Evidence map›Paper›PMID 22154610›Full record

ArticleSocial science & medicine (1982)2012

Coupling infectious diseases, human preventive behavior, and networks--a conceptual framework for epidemic modeling.

Liang Mao, Yan Yang

Abstract read
In one paragraph

Article in Social science & medicine (1982), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Long Covid: conceptualizing the challenges for public health.Journal of public health (Oxford, England) · 2023
    Article
  5. Article
  6. Article
  7. Research on the Influence of Information Diffusion on the Transmission of the Novel Coronavirus (COVID-19).International journal of environmental research and public health · 2022
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. The Prediction of Infectious Diseases: A Bibliometric Analysis.International journal of environmental research and public health · 2020
    Review
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  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

2 authors.

Liang MaoDepartment of Geography, University of Florida, P.O. Box 117315, 3142 Turlington Hall, Gainesville, FL 32611, USA. liangmao@ufl.edu
Yan Yang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human-disease interactions involve the transmission of infectious diseases among individuals and the practice of preventive behavior by individuals. Both infectious diseases and preventive behavior diffuse simultaneously through human networks and interact with one another, but few existing models have coupled them together. This article proposes a conceptual framework to fill this knowledge gap and illustrates the model establishment. The conceptual model consists of two networks and two diffusion processes. The two networks include: an infection network that transmits diseases and a communication network that channels inter-personal influence regarding preventive behavior. Both networks are composed of same individuals but different types of interactions. This article further introduces modeling approaches to formulize such a framework, including the individual-based modeling approach, network theory, disease transmission models and behavioral models. An illustrative model was implemented to simulate a coupled-diffusion process during an influenza epidemic. The simulation outcomes suggest that the transmission probability of a disease and the structure of infection network have profound effects on the dynamics of coupled-diffusion. The results imply that current models may underestimate disease transmissibility parameters, because human preventive behavior has not been considered. This issue calls for a new interdisciplinary study that incorporates theories from epidemiology, social science, behavioral science, and health psychology.

Indexed as

CommunicationHealth BehaviorModels, BiologicalCommunicable DiseasesComputer SimulationEpidemicsHumansInfluenza, HumanPrimary PreventionSocial EnvironmentSocial Support

Identifiers

PMID22154610
PMCPMC7126515

What OpenQuestion holds

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Registered trials

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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.