Genetic diversity of influenza A(H3N2) viruses in Northern Cameroon during the 2014‐2016 influenza seasons

Njifon, Hermann Landry Munshili; Monamele, Chavely Gwladys; Vernet, Marie‐Astrid; Njankouo, Mohamadou Ripa; Deweerdt, Louis; Nono, Raphael; Kenmoe, Sébastien; Mbacham, Wilfred; Njouom, Richard

doi:10.1002/jmv.25456

Cited by 6 publications

(20 citation statements)

References 27 publications

(37 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In 2014, new strains similar to the 2014 SH season A/Texas/50/2012(H3N2) vaccine strain were sampled in Congo [ 97 ], South Africa [ 77 ], and Southern and Northern Cameroon [ 78 , 79 ]. The A/Texas/50/2012(H3N2) vaccine showed low efficacy in South Africa (VE: −18.4% (−171.5 to −48.4) [ 77 ], and the majority of the sampled Congo and South Cameroon strains were also antigenically similar to the A/Switzerland/9715293/2013(H3N2) vaccine strain used later in 2015 [ 78 , 97 ].…”

Section: Resultsmentioning

confidence: 99%

“…H3N2 strains sampled in Egypt strains between 2015 and 2017 had several mutated antigenic sites A (T135K, R142G/K/A, N144K/S, N145S), B (L157S, F159Y, K160T), C (D53N/G, N278K), and D (N121D/K/S, N225D), and all had the non-agglutinating substitution N225D [ 101 ]. Strains sampled in the same period (2015–2017) from Northern and Southern Cameroon were similar to the 2016–2017 season SNH A/Hong Kong/4801/2014(H3N2) vaccine strain but had different dominant antigenic sites resulting in different efficacy of the A/Switzerland/9715293/2013(H3N2) vaccine in Northern (80.55%) and Southern Cameroon (17%) in 2015 [ 78 , 79 ].…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Molecular Epidemiology and Evolutionary Dynamics of Human Influenza Type-A Viruses in Africa: A Systematic Review

et al. 2022

View full text Add to dashboard Cite

Genomic characterization of circulating influenza type-A viruses (IAVs) directs the selection of appropriate vaccine formulations and early detection of potentially pandemic virus strains. However, longitudinal data on the genomic evolution and transmission of IAVs in Africa are scarce, limiting Africa’s benefits from potential influenza control strategies. We searched seven databases: African Journals Online, Embase, Global Health, Google Scholar, PubMed, Scopus, and Web of Science according to the PRISMA guidelines for studies that sequenced and/or genomically characterized Africa IAVs. Our review highlights the emergence and diversification of IAVs in Africa since 1993. Circulating strains continuously acquired new amino acid substitutions at the major antigenic and potential N-linked glycosylation sites in their hemagglutinin proteins, which dramatically affected vaccine protectiveness. Africa IAVs phylogenetically mixed with global strains forming strong temporal and geographical evolution structures. Phylogeographic analyses confirmed that viral migration into Africa from abroad, especially South Asia, Europe, and North America, and extensive local viral mixing sustained the genomic diversity, antigenic drift, and persistence of IAVs in Africa. However, the role of reassortment and zoonosis remains unknown. Interestingly, we observed substitutions and clades and persistent viral lineages unique to Africa. Therefore, Africa’s contribution to the global influenza ecology may be understated. Our results were geographically biased, with data from 63% (34/54) of African countries. Thus, there is a need to expand influenza surveillance across Africa and prioritize routine whole-genome sequencing and genomic analysis to detect new strains early for effective viral control.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Molecular Epidemiology and Evolutionary Dynamics of Human Influenza Type-A Viruses in Africa: A Systematic Review

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Due to similar clinical presentations to other infectious agents, presumptive treatment of influenza in hospital settings usually involves the administration of antimalarial and antibacterial drugs which could have as consequence the development of anti-microbial resistance [13]. Meanwhile, previous genomic data has shown that neuraminidase inhibitors are potent antivirals that could be used for influenza therapy in Cameroon [14][15][16][17]. Thus, predicting influenza can have important healthcare benefits to the individual as well as to the community.…”

