Tuberculosis and the SARS-CoV-2 pandemic: A time series study of vulnerable populations in the state of São Paulo

• Grant number: 24/20603-6
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: February 01, 2025
• End date: December 31, 2025
• Field of knowledge: Health Sciences - Nursing - Public Health Nursing
• Principal Investigator: Ricardo Alexandre Arcêncio
• Grantee: Daniele de Moraes Pinheiro
• Host Institution: Escola de Enfermagem de Ribeirão Preto (EERP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
• Associated research grant: 22/08510-7 - Interaction and effect of the COVID-19 pandemic on Tuberculosis control in the State of São Paulo: political-social, clinical-epidemiological aspects and innovative practices, AP.TEM

Abstract

Introduction: Tuberculosis (TB), although preventable and curable, remains a serious global public health problem. Before the emergence of COVID-19, TB was the leading cause of death from a single infectious agent worldwide. With the advent of the pandemic, challenges in combating TB have intensified, especially among the most vulnerable populations, such as people experiencing homelessness, individuals deprived of liberty, migrants, people living with HIV/AIDS, and Indigenous populations. This scenario highlighted the need to develop new strategies to mitigate TB's impacts, as well as to assess the impact of COVID-19 on TB control, focusing on vulnerable populations. Objective: To examine the temporal trends in TB cases and deaths in the state of São Paulo among vulnerable populations and changes in these trends during the COVID-19 pandemic period. Materials and Methods: This is an ecological, time-series study conducted in the state of São Paulo. The study population will include all TB cases and deaths reported in the Notifiable Diseases Information System (SINAN) from 2015 to 2023. Descriptive analyses of the cases will be performed using descriptive statistics to characterize the profile of TB cases. In the second stage, time-series analysis will be conducted, including the calculation of incidence and mortality rates, seasonal-trend decomposition of time series by Loess (Seasonal-Trend Decomposition of Time Series by Loess), and detection of structural changes in the time series following the COVID-19 pandemic using the breakpoint method.