The Impact of the COVID-19 Pandemic on the Clinical and Epidemiological Profile of Severe Acute Respiratory Infection in Bahia, Brazil: A Comparative Analysis of Pre- and Post-Pandemic Trends

Abstract

In recent years, the incidence of Severe Acute Respiratory Infection (SARI) has increased due to the emergence of SARS-CoV-2. However, the impact of the COVID-19 pandemic extends beyond mortality rates. Recent analyses suggest that the introduction and spread of SARS-CoV-2 have significantly affected the epidemiology of other key respiratory viruses, such as influenza virus (FLUV), respiratory syncytial virus (RSV), and rhinovirus (RV). These changes raise new questions about the dynamics and incidence of post-COVID-19 respiratory infections, as well as potential alterations in symptom profiles and clinical outcomes. In this study, we analyzed data from the Epidemiological Surveillance Information System of Respiratory Viral Agents (SIVEP-Gripe), established by the Brazilian Ministry of Health, to examine the profile of SARI before and during the COVID-19 pandemic in Brazil. Our data reveal a distinct epidemiological pattern, with a significant decrease in FLUV notifications during the pandemic, accompanied by peaks in RSV and RV cases in late 2020. Additionally, there was a shift in the age distribution of RSV and other viral infections, with individuals infected during the pandemic being older than those infected before the pandemic. Interestingly, the introduction and spread of SARS-CoV-2 in Bahia State resulted in a reduction in the frequency of symptoms associated with non-SARS-CoV-2 SARI, without altering clinical outcomes. Our findings suggest that the circulation of SARS-CoV-2 has contributed to a clinical and epidemiological shift, particularly for FLUV, RSV, and other viruses, marked by a reduction in symptoms such as fever, dyspnea, respiratory distress, and the need for ventilatory support. The underlying mechanisms driving these changes remain unclear. These insights are crucial for public health authorities and policymakers to refine surveillance strategies and enhance control measures for respiratory viruses, particularly those causing SARI.

Keywords: SARI; SARS-CoV-2; influenza virus; respiratory syncytial virus; seasonality; symptoms.

Figure 1

SARI notifications in Bahia State. Monthly notifications of SARI cases in Bahia State, Brazil, from January 2019 to December 2020, with confirmation by PCR. (A) All notification for SARI in Bahia state during January 2019 and December 2020, including those positive (viral detection, black line) and negative (no viral detection, gray line). (B) SARI notification by viruses during January 2019 and December 2020: human metapneumovirus (yellow), parainfluenza 1 (light green), parainfluenza 2 (orange), parainfluenza 3 (green), influenza A (green forest), influeza B (dark red), respiratory adenovirus (violet), respiratory syncytial virus (blue), rhinovirus (red), SARS-CoV-2 (pink).

Figure 2

Age distribution of individuals with SARI caused by different respiratory viruses. (A) Age distribution of total SARI cases caused by respiratory viruses in 2019 and 2020. (B) Age distribution of total SARI cases stratified by specific viruses. (C) Age distribution of total SARI cases caused by influenza virus (FLUV). (D) Age distribution of total SARI cases caused by respiratory syncytial virus (RSV). (E) Age distribution of total SARI cases caused by other respiratory viruses (OV). The following statistical analyses were performed: Two-tailed Mann–Whitney U test (A,C–E) and Kruskal–Wallis test followed by Dunn’s multiple comparison test (B).

Figure 3

Population pyramid frequency of individuals with SARI caused by different respiratory viruses. Population pyramid frequency for influenza virus (FLUV) (A), respiratory syncytial virus (RSV) (B), other respiratory viruses (OVs) (C), and SARS-CoV-2 (D), with respective overlapping curves (on the right). (E) Overlapping curves for total SARI cases caused by respiratory viruses.

Figure 4

Differences in symptoms and other clinical characteristics of SARI by year reported in Bahia State, Brazil, during 2019–2020. Frequency of symptoms in individuals diagnosed with SARI according to infection caused by FLUV (A), RSV (B), and OVs (C). Frequency of other clinical characteristics (outcomes, comorbidities, and use of ventilatory support) in individuals diagnosed with SARI according to infection caused by FLUVs (D), RSV (E), and OVs (F). Asterisk (*) indicates statistical significance with p < 0.05 between 2019 x 2020.

Figure 5

Prevalence of symptoms and other clinical characteristics of SARI by year reported in Bahia State, Brazil, during 2019–2020. Prevalence of symptoms (A) and other clinical characteristics (outcomes, comorbidities, and use of ventilatory support) (B) in cases with confirmed laboratory results for FLUV (blue), OV (green), RSV (yellow), and SARS-CoV-2 (orange).