Evidence map›Paper›PMID 38053386›Full record

ArticleJournal of the Royal Society, Interface2023

Population age and household structures shape transmission dynamics of emerging infectious diseases: a longitudinal microsimulation approach.

Signe Møgelmose, Laurens Vijnck, Frank Neven, Karel Neels, Philippe Beutels, Niel Hens

Open access · hybridAbstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 10% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. medRxiv : the preprint server for health sciences · 2026
    Article
  4. The Role of Youths in Within-Household Tuberculosis Transmission: A Household Contact Cohort Study.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026
    Article
  5. 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

6 authors at 2 institutions in 2 countries.

Signe MøgelmoseData Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics, Hasselt University, Hasselt, Belgium.ORCID 0000-0001-6399-7424
Laurens VijnckData Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics, Hasselt University, Hasselt, Belgium.
Frank NevenData Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics, Hasselt University, Hasselt, Belgium.
Karel NeelsCenter for Population, Family and Health, University of Antwerp, Antwerp, Belgium.
Philippe BeutelsCentre for Health Economic Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.
Niel HensData Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics, Hasselt University, Hasselt, Belgium.ORCID 0000-0003-1881-0637
University of Antwerp · BEHasselt University · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Host population demographics and patterns of host-to-host interactions are important drivers of heterogeneity in infectious disease transmission. To improve our understanding of how population structures and changes therein influence disease transmission dynamics at the individual and population level, we model a dynamic age- and household-structured population using longitudinal microdata drawn from Belgian census and population registers. At different points in time, we simulate the spread of a close-contact infectious disease and vary the age profiles of infectiousness and susceptibility to reflect specific infections (e.g. influenza and SARS-CoV-2) using a two-level mixing model, which distinguishes between exposure to infection in the household and exposure in the community. We find that the strong relationship between age and household structures, in combination with social mixing patterns and epidemiological parameters, shape the spread of an emerging infection. Disease transmission in the adult population in particular is to a large degree explained by differential household compositions and not just household size. Moreover, we highlight how demographic processes alter population structures in an ageing population and how these in turn affect disease transmission dynamics across population groups.

Indexed as

Communicable Diseases, EmergingInfluenza, HumanAdultFamily CharacteristicsHumansdemographydisease transmissionepidemiologyhousehold structuresmathematical modellingpopulation ageing

Identifiers

PMID38053386
PMCPMC10698481
OpenAlexW4389393844

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.