Study population and setting
This study considered 21 US counties that hosted rallies in support of Donald Trump’s 2020 presidential campaign. The authors compared the change in incident COVID-19 cases before and after the rallies with a prediction of what would have occurred in those counties had the rally not occurred. The prediction was based on incident COVID-19 cases in a matched set of counties in which there was no rally, adjusted for a set of variables describing important differences between rally and non-rally regions. Separate analyses were conducted for each event, and combined afterwards. In order to explore the degree to which the methods might have affected results, the authors used a variety of procedures, matching variables, and adjustment schemes. These variables included county-level demographics, urbanicity, political preferences, COVID-19 policies, and socioeconomic status. COVID-19 case fatality rates (the proportion of cases who died) were estimated for each county by dividing deaths by incident cases after a lag. The number of additional cases attributable to the rally was multiplied by the estimated case fatality rate to estimate the number of deaths attributable to the rallies.
Summary of Main Findings
The primary analysis (matching counties was based on cases per capita) found that rallies increased the number of cases in rally counties by 332 per 100,000 residents (95% CI: 156 to 508), for a total of 38,697 additional cases and 775 additional deaths. In an alternate model that matched counties based on additional demographic variables (total population, % college-educated, and 2016 Trump vote %), the estimated effect was slightly smaller, with an additional 261 cases per 100,000 residents (95% CI: 62 to 460) and 608 additional deaths. Additional model variants produced broadly similar results.
The methods, and the in-depth treatment of alternative sets of assumptions and models, are well designed and appropriate for examining the impact of rallies on local cases. The implied difference-in-difference strategy using a matching scheme with adjustment is very likely to thoroughly address differences between rallies, and provides a strong foundation for identifying the impact of the rallies on cases. The authors directly address many of the issues that make this kind of estimation difficult through individualized statistical modeling for each region, careful selection of comparators, and in-depth examination of the effects of alternative assumptions, models, and procedures.
The most substantial limitation is the weakness of the method for estimating deaths conditional on additional cases. Estimates of county-specific case fatality rates are highly uncertain, since cases likely to be attributable to the rallies are likely in different kinds of people than would have occurred otherwise, and the case fatality rate may change over time. There is also little detail and visual representation of the county-specific models themselves, so it is difficult to evaluate the validity of key assumptions, particularly regarding the rates of COVID-19 in counties used as controls. Visual representation of the case trends in counties with and without rallies would have enabled evaluation of model assumptions.
While other studies have explored the impact of mass gatherings or found associations between political alignment and COVID-19 cases, this study provides direct evidence of how a pattern of mass political gatherings directly impacted COVID-19 cases. Further, the design of the study can serve as an example for future research on similar topics and/or using similar methods.
This review was posted on: 13 November 2020