Diagnosis of pulmonary tuberculosis in the state of São Paulo: temporal trend of indicators in the context of the covid-19 pandemic

• Grant number: 23/06383-0
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Effective date (Start): November 01, 2023
• Effective date (End): October 31, 2025
• Field of knowledge: Health Sciences - Nursing - Public Health Nursing
• Principal Investigator: Ione Carvalho Pinto
• Grantee: Mariana Gaspar Botelho Funari de Faria
• Host Institution: Escola de Enfermagem de Ribeirão Preto (EERP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
• Associated scholarship(s): 24/10681-0 - Diagnosis of pulmonary tuberculosis in the state of São Paulo: temporal trend of indicators in the context of the Covid-19 pandemic, BE.EP.PD

Abstract

Tuberculosis is a crucial social issue since about 4,500 people died in 2020 in Brazil. Since 2003, TB has been among the priorities of the Brazilian government. However, despite progress toward ending TB, prevention, diagnosis and treatment remain challenging. With the emergence of covid-19, such a devastating health scenario weakened the performance of national TB control programs, with abrupt effects on the diagnosis of the disease, whose efforts were directed towards policies to combat the pandemic. In this context, the present study aims to analyze the trend of indicators of access to the diagnosis of pulmonary tuberculosis before, during and after the covid-19 pandemic in São Paulo state. It is an ecological time series study whose study population will be composed of new cases of tuberculosis reported between 2014 and 2023 in the state. Sociodemographic, clinical, diagnostic, and outcome variables will be collected from TB WEB and SITE-TB. After collection, monthly performance indicators for the state of São Paulo in the diagnosis of tuberculosis will be calculated during the study period. In order to track the performance of the indicators over a period, the time series will be decomposed by the Loess method (Seasonal Decomposition of Time Series by Loess - STL), and later, the trend will be analyzed by the interrupted time series in order to assess whether the covid pandemic -19 caused an immediate impact (change in level) and/or progressive impact (change in trend) in the series values, with the proposition of regression/correlation between the variables.