Evidence map›Paper›PMID 30253772›Full record

ArticleBMC medicine2018

Quantifying the impact of social groups and vaccination on inequalities in infectious diseases using a mathematical model.

James D Munday, Albert Jan van Hoek, W John Edmunds, Katherine E Atkins

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.9field-weighted citation impact, top 9% of its field
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

15 citing papers in PubMed, 38 citations in OpenAlex.

  1. Review
  2. Article
  3. Closing the Gap in Race-based Inequities for Seasonal Influenza Hospitalizations: A Modeling Study.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2025
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  5. Article
  6. Article
  7. Review
  8. Article
  9. The COVID-19 Vaccination and Vaccine Inequity Worldwide: An Empirical Study Based on Global Data.International journal of environmental research and public health · 2022
    Article
  10. Article
  11. Review
  12. Article
  13. Article
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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

4 authors at 1 institution in 2 countries.

James D MundayCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK. James.Munday@lshtm.ac.uk.ORCID 0000-0002-6206-7134
Albert Jan van HoekCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
W John EdmundsCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Katherine E AtkinsCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
London School of Hygiene & Tropical Medicine · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocial and cultural disparities in infectious disease burden are caused by systematic differences between communities. Some differences have a direct and proportional impact on disease burden, such as health-seeking behaviour and severity of infection. Other differences-such as contact rates and susceptibility-affect the risk of transmission, where the impact on disease burden is indirect and remains unclear. Furthermore, the concomitant impact of vaccination on such inequalities is not well understood.

methodsTo quantify the role of differences in transmission on inequalities and the subsequent impact of vaccination, we developed a novel mathematical framework that integrates a mechanistic model of disease transmission with a demographic model of social structure, calibrated to epidemiologic and empirical social contact data.

resultsOur model suggests realistic differences in two key factors contributing to the rates of transmission-contact rate and susceptibility-between two social groups can lead to twice the risk of infection in the high-risk population group relative to the low-risk population group. The more isolated the high-risk group, the greater this disease inequality. Vaccination amplified this inequality further: equal vaccine uptake across the two population groups led to up to seven times the risk of infection in the high-risk group. To mitigate these inequalities, the high-risk population group would require disproportionately high vaccination uptake.

conclusionOur results suggest that differences in contact rate and susceptibility can play an important role in explaining observed inequalities in infectious diseases. Importantly, we demonstrate that, contrary to social policy intentions, promoting an equal vaccine uptake across population groups may magnify inequalities in infectious disease risk.

Indexed as

Health Status DisparitiesModels, TheoreticalVaccinationCommunicable DiseasesDisease Transmission, InfectiousHumansRisk FactorsSocioeconomic FactorsInequalityInfluenzaMathematical modellingRubellaSocial groupsVaccination

Identifiers

PMID30253772
PMCPMC6156851
OpenAlexW2889156244

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.