ArticleEpidemiology and infection2021
Investigation of US
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 25 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
25 citing papers in PubMed, 29 citations in OpenAlex.
- An integrated One Health surveillance on cyclosporiasis outbreaks in the United States.New microbes and new infections · 2026Article
- Genetic characterization ofLancet regional health. Americas · 2025Article
- Assessing the sequencing success and analytical specificity of a targeted amplicon deep sequencing workflow for genotyping the foodborne parasiteJournal of clinical microbiology · 2025Article
- Genetic diversity withinParasitology · 2025Article
- Detectability and Persistence ofPathogens (Basel, Switzerland) · 2025Article
- Evaluating Foodborne Cyclosporiasis Using Foodborne Diseases Active Surveillance Network and Foodborne Disease Outbreak Surveillance System Data, 2015-2019.The American journal of tropical medicine and hygiene · 2025Article
- Cyclospora Genotypic Variations and Associated Epidemiologic Characteristics, United States, 2018-2021.Emerging infectious diseases · 2025Article
- Sources and Prevalence of Cyclospora cayetanensis in Southeastern U.S. Growing Environments.Journal of food protection · 2024Article
- Evaluation of the Increased Genetic Resolution and Utility for Source Tracking of a Recently Developed Method for GenotypingMicroorganisms · 2024Article
- Evaluation of nuclear and mitochondrial phylogenetics for the subtyping of Cyclospora cayetanensis.Parasitology research · 2023Article
- The limit of detection of the BioFire® FilmArray® gastrointestinal panel for the foodborne parasite Cyclospora cayetanensis.Diagnostic microbiology and infectious disease · 2023Article
- Article
- Retrospective evaluation of an integrated molecular-epidemiological approach to cyclosporiasis outbreak investigations - United States, 2021.Epidemiology and infection · 2023Article
- Epidemiologic Utility of a Framework for Partition Number Selection When Dissecting Hierarchically Clustered Genetic Data Evaluated on the Intestinal Parasite Cyclospora cayetanensis.American journal of epidemiology · 2023Article
- Genetic characterization ofInternational journal for parasitology. Parasites and wildlife · 2023Article
- Article
- Optimizing hierarchical tree dissection parameters using historic epidemiologic data as 'ground truth'.PloS one · 2023Article
- Novel insights on the genetic population structure of human-infectingCurrent research in parasitology & vector-borne diseases · 2023Article
- An improved framework for detecting discrete epidemiologically meaningful partitions in hierarchically clustered genetic data.Bioinformatics advances · 2023Article
- Development of a targeted amplicon sequencing method for genotypingFrontiers in microbiology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cyclosporiasis is an illness characterised by watery diarrhoea caused by the food-borne parasite Cyclospora cayetanensis. The increase in annual US cyclosporiasis cases led public health agencies to develop genotyping tools that aid outbreak investigations. A team at the Centers for Disease Control and Prevention (CDC) developed a system based on deep amplicon sequencing and machine learning, for detecting genetically-related clusters of cyclosporiasis to aid epidemiologic investigations. An evaluation of this system during 2018 supported its robustness, indicating that it possessed sufficient utility to warrant further evaluation. However, the earliest version of CDC's system had some limitations from a bioinformatics standpoint. Namely, reliance on proprietary software, the inability to detect novel haplotypes and absence of a strategy to select an appropriate number of discrete genetic clusters would limit the system's future deployment potential. We recently introduced several improvements that address these limitations and the aim of this study was to reassess the system's performance to ensure that the changes introduced had no observable negative impacts. Comparison of epidemiologically-defined cyclosporiasis clusters from 2019 to analogous genetic clusters detected using CDC's improved system reaffirmed its excellent sensitivity (90%) and specificity (99%), and confirmed its high discriminatory power. This C. cayetanensis genotyping system is robust and with ongoing improvement will form the basis of a US-wide C. cayetanensis genotyping network for clinical specimens.
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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.