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Proceedings of the 10th International Colloquium on Paratuberculosis

Proceedings of the 10th International Colloquium on Paratuberculosis

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#218 Johne’s disease in <str<strong>on</strong>g>the</str<strong>on</strong>g> New Zealand nati<strong>on</strong>al dairy herd - an analysis <str<strong>on</strong>g>of</str<strong>on</strong>g> a decade <str<strong>on</strong>g>of</str<strong>on</strong>g><br />

dairy cow culling records<br />

Hinrich Voges<br />

LIC, New Zealand<br />

The LIC Nati<strong>on</strong>al Dairy Cow Database allows New Zealand (NZ) dairy farmers to record culling (including<br />

deaths) due to Johne’s disease (JD). Analysis <str<strong>on</strong>g>of</str<strong>on</strong>g> <str<strong>on</strong>g>the</str<strong>on</strong>g>se voluntary JD culling records over ten dairy seas<strong>on</strong>s<br />

from 1998/99 to 2007/08 reveal that approximately 8% <str<strong>on</strong>g>of</str<strong>on</strong>g> New Zealand dairy herds cull 0.5% <str<strong>on</strong>g>of</str<strong>on</strong>g> <str<strong>on</strong>g>the</str<strong>on</strong>g>ir cows with<br />

signs <str<strong>on</strong>g>of</str<strong>on</strong>g> Johne’s disease per annum. JD risks in <str<strong>on</strong>g>the</str<strong>on</strong>g> NZ dairy cow populati<strong>on</strong> have remained essentially static<br />

over that period with 0.05% reported annual incidence nati<strong>on</strong>ally.<br />

In spite <str<strong>on</strong>g>of</str<strong>on</strong>g> typically high levels <str<strong>on</strong>g>of</str<strong>on</strong>g> dairy herd and cattle movements in NZ, <str<strong>on</strong>g>the</str<strong>on</strong>g> data reveals distinct regi<strong>on</strong>al<br />

and breed differences in JD culling rates. The Northland regi<strong>on</strong> records <str<strong>on</strong>g>the</str<strong>on</strong>g> lowest level <str<strong>on</strong>g>of</str<strong>on</strong>g> Johne’s disease with<br />

2% <str<strong>on</strong>g>of</str<strong>on</strong>g> dairy herds culling less than 0.2% per annum, while <str<strong>on</strong>g>the</str<strong>on</strong>g> West Coast is <str<strong>on</strong>g>the</str<strong>on</strong>g> <strong>on</strong>ly regi<strong>on</strong> where within-herd<br />

culling rates exceed 1% am<strong>on</strong>gst herds recording JD culls. Jersey breed is associated with significantly higher<br />

risk than Friesian (RR = 4.26; p < 0.001), although it remains unclear whe<str<strong>on</strong>g>the</str<strong>on</strong>g>r this reflects differences in breed<br />

susceptibility.<br />

Forty percent <str<strong>on</strong>g>of</str<strong>on</strong>g> all JD culls and deaths occur over three m<strong>on</strong>ths in spring – coinciding with calving and<br />

<strong>on</strong>set <str<strong>on</strong>g>of</str<strong>on</strong>g> lactati<strong>on</strong>. As expected JD risks are str<strong>on</strong>gly correlated with increasing age and peak am<strong>on</strong>gst eightyear-old<br />

cows, which are almost three times as likely to succumb to Johne’s disease as three-year-old cows.<br />

#223 A stochastic and age-structured compartmental model for MAP infecti<strong>on</strong> <strong>on</strong> a US dairy<br />

herd with test-based culling interventi<strong>on</strong><br />

Zhao Lu, Ynte H Schukken, Rebecca L Smith, Yrjo T Grohn<br />

College <str<strong>on</strong>g>of</str<strong>on</strong>g> Veterinary Medicine, Cornell University, USA<br />

