Evidence map›Paper›PMID 41718047›Full record

ArticleEpidemiologia (Basel, Switzerland)2026

Geographical Variation in SARS-CoV-2 Transmission Potential in Massachusetts.

Ina Sze-Ting Lee, Xinyi Hua, Jing Xiong Kersey, Kayoko Shioda, Gerardo Chowell, Isaac Chun-Hai Fung

Abstract read
In one paragraph

Article in Epidemiologia (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ina Sze-Ting LeeSchool of Public Health, Boston University, Boston, MA 02118, USA.ORCID 0009-0009-4426-6154
Xinyi HuaDepartment of Microbiology, Immunology and Molecular Genetics, College of Medicine, University of Kentucky, Lexington, KY 40536, USA.
Jing Xiong KerseyDepartment of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA 30460, USA.ORCID 0000-0001-7256-3978
Kayoko ShiodaDepartment of Global Health, School of Public Health, Boston University, Boston, MA 02118, USA.
Gerardo ChowellDepartment of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA 30303, USA.ORCID 0000-0003-2194-2251
Isaac Chun-Hai FungDepartment of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA 30460, USA.ORCID 0000-0001-5496-2529

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesThis ecological study aimed to investigate changes in the time-varying reproduction number (Rt) of SARS-CoV-2 across six regions of Massachusetts from 2020 to 2022 and to evaluate the impact of various nonpharmaceutical interventions (NPIs) implemented in 2020 by examining associated changes in the Rt.

methodsCOVID-19 incident case data from the Johns Hopkins University database were adjusted for reporting delays using deconvolution and for underreporting via a Poisson-distributed multiplier of 4. Negative and zero counts were corrected using imputation. Rt was estimated using R package

resultsFrom 2020 to 2022, Massachusetts experienced five COVID-19 surges, linked to the wild-type strain and emerging variants, with Rt exceeding 1 during each wave and stabilizing at or dropping below 1 during low-incidence phases. School closure and gathering restrictions, the first major intervention, were associated with a 14.7% statewide reduction in Rt (95% credible interval (CrI): -23.6%, -5.6%), with greater reductions in high-density areas such as Boston (-16.9%; 95% CrI: -26.9%, -7.5%). No statistically significant changes in Rt were found to be associated with other NPIs in 2020, including the mask mandate, reopening phases, travel restrictions and quarantine requirements, and curfews.

conclusionsOur findings highlight the different NPIs' varying impacts on COVID-19 transmission dynamics across regions in Massachusetts in 2020 and underscore the importance of early interventions for future pandemic preparedness.

Indexed as

COVID-19epidemiologynon-pharmaceutical interventionsreproduction numbertime series analysisUnited States

Identifiers

PMID41718047
PMCPMC12922091

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.