Evidence map›Paper›PMID 35610237›Full record

ArticleNature communications2022

Addressing the socioeconomic divide in computational modeling for infectious diseases.

Michele Tizzoni, Elaine O Nsoesie, Laetitia Gauvin, Márton Karsai, Nicola Perra, Shweta Bansal

Abstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 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

32 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Incorporating Social Determinants of Health in Infectious Disease Models: A Systematic Review of Guidelines.Medical decision making : an international journal of the Society for Medical Decision Making · 2024
    Pooled it
  2. Article
  3. Partisan differences in health behaviors can impact respiratory disease dynamics.medRxiv : the preprint server for health sciences · 2026
    Article
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  13. Review
  14. Comparative evaluation of behavioral epidemic models using COVID-19 data.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  15. Review
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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.

Michele TizzoniISI Foundation, Turin, Italy. michele.tizzoni@isi.it.ORCID 0000-0001-7246-2341
Elaine O NsoesieDepartment of Global Health, School of Public Health, Boston University, Boston, MA, USA.ORCID 0000-0001-9170-8714
Laetitia GauvinISI Foundation, Turin, Italy.
Márton KarsaiDepartment of Network and Data Science, Central European University, 1100, Vienna, Austria.ORCID 0000-0001-5382-8950
Nicola PerraSchool of Mathematical Sciences, Queen Mary University of London, London, UK.ORCID 0000-0002-5559-3064
Shweta BansalDepartment of Biology, Georgetown University, Washington, DC, USA.

Funding

Vaccine hesitancy and erosion of herd immunity: harnessing big data to forecast disease re-emergenceR01GM123007 · NIGMS · GEORGETOWN UNIVERSITY · PI BANSAL, SHWETA · 2017 to 2021
$2.1M
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Communicable DiseasesComputer SimulationHumansSocioeconomic Factors

Identifiers

PMID35610237
PMCPMC9130127

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.