Foot-and-mouth disease virus (FMDV) has a substantial impact on cattle populations in Uganda, causing short- and long-term production losses and hampering local and international trade. Although FMDV has persisted in Uganda for at least 60 years, its epidemiology there and in other endemic settings remains poorly understood. Here, we utilized a large-scale cross-sectional study of cattle to elucidate the dynamics of FMDV spread in Uganda. Sera samples (n = 14,439) from 211 herds were analyzed for non-structural protein reactivity, an indication of past FMDV exposure. Serological results were used to determine spatial patterns, and a Bayesian multivariable logistic regression mixed model was used to identify risk factors for FMDV infection. Spatial clustering of the disease was evident, with higher risk demonstrated near international borders. Additionally, high cattle density, low annual rainfall, and pastoralism were associated with increased likelihood of FMD seropositivity. These results provide insights into the complex epidemiology of FMDV in Uganda and will help inform refined control strategies in Uganda and other FMDV-endemic settings.
Bibliographical noteFunding Information:
This study was funded by the Cooperative Biological Engagement Program of the United States Department of Defense, Defense Threat Reduction Agency [agreement #8802 ]. Additional support was provided by the Agricultural Research Service, United States Department of Agriculture [CRIS project #1940-32000-061-00D ]. AM was funded by the National Institute of Food and Agriculture, United States Department of Agriculture [grant #2016-38420-25288 ].
© 2019 Elsevier B.V.
- Bayesian statistics
- Foot and mouth disease
- Risk factors
- Spatial analysis