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The contagion externality of a superspreading event: The Sturgis Motorcycle Rally and COVID-19.

ABSTRACT: Large in-person gatherings of travelers who do not socially distance are classified as the "highest risk" for COVID-19 spread by the Centers for Disease Control and Prevention (CDC). From August 7-16, 2020, nearly 500,000 motorcycle enthusiasts converged on Sturgis, South Dakota for its annual rally in an environment without mask-wearing requirements or other mitigating policies. This study is the first to explore this event's public health impacts. First, using anonymized cell phone data, we document that foot traffic at restaurants/bars, retail establishments, and entertainment venues rose substantially at event locations. Stay-at-home behavior among local residents fell. Second, using a synthetic control approach, we find that the COVID-19 case rate increased substantially in Meade County and in the state of South Dakota in the month following the Rally. Finally, using a difference-in-differences model to assess nationwide spread, we find that following the Sturgis event, counties outside of South Dakota that contributed the highest inflows of rally attendees experienced a 6.4-12.5% increase in COVID-19 cases relative to counties without inflows. Our findings highlight that local policy decisions assessing the tradeoff between local economic benefits and COVID-19 health costs will not be socially optimal in the presence of large contagion externalities.

SUBMITTER: Dave D

PROVIDER: S-EPMC7753804 | biostudies-literature |

REPOSITORIES: biostudies-literature

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A hospital cluster of COVID-19 associated with a SARS-CoV-2 superspreading event.

Project description:Background/purposeSuperspreading events (SSEs) are pivotal in the spread of SARS-CoV-2. This study aimed to investigate an SSE of COVID-19 in a hospital and explore the transmission dynamics and heterogeneity of SSE.MethodsWe performed contact tracing for all close contacts in a cluster. We did nasopharyngeal or throat swabbing for SARS-CoV-2 by real-time RT-PCR. Environmental survey was performed. The epidemiological and clinical characteristics of the SSE were studied.ResultsPatient 1 with congestive heart failure and cellulitis, who had onset of COVID-19 two weeks after hospitalization, was the index case. Patient 1 led to 8 confirmed cases, including four health care workers (HCW). Persons tested positive for SARS-CoV-2 were HCW (n = 4), patient 1's family (n = 2), an accompanying person of an un-infected in-patient (n = 1), and an in-patient admitted before the SSE (n = 1). The attack rate among the HCW was 3.2 % (4/127). Environmental survey confirmed contamination at the bed rails, mattresses, and sink in the room patient 1 stayed, suggesting fomite transmission. The index case's sputum remained positive on illness day 35. Except one asymptomatic patient, at least three patients acquired the infection from the index case at the pre-symptomatic period. The effective reproduction number (Rt) was 0.9 (8/9).ConclusionThe host factor (heart failure, longer viral shedding), transmissibility of SARS-CoV-2 (Rt, pre-symptomatic transmission), and possible multiple modes of transmission altogether contributed to the SSE. Rapid response and advance deployment of multi-level protection in hospitals could mitigate COVID-19 transmission to one generation, thereby reducing its impact on the healthcare system.

| S-EPMC8294754 | biostudies-literature

A COVID-19 superspreading event involving two variants during sociotherapy activities in a French mental health centre.

Project description:Background/purposeInvestigation of a COVID-19 super-spreading event involving both beta and delta variants of SARS-CoV-2, following a choir in a mental health centre.MethodsAn epidemiological and biological (RT-PCR, mutations screening and sequencing) investigation was carried out to identify the chains of transmission. A morbidity and mortality review was performed using ALARM root causes analysis to understand how this superspreading event could have taken place.ResultsOn May 25 and 26, 2021, all 13 choir participants were screened. Of these, eight were positive. None of them was vaccinated. Biological results suggested seven cases of delta variants (three confirmed by sequencing) and one case of beta variant. The screening of 141 contact individuals identified 21 subsequent cases with a suspected delta variant and two cases of suspected beta variant. Since the two index cases had similar Ct during the choir, this suggests different spreading abilities. The contributing factors were multiple, including underestimation of infectious risks by the social therapy team in relation to low individual and collective perceived vulnerability CONCLUSION: HCPs involved in sociotherapy must be aware of, and trained to mitigate, the risk of superspreading event. Conventional distancing and good natural ventilation appear to not be enough to prevent spread of more transmissible variants of SARS-CoV-2.

| S-EPMC9113770 | biostudies-literature

Superspreading in the emergence of COVID-19 variants.

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| S-EPMC7245292 | biostudies-literature

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| S-EPMC8112283 | biostudies-literature

Quantifying superspreading for COVID-19 using Poisson mixture distributions.

Project description:The number of secondary cases, i.e. the number of new infections generated by an infectious individual, is an important parameter for the control of infectious diseases. When individual variation in disease transmission is present, like for COVID-19, the distribution of the number of secondary cases is skewed and often modeled using a negative binomial distribution. However, this may not always be the best distribution to describe the underlying transmission process. We propose the use of three other offspring distributions to quantify heterogeneity in transmission, and we assess the possible bias in estimates of the mean and variance of this distribution when the data generating distribution is different from the one used for inference. We also analyze COVID-19 data from Hong Kong, India, and Rwanda, and quantify the proportion of cases responsible for 80% of transmission, [Formula: see text], while acknowledging the variation arising from the assumed offspring distribution. In a simulation study, we find that variance estimates may be biased when there is a substantial amount of heterogeneity, and that selection of the most accurate distribution from a set of distributions is important. In addition we find that the number of secondary cases for two of the three COVID-19 datasets is better described by a Poisson-lognormal distribution.

| S-EPMC8266910 | biostudies-literature

Superspreading in early transmissions of COVID-19 in Indonesia.

