Fangcang shelter hospitals are modular,rapidly deployable facilities that play a vital role in pandemic response by providing centralized isolation and basic medical care for large patient populations.Artificial intel...Fangcang shelter hospitals are modular,rapidly deployable facilities that play a vital role in pandemic response by providing centralized isolation and basic medical care for large patient populations.Artificial intelligence(AI)has the potential to transform Fangcang shelter hospitals into intelligent,responsive systems that are capable of significantly improving emergency preparedness,operational efficiency,and patient outcomes.Key application areas include site selection and design optimization,clinical decision support,AI-assisted clinical documentation and patient engagement,intelligent robotics,and operational management.However,realizing AI's full potential requires overcoming several challenges,including limited data accessibility,privacy and governance concerns,inadequate algorithmic adaptability in dynamic emergency settings,insufficient transparency and accountability in AI-driven decisions,fragmented system architectures due to proprietary formats,high costs disproportionate to the temporary nature of Fangcang shelter hospitals,and hardware reliability in austere environments.Addressing these challenges demands standardized data-sharing frameworks,development of explainable and robust AI algorithms,clear ethical and legal oversight,interoperable modular system designs,and active collaboration among multidisciplinary stakeholders.展开更多
The coronavirus disease 2019(COVID-19)pandemic caused by frequently mutating severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)has had a worldwide impact.However,detailed data on the potential aerosol transmi...The coronavirus disease 2019(COVID-19)pandemic caused by frequently mutating severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)has had a worldwide impact.However,detailed data on the potential aerosol transmission of SARS-CoV-2 in real-world and controlled laboratory settings remain sparse.During the COVID-19 pandemic in Shanghai,China in 2022,samples were collected in a Fangcang shelter hospital,a large-scale temporary hospital rapidly built by converting the existing National Exhibition and Convention Center(Shanghai)into a health care facility.Aerosol samples at different sites and intervals around patients and in public areas,surface samples,and pharyngeal swab samples from corresponding patients were included.Samples were tested for SARS-CoV-2 using real-time quantitative polymerase chain reaction(RT-qPCR)assays,followed by sequencing if the cycle threshold(Ct)value was<30.The positivity rate for SARS-CoV-2 in aerosol samples was high in contaminated zones(37.5%,104/277),especially around the bed(41.2%,68/165)and near ventilation inlets(45.2%,14/31).The prevalence of SARS-CoV-2 around the bed,public areas,and air inlets of exhaust vents fluctuated and was closely related to the positivity rate among patients at corresponding sampling sites.Some surface samples of different personal protective equipment from medical staff had high positivity rates.Sixty sequences of joined ORF1ab and spike genes obtained from sixty samples represented two main clusters of Omicron SARS-CoV-2.There was consistency in virus sequences from the same patient and their environment,and the detected virus sequences matched those of virus strains in circulation during the collection periods,which indicated a high likelihood of cross-contamination in the Fangcang shelter hospital.In summary,the results provide a quantitative and real landscape of the aerosol transmission of SARS-CoV-2 and a patient-centered view of contamination in large and enclosed spaces and offer a useful guide for taking targeted measures to avoid nosocomial infections during the management of SARS-CoV-2 or other respiratory virus diseases in a Fangcang shelter hospital.展开更多
Objective:To analyze the epidemiological characteristics of COVID-19 cases(Omicron variant BA5.1.3)in a hotel Fangcang shelter hospital in Sanya,Hainan Province,and provide basis for optimizing epidemic prevention and...Objective:To analyze the epidemiological characteristics of COVID-19 cases(Omicron variant BA5.1.3)in a hotel Fangcang shelter hospital in Sanya,Hainan Province,and provide basis for optimizing epidemic prevention and control strategies.Methods:The epidemiological data of COVID-19 cases admitted to a hotel Fangcang shelter hospital in Sanya from August 10 to August 30 in 2022 were collected for descriptive epidemiological analysis.Results:By August 30,703 cases of COVID-19 had been treated in the hotel Fangcang shelter hospital.The epidemiological characteristics analysis showed that 328 cases were male,accounting for 46.7%,and 375 cases were female,accounting for 53.3%.The ratio of male to female was 0.87:1.The age range was 8 months to 85 years old,with a median of 37(20,49)years old.The majority of people aged 31-59 years old,accounting for 51.4%.Asymptomatic infection accounted for 39.8%,and mild infection accounted for 60.2%,the main clinical symptoms were cough 