Evidence map›Paper›PMID 40027595›Full record

ArticleInfectious Disease Modelling2025

Interventions for SARS-CoV-2 prevention among Jailed adults: A network-based modeling analysis.

Isaac Schneider, Karina Wallrafen-Sam, Shanika Kennedy, Matthew J Akiyama, Anne C Spaulding, Samuel M Jenness

Abstract read
In one paragraph

Article in Infectious Disease Modelling, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Isaac SchneiderDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, USA.
Karina Wallrafen-SamDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, USA.
Shanika KennedyDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, USA.
Matthew J AkiyamaDivisions of General Internal Medicine & Infectious Diseases, Albert Einstein College of Medicine, Bronx, NY, USA.
Anne C SpauldingDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, USA.
Samuel M JennessDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, USA.

Funding

EpiModel 2.0: Integrated Network Models for HIV/STI Prevention ScienceR01AI138783 · NIAID · EMORY UNIVERSITY · PI JENNESS, SAMUEL · 2018 to 2021
$3.0M
Bill & Melinda Gates Foundation INV-035562NIAID NIH HHS R01 AI138783
6 · The paper itself

Abstract

Background: Airborne pathogens present challenges in settings like jails or prisons with a high density of contacts. The state of Georgia has the highest percentage of its citizens under correctional supervision in the United States. Yet, it had slow COVID vaccine uptake among jail residents, requiring prevention also using non-pharmaceutical interventions. Using a network-based SARS-CoV-2 transmission model parameterized with data from the Fulton County Jail, this study investigates the impact of three SARS-CoV-2 prevention strategies: vaccination, contact tracing and quarantining, and jail release to reduce jail population density. Methods: Social contact networks were simulated at two different overlapping network layers: cell and block. Cell-level contacts represented shared confined sleeping space, whereas block-level contacts represented shared socialization space. Contact tracing and quarantining were simulated at the cell-level or both cell- and block-levels, hereafter referred to as all-level. A reference scenario and nine intervention scenarios were simulated three hundred times to estimate the median and interquartile range (IQR) of the outcome measures. Each scenario simulated a 185-day period to measure the prolonged effects of the interventions amid a potential COVID outbreak in the jail. The cumulative incidence, number of infections averted (NIA), and percentage of infections averted (PIA) were calculated comparing interventions against a base scenario without them. For the seven scenarios involving contact tracing and quarantining, total quarantines over the simulation and the number of quarantines per day were calculated to determine the quarantine requirements. Sensitivity analyses compared the impact of jointly varying vaccination rates and contact tracing rates. Results: Cell-level contact tracing alone was an ineffective intervention (3.2% PIA), but its impact increased in combination with other interventions (i.e., vaccination or increased jail release rate). The other intervention strategies each produced a PIA over 10%, with the jail release scenario producing a PIA of nearly 20% despite only resulting in a 13% reduction in the jail population. The all-level contact tracing only scenario was effective at both 50% and 100% of contacts traced, but feasibility would be limited without a reduction in the jail population. Conclusions: Implementing a combination intervention approach could substantially reduce the morbidity from COVID-19 and future respiratory viruses in this jail setting while providing secondary protection to the community.

Identifiers

PMID40027595
PMCPMC11869379

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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.