Restoring trust in government and institutions may influence pandemic decision making

During the COVID-19 pandemic, local, state and national agencies were continually updating infection information to educate the public and leaders tasked with balancing public health and economic growth. At the time, different communities and countries reacted differently to this information: Some locales kept schools open while entire countries were placed under mandatory lockdowns.

While infection rates, season and other factors undoubtedly influenced the behavior and decisions in various locations worldwide, individuals’ decisions to shelter-in-place, mask or go about normal daily life within a single community varied greatly despite having access to similar information.

This prompted a group of researchers from the Joint Support-Center for Data Science Research, the Research Organization of Information and Systems (ROIS-DS) and the Institute of Statistical Mathematics in Japan to systematically investigate whether people in different cultures and within cultures react differently to similar pandemic information. The researchers created surveys to collect demographic information about volunteers and how they would react to specific information regarding 18 hypothetical COVID-19 social situations in the context of, for example, local infection rates, personal vaccination status or the number of available hospital beds. The identically-designed surveys were conducted during 2022 in three regions —the UK, Japan, and Taiwan—selected for their similarities as high-income economies and being insular states capable of undertaking relatively strict border measures.

The team published their research on August 13^th, 2025 in Data Science Journal.
(https://datascience.codata.org/articles/10.5334/dsj-2025-021)

Now that COVID-19 is considered an endemic disease worldwide, the researchers’ goal was to characterize the factors that influence riskier versus risk-averse behaviors in the context of new diseases.  “We designed this study to gain a deeper, data-driven understanding of the relationship between information provision and people's behaviors related to new infectious diseases,” said Dr. Naoko Kato-Nitta, a primary author of the research paper.

The researchers discovered key differences in how individuals from different cultures, Japan, Taiwan and the U.K., respond to the same information. Specifically, respondents from Japan and Taiwan were most sensitive to the number of hypothetical people who were infected daily with COVID-19. This information would evoke more cautious behaviors in Japanese and Taiwanese respondents compared to other types of information, such as their ability to work from home.

In contrast, respondents for the U.K. were most sensitive to the presence of a familiar infected person, such as a coworker or family member. This information elicited more risk-averse behaviors in U.K. respondents versus, for example, capacity restrictions at large events, the number of new infections or whether they lived with an elderly or high-risk family member.

“The study’s findings can contribute to policymakers’ and medical experts’ deeper understanding of the relationship between information provision and behaviors related to a new infectious disease, as well as emphasize how data-driven analysis can be leveraged to gain deeper insights into complex societal behaviors,” said Kato-Nitta.

Besides revealing how different cultures can respond differently to the same information, the research group also identified subgroups within respondents—risk-taking versus more cautious groups—that share specific characteristics. The team found that risk-taking subgroups had a higher proportion of younger-male respondents with vaccine hesitancy, which might reflect that this subgroup is more confident in their physical health. In contrast, the risk-averse group included a higher proportion of individuals that couldn’t be vaccinated for medical reasons, higher science literacy, or had a higher trust in governmental or institutional measures against the spread of the virus. This was consistent between all three cultural regions.

The study revealed that restoring people’s trust in governmental and medical institutions may go a long way towards influencing individual decision making and behavioral change, particularly in more risk-taking subgroups. Importantly, this type of effort could significantly impact the course of pandemics in the future.

“My ultimate goal is to more comprehensively understand the key factors that affect people’s risk perceptions toward applying emerging science to everyday life based on empirical results and to establish a new model of science communication,” said Kato-Nitta.

This study was supported by a Strategic Research Projects grant from the Research Organization of Information and Systems (ROIS) and a KAKENHI (JP21K02938 and 25K06630) grant from the Japan Society for the Promotion of Science.

 

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About the Joint Support-Center for Data Science Research (ROIS-DS)

The Joint Support-Center for Data Science Research (ROIS-DS) is a part of Japan's Research Organization of Information and Systems (ROIS). Established in 2016, ROIS-DS is a joint research center for the advancement of interdisciplinary data science. The center's mission is to support wide range of researchers and students to conduct research in data-sciences in the hope of solving scientific and social problems. The center aims to cultivate and strengthen collaboration and cooperation among universities and other institutions by promoting data sharing and providing data analysis support across disciplines, as well as helping human resource development related to data science.

 

About the Institute of Statistical Mathematics

The Institute of Statistical Mathematics (ISM) is part of Japan's Research Organization of Information and Systems (ROIS). With more than 75 years of history, the institute is an internationally renowned facility for research on statistical mathematics including survey research and the Japanese national character survey. ISM comprises three different departments including the Department of Statistical Modeling, the Department of Statistical Data Science, and the Department of Statistical Inference and Mathematics, as well as several key data and research centers. Through the efforts of various research departments and centers, ISM aims to continuously facilitate cutting edge research collaboration with universities, research institutions, and industries both in Japan and other countries.

 

About the Research Organization of Information and Systems (ROIS)

ROIS is a parent organization of four national institutes (National Institute of Polar Research, National Institute of Informatics, the Institute of Statistical Mathematics and National Institute of Genetics) and the Joint Support-Center for Data Science Research. It is ROIS's mission to promote integrated, cutting-edge research that goes beyond the barriers of these institutions, in addition to facilitating their research activities, as members of inter-university research institutes.

 

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