Abstract Introduction: The COVID-19 disease has spread to over 200 countries and territories since the first case was recorded in Wuhan, China in December 2019. In Kenya, the first case of COVID-19 was recorded on 13th March 2020 and since then over five thousand cases have been confirmed as of 26th June 2020. In the same period, one hundred and forty four mortality cases had been recorded in the country. With the rapid changing situation, timely and reliable data is required for monitoring, planning and rapid decision making with an aim of reversing the already deteriorating situation (economic, health, learning among others) in the country. Methods: The study used the exponential growth model to estimate the daily growth rate and the real-time-effective reproduction number. The study also estimated the naïve and the adjusted Case Fatality Rates. Results: The naïve-Case Fatality Rate of 26th June 2020 which was the 106 day after the first case was confirmed in Kenya was estimated as 2.5% while the adjusted Case Fatality Rate with a lag of 2 days was estimated as 2.6%. The daily exponential growth rate was estimated as 0.22 while the real-time reproduction number as of 26th June 2020 was estimated as 1.28 [95% CI: 1.27 – 1.29]. Conclusion: The daily growth rate and the real-time reproduction number indicated that the outbreak was still growing as of the time of analysis.

Introduction: The COVID-19 disease has spread to over 200 countries and territories since the first case was recorded in Wuhan, China in December 2019. In Kenya, the first case of COVID-19 was recorded on 13th March 2020, since then over one hundred cases have been confirmed, and three deaths recorded as of 2nd April 2020. With the rapid changing situation, timely and reliable data is required for monitoring, planning and rapid decision making with an aim of reversing the already deteriorating situation (economic, health, learning among others) in the country. Methods: The study used the exponential model to project the expected daily cumulative cases in Kenya within the first 40 days. The study opted to do a short time prediction owing to the fact that the scenario is rapidly changing. Data used in the analysis was obtained from the daily updates by the Kenya Ministry of Health, and analysis was done using Stata Version 15 and MS Excel 2010. Results: The Case Fatality Rate on day 21 was estimated as 2.7% (95% CI 0.01 – 7.80), with varying daily estimates as expected. The model estimated that the 1,000 confirmed cases will be reached by 14th April 2020 while the 4,000 cases will be reached by 21st April 2020. The results indicate that it will take 33 days for Kenya to reach the 1,000 confirmed cases and 40 days to reach the 4,000 casesConclusion: Massive screening and contact tracing of all individuals who entered the country within 28 days prior to the mandatory screening should be planned and implemented immediately with an aim of increasing the chances of getting active cases, and possible transmission through such contacts. Continuous modeling of data is needed in order to cater for other factors which were not considered in this study such as the impact of mandatory quarantine, night curfews and suspension of international flights