A Data-driven Individual-based Model of Infectious Disease in Livestock Operation: A Validation Study for Paratuberculosis

Abstract

24Chronic livestock diseases cause large financial loss and affect the animal health and welfare. 25Controlling these diseases mostly requires precise information on both individual animal and 26 population dynamics to inform farmer's decision. Mathematical models provide opportunities to 27 test different control and elimination options rather implementing them in real herds, but these 28 models require valid parameter estimation and validation. Fitting these models to data is a 29 difficult task due to heterogeneities in livestock processes. In this paper, we develop an 30 infectious disease modeling framework for a livestock disease (paratuberculosis) that is caused 31 by Mycobacterium avium subsp. paratuberculosis (MAP). Infection with MAP leads to reduced 32 milk production, pregnancy rates, and slaughter value and increased culling rates in cattle and 33 causes significant economic losses to the dairy industry in the US. These economic effects are 34 particularly important motivations in the control and elimination of MAP. In this framework, an 35 individual-based model (IBM) of a dairy herd was built and a MAP infection was integrated on 36 top of it. Once the model produced realistic dynamics of MAP infection, we implemented an 37 evaluation method by fitting it to data from three dairy herds from the Northeast region of the 38 US. The model fitting exercises used least-squares and parameter space searching methods to 39 obtain the best-fitted values of selected parameters. The best set of parameters were used to 40 model the effect of interventions. The results show that the presented model can complement 41 real herd statistics where the intervention strategies suggested a reduction in MAP but no 42 elimination was observed. Overall, this research not only provides a complete model for MAP 43 infection dynamics in a cattle herd, but also offers a method for estimating parameter by fitting 44 IBM models.45 46 47 48 Chronic livestock diseases like paratuberculosis (PTB) and bovine tuberculosis (bTB) are 49 commonly reported worldwide (1,2). Bovine TB is caused by the pathogen Mycobacterium bovis 50 (M. bovis) while PTB is caused by Mycobacterium avium subsp. paratuberculosis (MAP). In the 51UK, bTB has been spreading over the last two decades, putatively due to the presence of a 52 wildlife reservoir in badgers(3). In United States (US), 68% of dairy herds have apparently at least 53 one cow that is infected with MAP (4). Both diseases pose a potential threat not only to animal 54 health and production, but also to public health. Historically, bTB has been a contributor to 55 human TB cases worldwide and PTB infections in humans have been associated with an 56 increased risk of Crohn's disease in humans(5). Recently, it has been reported that these 57 diseases may induce additional collateral risks for public health due to dispensed antibiotics as 58 a treatment in some cases can potentially contribute to the spread of antibiotic resistance(6). 60In the US cattle industry, the cost of PTB was estimated at...

Who infects Whom? - Reconstructing infection chains of Mycobacterium avium ssp. paratuberculosis in an endemically infected dairy herd by use of genomic data

“…It was a closed farm for years before the start of the study and did not purchase animals during the study. Apparent herd-prevalence based on bacterial culture (faecal matter and tissues) and serology was as high as 7.6% in 2004 and decreased to 0–2.4% in 2010 (23).…”

Modeling and Simulation for Decision Support in Precision Livestock Farming

“…The degree of parameterization within data-driven simulation in research varies, affecting the flexibility of scenarios which can be modelled. Some DDS approaches use data only to estimate the model parameters (Al-Mamun et al 2018), but other studies also drive the model structure from observational data (Widgren et al 2019). Dynamic Data-Driven Simulation (DDDS) is a type of data-driven simulation which uses real-time data to detect the system model and feeds the simulation results back into the model continuously to gain more accurate and on time results.…”

“…multiscale agent based simulation of a dairy herd (Al-Mamun et al 2018). welfare ABM Data-driven (only parameters) individual-based model of infectious disease (Mostert et al 2018).…”