Balancing socio-economic and public health impact of COVID19 for its sustainable control and mitigation (SOPHIA)
- Funded by FWO Belgium
- Total publications:2 publications
Grant number: G0G9820N
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Key facts
Disease
COVID-19Known Financial Commitments (USD)
$292,500Funder
FWO BelgiumPrincipal Investigator
Ingmar Nopens, Christel Faes, Jan Baetens, Mattias Desmet, Ellen Van De Vijver, Marc Van Meirvenne, Thomas Nuyens…Research Location
BelgiumLead Research Institution
Katholieke Universiteit Leuven, Ghent University, University of HasseltResearch Priority Alignment
N/A
Research Category
Secondary impacts of disease, response & control measures
Research Subcategory
Indirect health impacts
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
Given the uncertainty about the further development of the COVID-19 pandemic, decision makers urgently need to balance the immediate public health impact of the virus and the - yet uninvestigated - psychological and socio-economic impacts of the mitigation measures that were imposed to safeguard our health care system. Just as the spread of COVID-19 itself, these effects are spatially heterogeneous and scale dependent, hence the need to study the intertwined psychological and socio-economic impacts at multiple spatial scales. To better understand the spatial heterogeneity of these effects, the inverse question is equally important: how does the socio-economic condition of a region affect both the virus spread and the impact of the measures? We will consider data on suicides, use of psychofarmaca, absenteeism due to psychological suffering, burnouts,... Since analysis of these data by the responsible governmental agencies lags at least one year, we will collect raw data and conduct (geostatistical) data analyses in relation to spatio-temporal variation in the measures to support decision-making on further control and mitigation strategies. We will use available socio-economic data at a high spatial resolution to infer relationships among the spacedependent parameters in the spatial COVID-19 model, the observed local spread of the virus and the psychological and socio-economic response on the measures. At the smallest spatial scales, this will require geostatistical methods.
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