Balancing health and economy: A new model to assess pandemic response strategies

In order to minimize the impact of a pandemic on the economy, which would be more effective: a lockdown or letting individuals spontaneously reduce their risk of infection? Research recently published in the journal Nature Human Behaviour by Spanish scientists suggests that these two widely debated options lead to similar outcomes; that is, the economy will always be damaged, but at least a lockdown will save more lives. Using an innovative model on the impact on health and the economy of the measures applied during the pandemic, an international team including researchers from the University of Zaragoza and the Universidad Carlos III de Madrid (UC3M) is addressing some of the central debates on measures during the COVID-19 pandemic. This model, tested using data from New York City's responses to this pandemic, will allow governments to make difficult decisions and assess which policies are most effective in minimizing the socio-economic impact of a pandemic in the future.

The computational model, which has been developed by an international team co-led by researchers Alberto Aleta and Yamir Moreno from the Institute for Biocomputation and Physics of Complex Systems (BIFI-UNIZAR), together with Marco Pangallo from the CENTAI Institute in Italy, allows us to simulate with great detail the evolution of a pandemic, its effect on the economy and, in turn, how the economy influences the course of the pandemic.

The modelling of this balance between health and economic impact, published in the latest issue of the journal Nature Human Behaviour, is the result of years of work by an interdisciplinary team of research staff with backgrounds in economics and epidemiology, as well as physics, computer science and applied mathematics, all united by a shared expertise in complexity science. This international research group combined economic modelling with epidemic data to create a comprehensive tool that can predict the health-economic outcomes of political and health measures during a pandemic.

The model developed represents significant progress that can help governments plan responses to future pandemics."

Esteban Moro, one of the study's authors from MIT´s Sociotechnical Systems Research Centre and UC3M

Among the conclusions obtained in the study on the effectiveness of government interventions, researchers have found that both stricter lockdowns and strong change in behaviour lead to more unemployment and fewer COVID-19 deaths. In addition, closing non-physical (non-customer contact) industries, such as manufacturing, has little impact on infections but significantly increases unemployment. Delaying the start of protective measures does little to help the economy and worsens epidemic outcomes in all scenarios.

This study also rejects the idea (more widespread in the US than in Spain) that self-protection of those most vulnerable to the virus would have saved the economy during the COVID-19 pandemic. Overall, their results have revealed that low-income workers bear the brunt of political decisions related to the health-economy trade-off; that is, the measures lead to more job losses and more lives saved among low-income workers than among high-income workers.

For Alberto Aleta, one of the two lead authors of the work, this study sheds light on the divergent views that arose during the pandemic: "According to some, the lockdowns did not impose a trade-off between health and economy because if the virus had not remained under control, the economy would have been damaged anyway. According to others, with the virus out of control, at-risk people would spontaneously minimise contact, obtaining better epidemiological and economic results, without trade-offs between health and the economy. These debates remained unresolved, partly due to the lack of quantitative, data-driven models that could provide clear scientific evidence in favour of one position or the other. Until now."

"Studying the rules of human behaviour and incorporating them into models is crucial for making the most effective decisions in crisis situations," says Yamir Moreno. "Our work shows that the availability of detailed data makes it possible to build agent-based models to study mitigation strategies and behavioural feedback during a pandemic. Although lockdowns and a change in behaviour lead to similar scenarios, the latter is the result of self-organisation, while the former can be implemented as soon as required for maximum effectiveness."

This research article is timely, given the debate on measures during COVID-19, according to Esteban Moro: "Governments around the world have begun their 'moments of reflection', reviewing the effectiveness of a wide range of policies implemented during that pandemic," he says. The innovative model provided by this international consortium of researchers offers detailed insights based on urban mobility data, indicating that both forced lockdowns and voluntary behaviour change lead to a significant impact on health and the economy. "The model challenges the proposal that it was possible to save lives without doing any damage to the economy. Those who made such claims were not basing their belief on quantitative analysis," adds Esteban Moro.

This international team of scientists includes researchers from the CENTAI Institute in Turin; the University of Zaragoza; the Complexity Science Hub in Vienna; the Universidad Carlos III de Madrid; Northeastern University (Boston & Portland); the Institute for New Economic Thinking at the Oxford Martin School; the Bloomington University School of Public Health; the Massachusetts Institute of Technology; and the Santa Fe Institute.