Viral co‐infection with human respiratory syncytial virus in suspected acute and severe respiratory tract infections during COVID‐19 pandemic in Yaoundé, Cameroon, 2020–2021

Yifomnjou, Moise Henri Moumbeket; Monamele, Gwladys Chavely; Njankouo‐Ripa, Mohamadou; Modiyinji, Abdou Fatawou; Ngoupo, Paul Alain; Boyomo, Onana; Njouom, Richard

doi:10.1111/irv.13131

Cited by 6 publications

(5 citation statements)

References 61 publications

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“…Many studies conducted during the COVID-19 pandemic reported possible coinfections of SARS-CoV-2 with other respiratory pathogens, including bacteria, fungi, and viruses [ 12 , 34 , 35 ]. In our three-year follow-up study, a rate of 7.2% of coinfections was detected, which is consistent with other reports [ 4 , 36 , 37 ]. Seven types of seasonal respiratory viruses were identified in mixed infections with SARS-CoV-2, among which RSV was the most common co-pathogen.…”

Section: Discussionsupporting

confidence: 93%

Epidemiological and Genetic Characteristics of Respiratory Viral Coinfections with Different Variants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)

Trifonova,

Korsun,

Madzharova

et al. 2024

Viruses

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This study aimed to determine the incidence and etiological, seasonal, and genetic characteristics of respiratory viral coinfections involving severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Between October 2020 and January 2024, nasopharyngeal samples were collected from 2277 SARS-CoV-2-positive patients. Two multiplex approaches were used to detect and sequence SARS-CoV-2, influenza A/B viruses, and other seasonal respiratory viruses: multiplex real-time polymerase chain reaction (PCR) and multiplex next-generation sequencing. Coinfections of SARS-CoV-2 with other respiratory viruses were detected in 164 (7.2%) patients. The most common co-infecting virus was respiratory syncytial virus (RSV) (38 cases, 1.7%), followed by bocavirus (BoV) (1.2%) and rhinovirus (RV) (1.1%). Patients ≤ 16 years of age had the highest rate (15%) of mixed infections. Whole-genome sequencing produced 19 complete genomes of seasonal respiratory viral co-pathogens, which were subjected to phylogenetic and amino acid analyses. The detected influenza viruses were classified into the genetic groups 6B.1A.5a.2a and 6B.1A.5a.2a.1 for A(H1N1)pdm09, 3C.2a1b.2a.2a.1 and 3C.2a.2b for A(H3N2), and V1A.3a.2 for the B/Victoria lineage. The RSV-B sequences belonged to the genetic group GB5.0.5a, with HAdV-C belonging to type 1, BoV to genotype VP1, and PIV3 to lineage 1a(i). Multiple amino acid substitutions were identified, including at the antibody-binding sites. This study provides insights into respiratory viral coinfections involving SARS-CoV-2 and reinforces the importance of genetic characterization of co-pathogens in the development of therapeutic and preventive strategies.

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Section: Discussionsupporting

confidence: 93%

Epidemiological and Genetic Characteristics of Respiratory Viral Coinfections with Different Variants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)

Trifonova,

Korsun,

Madzharova

et al. 2024

Viruses

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“…This manuscript compares influenza data before and during the COVID-19 pandemic and describes SARS-CoV-2 data during the period of co-circulation of both respiratory viruses in Cameroon. (12.6% vs. 12.8%) during the pandemic period [11]. The reason for the higher SARS-CoV-2 detection rate in the latter study is due to the mixed target population, which consisted of persons captured by the influenza sentinel surveillance and from facilities testing suspected cases of COVID-19.…”

Section: Discussionmentioning

confidence: 69%

“…A recent study by Moumbeket et al. in Cameroon found almost equal circulation of influenza virus and SARS‐CoV‐2 (12.6% vs. 12.8%) during the pandemic period [11]. The reason for the higher SARS‐CoV‐2 detection rate in the latter study is due to the mixed target population, which consisted of persons captured by the influenza sentinel surveillance and from facilities testing suspected cases of COVID‐19.…”

Section: Discussionmentioning

confidence: 79%

“…During the COVID-19 pandemic, SARS-CoV-2 diagnosis was performed using the DaAn Gene protocol (Daan Gene Co., Ltd., of Sun Yat-sen University, China; EUL 0493-141-00), which targets the open reading frame (ORF) 1ab and nucleocapsid (N) genes, or the Abbott RealTime SARS-CoV-2 Assay (Abbott Molecular Inc., USA, EUL-0503-027-00), which targets the RNA-dependent RNA polymerase (RdRp) and N genes [11].…”

Section: Detection Of Sars-cov-2 Virusesmentioning

confidence: 99%

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The Detection of Influenza Virus Before and During the COVID‐19 Pandemic in Cameroon

