Cognitive Model for Epidemiological Surveillance in the Public Space. The Case of Chone, Ecuador

Abstract

Given inadequate public health conditions and weak leadership processes in epidemiological containment and prevention in the cities of Ecuador, the generation of local information is required for public decision-making regarding COVID-19, taking advantage of socio-technological innovations as support for spatial planning processes. This article proposes the design and application of a model for the prevention of epidemiological contagion risks in public spaces and places of social congregation, which facilitates the identification of behavioral patterns that imply epidemiological contagion risks and the design of healthy cities; as well as the development of networks of care and mutual support in the face of socio-spatial needs due to pandemic events. The study focuses on theoretical and empirical advances in the processes of epidemiological surveillance in the public space based on collective intelligence mediated with disruptive technologies. The results obtained through a mixed methodological design of the quantitative and qualitative analysis, which includes primary information sources, thanks to the application of citizen surveys and public space control reports of the Municipality of Chone, a prototype model of collaborative and anonymous surveillance software is defined, characterized by 3 functions: a) participatory surveillance assigned to the public space users, b) the assisted surveillance function, and c) the care network. The research suggests the governmental adoption of this cognitive model through a function called "Community COVID-19" added to the existing Cognitive Urban Planning web platform, to train its operability and initiate the recording of incidents in real-time in the territory.