Epidemiological modeling for the assessment of bovine tuberculosis surveillance in the dairy farm network in Emilia-Romagna (Italy)

Background/Question/Methods

Bovine tuberculosis (bTB) caused by Mycobacterium bovis is among the major disease threats to wild and farmed animals worldwide. In order to protect livestock from bTB, most countries developed surveillance systems based on in-vivo tuberculin skin-testing (PPD) and post-mortem carcass inspection (SI).

Emilia-Romagna (ER - Northern Italy) has been bTB-free since 2007, but the effectiveness of its bTB surveillance system has not been assessed yet.

Aim of this work was to evaluate the bTB surveillance system performance in the network of 4300 ER dairy farms. We built a stochastic network model that represents both within-farm, through a Susceptible-Exposed-Infected framework, and between-farm dynamics of bTB. We estimated model parameters using data on previous epidemics (within-farm) and the national cattle movement database (between-farm). Infection dynamics were simulated under five different scenarios: current ER surveillance system based on three different components (routine PPD, exchanged cattle PPD, and SI), a hypothetical no surveillance scenario, and three additional scenarios in which one surveillance component was removed at a time. For each scenario, we ran 10000 simulations of bTB outbreaks following the introduction of a bTB-exposed individual. We ranked surveillance systems using the time required for outbreak detection and the outbreaks magnitude as measures of performance.

Results/Conclusions

The within-farm bTB basic reproduction number, R₀=5.72 (S.E.=1.997), was higher than that estimated for UK cattle herds, between 1.5 and 4.90 depending on herd size, reflecting closer contact of individuals inside indoor premises in contrast to pasture lands.

Simulations showed that the current integrated surveillance system is effective in detecting bTB in ER herds: as it is able to decrease the mean number of infected farms per outbreaks from 8.40 (S.E.=0.166) in the absence of surveillance to 1.13 (S.E.=0.004). Among the three surveillance system components, the slaughterhouse inspection and the routine on-farm testing were the most effective ones, both for mean time-to-detection and for outbreaks magnitude. On the contrary, the exchanged cattle testing was marginally effective in detecting bTB outbreaks. This outcome was unexpected, because the main route of transmission for bTB in ER is through animal movement among farms. This is due to the low density of the network, that means a low number of cattle exchanges among this network.

Our mathematical modeling approach provides to decision-makers a cost-effective tool to assess the effectiveness of the current surveillance system for the bTB in ER, by highlighting strength and weakness of the different components of the single strategies in act.