Propensity score (PS) adjustment can control confounding effects and reduce bias when estimating treatment effects in non-randomized trials or observational studies. PS methods are becoming increasingly used to estima...Propensity score (PS) adjustment can control confounding effects and reduce bias when estimating treatment effects in non-randomized trials or observational studies. PS methods are becoming increasingly used to estimate causal effects, including when the sample size is small compared to the number of confounders. With numerous confounders, quasi-complete separation can easily occur in logistic regression used for estimating the PS, but this has not been addressed. We focused on a Bayesian PS method to address the limitations of quasi-complete separation faced by small trials. Bayesian methods are useful because they estimate the PS and causal effects simultaneously while considering the uncertainty of the PS by modelling it as a latent variable. In this study, we conducted simulations to evaluate the performance of Bayesian simultaneous PS estimation by considering the specification of prior distributions for model comparison. We propose a method to improve predictive performance with discrete outcomes in small trials. We found that the specification of prior distributions assigned to logistic regression coefficients was more important in the second step than in the first step, even when there was a quasi-complete separation in the first step. Assigning Cauchy (0, 2.5) to coefficients improved the predictive performance for estimating causal effects and improving the balancing properties of the confounder.展开更多
Objective: To develop an illness severity score that predicts short-term mortality, based on a small number of readily available measurements, and overcomes limitations of the SOFA score, for use in research involving...Objective: To develop an illness severity score that predicts short-term mortality, based on a small number of readily available measurements, and overcomes limitations of the SOFA score, for use in research involving large-scale electronic health records. Design: Retrospective analysis of electronic records for 37,739 adult inpatients. Setting: A single tertiary care hospital system from 2016-2022. Patients: 37,739 adult ICU patients. Interventions: IMPS was developed using logistic regression with the 6 SOFA components, age, sex and missingness indicators as predictors, and 10-day mortality as the outcome. This was compared with SOFA with median imputation. Measurements and Main Results: Discrimination was evaluated by AUROC, calibration by comparing predicted and observed mortality. IMPS showed excellent discrimination (AUROC 0.80) and calibration. It outperformed SOFA alone (AUROC 0.70) and with age/sex (0.74). Conclusions: By retaining continuous data, adding age, allowing for missingness, and optimizing weights based on empirical mortality association, IMPS achieved substantially better mortality prediction than the original SOFA.展开更多
Professionalism is crucial in all professions and is particularly important in the medical field.Measuring students' perceptions of professionalism can help to form education targeting the enhancement of professio...Professionalism is crucial in all professions and is particularly important in the medical field.Measuring students' perceptions of professionalism can help to form education targeting the enhancement of professionalism.This study aimed to validate an effective assessment tool for the measurement of medical students5 perceptions of medical professionalism in China's Mainland.The cross-sectional survey was conducted in three medical colleges in Guangdong,China.Of the 2103 eligible medical students,1976 responded,and 1856 questionnaires were deemed valid.Students from clinical medicine in these three medical colleges were randomly selected by cluster sampling.First,a Simplified Chinese Version questionnaire to measure Student's Perception of Medical Professionalism (SCV-SPMP) was constructed.Second,questionnaires from 1856 students majoring in clinical medicine at three medical colleges were included in the analysis.Third,exploratory factor analysis,Cronbach's alpha,item-subscale correlation,and confirmatory factor analysis were conducted to test the validity and reliability of the SCV-SPMP.Nine items were eliminated following exploratory factor analysis,and four subscales were extracted from the analysis.All internal consistency reliability exceeded the minimum standard.The overall Cronbach's alpha was 0.94,and four subscales' alphas were 0.82 (Accountability and excellence),0.81 (Duty),0.89 (Honor and integrity),and 0.85 (Practice habits and respect for others),respectively.The model fit was good.The convergent validity and discriminant validity were acceptable.The modified SCVSPMP was found to be a valid and reliable tool to capture the main features of Chinese students' perceptions of medical professionalism in four dimensions,and it provides a quantitative method for the measurement of the students' perceptions in China's Mainland..展开更多
