Crowdsourcing for the spatialization and signaling of Covid-19 transmission predictors: an approach based on risk perception

• Murilo Guerreiro Arouca UFBA
• Carlos Daniel S. Cruz UFBA
• Marcos Ennes Barreto UFBA / LSE
• Isa Beatriz da C. Neves UFBA
• Federico Costa UFBA
• Hussein Khalil SLU
• Ricardo Lustosa Brito UFBA

DOI: https://doi.org/10.5753/sbsc.2022.19477

Resumo

Popular participation in public health actions is essential for fighting Covid-19, especially in vulnerable urban communities where the lack of geographical data at fine resolution scale hinders appropriate spatial responses. This work proposes a crowdsourcing-based solution that captures georeferenced data regarding the population's perception of risk in relation to transmission predictors of Coronavirus. The proposed solution allows for mapping and sending real-time alerts regarding the presence of such transmission predictors. A validation study involving 20 people from a community in the city of Salvador revealed that the proposed solution is highly acceptable as user-centred alert tool, especially among young people.

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