Can pharmaceutical pollution alter the spread of infectious disease? A case study using fluoxetine.
Lucinda C AulsebrookBob B M WongMatthew D HallPublished in: Philosophical transactions of the Royal Society of London. Series B, Biological sciences (2023)
Human activity is changing global environments at an unprecedented rate, imposing new ecological and evolutionary ramifications on wildlife dynamics, including host-parasite interactions. Here we investigate how an emerging concern of modern human activity, pharmaceutical pollution, influences the spread of disease in a population, using the water flea Daphnia magna and the bacterial pathogen Pasteuria ramosa as a model system. We found that exposure to different concentrations of fluoxetine-a widely prescribed psychoactive drug and widespread contaminant of aquatic ecosystems-affected the severity of disease experienced by an individual in a non-monotonic manner. The direction and magnitude of any effect, however, varied with both the infection outcome measured and the genotype of the pathogen. By contrast, the characteristics of unexposed animals, and thus the growth and density of susceptible hosts, were robust to fluoxetine. Using our data to parameterize an epidemiological model, we show that fluoxetine is unlikely to lead to a net increase or decrease in the likelihood of an infectious disease outbreak, as measured by a pathogen's transmission rate or basic reproductive number. Instead, any given pathogen genotype may experience a twofold change in likely fitness, but often in opposing directions. Our study demonstrates that changes in pharmaceutical pollution give rise to complex genotype-by-environment interactions in its influence of disease dynamics, with repercussions on pathogen genetic diversity and evolution. This article is part of the theme issue 'Infectious disease ecology and evolution in a changing world'.
Keyphrases
- infectious diseases
- heavy metals
- risk assessment
- candida albicans
- endothelial cells
- human health
- genetic diversity
- particulate matter
- health risk assessment
- climate change
- induced pluripotent stem cells
- magnetic resonance
- physical activity
- big data
- emergency department
- electronic health record
- drinking water
- air pollution
- data analysis
- contrast enhanced
- plasmodium falciparum
- deep learning
- trypanosoma cruzi
- toxoplasma gondii