Scientists have revealed that social gatherings are one of the most likely areas where pathogen transmission could occur. Therefore, many effective non-pharmaceutical interventions (NPIs) have been implemented during epidemics and pandemics, such as limiting the size of gatherings, social distancing, use of facemasks, etc.
Study: Infectious disease dynamics and restrictions on social gathering size. Image Credit: View Apart/Shutterstock
Background
This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources
During the ongoing coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), policymakers have identified restrictions in gathering size as one of the NPI strategies to prevent COVID-19 transmission.
Several studies have claimed that among different NPIs, restrictions in gathering size have been the most effective approach in preventing the spread of the pathogen. However, due to methodological challenges and the non-systematic manner of their rollout, it has been difficult to assess the impact of specific NPIs in managing SARS-CoV-2 transmission.
Many theories have shown that gathering size restrictions positively reduce SARS-CoV-2 transmission, as it limits the number of contacts between individuals, which effectively prevents the pathogen from spreading. However, it is not yet clear how low the restrictions (number of people allowed in a gathering) must be set to control a specific pathogenic transmission, maintain a stable number of cases, or completely eliminate the pathogen from the population.
Policymakers have undertaken a variety of approaches to set gathering size thresholds which varies with a different set of objectives or local disease dynamics. These set numbers have also reflected ambiguity in the optimal strategy. In the UK, initially, the government restricted gatherings over 500 people in March 2020 before commencing lockdowns. Subsequently, when the lockdown relaxed in late summer, a new “rule of six” was implemented in September 2020.
Importance of implementing restrictions on gathering sizes
Some of the reasons that support the strategy to limit gathering sizes include the prevention of the possibility of superspreading events, especially during social gatherings. Some studies have hypothesized that control or suppression of emerging pathogens can be achieved via a targeted reduction in mass gatherings.
Additionally, multiple retrospective studies have confirmed the occurrences of new COVID-19 cases associated with individuals attending family and friends’ gatherings. These studies have indicated that social gatherings are an important source of new SARS-CoV-2 cases. In the past, restrictions on social gatherings have been among the first implemented measures, which might be due to the perception that social gatherings hold less value than other gatherings in schools and hospitals.
Although both the United States and European Centers for Disease Control have restricted the size and duration of social gatherings, they failed to mention the specific timing of implementing the restriction and threshold allowable number for social gatherings based on a scientific basis. Due to the lack of scientific backing, while implementing a strategy, the duration and size of allowable social gatherings varied from one country to another, with the gathering size permitted from two to 5,000. Restriction on social gatherings changed randomly as the pandemic progressed.
A new study has been published on the medRxiv* preprint server that used epidemiological theory to elucidate the association between gathering size and general disease dynamics. Researchers have also attempted to enumerate the elements associated with quantifying or predicting the impact of a given threshold number linked to the prevalence of new cases.
About the study
The authors revealed that while implementing restrictions or setting optimal threshold numbers in social gatherings, policymakers must consider the distribution of the size of the gathering with respect to the local conditions. Although most of the studies have reported the impact of large gatherings, this study has shown how frequent small gatherings are a significant contributor to transmission dynamics.
Scientists utilized the empirical data from previous studies that revealed that gathering size distributions are “heavy-tailed,” which indicates a considerable decrease in the emergence of new cases would occur when threshold numbers are set quite low.
Scientists revealed that the theory of setting low threshold numbers for social gatherings is applicable for future SARS-CoV-2 variants as well. This finding is in line with previous studies that showed gatherings containing more than fifty individuals have a relatively smaller epidemiological impact than small and medium-sized groups of 10 to 50 individuals to COVID-19 epidemics.
Limitations and next steps
In this study, scientists used a single probability that caused ignoring several important heterogeneities in transmission risk, such as the use of face coverings, indoor vs. outdoor gatherings, ventilation, etc. Scientists also assumed that the probability of transmission is constant across gathering sizes, which may not always be true, and thereby, may cause overestimation in the result. Another assumption made in this study was that all new infections were equivalent, not considering heterogeneity in the impact of secondary infections.
Scientists indicated that more data on human gathering sizes dynamics are required to determine the facet of social dynamics. These data will enable scientists to formulate more tailored and effective restrictions. Additionally, a better knowledge of micro-dynamics of COVID-19 transmission during an outbreak is required for specific predictions along with better infectious disease models with detailed parameterization
This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources
Article Revisions
- May 10 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.
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