Factors influencing SARS-CoV-2 transmission and outbreak control measures in densely populated settings.
Ontology highlight
ABSTRACT:
SUBMITTER: Pung R
PROVIDER: S-EPMC8316572 | biostudies-literature | 2021 Jul
REPOSITORIES: biostudies-literature
Publications
Factors influencing SARS-CoV-2 transmission and outbreak control measures in densely populated settings.
Pung Rachael R Lin Bernard B Maurer-Stroh Sebastian S Sirota Fernanda L FL Mak Tze Minn TM Octavia Sophie S Pang Junxiong J Tan Iain Beehuat IB Tan Clive C Ong Biauw Chi BC Cook Alex R AR Lee Vernon J VJ
Scientific reports 20210727 1
Starting with a handful of SARS-CoV-2 infections in dormitory residents in late March 2020, rapid transmission in their dense living environments ensued and by October 2020, more than 50,000 acute infections were identified across various dormitories in Singapore. The aim of the study is to identify combination of factors facilitating SARS-CoV-2 transmission and the impact of control measures in a dormitory through extensive epidemiological, serological and phylogenetic investigations, supported ...[more]
Similar Datasets
Project description:BackgroundDuring the SARS-CoV-2 pandemic, nurses of primary health care has been an important role in Spain. Even so, the data obtained in the tracing have been scarcely used to investigate the possible mechanisms of transmission. Few studies focused on community transmission, evaluating the effectiveness of individual protective measures and exposure environment. The main aim of the study was to evaluate the association between individual protective measures and SARS-CoV-2 transmission in the community and to compare secondary attack rates in different exposure settings.MethodsA case-control study from contact tracing of SARS-CoV-2 index patients. COVID-19 contact tracing was led by nurses at the COVID-19 Coordinating Centre in Majorca (Spain). During the systematic tracing, additional information for this study was collected from the index patient (social-demographic variables, symptoms, the number of close contacts). And also, the following variables from their close contacts: contact place, ventilation characteristics mask-wearing, type of mask, duration of contact, shortest distance, case-contact relationship, household members, and handwashing, the test result for SARS-CoV-2 diagnostic. Close contacts with a positive test for SARS-CoV-2 were classified as "cases" and those negative as "controls."ResultsA total of 1,778 close contacts from 463 index patients were identified. No significant differences were observed between the sexes but between age groups. Overall Secondary Attack Rate (SAR) was 24.0% (95% CI: 22.0-26.0%), 36.9% (95% CI: 33.2-40.6%) in closed spaces without ventilation and 50.7% (95% CI: 45.6-55.8%) in exposure time > 24 h. A total of 49.2% of infections occurred among household members. Multivariate logistic regression analysis showed that open-air setting (OR 0.43, 95% CI: 0.27-0.71), exposure for less than 1 h (OR 0.19, 95% CI: 0.11-0.32), and wearing a mask (OR 0.49, 95% CI: 0.28-0.85) had a protective effect transmission of SARS-CoV-2 in the community.ConclusionVentilation of the space, mask-wearing and shorter exposure time were associated with a lower risk of transmission in the community. The data obtained allowed an assessment of community transmission mechanisms and could have helped to improve and streamline tracing by identifying close contacts at higher risk.
| S-EPMC10801386 | biostudies-literature
Project description:A COVID-19 outbreak occurred among residents of a Roma settlement in Greece (8 April-4 June 2020). The aim of this study was to identify factors associated with an increased risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and to evaluate the effectiveness of control measures implemented. Data were analyzed from individuals that were tested for SARS-CoV-2 during contact tracing, population screening or hospital visits. RT-PCR was used for the detection of SARS-CoV-2 in oropharyngeal samples. Risk factors for household secondary attack rates (SAR) and hospitalization with COVID-19 were examined using chi-square tests, Fisher's exact tests and logistic regression analyses. During the outbreak, 142 cases, 20 hospitalizations and 1 death were recorded, with a total of 2273 individuals tested. The risk of hospitalization was associated with age (OR: 1.04, 95% CI: 1.02-1.07) and Cycle threshold (Ct) values (OR for a decrease in Ct values by 1: 1.18, 95% CI: 1.07-1.31). Household SAR was estimated at 38.62% (95% CI: 32.50-45.01%). After the designation of an isolation facility for cases, household SAR declined from 74.42% to 31.03%. Household size was associated with the risk of infection (OR: 2.65, 95% CI: 1.00-7.07). The presence of COVID-19 symptoms among index cases was correlated with higher transmission (OR: 23.68, 95% CI 2.21-253.74) in multivariate analysis, while age was found to be associated with SAR only in univariate analysis. Roma communities can be particularly vulnerable to the spread of SARS-CoV-2. In similar settings, symptomatic cases are more important transmitters of SARS-CoV-2. Within these communities, immediate measures should be implemented to mitigate disease spread.
