Dataset Information

Swiss public health measures associated with reduced SARS-CoV-2 transmission using genome data.

ABSTRACT: Genome sequences from evolving infectious pathogens allow quantification of case introductions and local transmission dynamics. We sequenced 11,357 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from Switzerland in 2020 - the sixth 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 contrasted these estimates with simple null models representing the absence of certain public health measures. We show that Switzerland's border closures de-coupled case introductions from incidence in neighboring countries. Under a simple model, we estimate an 86-98% reduction in introductions during Switzerland's strictest border closures. Furthermore, the Swiss 2020 partial lockdown roughly halved the time for sampled introductions to die out. Last, we quantified local transmission dynamics once introductions into Switzerland occurred, using a phylodynamic model. We found 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.

SUBMITTER: Nadeau SA

PROVIDER: S-EPMC9765449 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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Swiss public health measures associated with reduced SARS-CoV-2 transmission using genome data.

Nadeau Sarah A SA Vaughan Timothy G TG Beckmann Christiane C Topolsky Ivan I Chen Chaoran C Hodcroft Emma E Schär Tobias T Nissen Ina I Santacroce Natascha N Burcklen Elodie E Ferreira Pedro P Jablonski Kim Philipp KP Posada-Céspedes Susana S Capece Vincenzo V Seidel Sophie S Santamaria de Souza Noemi N Martinez-Gomez Julia M JM Cheng Phil P Bosshard Philipp P PP Levesque Mitchell P MP Kufner Verena V Schmutz Stefan S Zaheri Maryam M Huber Michael M Trkola Alexandra A Cordey Samuel S Laubscher Florian F Gonçalves Ana Rita AR Aeby Sébastien S Pillonel Trestan T Jacot Damien D Bertelli Claire C Greub Gilbert G Leuzinger Karoline K Stange Madlen M Mari Alfredo A Roloff Tim T Seth-Smith Helena H Hirsch Hans H HH Egli Adrian A Redondo Maurice M Kobel Olivier O Noppen Christoph C du Plessis Louis L Beerenwinkel Niko N Neher Richard A RA Beisel Christian C Stadler Tanja T

Science translational medicine 20230125 680

Genome sequences from evolving infectious pathogens allow quantification of case introductions and local transmission dynamics. We sequenced 11,357 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from Switzerland in 2020-the sixth 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 contrasted these estimates with simple null models representing the absence of c ...[more]

PMID: 36346321

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Project description:BackgroundStringent public health measures have been shown to influence the transmission of SARS-CoV-2 within school environments. We investigated the potential transmission of SARS-CoV-2 in a primary school setting with and without public health measures, using fine-grained physical positioning traces captured before the COVID-19 pandemic.MethodsApproximately 172.63 million position data from 98 students and six teachers from an open-plan primary school were used to predict a potential transmission of SARS-CoV-2 in primary school settings. We first estimated the daily average number of contacts of students and teachers with an infected individual during the incubation period. We then used the Reed-Frost model to estimate the probability of transmission per contact for the SARS-CoV-2 Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron variant (B.1.1.529). Finally, we built a binomial distribution model to estimate the probability of onward transmission in schools with and without public health measures, including face masks and physical distancing.ResultsAn infectious student would have 49.1 (95% confidence interval (CI) = 46.1-52.1) contacts with their peers and 2.00 (95% CI = 1.82-2.18) contacts with teachers per day. An infectious teacher would have 47.6 (95% CI = 45.1-50.0) contacts with students and 1.70 (95% CI = 1.48-1.92) contacts with their colleague teachers per day. While the probability of onward SARS-CoV-2 transmission was relatively low for the Alpha and Delta variants, the risk increased for the Omicron variant, especially in the absence of public health measures. Onward teacher-to-student transmission (88.9%, 95% CI = 88.6%-89.1%) and teacher-to-teacher SARS-CoV-2 transmission (98.4%, 95% CI = 98.5%-98.6%) were significantly higher for the Omicron variant without public health measures in place.ConclusionsOur findings illustrate that, despite a lower frequency of close contacts, teacher-to-teacher close contacts demonstrated a higher risk of transmission per contact of SARS-CoV-2 compared to student-to-student close contacts. This was especially significant with the Omicron variant, with onward transmission more likely occurring from teacher index cases than student index cases. Public health measures (eg, face masks and physical distance) seem essential in reducing the risk of onward transmission within school environments.

Project description:ObjectiveTo review the evidence on the effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality.DesignSystematic review and meta-analysis.Data sourcesMedline, Embase, CINAHL, Biosis, Joanna Briggs, Global Health, and World Health Organization COVID-19 database (preprints).Eligibility criteria for study selectionObservational and interventional studies that assessed the effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality.Main outcome measuresThe main outcome measure was incidence of covid-19. Secondary outcomes included SARS-CoV-2 transmission and covid-19 mortality.Data synthesisDerSimonian Laird random effects meta-analysis was performed to investigate the effect of mask wearing, handwashing, and physical distancing measures on incidence of covid-19. Pooled effect estimates with corresponding 95% confidence intervals were computed, and heterogeneity among studies was assessed using Cochran's Q test and the I2 metrics, with two tailed P values.Results72 studies met the inclusion criteria, of which 35 evaluated individual public health measures and 37 assessed multiple public health measures as a "package of interventions." Eight of 35 studies were included in the meta-analysis, which indicated a reduction in incidence of covid-19 associated with handwashing (relative risk 0.47, 95% confidence interval 0.19 to 1.12, I2=12%), mask wearing (0.47, 0.29 to 0.75, I2=84%), and physical distancing (0.75, 0.59 to 0.95, I2=87%). Owing to heterogeneity of the studies, meta-analysis was not possible for the outcomes of quarantine and isolation, universal lockdowns, and closures of borders, schools, and workplaces. The effects of these interventions were synthesised descriptively.ConclusionsThis systematic review and meta-analysis suggests that several personal protective and social measures, including handwashing, mask wearing, and physical distancing are associated with reductions in the incidence covid-19. Public health efforts to implement public health measures should consider community health and sociocultural needs, and future research is needed to better understand the effectiveness of public health measures in the context of covid-19 vaccination.Systematic review registrationPROSPERO CRD42020178692.

Dataset Information

Swiss public health measures associated with reduced SARS-CoV-2 transmission using genome data.

Publications

Swiss public health measures associated with reduced SARS-CoV-2 transmission using genome data.

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