Abstract
The study aimed to evaluate regional variation in SARS-CoV-2 transmission and assess associations between public health interventions and the time-varying reproduction number (Rt) across Maine from January 2020 to February 2023. Daily confirmed COVID-19 case counts were adjusted for reporting anomalies and delays using deconvolution. Infection counts were estimated by applying a Poisson-distributed multiplier of 4 to account for underreporting. Rt was estimated using EpiEstim with a 7-day sliding window from January 2020 through February 2023. The analysis of associations between Rt and public health interventions was limited to 2020, concluding just before COVID-19 vaccines became available in Maine in December 2020. EpiEstim was parameterized with an Omicron-specific serial interval distribution (main analysis) and an early-pandemic serial interval distribution (sensitivity analysis). Maine experienced four major COVID-19 waves. Rt values fluctuated but remained close to 1 at both the statewide and district levels. No statistically significant changes in Rt were observed in association with any interventions implemented in 2020. Our findings underscore the challenges of quantifying intervention impacts in rural settings, where low incidence and sparse data can obscure the effects of interventions. This highlights the need for enhanced surveillance tools tailored to the unique constraints of rural public health contexts.
| Original language | English |
|---|---|
| Article number | 893 |
| Journal | Pathogens |
| Volume | 14 |
| Issue number | 9 |
| DOIs | |
| State | Published - Sep 5 2025 |
Scopus Subject Areas
- Immunology and Allergy
- Molecular Biology
- General Immunology and Microbiology
- Microbiology (medical)
- Infectious Diseases
Keywords
- COVID-19
- United States
- epidemiology
- non-pharmaceutical interventions
- reproduction number
- time series analysis