| Literature DB >> 28301480 |
Stacey A Elmore1, Richard B Chipman2, Dennis Slate2, Kathryn P Huyvaert3, Kurt C VerCauteren1, Amy T Gilbert1.
Abstract
Rabies is an ancient viral disease that significantly impacts human and animal health throughout the world. In the developing parts of the world, dog bites represent the highest risk of rabies infection to people, livestock, and other animals. However, in North America, where several rabies virus variants currently circulate in wildlife, human contact with the raccoon rabies variant leads to the highest per capita population administration of post-exposure prophylaxis (PEP) annually. Previous rabies variant elimination in raccoons (Canada), foxes (Europe), and dogs and coyotes (United States) demonstrates that elimination of the raccoon variant from the eastern US is feasible, given an understanding of rabies control costs and benefits and the availability of proper tools. Also critical is a cooperatively produced strategic plan that emphasizes collaborative rabies management among agencies and organizations at the landscape scale. Common management strategies, alone or as part of an integrated approach, include the following: oral rabies vaccination (ORV), trap-vaccinate-release (TVR), and local population reduction. As a complement, mathematical and statistical modeling approaches can guide intervention planning, such as through contact networks, circuit theory, individual-based modeling, and others, which can be used to better understand and predict rabies dynamics through simulated interactions among the host, virus, environment, and control strategy. Strategies derived from this ecological lens can then be optimized to produce a management plan that balances the ecological needs and program financial resources. This paper discusses the management and modeling strategies that are currently used, or have been used in the past, and provides a platform of options for consideration while developing raccoon rabies virus elimination strategies in the US.Entities:
Mesh:
Year: 2017 PMID: 28301480 PMCID: PMC5354248 DOI: 10.1371/journal.pntd.0005249
Source DB: PubMed Journal: PLoS Negl Trop Dis ISSN: 1935-2727
Fig 1Current geographic distribution of rabies virus variants in the continental US and Canada.
Previously published ORV campaigns in North America and the estimated population seroprevalence in response to vaccination.
| Species Tested | Study Location | Bait Type | Flight-Line spacing (km) | Bait Density (baits/km2) | Post-Bait Seroprevalence (%) | Diagnostic Test Used | Reference |
|---|---|---|---|---|---|---|---|
| Red foxes | Eastern Ontario, Canada | ERA | 1.0–2.0 | 20 | nd | n/a | [ |
| Red foxes | Toronto, Ontario, Canada | ERA | n/a | 49–69 | 46–80 (mean = 61) | VNT, ELISA | [ |
| Red foxes | Ontario, Canada | V-RG | 0.75–1.5 | 75, 150 | 7–28 (mean = 14) | cELISA | [ |
| Gray foxes | West-central Texas, US | V-RG | 0.8 | 27–39 | 37–84 (mean = 62) | VNT | [ |
| Coyotes | South Texas, US | V-RG | 0.8 | 19–27 | 18–87 (mean = 56) | VNT | [ |
| Raccoons | Anne Arundel County, Maryland, US | V-RG | 0.5 | 75, 100 | 21–47 (mean = 33) | VNT | [ |
| Raccoons | Massachusetts, US | V-RG | n/a | 103 (uniform), 93 (targeted), 135(targeted) | 16–55 (uniform), | VNT | [ |
| Raccoons | New Jersey, US | V-RG | n/a | 64 (targeted) | 7–71 (mean = 41) | VNT | [ |
| Raccoons | Wolfe Island, Ontario, Canada | V-RG | 1.5 | 75, 150 | nd | n/a | [ |
| Raccoons | Parramore Island, Virginia, US | V-RG | n/a | 1000 | 52 | VNT | [ |
| Raccoons | Ohio, US | V-RG | 0.5 | 75, | 22, 18, 11 | VNT | [ |
| Raccoons | Maine, US | V-RG | 1.0 | 75 | 30–33, | VNT, cELISA | [ |
| Raccoons | Vermont, US | V-RG | 0.75 | 150 | 38, | VNT, cELISA | [ |
| Raccoons | Quebec, Canada | ONRAB | 0.75 | 150 | 52, | VNT, cELISA | [ |
| Raccoons | West Virginia, US | ONRAB | 0.75 | 75 | 49 | VNT | [ |
| Raccoons | New Brunswick, Canada | ONRAB | 1.0 | 75 | 75–78, | VNT, cELISA | [ |
| Skunks | Maine, US | V-RG | 1.0 | 75 | 3–11, | VNT, cELISA | [ |
| Skunks | Ontario, Canada | ONRAB | 0.25, 0.50 | 300 | 20–34 | cELISA | [ |
| Skunks | West Virginia, US | ONRAB | 0.75 | 75 | 7 | VNT | [ |
| Skunks | New Brunswick, Canada | ONRAB | 1.0 | 75 | 15–18, | VNT, cELISA | [ |
1Straight line along a ravine (unit is baits/km).
2Not determined, but apparent elimination of raccoon rabies from the island; used in conjunction with TVR and population reduction.
3Based on titers (≥5, ≥12, ≥56, respectively).
4Including only strong positives (inhibition value ≥26%).
5Including suspect and strong positives (inhibition value ≥16%).
VNT, virus neutralization test; ELISA, enzyme-linked immunosorbent assay; cELISA, competitive ELISA; nd, not determined; n/a, not applicable.
Summary of modeling approaches used to understand rabies dynamics in wildlife, conceptually structured as in Keeling and Rohani [90].
| Method | Key Features | Pros | Cons | Examples |
|---|---|---|---|---|
| • Basic compartmental models (e.g., SIR, SIS, SEIR) | • Computationally simple | • May not be biologically accurate | • Early red fox compartmental models [ | |
| • Explicit modeling of random events as part of model process/behavior | • Estimates a more accurate presentation of stochastic nature of small populations and extinction processes | • Computationally intensive | • Early models of the mid-Atlantic epizootic in raccoons [ | |
| • Application of demographic cohorts which have quantified risk of transmission or susceptibility | • May help to identify individuals, social groups, or specific behaviors that influence rabies dynamics | • Requires increased computational time and data needs for accurate parameterization | • Social network models [ | |
| • Multiple host species affect the transmission cycle | • Better understanding of multi-species (biodiversity) effects on transmission dynamics | • Increased computational time and data needs for parameterization | • Raccoon/skunk spillover model [ | |
| • Transmission and/or susceptibility of host has pronounced seasonality, within and/or across years | • Better understanding of how life history impacts transmission dynamics (e.g. mating, migration, parturition) | • Increased computational time and data needs for parameterization | • Early red fox rabies models with seasonality [ | |
| • Metapopulation models | • Focus on real landscapes of disease spread | • Increased computational time | • Extension of red fox models to include spatial dynamics [ |
SIR, susceptible-infected-recovered; SIS, susceptible-infected-susceptible; SEIR, susceptible-exposed-infected-recovered