Modeling Tuberculosis Dynamics, Detection and Control in Cattle Herds

Abstract

Epidemiological models are key tools for designing and evaluating detection and control strategies against animal infectious diseases. In France, after decades of decrease of bovine tuberculosis (bTB) incidence, the disease keeps circulating. Increasing prevalence levels are observed in several areas, where the detection and control strategy could be adapted. The objective of this work was to design and calibrate a model of the within-herd transmission of bTB. The proposed model is a stochastic model operating in discrete-time. Three health states were distinguished: susceptible, latent and infected. Dairy and beef herd dynamics and bTB detection and control programs were explicitly represented. Approximate Bayesian computation was used to estimate three model parameters from field data: the transmission parameter when animals are inside (βinside) and outside (βoutside) buildings, and the duration of the latent phase. An independent dataset was used for model validation. The estimated median was 0.43 [0.16–0.84] month−1 for βinside and 0.08 [0.01–0.32] month−1 for βoutside. The median duration of the latent period was estimated 3.5 [2]–[8] months. The sensitivity analysis showed only minor influences of fixed parameter values on these posterior estimates. Validation based on an independent dataset showed that in more than 80% of herds, the observed proportion of animals with detected lesions was between the 2.5% and 97.5% percentiles of the simulated distribution. In the absence of control program and once bTB has become enzootic within a herd, the median effective reproductive ratio was estimated to be 2.2 in beef herds and 1.7 in dairy herds. These low estimates are consistent with field observations of a low prevalence level in French bTB-infected herds.

Assessment of listing and categorisation of animal diseases within the framework of the Animal Health Law (Regulation (EU) No 2016/429): bovine tuberculosis

“…This difference was due to a lower age at culling for dairy cows than for beef cows. These low estimates were consistent with field observations of a low prevalence level in French bTB‐infected herds (Bekara et al., ).…”

“…This difference was due to a lower age at culling for dairy cows than for beef cows. These low estimates were consistent with field observations of a low prevalence level in French bTB-infected herds (Bekara et al, 2014). accompanied by the veterinary certificate and they comply with the requirements set out in the certificate.…”

“…Bekara et al. () reported that the median within‐herd transmission coefficient for housed animals in France was five times as high as in the pasture: 0.43 month −1 (0.16–0.84) and 0.08 month −1 (0.01–0.32), respectively. These estimated medians were consistent with the estimates of within‐herd transmission of bTB in Spain proposed by Alvarez et al.…”

“…In stables and barns used to house tuberculous cattle, infected droplets and particles may be constantly present in the air, presenting a hazard to susceptible animals and farm workers (Cousins, 2001). Bekara et al (2014) reported that the median within-herd transmission coefficient for housed animals in France was five times as high as in the pasture: 0.43 month À1 (0.16-0.84) and 0.08 month À1 (0.01-0.32), respectively. These estimated medians were consistent with the estimates of within-herd transmission of bTB in Spain proposed by Alvarez et al (2012b), with higher transmission coefficients in dairy herds (median 0.39 month À1 ) than in beef herds (0.19 month À1 ).…”

Estimating wildlife disease dynamics in complex systems using an Approximate Bayesian Computation framework

“…The ABC framework grew out of simple rejection algorithms that generate samples from probability distributions using large amounts of simulated data and summary statistics (Tavaré et al 1997, Pritchard et al 1999. It has since been adopted and refi ned in the fi elds of population genetics (Hamilton et al 2005 ), human epidemiology (Shriner et al 2006, Tanaka et al 2006, McKinley et al 2009 ), livestock epidemiology (Bekara et al 2014 ), and ecology (Jabot andChave 2009 , Scranton et al 2014 ). An ABC technique using sequential Monte Carlo (ABC-SMC) is more computationally effi cient than its predecessors (Sisson et al 2007, Beaumont et al 2009, Toni et al 2009, Beaumont 2010, Csilléry et al 2010, and has recently been used to investigate costs to drug resistance in Mycobacterium tuberculosis (Luciani et al 2009 ) and to estimate disease parameters for Ebola virus (McKinley et al 2009 ), a macroparasite infection of domestic cats (Drovandi and Pettitt 2011 b ), hospitalacquired staph infections (Drovandi and Pettitt 2011 a ), and Severe Acute Respiratory Syndrome, SARS (Walker et al 2010 ).…”