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Development of a Novel Rabies Simulation Model for Application in a Non-endemic Environment.

Dürr S, Ward MP - PLoS Negl Trop Dis (2015)

Bottom Line: Mathematical and simulation disease models are useful tools to provide insights on the most effective control strategies and to inform policy decisions.Illustrative simulations produced plausible results with epidemic characteristics expected for rabies outbreaks in disease free regions (mean R0 1.7, epidemic peak 97 days post-incursion, vaccination as the most effective response strategy).Systematic sensitivity analysis identified that model outcomes were most sensitive to seven of the 30 model parameters tested.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Veterinary Science, The University of Sydney, Camden, New South Wales, Australia.

ABSTRACT
Domestic dog rabies is an endemic disease in large parts of the developing world and also epidemic in previously free regions. For example, it continues to spread in eastern Indonesia and currently threatens adjacent rabies-free regions with high densities of free-roaming dogs, including remote northern Australia. Mathematical and simulation disease models are useful tools to provide insights on the most effective control strategies and to inform policy decisions. Existing rabies models typically focus on long-term control programs in endemic countries. However, simulation models describing the dog rabies incursion scenario in regions where rabies is still exotic are lacking. We here describe such a stochastic, spatially explicit rabies simulation model that is based on individual dog information collected in two remote regions in northern Australia. Illustrative simulations produced plausible results with epidemic characteristics expected for rabies outbreaks in disease free regions (mean R0 1.7, epidemic peak 97 days post-incursion, vaccination as the most effective response strategy). Systematic sensitivity analysis identified that model outcomes were most sensitive to seven of the 30 model parameters tested. This model is suitable for exploring rabies spread and control before an incursion in populations of largely free-roaming dogs that live close together with their owners. It can be used for ad-hoc contingency or response planning prior to and shortly after incursion of dog rabies in previously free regions. One challenge that remains is model parameterisation, particularly how dogs' roaming and contacts and biting behaviours change following a rabies incursion in a previously rabies free population.

No MeSH data available.


Related in: MedlinePlus

Summary of model outputs for 6000 repetitions including results from all three control strategies in both regions (1000 repetitions for each scenario).(A) Frequency distribution of the basic reproductive ratio R0, (B) frequency distribution of the day of the epidemic peak and (C) number of newly infected dogs at the day of the epidemic peak.
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pntd.0003876.g005: Summary of model outputs for 6000 repetitions including results from all three control strategies in both regions (1000 repetitions for each scenario).(A) Frequency distribution of the basic reproductive ratio R0, (B) frequency distribution of the day of the epidemic peak and (C) number of newly infected dogs at the day of the epidemic peak.

Mentions: The number of secondary cases was reported for every rabid dog over the duration of the outbreak. From these records, the basic reproductive ratio R0 was calculated and defined as the mean number of secondary cases for dogs becoming infectious within the first phase–i.e. up to its peak–of an epidemic. The peak of the epidemic is defined as the day with the highest number of newly infectious animals over the entire outbreak. R0 ranged from 0−6.1 (median 1.8) for RV, 0−6.1 (median 1.7) for RC and 0−5.7 (median 1.7) for MB (S9 Fig) with an overall median of 1.7 (Fig 5A). The epidemic peak was reached on average after 93 days (Fig 5B) with a mean of 17 newly infected dogs (Fig 5C). The number of secondary cases derived from each index dog was highly variable and ranged from 0 to 79 (median of 25) for NPA and 4 to 106 (40) for Elcho Island. Over the duration of the outbreak, the effective reproductive ratio Rt and the number of dogs in the susceptible population decreased in a wave pattern (S10 Fig). The value of 1 for mean Rt is reached during the second or third wave. This reflects that Rt depends on the dogs remaining in the population and finally the outbreak dies out because there are no susceptible dogs left that are close enough to the infectious dogs.


Development of a Novel Rabies Simulation Model for Application in a Non-endemic Environment.

Dürr S, Ward MP - PLoS Negl Trop Dis (2015)

Summary of model outputs for 6000 repetitions including results from all three control strategies in both regions (1000 repetitions for each scenario).(A) Frequency distribution of the basic reproductive ratio R0, (B) frequency distribution of the day of the epidemic peak and (C) number of newly infected dogs at the day of the epidemic peak.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4482682&req=5

pntd.0003876.g005: Summary of model outputs for 6000 repetitions including results from all three control strategies in both regions (1000 repetitions for each scenario).(A) Frequency distribution of the basic reproductive ratio R0, (B) frequency distribution of the day of the epidemic peak and (C) number of newly infected dogs at the day of the epidemic peak.
Mentions: The number of secondary cases was reported for every rabid dog over the duration of the outbreak. From these records, the basic reproductive ratio R0 was calculated and defined as the mean number of secondary cases for dogs becoming infectious within the first phase–i.e. up to its peak–of an epidemic. The peak of the epidemic is defined as the day with the highest number of newly infectious animals over the entire outbreak. R0 ranged from 0−6.1 (median 1.8) for RV, 0−6.1 (median 1.7) for RC and 0−5.7 (median 1.7) for MB (S9 Fig) with an overall median of 1.7 (Fig 5A). The epidemic peak was reached on average after 93 days (Fig 5B) with a mean of 17 newly infected dogs (Fig 5C). The number of secondary cases derived from each index dog was highly variable and ranged from 0 to 79 (median of 25) for NPA and 4 to 106 (40) for Elcho Island. Over the duration of the outbreak, the effective reproductive ratio Rt and the number of dogs in the susceptible population decreased in a wave pattern (S10 Fig). The value of 1 for mean Rt is reached during the second or third wave. This reflects that Rt depends on the dogs remaining in the population and finally the outbreak dies out because there are no susceptible dogs left that are close enough to the infectious dogs.

Bottom Line: Mathematical and simulation disease models are useful tools to provide insights on the most effective control strategies and to inform policy decisions.Illustrative simulations produced plausible results with epidemic characteristics expected for rabies outbreaks in disease free regions (mean R0 1.7, epidemic peak 97 days post-incursion, vaccination as the most effective response strategy).Systematic sensitivity analysis identified that model outcomes were most sensitive to seven of the 30 model parameters tested.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Veterinary Science, The University of Sydney, Camden, New South Wales, Australia.

ABSTRACT
Domestic dog rabies is an endemic disease in large parts of the developing world and also epidemic in previously free regions. For example, it continues to spread in eastern Indonesia and currently threatens adjacent rabies-free regions with high densities of free-roaming dogs, including remote northern Australia. Mathematical and simulation disease models are useful tools to provide insights on the most effective control strategies and to inform policy decisions. Existing rabies models typically focus on long-term control programs in endemic countries. However, simulation models describing the dog rabies incursion scenario in regions where rabies is still exotic are lacking. We here describe such a stochastic, spatially explicit rabies simulation model that is based on individual dog information collected in two remote regions in northern Australia. Illustrative simulations produced plausible results with epidemic characteristics expected for rabies outbreaks in disease free regions (mean R0 1.7, epidemic peak 97 days post-incursion, vaccination as the most effective response strategy). Systematic sensitivity analysis identified that model outcomes were most sensitive to seven of the 30 model parameters tested. This model is suitable for exploring rabies spread and control before an incursion in populations of largely free-roaming dogs that live close together with their owners. It can be used for ad-hoc contingency or response planning prior to and shortly after incursion of dog rabies in previously free regions. One challenge that remains is model parameterisation, particularly how dogs' roaming and contacts and biting behaviours change following a rabies incursion in a previously rabies free population.

No MeSH data available.


Related in: MedlinePlus