A review of foot-and-mouth disease in Ethiopia: epidemiological aspects, economic implications, and control strategies

Zewdie, Girma; Akalu, Mirtneh; Tolossa, Wondwossen; Belay, Hassen; Deresse, Getaw; Zekarias, Mariamawit; Tesfaye, Yeneneh

doi:10.1186/s12985-023-02263-0

Cited by 3 publications

(3 citation statements)

References 151 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In Tanzania, a nearly comparable WTP amount, i.e., 1.84 USD, was reported for the cattle FMD vaccine [ 23 ]. Kairu-wanyoike et al [ 5 ] estimated a mean WTP of 3.03 USD for the contagious bovine pleuropneumonia vaccination in the Narok south district of Kenya.…”

Section: Discussionmentioning

confidence: 99%

“…In Ethiopia, various control methods are employed to manage Foot-and-Mouth Disease (FMD), including the implementation of biosecurity measures. These measures encompass conducting vaccination campaigns, implementing disinfection protocols, ensuring safe disposal of carcasses, raising public awareness and education about FMD, and administering antibiotics to combat secondary bacterial complications [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

“…However, the use of vaccines that cover multiple serotypes and strains presents challenges due to reduced potency and higher costs compared to single-serotype vaccines [ 4 ]. Achieving effective cross-protection among the various serotypes and strains is also difficult [ 5 ]. In Ethiopia, FMD outbreaks are widespread across all production systems, particularly in mixed crop-livestock, pastoral, and market-oriented districts.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Assessing farmers’ willingness to pay for FMD vaccines and factors influencing payment: a contingent valuation study in central Oromia, Ethiopia

Layessa,

Gebremedhin,

Sarba

et al. 2024

BMC Vet Res

View full text Add to dashboard Cite

Background Foot and mouth disease is a contagious, transboundary, and economically devastating viral disease of cloven-hoofed animals. The disease can cause many consequences, including decreased productivity, limited market access, and elimination of flocks or herds. This study aimed to assess farmers’ willingness to pay (WTP) for foot and mouth disease (FMD) vaccines and identify factors influencing their WTP. A cross-sectional questionnaire survey was conducted on 396 randomly selected livestock-owning farmers from three districts in the central Oromia region (Ambo, Dendi, and Holeta districts. The study utilized the contingent valuation method, specifically employing dichotomous choice bids with double bounds, to evaluate the willingness to pay (WTP) for the FMD vaccine. Mean WTP was assessed using interval regression, and influential factors were identified. Results The study revealed that the farmer’s mean willingness to pay for a hypothetical foot and mouth disease vaccine was 37.5 Ethiopian Birr (ETB) [95% confidence interval [CI]: 34.5 40.58] in all data, while it was 23.84 (95% CI: 21.47–26.28) in the mixed farming system and 64.87 Ethiopian Birr (95% CI: 58.68 71.15) in the market-oriented farming system. We identified main livelihood, management system, sales income, breed, keeping animals for profit, and foot and mouth disease impact perception score as significant variables (p ≤ 0.05) determining the farmers’ WTP for the FMD vaccine. Conclusion Farmers demonstrated a high computed willingness to pay, which can be considered an advantage in the foot and mouth disease vaccination program in central Oromia. Therefore, it is necessary to ensure sufficient vaccine supply services to meet the high demand revealed.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Assessing farmers’ willingness to pay for FMD vaccines and factors influencing payment: a contingent valuation study in central Oromia, Ethiopia

Layessa,

Gebremedhin,

Sarba

et al. 2024

BMC Vet Res

View full text Add to dashboard Cite

show abstract

Adoption of veterinary vaccines, determining factors, and barriers in Southwest Ethiopia: Implications for livestock health and disease management strategies

Robi,

Bogale,

Temteme

et al. 2024

Preventive Veterinary Medicine

View full text Add to dashboard Cite

A unified Foot and Mouth Disease dataset for Uganda: evaluating machine learning predictive performance degradation under varying distributions

Kapalaga,

Kivunike,

Kerfua

et al. 2024

Front. Artif. Intell.

View full text Add to dashboard Cite

In Uganda, the absence of a unified dataset for constructing machine learning models to predict Foot and Mouth Disease outbreaks hinders preparedness. Although machine learning models exhibit excellent predictive performance for Foot and Mouth Disease outbreaks under stationary conditions, they are susceptible to performance degradation in non-stationary environments. Rainfall and temperature are key factors influencing these outbreaks, and their variability due to climate change can significantly impact predictive performance. This study created a unified Foot and Mouth Disease dataset by integrating disparate sources and pre-processing data using mean imputation, duplicate removal, visualization, and merging techniques. To evaluate performance degradation, seven machine learning models were trained and assessed using metrics including accuracy, area under the receiver operating characteristic curve, recall, precision and F1-score. The dataset showed a significant class imbalance with more non-outbreaks than outbreaks, requiring data augmentation methods. Variability in rainfall and temperature impacted predictive performance, causing notable degradation. Random Forest with borderline SMOTE was the top-performing model in a stationary environment, achieving 92% accuracy, 0.97 area under the receiver operating characteristic curve, 0.94 recall, 0.90 precision, and 0.92 F1-score. However, under varying distributions, all models exhibited significant performance degradation, with random forest accuracy dropping to 46%, area under the receiver operating characteristic curve to 0.58, recall to 0.03, precision to 0.24, and F1-score to 0.06. This study underscores the creation of a unified Foot and Mouth Disease dataset for Uganda and reveals significant performance degradation in seven machine learning models under varying distributions. These findings highlight the need for new methods to address the impact of distribution variability on predictive performance.

show abstract

A review of foot-and-mouth disease in Ethiopia: epidemiological aspects, economic implications, and control strategies

Cited by 3 publications

References 151 publications

Assessing farmers’ willingness to pay for FMD vaccines and factors influencing payment: a contingent valuation study in central Oromia, Ethiopia

Assessing farmers’ willingness to pay for FMD vaccines and factors influencing payment: a contingent valuation study in central Oromia, Ethiopia

Adoption of veterinary vaccines, determining factors, and barriers in Southwest Ethiopia: Implications for livestock health and disease management strategies

A unified Foot and Mouth Disease dataset for Uganda: evaluating machine learning predictive performance degradation under varying distributions

Contact Info

Product

Resources

About