To the Editor: Hypoxic hepatitis(HH), also known as ischemic hepatitis or shock liver, is a liver injury characterized by necrosis of centrilobular hepatocytes with a rapid increase in serum aminotransferase levels. T...To the Editor: Hypoxic hepatitis(HH), also known as ischemic hepatitis or shock liver, is a liver injury characterized by necrosis of centrilobular hepatocytes with a rapid increase in serum aminotransferase levels. The incidence rate of HH among patients in the intensive care unit(ICU) was found to be 0.9%-11.9% [1]. Occurrence of HH appears to have a significant impact on the clinical outcome.展开更多
Background Coronavirus disease 2019(COVID-19)tends to have mild presentations in children.However,severe and critical cases do arise in the pediatric population with debilitating systemic impacts and can be fatal at t...Background Coronavirus disease 2019(COVID-19)tends to have mild presentations in children.However,severe and critical cases do arise in the pediatric population with debilitating systemic impacts and can be fatal at times,meriting further attention from clinicians.Meanwhile,the intricate interactions between the pathogen virulence factors and host defense mechanisms are believed to play indispensable roles in severe COVID-19 pathophysiology but remain incompletely understood.Data sources A comprehensive literature review was conducted for pertinent publications by reviewers independently using the PubMed,Embase,and Wanfang databases.Searched keywords included“COVID-19 in children”,“severe pediatric COVID-19”,and“critical illness in children with COVID-19”.Results Risks of developing severe COVID-19 in children escalate with increasing numbers of co-morbidities and an unvaccinated status.Acute respiratory distress stress and necrotizing pneumonia are prominent pulmonary manifestations,while various forms of cardiovascular and neurological involvement may also be seen.Multiple immunological processes are implicated in the host response to COVID-19 including the type I interferon and inflammasome pathways,whose dysregulation in severe and critical diseases translates into adverse clinical manifestations.Multisystem inflammatory syndrome in children(MIS-C),a potentially life-threatening immune-mediated condition chronologically associated with COVID-19 exposure,denotes another scientific and clinical conundrum that exemplifies the complexity of pediatric immunity.Despite the considerable dissimilarities between the pediatric and adult immune systems,clinical trials dedicated to children are lacking and current management recommendations are largely adapted from adult guidelines.Conclusions Severe pediatric COVID-19 can affect multiple organ systems.The dysregulated immune pathways in severe COVID-19 shape the disease course,epitomize the vast functional diversity of the pediatric immune system and highlight the immunophenotypical differences between children and adults.Consequently,further research may be warranted to adequately address them in pediatric-specific clinical practice guidelines.展开更多
Partial endothelial-to-mesenchymal transition(EndMT)is an intermediate phenotype observed in endothelial cells(ECs)undergoing a transition toward a mesenchymal state to support neovascularization during(patho)physiolo...Partial endothelial-to-mesenchymal transition(EndMT)is an intermediate phenotype observed in endothelial cells(ECs)undergoing a transition toward a mesenchymal state to support neovascularization during(patho)physiological angiogenesis.Here,we investigated the occurrence of partial EndMT in ECs under hypoxic/ischemic conditions and identified general transcription factor IIH subunit 4(GTF2H4)as a positive regulator of this process.In addition,we discovered that GTF2H4 collaborates with its target protein excision repair cross-complementation group 3(ERCC3)to co-regulate partial EndMT.Furthermore,by using phosphorylation proteomics and site-directed mutagenesis,we demonstrated that GTF2H4 was involved in the phosphorylation of receptor coactivator 3(NCOA3)at serine 1330,which promoted the interaction between NCOA3 and p65,resulting in the transcriptional activation of NF-κB and the NF-kB/Snail signaling axis during partial EndMT.In vivo experiments confirmed that GTF2H4 significantly promoted partial EndMT and angiogenesis after ischemic injury.Collectively,our findings reveal that targeting GTF2H4 is promising for tissue repair and offers potential opportunities for treating hypoxic/ischemic diseases.展开更多
