ArticleAdvances in experimental medicine and biology2023
Application of Graphs in a One Health Framework.
Article in Advances in experimental medicine and biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Authors and funding
2 authors.
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Abstract
The One Health framework, which advocates the crucial interconnection between environmental, animal, and human health and well-being, is becoming of increasing importance and acceptance in health sciences over the last years. The hottest public health topics of the latest years, like zoonotic diseases (e.g., the recent pandemic) or the increasing antibiotic resistance, characterized by many as "pandemic of the future," make the more holistic and combinatorial approach of One Health a necessity to combat such complex problems. Multiple graphs and graph theory have found applications in health sciences for many years, and they can now extend to usage across all levels of a One Health approach to health, ranging from genome, one disease level, to epidemiology and ecosystem graphs. For that last ecosystem layer, a proposed approach is the utilization of process graphs from the chemical engineering field, in order to understand a whole system and what constitute the most crucial aspects of a One Health issue in ecosystem level. Here P-graphs are focused alongside their combinatorial algorithms, implemented in R, and their application researched in an effort to extract information and plan interventions.
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37486492What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.