Evidence map›Paper›PMID 42662657›Full record

ArticleCureus2026

Distribution Patterns of Non-SARS-CoV-2 Respiratory Pathogens Among Patients With Influenza-Like Illness During the COVID-19 Pandemic: A Cross-Sectional Study From Bangladesh.

Sharmin Sultana, Abu Taher, Nirvana Haque, S M Rashed Ul Islam, Md Nazrul Islam, Afzalun Nessa

Abstract read
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Sharmin SultanaVirology, Bangladesh Medical University, Dhaka, BGD.
Abu TaherAnesthesia, Analgesia and Intensive Care Medicine, Bangladesh Medical University, Dhaka, BGD.
Nirvana HaqueData Science and Business, York University, Toronto, CAN.
S M Rashed Ul IslamVirology, Bangladesh Medical University, Dhaka, BGD.
Md Nazrul IslamVirology, Bangladesh Medical University, Dhaka, BGD.
Afzalun NessaVirology, Bangladesh Medical University, Dhaka, BGD.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDuring the COVID-19 pandemic, diagnostic efforts were heavily concentrated on SARS-CoV-2, leaving patients who tested negative with limited etiological workup despite continuing to present with influenza-like illness. This study aimed to identify and characterize the non-SARS-CoV-2 respiratory pathogens responsible for illness in this group at a tertiary care hospital in Bangladesh.

methodsWe conducted a descriptive cross-sectional study at the Department of Virology, Bangladesh Medical University (BMU), from July to December 2022, enrolling 165 adults with influenza-like symptoms who tested negative for SARS-CoV-2. Nasopharyngeal swabs were analyzed by multiplex real-time PCR (VIASURE Respiratory Panel III kit, CerTest Biotec, Zaragoza, Spain). Pathogen distribution was assessed using Chi-squared goodness-of-fit (GoF) as a global test, confirmed by exact Monte Carlo multinomial simulation (100,000 runs). Individual pathogens were compared using binomial exact tests with Benjamini-Hochberg (BH)-false discovery rate (FDR) correction. Co-infection independence was assessed with one-sided Fisher's exact tests plus BH-FDR correction; effect sizes are reported as odds ratios (ORs) with 95% confidence intervals (CIs).

resultsOf 165 participants (mean age 34.8 ± 12.7 years; 61.8% male), 59 (35.8%; 95% CI: 28.8%-43.3%) had at least one pathogen, yielding 46 viral and 29 bacterial pathogen detections. Both distributions deviated significantly from uniformity (viral: χ²(6) = 48.35, p < 0.001; bacterial: χ²(2) = 20.14, p < 0.001). Human rhinovirus was the most statistically significant viral pathogen (21/46; 45.7%; BH-adjusted p < 0.001; z = +6.08), and

conclusionNon-SARS-CoV-2 respiratory pathogens like human rhinovirus and

Indexed as

bangladeshco-infectionmultiplex pcrpandemicrespiratory tract infectionsrhinovirussars-cov-2streptococcus pneumoniae

Identifiers

PMID42662657
PMCPMC13521323

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.