AUTHOR=Innocent Giles T. , Vance Ciara , Ewing David A. , McKendrick Iain J. , Hailemariam Solomon , Nwankpa Veronica R. , Allan Fiona K. , Schnier Christian , Peters Andrew R. TITLE=Patterns of mortality in domesticated ruminants in Ethiopia JOURNAL=Frontiers in Veterinary Science VOLUME=9 YEAR=2022 URL=https://www.frontiersin.org/journals/veterinary-science/articles/10.3389/fvets.2022.986739 DOI=10.3389/fvets.2022.986739 ISSN=2297-1769 ABSTRACT=Background

Premature death of livestock is a problem in all ruminant production systems. While the number of premature ruminant deaths in a country is a reasonable indicator for the nation's health, few data sources exist in a country like Ethiopia that can be used to generate valid estimates. The present study aimed to establish if three different data sets, each with imperfect information on ruminant mortality, including abortions, could be combined into improved estimates of nationwide mortality in Ethiopia.

Methods

We combined information from a recent survey of ruminant mortality with information from the Living Standards Measurement Study and the Disease Outbreak and Vaccination Reporting dataset. Generalized linear mixed and hurdle models were used for data analysis, with results summarized using predicted outcomes.

Results

Analyses indicated that most herds experienced zero mortality and reproductive losses, with rare occasions of larger losses. Diseases causing deaths varied greatly both geographically and over time. There was little agreement between the different datasets. While the models aid the understanding of patterns of mortality and reproductive losses, the degree of variation observed limited the predictive scope.

Conclusions

The models revealed some insight into why mortality rates are variable over time and are therefore less useful in measuring production or health status, and it is suggested that alternative measures of productivity, such as number of offspring raised to 1 year old per dam, would be more stable over time and likely more indicative.