The use of movement data and network models to measure the effectiveness of control strategies for foot-and-mouth disease in swine

Abstract

Foot-and-mouth disease has been considered a significant epidemic threat to livestock since the sixteenth century, hindering animal health and leading to direct and indirect economic losses through treatment, decreased productivity, trade restrictions, and disease control programs. The disease is caused by infection with foot-and-mouth disease virus (FMDV), which belongs to the Aphthovirus genus and the family Picornavirdae. There are several main serotypes circulating throughout the world, with numerous subtypes creating challenges for global eradication. In the event of a of foot-and-mouth disease (FMD) incursion into an FMD-free country, response strategies are required to control, contain and eradicate the pathogen as efficiently as possible. Simulation models have often been used to test the effectiveness and efficiency of alternative control strategies to mitigate the spread of infectious animal diseases and have contributed greatly to advancements in our understanding of disease transmission. However, quantitative values on the duration of the stages of FMD infection, within-farm transmission dynamics, and understanding between-farm movement patterns are all essential components in using simulation models in livestock populations. In this thesis, we quantified values associated with the duration of the stages of FMD infection (latent period, subclinical period, incubation period, and duration of infection), probability of transmission (within-herd and between-herd via spatial spread), and time to the diagnosis of a vesicular disease within a herd using a meta-analysis of peer-reviewed literature and expert opinion. We then assessed the impact of farm structure (different barns or rooms for breeding and gestation, farrowing, nursery, and finishing) and demography (piglet births and deaths, and animal movement within and off of the farm) by testing the impact of assuming a homogeneous mixing/closed population, a common assumption for within-farm models of highly contagious diseases of swine, such as foot-and-mouth disease (FMD), on predictions about disease spread. Looking beyond within-farm dynamics, we described the annual movement patterns between swine farms in three production systems of the United States and identified farms that may be targeted to increase the efficacy of infectious disease control strategies. We then used the results from the within-farm model and analysis of movement patterns to understand the impact of using empirical movement data compared to simulated movement data and compared targeted control strategies using metrics of the movement data to control strategies that are based on geographical factors such as zones and rings. The results worth highlighting from of our investigations include the following: Chapter 2: When quantifying the duration of the stages of FMD infection in swine, we found that the latent period and the incubation period ranged from 1 to 7 days and 1 to 9 days, respectively. Furthermore, we found that distribution of those values is dependent on the strain of FMDV, in which some strains have a shorter latent period and incubation period than others, which should be considered when modeling FMD transmission. Chapter 3: In this chapter, we incorporated farm structure and demography in to the within-herd model and observed transmission dynamics that differed in the latter portion of an outbreak in certain conditions. Specifically, we observed that farm structure and demography, which were included in the farrow to finish and farrow to wean farms, resulted in FMD virus persistence within the population, which can have significant impacts on between-farm spread. Chapter 4: Through our analysis of empirical movement data, we showed that targeting farms based on a metric that captured the temporal sequence of movements (mean infection potential), substantially reduced the potential for transmission of an infectious pathogen in the contact network and performed consistently well across production systems. This result highlights the importance of detailed movement data in understanding potential disease spread within production systems. Chapter 5: In this chapter we modeled the impact of alternative control strategies on between-farm transmission of FMD, we saw that control strategies, which preemptively targeted specific farms based on their spatial network, reduced the number of infected farms, duration of the epidemic, number of vaccinated farms, and the number of culled farms when compared to reactive scenarios that used the formation of rings and zones around infected-detected farms.