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Record W4313409823 · doi:10.2196/37587

Pilot Evaluation of Possible Airborne Transmission in a Geriatric Care Facility Using Carbon Dioxide Tracer Gas: Case Study

2022· article· en· W4313409823 on OpenAlexvenueno aff
Yo Ishigaki, Shinji Yokogawa, Yuki Minamoto, Akira Saito, Hiroko Kitamura, Yuto Kawauchi

Bibliographic record

VenueJMIR Formative Research · 2022
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceKDDI Foundation
KeywordsEnvironmental scienceOutbreakAerosolCoronavirus disease 2019 (COVID-19)Airborne transmissionTRACERSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)AdvectionMedicineTransmission (telecommunications)MeteorologyEnvironmental healthInfectious disease (medical specialty)GeographyEngineeringDisease

Abstract

fetched live from OpenAlex

Background Although several COVID-19 outbreaks have occurred in older adult care facilities throughout Japan, no field studies focusing on airborne infections within these settings have been reported. Countermeasures against airborne infection not only consider the air change rate (ACR) in a room but also the airflow in and between rooms. However, a specific method has not yet been established by Japanese public health centers or infectious disease–related organizations. Objective In April 2021, 59 COVID-19 cases were reported in an older adult care facility in Miyagi, Japan, and airborne transmission was suspected. The objective of this study was to simultaneously reproduce the ACR and aerosol advection in this facility using the carbon dioxide (CO2) tracer gas method to elucidate the specific location and cause of the outbreak. These findings will guide our recommendations to the facility to prevent recurrence. Methods In August 2021, CO2 sensors were placed in 5 rooms where airborne infection was suspected, and the CO2 concentration was intentionally increased using dry ice, which was subsequently removed. The ACR was then estimated by applying the Seidel equation to the time-series changes in the CO2 concentration due to ventilation. By installing multiple sensors outside the room, advection outside the room was monitored simultaneously. Aerosol advection was verified using computer simulations. Although the windows were closed at the time of the outbreak, we conducted experiments under open-window conditions to quantify the effects of window opening. Results The ACR values at the time of the outbreak were estimated to be 2.0 to 6.8 h−1 in the rooms of the facility. A low-cost intervention of opening windows improved the ventilation frequency by a factor of 2.2 to 5.7. Ventilation depended significantly on the window-opening conditions (P values ranging from .001 to .03 for all rooms). Aerosol advection was detected from the private room to the day room in agreement with the simulation results. Considering that the individual who initiated the infection was in the private room on the day of infection, and several residents, who later became secondarily infected, were gathered in the day room, it was postulated that the infectious aerosol was transmitted by this air current. Conclusions The present results suggest that secondary infections can occur owing to aerosol advection driven by large-scale flow, even when the building design adheres to the ventilation guidelines established in Japan. Moreover, the CO2 tracer gas method facilitates the visualization of areas at a high risk of airborne infection and demonstrates the effectiveness of window opening, which contributes to improved facility operations and recurrence prevention.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.126
GPT teacher head0.448
Teacher spread0.322 · 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

Citations12
Published2022
Admission routes1
Has abstractyes

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