Background SARS-CoV-2 continues to mutate over time,and reports on children infected with Omicron BA.5 are limited.We aimed to analyze the specific symptoms of Omicron-infected children and to improve patient care.Met...Background SARS-CoV-2 continues to mutate over time,and reports on children infected with Omicron BA.5 are limited.We aimed to analyze the specific symptoms of Omicron-infected children and to improve patient care.Methods We selected 315 consecutively hospitalized children with Omicron BA.5 and 16,744 non-Omicron-infected febrile children visiting the fever clinic at our hospital between December 8 and 30,2022.Specific convulsions and body temperatures were compared between the two cohorts.We analyzed potential associations between convulsions and vaccination,and additionally evaluated the brain damage among severe Omicron-infected children.Results Convulsion rates(97.5%vs.4.3%,P<0.001)and frequencies(median:2.0 vs.1.6,P<0.001)significantly differed between Omicron-infected and non-Omicron-infected febrile children.The body temperatures of Omicron-infected children were significantly higher during convulsions than when they were not convulsing and those of non-Omicron-infected febrile children during convulsions(median:39.5 vs.38.2 and 38.6℃,both P<0.001).In the three Omicron-subgroups,the temperature during convulsions was proportional to the percentage of patients and significantly differed(P<0.001),while not in the three non-Omicron-subgroups(P=0.244).The convulsion frequency was lower in the 55 vaccinated children compared to the 260 non-vaccinated children(average:1.8 vs.2.1,P<0.001).The vaccination dose and convulsion frequency in Omicron-infected children were significantly correlated(P<0.001).Fifteen of the 112 severe Omicron cases had brain damage.Conclusions Omicron-infected children experience higher body temperatures and frequencies during convulsions than those of non-Omicron-infected febrile children.We additionally found evidence of brain damage caused by infection with omicron BA.5.Vaccination and prompt fever reduction may relieve symptoms.展开更多
Summary What is already known about this topic?During the coronavirus disease 2019(COVID-19)pandemic,tremendous efforts have been made in countries to suppress epidemic peaks and strengthen hospital services to avoid ...Summary What is already known about this topic?During the coronavirus disease 2019(COVID-19)pandemic,tremendous efforts have been made in countries to suppress epidemic peaks and strengthen hospital services to avoid hospital strain and ultimately reduce the risk of death from COVID-19.However,there is limited empirical evidence that hospital strain increases COVID-19 deaths.展开更多
Dear Editor,Recent study showed that around 80%of coronavirus disease-19(COVID-19)patients are moderate cases who will recover with or without conventional treatment,while the remaining 20%developed severe disease req...Dear Editor,Recent study showed that around 80%of coronavirus disease-19(COVID-19)patients are moderate cases who will recover with or without conventional treatment,while the remaining 20%developed severe disease requiring intensive care.1 Early and accurate screening of new COVID-19 patients to identify those who will develop severe disease will facilitate decision-making on appropriate treatment regimens and reasonable allocation of limited healthcare resources.Therefore,novel predictive factors for disease progress from moderate to severe are urgently needed.展开更多
Background.Prediction of mortality risk in intensive care units(ICU)is an important task.Data-driven methods such as scoring systems,machine learning methods,and deep learning methods have been investigated for a long...Background.Prediction of mortality risk in intensive care units(ICU)is an important task.Data-driven methods such as scoring systems,machine learning methods,and deep learning methods have been investigated for a long time.However,few datadriven methods are specially developed for pediatric ICU.In this paper,we aim to amend this gap—build a simple yet effective linear machine learning model from a number of hand-crafted features for mortality prediction in pediatric ICU.Methods.We use a recently released publicly available pediatric ICU dataset named pediatric intensive care(PIC)from Children’s Hospital of Zhejiang University School of Medicine in China.Unlike previous sophisticated machine learning methods,we want our method to keep simple that can be easily understood by clinical staffs.Thus,an ensemble step-wise feature ranking and selection method is proposed to select a small subset of effective features from the entire feature set.A logistic regression classifier is built upon selected features for mortality prediction.Results.The final predictive linear model with 11 features achieves a 0.7531 ROC-AUC score on the hold-out test set,which is comparable with a logistic regression classifier using all 397 features(0.7610 ROC-AUC score)and is higher than the existing well known pediatric mortality risk scorer PRISM III(0.6895 ROC-AUC score).Conclusions.Our method improves feature ranking and selection by utilizing an ensemble method while keeping a simple linear form of the predictive model and therefore achieves better generalizability and performance on mortality prediction in pediatric ICU.展开更多
