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This study adds to previous work with the finding that infection might have reached a temporal but not a spatial equilibrium and that between herd variability in PP might arise through variability in cattle age, herd size, herd purpose and the formation of new herds.
However, the non-linear model proposed by Chang et al. (2000) and the state space based models of Hwang and Salmon (2004) lead to consistent results indicating strong evidence of herd formation in all sectors.
Design prevalences of 0.1 1% of herds and 5% of animals within an infected herd were used.
Data from this period reflect a biased sub-sample of herds and sub-herds left behind.
The SSP detected a minimum of 56.25% of low AP herds (AP ≤2.0%) up to a maximum of 100% of herds with a within-herd AP ≥8.0%.
Burden of MAP infection in producer herds and veterinarian client herds were summarized and compared among types of herds.
Two types of herds were included in the case-control study: 41 farrowing herds and 28 farrow-to-finish herds.
The sample of herds constituted 20% of the Danish dairy herd population in 1993.
Inclusion of herds, clinical examination in the herds and selection of piglets was done by HK.
MSD Animal Health had no influence on the selection of herds or specific animals in the herds.
The formation of bubbles in the markets is followed by a strong herding phenomenon amongst traders [9], and the burst of these bubbles is accompanied by strong synchrony in the markets reminiscent of epileptic seizures.
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