ArticlePloS one2013
Behavioral responses to epidemics in an online experiment: using virtual diseases to study human behavior.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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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.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Behavioural change models for infectious disease transmission: a systematic review (2010-2015).Journal of the Royal Society, Interface · 2016Pooled it
- Understanding the value of a forecast using an online game.PloS one · 2026Article
- Rather doomed than uncertain: risk attitudes and transmissive behavior under asymptomatic infection.Economic theory · 2022Article
- Non-pharmaceutical interventions during the COVID-19 pandemic: A review.Physics reports · 2021Review
- Excess influenza hospital admissions and costs due to the 2009 H1N1 pandemic in England.Health economics · 2019Article
- Next Generation Technology for Epidemic Prevention and Control: Data-Driven Contact Tracking.IEEE access : practical innovations, open solutions · 2019Article
- Signifying Zika: heterogeneity in the representations of the virus by history of infection.Cadernos de saude publica · 2018Article
- Spontaneous social distancing in response to a simulated epidemic: a virtual experiment.BMC public health · 2015Article
- Network information analysis reveals risk perception transmission in a behaviour-influenza dynamics system.Epidemiology and infection · 2015Article
- Acceptability of Nonpharmaceutical Interventions to Prevent the Risk of COVID-19 Infection in the United States.MDM policy & practiceArticle
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We report the results of a study we conducted using a simple multiplayer online game that simulates the spread of an infectious disease through a population composed of the players. We use our virtual epidemics game to examine how people respond to epidemics. The analysis shows that people's behavior is responsive to the cost of self-protection, the reported prevalence of disease, and their experiences earlier in the epidemic. Specifically, decreasing the cost of self-protection increases the rate of safe behavior. Higher reported prevalence also raises the likelihood that individuals would engage in self-protection, where the magnitude of this effect depends on how much time has elapsed in the epidemic. Individuals' experiences in terms of how often an infection was acquired when they did not engage in self-protection are another factor that determines whether they will invest in preventive measures later on. All else being equal, individuals who were infected at a higher rate are more likely to engage in self-protective behavior compared to those with a lower rate of infection. Lastly, fixing everything else, people's willingness to engage in safe behavior waxes or wanes over time, depending on the severity of an epidemic: when prevalence is high, people are more likely to adopt self-protective measures as time goes by; when prevalence is low, a 'self-protection fatigue' effect sets in whereby individuals are less willing to engage in safe behavior over time.
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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.