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Record W2941251512 · doi:10.47339/ephj.2018.59

Environmental sampling for legionella proliferation risk in three long-term care facilities in Vancouver, British Columbia

2015· article· en· W2941251512 on OpenAlexvenueaboutno aff
Kelsey A. Stele, Environmental Health BCIT School of Health Sciences, Helen Heacock

Bibliographic record

VenueBCIT Environmental Public Health Journal · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLegionella and Acanthamoeba research
Canadian institutionsnot available
Fundersnot available
KeywordsLegionellaEnvironmental scienceLong-term careEnvironmental engineeringEnvironmental healthMedicineWaste managementEngineeringBiology

Abstract

fetched live from OpenAlex


 Background: Legionella is a pathogen that causes Legionnaires’ disease in high risk populations. The pathogen is known to exist in plumbing systems that do not have preventative factors in place to prevent its growth and proliferation. Legionella grows between 25˚C and 42˚C and is killed at 60˚C, yet long-term care facilities (LTCFs) reduce accessible hot water temperatures from 60˚C at the hot water tank to less than 49˚C at the taps in order to prevent scalding of their residents. Currently, prevention against scalding takes precedence as temperature at accessible taps is regulated within the Residential Care Regulation (RCR) of the Community Care and Assisted Living Act. It is thought that Legionella proliferation risk can be balanced with scalding in-part through the appropriate installation location of thermostatic mixing valves (TMVs). Methods: Three LTCFs in Vancouver, British Columbia were selected for environmental sampling for Legionella proliferation risk. At each LTCF the author recorded the type of hot water tank, temperature of water within the hot water tank, the presence of a TMV and temperature of pipes before and after the TMV. As well, the author recorded hot water temperatures after one minute and free available chlorine concentration ([FAC]) at numerous resident-accessible taps throughout each LTCF. Results: The hot water tank temperatures were set at 60.6˚C, 73.0˚C and 62.0˚C for LTCF #1, LTCF #2 and LTCF #3, respectively. All three LTCFs had installed a TMV within the boiler room immediately after the hot water tank. It was found that LTCF #1’s plumbing system water temperature was reduced from 60.6˚C (at the tank) to 48.9˚C after the TMV. LTCF #2’s plumbing system water temperature was reduced from 73.0˚C (at the tank) to 43.3˚C after the TMV. LTCF #3 was an older plumbing system that did not have thermometers within the boiler room to check the drop in temperature after the TMV. Water temperatures at taps were compared to a standard of 49°C and [FAC] levels at taps to a standard of 0.2 mg/L. The mean hot water temperature and mean [FAC] residual for all three LTCFs were 40.2˚C and 0.27 mg/L, respectively. For all three LTCFs, it was statistically significant that mean water temperatures were less than the comparison value of 49˚C (LTCF #1 p = 0.00000, LTCF #2 p = 0.00022, LTCF #3 p = 0.00110). It was also statistically significant that the mean [FAC] of all three LTCFs were greater than the comparison vale of 0.20 mg/L (LTCF #1 p = 0.00042, LTCF #2 p = 0.00000, LTCF #3 p = 0.00107). Conclusion: It was found that all three LTCFs had set preventive measures in place to protect their residents. Water was heated to at least 60˚C to prevent Legionella and lowered to less than 49˚C to prevent scalding. [FAC] residual was also adequate to prevent growth of Legionella. However, the location of the TMV in the boiler room was suspected to be a possible contributing factor to Legionella growth, especially if cold water temperatures were to reach 20˚C or above, as they could in warm summer months. Further research is needed to determine the significance of the TMV location and the presence of Legionella.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.926

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.038
GPT teacher head0.283
Teacher spread0.244 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes2
Has abstractyes

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