共检索10条数据Total：10
2020-04-09
State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China. hongzhang@rcees.ac.cn.;University of Chinese Academy of Sciences, Beijing 100049, China.;State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.;University of Chinese Academy of Sciences, Beijing 100049, China.;State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, Hubei 430072, China.;University of Chinese Academy of Sciences, Beijing 100049, China.;Changjiang Water Resources Protection Institute, Wuhan, Hubei 430051, China.
2020-04-09
State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China. hongzhang@rcees.ac.cn.;University of Chinese Academy of Sciences, Beijing 100049, China.;State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.;University of Chinese Academy of Sciences, Beijing 100049, China.;State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, Hubei 430072, China.;University of Chinese Academy of Sciences, Beijing 100049, China.;Changjiang Water Resources Protection Institute, Wuhan, Hubei 430051, China.
2020-04-05
Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China.;Zhuhai Center for Disease Control and Prevention, Zhuhai, China.;Dermatology Hospital of Southern Medical University, Guangzhou, China; University of North Carolina Project-China, Guangzhou 510095, China. Electronic address: Weiming_tang@med.unc.edu.
2020-04-05
Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China.;Zhuhai Center for Disease Control and Prevention, Zhuhai, China.;Dermatology Hospital of Southern Medical University, Guangzhou, China; University of North Carolina Project-China, Guangzhou 510095, China. Electronic address: Weiming_tang@med.unc.edu.
2020-03-18
Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.;Institute for Global Health Policy Research, Bureau of International Health Cooperation, National Center for Global Health and Medicine, Tokyo, Japan.;Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.;International Health Care Center, National Center for Global Health and Medicine, Tokyo, Japan.
To assess the effectiveness of response strategies of avoiding large gatherings or crowded areas and to predict the spread of COVID-19 infections in Japan, we developed a stochastic transmission model by extending the Susceptible-Infected-Removed (SIR) epidemiological model with an additional modeling of the individual action on whether to stay away from the crowded areas. The population were divided into three compartments: Susceptible, Infected, Removed. Susceptible transitions to Infected every hour with a probability determined by the ratio of Infected and the congestion of area. The total area consists of three zones crowded zone, mid zone and uncrowded zone, with different infection probabilities characterized by the number of people gathered there. The time for each people to spend in the crowded zone is curtailed by 0, 2, 4, 6, 7, and 8 hours, and the time spent in mid zone is extended accordingly. This simulation showed that the number of Infected and Removed will increase
2020-03-18
Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.;Institute for Global Health Policy Research, Bureau of International Health Cooperation, National Center for Global Health and Medicine, Tokyo, Japan.;Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.;International Health Care Center, National Center for Global Health and Medicine, Tokyo, Japan.
To assess the effectiveness of response strategies of avoiding large gatherings or crowded areas and to predict the spread of COVID-19 infections in Japan, we developed a stochastic transmission model by extending the Susceptible-Infected-Removed (SIR) epidemiological model with an additional modeling of the individual action on whether to stay away from the crowded areas. The population were divided into three compartments: Susceptible, Infected, Removed. Susceptible transitions to Infected every hour with a probability determined by the ratio of Infected and the congestion of area. The total area consists of three zones crowded zone, mid zone and uncrowded zone, with different infection probabilities characterized by the number of people gathered there. The time for each people to spend in the crowded zone is curtailed by 0, 2, 4, 6, 7, and 8 hours, and the time spent in mid zone is extended accordingly. This simulation showed that the number of Infected and Removed will increase
2021-11-24
Division of Rheumatology, Department of Medicine, Columbia University Irving Medical Center, 630 West 168th Street, P&S 10-508, New York, NY, 10032, USA.; Division of Rheumatology, Department of Medicine, Columbia University Irving Medical Center, 630 West 168th Street, P&S 10-508, New York, NY, 10032, USA.; Columbia University Vagelos College of Physicians and Surgeons, New York, NY, 10032, USA.; Division of Rheumatology, Department of Medicine, Columbia University Irving Medical Center, 630 West 168th Street, P&S 10-508, New York, NY, 10032, USA.; Division of Rheumatology, Department of Medicine, Columbia University Irving Medical Center, 630 West 168th Street, P&S 10-508, New York, NY, 10032, USA.; Division of Rheumatology, Department of Medicine, Columbia University Irving Medical Center, 630 West 168th Street, P&S 10-508, New York, NY, 10032, USA.; Division of Rheumatology, Department of Medicine, Columbia University Irving Medical Center, 630 West 168th Street, P&S 10-508, New York, NY, 10032, USA. ada20@cumc.columbia.edu.
