Patterns of mortality in domesticated ruminants in Ethiopia

Abstract

BackgroundPremature 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.MethodsWe 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.ResultsAnalyses 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.ConclusionsThe 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.

Gastrointestinal nematodiasis of goats in Somali pastoral areas, Ethiopia

“…Despite the large population of goats (30.20 million) in Ethiopia ( CSA, 2016 ), the economic benefits of livestock are restricted due to diseases, malnutrition, inadequate management, and lack of access to veterinary care, despite being an abundant resource. This contributes to high morbidity and mortality rates, with annual losses of up to 50% of the total livestock product value ( Innocent et al, 2022 ). Goats frequently contract gastrointestinal (GI) parasitic infections, particularly nematodes, which result in significant economic losses due to animal mortality and decreased weight gain ( Dey et al, 2020 ).…”

Livestock Disease Data Management for E-Surveillance and Disease Mapping Using Cluster Analysis

“…A. Data Management Framework After carefully reviewing research publications, we identified limitations in the current science of art [8,[12][13][14][15][16][17], and through discussions with key stakeholders, we explored their roles and proposed the following ELHRs, as shown in FIGURE 1. The diverse data values related to different stakeholders with detailed descriptions is also presented in TABLE 1.…”

“…Outbreak and Vaccination Reporting System (DOVAR) is a digital platform to manage and report disease outbreaks. Its main purpose is to conduct national passive surveillance through the collection of animal disease outbreaks and vaccination data on a monthly basis [14]. Nevertheless, this platform proves effective for managing livestock health data, it lacks the comprehensiveness and functionalities to address the entire range of livestock health-related information and beside it failed to provide timely livestock health-related information.…”

“…The research in [14], aimed to address the premature death of domesticated ruminants in Ethiopia by combining farmer survey data, living standards measurement data, and Disease Outbreak and Vaccination Reporting (DOVAR) dataset. The results showed that most herds experienced mortality and reproductive losses.…”

Systematic map of the most recent evidence (2010–2019) on ruminant production-limiting disease prevalence and associated mortality in Ethiopia

“…On these grounds, disease-associated livestock morbidity and mortality have become a highly relevant topic for international policy and research in Ethiopia, and a considerable number of research initiatives have been generated over recent years, resulting in an increasing volume of evidence. However, the evidence suggests that mortality rates are variable, and that disease causing deaths can vary greatly over geography and time ( 9 ). Although, there have been some comprehensive efforts to collate evidence for specific ruminant diseases in the country, no systematic mapping of the whole body of evidence has so far been undertaken.…”