aceCan't see the forest for the trees? Statistical considerations for disease macroecology
Disease macroecology relies on large, complex datasets to understand the biotic and abiotic factors shaping parasite distributions and emerging infectious disease risk. These datasets span local to global host-parasite interactions and often integrate diverse host or parasite traits across evolutionary histories. Selecting appropriate statistical approaches requires first asking key questions about the study system: How well is the system understood? How important is predictor accuracy? How much bias is present…
Can't see the forest for the trees? Statistical considerations for disease macroecology: Disease macroecology relies on large, complex datasets to understand the biotic and abiotic factors shaping parasite distributions and emerging infectious disease risk.
Evidence
- Peer-reviewedJournal of Helminthology2026-09-18
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Truvace Impact Record TRV-2026-1142, v2: “Can't see the forest for the trees? Statistical considerations for disease macroecology.” Truvace, 2026-10-26. /record/TRV-2026-1142 (accessed at citation time). sha256 98595f565b4db12a…
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