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Abstract Theoretical models suggest that infectious diseases could play a substantial role in determining the spatial extent of host species, but few studies have collected the empirical data required to test this hypothesis. Pathogens that sterilize their hosts or spread through frequency‐dependent transmission could have especially strong effects on the limits of species' distributions because diseased hosts that are sterilized but not killed may continue to produce infectious stages and frequency‐dependent transmission mechanisms are effective even at very low population densities. We collected spatial pathogen prevalence data and population abundance data for alpine carnations infected by the sterilizing pathogenMicrobotryum dianthorum, a parasite that is spread through both frequency‐dependent (vector‐borne) and density‐dependent (aerial spore transmission) mechanisms. Our 13‐year study reveals rapid declines in population abundance without a compensatory decrease in pathogen prevalence. We apply a stochastic, spatial model of parasite spread that accommodates spatial habitat heterogeneity to investigate how the population dynamics depend on multimodal (frequency‐dependent and density‐dependent) transmission. We found that the observed rate of population decline could plausibly be explained by multimodal transmission, but is unlikely to be explained by either frequency‐dependent or density‐dependent mechanisms alone. Multimodal pathogen transmission rates high enough to explain the observed decline predicted that eventual local extinction of the host species is highly likely. Our results add to a growing body of literature showing how multimodal transmission can constrain species distributions in nature.
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Phylogenetic inference of inter-population transmission rates for infectious diseases
Estimating transmission rates is a challenging yet essential aspect of comprehending and controlling the spread of infectious diseases. There are various methods available for this purpose, each with its own assumptions, data requirements, and limitations. This paper introduces a phylogenetic approach called transRate, designed to estimate inter-population transmission rates. The phylogenetic method, which maintains statistical consistency under the multi-population Susceptible-Infected-Recovered (SIR) model, integrates genetic information with traditional epidemiological approaches. This integration improves the accuracy of transmission rate estimates, facilitating more effective disease control and prevention strategies. Simulation analyses validate the precision of transRate in estimating transmission rates. With the growing abundance of public databases for genomic sequences, transRate is becoming more prevalent in tracking and preventing the spread of such diseases.
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- Award ID(s):
- 2243206
- PAR ID:
- 10516063
- Editor(s):
- Ma, Shuangge; Chen, Zhenxia
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Briefings in Bioinformatics
- Volume:
- 25
- ISSN:
- 10-1093
- Page Range / eLocation ID:
- 312
- Subject(s) / Keyword(s):
- phylogenetic tree, SIR model, Infectious disease, COVID-19, transmission rate
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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