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Published on: February 23, 2014
Shifting respiratory pathogens: Post-COVID-19 trends in community-acquired infections in underserved communities
Rayane Rafei1, Marwan Osman2, Bashir Amer Barake3
1Laboratoire Microbiologie Santé et Environnement (LMSE), Doctoral School for Science and Technology, Faculty of Public Health, Lebanese University, Tripoli, Lebanon.
Abstract:
Respiratory tract infections, caused by various bacteria and viruses, pose a significant global health burden. In Lebanon, post-COVID-19 epidemiological data on respiratory infections remain scarce. To address this gap, this multicenter study investigates the epidemiology of community-acquired acute respiratory infections among children and adults in Tripoli, North Lebanon. From May 2023 to February 2024, nasopharyngeal samples were collected from outpatients with acute respiratory infections visiting hospitals and pediatric clinics in Tripoli. Samples were analyzed using BioFire® Respiratory Panel 2.1 Plus (bioMérieux, France), which targets 23 pathogens, including 19 viruses and four bacteria. We used multivariable logistic regression models to identify the determinants of respiratory infections and examine associations between respiratory pathogens. Among 324 enrolled patients, 69.1% were co-infected with at least one pathogen. Human rhinovirus/enterovirus was the most prevalent (27.2%), followed by influenza A (19.8%), particularly influenza A/H1-2009 (16.4%), and RSV (11.4%). SARS-CoV-2 was still circulating with a prevalence of 6.8%. Classical human coronaviruses accounted for 6.1% of infections, with HCoV-NL63 (2.8%) being the most common. Parainfluenza viruses were identified in 5.2% of patients, with type 4 (2.5%) being the most prevalent, followed by type 3 (1.5%), type 1 (1.2%), and type 2 (0.3%). Logistic regression analysis revealed that human rhinovirus/enterovirus infection decreased the likelihood of influenza A (OR=0.25; 95%CI = 0.10-0.54; P = 0.001) or SARS-CoV-2 (OR=0.21; 95%CI = 0.03-0.75; P = 0.039) co-infection. Additionally, our logistic regression models identified significant associations between various determinants, symptoms, and common viruses, including a lower likelihood of influenza A (OR=0.23; 95%CI = 0.06-0.76; P = 0.019) and RSV (OR=0.29; 95%CI = 0.10-0.76; P = 0.017) infection among patients with higher educational levels. Notably, parainfluenza virus infections occurred significantly more in refugee patients (OR=7.22; 95%CI = 1.19-37.0; P = 0.020) compared to the host community. In conclusion, this study provides critical insights into the post-pandemic epidemiology of respiratory infections in Lebanon, informing clinicians, health authorities, and policymakers to optimize diagnostics, preventive measures, and antimicrobial stewardship strategies.
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