Data‐Driven Models of Foot‐and‐Mouth Disease Dynamics: A Review

Abstract

Summary Foot-and-mouth disease virus (FMDV) threatens animal health and leads to considerable economic losses worldwide. Progress towards minimizing both veterinary and financial impact of the disease will be made with targeted disease control policies. In order to move towards targeted control, specific targets and detailed control strategies must be defined. One approach for identifying targets is to use mathematical and simulation models quantified with accurate and fine-scale data to design and evaluate alternative control policies. Nevertheless, published models of FMDV vary in modeling techniques and resolution of data incorporated. In order to determine which models and data sources contain enough detail to represent realistic control policy alternatives, we performed a systematic literature review of all FMDV dynamical models that use host data, disease data, or both data types. For the purpose of evaluating modeling methodology, we classified models by control strategy represented, resolution of models and data, and location modeled. We found that modeling methodology has been well developed to the point where multiple methods are available to represent detailed and contact-specific transmission and targeted control. However, detailed host and disease data needed to quantify these models are only available from a few outbreaks. To address existing challenges in data collection, novel data sources should be considered and integrated into models of FMDV transmission and control. We suggest modeling multiple endemic areas to advance local control, global control, and better understand FMDV transmission dynamics. With incorporation of additional data, models can assist with both the design of targeted control and identification of transmission drivers across geographic boundaries.

Modeling Dynamic Human Behavioral Changes in Animal Disease Models: Challenges and Opportunities for Addressing Bias

“…Since the seminal application of infectious disease models to the 2001 foot-and-mouth disease (FMD) outbreak in the United Kingdom (UK), the number of published modeling studies for livestock diseases has increased dramatically ( 1 , 2 ). These models can be useful tools for evaluating the efficacy of different disease control strategies especially in situations where it may not be ethically justifiable or where it may be too time consuming and expensive to perform research studies in the real world.…”

Parameter Values for Epidemiological Models of Foot-and-Mouth Disease in Swine

“…A common approach to quantify parameter values is to use existing disease data. For instance, a recent review of data-driven models of FMD revealed that data from 12 different epidemics have been used in models and that more than half used data from the 2001 UK epidemic ( 24 ), where pigs were not largely involved. However, transmission characteristics of FMD infection are influenced by biological processes specific to the strain of FMD virus, host, and environmental factors, such as the rate of contact ( 17 , 25 ) and variations of parameter values, associated with these factors should be considered.…”

“…While the inoculation of donor animals is essential to reliably produce infectious animals with clinical disease, using the time course of disease in these animals to estimate the latent period is not appropriate as direct inoculation evades the host first line of defenses against infection ( 21 ). Current studies of FMD in swine suggest that initial virus entry occurs at the lymphoid tissues of the pharyngeal region followed by low-level viremia, then replication and development of vesicles in epithelial tissues ( 17 , 24 ). Much greater amplification of the virus occurs in the epithelial cells leading to a substantially greater, detectable level of viremia in the pig ( 26 , 27 ).…”

Multi-scale dynamics of infectious diseases

“…R0 in cattle has been estimated between 2.5 and 73 [6][7][8][9], despite a very brief mean infectious period of 1.7 days [10]. This capacity for explosive spread of FMD at multiple spatial scales has stimulated interest in multiscale disease dynamic models focused on theoretical FMD outbreaks in naive host populations [11]. These studies typically use data from past FMD outbreaks and laboratory experiments to parametrize models that predict disease spread at farm to regional and national scales, and evaluate interventions aimed at limiting transmission and the risk of major epidemics [7,[12][13][14][15].…”