  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.
