An automatic Covid19 tracker for the East African Regional

Abstract

The outbreak of the Covid19 global pandemic in December 2019 in Wuhan province in mainland China became biggest threat to mankind because little is knew about coronavirus (The virus that causes the disease Covid19). That is to say information on how fast it can spread, how fatal it is, what the risk factors associated with. In March of 2020 the East African land confirmed her first civid19 and there was panic throughout the 5 states and responded via nationwide lockdowns, curfew periods and massive fund the Ministry of Health to combat this deadly disease. In these desperate times there was a need to provide information real-time and reliable information on the status quo of the disease in terms of number of cases confirmed, deaths, recoveries active cases. And since all countries in the world were only focusing on themselves, I was motivated to utilize my programming and statistical skills develop a web application to provide the East Africa community with fast and reliable information in the pam of their hands as long as they have any device that can connect to the internet any time and anyway. Through accessing the John Hopkins University, Covid19 data repository on Github and using the free shinyapps.io server offered by Rstudio. I was able to provide auto updating visualizations using the ggplot2, dygraphs, and plotly packages. This made it easy for anyone in East African to easily understand the patterns and compare the countries’ performance even without have strong statistical background.