Detecting in-school transmission of SARS-CoV-2 from case ratios and documented clusters.
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ABSTRACT:
SUBMITTER: Johnson KE
PROVIDER: S-EPMC8095228 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background: Concern about the health impact of novel coronavirus SARS-CoV-2 has resulted in widespread enforced reductions in people's movement ("lockdowns"). However, there are increasing concerns about the severe economic and wider societal consequences of these measures. Some countries have begun to lift some of the rules on physical distancing in a stepwise manner, with differences in what these "exit strategies" entail and their timeframes. The aim of this work was to inform such exit strategies by exploring the types of indoor and outdoor settings where transmission of SARS-CoV-2 has been reported to occur and result in clusters of cases. Identifying potential settings that result in transmission clusters allows these to be kept under close surveillance and/or to remain closed as part of strategies that aim to avoid a resurgence in transmission following the lifting of lockdown measures. Methods: We performed a systematic review of available literature and media reports to find settings reported in peer reviewed articles and media with these characteristics. These sources are curated and made available in an editable online database. Results: We found many examples of SARS-CoV-2 clusters linked to a wide range of mostly indoor settings. Few reports came from schools, many from households, and an increasing number were reported in hospitals and elderly care settings across Europe. Conclusions: We identified possible places that are linked to clusters of COVID-19 cases and could be closely monitored and/or remain closed in the first instance following the progressive removal of lockdown restrictions. However, in part due to the limits in surveillance capacities in many settings, the gathering of information such as cluster sizes and attack rates is limited in several ways: inherent recall bias, biased media reporting and missing data.
| S-EPMC7327724 | biostudies-literature
Project description:BackgroundSeveral studies have reported SARS-CoV-2 outbreaks in schools, with a wide range of secondary attack rate (SAR; range: 0-100%). We aimed to examine key risk factors to better understand SARS-CoV-2 transmission in schools.MethodsWe collected records of 35 SARS-CoV-2 school outbreaks globally published from January 2020 to July 2021 and compiled information on hypothesized risk factors. We utilized the directed acyclic graph (DAG) to conceptualize risk mechanisms, used logistic regression to examine each risk-factor group, and further built multirisk models.ResultsThe best-fit model showed that the intensity of community transmission (adjusted odds ratio [aOR]: 1.11, 95% CI: 1.06-1.16, for each increase of 1 case per 10 000 persons per week) and individualism (aOR: 2.72, 95% CI: 1.50-4.95, above vs. below the mean) was associated higher risk, whereas preventive measures (aOR: 0.25, 95% CI: 0.19-0.32, distancing and masking vs. none) and higher population immunity (aOR: 0.57, 95% CI: 0.46-0.71) were associated with lower risk of SARS-CoV-2 transmission in schools. Compared with students in high schools, the aOR was 0.47 (95% CI: 0.23-0.95) for students in preschools and 0.90 (95% CI: 0.76-1.08) for students in primary schools.ConclusionsPreventive measures in schools (e.g., social distancing and mask wearing) and communal efforts to lower transmission and increase vaccination uptake (i.e., vaccine-induced population immunity) in the community should be taken to collectively reduce transmission and protect children in schools.
| S-EPMC9111692 | biostudies-literature
Project description:The unprecedented severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) global sequencing effort has suffered from an analytical bottleneck. Many existing methods for phylogenetic analysis are designed for sparse, static datasets and are too computationally expensive to apply to densely sampled, rapidly expanding datasets when results are needed immediately to inform public health action. For example, public health is often concerned with identifying clusters of closely related samples, but the sheer scale of the data prevents manual inspection and the current computational models are often too expensive in time and resources. Even when results are available, intuitive data exploration tools are of critical importance to effective public health interpretation and action. To help address this need, we present a phylogenetic heuristic that quickly and efficiently identifies newly introduced strains in a region, resulting in clusters of infected individuals, and their putative geographic origins. We show that this approach performs well on simulated data and yields results largely congruent with more sophisticated Bayesian phylogeographic modeling approaches. We also introduce Cluster-Tracker (https://clustertracker.gi.ucsc.edu/), a novel interactive web-based tool to facilitate effective and intuitive SARS-CoV-2 geographic data exploration and visualization across the USA. Cluster-Tracker is updated daily and automatically identifies and highlights groups of closely related SARS-CoV-2 infections resulting from the transmission of the virus between two geographic areas by travelers, streamlining public health tracking of local viral diversity and emerging infection clusters. The site is open-source and designed to be easily configured to analyze any chosen region, making it a useful resource globally. The combination of these open-source tools will empower detailed investigations of the geographic origins and spread of SARS-CoV-2 and other densely sampled pathogens.
