Coronavirus Infections ; epidemiology ; Humans

Coronavirus ; Coronavirus Infections ; epidemiology ; Humans ; Respiratory Tract Infections ; epidemiology

Coronavirus Infections ; epidemiology ; Humans ; Middle East ; epidemiology ; Respiratory Tract Infections ; epidemiology ; virology ; Singapore ; epidemiology ; Syndrome

Coronavirus Infections ; epidemiology ; prevention & control ; transmission ; Global Health ; Humans ; Middle East Respiratory Syndrome Coronavirus

OBJECTIVES: To explore and analyze the epidemic features of coronavirus disease 2019 (COVID-19) in Hunan Province from January 21, 2020 to March 14, 2020, as well as to investigate the COVID-19 epidemics in each city of Hunan Province. METHODS: The epidemic data was obtained from the official website of Hunan Province's Health Commission. The data of each city of Hunan Province was analyzed separately. Spatial distribution of cumulative confirmed COVID-19 patients and the cumulative occurrence rate was drawn by ArcGIS software for each city in Hunan Province. Some regional indexes were also compared with that in the whole country. RESULTS: The first patient was diagnosed in January 21, sustained patient growth reached its plateau in around February 17. Up to March 14, the cumulative confirmed COVID-19 patients stopped at 1 018. The cumulative occurrence rate of COVID-19 patients was 0.48 per 0.1 million person. The number of cumulative severe patients was 150 and the number of cumulative dead patients was 4. The mortality rate (0.39%) and the cure rate (99.6%) in Hunan Province was significantly lower and higher respectively than the corresponding average rate in the whole country (0.90% and 96.2%, Hubei excluded). The first 3 cities in numbers of the confirmed patients were Changsha, Yueyang, and Shaoyang. While sorted by the cumulative occurrence rate, the first 3 cities in incidence were Changsha, Yueyang, and Zhuzhou. CONCLUSIONS The epidemic of COVID-19 spread out smoothly in Hunan Province. The cities in Hunan Province implement anti-disease strategies based on specific situations on their own and keep the epidemic in the range of controllable.
Betacoronavirus ; China ; epidemiology ; Cities ; epidemiology ; Coronavirus Infections ; epidemiology ; mortality ; Humans ; Pandemics ; Pneumonia, Viral ; epidemiology ; mortality

Middle East respiratory syndrome (MERS) has raised global public health concerns. The recent outbreak of MERS coronavirus (MERS-CoV) infection has led to 1 338 laboratory-confirmed cases in 26 countries worldwide as reported till 19 June, 2015. MERS-CoV may be considered a zoonotic virus that has crossed the species barrier to humans, but the pathogenesis and the routes of transmission are not completely understood. Most MERS-CoV cases reported thus far have a history of residence in or travel to the Middle East. Human-to-human transmission though was observed on some occasions in Korea, it is documented as non-sustainable event. The envelope spike glycoprotein on the surface of MERS-CoV which mediates receptor binding, membrane fusion and viral entry is thought to be involved in the mechanism of MERS-CoV.No specific and effective treatment for MERS-CoV is currently recommended, although supportive treatment has played an important role. Prophylactic strategies are necessary to prevent MERS-CoV infection.
Coronavirus Infections ; diagnosis ; epidemiology ; therapy ; Humans ; Middle East Respiratory Syndrome Coronavirus ; pathogenicity ; physiology ; Spike Glycoprotein, Coronavirus ; metabolism ; Virus Internalization

Middle East Respiratory Syndrome coronavirus (MERS-CoV) was first isolated from a patient with severe pneumonia in 2012. The 2015 Korea outbreak of MERSCoV involved 186 cases, including 38 fatalities. A total of 83% of transmission events were due to five superspreaders, and 44% of the 186 MERS cases were the patients who had been exposed in nosocomial transmission at 16 hospitals. The epidemic lasted for 2 months and the government quarantined 16,993 individuals for 14 days to control the outbreak. This outbreak provides a unique opportunity to fill the gap in our knowledge of MERS-CoV infection. Therefore, in this paper, we review the literature on epidemiology, virology, clinical features, and prevention of MERS-CoV, which were acquired from the 2015 Korea outbreak of MERS-CoV.
Coronavirus ; Coronavirus Infections* ; Disease Outbreaks ; Epidemiology ; Humans ; Korea ; Middle East Respiratory Syndrome Coronavirus ; Middle East* ; Pneumonia ; Republic of Korea* ; Virology

OBJECTIVETo investigate human coronaviruses (HCoVs) infection in children with acute lower respiratory tract infection(ALRTI)and to explore the clinical features of ALRTI caused by HCoVs in children.

METHODTotally 4 371 children with clinical diagnosis of ALRTI during the period from March 2007 to February 2015 seen in Beijing Children's Hospital were recruited into this study. Patients were divided into 4 groups by age, including 1 890 cases in < 1 year group, 788 cases in 1-3 years group, 553 cases in 3-6 years group, 1140 cases in ≥6 years group. One nasopharyngeal aspirate specimen was collected from each patient. RT-PCR methods were applied to detect 9 common respiratory viruses including HCoVs (including HCoV-OC43, HCoV-229E, HCoV-NL63 and HCoV-HKU1), respiratory syncytial virus (RSV) and so on. Clinical features of ALRTI with single HCoVs infection were analyzed and compared with hospitalized ALRTI cases with single RSV infection in the same period.

