Governments worldwide have implemented non-pharmaceutical interventions(NPIs)to control the spread of coronavirus disease 2019(COVID-19),and it is crucial to accurately assess the effectiveness of such measures.Many s...Governments worldwide have implemented non-pharmaceutical interventions(NPIs)to control the spread of coronavirus disease 2019(COVID-19),and it is crucial to accurately assess the effectiveness of such measures.Many studies have quantified the risk of infection transmission and used simulations to compare the risk before and after the implementation of NPIs to judge policies’effectiveness.However,the choice of metric used to quantify the risk can lead to different conclusions regarding the effectiveness of a policy.In this study,we analyze the correlation between different transmission-risk metrics,pedestrian environments,and types of infectious diseases using simulation-generated data.Our findings reveal conflicting results among five different metric types in specific environments.More specifically,we observe that,when the randomness of pedestrian trajectories in indoor spaces is low,the closeness centrality exhibits a higher correlation coefficient with infection-based metrics than with contact-based metrics.Furthermore,even within the same pedestrian environment,the likelihood of discrepancies between infection-based metrics and other metrics increases for infectious diseases with low transmission rates.These results highlight the variability in the measured effectiveness of NPIs depending on the chosen metric.To evaluate NPIs accurately,facility managers should consider the type of facility and infectious disease and not solely rely on a single metric.This study provides a simulation model as a tool for future research and improves the reliability of pedestrian-simulation-based NPI effectiveness analysis methods.展开更多
AIM： To compare the clinical characteristics of infectious keratopathy in type 2 diabetes mellitus（T2DM） and nondiabetes mellitus（NDM） and to investigate risk factors for infectious keratopathy in T2DM patients. ...AIM： To compare the clinical characteristics of infectious keratopathy in type 2 diabetes mellitus（T2DM） and nondiabetes mellitus（NDM） and to investigate risk factors for infectious keratopathy in T2DM patients. METHODS： Totally 230 patients with T2DM and 168 with NDM diagnosed as infectious keratopathy were hospitalized at Qingdao Eye Hospital from 2001 to 2015. Data including sex, age, occupation, season, smoking and alcohol consumption habits, duration between onset and treatments, duration of hospitalization were collected. Initially identified indicators were analyzed with a multivariate logistic regression. Glycosylated hemoglobin A1 c（Hb A1 c） in patients with T2DM was analyzed. The infectious keratopathies in the two groups were categorized and compared.RESULTS： The diabetic group consisted of 146（63.5%） males and 84（36.5%） females. The NDM group consisted of 111（66.1%） males and 57（33.9%） females. There was no signigicantly difference in sex distribution between the two groups（P〉0.05）. There were significant differences in age, occupation of patients, season of the onset of diseases, duration between onset and treatment, and durations of hospitalization between the two groups（P〈0.05）. In most of the patients in the diabetic group, the duration between onsetand treatment was ≤3 mo, and most was ≥3 mo in the NDM group. Multivariate logistic regression analysis revealed that age and season were related to the development of corneal infection in the T2DM group（OR=1.709, 1.706）. In the T2DM group, Hb A1 c was 9.09%±2.12%. There were statistically significant differences in the incidences of bacterial keratitis and herpes simplex keratitis in the two groups（P〈0.05）, but no significant statistical difference was found between fungal keratitis and amoebic keratitis（P〉0.05）. CONCLUSION： Advanced age and the summer and winter seasons are identified as risk factors for infectious keratopathy in T2DM patients, and T2DM patients are more prone to bacterial keratitis.展开更多
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Ministry of Science and ICT(MSIT),Republic of Korea(1711185759).
文摘Governments worldwide have implemented non-pharmaceutical interventions(NPIs)to control the spread of coronavirus disease 2019(COVID-19),and it is crucial to accurately assess the effectiveness of such measures.Many studies have quantified the risk of infection transmission and used simulations to compare the risk before and after the implementation of NPIs to judge policies’effectiveness.However,the choice of metric used to quantify the risk can lead to different conclusions regarding the effectiveness of a policy.In this study,we analyze the correlation between different transmission-risk metrics,pedestrian environments,and types of infectious diseases using simulation-generated data.Our findings reveal conflicting results among five different metric types in specific environments.More specifically,we observe that,when the randomness of pedestrian trajectories in indoor spaces is low,the closeness centrality exhibits a higher correlation coefficient with infection-based metrics than with contact-based metrics.Furthermore,even within the same pedestrian environment,the likelihood of discrepancies between infection-based metrics and other metrics increases for infectious diseases with low transmission rates.These results highlight the variability in the measured effectiveness of NPIs depending on the chosen metric.To evaluate NPIs accurately,facility managers should consider the type of facility and infectious disease and not solely rely on a single metric.This study provides a simulation model as a tool for future research and improves the reliability of pedestrian-simulation-based NPI effectiveness analysis methods.
基金Supported by the National Natural Science Foundation of China(No.81500703)the Natural Science Foundation of Shandong Province(No.ZR2014HQ059No.ZR2015YL027)
文摘AIM： To compare the clinical characteristics of infectious keratopathy in type 2 diabetes mellitus（T2DM） and nondiabetes mellitus（NDM） and to investigate risk factors for infectious keratopathy in T2DM patients. METHODS： Totally 230 patients with T2DM and 168 with NDM diagnosed as infectious keratopathy were hospitalized at Qingdao Eye Hospital from 2001 to 2015. Data including sex, age, occupation, season, smoking and alcohol consumption habits, duration between onset and treatments, duration of hospitalization were collected. Initially identified indicators were analyzed with a multivariate logistic regression. Glycosylated hemoglobin A1 c（Hb A1 c） in patients with T2DM was analyzed. The infectious keratopathies in the two groups were categorized and compared.RESULTS： The diabetic group consisted of 146（63.5%） males and 84（36.5%） females. The NDM group consisted of 111（66.1%） males and 57（33.9%） females. There was no signigicantly difference in sex distribution between the two groups（P〉0.05）. There were significant differences in age, occupation of patients, season of the onset of diseases, duration between onset and treatment, and durations of hospitalization between the two groups（P〈0.05）. In most of the patients in the diabetic group, the duration between onsetand treatment was ≤3 mo, and most was ≥3 mo in the NDM group. Multivariate logistic regression analysis revealed that age and season were related to the development of corneal infection in the T2DM group（OR=1.709, 1.706）. In the T2DM group, Hb A1 c was 9.09%±2.12%. There were statistically significant differences in the incidences of bacterial keratitis and herpes simplex keratitis in the two groups（P〈0.05）, but no significant statistical difference was found between fungal keratitis and amoebic keratitis（P〉0.05）. CONCLUSION： Advanced age and the summer and winter seasons are identified as risk factors for infectious keratopathy in T2DM patients, and T2DM patients are more prone to bacterial keratitis.
