Multivariate spatiotemporal risk of syphilis cases in São Paulo, Brazil (2018–2022)

The number of syphilis-related infections has increased annually worldwide and especially in the Americas, with emphasis on Brazil, although trends may vary according to country and period, with fluctuations occurring at different temporal intervals. The objective of this study was to characterize the cases of acquired (AS), gestational (GS), and congenital (CS) syphilis and to identify the multiple spatial and spatiotemporal clusters of these diseases, considering the period from 2018 to 2022, in order to analyze changes in the epidemiological pattern of syphilis during this timeframe. This exploratory multiple-group ecological study groups patterns of syphilis in the 645 municipalities of the Brazilian state of São Paulo, Brazil. The study population consisted of all reported cases of acquired (AS), gestational (GS), and congenital (CS) syphilis among residents of these municipalities during the study period. The analyses included the calculation of standardized rates (AS), detection rates (GS), and incidence rates (CS) using population estimates as denominators, as well as descriptive and spatial statistical analyses. Spatial and spatiotemporal clusters multiple, bivariate, and univariate were identified using scan statistics. All analyses were performed using open-access software, including SaTScan™ and QGIS™. 199,270 cases of AS, 72,132 of GS, and 20,059 of CS were reported. There was significant growth in 2022. In the purely spatial analysis, 19 high-risk clusters were identified. Of which seven were multivariate (AS, GS, and CS), six bivariate (AS and GS; GS and CS; AS and CS), and another six univariate (AS and CS), all distributed among 35 municipalities. The temporal analysis identified a multiple cluster for 2022. The spatiotemporal scan identified a multiple high-risk cluster, also in 2022, involving the municipalities of Diadema, São Caetano do Sul, São Paulo, and Taboão da Serra, coinciding with the cluster identified in the purely spatial analysis. The employed analysis proved to be a powerful tool to identify multiple, bi-, and univariate occurrences of AS, GS, and CS, indicating the municipalities with a significant occurrence of syphilis in the different population subgroups. Health managers should consider the extreme need in these locations for interventions related to the theme.