Section: Introductionmentioning

confidence: 99%

Clinical signs predictive of influenza virus infection in Cameroon

et al. 2020

Self Cite

View full text Add to dashboard Cite

Influenza virus accounts for majority of respiratory virus infections in Cameroon. According to the World Health Organization (WHO), influenza-like illnesses (ILI) are identified by a measured temperature of �38˚C and cough, with onset within the past 10 days. Other symptoms could as well be observed however, none of these are specific to influenza alone. This study aimed to determine symptom based predictors of influenza virus infection in Cameroon. Individuals with ILI were recruited from 2009-2018 in sentinel sites of the influenza surveillance system in Cameroon according to the WHO case definition. Individual data collection forms accompanied each respiratory sample and contained clinical data. Samples were analyzed for influenza using the gold standard assay. Two statistical methods were compared to determine the most reliable clinical predictors of influenza virus activity in Cameroon: binomial logistic predictive model and random forest model. Analyses were performed in R version 3.5.2. A total of 11816 participants were recruited, of which, 24.0% were positive for influenza virus. Binomial logistic predictive model revealed that the presence of cough, rhinorrhoea, headache and myalgia are significant predictors of influenza positivity. The prediction model had a sensitivity of 75.6%, specificity of 46.6% and AUC of 66.7%. The random forest model categorized the reported symptoms according to their degree of importance in predicting influenza virus infection. Myalgia had a 2-fold higher value in predicting influenza virus infection compared to any other symptom followed by arthralgia, head ache, rhinorrhoea and sore throat. The model had a OOB error rate of 25.86%. Analysis showed that the random forest model had a better performance over the binomial regression model in predicting influenza infection. Rhinorrhoea, headache and myalgia were symptoms reported by both models as significant predictors of influenza infection in Cameroon. These symptoms could be used by clinicians in their decision to treat patients.

show abstract

“…In this paper we aim to model and nowcast (hereafter referred to as, forecast) ILI in Cameroon using data from a surveillance system for influenza and ILI implemented by the Ministry of Health (MOH) in Cameroon 28 . Recent studies on influenza and ILI surveillance in Cameroon have focused on viral identification 29 , understanding genetic diversity 30,31 , and seasonality of All rights reserved. No reuse allowed without permission.…”

Section: Introductionmentioning

confidence: 99%

Nowcasting Influenza-like Illness Trends in Cameroon

Nsoesie

Oladeji

Abah

et al. 2020

Preprint

View full text Add to dashboard Cite

Although acute respiratory infections are a leading cause of mortality in sub-Saharan Africa, surveillance of diseases such as influenza is mostly neglected. Evaluating the usefulness of influenza-like illness (ILI) surveillance systems and developing approaches for forecasting future trends is important for pandemic preparedness. We applied statistical and machine learning models to forecast 2012 to 2018 trends in ILI cases reported by the Cameroon Ministry of Health (MOH), using Google searches for influenza symptoms, treatments, natural or traditional remedies as well as, infectious diseases with a high burden (i.e., AIDS, malaria, tuberculosis). The variance explained by the models based on Google search data were 87.7%, 79.1% and 52.0% for the whole country, the Littoral and Centre regions respectively. Our study demonstrates the need for developing contextualized approaches when using digital data for disease surveillance and demonstrates the potential usefulness of search data for monitoring ILI in sub-Saharan African countries.

show abstract

Genetic diversity of influenza A(H3N2) viruses in Northern Cameroon during the 2014‐2016 influenza seasons

Cited by 6 publications

References 27 publications

Molecular Epidemiology and Evolutionary Dynamics of Human Influenza Type-A Viruses in Africa: A Systematic Review

Molecular Epidemiology and Evolutionary Dynamics of Human Influenza Type-A Viruses in Africa: A Systematic Review

Clinical signs predictive of influenza virus infection in Cameroon

Nowcasting Influenza-like Illness Trends in Cameroon

Contact Info

Product

Resources

About