Spatial and temporal patterns of foot and mouth disease outbreaks (2011–2022) in cattle export-sourcing areas of southeastern Ethiopia

Abstract Background Foot-and-mouth disease (FMD) is a highly contagious viral infection that infects cloven-hoofed animals, including cattle, sheep, goats, swine, and various wildlife species. Ethiopia is found in pool four where Serotype A, Serotype O, SAT1 and SAT2 are endemic. A retrospective study was conducted to analyse the spatial and temporal patterns of FMD outbreaks in export-sourcing areas of Southeastern Ethiopia over 12 years (from January 2011 to December 2022), using reported FMD outbreak data. Geographically, the area extending from Borana to East Shoa, along the main road connecting Moyale to Adama, was identified as the primary FMD outbreak zone within the cattle export-sourcing areas of southeastern Ethiopia. Results The data on Foot-and-mouth disease (FMD) outbreaks over the past twelve years (from January 2011 to December 2022) obtained from the Ministry of Agriculture’s, Ethiopia database were retrieved and analyzed. There were a total of 58,426 cases across 247 outbreaks in 11 zones and 89 districts within the cattle export-sourcing areas of southeastern Ethiopia. On average, there were 20.3 outbreaks per year, with a median of 18 outbreaks annually, corresponding to approximately 4.6 outbreaks per month. The highest incidence occurred in January. The year with the most reported outbreaks was 2011, which had 54 outbreaks, followed by 2020 with 39 outbreaks and 2015 with 30 outbreaks In contrast, there were very few outbreaks recorded in 2014 and 2019. The case fatality rate was 1.02%, and an estimated 4,775,124 cattle were at risk of FMD infection. A time-series decomposition of the FMD outbreak data revealed seasonal trends. The trend analysis indicated that FMD outbreaks occurred in a cycle of two to five years, with peaks observed in 2011, 2012, 2015, and 2021. The incidence of FMD outbreaks varied across different zones, being lowest in the Afder and Gedeo zones and highest in the Arsi zone. An analysis using a space-time permutation probability model within the SaTScan software, with a maximum cluster size of 50%, identified five high-risk clusters and four low-risk clusters that were statistically significant (P