COVID-19 Clusters Research Articles

Lessons learned from the investigation of a COVID-19 cluster in Creil, France: effectiveness of targeting symptomatic cases and conducting contact tracing around them

BackgroundThis study presents the methods and results of the investigation into a SARS-CoV-2 outbreak in a professional community. Due to the limited testing capacity available in France at the time, we elaborated a testing strategy according to pre-test probability.MethodsThe investigation design combined active case finding and contact tracing around each confirmed case with testing of at-risk contact persons who had any evocative symptoms (n = 88). One month later, we performed serology testing to test and screen symptomatic and asymptomatic cases again (n = 79).ResultsTwenty-four patients were confirmed (14 with RT-PCR and 10 with serology). The attack rate was 29% (24/83). Median age was 40 (24 to 59), and the sex ratio was 15/12. Only three cases were asymptomatic (= no symptoms at all, 13%, 95% CI, 3–32). Nineteen symptomatic cases (79%, 95% CI, 63–95) presented a respiratory infection, two of which were severe. All the RT-PCR confirmed cases acquired protective antibodies.Median incubation was 4 days (from 1 to 13 days), and the median serial interval was 3 days (0 to 15). We identified pre-symptomatic transmission in 40% of this cluster, but no transmission from asymptomatic to symptomatic cases.ConclusionWe report the effective use of targeted testing according to pre-test probability, specifically prioritizing symptomatic COVID-19 diagnosis and contact tracing. The asymptomatic rate raises questions about the real role of asymptomatic infected people in transmission. Conversely, pre-symptomatic contamination occurred frequently in this cluster, highlighting the need to identify, test, and quarantine asymptomatic at-risk contact persons (= contact tracing). The local lockdown imposed helped reduce transmission during the investigation period.

Size and duration of COVID-19 clusters go along with a high SARS-CoV-2 viral load: A spatio-temporal investigation in Vaud state, Switzerland

To understand the geographical and temporal spread of SARS-CoV-2 during the first documented wave of infection in the state of Vaud, Switzerland, we analyzed clusters of positive cases using the precise residential location of 33,651 individuals tested (RT-PCR) between January 10 and June 30, 2020. We used a prospective Poisson space-time scan statistic (SaTScan) and a Modified Space–Time Density-Based Spatial Clustering of Application with Noise (MST-DBSCAN) to identify both space-time and transmission clusters, and estimated cluster duration, transmission behavior (emergence, growth, reduction, etc.) and relative risk. For each cluster, we computed the number of individuals, the median age of individuals and their viral load.Among the 1684 space-time clusters identified, 457 (27.1%) were significant (p ≤ 0.05), such that they harbored a higher relative risk of infection within the cluster than compared to regions outside the cluster. Clusters lasted a median of 11 days (IQR 7–13) and included a median of 12 individuals per cluster (IQR 5–20). The majority of significant clusters (n = 260; 56.9%) had at least one person with an extremely high viral load (>1 billion copies/ml). Those clusters were considerably larger (median of 17 infected individuals, p < 0.001) than clusters with individuals showing a viral load below 1 million copies/ml (median of three infected individuals). The highest viral loads were found in clusters with the lowest average age group considered in the investigation, while clusters with the highest average age had low to middle viral load. In 20 significant clusters, the viral load of the three first cases was below 100,000 copies/ml, suggesting that subjects with fewer than 100,000 copies/ml may still be contagious. Notably, the dynamics of transmission clusters made it possible to identify three diffusion zones, which predominantly differentiated between rural and urban areas, the latter being more prone to persistence and expansion, which may result in the emergence of new clusters nearby.The use of geographic information is key for public health decision makers in mitigating the spread of the SARS-CoV-2 virus. This study suggests that early localization of clusters may help implement targeted protective measures limiting the spread of the virus.

Disease surveillance for the COVID-19 era: time for bold changes

The COVID-19 pandemic has exposed weaknesses in disease surveillance in nearly all countries. Early identification of COVID-19 cases and clusters for rapid containment was hampered by inadequate diagnostic capacity, insufficient contact tracing, fragmented data systems, incomplete data insights for public health responders, and suboptimal governance of all these elements. Once SARS-CoV-2 became widespread, interventions to control community transmission were undermined by weak surveillance of cases and insufficient national capacity to integrate data for timely adjustment of public health measures.

