Age‐prevalence curves in a multi‐species parasite community

Abstract The relationship between infection prevalence and host age is informative because it can reveal processes underlying disease dynamics. Most prior work has assumed that age‐prevalence curves are shaped by infection rates, host immunity and/or infection‐induced mortality. Interactions between parasites within a host have largely been overlooked as a source of variation in age‐prevalence curves. We used field survey data and models to examine the role of interspecific interactions between parasites in shaping age‐prevalence curves. The empirical dataset included quantification of parasite infection prevalence for eight co‐occurring trematodes in over 15,000 snail hosts. We characterized age‐prevalence curves for each taxon, examined how they changed over space in relation to co‐occurring trematodes and tested whether the shape of the curves aligned with expectations for the frequencies of coinfections by two taxa in the same host. The models explored scenarios that included negative interspecific interactions between parasites, variation in the force‐of‐infection (FOI) and infection‐induced mortality that varied with host age, which were mechanisms hypothesized to be important in the empirical dataset. In the empirical dataset, four trematode parasites had monotonic increasing age‐prevalence curves and four had unimodal age‐prevalence curves. Some of the curves remained consistent in shape in relation to the prevalence of other potentially interacting trematodes, while some shifted from unimodal to monotonic increasing, suggesting release from negative interspecific interactions. The most common taxa with monotonic increasing curves had lower co‐infection frequencies than expected, suggesting they were competitively dominant. Taxa with unimodal curves had coinfection frequencies that were closer to those expected by chance. The model showed that negative interspecific interactions between parasites can cause a unimodal age‐prevalence curve in the subordinate taxon. Increases in the FOI and/or infection‐induced mortality of the dominant taxon cause shifts in the peak prevalence of the subordinate taxon to a younger host age. Infection‐induced mortality that increased with host age was the only scenario that caused a unimodal curve in the dominant taxon. Results indicated that negative interspecific interactions between parasites contributed to variation in the shape of age‐prevalence curves across parasite taxa and support the growing importance of incorporating interactions between parasites in explaining population‐level patterns of host infection over space and time. Read the free Plain Language Summary for this article on the Journal blog.

Authors

Institutions

Publication Details

Journal
Functional Ecology
Published
2024-11-19
DOI
https://doi.org/10.1111/1365-2435.14701
Citations
2
Primary Topic
Parasite Biology and Host Interactions
Type
article
Field-Weighted Citation Impact
0.92

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Age‐prevalence curves in a multi‐species parasite community

Daniel L. Preston, Márk Novák, Landon P. Falke
2 citations
Functional Ecology
Parasite Biology and Host Interactions
0.92
article

Age‐prevalence curves in a multi‐species parasite community

Daniel L. Preston, Márk Novák, Landon P. Falke
article en
2 citations

Abstract

Abstract The relationship between infection prevalence and host age is informative because it can reveal processes underlying disease dynamics. Most prior work has assumed that age‐prevalence curves are shaped by infection rates, host immunity and/or infection‐induced mortality. Interactions between parasites within a host have largely been overlooked as a source of variation in age‐prevalence curves. We used field survey data and models to examine the role of interspecific interactions between parasites in shaping age‐prevalence curves. The empirical dataset included quantification of parasite infection prevalence for eight co‐occurring trematodes in over 15,000 snail hosts. We characterized age‐prevalence curves for each taxon, examined how they changed over space in relation to co‐occurring trematodes and tested whether the shape of the curves aligned with expectations for the frequencies of coinfections by two taxa in the same host. The models explored scenarios that included negative interspecific interactions between parasites, variation in the force‐of‐infection (FOI) and infection‐induced mortality that varied with host age, which were mechanisms hypothesized to be important in the empirical dataset. In the empirical dataset, four trematode parasites had monotonic increasing age‐prevalence curves and four had unimodal age‐prevalence curves. Some of the curves remained consistent in shape in relation to the prevalence of other potentially interacting trematodes, while some shifted from unimodal to monotonic increasing, suggesting release from negative interspecific interactions. The most common taxa with monotonic increasing curves had lower co‐infection frequencies than expected, suggesting they were competitively dominant. Taxa with unimodal curves had coinfection frequencies that were closer to those expected by chance. The model showed that negative interspecific interactions between parasites can cause a unimodal age‐prevalence curve in the subordinate taxon. Increases in the FOI and/or infection‐induced mortality of the dominant taxon cause shifts in the peak prevalence of the subordinate taxon to a younger host age. Infection‐induced mortality that increased with host age was the only scenario that caused a unimodal curve in the dominant taxon. Results indicated that negative interspecific interactions between parasites contributed to variation in the shape of age‐prevalence curves across parasite taxa and support the growing importance of incorporating interactions between parasites in explaining population‐level patterns of host infection over space and time. Read the free Plain Language Summary for this article on the Journal blog.

Functional EcologyVol. 39(1)
National Oceanic and Atmospheric Administration (US), Oregon State University (US), Integrated Statistics (United States) (US), NOAA National Marine Fisheries Service Northeast Fisheries Science Center (US), Colorado State University (US)
National Science Foundation, University of Wisconsin-Madison, Colorado State University, Division of Graduate Education
Good health and well-being
Openalex Percentile: Top 22%
Parasite Biology and Host Interactions
0.92
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.