Giuseppe
Emeritus
J Infect. 2009 Oct 6. [Epub ahead of print]
Probabilistic indoor transmission modeling for influenza (sub)type viruses in Taiwan.
Chen SC, Liao CM. - Department of Public Health, Chung Shan Medical University, Taichung, Taiwan 40242, ROC; Department of Family and Community Medicine, Chung Shan Medical University Hospital, Taichung, Taiwan 40242, ROC.
OBJECTIVES:
To use a probability based transmission modeling approach to examine the influenza risk of infection virus in indoor environments. This was based on 10 years of data gathered from influenza-like illness sentinel physician and laboratory surveillance, and experimental viral shedding data in Taiwan.
METHODS:
We integrated sentinel physician-reported cases and positive rates of influenza A (H1N1), A (H3N2), influenza B, and respiratory syncytial virus in Taiwan using the Wells-Riley mathematical model. This model incorporates environmental factors such as room ventilation and breathing rates. We also linked vaccine match rate with related transmission estimations to predict the controllable potential using a control model characterized by basic reproduction number (R(0)) and proportion of asymptomatic infections (theta).
RESULTS:
A quantitative framework was developed to better understand the infection risk and R(0) estimates of A (H1N1), A (H3N2), and B viruses. The viral concentration in human fluid was linked successfully with quantum generation rates to estimate virus-specific infection risks. Our results revealed that A (H3N2) virus had a higher transmissibility and uncontrollable potential than the A (H1N1) and B viruses.
CONCLUSIONS:
Probabilistic transmission model can incorporate virus-specific data on experimental viral shedding, long-term sentinel physician and laboratory surveillance to predict virus-specific infection risks in Taiwan.
PMID: 19818365 [PubMed - as supplied by publisher]
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Probabilistic indoor transmission modeling for influenza (sub)type viruses in Taiwan.
Chen SC, Liao CM. - Department of Public Health, Chung Shan Medical University, Taichung, Taiwan 40242, ROC; Department of Family and Community Medicine, Chung Shan Medical University Hospital, Taichung, Taiwan 40242, ROC.
OBJECTIVES:
To use a probability based transmission modeling approach to examine the influenza risk of infection virus in indoor environments. This was based on 10 years of data gathered from influenza-like illness sentinel physician and laboratory surveillance, and experimental viral shedding data in Taiwan.
METHODS:
We integrated sentinel physician-reported cases and positive rates of influenza A (H1N1), A (H3N2), influenza B, and respiratory syncytial virus in Taiwan using the Wells-Riley mathematical model. This model incorporates environmental factors such as room ventilation and breathing rates. We also linked vaccine match rate with related transmission estimations to predict the controllable potential using a control model characterized by basic reproduction number (R(0)) and proportion of asymptomatic infections (theta).
RESULTS:
A quantitative framework was developed to better understand the infection risk and R(0) estimates of A (H1N1), A (H3N2), and B viruses. The viral concentration in human fluid was linked successfully with quantum generation rates to estimate virus-specific infection risks. Our results revealed that A (H3N2) virus had a higher transmissibility and uncontrollable potential than the A (H1N1) and B viruses.
CONCLUSIONS:
Probabilistic transmission model can incorporate virus-specific data on experimental viral shedding, long-term sentinel physician and laboratory surveillance to predict virus-specific infection risks in Taiwan.
PMID: 19818365 [PubMed - as supplied by publisher]
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