ArticleThe Science of the total environment2021
How do social media and individual behaviors affect epidemic transmission and control?
Article in The Science of the total environment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 60 citations in OpenAlex.
- Dynamical analysis of the SVEIR-M epidemic model with age structure under media coverage.Infectious Disease Modelling · 2026Article
- Evaluating the association between COVID-19 transmission and mobility in omicron outbreaks in China.Communications medicine · 2025Article
- Subject Modeling-Based Analysis of the Evolution and Intervention Strategies of Major Emerging Infectious Disease Events.Risk management and healthcare policy · 2025Article
- Measles resurgence in Armenia: unmasking health system vulnerabilities and crafting comprehensive eradication strategies - a review.Annals of medicine and surgery (2012) · 2024Review
- Chaos in Opinion-Driven Disease Dynamics.Entropy (Basel, Switzerland) · 2024Article
- Exploring the Singapore general population's trust in COVID-19 information from different sources and its association with perceived risk of infection during the pandemic.Frontiers in public health · 2024Article
- Article
- The long-term effectiveness and cost-effectiveness of public health interventions; how can we model behavior? A review.Health economics · 2023Review
- The relationship between the sources of confidence in overcoming COVID-19 and the improvement of medical students' professional identity: mediation by medical students' attention to COVID-19.BMC medical education · 2023Article
- The impact of the intensity of media use on potential tourists' risk perception and travel protective behavioral intentions in COVID-19.Frontiers in psychology · 2023Article
- FOMO (fate of online media only) in infectious disease modeling: a review of compartmental models.International journal of dynamics and control · 2023Review
- How local outbreak of COVID-19 affect the risk of internet public opinion: A Chinese social media case study.Technology in society · 2022Article
- Using simulation modelling and systems science to help contain COVID-19: A systematic review.Systems research and behavioral science · 2022Article
- Exploring a Multi-Layer Coupled Network Propagation Model Based on Information Diffusion and Bounded Trust.International journal of public health · 2022Article
- Environmental Value and Pro-environmental Behavior Among Young Adults: The Mediating Role of Risk Perception and Moral Anger.Frontiers in psychology · 2022Article
- Analysis of efficacy of intervention strategies for COVID-19 transmission: A case study of Hong Kong.Environment international · 2021Article
- Appropriate Strategies for Reducing the Negative Impact of Online Reports of Suicide and Public Opinion From Social Media in China.Frontiers in public health · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the outbreak of infectious diseases such as COVID-19, social media channels are important tools for the public to obtain information and form their opinions on infection risk, which can affect their disease prevention behaviors and the consequent disease transmission processes. However, there has been a lack of theoretical investigation into how social media and human behaviors jointly affect the spread of infectious diseases. In this study, we develop an agent-based modeling framework that couples (1) a general opinion dynamics model that describes how individuals form their opinions on epidemic risk with various information sources, (2) a behavioral adoption model that simulates the adoption of disease prevention behaviors, and (3) an epidemiological SEIR model that simulates the spread of diseases in a host population. Through simulating the spread of a coronavirus-like disease in a hypothetical residential area, the modeling results show that social media can make a community more sensitive to external drivers. Social media can increase the public's awareness of infection risk, which is beneficial for epidemic containment, when high-quality epidemic information exists at the early stage of pandemics. However, fabricated and fake news on social media, after a "latent period", can lead to a significant increase in infection rate. The modeling results provide scientific evidence for the intricate interplay between social media and human behaviors in epidemic dynamics and control, and highlight the importance of public education to promote behavioral changes and the need to correct misinformation and fake news on social media in a timely manner.
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Registered trials
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.