Evidence map›Paper›PMID 29545629›Full record

ArticleScientific reports2018

Cryptosporidium oocyst persistence in agricultural streams -a mobile-immobile model framework assessment.

J D Drummond, F Boano, E R Atwill, X Li, T Harter, A I Packman

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 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
1.1field-weighted citation impact, top 29% of its field
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, 14 citations in OpenAlex.

  1. Effect of beaver dam analogs (BDAs) on waterborne protozoal pathogensApplied and environmental microbiology · 2025
    Article
  2. Article
  3. Analysis of Long Non-Coding RNA inFrontiers in cellular and infection microbiology · 2020
    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

6 authors at 4 institutions in 3 countries.

J D DrummondIntegrative Freshwater Ecology Group, Centre for Advanced Studies of Blanes (CEAB-CSIC), Blanes, Girona, Spain. j.drummond@ceab.csic.es.ORCID 0000-0002-6501-7618
F BoanoDepartment of Environment, Land and Infrastructure Engineering, Politecnico di Torino, Torino, Italy.
E R AtwillDepartment of Population Health and Reproduction, University of California, Davis, California, USA.
X LiDepartment of Population Health and Reproduction, University of California, Davis, California, USA.
T HarterDepartment of Land, Air, and Water Resources, University of California, Davis, California, USA.
A I PackmanDepartment of Civil and Environmental Engineering, Northwestern University, Evanston, Illinois, USA.
University of California, Davis · USCentre d'Estudis Avançats de Blanes · ESNorthwestern University · USPolitecnico di Torino · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rivers are a means of rapid and long-distance transmission of pathogenic microorganisms from upstream terrestrial sources. Pathogens enter streams and rivers via overland flow, shallow groundwater discharge, and direct inputs. Of concern is the protozoal parasite, Cryptosporidium, which can remain infective for weeks to months under cool and moist conditions, with the infectious stage (oocysts) largely resistant to chlorination. We applied a mobile-immobile model framework to assess Cryptosporidium transport and retention in streams, that also accounts for inactivation. The model is applied to California's Central Valley where Cryptosporidium exposure can be at higher risk due to agricultural and wildlife nonpoint sources. The results demonstrate that hyporheic exchange is an important process to include in models characterizing pathogen dynamics in streams, delaying downstream transmission and allowing for immobilization processes, such as reversible filtration in the sediments, to occur. Although in-stream concentrations decrease relatively quickly (within hours), pathogen accumulation of up to 66% of the inputs due to immobilization processes in the sediments and slower moving surface water could result in long retention times (months to years). The model appropriately estimates baseflow pathogen accumulation and can help predict the potential loads of resuspended pathogens in response to a storm event.

Indexed as

Models, TheoreticalAgricultureCryptosporidiumEnvironmental MonitoringGeologic SedimentsGroundwaterOocystsRisk FactorsRivers

Identifiers

PMID29545629
PMCPMC5854703
OpenAlexW2792475672

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.