Social-oriented, evidence-based Covid-19 prevention using GIS
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Abstract
Covid-19 has a socially skewed impact and prevention must be tailored specifically accordingly. The purpose is to implement an area-specific, social-oriented prevention in residential areas, slums, etc. based on epidemiological data from well-defined samples of the population.
Methods: Data for calculating the incidence rates and prevalence rates are collected like for an epidemiological study intervention. Local councils of each district and streets with its local characteristics, such as slum, business districts, industrial, etc. implement the data collection and assistance together with experts from ministries and universities.
Results: With valid epidemiological data as the background, the prevention is implemented in the barriers with the highest risks. Local councils of each district of the city implement data collection and plan prevention together with experts from ministries and universities.
Conclusion: By taking Covid-19 prevention into a scientific epidemiological context using the spatial distribution Geographic Information Systems (GIS) of the incidence - and prevalence rates, an effective social-oriented prevention is achieved.
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