Evidence map›Paper›PMID 29636794›Full record

ArticleEvolutionary applications2018

Complexity and biosemiotics in evolutionary ecology of zoonotic infectious agents.

Michael Kosoy, Roman Kosoy

Abstract read
In one paragraph

Article in Evolutionary applications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Parasites and wildlife in a changing world: The vector-host- pathogen interaction as a learning case.International journal for parasitology. Parasites and wildlife · 2019
    Review
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Michael KosoyDivision of Vector-Borne Diseases Centers for Disease Control and Prevention Fort Collins CO USA.ORCID 0000-0002-0039-4981
Roman KosoyDepartment of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York NY USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

More is not automatically better. Generation and accumulation of information reflecting the complexity of zoonotic diseases as ecological systems do not necessarily lead to improved interpretation of the obtained information and understanding of these complex systems. The traditional conceptual framework for analysis of diseases ecology is neither designed for, nor adaptable enough, to absorb the mass of diverse sources of relevant information. The multidirectional and multidimensional approaches to analyses form an inevitable part in defining a role of zoonotic pathogens and animal hosts considering the complexity of their inter-relations. And the more data we have, the more involved the interpretation needs to be. The keyword for defining the roles of microbes as pathogens, animals as hosts, and environmental parameters as infection drivers is "functional importance." Microbes can act as pathogens toward their host only if/when they recognize the animal organism as the target. The same is true when the host recognizes the microbe as a pathogen rather than harmless symbiont based on the context of its occurrence in that host. Here, we propose conceptual tools developed in the realm of the interdisciplinary sciences of complexity and biosemiotics for extending beyond the currently dominant mindset in ecology and evolution of infectious diseases. We also consider four distinct hierarchical levels of perception guiding how investigators can approach zoonotic agents, as a subject of their research, representing differences in emphasizing particular elements and their relations versus more unified systemic approaches.

Indexed as

bacteriabiosemioticscomplexitydisease evolutionhost–parasite interactionsinfection ecologypathogen

Identifiers

PMID29636794
PMCPMC5891042

What OpenQuestion holds

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Registered trials

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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.