Modelo multicritério de apoio a decisão na seleção de atividades para o controle do Aedes Aegypti: estudo de caso em Natal/RN

Abstract

The recurrent mobilization of the health sector to control Aedes Aegypti is a reflection of the huge risks that the transmitted viruses by this vector have been causing to human health. Although there is a big self promotion from the Brazilian Ministry of Health for the usage of applied researches as strategic investments to the mitigation of complex environments that involve its control, it is still necessary to advance under the coordination of methods and techniques, in order to achieve better sturdiness index and less time response in the application of available activities. Thus, this study aims to develop a multicriteria model for decision support to the selection of Aedes Aegypti control activities, through a case study in the city of Natal / RN. Its construction was carried out in three stages, they are: preliminary; modeling and choice; and finalization, with second one made possible by the Flexible and Interactive Tradeoff (FITradeoff) for ranking problems, selected according to the delimitation of the problem regarding the alignment of the preference structure (P, I), compensatory rationality and the search for effort reducing for the decision maker for picking up partial or inaccurate information in the elicitation process. Furthermore, ten actors were involved to build the model, eight of them were internal and two of them were externs to the zoonoses control center of Natal (CCZ-Natal); observation of four operation scenarios to control the arboviruses, based in trasmission levels; and fianlly, evaluation of eleven alternatives in the perspective of six criterias. As a result, there were obtained the Rankings of the interventions evaluated in each one of the four control operation scenarios in the city, taking in consideration technical criterias guided by the Pan-american Health Organization (OPAS). This process culminated in an organized decision support model that can support decision makers minimizing the effects and risks related to the vector proliferation, based in robust and accurate information given the positive evaluation of the CCZ-Natal manager regarding the sensitivity of the model.