The Canton Ticino was the first region in Switzerland to be hit by the Covid-19 outbreak, leading local authorities to act quickly and efficiently to avoid the much feared overloading of the healthcare system. Unprecedented measures to contain and mitigate the epidemic have been enforced following the FOPH and the WHO recommendations. However, the response to the epidemic needs to account for the local context, culture, and circumstances, and of the unique characteristics of the health system. How can decision makers deal with such an unprecedented - and unknown - situation? What are the skills and methods required to determine, for example, how to modulate the capacity of the health system, including the number and organization of hospital wards and beds, to tackle the emergency?
Faced with such a challenge, a team of experts, involving professors Paolo Ferrari (Chief Medical Officer of the Ente Ospedaliero Cantonale, EOC - the public healthcare provider), Paulo Gonçalves (Full professor of Management at the USI Faculty of Economics), Emiliano Albanese (epidemiologist and Director of the Institute of Public Health at USI), Luca Crivelli (Director of the Department of Business Administration, Health and Social Affairs at SUPSI and lecturer at USI) have decided to support the work of the cantonal taskforce with the development of behavioural projection models that could not only project the spread of the disease, but also its impact on the hospital system.
"We developed a system dynamics model based on the traditional SEIR epidemiological model, with works by capturing data on Susceptible, Exposed (pre-symptomatic), Infected (symptomatic), individuals among the population", explains Prof. Gonçalves, who at USI runs also two executive training courses in humanitarian operations and logistics, during which participants are trained on these modelling systems to be deployed in the field. "In addition to the SEIR, our model captures the population of asymptomatic infectious individual and the testing of symptomatic individuals. We learned, in fact, that a significant fraction of the population infected with the virus never develop any symptoms, but they can still infect other individuals".
The modelling approach is used extensively in epidemiology to project how infectious diseases progress and to show the likely outcome of an epidemic, and therefore help inform decision makers on the health system adaptive changes, increases in services capacity, and on public health interventions, their timing, duration, and modes of implementation. Models like the SEIR are essentially based on assumptions, or collected statistics along with mathematics, to find parameters for various infectious diseases and use those parameters to calculate the effects of different interventions, like mass vaccination programmes. The modelling can help predict future growth patterns as measures are lifted or modulated, and are used to improve the preparedness of the health system also for future outbreaks.
"Our model was developed at the onset of the Covid-19 outbreak, when it was still considered an epidemic", says Prof. Gonçalves. "The collaboration with the EOC allowed us to collect data on the number of people hospitalised in the general ward and in intensive care, allowing us to also model these conditions explicitly. Moreover, our model integrates epidemiological relationships with behavioural changes, such as the social distancing reaction from high mortality rates, and the feedback from high incidence rates into the hospital system", Gonçalves concludes.
- Faculty of Biomedical Sciences
- Faculty of Economics