Project description:This paper presents a study of early epidemiological assessment of COVID-19 transmission dynamics in Indonesia. The aim is to quantify heterogeneity in the numbers of secondary infections. To this end, we estimate the basic reproduction number [Formula: see text] and the overdispersion parameter [Formula: see text] at two regions in Indonesia: Jakarta-Depok and Batam. The method to estimate [Formula: see text] is based on a sequential Bayesian method, while the parameter [Formula: see text] is estimated by fitting the secondary case data with a negative binomial distribution. Based on the first 1288 confirmed cases collected from both regions, we find a high degree of individual-level variation in the transmission. The basic reproduction number [Formula: see text] is estimated at 6.79 and 2.47, while the overdispersion parameter [Formula: see text] of a negative-binomial distribution is estimated at 0.06 and 0.2 for Jakarta-Depok and Batam, respectively. This suggests that superspreading events played a key role in the early stage of the outbreak, i.e., a small number of infected individuals are responsible for large numbers of COVID-19 transmission. This finding can be used to determine effective public measures, such as rapid isolation and identification, which are critical since delay of diagnosis is the most common cause of superspreading events.

| S-EPMC7769976 | biostudies-literature

Modeling the Global Dynamic Contagion of COVID-19.

Project description:The COVID-19 infections have profoundly and negatively impacted the whole world. Hence, we have modeled the dynamic spread of global COVID-19 infections with the connectedness approach based on the TVP-VAR model, using the data of confirmed COVID-19 cases during the period of March 23rd, 2020 to September 10th, 2021 in 18 countries. The results imply that, (i) the United States, the United Kingdom and Indonesia are global epidemic centers, among which the United States has the highest degree of the contagion of the COVID-19 infections, which is stable. South Korea, France and Italy are the main receiver of the contagion of the COVID-19 infections, and South Korea has been the most severely affected by the overseas epidemic; (ii) there is a negative correlation between the timeliness, effectiveness and mandatory nature of government policies and the risk of the associated countries COVID-19 epidemic affecting, as well as the magnitude of the net contagion of domestic COVID-19; (iii) the severity of domestic COVID-19 epidemics in the United States and Canada, Canada and Mexico, Indonesia and Canada is almost equivalent, especially for the United States, Canada and Mexico, whose domestic epidemics are with the same tendency; (iv) the COVID-19 epidemic has spread though not only the central divergence manner and chain mode of transmission, but also the way of feedback loop. Thus, more efforts should be made by the governments to enhance the pertinence and compulsion of their epidemic prevention policies and establish a systematic and efficient risk assessment mechanism for public health emergencies.

| S-EPMC8795671 | biostudies-literature

Risk avoidance, offsetting community effects, and COVID-19: Evidence from an indoor political rally.

Project description:The Centers for Disease Control and Prevention (CDC) deem large indoor gatherings without social distancing the "highest risk" activity for COVID-19 contagion. On June 20, 2020, President Donald J. Trump held his first mass campaign rally following the US coronavirus outbreak at the indoor Bank of Oklahoma arena. In the weeks following the event, numerous high-profile national news outlets reported that the Trump rally was "more than likely" the cause of a coronavirus surge in Tulsa County based on time series data. This study is the first to rigorously explore the impacts of this event on social distancing and COVID-19 spread. First, using data from SafeGraph Inc, we show that while non-resident visits to census block groups hosting the Trump event grew by approximately 25 percent, there was no decline in net stay-at-home behavior in Tulsa County, reflecting important offsetting behavioral effects. Then, using data on COVID-19 cases from the CDC and a synthetic control design, we find little evidence that COVID-19 grew more rapidly in Tulsa County, its border counties, or in the state of Oklahoma than each's estimated counterfactual during the five-week post-treatment period we observe. Difference-in-differences estimates further provide no evidence that COVID-19 rates grew faster in counties that drew relatively larger shares of residents to the event. We conclude that offsetting risk-related behavioral responses to the rally-including voluntary closures of restaurants and bars in downtown Tulsa, increases in stay-at-home behavior, displacement of usual activities of weekend inflows, and smaller-than-expected crowd attendance-may be important mechanisms.Supplementary informationThe online version contains supplementary material available at 10.1007/s11166-021-09359-4.

| S-EPMC8535106 | biostudies-literature

Political trust during the Covid-19 pandemic: Rally around the flag or lockdown effects?

Project description:How can we explain the rise in diffuse political support during the Covid-19 pandemic? Recent research has argued that the lockdown measures generated political support. In contrast, I argue that the intensity of the pandemic rallied people around political institutions. Collective angst in the face of exponentially rising Covid-19 cases depresses the usual cognitive evaluations of institutions and leads citizens to rally around existing intuitions as a lifebuoy. Using a representative Dutch household survey conducted over March 2020, I compare the lockdown effect to the dynamic of the pandemic. I find that the lockdown effect is driven by pre-existing time trends. Accounting for non-linearities in time makes the lockdown effect disappear. In contrast, more flexible modelling techniques reveal a robust effect of Covid-19 infections on political trust. In line with an anxiety effect, I find that standard determinants of political trust - such as economic evaluations and social trust - lose explanatory power as the pandemic spreads. This speaks to an emotionally driven rally effect that pushes cognitive evaluations to the background.

| S-EPMC7753486 | biostudies-literature

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