Chikungunya is an emerging threat for health security all over the world which is spreading very fast. Researches for proper forecasting of the incidence rate of chikungunya has been going on in many places in which DARPA has done a very extensive summarized result from 2014 to 2017 with the data of suspected cases, confirmed cases, deaths, population and incidence rate in different countries. In this project, we have analysed the dataset from DARPA and extended it to predict the incidence rate using different features of weather like temperature, humidity, dewiness, wind and pressure along with the latitude and longitude of every country. We had to use different APIs to find out these extra features from 2014-2016. After creating a pure dataset, we have used Linear Regression to predict the incidence rate and calculated the accuracy and error rate.
翻译:Chikungunya是全世界健康安全面临的一个新出现的威胁,正在迅速蔓延,在2014年至2017年期间,美国移民和难民管理局对不同国家的疑似病例、确诊病例、死亡、人口和发病率的数据进行了非常广泛的总结,对许多地方进行了适当预测Chikungunya发病率的研究,对这些地区进行了广泛分析。在这个项目中,我们分析了来自美国移民和难民管理局的数据集,并扩大了该数据集的范围,利用不同天气特征,如温度、湿度、脱水度、风和压力以及每个国家的纬度和经度来预测发病率。我们不得不使用不同的API来发现2014年至2016年的这些额外特征。在创建了纯数据集之后,我们利用线性回归来预测发生率并计算准确率和误差率。