984 Hospital Transmission of COVID-19 in Trauma Surgery

IntroductionA single-site retrospective study identified a suspected cluster of hospital-acquired COVID-19 in trauma patients. The study aims to identify contributing factors in order to minimise future risk to patients and staff.MethodA single-site retrospective cohort study including all T&O patients who underwent surgery with confirmed peri-operative COVID-19 infection. The primary outcome was 30-day mortality. Exposures investigated included diagnostic timing and theatre designation.Results92% of participants were not tested pre-operatively. 75% met the criteria for hospital acquired COVID-19. Only 2 patients were operated on in designated COVID-19 theatres. Two lists accounted for 50% of the T&O COVID-positive patients. Remaining patients on both lists were discharged without further testing. Local 30-day mortality rate (25%) was in line with the findings of the international COVIDSurg Study (23.8%). No further COVID-positive T&O cases identified since the introduction of blanket admission swabbing.ConclusionsThe majority of patients did not meet criteria for pre-operative testing. Thus, were not operated on in appropriately designated theatres despite unknown COVID status, increasing risk of cross-contamination. Complacency due to designation of “clean” and “dirty” wards, atypical presentation and bay nursing may have contributed to hospital transmission. Findings emphasise the importance of treating patients as COVID positive until proven otherwise.

Detecting COVID-19 Clusters at High Spatiotemporal Resolution, New York City, New York, USA, June-July 2020.

A surveillance system that uses census tract resolution and the SaTScan prospective space-time scan statistic detected clusters of increasing severe acute respiratory syndrome coronavirus 2 test percent positivity in New York City, NY, USA. Clusters included one in which patients attended the same social gathering and another that led to targeted testing and outreach.

The role of religion in mitigating the COVID-19 pandemic: the Malaysian multi-faith perspectives.

Social distancing is crucial in breaking the cycle of transmission of COVID-19. However, many religions require the faithful to congregate. In Malaysia, the number of COVID-19 cases spiked up from below 30 in February 2020 to more than a thousand a month later. The sudden increase was mostly linked to a large Islamic gathering attended by 16,000 near the capital, Kuala Lumpur. Another large COVID-19 cluster was from a church gathering in Kuching, Sarawak. Within a few weeks, Malaysia became the worst hit country by COVID-19 in Southeast Asia. While religious leaders have advised social distancing among their congregants, the belief that “God is our shield” is often cited for gathering. There is a need to promote sound decision-making among religious adherents so that they will not prioritize their loyalty to the subjective interpretation of religion over evidence-based medicine. Malaysia, a multi-cultural and multi-faith country, is an example of how religious beliefs could strongly influence health behaviours at individual and community levels. In this article, we detail the religious aspects of COVID-19 prevention and control in Malaysia and discuss the possible role of religious organizations in encouraging sound decision-making among religious adherents in mitigating this crisis. We make recommendations on how to promote a partnership between the healthcare system and religious organizations, and how religion and faith could be integrated into health promotion channels and resources in the response of COVID-19 and future communicable diseases.

TRB sequences targeting ORF1a/b are associated with disease severity in hospitalized COVID-19 patients.

The potential protective or pathogenic role of the adaptive immune response to SARS‐CoV‐2 infection has been vigorously debated. While COVID‐19 patients consistently generate a T lymphocyte response to SARS‐CoV‐2 antigens, evidence of significant immune dysregulation in these patients continues to accumulate. In this study, next generation sequencing of the T cell receptor beta chain (TRB) repertoire was conducted in hospitalized COVID‐19 patients to determine if immunogenetic differences of the TRB repertoire contribute to disease course severity. Clustering of highly similar TRB CDR3 amino acid sequences across COVID‐19 patients yielded 781 shared TRB sequences. The TRB sequences were then filtered for known associations with common diseases such as EBV and CMV. The remaining sequences were cross‐referenced to a publicly accessible dataset that mapped COVID‐19 specific TCRs to the SARS‐CoV‐2 genome. We identified 158 SARS‐CoV‐2 specific TRB sequences belonging to 134 clusters in our COVID‐19 patients. Next, we investigated 113 SARS‐CoV‐2 specific clusters binding only one peptide target in relation to disease course. Distinct skewing of SARS‐CoV‐2 specific TRB sequences toward the nonstructural proteins (NSPs) encoded within ORF1a/b of the SARS‐CoV‐2 genome was observed in clusters associated with critical disease course when compared to COVID‐19 clusters associated with a severe disease course. These data imply that T‐lymphocyte reactivity towards peptides from NSPs of SARS‐CoV‐2 may not constitute an effective adaptive immune response and thus may negatively affect disease severity.