What is already known about this topic?After the initial coronavirus disease 2019(COVID-19)outbreak in Wuhan,China,the outbreaks during the dynamic-zero policy period in the mainland of China have not been systematica...What is already known about this topic?After the initial coronavirus disease 2019(COVID-19)outbreak in Wuhan,China,the outbreaks during the dynamic-zero policy period in the mainland of China have not been systematically documented.What is added by this report?We summarized the characteristics of 74 imported COVID-19 outbreaks between March 19,2020 and December 31,2021.All outbreaks of early severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)variants were successfully contained with the aid of nucleic acid testing,modern communication technologies,and non-pharmacological interventions.What are the implications for public health practice?These findings provide us with confidence for the containment of future emerging infectious diseases alike at early stages to prevent pandemics or to win time to gain experience,develop vaccines and drugs,vaccinate people,and wait for the possible lessening of the virus’pathogenicity.展开更多
文摘Propensity score (PS) adjustment can control confounding effects and reduce bias when estimating treatment effects in non-randomized trials or observational studies. PS methods are becoming increasingly used to estimate causal effects, including when the sample size is small compared to the number of confounders. With numerous confounders, quasi-complete separation can easily occur in logistic regression used for estimating the PS, but this has not been addressed. We focused on a Bayesian PS method to address the limitations of quasi-complete separation faced by small trials. Bayesian methods are useful because they estimate the PS and causal effects simultaneously while considering the uncertainty of the PS by modelling it as a latent variable. In this study, we conducted simulations to evaluate the performance of Bayesian simultaneous PS estimation by considering the specification of prior distributions for model comparison. We propose a method to improve predictive performance with discrete outcomes in small trials. We found that the specification of prior distributions assigned to logistic regression coefficients was more important in the second step than in the first step, even when there was a quasi-complete separation in the first step. Assigning Cauchy (0, 2.5) to coefficients improved the predictive performance for estimating causal effects and improving the balancing properties of the confounder.
文摘Objective: To develop an illness severity score that predicts short-term mortality, based on a small number of readily available measurements, and overcomes limitations of the SOFA score, for use in research involving large-scale electronic health records. Design: Retrospective analysis of electronic records for 37,739 adult inpatients. Setting: A single tertiary care hospital system from 2016-2022. Patients: 37,739 adult ICU patients. Interventions: IMPS was developed using logistic regression with the 6 SOFA components, age, sex and missingness indicators as predictors, and 10-day mortality as the outcome. This was compared with SOFA with median imputation. Measurements and Main Results: Discrimination was evaluated by AUROC, calibration by comparing predicted and observed mortality. IMPS showed excellent discrimination (AUROC 0.80) and calibration. It outperformed SOFA alone (AUROC 0.70) and with age/sex (0.74). Conclusions: By retaining continuous data, adding age, allowing for missingness, and optimizing weights based on empirical mortality association, IMPS achieved substantially better mortality prediction than the original SOFA.
文摘Professionalism is crucial in all professions and is particularly important in the medical field.Measuring students' perceptions of professionalism can help to form education targeting the enhancement of professionalism.This study aimed to validate an effective assessment tool for the measurement of medical students5 perceptions of medical professionalism in China's Mainland.The cross-sectional survey was conducted in three medical colleges in Guangdong,China.Of the 2103 eligible medical students,1976 responded,and 1856 questionnaires were deemed valid.Students from clinical medicine in these three medical colleges were randomly selected by cluster sampling.First,a Simplified Chinese Version questionnaire to measure Student's Perception of Medical Professionalism (SCV-SPMP) was constructed.Second,questionnaires from 1856 students majoring in clinical medicine at three medical colleges were included in the analysis.Third,exploratory factor analysis,Cronbach's alpha,item-subscale correlation,and confirmatory factor analysis were conducted to test the validity and reliability of the SCV-SPMP.Nine items were eliminated following exploratory factor analysis,and four subscales were extracted from the analysis.All internal consistency reliability exceeded the minimum standard.The overall Cronbach's alpha was 0.94,and four subscales' alphas were 0.82 (Accountability and excellence),0.81 (Duty),0.89 (Honor and integrity),and 0.85 (Practice habits and respect for others),respectively.The model fit was good.The convergent validity and discriminant validity were acceptable.The modified SCVSPMP was found to be a valid and reliable tool to capture the main features of Chinese students' perceptions of medical professionalism in four dimensions,and it provides a quantitative method for the measurement of the students' perceptions in China's Mainland..
