ABSTRACT
BACKGROUND AND AIM: Dengue is a viral febrile infectious disease characterized by mild symptoms that can progress to dengue hemorrhagic fever (DHF). Due to socioeconomic and environmental reasons, it is a significant public health problem in Brazil with high morbidity rates among children. The objective is to analyze the epidemiological behavior of dengue and DHF hospitalizations in Brazil and point out the importance of health surveillance. METHOD(S): Data were collected from the Sistema de Informacoes Hospitalares of the Brazilian Ministry of Health. The study population was children from zero to 14 years old diagnosed with classic dengue and/or DHF from January 2008 to November 2021 in Brazil. The variables analyzed were hospitalizations and deaths over the years, hospitalization time and expenses. RESULT(S): A total of 192,424 hospitalizations for dengue and DHF were reported, of which 95.3% were considered medical emergencies. Its epidemiological behavior has fluctuated over the years, with an increase of 162.0% between 2017 and 2019, followed by a decreasing trend starting in 2020. Despite the low mortality rate (0.24%), this scenario was responsible for $12,347,942.38 in expenses and a total of 652,552 hospitalization days. CONCLUSION(S): Dengue is responsible for a major socioeconomic impact on Brazilian's public health system since its severe cases require intensive care to avoid shock, organ failure and death. Due to COVID-19 pandemic and population's fear of contamination in medical facilities, underreporting of arboviruses cases was observed. Since early diagnosis and monitoring are predictors of good prognosis, it is crucial to encourage notification, epidemiological surveillance and sanitary hygiene measures.
ABSTRACT
Paper aims: The aim is to develop a vaccine distribution routing model (VDRM) in order to support governments to mitigate the pandemic caused by COVID-19. Originality: As far as we know, no metaheuristics has been developed for vaccine distribution, and specifically, to support the Brazilian government. Research method: A metaheuristic is developed based on the combination and adaptation of GRASP (Greedy Randomized Adaptive Search Procedure) with VND (Variable Neighborhood Descent), considering different refinement operators. Finally, as a way of validating the model, a numerical application in the state of Pernambuco (Brazil) was performed. Main findings: Metaheuristic proved to be effective for developing adequate planning for the allocation of ampoules with vaccines to combat COVID-19. Effective analysis was obtained in the evaluation of the proposed algorithm, both in terms of computational effort and the quality of the final solution. An efficiency of approximately 75% was obtained in relation to the current distribution procedure adopted by the state of Pernambuco. Implications for theory and practice: To mitigate disease, adequate logistics for transporting and distributing vaccines is essential, especially in emergency situations to face pandemic crises. Thus, the developed metaheuristic can support governments and companies in any situation demanded, making the decision of how the distribution of the ampoules will be more agile. © 2021. All Rights Reserved.