Full genome viral sequences inform patterns of SARS-CoV-2 spread into and within Israel

Miller, Danielle; Martin, Michael; Harel, Noam; Tirosh, Omer; Kustin, Talia; Meir, Moran; Sorek, Nadav; Gefen-Halevi, Shiraz; Amit, Sharon; Vorontsov, Olesya; Shaag, Avraham; Wolf, Dana; Peretz, Avi; Shemer‐Avni, Yonat; Roif-Kaminsky, Diana; Kopelman, Naama M.; Huppert, Amit; Koelle, Katia; Stern, Adi

doi:10.1038/s41467-020-19248-0

Cited by 118 publications

(99 citation statements)

References 41 publications

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“…We obtained 212 complete genomes (Fig 1B), mostly from samples with higher viral loads (Fig 1B). Consensus genomes had a median of 7 substitutions relative to the Wuhan-Hu-1/2019 reference sequence (range [4][5][6][7][8][9][10][11][12]. Phylogenetic analysis of whole consensus genomes identified 10 unique evolutionary lineages in our cohort (lineages determined by the PANGOLIN system, see Methods; Fig 1C).…”

Section: Resultsmentioning

confidence: 99%

“…Over the course of the SARS-CoV-2 pandemic, whole genome sequencing has been widely used to characterize patterns of broad geographic spread, transmission in local clusters, and the spread of specific viral variants [1][2][3][4][5][6]. Early reports demonstrated that SARS-CoV-2 exhibits genetic diversity within infected hosts, but this has been less studied than consensus-level genomic diversity [7].…”

Section: Introductionmentioning

confidence: 99%

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Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts

et al. 2021

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Analysis of SARS-CoV-2 genetic diversity within infected hosts can provide insight into the generation and spread of new viral variants and may enable high resolution inference of transmission chains. However, little is known about temporal aspects of SARS-CoV-2 intrahost diversity and the extent to which shared diversity reflects convergent evolution as opposed to transmission linkage. Here we use high depth of coverage sequencing to identify within-host genetic variants in 325 specimens from hospitalized COVID-19 patients and infected employees at a single medical center. We validated our variant calling by sequencing defined RNA mixtures and identified viral load as a critical factor in variant identification. By leveraging clinical metadata, we found that intrahost diversity is low and does not vary by time from symptom onset. This suggests that variants will only rarely rise to appreciable frequency prior to transmission. Although there was generally little shared variation across the sequenced cohort, we identified intrahost variants shared across individuals who were unlikely to be related by transmission. These variants did not precede a rise in frequency in global consensus genomes, suggesting that intrahost variants may have limited utility for predicting future lineages. These results provide important context for sequence-based inference in SARS-CoV-2 evolution and epidemiology.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts

et al. 2021

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“… 4 6 37 For example, if only 20% of the population were able to develop a sufficient viral load to infect others, then protective immunity in this subpopulation would be sufficient for an innocuous endemic equilibrium. 47 Furthermore, if seroconversion occurs largely in the subpopulation spreading the virus, 48 a sufficient herd immunity may only require a seroprevalence of around 10% of the effective population (right panel of figure 4 ). In short, one might challenge the assumption that COVID-19 is spread homogeneously across the population.…”

Section: Heterogeneity In Exposure Susceptibility and Transmissionmentioning

confidence: 99%

‘Dark matter’, second waves and epidemiological modelling

2020

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Recent reports using conventional Susceptible, Exposed, Infected and Removed models suggest that the next wave of the COVID-19 pandemic in the UK could overwhelm health services, with fatalities exceeding the first wave. We used Bayesian model comparison to revisit these conclusions, allowing for heterogeneity of exposure, susceptibility and transmission. We used dynamic causal modelling to estimate the evidence for alternative models of daily cases and deaths from the USA, the UK, Brazil, Italy, France, Spain, Mexico, Belgium, Germany and Canada over the period 25 January 2020 to 15 June 2020. These data were used to estimate the proportions of people (i) not exposed to the virus, (ii) not susceptible to infection when exposed and (iii) not infectious when susceptible to infection. Bayesian model comparison furnished overwhelming evidence for heterogeneity of exposure, susceptibility and transmission. Furthermore, both lockdown and the build-up of population immunity contributed to viral transmission in all but one country. Small variations in heterogeneity were sufficient to explain large differences in mortality rates. The best model of UK data predicts a second surge of fatalities will be much less than the first peak. The size of the second wave depends sensitively on the loss of immunity and the efficacy of Find-Test-Trace-Isolate-Support programmes. In summary, accounting for heterogeneity of exposure, susceptibility and transmission suggests that the next wave of the SARS-CoV-2 pandemic will be much smaller than conventional models predict, with less economic and health disruption. This heterogeneity means that seroprevalence underestimates effective herd immunity and, crucially, the potential of public health programmes.

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“…Over the course of the SARS-CoV-2 pandemic, whole genome sequencing has been widely used to characterize patterns of broad geographic spread, transmission in local clusters, and the spread of specific viral variants 1 – 6 . Early reports demonstrated that SARS-CoV-2 exhibits genetic diversity within infected hosts, but this has been less studied than consensus-level genomic diversity 7 .…”

Section: Introductionmentioning

confidence: 99%

Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts

Valesano

Rumfelt

Dimcheff

et al. 2021

Preprint

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Analysis of SARS-CoV-2 genetic diversity within infected hosts can provide insight into the generation and spread of new viral variants and may enable high resolution inference of transmission chains. However, little is known about temporal aspects of SARS-CoV-2 intrahost diversity and the extent to which shared diversity reflects convergent evolution as opposed to transmission linkage. Here we use high depth of coverage sequencing to identify within-host genetic variants in 325 specimens from hospitalized COVID-19 patients and infected employees at a single medical center. We validated our variant calling by sequencing defined RNA mixtures and identified a viral load threshold that minimizes false positives. By leveraging clinical metadata, we found that intrahost diversity is low and does not vary by time from symptom onset. This suggests that variants will only rarely rise to appreciable frequency prior to transmission. Although there was generally little shared variation across the sequenced cohort, we identified intrahost variants shared across individuals who were unlikely to be related by transmission. These variants did not precede a rise in frequency in global consensus genomes, suggesting that intrahost variants may have limited utility for predicting future lineages. These results provide important context for sequence-based inference in SARS-CoV-2 evolution and epidemiology.

show abstract

Full genome viral sequences inform patterns of SARS-CoV-2 spread into and within Israel

Cited by 118 publications

References 41 publications

Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts

Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts

‘Dark matter’, second waves and epidemiological modelling

Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts

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