基金supported by grants from the National Natural Science Foundation of China (81571475, 81471480, 81671956 and 81630037)the Zhejiang Provincial Program for the Cultivation of High-level Innovative Health Talentsthe Key Program of the Independent Design Project of National Clinical Research Center for Child Health (G20B0009)。
文摘To the Editor: Hypoxic hepatitis(HH), also known as ischemic hepatitis or shock liver, is a liver injury characterized by necrosis of centrilobular hepatocytes with a rapid increase in serum aminotransferase levels. The incidence rate of HH among patients in the intensive care unit(ICU) was found to be 0.9%-11.9% [1]. Occurrence of HH appears to have a significant impact on the clinical outcome.
文摘Background Coronavirus disease 2019(COVID-19)tends to have mild presentations in children.However,severe and critical cases do arise in the pediatric population with debilitating systemic impacts and can be fatal at times,meriting further attention from clinicians.Meanwhile,the intricate interactions between the pathogen virulence factors and host defense mechanisms are believed to play indispensable roles in severe COVID-19 pathophysiology but remain incompletely understood.Data sources A comprehensive literature review was conducted for pertinent publications by reviewers independently using the PubMed,Embase,and Wanfang databases.Searched keywords included“COVID-19 in children”,“severe pediatric COVID-19”,and“critical illness in children with COVID-19”.Results Risks of developing severe COVID-19 in children escalate with increasing numbers of co-morbidities and an unvaccinated status.Acute respiratory distress stress and necrotizing pneumonia are prominent pulmonary manifestations,while various forms of cardiovascular and neurological involvement may also be seen.Multiple immunological processes are implicated in the host response to COVID-19 including the type I interferon and inflammasome pathways,whose dysregulation in severe and critical diseases translates into adverse clinical manifestations.Multisystem inflammatory syndrome in children(MIS-C),a potentially life-threatening immune-mediated condition chronologically associated with COVID-19 exposure,denotes another scientific and clinical conundrum that exemplifies the complexity of pediatric immunity.Despite the considerable dissimilarities between the pediatric and adult immune systems,clinical trials dedicated to children are lacking and current management recommendations are largely adapted from adult guidelines.Conclusions Severe pediatric COVID-19 can affect multiple organ systems.The dysregulated immune pathways in severe COVID-19 shape the disease course,epitomize the vast functional diversity of the pediatric immune system and highlight the immunophenotypical differences between children and adults.Consequently,further research may be warranted to adequately address them in pediatric-specific clinical practice guidelines.
基金This work was supported by the National Natural Science Foundation of China(82170334 and 81870182)。
文摘Partial endothelial-to-mesenchymal transition(EndMT)is an intermediate phenotype observed in endothelial cells(ECs)undergoing a transition toward a mesenchymal state to support neovascularization during(patho)physiological angiogenesis.Here,we investigated the occurrence of partial EndMT in ECs under hypoxic/ischemic conditions and identified general transcription factor IIH subunit 4(GTF2H4)as a positive regulator of this process.In addition,we discovered that GTF2H4 collaborates with its target protein excision repair cross-complementation group 3(ERCC3)to co-regulate partial EndMT.Furthermore,by using phosphorylation proteomics and site-directed mutagenesis,we demonstrated that GTF2H4 was involved in the phosphorylation of receptor coactivator 3(NCOA3)at serine 1330,which promoted the interaction between NCOA3 and p65,resulting in the transcriptional activation of NF-κB and the NF-kB/Snail signaling axis during partial EndMT.In vivo experiments confirmed that GTF2H4 significantly promoted partial EndMT and angiogenesis after ischemic injury.Collectively,our findings reveal that targeting GTF2H4 is promising for tissue repair and offers potential opportunities for treating hypoxic/ischemic diseases.
基金supported by the Science and Technology Planning Project of Guangdong Province(No.2020B1111170001)The funder had no role in the study design,data collection and analysis,decision to publish,or preparation of the manuscript.
