Integrated Ectoparasite Management in Dairy Animals: Detection, Forecasting, and Control Strategies for Improved Health and Productivity
Shruti Gupta *
Livestock Production and Management, Indian Veterinary Research Institute, Izatnagar, India.
*Author to whom correspondence should be addressed.
Abstract
Ectoparasites remain a major constraint on dairy animal productivity, with adverse effects on animal health and welfare, milk production, growth, fertility, hide quality, and farm profitability. Ticks, biting and nuisance flies, lice, and mites cause direct injury through blood loss, irritation, skin damage, restlessness, and reduced feeding and resting time. They also contribute to production losses by transmitting or facilitating diseases such as babesiosis, theileriosis, anaplasmosis, eye and udder infections, mange, and secondary skin conditions. The scale of this burden is illustrated by field and economic data: hard-tick infestation has been recorded in over 60% of screened dairy cattle in parts of India, close to 80% of the world's cattle are considered at risk of tick infestation, and annual losses from ticks and tick-borne diseases are estimated at USD 22-30 billion globally and about USD 787.63 million in India alone, mostly from reduced milk yield, treatment costs, and hide damage. This review summarises the major ectoparasites of dairy animals, their economic importance, the factors promoting their spread, and current approaches to detection, forecasting, and control. Climate change, acaricide resistance, intensive animal management, animal movement, poor manure and shed hygiene, and the increased use of susceptible high-yielding breeds are identified as key drivers of ectoparasite pressure. Detection methods range from visual inspection, counting, stereomicroscopy, and thermal imaging to molecular assays, biosensors, image recognition, surveillance mapping, and resistance testing. Control strategies include judicious chemical use, integrated parasite management, biological control, tick vaccines, resistant breeds, plant-based and nanoscale formulations, improved husbandry, pasture management, quarantine, and modern fly traps. Digital tools, including connected sensors, artificial intelligence, machine learning, and weather-based forecasting, can strengthen early warning and support more timely interventions. The review emphasises that durable ectoparasite management cannot rely on a single method. Locally adapted, integrated programmes, guided by monitoring and supported by farmer training, are needed to reduce production losses, limit chemical misuse, slow resistance development, and improve dairy animal health and welfare.
Keywords: Artificial intelligence, biosensors, dairy animal health, ectoparasites, forecasting models, integrated parasite management, milk productivity, precision livestock farming, tick-borne diseases, vector control