Maternal Tuberculosis Detection During COVID-19 in Brazil

Giuliana Facco Machado

Faceres, Brazil

Title: Maternal Tuberculosis Detection During the COVID-19 Pandemic in Brazil: Evidence of Surveillance Resilience Within a Universal Health System (2020–2024)

Abstract

Tuberculosis (TB) during pregnancy results in significant maternal morbidity and adverse perinatal outcomes. These effects are pronounced in high-burden countries such as Brazil. The COVID-19 pandemic disrupted prenatal care and infectious disease surveillance. This raised concerns regarding maternal health. This context offered an opportunity to evaluate whether a universal maternal health system could maintain TB detection in pregnancy amid systemic stress.

Building on this context, a nationwide, population-based, retrospective study was conducted using surveillance data from Brazil’s Notifiable Diseases Information System (SINAN), accessed via the Ministry of Health's database (DATASUS). All confirmed TB cases among women aged 10–49 years reported between 2020 and 2024 were included, with pregnancy status identified from notification records. The primary outcome was the annual proportion of TB cases diagnosed during pregnancy.

To investigate trends in TB detection during pregnancy, temporal variation was assessed using logistic regression, with pregnancy status (yes/no) as the dependent variable. The calendar year was first analysed as a continuous predictor and subsequently as a categorical variable, with 2020 as the reference. Odds ratios (OR) with 95% confidence intervals (CI) were estimated. Model fit was evaluated using deviance statistics and the Akaike Information Criterion (AIC). Analyses were performed in R (R Foundation for Statistical Computing, Vienna, Austria). Statistical significance was set at p < 0.05.

From 2020 to 2024, 143,655 confirmed TB cases among women were recorded nationwide. Notably, the proportion of cases occurring during pregnancy declined slightly between 2020 and 2021, but the change was not statistically significant (1.82% to 1.63%; OR 0.89; 95% CI 0.78–1.02). Detection rates remained stable from 2022 to 2024 (2022: OR 0.92; 95% CI 0.81–1.04; 2023: OR 0.97; 95% CI 0.86–1.10; 2024: OR 0.97; 95% CI

0.86–1.10), and no significant linear trend was observed. These results suggest that Brazil's maternal TB surveillance was largely maintained even under pandemic pressure, likely due to robust integration into the Sistema Único de Saúde (SUS).

This evidence indicates that integrated prenatal surveillance systems can mitigate the negative effects of global crises on the detection of maternal infectious diseases. For public health, this underscores the necessity of investing in and maintaining robust surveillance infrastructures within prenatal care, particularly in high-burden settings. In obstetric populations, sustained surveillance functions not only as an epidemiological indicator but also as a critical structural safeguard that helps ensure timely diagnosis and intervention, thereby supporting improved maternal and perinatal health outcomes. These findings highlight the broader public health implication that resilient health systems are essential for maintaining maternal health services during periods of systemic stress.

What will the audience take away from presentation?

Understand the impact of health coverage on continuous maternal infectious disease surveillance during crises.

Utilize national surveillance data to assess the resilience of maternal health systems within individual countries.
Analyze variations in disease trends in the broader context of global health.
Evaluate the effects of underreporting and access barriers on maternal health data during crises.
Incorporate surveillance data into policy dialogues aimed at safeguarding maternal health in vulnerable populations.

How will this help the audience in their job? Is this research that other faculty could use to expand their research or teaching? Does this provide a practical solution to a problem that could simplify or make a designer’s job more efficient? Will it improve the accuracy of a design, or provide new information to assist in a design problem? List all other benefits.

This research presents a straightforward model for evaluating maternal infectious disease surveillance during emergencies. It further facilitates discussions on strategies for health systems to protect pregnant individuals under stress. The Brazilian case study provides guidance for planning in other middle-income countries with high disease burdens.

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Title: Maternal Tuberculosis Detection During the COVID-19 Pandemic in Brazil: Evidence of Surveillance Resilience Within a Universal Health System (2020–2024)

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