Evidence map›Paper›PMID 27589798›Full record

ArticleToxins2016

Development of Toxicological Risk Assessment Models for Acute and Chronic Exposure to Pollutants.

Elke S Reichwaldt, Daniel Stone, Dani J Barrington, Som C Sinang, Anas Ghadouani

Abstract read
In one paragraph

Article in Toxins, 2016. 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. Article
  2. Review
  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

5 authors.

Elke S ReichwaldtAquatic Ecology and Ecosystem Studies, School of Civil, Environmental and Mining Engineering, The University of Western Australia, 35 Stirling Highway, M015, Crawley WA 6009, Western Australia, Australia. elke.reichwaldt@uwa.edu.au.
Daniel StoneAquatic Ecology and Ecosystem Studies, School of Civil, Environmental and Mining Engineering, The University of Western Australia, 35 Stirling Highway, M015, Crawley WA 6009, Western Australia, Australia. 20514707@student.uwa.edu.au.
Dani J BarringtonInternational Water Centre, Department of Marketing, Monash University, School of Public Health, The University of Queensland, Level 16, 333 Ann Street, Brisbane QLD 4000, Queensland, Australia. dani.barrington@monash.edu.
Som C SinangFaculty of Science and Mathematics, Sultan Idris Education University, Tanjong Malim 35900, Perak, Malaysia. somcit@fsmt.upsi.edu.my.
Anas GhadouaniAquatic Ecology and Ecosystem Studies, School of Civil, Environmental and Mining Engineering, The University of Western Australia, 35 Stirling Highway, M015, Crawley WA 6009, Western Australia, Australia. anas.ghadouani@uwa.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alert level frameworks advise agencies on a sequence of monitoring and management actions, and are implemented so as to reduce the risk of the public coming into contact with hazardous substances. Their effectiveness relies on the detection of the hazard, but with many systems not receiving any regular monitoring, pollution events often go undetected. We developed toxicological risk assessment models for acute and chronic exposure to pollutants that incorporate the probabilities that the public will come into contact with undetected pollution events, to identify the level of risk a system poses in regards to the pollutant. As a proof of concept, we successfully demonstrated that the models could be applied to determine probabilities of acute and chronic illness types related to recreational activities in waterbodies containing cyanotoxins. Using the acute model, we identified lakes that present a 'high' risk to develop Day Away From Work illness, and lakes that present a 'low' or 'medium' risk to develop First Aid Cases when used for swimming. The developed risk models succeeded in categorising lakes according to their risk level to the public in an objective way. Modelling by how much the probability of public exposure has to decrease to lower the risks to acceptable levels will enable authorities to identify suitable control measures and monitoring strategies. We suggest broadening the application of these models to other contaminants.

Indexed as

Environmental MonitoringModels, TheoreticalDose-Response Relationship, DrugHumansLakesMarine ToxinsMicrocystinsRisk AssessmentWater Pollutantscyanoginosin LRMarine ToxinsMicrocystinsWater Pollutantsacute riskchronic riskcyanobacteriaenvironmental risk assessmentmicrocystinspollutantprobability of exposure

Identifiers

PMID27589798
PMCPMC5037477

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.