ArticleEpidemiology and infection2021
A scoping review of the detection, epidemiology and control of
Article in Epidemiology and infection, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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.
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.
Who cites it
10 citing papers in PubMed.
- Molecular detection of Cyclospora cayetanensis in fresh produce and irrigation water in peri-urban settings: a cross-sectional study of the environmental-agricultural interface.BMC microbiology · 2026Article
- Microbial Contamination Risks From Adjacent and Nearby Land: Evidence and Implications for Produce Safety.Journal of food science · 2026Review
- Review
- Evaluation of nucleic acid extraction methods for recovery of Cyclospora cayetanensis, Salmonella enterica, and murine norovirus from water and sludge.Journal of microbiological methods · 2025Article
- DNA Aptamer-Based Staining and Fluorescence Microscopy for Rapid Detection of Cyclospora Cayetanensis Oocysts.Journal of fluorescence · 2025Article
- Article
- Molecular Detection ofMicroorganisms · 2023Article
- Migrating Anatidae as Sources of Environmental Contamination with ZoonoticPathogens (Basel, Switzerland) · 2023Review
- Comparative Evaluation of an Easy Laboratory Method for the Concentration of Oocysts and Commercial DNA Isolation Kits for the Molecular Detection ofMicroorganisms · 2022Article
- Seasonal Differences inMicroorganisms · 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
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cyclospora cayetanensis is a parasite causing cyclosporiasis (an illness in humans). Produce (fruits, vegetables, herbs), water and soil contaminated with C. cayetanensis have been implicated in human infection. The objective was to conduct a scoping review of primary research in English on the detection, epidemiology and control of C. cayetanensis with an emphasis on produce, water and soil. MEDLINE® (Web of ScienceTM), Agricola (ProQuest), CABI Global Health, and Food Science and Technology Abstracts (EBSCOhost) were searched from 1979 to February 2020. Of the 349 relevant primary research studies identified, there were 75 detection-method studies, 40 molecular characterisation studies, 38 studies of Cyclospora in the environment (33 prevalence studies, 10 studies of factors associated with environmental contamination), 246 human infection studies (212 prevalence/incidence studies, 32 outbreak studies, 60 studies of environmental factors associated with non-outbreak human infection) and eight control studies. There appears to be sufficient literature for a systematic review of prevalence and factors associated with human infection with C. cayetanensis. There is a dearth of publicly available detection-method studies in soil (n = 0) and water (n = 2), prevalence studies on soil (n = 1) and studies of the control of Cyclospora (particularly on produce prior to retail (n = 0)).
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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.