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Record W2086287821 · doi:10.1016/j.phr.2004.05.008

A Review of Outbreaks of Waterborne Disease Associated with Ships: Evidence for Risk Management

2004· review· en· W2086287821 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePublic Health Reports · 2004
Typereview
Languageen
FieldMedicine
TopicTravel-related health issues
Canadian institutionsHealth Canada
Fundersnot available
KeywordsOutbreakWaterborne diseasesCryptosporidiumEnvironmental healthNorovirusWater supplyFishingEnvironmental scienceVeterinary medicineMedicineBiologyEnvironmental engineeringFisheryMicrobiologyVirology

Abstract

fetched live from OpenAlex

OBJECTIVE: The organization of water supply to and on ships differs considerably from that of water supply on land. Risks of contamination can arise from source water at the port or during loading, storage, or distribution on the ship. The purpose of this article is to review documented outbreaks of waterborne diseases associated with passenger, cargo, fishing, and naval ships to identify contributing factors so that similar outbreaks can be prevented in the future. METHODS: The authors reviewed 21 reported outbreaks of waterborne diseases associated with ships. For each outbreak, data on pathogens/toxins, type of ship, factors contributing to outbreaks, mortality and morbidity, and remedial action are presented. RESULTS: The findings of this review show that the majority of reported outbreaks were associated with passenger ships and that more than 6,400 people were affected. Waterborne outbreaks due to Enterotoxigenic Escherichia coli, noroviruses, Salmonella spp, Shigella sp, Cryptosporidium sp, and Giardia lamblia occurred on ships. Enterotoxigenic E. coli was the pathogen most frequently associated with outbreaks. One outbreak of chemical water poisoning also occurred on a ship. Risk factors included contaminated port water, inadequate treatment, improper loading techniques, poor design and maintenance of storage tanks, ingress of contamination during repair and maintenance, cross-connections, back siphonage, and insufficient residual disinfectant. CONCLUSIONS: Waterborne disease outbreaks on ships can be prevented. The factors contributing to outbreaks emphasize the need for hygienic handling of water along the supply chain from source to consumption. A comprehensive approach to water safety on ships is essential. This may be achieved by the adoption of Water Safety Plans that cover design, construction, operation, and routine inspection and maintenance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.498
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.248
GPT teacher head0.463
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it