Crowdsourcing for the spatialization and signaling of Covid-19 transmission predictors: an approach based on risk perception
Anais do XVII Simpósio Brasileiro de Sistemas Colaborativos (SBSC 2022)(2022)
摘要
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.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要