The Role of Doctors in Facing the COVID-19 Pandemic in the Indonesian Worker Community

COVID-19, which is caused by the SARS-CoV-2 virus, first entered and infectedIndonesians on March 1, 2020. A woman (31 years old) felt sick two days afterdancing with a Japanese citizen living in Malaysia, who was also recently confirmedto have COVID-19. The woman&amp;#39;s mother (64 years old) was finally infected andconfirmed as a sufferer of COVID-19. Since then, among all contacts from Japanesecitizens (33 people consisting of drivers, guides, restaurant waiters, and other guestsat the dance) and from the first COVID-19 case in Indonesia (80 people), most peoplewere those who worked directly related to the case tracing 1 . A total of 11 people wereconfirmed to have an infection, with 2 of them were asymptomatic cases. Of the 11people, 10 were contacts of the foreign nationals; and 1 case was the first Indonesiancitizen's mother.The next COVID-19 cluster description in the community is very similar to the firstcluster, namely work-related contacts and family contacts. New clusters continue toemerge from various industries and offices that dominate the number of new cases inIndonesia.

COVID-19: Studying dissociative experiences in a confined sample of tunisian people

IntroductionDissociative experiences have been studied in different circumstances.ObjectivesIn this study we aim to analyze dissociative phenomena under a stress factor: lockdown.MethodsWe conducted a cross sectional-study, using an online survey, spread during lockdown period in Tunisia, between the 2nd and the 8th of April. It was comprised of sociodemographic, geographic, medical history, confinement status and DES-II questionnaire in its french version. Age superior than 18 was the only inclusion criteria and the no respect of lockdown was the exclusion criteria. Based on former studies on DES-II, 3 sub scores have been assessed; amnesia (measures memory loss), depersonalization (sense of unreality of the self ) and absorption (the absorption has to do with one’s traumatic experiences).ResultsWe recruited 167 individuals; 100 women and 67 men. The most common age class was 20 to 30 years old (60.5% of the sample). The Mean total score was 11.06 which was higher than mentioned in earlier studies. The mean score was 15,11 for absorption; 5,28 for amnesia and 6,88 for depersonalization subscale. Significant differences in scores were found based on different variables. Women had higher absorption score (p=0.011). Besides people living in COVID-19 clusters had lower total score (p=0.038). Finally, people with somatic medical history showed higher total score (p=0.013), absorption score (p=0.003) and depersonalization score (p=0.012) compared to those with none.ConclusionsDuring lockdown, dissociative experiences showed to be more frequent. But does this mean that a resurgence in PTSD (posttraumatic stress disorder) or ASD (acute stress disorder) in the months to come.

Modifications to the delivery of NHS face-to-face general practice consultations during the COVID-19 pandemic in England.

Background: To minimise transmission of SARS-CoV-2, the virus causing COVID-19, delivery of general practice consultations has been modified to enable the separation of diagnosed or suspected COVID-19 patients from others. Remote triage and consultations are currently the default model, with adapted face-to-face contact used when clinically necessary. This study aimed to identify the modified face-to-face delivery models used across England, and evidence for their effectiveness. Methods: In June 2020, a national survey was sent by email to the 135 Clinical Commissioning Groups (CCGs) in England to identify local organisation of face-to-face general practice consultations since March 2020. An email was sent to Public Health England (PHE) requesting information about COVID-19 outbreaks or clusters linked to general practice. Results: All CCGs responded. Separation of COVID-19 patients from others was achieved using combinations of the following models: zoned surgeries (used in 47% of CCGs), where COVID-19 and other patients are separated within their own practice;'hot' or 'cold' hubs (used in 90% of CCGs), separate sites where COVID-19 or other patients registered at one of several collaborating practices are seen;'hot' and 'cold' home visits (used in 70% of CCGs). One of seven model combinations was used across each CCG, with some flexibility according to changing need shown through hub availability. Concomitant PHE data showed less than 2% of COVID-19 outbreaks or clusters in England were linked to general practice. Conclusions: Varied, flexible ways of delivering face-to-face general practice consultations were identified. While COVID-19 outbreaks or clusters linked to general practice constituted a small proportion of totals, their investigation, together with evaluations of the modified delivery models in terms of management of COVID-19 and other conditions and impacts on staff and patients, may aid future management of the pandemic and identify aspects of adapted practice of benefit beyond this.

