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Abstract The immune system is the primary barrier to parasite infection, replication, and transmission following exposure, and variation in immunity can accordingly manifest in heterogeneity in traits that govern population-level infectious disease dynamics. While much work in ecoimmunology has focused on individual-level determinants of host immune defense (e.g., reproductive status and body condition), an ongoing challenge remains to understand the broader evolutionary and ecological contexts of this variation (e.g., phylogenetic relatedness and landscape heterogeneity) and to connect these differences into epidemiological frameworks. Ultimately, such efforts could illuminate general principles about the drivers of host defense and improve predictions and control of infectious disease. Here, we highlight recent work that synthesizes the complex drivers of immunological variation across biological scales of organization and scales these within-host differences to population-level infection outcomes. Such studies note the limitations involved in making species-level comparisons of immune phenotypes, stress the importance of spatial scale for immunology research, showcase several statistical tools for translating within-host data into epidemiological parameters, and provide theoretical frameworks for linking within- and between-host scales of infection processes. Building from these studies, we highlight several promising avenues for continued work, including the application of machine learning tools and phylogenetically controlled meta-analyses to immunology data and quantifying the joint spatial and temporal dependencies in immune defense using range expansions as model systems. We also emphasize the use of organismal traits (e.g., host tolerance, competence, and resistance) as a way to interlink various scales of analysis. Such continued collaboration and disciplinary cross-talk among ecoimmunology, disease ecology, and mathematical modeling will facilitate an improved understanding of the multi-scale drivers and consequences of variation in host defense.
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Human Infection Challenge Studies: a Test for the Social Value Criterion of Research Ethics
ABSTRACT Human infection challenge studies involving the intentional infection of research participants with a disease-causing agent have recently been suggested as a means to speed up the search for a vaccine for the ongoing coronavirus disease 2019 (COVID-19) outbreak. Calls for challenge studies, however, rely on the expected social value of these studies. This value represents more than the simple possibility that a successful study will lead to the rapid development and dissemination of vaccines but also some expectation that this will actually occur. I show how this expectation may not be realistic in the current political moment and offer potential ways to make sure that any challenge trials that arise actually achieve their goals.
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- Award ID(s):
- 1734521
- PAR ID:
- 10257294
- Editor(s):
- Imperiale, Michael J.
- Date Published:
- Journal Name:
- mSphere
- Volume:
- 5
- Issue:
- 4
- ISSN:
- 2379-5042
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1128/mSphere.00669-20
