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

BACKGROUND: Influenza 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. METHODS: The 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. RESULTS: A 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. CONCLUSION: The COVID-19 pandemic had a significant impact on the seasonal influenza by changing the seasonality of the virus and reducing its detection rates.

Clinical signs predictive of influenza virus infection in Cameroon.

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.

Evaluation of a mobile health approach to improve the Early Warning System of influenza surveillance in Cameroon.

BACKGROUND: Rapid reporting of surveillance data is essential to better inform national prevention and control strategies. OBJECTIVES: We compare the newly implemented smartphone-based system to the former paper-based and short message service (SMS) for collecting influenza epidemiological data in Cameroon. METHODS: Of the 13 sites which collect data from persons with influenza-like illness (ILI), six sites send data through the EWS, while seven sites make use of the paper-based system and SMS. We used four criteria for the comparison of the data collection tools: completeness, timeliness, conformity and cost. RESULTS: Regarding the different collection tools, data sent by the EWS were significantly more complete (97.6% vs 81.6% vs 44.8%), prompt (74.4% vs n/a vs 60.7%) and of better quality (93.7% vs 76.1% vs 84.0%) than data sent by the paper-based system and SMS, respectively. The average cost of sending a datum by a sentinel site per week was higher for the forms (5.0 USD) than for the EWS (0.9 USD) and SMS (0.1 USD). The number of outpatient visits and subsequently all surveillance data decreased across the years 2017-2019 together with the influenza positivity rate from 30.7% to 28.3%. Contrarily, the proportion of influenza-associated ILI to outpatient load was highest in the year 2019 (0.37 per 100 persons vs 0.28 and 0.26 in the other 2 years). CONCLUSION: All sentinel sites and even other disease surveillance systems are expected to use this tool in the near term future due to its satisfactory performance and cost.

Circulation of influenza virus from 2009 to 2018 in Cameroon: 10 years of surveillance data.

Since the recent emergence of several subtypes of influenza viruses with pandemic potentials, there has been growing interest on the control of this infection worldwide. This study aimed to describe the 10 years of influenza activity in Cameroon between January 2009 and December 2018. Respiratory samples were collected from sentinel sites responsible for influenza surveillance in Cameroon and analyzed for the presence of influenza. Globally, 9 of the 10 administrative regions of the country were represented with at least 1 year of data. A total of 11816 respiratory samples were collected and influenza virus detection rate was 24.0%. The most represented age group was the 0-1 years representing more than 40% of the collected samples and possessing the lowest proportion of influenza cases (16.2%). Meanwhile higher proportions of influenza positive cases was found in the 2-4, 5-14 and 15-49 years age group at ≥29%. Among outpatients, the frequency of influenza virus was 24.8% while in hospitalized patients, 18.7% of samples were positive for influenza virus. We noted year-round circulation of influenza virus in Cameroon with 2 peaks in activity: a major peak in the months of September to December and a minor peak in the months of March to July. Antigenic characterization of influenza isolates showed 37.5% (6/16) vaccine match between the predominant Cameroon strains and the Northern hemisphere vaccine strains with majority of vaccine match observed in influenza B/Victoria subtype (4/6; 66.7%). Data collected from this surveillance system is essential to add to global information on the spread of influenza.

Molecular characterization of influenza A(H1N1)pdm09 in Cameroon during the 2014-2016 influenza seasons.

In 2009, Influenza A(H1N1)pdm09 caused the first influenza pandemic of the 21st century with high mortality rates of about 284 500 deaths. This virus, however, continues to circulate as a seasonal influenza virus and to cause illness and deaths worldwide. In this study, we describe the genetic diversity of A(H1N1)pdm09 viruses collected between 2014 and 2016 in Cameroon. Three gene segments (HA, NA and M) of Cameroon strains were studied. The phylogenetic tree of the coding nucleotide sequences was generated by MEGA version 6.0 using a Maximum Likelihood method. The NA and M protein coding sequences were analyzed for the reported genetic markers of resistance against neuraminidase inhibitors and adamantanes, while predicted vaccine efficacy was estimated using the Pepitope method. Overall 39 strains were obtained. Phylogenetic analysis of the HA gene of influenza A(H1N1)pdm09 showed that Cameroon strains belonged to two major clades. The 2014 Cameroon sequences belonged to clade 6C while all sequences collected between 2015 and 2016 belonged to clade 6B. Majority of the samples had some mutations in the NA gene notably: I117M, N248D, and N369K while the amantadine-resistant M mutant, S31N, was found to be absent only in the two sequences collected in 2014. Overall, A/California/07/2009 vaccine strain showed a predicted vaccine efficacy of 24.55% to 35.77% against Cameroon A(H1N1)pdm09 strains circulating between 2014 and 2016. Our findings confirms the fast evolution of A(H1N1)pdm09 since its first introduction and highlights on the importance of influenza vaccine in reducing the burden caused by influenza in the community.

Influence of meteorological parameters in the seasonality of influenza viruses circulating in Northern Cameroon.

BACKGROUND: Several studies have demonstrated the role of meteorological parameters in the seasonality of influenza viruses in tropical and subtropical regions, most importantly temperature, humidity, and rainfall. OBJECTIVES: This study aimed to describe the influence of meteorological parameters in the seasonality of influenza viruses in Northern Cameroon, a region characterized by high temperatures. METHODS: This was a retrospective study performed in Garoua Cameroon from January 2014 to December 2016. Monthly proportions of confirmed influenza cases from six sentinel sites were considered as dependent variables, whereas monthly values of mean temperature, average relative humidity, and accumulated rainfall were considered as independent variables. A vector error correction model was used to determine the relationship between influenza activity and the meteorological variables. RESULTS AND CONCLUSION: Analysis showed that there was a statistically significant association between overall influenza activity and influenza A activity with respect to average relative humidity. A unit increase in humidity within a given month leads to more than 85% rise in the overall influenza and influenza A activity 2 months later. Meanwhile, none of the three meteorological variables could explain influenza B activity. This observation is essential in filling the gap of knowledge and could help in the prevention and control strategies to strengthen influenza surveillance program in Cameroon.