Assessing the delay to detection and the size of the outbreak at the time of detection of incursions of foot and mouth disease in Australia

East, I.J.; Martin, Peter; Langstaff, I.; Iglesias, R.M.; Sergeant, E.; Garner, M. G.

doi:10.1016/j.prevetmed.2015.12.005

Cited by 31 publications

(27 citation statements)

References 19 publications

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“…For Australia, the median time from first introduction to reporting was 17 days (range 9–89), and for New Zealand, the median time to detection was 13 days. A previous Australian study found considerable regional variability in the probability that an individual infected farm would report suspect FMD (24, 49). Recent experience of outbreaks of FMD in non-endemic countries indicate that it can take up to 3 weeks after introduction of the virus to the primary farm before the disease is recognized (40, 50–52).…”

Section: Discussionmentioning

confidence: 99%

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

Garner¹,

East²,

Stevenson

et al. 2016

Front. Vet. Sci.

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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.

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Section: Discussionmentioning

confidence: 99%

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

Garner¹,

East²,

Stevenson

et al. 2016

Front. Vet. Sci.

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“…For example, poliovirus is infective at pH values of 3.0, while FMDV is labile below pH values of 6.0 (Racaniello, 2013). Additionally, while both, poliovirus and FMDV have been shown to persist longer when the virus was inoculated onto a faecal media, and conditions in TA B L E 1 This table provides references by grouping for current models used for strategic policy development and studies that were either removed from further analysis or included for the full statistical analysis References Group # of Studies (Andel, 2018;Dórea, Nöremark, Widgren, & Frössling, 2017;East et al, 2016;Gale et al, 2015;Garner & Beckett, 2005;Harvey et al, 2007;Hayama, Yamamoto, Kobayashi, Muroga, & Tsutsui, 2013;Keeling et al, 2001;SANSON et al, 2011;Stevenson et al, 2013;Tildesley & Ryan, 2012;Traulsen, Rave, Teuffert, & Krieter, 2011) Current Policy Models - (Barlow, 1972;Barlow & Donaldson, 1973;Donaldson, 1972;Donaldson & Ferris, 1975) Removed 4 (Alexandersen et al, 2002;Bedson et al, 1927;Bøtner & Belsham, 2012;Donaldson et al, 1970;Eisner & McVicar, 1980;Grzitdnov, 1957;Hyslop, 1965;Kindiakov, 1960;McColl et al, 1995;Nauryzbaev, 1966;Olitsky et al, 1928;Pacheco et al, 2017;Rozov, 1966;Sellers & Parker, 1969;Shil'nikov, 1959;Wagener, 1928) Included 16…”

Section: The Influence Of Environmental Factors On Viral Survivalmentioning

confidence: 99%

Environmental persistence of foot‐and‐mouth disease virus applied to endemic regions

Mielke

Garabed

2019

Transbound Emerg Dis

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The consequences of foot‐and‐mouth disease impact regional economies and food security through animal mortality and morbidity, trade restrictions and burdens to veterinary infrastructure. Despite efforts to control the disease, some regions, mostly in warmer climates, persistently report disease outbreaks. Consequently, it is necessary to understand how environmental factors influence transmission, of this economically devastating disease. Extensive research covers basic aetiology and transmission potential of livestock and livestock products for foot‐and‐mouth disease virus (FMDV), with a subset evaluating environmental survival. However, this subset, completed in the early to mid‐20th century in Northern Europe and the United States, is not easily generalized to today's endemic locations. This review uncovered 20 studies, to assess current knowledge and analyse the effects of environmental variables on FMDV survival, using a Cox proportional hazards (Coxph) model. However, the dataset is limited, for example pH was included in three studies and only five studies reported both relative humidity (RH) and temperature. After dropping pH from the analysis, our results suggest that temperature alone does not describe FMDV survival; instead, interactions between RH and temperature have broader impacts across various conditions. For instance, FMDV is expected to survive longer during the wet season (survival at day 50 is ~90% at 16°C and 86% RH) versus the dry season (survival at day 50 approaches 0% at 16°C and 37.5% RH) or comparatively in the UK versus the Southwestern United States. Additionally, survival on vegetation topped 70% on day 75 when conditions exceeded 20°C with high RH (86%), drastically higher than the survival on inanimate surfaces at the same temperature and RH (~0%). This is important in tropical regions, where high temperatures can persist throughout the year, but RH varies. Therefore, parameter estimates, for disease modelling and control in endemic areas, require environmental survival data from a wider range of conditions.