| S-EPMC8002111 | biostudies-literature
Project description:ObjectiveTo reconstruct the transmission trajectory of SARS-CoV-2 and analyze the effects of control measures in China.MethodsPython 3.7.1 was used to write a SEIR class to model the epidemic procedure and proportional estimation method to estimate the initial true infected number. The epidemic area in China was divided into three parts, Wuhan city, Hubei province (except Wuhan) and China (except Hubei) based on the different transmission pattern. A testing capacity limitation factor for medical resources was imposed to model the number of infected but not quarantined individuals. Baidu migration data were used to assess the number of infected individuals who migrated from Wuhan to other areas.ResultsBasic reproduction number, R0, was 3.6 before the city was lockdown on Jan 23, 2020. The actual infected number the model predicted was 4508 in Wuhan before Jan 23, 2020. By January 22 2020, it was estimated that 1764 infected cases migrated from Wuhan to other cities in Hubei province. Effective reproductive number, R, gradually decreased from 3.6 (Wuhan), 3.4 (Hubei except Wuhan,) and 3.3 (China except Hubei) in stage 1 (from Dec 08, 2019 to Jan 22, 2020) to 0.67 (Wuhan), 0.59 (Hubei except Wuhan) and 0.63 (China except Hubei) respectively. Especially after January 23, 2020 when Wuhan City was closed, the infected number showed a turning point in Wuhan. By early April, there would be 42073 (95% confidence interval, 41673 to 42475), 21342 (95% confidence interval, 21057 to 21629) and 13384 (95% confidence interval, 13158 to 13612) infected cases in Wuhan, Hubei (except Wuhan) and China (except Hubei), respectively.ConclusionA series of control measures in China have effectively prevented the spread of COVID-19, and the epidemic should be under control in early April with very few new cases occasionally reported.
| S-EPMC7709801 | biostudies-literature
Project description:Most of the microbial degradation in oil reservoirs is believed to take place at the oil-water transition zone (OWTZ). However, a recent study indicates that there is microbial life enclosed in microliter-sized water droplets dispersed in heavy oil of Pitch Lake in Trinidad and Tobago. This life in oil suggests that microbial degradation of oil also takes place in water pockets in the oil-bearing rock of an oil leg independent of the OWTZ. However, it is unknown whether microbial life in water droplets dispersed in oil is a generic property of oil reservoirs rather than an exotic exception. Hence, we took samples from three heavy-oil seeps, Pitch Lake (Trinidad and Tobago), the La Brea Tar Pits (California, USA), and an oil seep on the McKittrick oil field (California, USA). All three tested oil seeps contained dispersed water droplets. Larger droplets between 1 and 10 μl revealed high cell densities of up to 109 cells ml-1 Testing for ATP content and LIVE/DEAD staining showed that these populations consist of active and viable microbial cells with an average of 60% membrane-intact cells and ATP concentrations comparable to those of other subsurface ecosystems. Microbial community analyses based on 16S rRNA gene amplicon sequencing revealed the presence of known anaerobic oil-degrading microorganisms. Surprisingly, the community analyses showed similarities between all three oil seeps, revealing common OTUs, although the sampling sites were thousands of kilometers apart. Our results indicate that small water inclusions are densely populated microhabitats in heavy oil and possibly a generic trait of degraded-oil reservoirs.IMPORTANCE Our results confirmed that small water droplets in oil are densely populated microhabitats containing active microbial communities. Since these microhabitats occurred in three tested oil seeps which are located thousands of kilometers away from each other, such populated water droplets might be a generic trait of biodegraded oil reservoirs and might be involved in the overall oil degradation process. Microbial degradation might thus also take place in water pockets in the oil-bearing oil legs of the reservoir rock rather than only at the oil-water transition zone.
| S-EPMC7237766 | biostudies-literature
Project description:The effectiveness of mask wearing at controlling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission has been unclear. While masks are known to substantially reduce disease transmission in healthcare settings [D. K. Chu et al., Lancet 395, 1973–1987 (2020); J. Howard et al., Proc. Natl. Acad. Sci. U.S.A. 118, e2014564118 (2021); Y. Cheng et al., Science eabg6296 (2021)], studies in community settings report inconsistent results [H. M. Ollila et al., medRxiv (2020); J. Brainard et al., Eurosurveillance 25, 2000725 (2020); T. Jefferson et al., Cochrane Database Syst. Rev. 11, CD006207 (2020)]. Most such studies focus on how masks impact transmission, by analyzing how effective government mask mandates are. However, we find that widespread voluntary mask wearing, and other data limitations, make mandate effectiveness a poor proxy for mask-wearing effectiveness. We directly analyze the effect of mask wearing on SARS-CoV-2 transmission, drawing on several datasets covering 92 regions on six continents, including the largest survey of wearing behavior (n= 20 million) [F. Kreuter et al., https://gisumd.github.io/COVID-19-API-Documentation (2020)]. Using a Bayesian hierarchical model, we estimate the effect of mask wearing on transmission, by linking reported wearing levels to reported cases in each region, while adjusting for mobility and nonpharmaceutical interventions (NPIs), such as bans on large gatherings. Our estimates imply that the mean observed level of mask wearing corresponds to a 19% decrease in the reproduction number R. We also assess the robustness of our results in 60 tests spanning 20 sensitivity analyses. In light of these results, policy makers can effectively reduce transmission by intervening to increase mask wearing.
