U.S. County-Level COVID-19 Annual Component Correlations with Climate and Demographics

United States county-level data correlating the annual component of COVID-19 cases with climatic and socio-demographic variables. The dataset contains regression results from wavelet analyses of logged case data up to March 2023, sourced from The New York Times. It was authored by Ilan N. Rubin and published on figshare under a CC-BY-4.0 license.

Use Cases

• Modeling the relationship between climate variables and COVID 19 seasonality based on the described wavelet analyses.
• Investigating socio-demographic factors influencing pandemic wave patterns based on the regression results.
• Validating epidemiological hypotheses about annual disease cycles using the calculated global wavelet transformations.

Strengths

• Analysis is based on data for each county or county equivalent in the United States, providing national coverage.
• All correlations are noted as statistically significant due to large sample sizes.
• Results highlight variables with an r² > 0.1, indicating a focus on meaningful relationships.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is 5.5 KB, indicating a very limited scope, likely containing summary results rather than raw data.

Provenance

Source

The New York Times COVID-19 case estimates.

Collection Method

Wavelet analysis and regression calculations performed by the author.

Time Range

Data until March 2023.

Freshness

Last updated 2026-04-27 17:44:51; freshness should be verified.

Geography

United States (county-level).