarily in the polymerase gene segments (PB2, PB1, and PA). DVG populations were highly 81 variable over time in DVG species composition as well as in DVG species relative abundance. 82Over the course of infection, individual DVG species were observed to arise, fluctuate in 83 abundance, as well as disappear from the DVG population. Overall, we found no trend towards 84 decreasing diversity of DVG populations or towards shorter DVG species during the five days 85 post challenge, likely due to the dominance of stochastic effects. Furthermore, we were unable to 86 detect an association between DVG levels and peak viral titers, potentially due to the negative 87 feedback between DVG and wild-type virus. Similarly, higher DVG levels were not associated 88 with more severe symptoms. This study helps to illustrate the stochastic dynamics of DVG 89 populations within a host during acute infection with a well-adapted viral strain, a scenario under 90 which fitness variation in the wild-type virus population is expected to be relatively small. 91 Materials and Methods 92Ethics statement. The procedures followed in the human challenge studies were in accordance 93 with the Declaration of Helsinki. The studies were approved by the institutional review boards 94 (IRBs) of Duke Univer...

Evidence-based public health approaches that minimize the introduction and spread of new SARS-CoV-2 transmission clusters are urgently needed in the United States and other countries struggling with expanding epidemics. Here we analyze 247 full-genome SARS-CoV-2 sequences from two nearby communities in Wisconsin, USA, and find surprisingly distinct patterns of viral spread. Dane County had the 12th known introduction of SARS-CoV-2 in the United States, but this did not lead to descendant community spread. Instead, the Dane County outbreak was seeded by multiple later introductions, followed by limited community spread. In contrast, relatively few introductions in Milwaukee County led to extensive community spread. We present evidence for reduced viral spread in both counties, and limited viral transmission between counties, following the statewide Safer-at-Home public health order, which went into effect 25 March 2020. Our results suggest that early containment efforts suppressed the spread of SARS-CoV-2 within Wisconsin.