THE EFFECTS OF THE COVID-19 PANDEMIC ON TUBERCULOSIS MORTALITY IN THE STATE OF SANTA CATARINA
João Pedro dos Santos Cury Schmid, Eleonora d’Orsi, Giovana De Marchi Castelli, Samuel Tomaz da Silva, Enzo Gonçalves Nascimento, Italo Pereira Barreto, Davi Augusto Rank, Luis Filipe De Assis Freitas Caixeta, et al. (9 authors)
The Brazilian Journal of Infectious Diseases · 2026-03
Abstract
Tuberculosis (TB) is an infectious disease that mainly affects the lungs and requires continuous attention from the health system. In 2023, Brazil recorded more than 6,000 TB deaths, surpassing this mark for the first time in 26 years, in a context of increasing incidence rates. This scenario is attributed to service disorganization during the COVID-19 pandemic, reduced BCG vaccination coverage, and declining cure rates among confirmed cases. Therefore, this study aims to compare TB mortality in Santa Catarina (SC) in the pre- and post-pandemic periods. Retrospective, quantitative epidemiological study. Data on TB cases and deaths were obtained from the Diretoria de Vigilância Epidemiológica de SC, and population data from the Instituto Brasileiro de Geografia e Estatística (IBGE). The biennia 2018–2019 (pre-pandemic) and 2023–2024 (post-pandemic) were analyzed. Annual mortality rates per 100,000 inhabitants were calculated and the proportion of deaths relative to cases was analyzed using the chi-square test, with Jamovi software. TB mortality rate increased by 72% between the analyzed periods, from 1.04 to 1.79 deaths per 100,000 inhabitants. A progressive increase in this rate over the years was also observed. The proportion of deaths relative to the number of cases increased from 2.83% to 3.83%, with statistical significance (p=0.003). There was a marked increase in TB mortality in SC in the post-pandemic period, both in absolute and proportional numbers. These findings reinforce the need to strengthen TB control strategies, focusing on integrated actions for diagnosis, treatment, and prevention. A limitation of the study is the use of aggregated secondary data without socioeconomic stratification or control of possible confounding factors.
MeSH terms
- Pandemic
- Medicine
- Tuberculosis
- Environmental health
- State (computer science)
- Population
- Geography
- Mortality rate