| S-EPMC9214145 | biostudies-literature
Project description:A detailed understanding of how and when severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission occurs is crucial for designing effective prevention measures. Other than contact tracing, genome sequencing provides information to help infer who infected whom. However, the effectiveness of the genomic approach in this context depends on both (high enough) mutation and (low enough) transmission rates. Today, the level of resolution that we can obtain when describing SARS-CoV-2 outbreaks using just genomic information alone remains unclear. In order to answer this question, we sequenced forty-nine SARS-CoV-2 patient samples from ten local clusters in NW Spain for which partial epidemiological information was available and inferred transmission history using genomic variants. Importantly, we obtained high-quality genomic data, sequencing each sample twice and using unique barcodes to exclude cross-sample contamination. Phylogenetic and cluster analyses showed that consensus genomes were generally sufficient to discriminate among independent transmission clusters. However, levels of intrahost variation were low, which prevented in most cases the unambiguous identification of direct transmission events. After filtering out recurrent variants across clusters, the genomic data were generally compatible with the epidemiological information but did not support specific transmission events over possible alternatives. We estimated the effective transmission bottleneck size to be one to two viral particles for sample pairs whose donor-recipient relationship was likely. Our analyses suggest that intrahost genomic variation in SARS-CoV-2 might be generally limited and that homoplasy and recurrent errors complicate identifying shared intrahost variants. Reliable reconstruction of direct SARS-CoV-2 transmission based solely on genomic data seems hindered by a slow mutation rate, potential convergent events, and technical artifacts. Detailed contact tracing seems essential in most cases to study SARS-CoV-2 transmission at high resolution.
| S-EPMC8889950 | biostudies-literature
Project description:ObjectiveAn understanding of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) transmission in schools is important. It is often difficult, using epidemiological information alone, to determine whether cases associated with schools represent multiple introductions from the community or transmission within the school. We describe the use of whole genome sequencing (WGS) in multiple schools to investigate outbreaks of SARS-CoV-2 in the pre-Omicron period.Study designSchool outbreaks were identified for sequencing by local public health units based on multiple cases without known epidemiological links. Cases of SARS-CoV-2 from students and staff from 4 school outbreaks in Ontario underwent WGS and phylogenetic analysis. The epidemiological clinical cohort data and genomic cluster data are described to help further characterize these outbreaks.ResultsA total of 132 positive SARS-CoV-2 cases among students and staff from 4 school outbreaks were identified with 65 (49%) of cases able to be sequenced with high-quality genomic data. The 4 school outbreaks consisted of 53, 37, 21 and 21 positive cases; within each outbreak there were between 8 and 28 different clinical cohorts identified. Among the sequenced cases, between 3 and 7 genetic clusters, defined as different strains, were identified in each outbreak. We found genetically different viruses within several clinical cohorts.ConclusionsWGS, together with public health investigation, is a useful tool to investigate SARS-CoV-2 transmission within schools. Its early use has the potential to better understand when transmission may have occurred, can aid in evaluating how well mitigation interventions are working and has the potential to reduce unnecessary school closures when multiple genetic clusters are identified.
| S-EPMC9990487 | biostudies-literature
Project description:Hereby, we report a confirmed case of intrauterine SARS-CoV-2 transmission with rapid placental dysfunction and fetal distress.
| PRJEB40434 | ENA
Project description:In early 2020 many countries closed schools to mitigate the spread of SARS-CoV-2. Since then, governments have sought to relax the closures, engendering a need to understand associated risks. Using address records, we construct a network of schools in England connected through pupils who share households. We evaluate the risk of transmission between schools under different reopening scenarios. We show that whilst reopening select year-groups causes low risk of large-scale transmission, reopening secondary schools could result in outbreaks affecting up to 2.5 million households if unmitigated, highlighting the importance of careful monitoring and within-school infection control to avoid further school closures or other restrictions.
