Estimating the transmission parameters of foot-and-mouth disease in Vietnam: A spatial-dynamic kernel-based model with outbreak and host data.

Foot-and-mouth disease (FMD) affects cloven-hoofed livestock and causes devastating damages to the world's economies. Being endemic in developing countries, FMD has imposed a significant threat to the FMD-freedom status in developed countries. The globally-concerted effort to eradicate FMD at its source has faced a substantial challenge of having little knowledge about how FMD spreads in developing countries. So far, FMD virus transmission parameters have been estimated based on only a dozen actual outbreak data, mostly in Europe. Meanwhile, the fundamental north-south differences in livestock production, trading, and quarantine systems have questioned the applicability of these estimates to developing countries. In this light, we aim to narrow the knowledge gap by estimating the FMD virus transmission parameters in an endemic country, Vietnam, the world's fifth- largest pork producer. We use the spatial-dynamic kernel-based approach combined with daily FMD incursion data and FMD-host census data. The estimation also considers livestock composition and livestock quantity by species, which can influence FMD transmission. In line with existing literature, we find that cattle and buffaloes have a larger influence on disease spread than pigs, and FMD transmission depends on the herd size and the distance between susceptible and infected premises. However, our findings show FMD virus can spread over a much more ample space in our case compared with those in existing literature (25 km and 50 km versus 10 km), and the kernels have much fatter tails. This difference is likely due to the weakness in biosecurity systems, poor implementation of surveillance and quarantine measures, and bad husbandry practices such as swill feeding, which are prevalent in developing countries. Thus, our estimated kernels will be helpful for Vietnam in developing suitable biosecurity measures to contain and eradicate the FMD virus. They are also highly relevant for other countries with livestock farming practices and climate conditions similar to those in Vietnam.

A cost-benefit analysis of Vietnam's 2006-2010 foot-and-mouth disease control program.

Foot-and-mouth disease (FMD) is arguably the most damaging animal disease, affecting three-quarters of the global livestock population. This paper provides a cost-benefit analysis of the first five-year program that used vaccination to contain and control FMD in an endemic country, Vietnam. Our spatial and dynamic model to simulate FMD outbreaks fully considered the distance among livestock premises, their herd sizes, and composition, all of which significantly affect FMD transmission. Our program benefit was consistently estimated due to the Law of Large Number and the design of pairing the control and treatment scenarios which allowed capturing the true benefit of each outbreak realization. The data used to monetize the program benefit were largely drawn from Vietnam's context and statistics, thus obviating the need to make many potentially undue assumptions. Meanwhile, the program costs were actual spending and allocated budget. We found that the vaccination program is highly cost-effective for Vietnam, yielding a net present value of US$136 million (in 2006 prices) over five years and a benefit-cost ratio of 5.7. Our results were robust to different assumptions about the vaccine effectiveness of the livestock unit.

Assessing biophysical and socio-economic impacts of climate change on regional avian biodiversity.

Climate change threatens biodiversity directly by influencing biophysical variables that drive species' geographic distributions and indirectly through socio-economic changes that influence land use patterns, driven by global consumption, production and climate. To date, no detailed analyses have been produced that assess the relative importance of, or interaction between, these direct and indirect climate change impacts on biodiversity at large scales. Here, we apply a new integrated modelling framework to quantify the relative influence of biophysical and socio-economically mediated impacts on avian species in Vietnam and Australia and we find that socio-economically mediated impacts on suitable ranges are largely outweighed by biophysical impacts. However, by translating economic futures and shocks into spatially explicit predictions of biodiversity change, we now have the power to analyse in a consistent way outcomes for nature and people of any change to policy, regulation, trading conditions or consumption trend at any scale from sub-national to global.

Early Decision Indicators for Foot-and-Mouth Disease Outbreaks in Non-Endemic Countries.

Disease managers face many challenges when deciding on the most effective control strategy to manage an outbreak of foot-and-mouth disease (FMD). Decisions have to be made under conditions of uncertainty and where the situation is continually evolving. In addition, resources for control are often limited. A modeling study was carried out to identify characteristics measurable during the early phase of a FMD outbreak that might be useful as predictors of the total number of infected places, outbreak duration, and the total area under control (AUC). The study involved two modeling platforms in two countries (Australia and New Zealand) and encompassed a large number of incursion scenarios. Linear regression, classification and regression tree, and boosted regression tree analyses were used to quantify the predictive value of a set of parameters on three outcome variables of interest: the total number of infected places, outbreak duration, and the total AUC. The number of infected premises (IPs), number of pending culls, AUC, estimated dissemination ratio, and cattle density around the index herd at days 7, 14, and 21 following first detection were associated with each of the outcome variables. Regression models for the size of the AUC had the highest predictive value (R2 = 0.51-0.9) followed by the number of IPs (R2 = 0.3-0.75) and outbreak duration (R2 = 0.28-0.57). Predictability improved at later time points in the outbreak. Predictive regression models using various cut-points at day 14 to define small and large outbreaks had positive predictive values of 0.85-0.98 and negative predictive values of 0.52-0.91, with 79-97% of outbreaks correctly classified. On the strict assumption that each of the simulation models used in this study provide a realistic indication of the spread of FMD in animal populations. Our conclusion is that relatively simple metrics available early in a control program can be used to indicate the likely magnitude of an FMD outbreak under Australian and New Zealand conditions.