The impact of GeneXpert® MTB/Rif in the detection of tuberculosis and its spatial pattern in Ribeirão Preto-SP

INTRODUCTION: In 2010, the WHO authorized the use of the GeneXpert® MTB/RIF system to perform the Molecular Rapid Test for TB (TRM-TB). The objective was to analyze the impact of GeneXpert® MTB/RIF in the detection of TB and multidrug-resistant TB and its spatial distribution pattern in Ribeirão Preto-SP. METHODS: Ecological study carried out in Ribeirão Preto-SP. The study population consisted of TB cases reported in the Tuberculosis Patient Control System (TBWeb) from 2006 to 2017. Descriptive analysis of cases was performed using descriptive statistics of quantitative parameters through the IBM SPS Statistics software version 25. To classify the temporal trend and observe the impact of the TRM-TB implementation, the Prais-Winsten and Interrupted Time Series (STI) methodologies were used through the StataSE software version 14 and also the ARIMA modeling in order to obtain a prediction of the TB rate for the coming years through RStudio software. To identify the spatial patterns of the disease in the city, the techniques of Kernel density estimator, G and G* and scanning (purely spatial, variation in temporal and spatio-temporal trends) were used. RESULTS: The temporal trend of TB showed a decrease of 18.1%/year and of 6.9%/year for children. The Northern District showed a decrease of 6.67%/year and the East District a growth of 17.5%/year in the incidence of TB. Resistant TB, after the implementation of the TRM-TB, increased by 0.6% per year. In most of the years analyzed, culture is requested for less than half of TB cases. An increase in the number of RMT requests and stationarity in smear microscopy requests was identified. Most cases were diagnosed through outpatient demand. With the spatial analysis used, it was observed that cases and clusters do not form randomly in space, verifying that TB is unevenly distributed in the municipality. CONCLUSION: Although resistant TB is not a problem in the scenario, the study showed an increase in its incidence, which puts it on alert. The use of spatial analysis made it possible to identify priority areas, putting them in evidence for health surveillance actions. We emphasize the importance of using spatial analysis tools to identify areas that should be prioritized for TB control, requiring greater attention to individuals who fit the profile indicated as \"at risk\" for the disease. (AU)