RESULT(1) Totally 2 895 cases were positive for at least one virus in this study in 4 371 ALRTI patients (positive rate 66.23%), in which 147 cases were positive for HCoVs infection (positive rate 3.36%). (2) Positive rates of HCoVs in each year from 2007 to 2014 were 6.11%, 3.79%, 4.69%, 4.31%, 2.38% 2.10%, 0.77% and 2.65%, respectively. The mean positive rates of HCoVs for each month from January to December were 2.53%, 2.12%, 3.63%, 6.68%, 1.53%, 3.77%, 3.92%, 3.00%, 2.15%, 5.26%, 3.01% and 2.80%. (3) Detection results of each subtypes of HCoVs in total 4 371 pediatric ALRTI patients were: 48 cases positive for HCoV-OC43(1.10%), 32 cases positive for HCoV-229E(0.73%), 25 cases positive for HCoV-NL63 (0.57%), 27 cases positive for HCoV-HKU1 (0.62%). (4) Positive rates of HCoVs infection in <1 year group, 1-3 years group, 3-6 years group and ≥ 6 years group were 4.13%, 5.08%, 2.71% and 1.23%, respectively. There were significant differences in positive rates of HCoV among groups (χ² = 27.218, P<0.01). (5) There were 16 hospitalized cases with single infection of HCoVs in this study, of which 12 cases were diagnosed as bronchopneumonia, 3 cases developed acute laryngeal obstruction, 2 cases had acute bronchial asthma attack. Common clinical manifestations included cough (14 cases), gasping (13 cases), dyspnea (9 cases), fever (6 cases), hoarseness (4 cases), laryngeal stridor (4 cases) and abnormality on chest X-ray (including fuzzy lung texture, patchy shadow and consolidation) (12 cases). (6) There were no significant differences in the incidence of clinical manifestations (including cough, gasping, dyspnea, fever and abnormality on chest X-ray), complications (including respiratory failure, myocardial damage, and acute bronchial asthma attack) and mechanical ventilation between hospitalized ALRTI patients with single HCoV infection and 193 patients with single RSV infection in the same period.

CONCLUSIONHCoVs are pathogens of ALRTI in children, The overall positive rate of HCoVs was 3.36% in this study. The clinical manifestations and severity of ALRTI caused by single HCoVs was comparable to that of ALRTI with single RSV infection in children.

Acute Disease ; Beijing ; Child ; Child, Preschool ; Coronavirus ; Coronavirus Infections ; epidemiology ; Humans ; Incidence ; Infant ; Respiratory Syncytial Virus Infections ; epidemiology ; Respiratory Syncytial Viruses ; Respiratory Tract Infections ; epidemiology ; virology

OBJECTIVE: To establish a SEIR epidemic dynamics model that can be used to evaluate the COVID-19 epidemic, and to predict and evaluate the COVID-19 epidemic in Hubei province using the proposed model. METHODS: COVID-19 SEIR transmission dynamics model was established, which took transmission ability in latent period and tracking quarantine interventions into consideration. Based on the epidemic data of Hubei province from January 23, 2020 to February 24, 2020, the parameters of the newly established modified SEIR model were fitted. By using Euler integral algorithm to solve the modified SEIR dynamics model, the epidemic situation in Hubei province was analyzed, and the impact of prevention and control measures such as quarantine and centralized treatment on the epidemic development was discussed. RESULTS: The theoretical estimation of the epidemic situation by the modified SEIR epidemic dynamics model is in good agreement with the actual situation in Hubei province. Theoretical analysis showed that prevention and control quarantine and medical follow-up quarantine played an important inhibitory effect on the outbreak of the epidemic.The centralized treatment played a key role in the rapid decline in the number of infected people. In addition, it is suggested that individuals should improve their prevention awareness and take strict self-protection measures to curb the increase in infected people. CONCLUSIONS The modified SEIR model is reliable in the evaluation of COVID-19 epidemic in Hubei province, which provides a theoretical reference for the decision-making of epidemic interventions.
Algorithms ; Betacoronavirus ; isolation & purification ; China ; epidemiology ; Coronavirus Infections ; epidemiology ; Humans ; Models, Biological ; Pandemics ; Pneumonia, Viral ; epidemiology

BACKGROUND: The ongoing new coronavirus pneumonia (Corona Virus Disease 2019, COVID-19) outbreak is spreading in China, but it has not yet reached its peak. Five million people emigrated from Wuhan before lockdown, potentially representing a source of virus infection. Determining case distribution and its correlation with population emigration from Wuhan in the early stage of the epidemic is of great importance for early warning and for the prevention of future outbreaks. METHODS: The official case report on the COVID-19 epidemic was collected as of January 30, 2020. Time and location information on COVID-19 cases was extracted and analyzed using ArcGIS and WinBUGS software. Data on population migration from Wuhan city and Hubei province were extracted from Baidu Qianxi, and their correlation with the number of cases was analyzed. RESULTS: The COVID-19 confirmed and death cases in Hubei province accounted for 59.91% (5806/9692) and 95.77% (204/213) of the total cases in China, respectively. Hot spot provinces included Sichuan and Yunnan, which are adjacent to Hubei. The time risk of Hubei province on the following day was 1.960 times that on the previous day. The number of cases in some cities was relatively low, but the time risk appeared to be continuously rising. The correlation coefficient between the provincial number of cases and emigration from Wuhan was up to 0.943. The lockdown of 17 cities in Hubei province and the implementation of nationwide control measures efficiently prevented an exponential growth in the number of cases. CONCLUSIONS The population that emigrated from Wuhan was the main infection source in other cities and provinces. Some cities with a low number of cases showed a rapid increase in case load. Owing to the upcoming Spring Festival return wave, understanding the risk trends in different regions is crucial to ensure preparedness at both the individual and organization levels and to prevent new outbreaks.
Betacoronavirus ; China ; epidemiology ; Coronavirus Infections ; epidemiology ; Emigration and Immigration ; Epidemics ; Humans ; Pandemics ; Pneumonia, Viral ; epidemiology