인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
We estimated the hourly probability of airborne severe acute respiratory coronavirus 2 (SARS-CoV-2) transmission and further the estimated number of persons at transmission risk in a day care centre by calculating the inhaled dose for airborne pathogens based on their concentration, exposure time and activity. Information about the occupancy and activity of the rooms was collected from day care centre personnel and building characteristics were obtained from the design values. The generation rate of pathogens was calculated as a product of viral load of the respiratory fluids and the emission of the exhaled airborne particles, considering the prevalence of the disease and the activity of the individuals. A well-mixed model was used in the estimation of the concentration of pathogens in the air. The Wells-Riley model was used for infection probability. The approach presented in this study was utilised in the identification of hot spots and critical events in the day care centre. Large variation in the infection probabilities and estimated number of persons at transmission risk was observed when modelling a normal day at the centre. The estimated hourly infection probabilities between the worst hour in the worst room and the best hour in the best room varied in the ratio of 100:1. Similarly, the number of persons at transmission risk between the worst and best cases varied in the ratio 1000:1. Although there are uncertainties in the input values affecting the absolute risk estimates the model proved to be useful in ranking and identifying the hot spots and events in the building and implementing effective control measures.
#Transmission (telecommunications)
#Airborne transmission
#Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
#Environmental science
#Coronavirus disease 2019 (COVID-19)
#Ranking (information retrieval)
#Statistics
#Medicine
#Estimation
#Risk assessment
#Environmental health
#Mathematics
#Disease
#Internal medicine
#Engineering
#Computer science
#Infectious disease (medical specialty)
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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