An analysis of COVID-19 clusters in India

BackgroundIn this study we cluster the districts of India in terms of the spread of COVID-19 and related variables such as population density and the number of specialty hospitals. Simulation using a compartment model is used to provide insight into differences in response to public health interventions. Two case studies of interest from Nizamuddin and Dharavi provide contrasting pictures of the success in curbing spread.MethodsA cluster analysis of the worst affected districts in India provides insight about the similarities between them. The effects of public health interventions in flattening the curve in their respective states is studied using the individual contact SEIQHRF model, a stochastic individual compartment model which simulates disease prevalence in the susceptible, infected, recovered and fatal compartments.ResultsThe clustering of hotspot districts provide homogeneous groups that can be discriminated in terms of number of cases and related covariates. The cluster analysis reveal that the distribution of number of COVID-19 hospitals in the districts does not correlate with the distribution of confirmed COVID-19 cases. From the SEIQHRF model for Nizamuddin we observe in the second phase the number of infected individuals had seen a multitudinous increase in the states where Nizamuddin attendees returned, increasing the risk of the disease spread. However, the simulations reveal that implementing administrative interventions, flatten the curve. In Dharavi, through tracing, tracking, testing and treating, massive breakout of COVID-19 was brought under control.ConclusionsThe cluster analysis performed on the districts reveal homogeneous groups of districts that can be ranked based on the burden placed on the healthcare system in terms of number of confirmed cases, population density and number of hospitals dedicated to COVID-19 treatment. The study rounds up with two important case studies on Nizamuddin basti and Dharavi to illustrate the growth curve of COVID-19 in two very densely populated regions in India. In the case of Nizamuddin, the study showed that there was a manifold increase in the risk of infection. In contrast it is seen that there was a rapid decline in the number of cases in Dharavi within a span of about one month.

Fine-Scale Space-Time Cluster Detection of COVID-19 in Mainland China Using Retrospective Analysis.

Exploring spatio-temporal patterns of disease incidence can help to identify areas of significantly elevated or decreased risk, providing potential etiologic clues. The study uses the retrospective analysis of space-time scan statistic to detect the clusters of COVID-19 in mainland China with a different maximum clustering radius at the family-level based on case dates of onset. The results show that the detected clusters vary with the clustering radius. Forty-three space-time clusters were detected with a maximum clustering radius of 100 km and 88 clusters with a maximum clustering radius of 10 km from 2 December 2019 to 20 June 2020. Using a smaller clustering radius may identify finer clusters. Hubei has the most clusters regardless of scale. In addition, most of the clusters were generated in February. That indicates China’s COVID-19 epidemic prevention and control strategy is effective, and they have successfully prevented the virus from spreading from Hubei to other provinces over time. Well-developed provinces or cities, which have larger populations and developed transportation networks, are more likely to generate space-time clusters. The analysis based on the data of cases from onset may detect the start times of clusters seven days earlier than similar research based on diagnosis dates. Our analysis of space-time clustering based on the data of cases on the family-level can be reproduced in other countries that are still seriously affected by the epidemic such as the USA, India, and Brazil, thus providing them with more precise signals of clustering.

Screening around a COVID-19 cluster: Exploring its impact on a local virus outbreak

ObjectiveIn March 2020, we implemented screening of the contacts of a COVID-19 cluster having occurred in the Lot-et-Garonne department, the first department of the Nouvelle-Aquitaine region to be affected by the active circulation of SARS-CoV-2. We aimed to describe the impact of this screening on the local SARS-CoV-2 outbreak. MethodsAll high-risk contacts, as well as the individuals living in their households, were screened. We detailed the evolution of the number of confirmed COVID-19 cases in the Lot-et-Garonne department and the rest of the Nouvelle-Aquitaine region. ResultsAmong the 89 screened individuals, 10 new cases were confirmed, including 4 asymptomatic persons. In Lot-et-Garonne, the number of confirmed COVID-19 cases immediately decreased after this screening and no epidemic peak occurred, contrary to what was observed in the rest of the region. ConclusionThe early screening of high-risk contacts of COVID-19 cases and members of their household implemented a few days before the first lockdown probably helped to prevent the spread of the virus in the department.