PURPOSE OF REVIEW: Three COVID-19 vaccines obtained emergency authorization from the Food and Drug Administration (FDA) and are widely used in the USA. Unfortunately, there is a paucity of evidence on the safety and efficacy of these vaccines in patients with autoimmune inflammatory rheumatic diseases (AIIRD), as these patients were excluded from all phases of vaccine development. Here we reviewed current data on COVID-19 vaccination in patients with AIIRD, with emphasis on systemic lupus erythematosus (SLE), and provided a comprehensive update on the benefits and risks of vaccination. RECENT FINDINGS: Patients with SLE have worse immune responses following SARS-CoV-2 vaccination than healthy controls. The efficacy of the COVID-19 vaccines seems to be further reduced by immunosuppressive medications, such as glucocorticoids (GC), methotrexate (MTX), mycophenolate/mycophenolic acid (MMF), and rituximab (RTX). However, these data do not substantiate that AIIRD patients are at greater
2020-02-29
Department of Infectious Diseases, The First Hospital of Changsha, Changsha, Hunan, China. 1286779459@qq.com.
OBJECTIVE: In December 2019, a new type of coronavirus-infected pneumonia broke out in Wuhan and spread rapidly to other parts of the country. The purpose of this study was to investigate the clinical features of coronavirus disease 2019 (COVID-19). MATERIALS AND METHODS: A retrospective analysis was performed on the confirmed cases of COVID-19, who were admitted to the North Hospital of Changsha first Hospital (Changsha Public Health treatment Center) from January 17 to February 7, 2020. RESULTS: The median age of COVID-19 patients was 45 years (range 33.5-57). The male patients accounted for 49.7%, 64.6% of the patients had a history of exposure in Wuhan, and 31.7% had family aggregation. The median days of onset were six, and the incidence of severe illness was 18.6%. Compared with the non-severe group, the severe group showed statistical significance in older age, hypertension, bilateral lung plaque shadow, decrease in lymphocyte count, increase in C-reactive protein (CRP),
2020-02-29
Department of Infectious Diseases, The First Hospital of Changsha, Changsha, Hunan, China. 1286779459@qq.com.
OBJECTIVE: In December 2019, a new type of coronavirus-infected pneumonia broke out in Wuhan and spread rapidly to other parts of the country. The purpose of this study was to investigate the clinical features of coronavirus disease 2019 (COVID-19). MATERIALS AND METHODS: A retrospective analysis was performed on the confirmed cases of COVID-19, who were admitted to the North Hospital of Changsha first Hospital (Changsha Public Health treatment Center) from January 17 to February 7, 2020. RESULTS: The median age of COVID-19 patients was 45 years (range 33.5-57). The male patients accounted for 49.7%, 64.6% of the patients had a history of exposure in Wuhan, and 31.7% had family aggregation. The median days of onset were six, and the incidence of severe illness was 18.6%. Compared with the non-severe group, the severe group showed statistical significance in older age, hypertension, bilateral lung plaque shadow, decrease in lymphocyte count, increase in C-reactive protein (CRP),
Division of Rheumatology, Department of Medicine, Columbia University Irving Medical Center, 161 Fort Washington Avenue, 2nd Floor, New York, NY, 10032, USA.; Division of Rheumatology, Department of Medicine, Columbia University Irving Medical Center, 161 Fort Washington Avenue, 2nd Floor, New York, NY, 10032, USA.; Division of Rheumatology, Department of Medicine, Columbia University Irving Medical Center, 161 Fort Washington Avenue, 2nd Floor, New York, NY, 10032, USA.; Division of Rheumatology, Department of Medicine, Columbia University Irving Medical Center, 161 Fort Washington Avenue, 2nd Floor, New York, NY, 10032, USA.; Division of Rheumatology, Department of Medicine, Columbia University Irving Medical Center, 161 Fort Washington Avenue, 2nd Floor, New York, NY, 10032, USA.; Division of Rheumatology, Department of Medicine, Columbia University Irving Medical Center, 161 Fort Washington Avenue, 2nd Floor, New York, NY, 10032, USA.; Division of Rheumatology, Department of Medicine, Columbia University Irving Medical Center, 161 Fort Washington Avenue, 2nd Floor, New York, NY, 10032, USA.; Division of Infectious Disease, Department of Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA.; Division of Rheumatology, Department of Medicine, Columbia University Irving Medical Center, 161 Fort Washington Avenue, 2nd Floor, New York, NY, 10032, USA. ada20@cumc.columbia.edu.
Since the first outbreak of Coronavirus Disease-2019 (COVID-19) in January 2020, the medical community has been pursuing effective countermeasures. Early in the pandemic, several small clinical and in vitro studies from France and China reported on the efficacy of chloroquine (CQ) and hydroxychloroquine (HCQ) against SARS-CoV-2 infections, which generated global attention towards these decades-old antimalarials (AM) and heralded numerous studies investigating their role in treating COVID-19. Despite several observational studies early in the pandemic affirming their beneficial role in treating COVID-19, 12 clinical studies reported no mortality benefits for CQ/HCQ in COVID-19 patients. The excitement over CQ/HCQ was ultimately quenched after three large randomized clinical trials, the COALITION-I trial in Brazil, the RECOVERY trial in the United Kingdom (UK), and the SOLIDARITY trial from World Health Organization (WHO) consistently reported no beneficial effects for CQ/HCQ in