A cross sectional study was conducted from November, 2011 to April, 2012 in Adigrat, Ethiopia, with the objective of assessing the prevalence of bovine mastitis, the risk factors associated with the disease and identifying the bacteria responsible for the disease. A total of 322 cows were selected from 10 small holder dairy farms using simple random sampling method. California Mastitis Test (CMT), clinical examination of udder and teats and bacteriological examination were employed. The overall prevalence of mastitis at a cow level was 64.3% (207/322), from which 15 (31/322) and 85% (176/322) were clinical and subclinical, respectively. The quarter level prevalence of the disease was also 54% (696/1288) from which 20.5 (264/1288) and 33.5% (432/1288) were clinical and subclinical form, respectively. As compared to the others, the right hind quarters were affected with the highest infection rate (63.9%). The left hind quarters were the second with an infection rate of 59.3% followed by right front quarters (52.5%) and left front quarters (40.4%). Among the bacterial causes of bovine mastitis in the study area, Staphylococcus aureus, Echerichia coli and Streptococcus agalactiae were the major isolates with percentages of 51.7, 20.9 and 20.3, respectively. All the potential risk factors considered in this study namely, parity, age, stage of lactation and breed showed significant effects on prevalence of mastitis in the present study. The present study concludes that mastitis was a major health problem of dairy cows in the area. Hence, strategic control measures against the disease and regular surveillance measures are recommended.

This paper investigates whether or not there is a policy window for making health data ‘Findable’, ‘Accessible’ (under well-defined conditions), ‘Interoperable’ and ‘Reusable’ (FAIR) in Ethiopia. The question is answered by studying the alignment of policies for health data in Ethiopia with the FAIR Guidelines or their ‘FAIR Equivalency’. Policy documents relating to the digitalisation of health systems in Ethiopia were examined to determine their FAIR Equivalency. Although the documents are fragmented and have no overarching governing framework, it was found that they aim to make the disparate health data systems in Ethiopia interoperable and boost the discoverability and (re)usability of data for research and better decision making. Hence, the FAIR Guidelines appear to be aligned with the regulatory frameworks for ICT and digital health in Ethiopia and, under the right conditions, a policy window could open for their adoption and implementation.