Modeling <str<strong>on</strong>g>of</str<strong>on</strong>g> <str<strong>on</strong>g>the</str<strong>on</strong>g> transmissi<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> MAP <strong>on</strong> dairy herds helps us understanding <str<strong>on</strong>g>the</str<strong>on</strong>g> dynamics and evaluating <str<strong>on</strong>g>the</str<strong>on</strong>g><br />

effectiveness <str<strong>on</strong>g>of</str<strong>on</strong>g> c<strong>on</strong>trol opti<strong>on</strong>s. When herd size is small, stochastic effects such as fadeout become important<br />

and stochastic modeling is necessary. To study <str<strong>on</strong>g>the</str<strong>on</strong>g> phenomena <str<strong>on</strong>g>of</str<strong>on</strong>g> highly variable prevalence and fadeout <str<strong>on</strong>g>of</str<strong>on</strong>g><br />

MAP infecti<strong>on</strong>, a stochastic compartmental model, with age structure including calves, heifers, and cows, was<br />

developed. We <str<strong>on</strong>g>the</str<strong>on</strong>g>n investigated <str<strong>on</strong>g>the</str<strong>on</strong>g> impact <str<strong>on</strong>g>of</str<strong>on</strong>g> various testing and culling strategies <strong>on</strong> <str<strong>on</strong>g>the</str<strong>on</strong>g> prevalence over<br />

time and <str<strong>on</strong>g>the</str<strong>on</strong>g> cumulative distributi<strong>on</strong> functi<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> fadeout. To incorporate <str<strong>on</strong>g>the</str<strong>on</strong>g> model parameter uncertainty and<br />

find <str<strong>on</strong>g>the</str<strong>on</strong>g> most important parameters for <str<strong>on</strong>g>the</str<strong>on</strong>g> probability <str<strong>on</strong>g>of</str<strong>on</strong>g> fadeout, we performed global parameter uncertainty<br />

and sensitivity analyses. Our results show that: (1) <str<strong>on</strong>g>the</str<strong>on</strong>g> threshold property <str<strong>on</strong>g>of</str<strong>on</strong>g> <str<strong>on</strong>g>the</str<strong>on</strong>g> reproducti<strong>on</strong> ratio, R, is generally<br />

not an accurate criteri<strong>on</strong> to determine <str<strong>on</strong>g>the</str<strong>on</strong>g> invasi<strong>on</strong> and persistence <str<strong>on</strong>g>of</str<strong>on</strong>g> MAP infecti<strong>on</strong>; (2) evaluati<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> <str<strong>on</strong>g>the</str<strong>on</strong>g><br />

effectiveness <str<strong>on</strong>g>of</str<strong>on</strong>g> testing and culling strategies based <strong>on</strong> prevalence over time and <str<strong>on</strong>g>the</str<strong>on</strong>g> cumulative distributi<strong>on</strong><br />

functi<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> fadeout is more appropriate; (3) for a farm <str<strong>on</strong>g>of</str<strong>on</strong>g> good management (low transmissi<strong>on</strong> rate), culling <str<strong>on</strong>g>of</str<strong>on</strong>g><br />

<strong>on</strong>ly high shedders based <strong>on</strong> ELISA tests is effective to eradicate MAP infecti<strong>on</strong> within 20 ~ 30 years; however,<br />

for a farm <str<strong>on</strong>g>of</str<strong>on</strong>g> poor management (high transmissi<strong>on</strong> rate), culling <str<strong>on</strong>g>of</str<strong>on</strong>g> <strong>on</strong>ly high shedders is not enough to eradicate<br />

MAP infecti<strong>on</strong> within 50 years, although <str<strong>on</strong>g>the</str<strong>on</strong>g> prevalence still decreases; (4) higher test-based culling rates<br />

for low and high shedders increase <str<strong>on</strong>g>the</str<strong>on</strong>g> probability <str<strong>on</strong>g>of</str<strong>on</strong>g> fadeout which may be important for <str<strong>on</strong>g>the</str<strong>on</strong>g> eradicati<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g><br />

MAP infecti<strong>on</strong>.<br />

191

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