| Sumario: | The Rift Valley fever (RVF) disease, a climate-sensitive zoonosis, causes 100% abortions and death in infected animals. This shock has an immediate effect on the food prices, particularly the animal-sourced foods. This study used an Interrupted Time Series (ITS) approach combined with Auto regressive Integrated Moving Average (ARIMA) model to model and assess the effects of the 2018 and 2021 RVF outbreaks on Kenya’s food price on economic disruptions. Data from several Kenyan cities, including Nairobi, Kisumu, Eldoret, and Mombasa, were analyzed to identify inflation trends across different markets. The findings clearly show significant price index fluctuations, with inflation escalating following critical RVF outbreak shock periods, particularly during the outbreak periods. In Nairobi, the lowest recorded value was -14.970, 25% of the observations were below -4.527, the middle value was 2.475, the average value was 6.014, 75% of the observations were below 10.742, and the highest recorded value was 51.450. In Wajir town for instance, the lowest recorded value was -14.590, 25% of the observations were below -4.875, the middle value was 1.230, the average value was 6.507, 75% of the observations were below 13.707, and the highest recorded value was 13.707. The ARIMA model successfully identified these changes, highlighting the distinct effects across all regions, with some areas exhibiting significant forecasting inaccuracies. Different ARIMA models with different orders were obtained including ARIMA(3,1,2)(0,0,1)[12].This study generates new knowledge, provides critical insights into market dynamics, and presents a predictive framework for dealing with future economic disruptions in Kenya and elsewhere. Policymakers can use these findings to create targeted strategies for stabilizing food prices and ensuring economic resilience during future RVF outbreaks.
|
|---|