Cognitive surveillance in public spaces for epidemiological control in Ecuador

The COVID-19 pandemic has underscored the limitations of public health infrastructure and leadership in epidemiological containment and prevention in Ecuadorian cities. Given this problem, this study emphasizes the necessity of generating localized data to inform public decision-making, leveraging socio-technological innovations to support spatial planning processes. This article presents the design and implementation of a model aimed at risk prevention of epidemiological contagion in public spaces and social congregation areas. The model enables real-time identification of behavioral patterns associated with contagion risks, facilitates the urban spaces redesign to promote health, and supports care networks to address socio-spatial needs arising from pandemic scenarios. The research integrates theoretical and empirical advancements in epidemiological surveillance, utilizing collective intelligence mediated by disruptive technologies. We employ a mixed methods approach that combines quantitative and qualitative analyses, integrating primary data from citizen surveys and public space surveillance reports provided by the Municipality of Chone. The findings led to the development of a collaborative and anonymous surveillance software prototype featuring three core functionalities: (a) participatory surveillance by public space users, (b) assisted surveillance mechanisms, and (c) care network integration. The study advocates for governmental adoption of this cognitive model by integrating a “COVID-19 Community” function into the existing Cognitive Urban Planning web platform. This addition would enable operational training and the systematic recording of epidemiological incidents, supporting urban resilience and public health management in intermediate cities.