Investment in Infectious Disease Control Capacity: The Case of a Potential Foot-and-Mouth Disease Outbreak in California

Health Economics and Policy,

Vaccination against Foot-and-mouth disease : do initial conditions affect its benefit?

When facing incursion of a major livestock infectious disease, the decision to implement a vaccination programme is made at the national level. To make this decision, governments must consider whether the benefits of vaccination are sufficient to outweigh potential additional costs, including further trade restrictions that may be imposed due to the implementation of vaccination. However, little consensus exists on the factors triggering its implementation on the field. This work explores the effect of several triggers in the implementation of a reactive vaccination-to-live policy when facing epidemics of foot-and-mouth disease. In particular, we tested whether changes in the location of the incursion and the delay of implementation would affect the epidemiological benefit of such a policy in the context of Scotland. To reach this goal, we used a spatial, premises-based model that has been extensively used to investigate the effectiveness of mitigation procedures in Great Britain. The results show that the decision to vaccinate, or not, is not straightforward and strongly depends on the underlying local structure of the population-at-risk. With regards to disease incursion preparedness, simply identifying areas of highest population density may not capture all complexities that may influence the spread of disease as well as the benefit of implementing vaccination. However, if a decision to vaccinate is made, we show that delaying its implementation in the field may markedly reduce its benefit. This work provides guidelines to support policy makers in their decision to implement, or not, a vaccination-to-live policy when facing epidemics of infectious livestock disease

Invasive Species Management: Foot-and-Mouth Disease in the U.S. Beef Industry

A conceptual bio-economic framework that integrates dynamic epidemiologicaleconomic processes was designed to analyze the effects of invasive species introduction on decision-making in a livestock sector (e.g., production and feeding). The framework integrates an epidemiological model, a dynamic livestock production model, domestic consumption, and international trade. The integrated approach captures producer and consumer responses to, and welfare outcomes of, livestock disease outbreaks, as well as alternative invasive species management policies. Scenarios of foot-and-mouth disease are simulated to demonstrate the usefulness of the framework in facilitating invasive species policy design.bio-economics, livestock, invasive species, foot-and-mouth disease, beef cattle production, Livestock Production/Industries,

Invasive Species Management: Foot-and-Mouth Disease in the U.S. Beef Industry

A conceptual bioeconomic framework that integrates dynamic epidemiological-economic processes was designed to analyze the effects of invasive species introduction on decision making in a livestock sector (e.g., production and feeding). The framework integrates an epidemiological model, a dynamic livestock production model, domestic consumption, and international trade. The integrated approach captures producer and consumer responses and welfare outcomes of livestock disease outbreaks, as well as alternative invasive species management policies. Scenarios of foot-and-mouth disease are simulated to demonstrate the usefulness of the framework in facilitating invasive species policy design.livestock, invasive species, foot-and-mouth disease, beef cattle production, Livestock Production/Industries,

Realistic assumptions about spatial locations and clustering of premises matter for models of foot-and-mouth disease spread in the United States

Spatially explicit livestock disease models require demographic data for individual farms or premises. In the U.S., demographic data are only available aggregated at county or coarser scales, so disease models must rely on assumptions about how individual premises are distributed within counties. Here, we addressed the importance of realistic assumptions for this purpose. We compared modeling of foot and mouth disease (FMD) outbreaks using simple randomization of locations to premises configurations predicted by the Farm Location and Agricultural Production Simulator (FLAPS), which infers location based on features such as topography, land-cover, climate, and roads. We focused on three premises-level Susceptible-Exposed-Infectious-Removed models available from the literature, all using the same kernel approach but with different parameterizations and functional forms. By computing the basic reproductive number of the infection (R0) for both FLAPS and randomized configurations, we investigated how spatial locations and clustering of premises affects outbreak predictions. Further, we performed stochastic simulations to evaluate if identified differences were consistent for later stages of an outbreak. Using Ripley's K to quantify clustering, we found that FLAPS configurations were substantially more clustered at the scales relevant for the implemented models, leading to a higher frequency of nearby premises compared to randomized configurations. As a result, R0 was typically higher in FLAPS configurations, and the simulation study corroborated the pattern for later stages of outbreaks. Further, both R0 and simulations exhibited substantial spatial heterogeneity in terms of differences between configurations. Thus, using realistic assumptions when de-aggregating locations based on available data can have a pronounced effect on epidemiological predictions, affecting if, where, and to what extent FMD may invade the population. We conclude that methods such as FLAPS should be preferred over randomization approaches

Is prevention better than cure? An empirical investigation for the case of avian influenza

The new EU Animal Health Strategy suggests a shift in emphasis away from control towards prevention and surveillance activities for the management of threats to animal health. The optimal combination of these actions will differ among diseases and depend on largely unknown and uncertain costs and benefits. This paper reports an empirical investigation of this issue for the case of Avian Influenza. The results suggest that the optimal combination of actions will be dependent on the objective of the decision maker and that conflict exists between an optimal strategy which minimises costs to the government and one which maximises producer profits or minimises negative effects on human health. From the perspective of minimising the effects on human health, prevention appears preferable to cure but the case is less clear for other objectives

A SPATIAL MODEL OF ANIMAL DISEASE CONTROL IN LIVESTOCK: EMPIRICAL ANALYSIS OF FOOT AND MOUTH DISEASE IN THE SOUTHERN CONE

This paper presents a multi-market model of animal disease control that extends the current literature by accounting for spatial and inter-temporal relations in both epidemiological and economic variables. The model is applied to Foot and Mouth Disease control in Argentina, Uruguay and Paraguay, but it is broadly generalizable.Research Methods/ Statistical Methods,

An Optimal Surveillance Measure Against Foot-and-Mouth Disease in the United States

Surveillance programs on farms and in the local environment provide an essential protection against the importation and spread of exotic diseases. Combined with border quarantine measures, these programs protect both consumers and producers from major health concerns and disease incursions that can potentially destroy local agricultural production and supporting industries, as well as generate substantial losses in trade and tourism. However, surveillance programs also impose costs in the form of expenditures on the surveillance program itself, along with the costs of disease management and eradication should an incursion occur. Taking border quarantine expenditures as given, this paper develops a stochastic optimal control model (with a jump-diffusion process) to determine the optimal level of surveillance activity against a disease incursion by minimizing the present value of the major direct and indirect costs of the disease, as well as the cost of the surveillance and disease management and eradication programs. The model is applied to the case of a potential entry and spread of Foot-and-Mouth Disease in the United States. Results show that current surveillance expenditures are far less than optimal.Surveillance measures, border quarantine, disease incursion and spread, Foot- and-Mouth disease, stochastic optimal control, Livestock Production/Industries, Q1, Q17, Q18,

The impact of contact tracing in clustered populations

The tracing of potentially infectious contacts has become an important part of the control strategy for many infectious diseases, from early cases of novel infections to endemic sexually transmitted infections. Here, we make use of mathematical models to consider the case of partner notification for sexually transmitted infection, however these models are sufficiently simple to allow more general conclusions to be drawn. We show that, when contact network structure is considered in addition to contact tracing, standard “mass action” models are generally inadequate. To consider the impact of mutual contacts (specifically clustering) we develop an improvement to existing pairwise network models, which we use to demonstrate that ceteris paribus, clustering improves the efficacy of contact tracing for a large region of parameter space. This result is sometimes reversed, however, for the case of highly effective contact tracing. We also develop stochastic simulations for comparison, using simple re-wiring methods that allow the generation of appropriate comparator networks. In this way we contribute to the general theory of network-based interventions against infectious disease