Should we use models to inform policy development?

Challenges to the Application of Spatially Explicit Stochastic Simulation Models for Foot-and-Mouth Disease Control in Endemic Settings: A Systematic Review

Simulation modeling has become common for estimating the spread of highly contagious animal diseases. Several models have been developed to mimic the spread of foot-and-mouth disease (FMD) in specific regions or countries, conduct risk assessment, analyze outbreaks using historical data or hypothetical scenarios, assist in policy decisions during epidemics, formulate preparedness plans, and evaluate economic impacts. Majority of the available FMD simulation models were designed for and applied in disease-free countries, while there has been limited use of such models in FMD endemic countries. This paper's objective was to report the findings from a study conducted to review the existing published original research literature on spatially explicit stochastic simulation (SESS) models of FMD spread, focusing on assessing these models for their potential use in endemic settings. The goal was to identify the specific components of endemic FMD needed to adapt these SESS models for their potential application in FMD endemic settings. This systematic review followed the PRISMA guidelines, and three databases were searched, which resulted in 1176 citations. Eighty citations finally met the inclusion criteria and were included in the qualitative synthesis, identifying nine unique SESS models. These SESS models were assessed for their potential application in endemic settings. The assessed SESS models can be adapted for use in FMD endemic countries by modifying the underlying code to include multiple cocirculating serotypes, routine prophylactic vaccination (RPV), and livestock population dynamics to more realistically mimic the endemic characteristics of FMD. The application of SESS models in endemic settings will help evaluate strategies for FMD control, which will improve livestock health, provide economic gains for producers, help alleviate poverty and hunger, and will complement efforts to achieve the Sustainable Development Goals.

Variations in seroprevalences of canine leishmaniasis: Could it be a consequence of the population structure?

Canine leishmaniasis is a parasitic disease caused by Leishmania infantum and is transmitted by Phlebotominae vectors. Despite numerous publications on the subject, some essential aspects of the epidemiology are not yet sufficiently clear. We proposed a stochastic model with the aim of identifying some important gaps in the current knowledge of leishmaniasis, such as the frequency of vector infection or a dog's life expectancy depending on their purpose and their health status. We only found that the purpose was a significant factor. Furthermore, we detected relationships among age, gender and habitat with the dogs' purposes that can affect the calculation of the overall seroprevalence of the analysed sample. The development of this model will allow us to discard potential confounding factors as gender, age, purpose or habitat.

"Wrong, but useful": negotiating uncertainty in infectious disease modelling

For infectious disease dynamical models to inform policy for containment of infectious diseases the models must be able to predict; however, it is well recognised that such prediction will never be perfect. Nevertheless, the consensus is that although models are uncertain, some may yet inform effective action. This assumes that the quality of a model can be ascertained in order to evaluate sufficiently model uncertainties, and to decide whether or not, or in what ways or under what conditions, the model should be 'used'. We examined uncertainty in modelling, utilising a range of data: interviews with scientists, policy-makers and advisors, and analysis of policy documents, scientific publications and reports of major inquiries into key livestock epidemics. We show that the discourse of uncertainty in infectious disease models is multi-layered, flexible, contingent, embedded in context and plays a critical role in negotiating model credibility. We argue that usability and stability of a model is an outcome of the negotiation that occurs within the networks and discourses surrounding it. This negotiation employs a range of discursive devices that renders uncertainty in infectious disease modelling a plastic quality that is amenable to 'interpretive flexibility'. The utility of models in the face of uncertainty is a function of this flexibility, the negotiation this allows, and the contexts in which model outputs are framed and interpreted in the decision making process. We contend that rather than being based predominantly on beliefs about quality, the usefulness and authority of a model may at times be primarily based on its functional status within the broad social and political environment in which it acts.

Uncertainties in the governance of animal disease: an interdisciplinary framework for analysis

Uncertainty is an inherent feature of strategies to contain animal disease. In this paper, an interdisciplinary framework for representing strategies of containment, and analysing how uncertainties are embedded and propagated through them, is developed and illustrated. Analysis centres on persistent, periodic and emerging disease threats, with a particular focus on cryptosporidiosis, foot and mouth disease and avian influenza. Uncertainty is shown to be produced at strategic, tactical and operational levels of containment, and across the different arenas of disease prevention, anticipation and alleviation. The paper argues for more critically reflexive assessments of uncertainty in containment policy and practice. An interdisciplinary approach has an important contribution to make, but is absent from current real-world containment policy.