Monamele,

Tsafack,

Bilounga

et al. 2024

Influenza Resp Viruses

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BackgroundInfluenza and severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) are both respiratory viruses with similar clinical manifestations and modes of transmission. This study describes influenza data before and during the coronavirus disease pandemic (COVID‐19) in Cameroon and SARS‐CoV‐2 data during the pandemic period.MethodsThe study ran from 2017 to 2022, and data were divided into two periods: before (2017–2019) and during (2020–2022) the COVID‐19 pandemic. Nasopharyngeal samples collected from persons with respiratory illness were tested for influenza using the Centers for Disease Control and Prevention (CDC) typing and subtyping assays. During the COVID‐19 pandemic, the respiratory specimens were simultaneously tested for SARS‐CoV‐2 using the DaAn gene protocol or the Abbott real‐time SARS‐CoV‐2 assay. The WHO average curve method was used to compare influenza virus seasonality before and during the pandemic.ResultsA total of 6246 samples were tested. Influenza virus detection rates were significantly higher in the pre‐pandemic period compared to the pandemic period (30.8% vs. 15.5%; p < 0.001). Meanwhile, the SARS‐CoV‐2 detection rate was 2.5%. A change in the seasonality of influenza viruses was observed from a bi‐annual peak before the pandemic to no clear seasonal pattern during the pandemic. The age groups 2–4 and 5–14 years were significantly associated with higher influenza positivity rates in both pre‐pandemic and pandemic periods. For SARS‐CoV‐2, all age groups above 15 years were the most affected population.ConclusionThe COVID‐19 pandemic had a significant impact on the seasonal influenza by changing the seasonality of the virus and reducing its detection rates.

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“…Moreover, the presence of one virus does not exclude the possibility that a second infection is present simultaneously. 5 Epidemiology suggests, furthermore, that co-infection from different pathogens is frequent because of common risk factors such as crowded living spaces, lapses in hand hygiene, social interactions, insufficient distancing, and other health determinants. 6…”

Section: Introductionmentioning

confidence: 99%

The Fallacy of a Single Diagnosis

Redelmeier

Shafir

2022

Med Decis Making

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Background Diagnostic reasoning requires clinicians to think through complex uncertainties. We tested the possibility of a bias toward an available single diagnosis in uncertain cases. Design We developed 5 different surveys providing a succinct description of a hypothetical individual patient scenaric. Each scenario was formulated in 2 versions randomized to participants, with the versions differing only in whether an alternative diagnosis was present or absent. The 5 scenarios were designed as separate tests of robustness using diverse cases, including a cautious scenario, a risky scenario, a sophisticated scenario, a validation scenario, and a comparative scenario (each survey containing only 1 version of 1 scenario). Participants included community members ( n = 1104) and health care professionals ( n = 200) who judged the chances of COVID infection in an individual patient. Results The first scenario described a cautious patient and found a 47% reduction in the estimated odds of COVID when a flu diagnosis was present compared with absent (odds ratio = 0.53, 95% confidence interval 0.30 to 0.94, P = 0.003). The second scenario described a less cautious patient and found a 70% reduction in the estimated odds of COVID in the presence of a flu diagnosis (odds ratio = 0.30, 95% confidence interval 0.13 to 0.70, P < 0.001). The third was a more sophisticated scenario presented to medical professionals and found a 73% reduction in the estimated odds of COVID in the presence of a mononucleosis diagnosis (odds ratio = 0.27, 95% confidence interval 0.10 to 0.75, P < 0.001). Two further scenarios—avoiding mention of population norms—replicated the results. Limitations Brief hypothetical scenarios may overestimate the extent of bias in more complicated medical situations. Conclusions These results demonstrate that an available simple diagnosis can lead individuals toward premature closure and a failure to fully consider additional severe diseases. Highlights Occum’s razor has been debated for centuries yet rarely subjected to experimental testing for evidence-based medicine. This article offers direct evidence that people favor an available simple diagnosis, thereby neglecting to consider additional serious diseases. The bias can lead individuals to mistakenly lower their judged likelihood of COVID or another disease when an alternate diagnosis is present. This misconception over the laws of probability appears in judgments by community members and by health care workers. The pitfall in reasoning extends to high-risk cases and is not easily attributed to information, incentives, or random chance.

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Viral co‐infection with human respiratory syncytial virus in suspected acute and severe respiratory tract infections during COVID‐19 pandemic in Yaoundé, Cameroon, 2020–2021

Cited by 6 publications

References 61 publications

Epidemiological and Genetic Characteristics of Respiratory Viral Coinfections with Different Variants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)

Epidemiological and Genetic Characteristics of Respiratory Viral Coinfections with Different Variants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)

The Detection of Influenza Virus Before and During the COVID‐19 Pandemic in Cameroon

The Fallacy of a Single Diagnosis

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