COS 183-9 - Stochastic fade-out in space: Will microscale disease-induced mortality along geographic corridors inhibit the macroscale spread of White-nose Syndrome?

Friday, August 10, 2012: 10:50 AM
D139, Oregon Convention Center
Suzanne M. O'Regan1, Krisztian Magori2, J. Tomlin Pulliam3, Marcus A. Zokan1, RajReni B. Kaul1, Heather D. Barton1 and John M. Drake4, (1)Odum School of Ecology, University of Georgia, Athens, GA, (2)School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL, (3)Odum School of Ecology, University of Georgia, (4)Center for the Ecology of Infectious Diseases, University of Georgia, Athens, GA
Background/Question/Methods

White-nose syndrome (WNS) is an emerging, often fatal, disease in bats. The spread of WNS occurs over at least two spatial scales including within winter roosting sites (where transmission is assumed to occur through direct contact) and between roosting sites (through dispersal of infected individuals). Some bat species, including the Little Brown bat, can migrate over long distances, potentially thereby spreading the disease at even larger spatial scales. Despite reports of mass mortality of bats, disease-induced-mortality has been overlooked as a potential mechanism for inhibiting macroscale spread of WNS. We hypothesized that (a) spatial heterogeneities will lead to fadeout of the disease before all counties in the U.S become infected (b) the final size of the WNS epidemic will differ over multiple spatial scales and (c) microscale epidemic burnout will prevent the extinction of the Little Brown bat population in the northeastern United States. We fitted a Susceptible-Infected-Recovered (SIR) model to cave-scale infection history within counties that were located in New York and Pennsylvania. To model the macroscale spread of WNS, we used a network model, which assumed spread between counties was determined by the distribution of hibernacula and climate. The SIR model determined the durations of epidemics within counties.

Results/Conclusions

Simulations of the multiscale model predict initial rapid expansion of the infection followed by microscale burnout inhibiting spread eventually, leading to macroscale fadeout of the disease. Our model suggests that the mean macroscale final epidemic size will be ~84% but in the northeastern U.S., ~99% of counties will be eventually infected.  Microscale burnout is unlikely to mitigate large-scale spread of WNS between counties, with mountainous regions with high cave density having a near-certain risk of infection of WNS. Once WNS reaches these regions, county burnout does not exceed the rate of newly infected counties until the winter of 2019-2020. To investigate the impact of WNS on viability of the northeastern Little Brown bat population, we estimated the annual decline rate each year in the northeastern U.S. In contrast to previous predictions, our model suggests that the northeastern population will persist in the long term, albeit at much reduced size, declining asymptotically to ~8% of the original mean population size by the winter of 2045-2046. Our results suggest that microscale burnout may mitigate the risk of regional population extinction of Little Brown bats but it will not inhibit that population from declining precipitously.