24.8%(105/423),fever 18.7%(79/423).8.8%of the infected people had a history of chronic basic diseases,and hypertension and diabetes were the most common.There were 416 infected patients discharged from hospital,and the median total hospital stay was 14(10,15)days.The proportion of people who did not receive COVID-19 vaccine was 10.1%,the proportion of people who completed one,two and three vaccination was 5.0%,36.3%and 48.6%respectively,and the proportion of people who completed two and three vaccinations among people ≥60 years old was only 10.1%and 8.8%.Conclusion:This strain was the novel coronavirus variant BA5.1.3,which was reported for the first time in China.It was more infectious and insidious,and generally susceptible to people of all ages.Therefore,it is necessary to strengthen personal prevention and control,and did a good job of external anti input and internal anti diffusion,and strengthen nucleic acid detection to realize timely detection and early treatment,and strengthen COVID-19 vaccination,to improve vaccination rate and reduce infection rate.展开更多
Most studies of coronavirus disease 2019(COVID-19)progression have focused on the transfer of patients within secondary or tertiary care hospitals from regular wards to intensive care units.Little is known about the r...Most studies of coronavirus disease 2019(COVID-19)progression have focused on the transfer of patients within secondary or tertiary care hospitals from regular wards to intensive care units.Little is known about the risk factors predicting the progression to severe COVID-19 among patients in community iso-lation,who are either asymptomatic or suffer from only mild to moderate symptoms.Using a multivari-able competing risk survival analysis,we identify several important predictors of progression to severe COVID-19—rather than to recovery—among patients in the largest community isolation center in Wuhan,China from 6 February 2020(when the center opened)to 9 March 2020(when it closed).All patients in community isolation in Wuhan were either asymptomatic or suffered from mild to moderate COVID-19 symptoms.We performed competing risk survival analysis on time-to-event data from a cohort study of all COVID-19 patients(n=1753)in the isolation center.The potential predictors we inves-tigated were the routine patient data collected upon admission to the isolation center:age,sex,respira-tory symptoms,gastrointestinal symptoms,general symptoms,and computed tomography(CT)scan signs.The main outcomes were time to severe COVID-19 or recovery.The factors predicting progression to severe COVID-19 were:male sex(hazard ratio(HR)=1.29,95%confidence interval(CI)1.04–1.58,p=0.018),young and old age,dyspnea(HR=1.58,95%CI 1.24–2.01,p<0.001),and CT signs of ground-glass opacity(HR=1.39,95%CI 1.04–1.86,p=0.024)and infiltrating shadows(HR=1.84,95%CI 1.22–2.78,p=0.004).The risk of progression was found to be lower among patients with nausea or vomiting(HR=0.53,95%CI 0.30–0.96,p=0.036)and headaches(HR=0.54,95%CI 0.29–0.99,p=0.046).Our results suggest that several factors that can be easily measured even in resource-poor set-tings(dyspnea,sex,and age)can be used to identify mild COVID-19 patients who are at increased risk of disease progression.Looking for CT signs of ground-glass opacity and infiltrating shadows may be an affordable option to support triage decisions in resource-rich settings.Common and unspecific symptoms(headaches,nausea,and vomiting)are likely to have led to the identification and subsequent community isolation of COVID-19 patients who were relatively unlikely to deteriorate.Future public health and clinical guidelines should build on this evidence to improve the screening,triage,and monitoring of COVID-19 patients who are asymtomatic or suffer from mild to moderate symptoms.展开更多
文摘Fangcang shelter hospitals are modular,rapidly deployable facilities that play a vital role in pandemic response by providing centralized isolation and basic medical care for large patient populations.Artificial intelligence(AI)has the potential to transform Fangcang shelter hospitals into intelligent,responsive systems that are capable of significantly improving emergency preparedness,operational efficiency,and patient outcomes.Key application areas include site selection and design optimization,clinical decision support,AI-assisted clinical documentation and patient engagement,intelligent robotics,and operational management.However,realizing AI's full potential requires overcoming several challenges,including limited data accessibility,privacy and governance concerns,inadequate algorithmic adaptability in dynamic emergency settings,insufficient transparency and accountability in AI-driven decisions,fragmented system architectures due to proprietary formats,high costs disproportionate to the temporary nature of Fangcang shelter hospitals,and hardware reliability in austere environments.Addressing these challenges demands standardized data-sharing frameworks,development of explainable and robust AI algorithms,clear ethical and legal oversight,interoperable modular system designs,and active collaboration among multidisciplinary stakeholders.
