Understanding the spatio-temporal social determinants of health to improve agent-based modelling of recurrent COVID-19 outbreaks (COVID-SHINE)

Epidemics are a major part of the “big picture” of historical change and development. They give rise to fears and anxieties, including phenomena of increasing stigmatization, hysteria, and social unrest; they have devastating effects on suffering and death, including the increase of health inequalities. How the scientific and global community deals with these issues may well be an important factor in determining the survival of our society, and perhaps of humankind. However, since epidemic diseases are not random events but phenomena created by the specific vulnerabilities of each society, a key challenge is to decipher the social structures and the factors that accompany them.

Like any other infectious disease, the COVID-19 pandemic is embedded in a social context that determines differential levels of exposure, susceptibility and access to health resources, thereby causing and amplifying inequalities in incidence. A central research concern is not just to understand the way the disease evolves and how it impacts society but also to predict, prevent, and control it. The project has two general aims: (1) to enhance the ability of modeling strategies to predict the dynamics of recurrent outbreaks of COVID-19 by incorporating social determinants of health, and (2) to develop an integrated systems framework to inform policies, emphasizing on the reduction of health inequalities. This study takes the pandemic evolution in the region of Catalonia as its empirical basis. The research team involved in the COVID-SHINE project is composed by three sub-teams, respectively in charge of the main pillars of the project: a) Epidemiology, Social Determinants of Health and Systemic Policy Framework: GREDS-EMCONET and JHU-UPF Public Policy Center, built upon a transdisciplinary team of researchers, b) Complexity analyses and Modeling: Institute for Cross- Disciplinary Physics and Complex Systems (IFISC) is a joint Institute of the University of the Balearic Islands (UIB) and the Spanish National Research Council (CSIC), c) Biomedicine and Clinical Epidemiology: Vall d’Hebron Institute for Research. This project is being funded by Fundación Bancaria La Caixa.

A central research concern is not just to understand the way the disease evolves and how it impacts society but also to predict, prevent, and control it. Despite the rapid progress in scientific research, many questions remain unanswered: How and through which key drivers is the pandemic evolving? What social factors promote vulnerability and what health inequalities is it generating? What are the best modeling strategies to capture the complexity of the pandemic and guide policy interventions? Therefore, the project is in line with the target of strengthening the capacity of all countries, particularly developing countries, for early warning, risk reduction and management of national and global health risks.

One of the key factors of the research is to provide and disseminate timely information based on our findings and recommendations. Due to its integrative and transformative nature, COVID-SHINE will advance knowledge to comprehensively address the SDH relevant to understanding/modifying the course of COVID-19. The COVID-SHINE will generate four main types of impacts at the societal level, strongly tapping on current social debates: (1) we expect our research will contribute to developing awareness of the existence of disadvantaged groups concerning the epidemics and of their own special needs. Disregarding equity criteria in pandemic plans may increase social inequalities and the overall burden of COVID-19 if new outbreaks affect the most disadvantaged contexts; (2) the COVID-SHINE project will allow us to generate predictions regarding the health inequalities that could potentially arise during and after recurrent waves as well as the effect of public health interventions; (3) identifying the socioeconomic factors that condition the spread of the disease at the small-area level will facilitate the precise targeting of public health interventions for community protection and health care resources allocation; (4) by identifying inequitable patterns of disease burden between communities and individuals prone to experience the worse evolution of the pandemic, these findings will contribute to the goal of implementing novel equity-related systemic policies.