Responses to COVID-19 Clusters in Long-term Care Facilities of Japan

2020年4月18日より4階建ての特別養護老人ホームにおいて，2階より10名の発熱者が出現し，新型コロナウイルスに対するPCR検査をホームで行い9名が陽性と判定され，当院に収容した．4月27日全入居者と全職員にホームでPCR検査を行った．その結果，入居者21名，ショートステイ1名と職員6名が陽性となった．陽性者22名をホームの2階に集めて，陰性者は3階と4階に移動した．ホームの2階と3階にゾーニングを行い，電子カルテ上に仮想病棟を構築し，検査や投薬点滴のオーダーができるようにし，入居者の状態も病院で把握できるようにした．ホームで血液検査や尿検査を行い，精査が必要と判断された場合，病院に搬送した．5月13日，69名に2回目のPCR検査を行い，2階は15名が陽性となり，3階から新たに3名が陽性となったため，この3名は2階に移動した．5月27日から6月19日まで，PCR検査を4回繰り返し，すべての入居者が2回連続陰性となったのを確認して，クラスターは収束したと判断した．この間，肺炎や多臓器不全などの合併症により，6名が死亡し，入居者の死亡率は14.3%だった．

Compounding Racialized Vulnerability: COVID-19 in Prisons, Jails, and Migrant Detention Centers.

Carceral institutions are among the largest clusters of COVID-19 in the United States. In response, activists and detainees have rallied around decarceration demands: the release of detainees and inmates to prevent exposure to COVID-19. This article theorizes the compounding racial vulnerability that has led to such a marked spread behind bars, mainly among race-class subjugated (RCS) communities. The authors provide an in-depth account of COVID-19 in American correctional facilities and the mobilization to reduce contagions. They also use two survey experiments to describe public support for harm reduction and decarceration demands and to measure the effects of information about racial inequalities in prison and poor conditions inside migrant detention centers. The authors found only one-third to one-half of respondents believe that response to COVID-19 in prisons and immigrant detention centers should be a high priority. They also found Americans are more supportive of harm reduction measures than decarceration efforts. Information about racial disparities increases support decarceration. They did not find any significant effect of information about poor conditions in migrant detention centers. The conditions in carceral institutions during the pandemic-and public opinion about them-highlight the realities of compounding racialized vulnerability in the United States.

Transmission chains of clusters of COVID-19 associated with a market in Beijing

Objective: To investigate the clusters of COVID-19 associated with a market (market Y) in Haidian District, Beijing, and analyze the chain of transmission and provide reference for effective prevention and control of COVID-19. Methods: The investigation of field epidemiology and cluster epidemic was used to describe the distributions of all COVID-19 cases. The time sequence diagram of the cases, disease onset was drawn and transmission chains were analyzed. Real-time RT-PCR assay was conducted for SARS-CoV-2 nucleic acid test by using the respiratory samples of the cases. Results: The COVID-19 epidemic, originated from a wholesale farm produce market (market X) in Fengtai District, Beijing, was introduced by a marketer in the market Y who had exposed to market X, causing 8 clusters of 20 confirmed cases of COVID-19 and one asymptomatic case, including 8 men and 13 women, in market Y, surrounding communities, food plaza, companies,families and other places. The incidence peaked during June 10-14, 2020; the median age of the cases was 45 years, ranging from 5 years to 87 years. The initial symptoms of the cases included fever (10/20) and pharynx discomfort (7/20). The median of incubation period was 5 days (IQR:3-8). The median of serial interval between primary case and secondary cases was 5 days with a secondary attack rate of 3.7%(20/538), and the secondary attack rate in household close-contacts was 14.0% (7/50). Conclusions: The clusters of COVID-19 associated with market Y were caused by several modes of transmission, including human-to-human, contaminated material-to-human, etc. The combined public-health response measures were effective to control the COVID-19 epidemic in Haidian district of Beijing.

Using Social Network Analysis to Identify Spatiotemporal Spread Patterns of COVID-19 around the World: Online Dashboard Development.

