Limits...
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

Distance kernel for contact between dogs from different households.(A) The daily probability with mean (straight line) and confidence intervals (dotted lines) of two dogs having a contact depends on the distance between their homes. (B) The probability of a daily contact for dogs living 200m away from a rabid dog (vertical line in (A)) is sampled from a beta-pert distribution with the mean of the kernel function as mode and the lower and upper confidence limits as minimum and maximum. prob = probability, hh = household.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4482682&req=5

pntd.0003876.g002: Distance kernel for contact between dogs from different households.(A) The daily probability with mean (straight line) and confidence intervals (dotted lines) of two dogs having a contact depends on the distance between their homes. (B) The probability of a daily contact for dogs living 200m away from a rabid dog (vertical line in (A)) is sampled from a beta-pert distribution with the mean of the kernel function as mode and the lower and upper confidence limits as minimum and maximum. prob = probability, hh = household.

Mentions: Second, the three types of rabies transmission are simulated. This begins with transmission to susceptible dogs living in the same household as rabid dogs, which depends on the probability of contact with the rabid dog, the probability of being bitten given the contact and the probability of rabies transmission given the bite. While the default values of the first two probabilities are >80%, the rabies transmission rate is about 50% (S1 Table). Only a successfully exposed dog becomes latently infected; dogs with failed exposure remain susceptible and have the same risk of being infected the following day. Next, rabies transmission to dogs living in a different household is simulated, which depends on the distance between the rabid dog and the susceptible dog (Fig 2). The daily probability pc that a susceptible dog living i meters from the rabid dog will be contacted is beta-pert distributed with a mode ofpc(mode)=1/(1+e−(α+βi))(1)and a minimum and maximum ofpc(min,max)=1/(1+e−(α+(β±1.96βse)i)).(2)


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

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

Distance kernel for contact between dogs from different households.(A) The daily probability with mean (straight line) and confidence intervals (dotted lines) of two dogs having a contact depends on the distance between their homes. (B) The probability of a daily contact for dogs living 200m away from a rabid dog (vertical line in (A)) is sampled from a beta-pert distribution with the mean of the kernel function as mode and the lower and upper confidence limits as minimum and maximum. prob = probability, hh = household.
© Copyright Policy
Related In: Results  -  Collection

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

pntd.0003876.g002: Distance kernel for contact between dogs from different households.(A) The daily probability with mean (straight line) and confidence intervals (dotted lines) of two dogs having a contact depends on the distance between their homes. (B) The probability of a daily contact for dogs living 200m away from a rabid dog (vertical line in (A)) is sampled from a beta-pert distribution with the mean of the kernel function as mode and the lower and upper confidence limits as minimum and maximum. prob = probability, hh = household.
Mentions: Second, the three types of rabies transmission are simulated. This begins with transmission to susceptible dogs living in the same household as rabid dogs, which depends on the probability of contact with the rabid dog, the probability of being bitten given the contact and the probability of rabies transmission given the bite. While the default values of the first two probabilities are >80%, the rabies transmission rate is about 50% (S1 Table). Only a successfully exposed dog becomes latently infected; dogs with failed exposure remain susceptible and have the same risk of being infected the following day. Next, rabies transmission to dogs living in a different household is simulated, which depends on the distance between the rabid dog and the susceptible dog (Fig 2). The daily probability pc that a susceptible dog living i meters from the rabid dog will be contacted is beta-pert distributed with a mode ofpc(mode)=1/(1+e−(α+βi))(1)and a minimum and maximum ofpc(min,max)=1/(1+e−(α+(β±1.96βse)i)).(2)

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