Analysing the spatio-temporal pattern of dengue cases and deaths at different geographic scales, considering climate change and under greenhouse gas emission scenarios

• Grant number: 21/11721-7
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: July 18, 2022
• End date: July 17, 2023
• Field of knowledge: Health Sciences - Collective Health - Public Health
• Principal Investigator: Francisco Chiaravalloti Neto
• Grantee: Patricia Marques Moralejo Bermudi
• Supervisor: Monica Pirani
• Host Institution: Faculdade de Saúde Pública (FSP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Institution abroad: Imperial College London, England
• Associated to the scholarship: 20/12371-7 - Spatio-temporal patterns of Dengue cases and deaths, associated factors and identification of risk areas at two geographical scales: municipalities in Brazil and intra-urban areas of Campinas, State of São Paulo, BP.DR

Abstract

Dengue is considered a neglected disease and an important public health problem, being one of the leading causes of death and hospitalization among arboviruses, affecting several countries in the world, including Brazil. In the country, the current scenario is considered hyperendemic for the disease, with an increase in the occurrence of fatal cases and with the co-circulation of the four viral serotypes. On a smaller scale, the city of Campinas - SP is considered to have the second highest number of cases in the state of São Paulo. The increase in the disease has been associated with climatic conditions, as these affect the epidemiological triad (environment, host and agent). Therefore, future global perspectives for worsening of these conditions may negatively accentuate the current scenario, justifying the importance of analyzing the incidence and mortality, based on different greenhouse gas emission scenarios.Another point worth highlighting is that there are reports of disconnection of national dengue control actions, which provides a lack of prioritization of risk areas. Therefore, studying the spatiotemporal patterns of disease incidence and mortality and seeking explanations for its interactions with environmental and socioeconomic factors it is of paramount importance, and may collaborate with the prioritization of resources, surveillance and disease control.Consequently, the goals of the study are to map in space and time the distribution of dengue, to investigate the effect of risk factors on the disease incidence and mortality, considering climate change, environmental and socioeconomic variables, and to predict these indicators, depending on different greenhouse gas emission scenarios in two geographical scales.For this, the study design will be ecological, with a period from 2000 to 2019 and using secondary data, for the municipalities of Brazil and for the intra-urban area of the municipality of Campinas - SP. Looking at two geographic scales can provide interesting information, with different specificities, to aid better understand the full context and at the respective levels of analysis, considering that as the geographical scale changes, the phenomenon usually presents itself in different ways.The spatio-temporal mapping of dengue incidence and mortality will be performed using hierarchical Bayesian models, taking into account the spatial and temporal autocorrelation, in different age structures and gender distribution, for the different geographic scales considered. In these models, they will be chosen between Poisson or negative binominal probability distributions, inflated or not inflated from zero, according to the disposition of the data. In addition, these models will be performed in a latent Guasian Bayesian context, using the Integrated Nested Laplace Approximation (INLA), through the R software. With the same parameters, Bayesian models will be performed to verify the relative risks of incidences and mortality by dengue, for each associated factor, considering socioeconomic and environmental variables. Finally, different different greenhouse gas emission scenarios will be considered to make predictions of dengue incidence and mortality. With the results of this project, it is expected to provide evidence to identify populations most vulnerable to dengue incidence and mortality, to bring insigths on the possible associated factors and mechanisms that act on macro and micro scale, and to predict the incidence and mortality of the disease, based on different greenhouse gas emission scenarios. (AU)