Predicting fadeout versus persistence of paratuberculosis in a dairy cattle herd for management and control purposes: a modelling study

Abstract

Epidemiological models enable to better understand the dynamics of infectious diseases and to assess ex-ante control strategies. For Mycobacterium avium subsp. paratuberculosis (Map), possible transmission routes have been described, but Map spread in a herd and the relative importance of the routes are currently insufficiently understood to prioritize control measures. We aim to predict early after Map introduction in a dairy cattle herd whether infection is likely to fade out or persist, when no control measures are implemented, using a modelling approach. Both vertical transmission and horizontal transmission via the ingestion of colostrum, milk, or faeces present in the contaminated environment were modelled. Calf-to-calf indirect transmission was possible. Six health states were represented: susceptible, transiently infectious, latently infected, subclinically infected, clinically affected, and resistant. The model was partially validated by comparing the simulated prevalence with field data. Housing facilities and contacts between animals were specifically considered for calves and heifers. After the introduction of one infected animal in a naive herd, fadeout occurred in 66% of the runs. When Map persisted, the prevalence of infected animals increased to 88% in 25 years. The two main transmission routes were via the farm's environment and in utero transmission. Calf-to-calf transmission was minor. Fadeout versus Map persistence could be differentiated with the number of clinically affected animals, which was rarely above one when fadeout occurred. Therefore, early detection of affected animals is crucial in preventing Map persistence in dairy herds.

Characteristics of the spatio-temporal network of cattle movements in France over a 5-year period

“…In such a case, local transmission due to within commune interactions could be considered as a homogeneous mixing process and the commune level network becomes valuable. For diseases mainly spreading through animal movements (such as paratuberculosis (Marcé et al, 2011), and bovine viral diarrhoea (Courcoul and Ezanno, 2010)), holding based networks should be preferred. Second, the degree correlation is negative at the holding level, whereas it is positive at the commune level.…”

Evaluation of testing strategies to identify infected animals at a single round of testing within dairy herds known to be infected with Mycobacterium avium ssp. paratuberculosis

“…The Marcé model, which generated input data for the current model, was used to simulate the number of animals by age class and stage of Continued infection in small and medium herds. It was assumed that no on-farm MAP controls were in place, with the potential for rapid within-herd transmission and high within-herd prevalence some years after initial MAP introduction (Marcé et al, 2011a;also Figure 1 and Table 3). We acknowledge that the figures are higher than often reported (Pozzato et al, 2011;Raizman et al, 2011), which may be due to ongoing interventions that are either JD-specific or that inadvertently control JD.…”

“…As outlined by Nielsen and Toft (2008) Marcé et al (2011a), this included the health states of susceptible and resistant. Animals were identifiable across 5 age classes, including unweaned calves (<10 wk of age), weaned calves (from weaning to 1 yr of age), young heifers (from 1 yr to first service), reproductive heifers (from first service to first calving), and cows (from parity 1 to ≥5).…”

“…After the introduction of one infected animal into a naïve herd, fadeout in the Marcé model occurred in approximately 66% of the runs (Marcé et al, 2011a). Therefore, analyses at each period were restricted to those iterations where MAP prevalence was nonzero.…”

The Johne paradigm: From detection to management to treatment

“…Herd management systems have been implemented in several countries around the world, all with the sole purpose of identifying MAP-infected animals to remove or segregate such individuals from the herd to lower the herd level bacterial burden to a manageable or undetectable level. [6][7][8][9][10][11] Herd management systems enacted in recent years have always had two commonalities: (a) the lack of a reliable diagnostic test used to determine the presence of MAP and (b) the inability to effectively determine the infected animal's corresponding disease level. Both of these steps are imperative in determining the overall health and well-being of a herd.…”