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Simultaneous spatial circulation of urban arboviral diseases, such as dengue, chikungunya, and Zika, is a major challenge. In this ecological study of urban arboviruses performed from 2015 to 2019, we analyzed the spatial and temporal dynamics of these arboviruses in all 92 municipalities and nine health regions of Rio de Janeiro state. Annual cumulative incidences are presented for all three arboviruses throughout the study period. Spatial analyses of the three studied arboviruses showed distinct behaviors among municipalities and health regions. Co-circulation of the three arboviruses in the state and a heterogeneous spatiotemporal pattern was observed for each disease and region, with dengue having a higher annual incidence during the five years of the study, as well as two consecutive epidemic years in the state. The increase in transmission in different regions of the state in one year culminated in an epidemic in the state in the following year. A high annual cumulative incidence of chikungunya occurred in municipalities from 2017 to 2019 and of Zika only in 2016. Some municipalities with higher population densities showed higher incidences for some arboviruses and appeared to contribute to the dissemination to cities of lower demographic density and maintenance of these urban arboviruses. Thus, regions recording increased incidences of the three diseases in their territories for long periods should be considered municipal poles, as they initiated and sustained high transmission within their region.

This work analyses the performance of the Brazilian spotted fever (SF) surveillance system in diagnosing and confirming suspected cases in the state of Rio de Janeiro (RJ), from 2007 to 2016 (July) using machine-learning techniques. Of the 890 cases reported to the Disease Notification Information System (SINAN), 11.7% were confirmed as SF, 2.9% as dengue, 1.6% as leptospirosis, and 0.7% as tick bite allergy, with the remainder being diagnosed as other categories (10.5%) or unspecified (72.7%). This study confirms the existence of obstacles in the diagnostic classification of suspected cases of SF by clinical signs and symptoms. Unlike man–capybara contact (1.7% of cases), man–tick contact (71.2%) represents an important risk indicator for SF. The analysis of decision trees highlights some clinical symptoms related to SF patient death or cure, such as: respiratory distress, convulsion, shock, petechiae, coma, icterus, and diarrhea. Moreover, cartographic techniques document patient transit between RJ and bordering states and within RJ itself. This work recommends some changes to SINAN that would provide a greater understanding of the dynamics of SF and serve as a model for other endemic areas in Brazil.