Monamele Gwladys C, Vernet Marie-Astrid, Nsaibirni Robert F J, Bigna Jean Joel R, Kenmoe Sebastien, Njankouo Mohamadou Ripa, Njouom Richard
National Influenza Centre, Centre Pasteur du Cameroun, Yaoundé, Cameroon.
Department of Microbiology and Parasitology, University of Buea, Buea, Cameroon.
PLoS One. 2017 Oct 31;12(10):e0186914. doi: 10.1371/journal.pone.0186914. eCollection 2017.
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.
流感与具有高度传染性的呼吸道感染有关。先前的研究发现，流感传播通常与气候变量相关，尤其是在温带地区。进行这项研究是为了填补热带地区流感发病率与三个气象参数（温度、降雨量和湿度）之间关系的知识空白。这是一项于2009年1月至2015年11月在喀麦隆雅温得进行的回顾性研究。来自五个哨点的确诊流感病例的每周比例被视为因变量，而平均温度、平均相对湿度和累积降雨量的每周值被视为自变量。使用单变量线性回归模型来确定流感活动与天气协变量之间的关联。采用时间序列方法预测流感活动的未来值。数据分为两部分；前71个月用于校准模型，最后12个月用于测试预测。总体而言，有1173例确诊的流感病毒感染病例。线性回归分析表明，流感活动与天气变量之间未观察到统计学上的显著关联。观察到的关系非常微弱（-0.1 < r < 0.1）。针对不同病毒类型（总体阳性、甲型流感和乙型流感）获得了三个预测模型。模型1（总体流感）和模型2（甲型流感）在估计期内拟合良好；然而，它们在预测方面未能做出良好的预测。累积降雨量是唯一能使两个模型都拟合良好的外部协变量。基于平稳R2，模型1和模型2分别可以解释该序列中29.5%和41.1%的变化。这项研究更强调了喀麦隆的流感全年都有活动这一事实。本研究中选择的气象变量无法对未来的流感活动做出良好预测，它们肯定是未考虑的其他因素的替代指标，如紫外线辐射、绝对湿度、空气质量和风。
