Quantitative risk assessment of Cryptosporidium species infection in dairy calves.
Cryptosporidium parvum is a zoonotic protozoan that infects many different mammals including cattle and humans. Cryptosporidiosis has become a concern for dairy producers because of the direct losses due to calves not performing well and the potential for environmental contamination with C. parvum. Identifying modifiable control points in the dynamics of infection in dairy herds will help identify management strategies that mitigate its risk. The quantitative risk assessment approach provides estimates of the risk associated with these factors so that cost-effective strategies can be implemented. Using published data from epidemiologic studies and a stochastic approach, we modeled the risk that C. parvum presents to dairy calves in 2 geographic areas: 1) the New York City Watershed (NYCW) in southeastern New York, and 2) the entire United States. The approach focused on 2 possible areas of exposure--the rearing environment and the maternity environment. In addition, we evaluated the contribution of many risk factors (e.g., age, housing, flies) to the end-state (i.e., total) risk to identify areas of intervention to decrease the risk to dairy calves. Expected risks from C. parvum in US dairy herds in rearing and maternity environments were 41.7 and 33.9%, respectively. In the NYCW, the expected risks from C. parvum in the rearing and maternity environments were 0.36 and 0.33%, respectively. In the US scenarios, the immediate environment contributed most of the risk to calves, whereas in the NYCW scenario, it was new calf infection. Therefore, within the NYCW, risk management activities may be focused on preventing new calf infections, whereas in the general US population, cleaning of calf housing would be a good choice for resource allocation. Despite the many assumptions inherent with modeling techniques, its usefulness to quantify the likelihood of risk and identify risk management areas is illustrated.
Nydam
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Department of Population Medicine and Diagnostic Science, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA.
Mohammed
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D000375:Aging; D000818:Animals; D002417:Cattle; D002418:Cattle Diseases / Q000453:epidemiology / Q000469:parasitology* / Q000635:transmission; D003457:Cryptosporidiosis / Q000453:epidemiology / Q000635:transmission / Q000662:veterinary*; D016785:Cryptosporidium parvum / Q000235:genetics; D003612:Dairying / Q000379:methods; D004777:Environment; D050456:Fomites / Q000662:veterinary; D006799:Housing, Animal; D016015:Logistic Models; D009519:New York City; D033661:Oocysts; D011336:Probability; D012307:Risk Factors; D012621:Seasons; D014481:United States; D014871:Water Microbiology; D014886:Weaning