Estimating front-wave velocity of infectious diseases: a simple, efficient method applied to bluetongue

Understanding the spatial dynamics of an infectious disease is critical when attempting to predict where and how fast the disease will spread. We illustrate an approach using a trend-surface analysis (TSA) model combined with a spatial error simultaneous autoregressive model (SAR_err model) to estimate the speed of diffusion of bluetongue (BT), an infectious disease of ruminants caused by bluetongue virus (BTV) and transmitted by Culicoides. In a first step to gain further insight into the spatial transmission characteristics of BTV serotype 8, we used 2007-2008 clinical case reports in France and TSA modelling to identify the major directions and speed of disease diffusion. We accounted for spatial autocorrelation by combining TSA with a SAR_err model, which led to a trend SAR_err model. Overall, BT spread from north-eastern to south-western France. The average trend SAR_err-estimated velocity across the country was 5.6 km/day. However, velocities differed between areas and time periods, varying between 2.1 and 9.3 km/day. For more than 83% of the contaminated municipalities, the trend SAR_err-estimated velocity was less than 7 km/day. Our study was a first step in describing the diffusion process for BT in France. To our knowledge, it is the first to show that BT spread in France was primarily local and consistent with the active flight of Culicoides and local movements of farm animals. Models such as the trend SAR_err models are powerful tools to provide information on direction and speed of disease diffusion when the only data available are date and location of cases.

Potential impact of introduction of foot-and-mouth disease from wild pigs into commercial livestock premises in California

OBJECTIVE

To estimate potential spread of foot-and-mouth disease (FMD) if introduced from wild pigs in California and to evaluate efficacies of various control strategies.

SAMPLE POPULATION

Data for California livestock and from hunter surveys on wild pigs in California.

PROCEDURES

A spatial, stochastic simulation model was used to simulate FMD epidemics that might occur if a dairy or beef herd were infected from contact with a wild pig. Index herd location and type were examined, in addition to different statewide movement ban (SWMB) durations, to determine their effect on extent of the epidemic.

RESULTS

Duration, number of infected premises, size of simulated outbreak, number of culled animals, and spatial distribution of infected herds resulting from the simulated outbreaks varied considerably among geographic regions, depending on index case type and location. Outbreaks beginning in the southern region of California were consistently longest, whereas those beginning in the northern region were shortest. The largest outbreaks resulted from index cases located in the southern and valley regions, whereas outbreaks were smallest when originating in the Sonoma or northern regions. For all regions, when the index herd was a dairy herd, size and duration of the outbreak were consistently reduced with implementation of an SWMB >or= 3 days.

CONCLUSIONS AND CLINICAL RELEVANCE

Introduction of FMDV from wild pigs into a dairy or beef herd could result in a large and rapidly spreading outbreak, potentially affecting large numbers of herds. Size and duration of the outbreak might be reduced with an SWMB; however, the impact is highly dependent on the index herd type and location.

The North American Animal Disease Spread Model: A simulation model to assist decision making in evaluating animal disease incursions

The North American Animal Disease Spread Model is a stochastic, spatial, state-transition simulation model for the spread of highly contagious diseases of animals. It was developed with broad international support to assist policy development and decision making involving disease incursions. User-established parameters define model behavior in terms of disease progression; disease spread by animal-to-animal contact, contact with contaminated personnel or equipment, and airborne dissemination; and the implementation of control measures such as destruction and vaccination. Resources available to implement disease control strategies, as well as the direct costs associated with these strategies, are taken into consideration. The model records a wide variety of measures of the extent of simulated outbreaks and other characteristics. The graphical interface and output visualization features also make it a useful tool for training and preparedness exercises. This model is now being used to evaluate outbreak scenarios and potential control strategies for several economically important exotic animal diseases in the United States, Canada, and elsewhere. NAADSM is freely available via the Internet at http://www.naadsm.org.