Journal Articles

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    Probability of freedom from foot-and-mouth disease virus serotype Asia 1 in Southeast Asia, China and Mongolia
    (Elsevier B V, 2025-11-01) Wada M; Han J-H; Purevsuren B; Rinzin K; Sutar A; Abila R; Subharat S
    Foot-and-mouth disease virus (FMDV) serotype Asia 1 has not been reported in Southeast Asia, China and Mongolia between 2018 and 2024, despite the endemicity of FMD in this region and the continued circulation of serotype Asia 1 in South Asia. While vaccines against Asia 1 are still occasionally used in this region, it is unknown whether the absence of reports indicates true disease freedom or surveillance gaps. This study aimed to estimate the sensitivity of existing passive surveillance systems, and the probability of regional freedom from serotype Asia 1 across eight countries using the scenario tree approach. Two stochastic scenario tree models were developed to estimate surveillance sensitivity for FMD (any serotypes) and serotype Asia 1 specifically. Country-specific input parameters were derived from a questionnaire survey of in-country experts on FMD vaccination practices, smallholders’ behaviour, sampling protocols and diagnostic laboratory capacity. Additionally, 2010 – 2022 data on FMD clinical samples submitted and confirmed Asia 1 cases were obtained from the World Reference Laboratory for FMD. Under a design annual incidence rate of 10 % at the village level and 20 % at the animal level, estimated surveillance sensitivity for FMD ranged from 100.0 % in Mongolia and 95.9 % in China to 1.7 % in Cambodia and < 0.1 % in Myanmar. Using the effective design incidence rate with a median of 0.02 – 0.07 % at the village level and 20 % at the animal level, the probability of detecting Asia 1 was estimated to be 0.0 – 6.7 % per country and 14.5 % for the region. The estimated probability of regional freedom from Asia 1 was 53.9 % after the first year without reporting. Over years of no reporting, this probability would increase, only if an annual risk of introduction remained below 6 %. The results were most sensitive to parameters related to sampling intensity and smallholders’ behaviour, particularly in countries with high surveillance sensitivity, such as Mongolia and China. Our findings highlight the low sensitivity of passive surveillance in the region, suggesting that serotype Asia 1 may have remained undetected under the current surveillance efforts. Strengthening data collection and continued efforts in increasing surveillance intensity are essential to improving confidence in the regional freedom from serotype Asia 1.
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    Decision-making for foot-and-mouth disease control: Objectives matter.
    (2016-06) Probert WJM; Shea K; Fonnesbeck CJ; Runge MC; Carpenter TE; Dürr S; Garner MG; Harvey N; Stevenson MA; Webb CT; Werkman M; Tildesley MJ; Ferrari MJ
    Formal decision-analytic methods can be used to frame disease control problems, the first step of which is to define a clear and specific objective. We demonstrate the imperative of framing clearly-defined management objectives in finding optimal control actions for control of disease outbreaks. We illustrate an analysis that can be applied rapidly at the start of an outbreak when there are multiple stakeholders involved with potentially multiple objectives, and when there are also multiple disease models upon which to compare control actions. The output of our analysis frames subsequent discourse between policy-makers, modellers and other stakeholders, by highlighting areas of discord among different management objectives and also among different models used in the analysis. We illustrate this approach in the context of a hypothetical foot-and-mouth disease (FMD) outbreak in Cumbria, UK using outputs from five rigorously-studied simulation models of FMD spread. We present both relative rankings and relative performance of controls within each model and across a range of objectives. Results illustrate how control actions change across both the base metric used to measure management success and across the statistic used to rank control actions according to said metric. This work represents a first step towards reconciling the extensive modelling work on disease control problems with frameworks for structured decision making.