Comparison of FTD® respiratory pathogens 33 and a singleplex CDC assay for the detection of respiratory viruses: A study from Cameroon.

INTRODUCTION: This study compares the detection of 14 common respiratory viruses by two different real-time reverse transcription polymerase chain reaction (rRT-PCR) methods: in house singleplex tests developed by the Centers for Disease Control and Prevention and the commercially available Fast Track Diagnostic (FTD®) Respiratory Pathogens 33 multiplex test. METHODS: A total of 217 nasopharyngeal swabs were analyzed using CDC singleplex rRT-PCR and FTD® Respiratory Pathogens 33 multiplex assays, for the detection of 14 respiratory viruses. RESULTS: The results showed that 179/217 (82.5%) samples were positive with the singleplex method and 183/217 (84.3%) with the FTD® Respiratory Pathogens 33 multiplex test. Excellent or satisfactory agreement was obtained for all viruses (k > 0.6) except Parainfluenzavirus 4 (k = 0.24) and influenza B (k = 0.51). CONCLUSION: Although the multiplex FTD kits were more expensive than the singleplex assay, the FTD kits yielded rapid results in a shorter timeframe, increasing efficiency of diagnosis.

Genetic and antigenic characterization of influenza A(H3N2) in Cameroon during the 2014-2016 influenza seasons.

The first outbreak of influenza A(H3N2) occurred in 1968 and caused the third flu pandemic of the 20th century. It has affected multiple countries over time. The best strategy to reduce the burden of influenza is through vaccination whose efficacy varies with respect to the circulating strains. This study was performed to better understand the molecular evolution of influenza A(H3N2) and assess vaccine efficacy in Cameroon. Complete sequences of three gene segments were obtained from 2014 to 2016 influenza seasons in Cameroon. Hemagglutinin (HA), Neuraminidase (NA) and matrix (M) genes of 35 A(H3N2) virus strains were amplified and sequenced. Predicted vaccine efficacy was measured using the Pepitope model. Phylogenetic analysis of the HA gene showed that all Cameroonian strains had evolved away from the 3C.1-A/Texas/50/2012-like clade. Globally, 2014 virus strains clustered with the 2015-2016 vaccine strain, 3C.3a-A/Switzerland/9715293/2013, whereas 2015 and 2016 virus strains clustered with the 2016-2017 vaccine strain, 3C.2a-A/HongKong/4801/2014. In order to determine the genotypic drug susceptibility to neuraminidase inhibitors and amantadine, the NA and M2 protein coding sequences were analyzed. There was no strain with characteristic mutation for resistance to neuraminidase inhibitors, per contra; all strains possessed the substitution S31N, peculiar of resistance to adamantanes. There was drift in influenza A(H3N2) dominant epitopes B (2014 and 2015) to epitopes A (2016) with a theoretical efficiency in vaccine ranging from low to moderate. The presence of several antigenic site mutations among H3N2 virus strains between 2014-2016 influenza seasons in Cameroon confirms the progressing evolution of circulating H3N2 strains.

Associations between meteorological parameters and influenza activity in a subtropical country: Case of five sentinel sites in Yaoundé-Cameroon.

Influenza is associated with highly contagious respiratory infections. Previous research has found that influenza transmission is often associated with climate variables especially in temperate regions. This study was performed in order to fill the gap of knowledge regarding the relationship between incidence of influenza and three meteorological parameters (temperature, rainfall and humidity) in a tropical setting. This was a retrospective study performed in Yaoundé-Cameroon from January 2009 to November 2015. Weekly proportions of confirmed influenza cases from five sentinel sites were considered as dependent variables, whereas weekly values of mean temperature, average relative humidity and accumulated rainfall were considered as independent variables. A univariate linear regression model was used in determining associations between influenza activity and weather covariates. A time-series method was used to predict on future values of influenza activity. The data was divided into 2 parts; the first 71 months were used to calibrate the model, and the last 12 months to test for prediction. Overall, there were 1173 confirmed infections with influenza virus. Linear regression analysis showed that there was no statistically significant association observed between influenza activity and weather variables. Very weak relationships (-0.1 < r < 0.1) were observed. Three prediction models were obtained for the different viral types (overall positive, Influenza A and Influenza B). Model 1 (overall influenza) and model 2 (influenza A) fitted well during the estimation period; however, they did not succeed to make good forecasts for predictions. Accumulated rainfall was the only external covariate that enabled good fit of both models. Based on the stationary R2, 29.5% and 41.1% of the variation in the series can be explained by model 1 and 2, respectively. This study laid more emphasis on the fact that influenza in Cameroon is characterized by year-round activity. The meteorological variables selected in this study did not enable good forecast of future influenza activity and certainly acted as proxies to other factors not considered, such as, UV radiation, absolute humidity, air quality and wind.