The role of evolution in the emergence of infectious diseases

Abstract

It is unclear when, where and how novel pathogens such as human immunodeficiency virus (HIV), monkeypox and severe acute respiratory syndrome (SARS) will cross the barriers that separate their natural reservoirs from human populations and ignite the epidemic spread of novel infectious diseases. New pathogens are believed to emerge from animal reservoirs when ecological changes increase the pathogen's opportunities to enter the human population and to generate subsequent human-to-human transmission. Effective human-to-human transmission requires that the pathogen's basic reproductive number, R(0), should exceed one, where R(0) is the average number of secondary infections arising from one infected individual in a completely susceptible population. However, an increase in R(0), even when insufficient to generate an epidemic, nonetheless increases the number of subsequently infected individuals. Here we show that, as a consequence of this, the probability of pathogen evolution to R(0) > 1 and subsequent disease emergence can increase markedly.

Figure 1. Schematic for the emergence of an infectious disease.

Introductions from the reservoir are followed by chains of transmission in the human population. Infections with the introduced strain (open circles) have a basic reproductive number R₀ < 1. Pathogen evolution generates an evolved strain (filled circles) with R₀ > 1. The infections caused by the evolved strain can go on to cause an epidemic. Daggers indicate no further transmission.

Figure 2. One-step evolution. A single change is required for the pathogen to evolve to R₀ > 1.

a, The probability that an introduction leads to an infection with an evolved strain of the pathogen (filled circle in Fig. 1) is highly sensitive to R₀, and is approximately linearly dependent on the mutation rate µ. Lines correspond to numerical solutions to the branching process model (see Supplementary Information) and symbols correspond to Monte-Carlo simulations following 10⁵ introductions. b, The probability of emergence per introduction depends on the R₀ value of the introduced pathogen and of the evolved pathogen. The solid, dashed and dotted lines correspond to the evolved pathogen having an R₀ of 1,000, 1.5 and 1.2 respectively.

Figure 3. Multiple-step evolution.

Here multiple evolutionary changes are required for evolution of the pathogen to have an R₀ > 1. a, Jackpot model with µ = 0.1 and n intermediate changes each with R₀ equal to that of the introduced pathogen: increasing the number of steps (n) greatly decreases the probability of evolution, and makes it more sensitive to the R₀ of the introduced pathogen. b, Alternative multi-step models for the one-intermediate (n = 1) case. The jackpot model (solid line), additive model (dashed line) and fitness valley model (dotted line) are shown (see text for details).