Mapping the issues of Indian donkey and mule population and identify the potential intervention strategies and partners


It is evident from the literature that working equines contribute much to the sustainable development goals through supporting the livelihood of poorest families worldwide. They are considered source of employment in various sectors including agriculture, construction, tourism and mining sector. However, the contribution in enhancing the livelihood of poor and welfare issues especially in the case of donkeys and mules are under-acknowledged and neglected in the policies and development programmes due to lack of information and data to support their contribution. Efforts by various animal welfare organisations to improve the welfare of working equines have not achieved significant positive changes. There is need for one welfare approach where welfare of animals and human to be considered interlinked to each other, so change in human welfare will bring positive change in animal welfare and improved animal welfare will increase the productivity and household income.


The study will follow desktop review, qualitative and quantitative data collection methods across the regions where donkey and mule populations are relatively higher.


This study is aimed to map the issues of Indian donkey and mule population and their dependents in the broader developmental context to identify the potential institutional innovations to bring positive changes in animal and human welfare.


1) To identify the donkey and mule population, trend and their usage patterns in rural, urban and industrial development context in different regions of India. 2) To specify the communities who own the donkey and mule population in different regions of the country. Evaluate the human development indicators associated with these communities specific to different regions. 3) To identify the key challenges and opportunities that impact the welfare of human and equine populations (one health approach) in the areas where donkey and mule populations are high.