Controlling bovine paratuberculosis at a regional scale: Towards a decision modelling tool

Abstract

Johne's disease (paratuberculosis), a worldwide enzootic disease of cattle caused by Mycobacterium avium subsp. paratuberculosis (Map), mainly introduced into farms by purchasing infected animals, has a large economic impact for dairy producers. Since diagnostic tests used in routine are poorly sensitive, observing Map spread in the field is hardly possible, whereas there is a need for evaluating control strategies. Our objective was to provide a modelling framework to compare the efficacy of regional control strategies combining internal biosecurity measures and testing of traded animals, against Map spread in a metapopulation of dairy cattle herds. We represented 12,857 dairy herds located in Brittany (France), based on data from 2005 to 2013, used to calibrate herd sizes and demographic rates and to define trade events in a multiscale model of Map infection dynamics. By clustering and categorical descriptive analysis of intensive simulations of this model, based on a numerical experimental design, a large panel of control measures was explored. Their efficacy was assessed on model outputs such as the prevalence and probability of extinction at the metapopulation level. In addition, we proposed a scoring for the effort required to implement control measures and prioritized control strategies based on their theoretical epidemiological efficacy. Our results clearly indicate that eradication cannot be achieved on the mid term using available control measures. However, we identified relevant combinations of measures that lead to the control of Map spread with realistic level of implementation and coverage. The study highlights the challenge of controlling paratuberculosis in an endemically infected region as related to the poor test characteristics and frequent trade movements. Our model lays the foundations for a flexible and efficient tool to help collective animal health managers in defining relevant control strategies at a regional scale, accounting for local specificities in terms of contact network and farms' characteristics.

Control measures to prevent the increase of paratuberculosis prevalence in dairy cattle herds: an individual-based modelling approach

“…If this control measure was not applied, the probability of stabilizing herd status over time was very low. Similarly, it was known that implementing a test-and-cull strategy alone, even with considerable effort, was not sufficient to prevent a degradation of herd status, as shown in previous modelling studies [ 33 , 40 , 43 ]. Nevertheless, it is not always possible to modify calf exposure on farms because it can involve expensive changes in farm structure (an additional building), that most farmers cannot afford.…”

“…Nevertheless, if Map can be reintroduced into herds, e.g. through animal purchases [ 39 , 40 ], such herds would be expected to rapidly have a higher prevalence. Control measures should therefore be implemented in herds with a high probability of being uninfected but located in an infected region.…”

Implications of Cattle Trade for the Spread and Control of Infectious Diseases in Slovenia

“…When assessing the impact of paratuberculosis, its potential for spreading and efficacy of different surveillance and control measures, the problems of the lack of empirical data and scarce resources can be overcome to a certain extent by the use of different mathematical and computational methods. In the case of paratuberculosis, these methods were used to study: the disease dynamics at the herd level (23)(24)(25), between-herd transmission and spread potential (11,26), evaluation of the surveillance systems and control measures (27)(28)(29), and assessment of economic consequences of the disease and control measures (30)(31)(32)(33)(34).…”

Neighbourhood contacts and trade movements drive the regional spread of bovine viral diarrhoea virus (BVDV)

“…In this context, modelling has been proven as an efficient approach to investigate the spread mechanisms of pathogens and to assess the impact of control strategies (e.g. [14] for bovine tuberculosis; [15] for bluetongue in cattle and sheep; [16] for bovine paratuberculosis). This approach is complementary to observations especially when sufficient biological information is not available or when field studies are difficult to perform.…”