| S-EPMC9191667 | biostudies-literature
Project description:We report the transmission dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) across different settings in Brunei. An initial cluster of SARS-CoV-2 cases arose from 19 persons who had attended the Tablighi Jama'at gathering in Malaysia, resulting in 52 locally transmitted cases. The highest nonprimary attack rates (14.8%) were observed from a subsequent religious gathering in Brunei and in households of attendees (10.6%). Household attack rates from symptomatic case-patients were higher (14.4%) than from asymptomatic (4.4%) or presymptomatic (6.1%) case-patients. Workplace and social settings had attack rates of <1%. Our analyses highlight that transmission of SARS-CoV-2 varies depending on environmental, behavioral, and host factors. We identify red flags for potential superspreading events, specifically densely populated gatherings with prolonged exposure in enclosed settings, persons with recent travel history to areas with active SARS-CoV-2 infections, and group behaviors. We propose differentiated testing strategies to account for differing transmission risk.
| S-EPMC7588541 | biostudies-literature
Project description:BackgroundFrom March to June 2022, an Omicron BA.2 epidemic occurred in Shanghai. We aimed to better understand the transmission dynamics and identify age-specific transmission characteristics for the epidemic.MethodsData on COVID-19 cases were collected from the Shanghai Municipal Health Commission during the period from 20th February to 1st June. The effective reproductive number (Rt) and transmission distance between cases were calculated. An age-structured SEIR model with social contact patterns was developed to reconstruct the transmission dynamics and evaluate age-specific transmission characteristics. Least square method was used to calibrate the model. Basic reproduction number (R0) was estimated with next generation matrix.ResultsR0 of Omicron variant was 7.9 (95% CI: 7.4 to 8.4). With strict interventions, Rt had dropped quickly from 3.6 (95% CI: 2.7 to 4.7) on 4th March to below 1 on 18th April. The mean transmission distance of the Omicron epidemic in Shanghai was 13.4 km (95% CI: 11.1 to 15.8 km), which was threefold longer compared with that of epidemic caused by the wild-type virus in Wuhan, China. The model estimated that there would have been a total 870,845 (95% CI: 815,400 to 926,289) cases for the epidemic from 20th February to 15th June, and 27.7% (95% CI: 24.4% to 30.9%) cases would have been unascertained. People aged 50-59 years had the highest transmission risk 0.216 (95% CI: 0.210 to 0.222), and the highest secondary attack rate (47.62%, 95% CI: 38.71% to 56.53%).ConclusionsThe Omicron variant spread more quickly and widely than other variants and resulted in about one third cases unascertained for the recent outbreak in Shanghai. Prioritizing isolation and screening of people aged 40-59 might suppress the epidemic more effectively. Routine surveillance among people aged 40-59 years could also provide insight into the stage of the epidemic and the timely detection of new variants.Trial registrationWe did not involve clinical trial.
| S-EPMC10121427 | biostudies-literature
Project description:Several 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. We 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. The 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. Preventive 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: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:BackgroundTransmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in acute-care settings affects patients, healthcare workers, and the healthcare system. We conducted an analysis of risk factors associated with outbreak severity to inform prevention strategies.MethodsThis cross-sectional analysis of COVID-19 outbreaks was conducted at Fraser Health acute-care sites between March 2020 and March 2021. Outbreak severity measures included COVID-19 attack rate, outbreak duration, and 30-day case mortality. Generalized linear models with generalized estimating equations were used for all outcome measures. A P value of 0.05 indicated statistical significance. Analyses were performed using SAS version 3.8 software, R version 4.1.0 software, and Stata version 16.0 software.ResultsBetween March 2020 and March 2021, 54 COVID-19 outbreaks were declared in Fraser Health acute-care sites. Overall, a 10% increase in the hand hygiene rate during the outbreak resulted in an 18% decrease in the attack rate (P < .01), 1 fewer death (P = .03), and shorter outbreaks (P < .01). A 10-year increase in unit age was associated with 2.2 additional days of outbreak (P < 0.01) and increases in the attack rate (P < .05) and the number of deaths (P < .01).DiscussionWe observed an inverse relationship between increased hand hygiene compliance during outbreaks and all 3 severity measures. Increased unit age was also associated with increases in each of the severity measures.ConclusionThis study highlights the importance of hand hygiene practices during an outbreak and the difficulties faced by older facilities, many of which have infrastructural challenges. The latter reinforces the need to incorporate infection control standards into healthcare planning and construction.
| S-EPMC10587374 | biostudies-literature