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About the Authors:
Mark D. Jankowski
Affiliations United States Fish and Wildlife Service, Pocatello, Idaho, United States of America, Department of Zoology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
Christopher J. Williams
Affiliation: Department of Statistics, University of Idaho, Moscow, Idaho, United States of America
Jeanne M. Fair
Affiliation: Biosecurity and Public Health, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
Jennifer C. Owen
* E-mail: [email protected]
Affiliations Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, United States of America, Department of Large Animal Clinical Sciences, Michigan State University, East Lansing, Michigan, United States of America
Introduction
In the last century, there has been an unprecedented increase in the numbers of emerging infectious diseases (EIDs), which pose significant risks to wild and domestic animal and human populations [1]. The goal and biggest challenge to health professionals is to predict and slow the course of a disease epidemic and minimize the number of affected individuals. Predicting the spread of a disease and changes in the number of infected individuals within a population is typically performed using epidemiological models, [2], [3] which track the number of susceptible, infected, and recovered individuals. However, these models frequently assume a homogeneous population in which the ‘infected’ are equally infectious. Yet, we know that populations are heterogeneous and that individuals vary in their ability to maintain pathogens, with some individuals exhibiting high pathogen loads (i.e. ‘supershedders’, [4]) while others maintain average or low pathogen loads.
The importance of transmission heterogeneity to the spread of disease is becoming increasingly recognized [5]–[7]. Nevertheless, our understanding is limited because it is not well studied [8]. The best illustration of the importance of heterogeneity in host response to pathogens is the incidence of superspreaders [2], [9], in which 20% of a host population contributes to 80% of transmission. Pathogen superspreading can be linked to disproportionate contact rates, heterogeneous pathogen load, or an interaction between these factors. However, to date, evidence for superspreaders has been primarily associated with an increase in contact rates and behavior of the individuals [10], rather than variation in a host’s infection intensity. Yet, given the same exposure rate we know that individuals vary in the ultimate pathogen load that they develop [7],...