Community epidemiology framework for classifying disease threats

Abstract

Recent evidence suggests that most parasites can infect multiple host species and that these are primarily responsible for emerging infectious disease outbreaks in humans and wildlife. However, the ecologic and evolutionary factors that constrain or facilitate such emergences are poorly understood. We propose a conceptual framework based on the pathogen's between- and within-species transmission rates to describe possible configurations of a multihost-pathogen community that may lead to disease emergence. We establish 3 dynamic thresholds separating 4 classes of disease outcomes, spillover, apparent multi-host, true multihost, and potential emerging infectious disease; describe possible disease emergence scenarios; outline the population dynamics of each case; and clarify existing terminology. We highlight the utility of this framework with examples of disease threats in human and wildlife populations, showing how it allows us to understand which ecologic factors affect disease emergence and predict the impact of host shifts in a range of disease systems.

Figure 1

Emerging infectious disease framework. A) Schematic diagram of the multihost-pathogen community. B) Possible outcomes for a novel host, H₂, after an initial infection by a pathogen endemic in an existing host, H₁, where (1) the pathogen is unable to invade H₂, (2) the pathogen invades but cannot be sustained within H₂, (3) the pathogen invades and persists in H₂, and (4) the pathogen invades and drives H₂ to extinction. C) Three thresholds separating the 4 possible outcomes: (i) the invasion threshold, (ii) the persistence threshold, and (iii) the host extinction threshold.

Figure 2

Community-epidemiology continuum, determined by the net between-H₁ and -H₂ transmission rate (f₁₂) and the net within-H₂ transmission rate (f₂₂). EID, emerging infectious disease.

Figure 3

Stochastic model predictions of system behavior in β₁₂–β₂₂ parameter space. Each square represents the average of 100 simulation runs. Two measures of pathogen persistence are shown: A) Mean prevalence of infection in H₂, where black represents zero prevalence and white represents 100% prevalence, and B) Proportion of time in which the pathogen is absent (i.e., has faded out) from H₂, where white represents zero fade-outs (i.e., the pathogen is always present in H₂) and black represents 100% fade-outs (i.e., the pathogen never infects H₂). C) Probability of pathogen-driven host extinction, where black represents the case in which all runs resulted in host extinction and white the case in which none of the runs resulted in host extinction. The horizontal dashed lines are the deterministic approximations of the persistence threshold (given by R₀ = 1 when β₁₂ = 0) and the vertical lines are the deterministic approximations of the host extinction threshold. The points marked A and B in panel A and the associated arrows represent different control scenarios for 2-host pathogen systems located at different points within the continuum (see text for details).