文摘Background SARS-CoV-2 continues to mutate over time,and reports on children infected with Omicron BA.5 are limited.We aimed to analyze the specific symptoms of Omicron-infected children and to improve patient care.Methods We selected 315 consecutively hospitalized children with Omicron BA.5 and 16,744 non-Omicron-infected febrile children visiting the fever clinic at our hospital between December 8 and 30,2022.Specific convulsions and body temperatures were compared between the two cohorts.We analyzed potential associations between convulsions and vaccination,and additionally evaluated the brain damage among severe Omicron-infected children.Results Convulsion rates(97.5%vs.4.3%,P<0.001)and frequencies(median:2.0 vs.1.6,P<0.001)significantly differed between Omicron-infected and non-Omicron-infected febrile children.The body temperatures of Omicron-infected children were significantly higher during convulsions than when they were not convulsing and those of non-Omicron-infected febrile children during convulsions(median:39.5 vs.38.2 and 38.6℃,both P<0.001).In the three Omicron-subgroups,the temperature during convulsions was proportional to the percentage of patients and significantly differed(P<0.001),while not in the three non-Omicron-subgroups(P=0.244).The convulsion frequency was lower in the 55 vaccinated children compared to the 260 non-vaccinated children(average:1.8 vs.2.1,P<0.001).The vaccination dose and convulsion frequency in Omicron-infected children were significantly correlated(P<0.001).Fifteen of the 112 severe Omicron cases had brain damage.Conclusions Omicron-infected children experience higher body temperatures and frequencies during convulsions than those of non-Omicron-infected febrile children.We additionally found evidence of brain damage caused by infection with omicron BA.5.Vaccination and prompt fever reduction may relieve symptoms.
基金the Shenzhen Science and Technology Programs(JSGG20220301090202005,KQTD20190929172835662).
文摘Summary What is already known about this topic?During the coronavirus disease 2019(COVID-19)pandemic,tremendous efforts have been made in countries to suppress epidemic peaks and strengthen hospital services to avoid hospital strain and ultimately reduce the risk of death from COVID-19.However,there is limited empirical evidence that hospital strain increases COVID-19 deaths.
基金supported by Guangdong Provincial Novel Coronavirus Scientific and Technological Project(2020111107001[B.D.])National Science and Technology Major Project of the Ministry of Science and Technology of China(2017ZX10103011[B.D.]).
文摘Dear Editor,Recent study showed that around 80%of coronavirus disease-19(COVID-19)patients are moderate cases who will recover with or without conventional treatment,while the remaining 20%developed severe disease requiring intensive care.1 Early and accurate screening of new COVID-19 patients to identify those who will develop severe disease will facilitate decision-making on appropriate treatment regimens and reasonable allocation of limited healthcare resources.Therefore,novel predictive factors for disease progress from moderate to severe are urgently needed.
文摘Background.Prediction of mortality risk in intensive care units(ICU)is an important task.Data-driven methods such as scoring systems,machine learning methods,and deep learning methods have been investigated for a long time.However,few datadriven methods are specially developed for pediatric ICU.In this paper,we aim to amend this gap—build a simple yet effective linear machine learning model from a number of hand-crafted features for mortality prediction in pediatric ICU.Methods.We use a recently released publicly available pediatric ICU dataset named pediatric intensive care(PIC)from Children’s Hospital of Zhejiang University School of Medicine in China.Unlike previous sophisticated machine learning methods,we want our method to keep simple that can be easily understood by clinical staffs.Thus,an ensemble step-wise feature ranking and selection method is proposed to select a small subset of effective features from the entire feature set.A logistic regression classifier is built upon selected features for mortality prediction.Results.The final predictive linear model with 11 features achieves a 0.7531 ROC-AUC score on the hold-out test set,which is comparable with a logistic regression classifier using all 397 features(0.7610 ROC-AUC score)and is higher than the existing well known pediatric mortality risk scorer PRISM III(0.6895 ROC-AUC score).Conclusions.Our method improves feature ranking and selection by utilizing an ensemble method while keeping a simple linear form of the predictive model and therefore achieves better generalizability and performance on mortality prediction in pediatric ICU.
基金Supported by the Shenzhen Science and Technology Programs(RKX20210901150004012,KQTD20190929172835662,JSGG20220301090202005).
文摘What is already known about this topic?After the initial coronavirus disease 2019(COVID-19)outbreak in Wuhan,China,the outbreaks during the dynamic-zero policy period in the mainland of China have not been systematically documented.What is added by this report?We summarized the characteristics of 74 imported COVID-19 outbreaks between March 19,2020 and December 31,2021.All outbreaks of early severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)variants were successfully contained with the aid of nucleic acid testing,modern communication technologies,and non-pharmacological interventions.What are the implications for public health practice?These findings provide us with confidence for the containment of future emerging infectious diseases alike at early stages to prevent pandemics or to win time to gain experience,develop vaccines and drugs,vaccinate people,and wait for the possible lessening of the virus’pathogenicity.