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“…Mathews ( 51 ) suggested that an incursion of FMD into Australia would not be readily detected, and identified these factors as contributing to the delayed detection of an FMD outbreak. Supporting this suggestion, modeling studies estimated an expected time to FMD detection after being introduced into the country of 22–47 days ( 53 , 56 ).…”

Section: Discussionmentioning

confidence: 91%

“…According to results from these assessments, once FMD has been introduced into a piggery, the most likely pathway of spread is through contaminated fomites ( Scenario 3 ). Spread of FMD through contaminated vehicles, equipment or clothing with poor or absent appropriate disinfection has been reported as an important pathway of FMD spread from infected properties ( 15 , 52 , 53 ). Spread through this pathway is estimated less likely to occur among small-scale piggeries selling informally due to the low frequency of animal and vehicle movements and the non-use of external staff in these properties compared to other piggeries.…”

Section: Discussionmentioning

confidence: 99%

“…By contrast, among small-scale pig producers selling at saleyards and abattoirs pig movements off farm are not as frequent as those among large-scale pig producers. This scenario was considered independent of the farmer detecting the infection, as movement of contaminated fomites could occur before detection of clinical signs occurs, given shedding of the virus could start during the pre-clinical phase of the disease ( 15 , 53 ). It could be argued that the earlier FMD is detected the less likely the virus would spread through fomites.…”

Section: Discussionmentioning

confidence: 99%

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A Comparative Assessment of the Risks of Introduction and Spread of Foot-and-Mouth Disease among Different Pig Sectors in Australia

Hernández‐Jover

Schembri

Holyoake³

et al. 2016

Front. Vet. Sci.

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Small-scale pig producers are believed to pose higher biosecurity risks for the introduction and spread of exotic diseases than commercial pig producers. However, the magnitude of these risks is poorly understood. This study is a comparative assessment of the risk of introduction and spread of foot-and-mouth disease (FMD) through different sectors of the pig industry: (1) large-scale pig producers; (2) small-scale producers (<100 sows) selling at saleyards and abattoirs; and (3) small-scale producers selling through informal means. An exposure and consequence assessments were conducted using the World Organization for Animal Health methodology for risk analysis, assuming FMD virus was introduced into Australia through illegal importation of infected meat. A quantitative assessment, using scenario trees and Monte Carlo stochastic simulation, was used to calculate the probabilities of exposure and spread. Input data for these assessments were obtained from a series of data gathering exercises among pig producers, industry statistics, and literature. Findings of this study suggest there is an Extremely low probability of exposure (8.69 × 10−6 to 3.81 × 10−5) for the three sectors of the pig industry, with exposure through direct swill feeding being 10–100 times more likely to occur than through contact with infected feral pigs. Spread of FMD from the index farm is most likely to occur through movement of contaminated fomites, pigs, and ruminants. The virus is more likely to spread from small-scale piggeries selling at saleyards and abattoirs than from other piggeries. The most influential factors on the spread of FMD from the index farm is the ability of the farmer to detect FMD, the probability of FMD spread through contaminated fomites and the presence of ruminants on the farm. Although small-scale producers selling informally move animals less frequently and do not use external staff, movement of pigs to non-commercial pathways could jeopardize animal traceability in the event of a disease outbreak. This study suggests that producers’ awareness on and engagement with legislative and industry requirements in relation to biosecurity and emergency animal disease management needs to be improved. Results from this study could be used by decision-makers to prioritize resource allocation for improving animal biosecurity in the pig industry.

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Assessing the delay to detection and the size of the outbreak at the time of detection of incursions of foot and mouth disease in Australia

Cited by 31 publications

References 19 publications

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

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

Environmental persistence of foot‐and‐mouth disease virus applied to endemic regions

A Comparative Assessment of the Risks of Introduction and Spread of Foot-and-Mouth Disease among Different Pig Sectors in Australia

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