Background: Effective control of infectious diseases relies heavily on understanding transmission dynamics and implementing interventions that reduce the spread. Non-pharmaceutical interventions (NPIs), such as mask-wearing, social distancing, and quarantining, are vital tools in managing outbreaks where vaccines or treatments are limited. However, the success of NPIs is influenced by human behavior, including compliance with guidelines, and attitudes such as beliefs about the effectiveness of interventions. In this study, we applied an innovative proximity-based experimentation platform to generate empirical data on behaviors and attitudes and their effect on disease transmission. Our platform uses a smartphone application that enables the spread of a digital pathogen among participants via Bluetooth during open-world "experimental epidemic games". This creates an environment for epidemiology field experimentation where researchers can control transmission mechanics and collect full ground-truth datasets. Methods: Our study employed the "epidemic" app to investigate the impact of risk perception and compliance to NPIs on pathogen transmission. Involving nearly 1,000 participants in a two-weeks long epidemic game at Wenzhou-Kean University (WKU) in China, the app generated a multimodal dataset, which allowed us to develop and parameterize Susceptible-Exposed-Infected-Recovered (SEIR) models. We quantified the extent by which behavioral factors, such as risk perception and compliance with quarantine, and strength of intervention strategies influence disease transmission. The model incorporates time-varying transmission rates that reflect changes in attitudes and behavior, and we calibrated it using the empirical data from the epidemic game to provide critical insights into how variations in NPI compliance levels affect outbreak control. Findings: The findings reveal that adherence to NPIs alone, which is influenced by changes in behavior and attitudes, may not result in the expected reduction in transmission, illustrating the complex interplay between behavioral factors and epidemic control. Moreover, the model further shows that changes in risk perception coupled with NPI adherence could significantly reduce infection levels as well as susceptibility. Interpretation: Our study highlights the usefulness of experimental epidemic games to generate realistic datasets, and the importance of integrating behavioral dynamics into epidemiological models to enhance the accuracy of predictions and the effectiveness of public health interventions during infectious disease outbreaks.

The authors have declared no competing interest.

The development of the original Operation Outbreak app and backend infrastructure has been supported by the Gordon and Betty Moore Foundation (grants GBMF9125, GBMF9125.01, and GBMF11392). The customizations of the app and backend required for the WKU game were funded by a startup grant awarded by UMass Chan Medical School to Andres Colubri.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The protocol for the experimental game was approved by WKU Ethics Committee.

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