Cognitive surveillance in public spaces for epidemiological control in Ecuador

Abstract

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.