tetano
Editor, Senior Moderator
PLoS One. 2017 Oct 31;12(10):e0186914. doi: 10.1371/journal.pone.0186914. eCollection 2017.
[h=1]Associations between meteorological parameters and influenza activity in a subtropical country: Case of five sentinel sites in Yaound?-Cameroon.[/h] Monamele GC[SUP]1,[/SUP][SUP]2[/SUP], Vernet MA[SUP]1[/SUP], Nsaibirni RFJ[SUP]1[/SUP], Bigna JJR[SUP]1[/SUP], Kenmoe S[SUP]1[/SUP], Njankouo MR[SUP]1[/SUP], Njouom R[SUP]1[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] 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 Yaound?-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.
PMID: 29088290 DOI: 10.1371/journal.pone.0186914
Free full text
[h=1]Associations between meteorological parameters and influenza activity in a subtropical country: Case of five sentinel sites in Yaound?-Cameroon.[/h] Monamele GC[SUP]1,[/SUP][SUP]2[/SUP], Vernet MA[SUP]1[/SUP], Nsaibirni RFJ[SUP]1[/SUP], Bigna JJR[SUP]1[/SUP], Kenmoe S[SUP]1[/SUP], Njankouo MR[SUP]1[/SUP], Njouom R[SUP]1[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] 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 Yaound?-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.
PMID: 29088290 DOI: 10.1371/journal.pone.0186914
Free full text