title: Long-distance dispersal and accelerating waves of disease: empirical relationships.
abstract: Classic approaches to modeling biological invasions predict a "traveling wave" of constant velocity determined by the invading organism's reproductive capacity, generation time, and dispersal ability. Traveling wave models may not apply, however, for organisms that exhibit long-distance dispersal. Here we use simple empirical relationships for accelerating waves, based on inverse power law dispersal, and apply them to diseases caused by pathogens that are wind dispersed or vectored by birds: the within-season spread of a plant disease at spatial scales of <100 m in experimental plots, historical plant disease epidemics at the continental scale, the unexpectedly rapid spread of West Nile virus across North America, and the transcontinental spread of avian influenza strain H5N1 in Eurasia and Africa. In all cases, the position of the epidemic front advanced exponentially with time, and epidemic velocity increased linearly with distance; regression slopes varied over a relatively narrow range among data sets. Estimates of the inverse power law exponent for dispersal that would be required to attain the rates of disease spread observed in the field also varied relatively little (1.74-2.36), despite more than a fivefold range of spatial scale among the data sets.
authors.affiliation: Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA. mundtc@science.oregonstate.edu
authors.forename: Christopher C
authors.initials: CC
authors.lastname: Mundt
authors.forename: Kathryn E
authors.initials: KE
authors.lastname: Sackett
authors.forename: LaRae D
authors.initials: LD
authors.lastname: Wallace
authors.forename: Christina
authors.initials: C
authors.lastname: Cowger
authors.forename: Joseph P
authors.initials: JP
authors.lastname: Dudley
mesh_terms: D000818:Animals; D001717:Birds / Q000821:virology; D003198:Computer Simulation; D003710:Demography; D018562:Disease Transmission, Infectious; D005585:Influenza in Birds / Q000453:epidemiology / Q000635:transmission; D008954:Models, Biological; D010935:Plant Diseases; D012044:Regression Analysis; D014901:West Nile Fever / Q000453:epidemiology / Q000635:transmission