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

Viruses, Journal Year: 2025, Volume and Issue: 17(3), P. 389 - 389

Published: March 9, 2025

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

Language: Английский

survInTime - Exploring surveillance methods and data analysis on Brazilian respiratory syndrome dataset and community mobility changes

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Sept. 27, 2023

Abstract Background The covid-19 pandemic brought negative impacts in almost every country the world. These were observed mainly public health sphere, with a rapid raise and spread of disease failed attempts to restrain it while there was no treatment. However, developing countries, severe other aspects such as intensification social inequality, poverty food insecurity. Specifically Brazil, miscommunication among government layers conducted control measures complete chaos continental dimensions. Brazil made an effort register granular informative data about case reports their outcomes, this is available can be consumed freely, are issues concerning integrity inconsistencies between real number cases notifications dataset. Results We projected implemented four types analysis explore Brazilian dataset Severe Acute Respiratory Syndrome (srag dataset) google community mobility change (mobility dataset). provides some diagnosis integration strategies integrate experimentation surveillance analysis. first type aims at describing exploring contained both datasets, starting by assessing quality missing data, then summarizing patterns found datasets. Second concerns statistical experiment estimate from organized periods time. also developed, third type, algorithm help understanding waves detecting them compare time across cities. Lastly, we build series datasets considering deaths, overall residential regular used features group cities similar behavior. Conclusion exploratory showed under representation many small that absent srag or very low than projections. assessed availability for each state, finding out not all states represented best coverage occurred Rio de Janeiro state. compared capacity place categories combination on estimating measuring errors identifying components could affect cases. In order target specific groups cities, cluster obtained outcomes behavior along time, highlighting divergence handling disease. Availability https://github.com/YasCoMa/dashboard-srag-mobility

Language: Английский