Evidence map›Paper›PMID 29566137›Full record

SynthesisEpidemiologic reviews2018

Dynamic Models of Infectious Disease Transmission in Prisons and the General Population.

Martial L Ndeffo-Mbah, Vivian S Vigliotti, Laura A Skrip, Kate Dolan, Alison P Galvani

Abstract readSystematic Review
In one paragraph

Synthesis in Epidemiologic reviews, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 3 pooled it
–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

37 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
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  7. Article
  8. COVID-19 Burden in Adult Correctional or Detention Facilities and the Surrounding Communities, January 1, 2020-July 20, 2021.Journal of correctional health care : the official journal of the National Commission on Correctional Health Care · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Dynamics of Respiratory Infectious Diseases in Incarcerated and Free-Living Populations: A Simulation Modeling Study.Medical decision making : an international journal of the Society for Medical Decision Making · 2023
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
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

5 authors.

Martial L Ndeffo-MbahCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, Connecticut.
Vivian S VigliottiCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, Connecticut.
Laura A SkripCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, Connecticut.
Kate DolanProgram of International Research and Training, National Drug and Alcohol Research Centre, University of New South Wales, Sydney, New South Wales, Australia.
Alison P GalvaniCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, Connecticut.

Funding

Impacts of Individual and Social Behavior on Influenza Dynamics and ControlU01GM087719 · NIGMS · YALE UNIVERSITY · PI GALVANI, ALISON P, MEYERS, LAUREN ANCEL · 2009 to 2018
$6.3M
Accelerating viral outbreak detection in US cities using mechanistic models, machine learning and diverse geospatial dataR01AI151176 · NIAID · YALE UNIVERSITY · PI GALVANI, ALISON P, MEYERS, LAUREN ANCEL · 2020 to 2024
$3.9M
Evaluating the social influences that impact vaccination decisionsU01GM105627 · NIGMS · YALE UNIVERSITY · PI GALVANI, ALISON P · 2013 to 2017
$1.6M
NIAID NIH HHS R01 AI151176NIGMS NIH HHS U01 GM087719NIGMS NIH HHS U01 GM105627
6 · The paper itself

Abstract

Incarcerated populations experience elevated burdens of infectious diseases, which are exacerbated by limited access to prevention measures. Dynamic models are used to assess the spread and control of diseases within correctional facilities and repercussions on the general population. Our systematic review of dynamic models of infectious diseases within correctional settings identified 34 studies published between 1996 and 2017. Of these, 23 focused on disease dynamics and intervention in prison without accounting for subsequent spread to the community. The main diseases modeled in these studies were human immunodeficiency virus (HIV; n = 14, 41%), tuberculosis (TB; n = 10, 29%), and hepatitis C virus (HCV; n = 7, 21%). Models were fitted to epidemiologic data in 14 studies; uncertainty and sensitivity analyses were conducted in 8, and validation of model projection against empirical data was done in 1 study. According to the models, prison-based screening and treatment may be highly effective strategies for reducing the burden of HIV, TB, HCV, and other sexually transmissible infections among prisoners and the general community. Decreasing incarceration rates were projected to reduce HIV and HCV infections among people who inject drugs and TB infections among all prisoners. Limitations of the modeling studies and opportunities for using dynamic models to develop quantitative evidence for informing prison infection control measures are discussed.

Indexed as

Disease Transmission, InfectiousModels, BiologicalPrisonersPrisonsCommunicable Disease ControlCommunicable DiseasesGlobal HealthHumans

Identifiers

PMID29566137
PMCPMC5982711

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.