Modelling the Impact of Human Behaviours on Infections Spread

Project Information

IMMUNE

Grant agreement ID: 101003183

DOI

10.3030/101003183

EC signature date 17 May 2021

Start date 1 June 2021

End date 31 December 2026

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost

€ 1 986 437,00

EU contribution

€ 1 986 437,00

Coordinated by

UNIVERSITA COMMERCIALE LUIGI BOCCONI
Italy

Periodic Reporting for period 3 - IMMUNE (Modelling the Impact of Human Behaviours on Infections Spread)

Reporting period: 2024-06-01 to 2025-11-30

Summary of the context and overall objectives of the project

In the context of significant strides in infectious disease control, recent outbreaks, including SARS, H1N1 influenza, Ebola, resurgent measles, and the novel Coronavirus, remain substantial threats to global health. Despite the proven efficacy and safety of vaccines, a troubling surge in vaccine hesitancy, notably pronounced in Europe, has resulted in increased vaccine refusal and a decline in routine immunization coverage. Widespread misconceptions, such as the belief in low disease prevalence post-immunization success, contribute to a reduced sense of urgency for vaccination. Mathematical modeling and computer simulations have emerged as indispensable tools for probing infectious disease dynamics and assessing the impact of vaccination strategies. Recent modeling endeavors transcend traditional assumptions, incorporating realistic demographic patterns and social interactions. However, the understanding of mechanisms steering behavioral responses to risk perception remains in its early stages, emphasizing the need for further research to inform policy decisions. The overarching goal of the IMMUNE project is to advance the epidemiological modeling framework by integrating human behaviors and their interconnections with underlying epidemiological processes. To achieve this, the IMMUNE project will: i) gather nationally representative data from selected EU countries on human perceptions and behaviors regarding infectious diseases, vaccine risks, and vaccination programs, analyze their spatial distribution within and between countries and their temporal dynamics; ii) explore the importance of peers' influence and network effects on individual's intentions regarding vaccination and other preventive behaviors; iii) develop infection-specific population and agent-based epidemiological models informed with the gathered country-specific behavioral data and assess the bidirectional effects and the interdependencies between the epidemiological process and the behavioral components. This comprehensive approach aims to enhance our understanding of the intricate interplay between human behaviors, vaccine acceptance, and infectious disease dynamics, ultimately contributing to informed and effective public health policies.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

With the aim of expanding epidemiological models with behavioral and human decisions processes, in the first 30 months of the project the IMMUNE team has designed a field study which aims at gathering data on individuals’ perceptions of risks on vaccines and diseases, vaccination decisions, adoption of preventive behaviors, peers influence, social interactions, exposures to information and associated trust, moral attitudes. The design of the field study has been anchored to a theoretical model of behavior change named “Capability, Opportunity, and Motivation Behavior Model” (COM-B).
In parallel to the primary data collection study, social media platforms (ie Twitter/X, Reddit) were also monitored and data was downloaded over time to assess online discourse with regards to vaccination decisions. In particular, data from a set of subreddits channels was downloaded to assess the presence of echo chambers and polarization attitudes. The role of peers’ influence on vaccination decision was investigated thanks to available data for Italy and the UK on vaccination decisions and exposures. This data is currently being used in an Agent-Based Modelling framework to assess the effects of network dynamics and individuals’ decisions on the overall vaccine uptake.
In addition to these activities, the team has been involved in several research projects driven by the occurrence of the COVID-19 global pandemic. During the first year of the global pandemic the IMMUNE team participated to a field study to collect local and national data on individuals’ social interactions. This kind of data is essential for infectious diseases models as they represent the channels through which the infection can spread in the population. Data was thus gathered firstly in the metropolitan city of Milan, in the northern part of Italy and Western epicenter of SARS-CoV-2 pandemic, and then nationally to assess the impact of the imposed tiers restrictions on individual behaviors and SARS-CoV-2 transmissibility. Research activities on Covid-19 vaccination decisions and face mask usage were also conducted given the extremely high relevance of these topics in the battle against the global spread of the virus. In particular, a first survey experiment was conducted to study whether and to what extent the provision of different kind of information had any effect on adults’ decision to vaccinate children. A second experiment examined the causal relationship between beliefs, social norms and reported intentions to engage in mask promoting behavior. A conjoint experiment was also conducted in 13 countries to evaluate citizens’ preferences for Covid-19 vaccine allocation priorities and for it being mandatory.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The IMMUNE project represents a groundbreaking initiative poised to revolutionize infectious disease modeling tools. Unlike conventional approaches, this project introduces a paradigm shift by integrating human behaviors as intrinsic elements within the model structure. This innovative approach marks a significant departure from traditional methodologies, offering a pioneering framework that considers the dynamic interplay between epidemic and pandemic processes and human behaviors. The ultimate goal is to enhance the realism of model simulations, aligning them more closely with actual scenarios.
To realize this ambitious objective, the project is undertaking comprehensive data collection initiatives across various European countries. These efforts aim to deepen our understanding of the intricate mechanisms underlying individuals' decision-making processes regarding vaccination and other preventive behaviors and to assess the impact of policy measures and communication strategies on shaping these decisions.
Recognizing the evolving landscape of information dissemination, the IMMUNE project acknowledges the significance of alternative data sources. Social media channels, serving as dynamic platforms for public discourse, are harnessed as valuable reservoirs of real-time information. By incorporating insights derived from social media into the modeling framework, the project aims to complement and enrich the primary data collection efforts. This multi-faceted approach ensures a comprehensive understanding of the factors influencing public health decisions.
The interdisciplinary nature of the IMMUNE project underscores its commitment to fostering collaboration across diverse fields, including epidemiology, behavioral science, and data analytics.
As the IMMUNE project progresses, it stands at the forefront of scientific innovation, pushing the boundaries of infectious disease modeling. The incorporation of human behaviors as integral components within the modeling framework heralds a new era of accuracy and relevance in simulating epidemic and pandemic scenarios. Through meticulous data collection efforts and the integration of alternative sources, the project aspires to empower policymakers and public health professionals with unparalleled insights, thereby contributing to more effective strategies for disease prevention and control.