In a recent study posted to the medRxiv* preprint server, researchers estimated region-specific basic reproduction number (R0) values for MSAs (metropolitan statistical areas) in the US (United States) based on compartmental modeling with reproduced severe acute syndrome coronavirus 2 (SARS-CoV-2) surveillance data.
Study: Differential contagiousness of respiratory disease across the United States. Image Credit: Evgenia.B/Shutterstock
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
Coronavirus disease 2019 (COVID-19) surveillance efforts in the US have provided valuable insights into SARS-CoV-2 transmission dynamics in the country. Several US areas were simultaneously affected by a single pathogenic virus (SARS-CoV-2) at the commencement of the SARS-CoV-2 pandemic. Therefore, comparing region-wise COVID-19 R0 estimates could elucidate how population characteristics of different areas merge for determining differential SARS-CoV-2 susceptibility.
The initial transmission of a communicable disease-causing pathogen in a specific population can be quantified based on the R0 values, which provide the expected number of new COVID-19 cases generated by an infected person in a susceptible population, depending on the properties of the causative pathogen and the population. The authors of the present study previously developed a compartmental analysis model that could reproduce daily SARS-CoV-2 infection case count data for the 15 most populated US MSAs and all 50 US states.
About the study
In the present study, researchers used their previously developed model to estimate regional COVID-19 R0 estimates for 280 out of 384 US MSAs, accounting for 95% and 82% of the US population residing in urban regions and the total population, respectively.
A compartmental model-based approach was used for the analysis, for which a homogeneous population is required. For ascertaining whether SARS-CoV-2 transmission occurs more homogeneously across the US MSA counties or states, three variability measures (Gini coefficient, Wasserstein-1 distance and Fano factor) were used to assess variability in COVID-19 incidence rates per week (i.e., risk of SARS-CoV-2 infection over seven days).
The compartmental model considered the initial period of NPIs (nonpharmaceutical interventions)/social distancing, during which a proportion of individuals adopted disease-avoiding behaviors. In contrast, the remaining individuals engaged freely in social activities without taking precautions for COVID-19 prevention.
The three variability measures were plotted as a function of the epidemiological week for the chosen MSAs and overlapping states. Histograms of time-averaged variability measures for multi-county MSAs and states were analyzed. For every MSA, the Bayesian inference approach, enabled by the MCMC (Markov chain Monte Carlo) sampling procedure, was applied to derive the maximum a posteriori (MAP) R0 estimates, equivalent to the maximum likelihood estimates.
The variability measures were calculated for epidemiological week 5 to week 52, corresponding to the period between January 26, 2020, and December 26, 2020, for MSAs and 50 states comprising multiple counties by amalgamating daily counts of confirmed SARS-CoV-2 infections at a county level. For variability assessments, data were obtained from The New York Times-maintained GitHub public repository.
Results
MSAs identified with the highest number of counties were Atlanta (n=29 counties), Washington (n=25 counties or county equivalents), New York City (NYC, n=23 counties or county-equivalents) and Virginia Beach (n=19 counties or county equivalents). The R0 estimates ranged between 1.9 (for the MSA encompassing Appleton, Wisconsin) and 7.7 (for the MSA encompassing Detroit, Michigan) for relative region-wise susceptibility to SARS-CoV-2 transmission.
The disparate R0 estimates indicated that the population features contributing to the initial spread of SARS-CoV-2 were heterogeneous geographically and combined to yield >4-fold contagiousness of SARS-CoV-2. The variability measures were lesser for the MSAs in comparison to those for overlapping states.
For all three variability measures, the MSA histograms showed left-side shifts in relation to those for the states, indicating that the county-level SARS-CoV-2 transmission risks showed greater homogeneity for US counties within the MSAs compared to those within the states. Region-specific model parameterizations were found to be consistent with SARS-CoV-2 surveillance data of US MSAs with >200 cumulative COVID-19 cases documented before May 21, 2020, and ≥5 novel cases of SARS-CoV-2 infections on any given day in the period between January 21, 2020, and June 21, 2020. The criteria were met by 280 US MSAs.
Overall, the study findings showed that SARS-CoV-2 contagiousness varied over a four-fold range across urban regions of the US. The findings may aid in mitigating future outbreaks of pulmonary diseases since a few urban regions were found to have a far greater susceptibility to rapid SARS-CoV-2 transmission than others.
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 15 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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