ArticleJournal of mammalogy2019
Topic modeling of major research themes in disease ecology of mammals.
Article in Journal of mammalogy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Trends and Opportunities in Tick-Borne Disease Geography.Journal of medical entomology · 2021Pooled it
- Estimating parasite infrapopulation size given imperfect detection: Proof-of-concept with ectoparasitic fleas on prairie dogs.International journal for parasitology. Parasites and wildlife · 2023Article
- Past and future uses of text mining in ecology and evolution.Proceedings. Biological sciences · 2022Review
- Reviewing the Past, Present, and Future Risks of Pathogens in Ghana and What This Means for Rethinking Infectious Disease Surveillance for Sub-Saharan Africa.Journal of tropical medicine · 2022Review
- Demography, education, and research trends in the interdisciplinary field of disease ecology.Ecology and evolution · 2021Article
- Article
- causalizeR: a text mining algorithm to identify causal relationships in scientific literature.PeerJ · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Disease ecology is a rapidly growing subdiscipline, and mammals and their parasites feature prominently in both historical and more recent research efforts. Nevertheless, the diversity of topics explored, and those not well explored, has not been systematically assessed. We conducted a systematic review of the published scientific literature in disease ecology of mammals and subjected the collection of original and review articles identified to a topic modeling approach, which is based on the words used in the published texts and their contexts (i.e., the frequency and strength of their semantic relationships with one another). In addition to concept maps identifying the most prominent research themes, we identified eight (not mutually exclusive) subcategories of studies, including experimental, theoretical, comparative, behavioral, immunological-microbiological, biogeographic-macroecological, vector-focused (e.g., mosquitoes), and disturbance-focused. The most prominent themes arising in review papers included the ecology of zoonotic diseases transmitted from non-human mammals, comparisons of pathogen prevalence between mammalian species, and pathogen discovery-disease surveillance studies, particularly of marine mammals and bats. For the original articles, the most prominent themes included ecology of rodent-transmitted viral and bacterial diseases and the population biology of zoonotic hosts. Most studies used comparative or descriptive approaches to investigate mammal-pathogen-disease relationships at a local scale, focusing on vector-borne diseases. Experimental, modeling, immunological, and behavioral approaches were strikingly underrepresented. Topics of strong conceptual importance, but that are underrepresented in the current literature, include: 1) the effects of the population density of mammalian hosts, and manipulations of density, on pathogen transmission; 2) macroecological studies that quantify effects of mammalian host species on parasite abundance and prevalence; and 3) effects of climate change on physiological and behavioral processes relevant to mammal-parasite interactions.
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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.