DAELF - novo método para detecção de aglomerados espaciais baseado em lógica Fuzzy para estudos epidemiológicos

Abstract

In the field of epidemiology, methods are needed that can detect spatial clusters in certain geographic areas while also addressing the spatial context, since this information is vital for understanding the event and for the decision-making process.

Spatial clustering methods associated with the uncertainties present in the health- disease process produce more reliable results than those used traditionally. The

objective of the study was to develop a new spatial clustering method using the theory of Fuzzy logic applied to epidemiology. This is an ecological, retrospective study with a quantitative approach. To construct and validate the new method, data on dengue from 2018 to 2023 and Covid-19 from 2020 to 2021 in the state of Paraíba were used. The new method was compared with the reference map of the Spatial Incidence Ratio and with other spatial clustering methods, demonstrating its functionality through a system based on Fuzzy rules. The new method presented competitive results, since it detected spatial clusters of high values in several areas of the state of Paraíba, taking into account the reference map of the Spatial Incidence Ratio. It is also worth noting that the new method can support decision-making by health managers, making the planning of strategies and combat actions more effective.