Dengue fever is a febrile vector borne disease and affects million people every year. It is caused by a Flavivirus and is considered a major public health problem. The increase in magnitude of dengue is strongly associated with continuous circulation of the four serotypes, which cause unpredictable epidemics. The current tools to combat virus circulation and vector infestation have not contributed to contain dengue spread and tools for dengue control and prevention are urgently needed. Disease incidence maps have always played a key role in epidemiological studies mainly to help public health managers to understand disease distribution and to establish control measures. Araraquara has been presenting an increase in dengue case report and the first dengue outbreak occurred in 2008, with an incidence of 639 cases per 100,000 inhabitants. From that year on, dengue cases have been occurring all year long. The highest incidences usually occur from March to May, usually right after a period of intense rainfall. Recent and unpublished analyses suggested spatial patterns that can help to prioritize areas to establish differential control measures. The gross incidence rates of dengue from 2008 to 2015 will be calculated for each census tract in the urban area using a single category of dengue incidence for each year. This aggregation technique preserves the phenomenon that is being studied in the best possible way since it preserves several important data from the census and the assessment of indicators. Further analysis is required to evaluate census tracts with different incidence rates and their importance in disease spread. However these incidences often suffer fluctuations with different and null values and a Bayesian model must be employed to reduce these fluctuations. This correction may provide a comprehensive spatial regression analysis that will help predict dengue occurrence in the city. The spatial regression model will be performed to investigate factors associated with dengue incidences according to census tracts, which also considers the existence of spatial dependence among the analyzed areas. The socioeconomic and demographic variables to be tested are based on Paulista Social Vulnerability Index (IPVS), which is calculated from Brazilian Institute of Geography and Statistics demographic census.
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