The COVID-19 pandemic has spread widely around the world. Many mathematical models have been proposed to investigate the inflection point (IP) and the spread pattern of COVID-19. However, no researchers have applied social network analysis (SNA) to cluster their characteristics. We aimed to illustrate the use of SNA to identify the spread clusters of COVID-19. Cumulative numbers of infected cases (CNICs) in countries/regions were downloaded from GitHub. The CNIC patterns were extracted from SNA based on CNICs between countries/regions. The item response model (IRT) was applied to create a general predictive model for each country/region. The IP days were obtained from the IRT model. The location parameters in continents, China, and the United States were compared. The results showed that (1) three clusters (255, n = 51, 130, and 74 in patterns from Eastern Asia and Europe to America) were separated using SNA, (2) China had a shorter mean IP and smaller mean location parameter than other counterparts, and (3) an online dashboard was used to display the clusters along with IP days for each country/region. Spatiotemporal spread patterns can be clustered using SNA and correlation coefficients (CCs). A dashboard with spread clusters and IP days is recommended to epidemiologists and researchers and is not limited to the COVID-19 pandemic.

The lab-confirmed interval of COVID-19 clusters and its application in the strength evaluation of prevention and control measures

BackgroundThe lab-confirmed interval is the date from lab confirmation in a core case (infector) to lab confirmation in a second case (infectee); however, its distribution and application are seldom reported. This study aimed to investigate the lab-confirmed interval and its application in the preliminary evaluation of the strength of disease prevention and control measures.MethodsTaking European countries and Chinese provinces outside Hubei as examples, we identified 63 infector-infectee pairs from European countries from Wikipedia, and 103 infector-infectee pairs from official public sources in Chinese provinces outside Hubei. The lab-confirmed intervals were obtained through analysis of the collected data and adopting the bootstrap method.ResultsThe mean lab-confirmed interval was 2.6 (95% CI: 2.1–3.1) days for Europe and 2.6 (95% CI: 1.9–3.3) days for China outside Hubei, which were shorter than the reported serial intervals. For index patients aged ≥60 years old, the lab-confirmed interval in Europe was slightly longer (mean: 2.9; 95% CI: 2.0–3.6) and obviously longer in China outside Hubei (mean: 3.8; 95% CI: 1.9–5.5) than that for patients aged < 60 years.ConclusionInvestigation of the lab-confirmed interval can provide additional information on the characteristics of emergent outbreaks and can be a feasible indication to evaluate the strength of prevention and control measures. When the lab-confirmed interval was shorter than the serial interval, it could objectively reflect improvements in laboratory capacity and the surveillance of close contacts.

Comparing aerosol concentrations and particle size distributions generated by singing, speaking and breathing

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has resulted in an unprecedented shutdown in social and economic activity, with the cultural sector particularly severely affected. Restrictions on musical performances have arisen from a perception that there is a significantly higher risk of aerosol production from singing than speaking, based upon high-profile examples of clusters of COVID-19 following choral rehearsals. However, comparing aerosol generation from different types of vocalization, including singing, across a range of volumes is a rapidly evolving area of research. Here, we measured aerosols from singing, speaking and breathing from a large cohort of 25 professional singers in a range of musical genres in a zero-background environment, allowing unequivocal attribution of aerosol production to specific vocalizations. We do not assess the relative volumes at which people speak and sing. However, both showed steep increases in mass concentration with increase in loudness (spanning a factor of 20–30 across the dynamic range measured, p < 0.001). At the quietest volume (50 to 60 dBA), neither singing (p = 0.19) nor speaking (p = 0.20) were significantly different to breathing. At the loudest volume (90 to 100 dBA), a statistically significant difference (p < 0.001) was observed between singing and speaking, but with singing only generating a factor of between 1.5 and 3.4 more aerosol mass. Guidelines for musical performances should be based on the loudness and duration of the vocalization, the number of participants and the environment in which the activity occurs, rather than the type of vocalization. Mitigations such as the use of amplification and increased attention to ventilation should be employed where practicable.Copyright © 2021 American Association for Aerosol Research

Environmental Investigation of SARS-CoV-2 in a Karaoke Bar: a Survey for a Cluster of COVID-19 in Hokkaido, Japan, 2020.

Environmental Investigation of SARS-CoV-2 in a Karaoke Bar: a Survey for a Cluster of COVID-19 in Hokkaido, Japan, 2020.