Evidence map›Paper›PMID 23028275›Full record

ArticlePLoS computational biology2012

Inferring the structure of social contacts from demographic data in the analysis of infectious diseases spread.

Laura Fumanelli, Marco Ajelli, Piero Manfredi, Alessandro Vespignani, Stefano Merler

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 108 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
108citing papers in PubMed, 1 pooled it
9.5field-weighted citation impact, top 1% 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

108 citing papers in PubMed, 1 synthesis or guideline pooled it, 227 citations in OpenAlex.

  1. Pooled it
  2. Trial
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  7. Article
  8. VIBES: A multiscale modeling approach integrating within-host and between-hosts dynamics in epidemics.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
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  13. Journal of preventive medicine and hygiene · 2025
    Article
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  17. Article
  18. Emergence of the reproduction matrix in epidemic forecasting.Journal of the Royal Society, Interface · 2024
    Article
  19. Infectious Disease Modelling · 2024
    Review
  20. Article

48 more citing papers are in PubMed but not listed here.

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 at 3 institutions in 2 countries.

Laura FumanelliBruno Kessler Foundation, Trento, Italy. lfumanelli@fbk.eu
Marco Ajelli
Piero Manfredi
Alessandro Vespignani
Stefano Merler
Fondazione Bruno Kessler · ITNortheastern University · USUniversity of Pisa · IT

Funding

EpiC: A Cyberinfrastructure that Supports the Plug-and-Play of Datasets & AlgoriR21DA024259 · NIDA · TRUSTEES OF INDIANA UNIVERSITY · PI BORNER, KATY, SHERMAN, STEVEN J · 2007 to 2010
$1.2M
NIDA NIH HHS R21 DA024259NIDA NIH HHS R21-DA024259
6 · The paper itself

Abstract

Social contact patterns among individuals encode the transmission route of infectious diseases and are a key ingredient in the realistic characterization and modeling of epidemics. Unfortunately, the gathering of high quality experimental data on contact patterns in human populations is a very difficult task even at the coarse level of mixing patterns among age groups. Here we propose an alternative route to the estimation of mixing patterns that relies on the construction of virtual populations parametrized with highly detailed census and demographic data. We present the modeling of the population of 26 European countries and the generation of the corresponding synthetic contact matrices among the population age groups. The method is validated by a detailed comparison with the matrices obtained in six European countries by the most extensive survey study on mixing patterns. The methodology presented here allows a large scale comparison of mixing patterns in Europe, highlighting general common features as well as country-specific differences. We find clear relations between epidemiologically relevant quantities (reproduction number and attack rate) and socio-demographic characteristics of the populations, such as the average age of the population and the duration of primary school cycle. This study provides a numerical approach for the generation of human mixing patterns that can be used to improve the accuracy of mathematical models in the absence of specific experimental data.

Indexed as

Interpersonal RelationsModels, StatisticalProportional Hazards ModelsComputer SimulationContact TracingData Interpretation, StatisticalDisease OutbreaksDisease Transmission, InfectiousEuropeHumansIncidencePopulation SurveillanceRisk AssessmentRisk Factors

Identifiers

PMID23028275
PMCPMC3441445
OpenAlexW2044351514

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.