RESUMEN
Genome sequences from evolving infectious pathogens allow quantification of case introductions and local transmission dynamics. We sequenced 11,357 SARS-CoV-2 genomes from Switzerland in 2020 - the 6th largest effort globally. Using a representative subset of these data, we estimated viral introductions to Switzerland and their persistence over the course of 2020. We contrast these estimates with simple null models representing the absence of certain public health measures. We show that Switzerlands border closures de-coupled case introductions from incidence in neighboring countries. Under a simple model, we estimate an 86 - 98% reduction in introductions during Switzerlands strictest border closures. Furthermore, the Swiss 2020 partial lockdown roughly halved the time for sampled introductions to die out. Finally, we quantified local transmission dynamics once introductions into Switzerland occurred, using a novel phylodynamic model. We find that transmission slowed 35 - 63% upon outbreak detection in summer 2020, but not in fall. This finding may indicate successful contact tracing over summer before overburdening in fall. The study highlights the added value of genome sequencing data for understanding transmission dynamics. One Sentence SummaryPhylogenetic and phylodynamic methods quantify the drop in case introductions and local transmission with implementation of public health measures.
RESUMEN
We estimate the basic reproductive number and case counts for 15 distinct SARS-CoV-2 outbreaks, distributed across 10 countries and one cruise ship, based solely on phylodynamic analyses of genomic data. Our results indicate that, prior to significant public health interventions, the reproductive numbers for a majority (10) of these outbreaks are similar, with median posterior estimates ranging between 1.4 and 2.8. These estimates provide a view which is complementary to that provided by those based on traditional line listing data. The genomic-based view is arguably less susceptible to biases resulting from differences in testing protocols, testing intensity, and import of cases into the community of interest. In the analyses reported here, the genomic data primarily provides information regarding which samples belong to a particular outbreak. We observe that once these outbreaks are identified, the sampling dates carry the majority of the information regarding the reproductive number. Finally, we provide genome-based estimates of the cumulative case counts for each outbreak, which allow us to speculate on the amount of unreported infections within the populations housing each outbreak. These results indicate that for the majority (7) of the populations studied, the number of recorded cases is much bigger than the estimated cumulative case counts, suggesting the presence of unsequenced pathogen diversity in these populations. Significance StatementSince the beginning of the COVID-19 outbreak in late 2019, researchers around the globe have sought to estimate the rate at which the disease spread through populations prior to public health intervention, as quantified by the parameter R0. This is often estimated based on case count data and may be biased due to the presence of import cases. To overcome this, we estimate R0 by applying Bayesian phylodynamic methods to SARS-CoV-2 genomes which have been made available by laboratories worldwide. We provide R0 and absolute infection count estimates for 15 distinct outbreaks. These estimates contribute to our understanding of the baseline transmission dynamics of the disease, which will be critical in guiding future public health responses to the pandemic.
RESUMEN
The investigation of migratory patterns of the SARS-CoV-2 pandemic before border closures in Europe is a crucial first step towards an in-depth evaluation of border closure policies. Here we analyze viral genome sequences using a phylodynamic model with geographic structure to estimate the origin and spread of SARS-CoV-2 in Europe prior to border closures. Based on SARS-CoV-2 genomes, we reconstruct a partial transmission tree of the early pandemic, including inferences of the geographic location of ancestral lineages and the number of migration events into and between European regions. We find that the predominant lineage spreading in Europe has a most recent common ancestor in Italy and was probably seeded by a transmission event in either Hubei or Germany. We do not find evidence for preferential migration paths from Hubei into different European regions or from each European region to the others. Sustained local transmission is first evident in Italy and then shortly thereafter in the other European regions considered. Before the first border closures in Europe, we estimate that the rate of occurrence of new cases from within-country transmission was within the bounds of the estimated rate of new cases from migration. In summary, our analysis offers a view on the early state of the epidemic in Europe and on migration patterns of the virus before border closures. This information will enable further study of the necessity and timeliness of border closures. Significance StatementWe estimate the origin and spread of SARS-CoV-2 in Europe prior to border closures based on viral genome sequences using a phylodynamic model with geographic structure. We confirm that the predominant European outbreak most likely started in Italy and spread from there. This outbreak was probably seeded by a transmission event in either Hubei or Germany. In particular, we find that before the first border closures in Europe, the rate of new cases occurring from within-country transmission was within the estimated bounds on the rate of new migration cases.
