Open AccessEpidemiological and evolutionary consequences of periodicity in treatment coverage
Author(s) -
Alicia Walter,
Sébastien Lion
Publication year - 2021
Publication title -
proceedings - royal society. biological sciences/proceedings - royal society. biological sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.342
H-Index - 253
eISSN - 1471-2954
pISSN - 0962-8452
DOI - 10.1098/rspb.2020.3007
Subject(s) - evolutionary dynamics , biology , pathogen , host (biology) , virulence , evolutionary biology , selection (genetic algorithm) , mathematical modelling of infectious disease , evolutionarily stable strategy , disease , ecology , infectious disease (medical specialty) , computer science , genetics , mathematics , demography , population , game theory , machine learning , mathematical economics , medicine , pathology , sociology , gene
Host heterogeneity is a key driver of host–pathogen dynamics. In particular, the use of treatments against infectious diseases creates variation in quality among hosts, which can have both epidemiological and evolutionary consequences. We present a general theoretical model to highlight the consequences of different imperfect treatments on pathogen prevalence and evolution. These treatments differ in their action on host and pathogen traits. In contrast with previous studies, we assume that treatment coverage can vary in time, as in seasonal or pulsed treatment strategies. We show that periodic treatment strategies can limit both disease spread and virulence evolution, depending on the type of treatment. We also introduce a new method to analytically calculate the selection gradient in periodic environments, which allows our predictions to be interpreted using the concept of reproductive value, and can be applied more generally to analyse eco-evolutionary dynamics in class-structured populations and fluctuating environments.