Second survey on the impact of social distancing measures on the Covid-19 epidemic in Spain

July 29, 2020

Younger people had fewer contacts outside home than  older people during the confinement of the Covid-19 pandemic, according to the first preliminary results of the survey of the Distance-Covid project, coordinated by IFISC (CSIC-UIB) researcher José Ramasco.

The researchers have just launched a second wave of the survey to understand how citizens' behavior is changing in the face of the epidemic and are asking for citizen collaboration. This information, which is completely anonymous, will provide a statistical basis for generating a series of scenarios and will help in the decision making process on possible action measures at this time of new outbreaks of infection.

The results of the first survey, which can be found on the project's website, collect information on the mobility and social behavior of citizens in recent months since the beginning of the pandemic, which is fundamental to understanding the spread and impact of Covid-19 in Spain.

With these first results, obtained after more than 4000 answers to the survey from a wide range of the population in Spain and with all the provinces represented, it has been possible to estimate the average number of people with whom adults resided during the last weeks of confinement in each autonomous community, and the patterns of contacts outside the home among different age groups. Using Bayesian estimation methods, the team has simulated the complete distributions of these estimates and is analyzing them to better understand how they affect the transmission patterns of Covid-19.

The Distancia-COVID project of the Consejo Superior de Investigaciones Científicas (CSIC), with the participation of IFISC (CSIC-UIB), the Centre d' Estudis Avançats de Blanes (CEAB), the Instituto de Física de Cantabria (IFCA), the Universitat Pompeu Fabra (UPF) and the Instituto de Economía, Geography and Demography (GDDI), is part of a multidisciplinary effort that uses computer and data science techniques to analyze the effect of the containment measures taken, on mobility and social behavior, to stop the spread of Covid-19. 


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