基金supported by National Key Research and Development Program of China(2019YFC1200500)supported by Emergency Key Program of Guangzhou Laboratory(EKPG21-01)supported by National Natural Science Foundation of China(32070166)。
文摘The coronavirus disease 2019(COVID-19)pandemic caused by frequently mutating severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)has had a worldwide impact.However,detailed data on the potential aerosol transmission of SARS-CoV-2 in real-world and controlled laboratory settings remain sparse.During the COVID-19 pandemic in Shanghai,China in 2022,samples were collected in a Fangcang shelter hospital,a large-scale temporary hospital rapidly built by converting the existing National Exhibition and Convention Center(Shanghai)into a health care facility.Aerosol samples at different sites and intervals around patients and in public areas,surface samples,and pharyngeal swab samples from corresponding patients were included.Samples were tested for SARS-CoV-2 using real-time quantitative polymerase chain reaction(RT-qPCR)assays,followed by sequencing if the cycle threshold(Ct)value was<30.The positivity rate for SARS-CoV-2 in aerosol samples was high in contaminated zones(37.5%,104/277),especially around the bed(41.2%,68/165)and near ventilation inlets(45.2%,14/31).The prevalence of SARS-CoV-2 around the bed,public areas,and air inlets of exhaust vents fluctuated and was closely related to the positivity rate among patients at corresponding sampling sites.Some surface samples of different personal protective equipment from medical staff had high positivity rates.Sixty sequences of joined ORF1ab and spike genes obtained from sixty samples represented two main clusters of Omicron SARS-CoV-2.There was consistency in virus sequences from the same patient and their environment,and the detected virus sequences matched those of virus strains in circulation during the collection periods,which indicated a high likelihood of cross-contamination in the Fangcang shelter hospital.In summary,the results provide a quantitative and real landscape of the aerosol transmission of SARS-CoV-2 and a patient-centered view of contamination in large and enclosed spaces and offer a useful guide for taking targeted measures to avoid nosocomial infections during the management of SARS-CoV-2 or other respiratory virus diseases in a Fangcang shelter hospital.
