# Multilevel analysis of determinants of cattle deaths in Ethiopia

## TL;DR

This paper examines factors influencing cattle deaths in Ethiopia using a multilevel analysis to inform better livestock management and policy.

## Contribution

The study introduces a multilevel ZINB regression model to analyze cattle mortality in Ethiopia, revealing regional and household-level determinants.

## Key findings

- 14.6% of the variance in cattle deaths is attributed to regional differences.
- Factors like vaccination status, farming type, and household characteristics significantly affect cattle mortality.
- Promoting mixed farming and improving veterinary services could reduce cattle deaths.

## Abstract

In Ethiopia, agriculture is a fundamental element of both the economy and the social fabric of the community. The sector employs 80-85 percent of the population and contributes 47% to the total GDP. Livestock contributes to people’s livelihoods through numerous channels: income, food, employment, transport, draft-over, manure, savings and insurance, social status, etc. Ethiopia is believed to have the largest livestock population in Africa. Despite this productive and reproductive performance is accompanied by poor health care, high disease incidence, poor management conditions, and unpredictable climactic conditions causing a significant cause of cattle death. The dependent variable is the count “number of occurrences of cattle death” that occurs randomly over time. A multilevel analysis was carried out with the anticipation that there would be variations in the number of cattle deaths per household throughout the region. Before analyzing the data with a multilevel method, check the variability using intra-class correlation (ICC), revealing that 14.6% of the variance in cattle deaths is attributable to the grouping level (Region) indicating the heterogeneity of cattle deaths between Regions. The multilevel ZINB regression model was identified as the best fit for analyzing cattle deaths per household. Factors such as types of agriculture, feeding areas, treatment methods, vaccination status, household land size, age of the household head, household size, and education level were found to significantly impact cattle mortality in the positive count portion of the random-intercept ZINB regression model. The Ministry of Agriculture should effectively raise awareness among agricultural producers regarding cattle vaccination and enhance the veterinary services available in the country. It is also advisable to promote a mixed farming approach rather than solely focusing on livestock farming to reduce cattle deaths. Farmers should consider reducing their household size and place greater emphasis on the welfare of their cattle.