| S-EPMC8007691 | biostudies-literature
Project description:IntroductionLittle is known about the role of school-aged children and household transmission at the start of the SARS-CoV-2 pandemic. To evaluate for SARS-CoV-2 in school-aged children and assess household transmission, we performed reverse transcription polymerase chain reaction on 670 archived specimens that were collected between September 1, 2019 and June 30, 2020 as part of a community-based study.Case presentationA single SARS-CoV-2 case was detected in an 11-year-old girl on March 18, 2020, resulting in very low prevalence (0.15% [95% CI, 0.03-0.84]) in this population. This case was associated with SARS-CoV-2 detection in all other household members. Symptoms were reported as mild to moderate. Whole genome sequencing supported household transmission of near-identical viruses within the 19B clade.DiscussionThis case represents the earliest known household cluster of SARS-CoV2 in Wisconsin.ConclusionThis case suggests that household transmission associated with school-aged children may have contributed to wide seeding across populations.
| S-EPMC8721881 | biostudies-literature
Project description:BackgroundWe sought to decipher transmission pathways in healthcare-associated infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within our hospital by epidemiological work-up and complementary whole genome sequencing (WGS). We report the findings of the four largest epidemiologic clusters of SARS-CoV-2 transmission occurring during the second wave of the pandemic from 11/2020 to 12/2020.MethodsAt the University Hospital Basel, Switzerland, systematic outbreak investigation is initiated at detection of any nosocomial case of SARS-CoV-2 infection, as confirmed by polymerase chain reaction, occurring more than five days after admission. Clusters of nosocomial infections, defined as the detection of at least two positive patients and/or healthcare workers (HCWs) within one week with an epidemiological link, were further investigated by WGS on respective strains.ResultsThe four epidemiologic clusters included 40 patients and 60 HCWs. Sequencing data was available for 70% of all involved cases (28 patients and 42 HCWs), confirmed epidemiologically suspected in house transmission in 33 cases (47.1% of sequenced cases) and excluded transmission in the remaining 37 cases (52.9%). Among cases with identical strains, epidemiologic work-up suggested transmission mainly through a ward-based exposure (24/33, 72.7%), more commonly affecting HCWs (16/24, 66.7%) than patients (8/24, 33.3%), followed by transmission between patients (6/33, 18.2%), and among HCWs and patients (3/33, 9.1%, respectively two HCWs and one patient).ConclusionsPhylogenetic analyses revealed important insights into transmission pathways supporting less than 50% of epidemiologically suspected SARS-CoV-2 transmissions. The remainder of cases most likely reflect community-acquired infection randomly detected by outbreak investigation. Notably, most transmissions occurred between HCWs, possibly indicating lower perception of the risk of infection during contacts among HCWs.
| S-EPMC10119817 | biostudies-literature
Project description:BackgroundThe first cases of COVID-19 caused by the SARS-CoV-2 virus were reported in China in December 2019. The disease has since spread globally. Many countries have instated measures to slow the spread of the virus. Information about the spread of the virus in a country can inform the gradual reopening of a country and help to avoid a second wave of infections. Our study focuses on Denmark, which is opening up when this study is performed (end-May 2020) after a lockdown in mid-March.MethodsWe perform a phylogenetic analysis of 742 publicly available Danish SARS-CoV-2 genome sequences and put them into context using sequences from other countries.ResultsOur findings are consistent with several introductions of the virus to Denmark from independent sources. We identify several chains of mutations that occurred in Denmark. In at least one case we find evidence that the virus spread from Denmark to other countries. A number of the mutations found in Denmark are non-synonymous, and in general there is a considerable variety of strains. The proportions of the most common haplotypes remain stable after lockdown.ConclusionEmploying phylogenetic methods on Danish genome sequences of SARS-CoV-2, we exemplify how genetic data can be used to trace the introduction of a virus to a country. This provides alternative means for verifying existing assumptions. For example, our analysis supports the hypothesis that the virus was brought to Denmark by skiers returning from Ischgl. On the other hand, we identify transmission routes which suggest that Denmark was part of a network of countries among which the virus was being transmitted. This challenges the common narrative that Denmark only got infected from abroad. Our analysis concerning the ratio of haplotypes does not indicate that the major haplotypes appearing in Denmark have a different degree of virality.
| S-EPMC7595399 | biostudies-literature