基金Hainan Province Science and Technology Special Fund(ZDKJ2021038)。
文摘Objective:To analyze the epidemiological characteristics of COVID-19 cases(Omicron variant BA5.1.3)in a hotel Fangcang shelter hospital in Sanya,Hainan Province,and provide basis for optimizing epidemic prevention and control strategies.Methods:The epidemiological data of COVID-19 cases admitted to a hotel Fangcang shelter hospital in Sanya from August 10 to August 30 in 2022 were collected for descriptive epidemiological analysis.Results:By August 30,703 cases of COVID-19 had been treated in the hotel Fangcang shelter hospital.The epidemiological characteristics analysis showed that 328 cases were male,accounting for 46.7%,and 375 cases were female,accounting for 53.3%.The ratio of male to female was 0.87:1.The age range was 8 months to 85 years old,with a median of 37(20,49)years old.The majority of people aged 31-59 years old,accounting for 51.4%.Asymptomatic infection accounted for 39.8%,and mild infection accounted for 60.2%,the main clinical symptoms were cough 24.8%(105/423),fever 18.7%(79/423).8.8%of the infected people had a history of chronic basic diseases,and hypertension and diabetes were the most common.There were 416 infected patients discharged from hospital,and the median total hospital stay was 14(10,15)days.The proportion of people who did not receive COVID-19 vaccine was 10.1%,the proportion of people who completed one,two and three vaccination was 5.0%,36.3%and 48.6%respectively,and the proportion of people who completed two and three vaccinations among people ≥60 years old was only 10.1%and 8.8%.Conclusion:This strain was the novel coronavirus variant BA5.1.3,which was reported for the first time in China.It was more infectious and insidious,and generally susceptible to people of all ages.Therefore,it is necessary to strengthen personal prevention and control,and did a good job of external anti input and internal anti diffusion,and strengthen nucleic acid detection to realize timely detection and early treatment,and strengthen COVID-19 vaccination,to improve vaccination rate and reduce infection rate.
基金supported by the Alexander von Humboldt Foundation in Germany and the Bill & Melinda Gates Foundation (Project INV-006261)supported by the National Center for Advancing Translational Sciences of the National Institutes of Health (KL2TR003143)+4 种基金supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor awardfunded by the German Federal Ministry of Education and Research, the European Union’s Research and Innovation Programme Horizon 2020the European & Developing Countries Clinical Trials Partnership (EDCTP)supported by the Sino-German Center for Research Promotion (Project C-0048), which is funded by the German Research Foundation (DFG)the National Natural Science Foundation of China (NSFC)
文摘Most studies of coronavirus disease 2019(COVID-19)progression have focused on the transfer of patients within secondary or tertiary care hospitals from regular wards to intensive care units.Little is known about the risk factors predicting the progression to severe COVID-19 among patients in community iso-lation,who are either asymptomatic or suffer from only mild to moderate symptoms.Using a multivari-able competing risk survival analysis,we identify several important predictors of progression to severe COVID-19—rather than to recovery—among patients in the largest community isolation center in Wuhan,China from 6 February 2020(when the center opened)to 9 March 2020(when it closed).All patients in community isolation in Wuhan were either asymptomatic or suffered from mild to moderate COVID-19 symptoms.We performed competing risk survival analysis on time-to-event data from a cohort study of all COVID-19 patients(n=1753)in the isolation center.The potential predictors we inves-tigated were the routine patient data collected upon admission to the isolation center:age,sex,respira-tory symptoms,gastrointestinal symptoms,general symptoms,and computed tomography(CT)scan signs.The main outcomes were time to severe COVID-19 or recovery.The factors predicting progression to severe COVID-19 were:male sex(hazard ratio(HR)=1.29,95%confidence interval(CI)1.04–1.58,p=0.018),young and old age,dyspnea(HR=1.58,95%CI 1.24–2.01,p<0.001),and CT signs of ground-glass opacity(HR=1.39,95%CI 1.04–1.86,p=0.024)and infiltrating shadows(HR=1.84,95%CI 1.22–2.78,p=0.004).The risk of progression was found to be lower among patients with nausea or vomiting(HR=0.53,95%CI 0.30–0.96,p=0.036)and headaches(HR=0.54,95%CI 0.29–0.99,p=0.046).Our results suggest that several factors that can be easily measured even in resource-poor set-tings(dyspnea,sex,and age)can be used to identify mild COVID-19 patients who are at increased risk of disease progression.Looking for CT signs of ground-glass opacity and infiltrating shadows may be an affordable option to support triage decisions in resource-rich settings.Common and unspecific symptoms(headaches,nausea,and vomiting)are likely to have led to the identification and subsequent community isolation of COVID-19 patients who were relatively unlikely to deteriorate.Future public health and clinical guidelines should build on this evidence to improve the screening,triage,and monitoring of COVID-19 patients who are asymtomatic or suffer from mild to moderate symptoms.
