Impact of Rift Valley fever outbreaks on food price index in Burundi: An interrupted time series analysis

Abstract

The livestock sector contributes to one of the Sustainable Development Goals (SDG) 2, which is zero hunger and affects all the four components of food security. For instance, the market price instability which is a component of food accessibility is majorly affected by unstable prices at the market, which are brought about by disease outbreaks. The main purpose of this study was to investigate the impact of the April 2022 Rift Valley fever (RVF) disease outbreaks on the food price index in Burundi using an Interrupted Time Series (ITS) analysis. The study estimated the impact of an intervention on an outcome variable for a single treatment group, when compared to a control group, and for multiple sequential interventions using the STATA software’s XTITSA command. The study found mixed evidence for the effectiveness of the intervention across the four regions namely Kirundo, Muyinga, Ngozi and Cibitoke. While Cibitoke displayed statistically significant improvements in both the starting level and pre-post trend, Muyinga only showed a significant effect in the starting level. Cibitoke exhibited a statistically significant increase in both initial level (+5.925, p < 0.05) and post-intervention trend (−1.172, p < 0.01), while Muyinga showed a significant effect in the starting level (+6.77, p < 0.01) but no significant trend shift. Kirundo and Ngozi showed no significant treatment effects. The average food price index across all regions was 8.94. The largest standard deviation (16.95) was found in Kirundo, indicating more significant fluctuations in food prices in that region. Kirundo and Ngozi exhibited statistically no significant treatment effects, potentially due to pre-existing differences in baseline levels and trends compared to Cibitoke. This highlights the importance of carefully selecting control groups with similar starting points and trajectories to ensure valid treatment effect estimates.