Objective: To describe the epidemiological characteristics of a cluster of COVID-19 cases reported in Baodi district of Tianjin as of 18 February, 2020, which might be associated with the exposure in a local department store, and provide suggestions for prevention and control strategy development. Methods: The basic characteristics, time and area distributions, clinical manifestations, epidemiological history and transmission mode of the COVID-19 cases associated with the department store exposure were analyzed. Results: A total of 40 COVID-19 cases were associated with the department store exposure, accounting for 75.47% of the total confirmed cases (53 cases) reported in Baodi district. The cases were mainly at the age of 60 years or older (35.00%) and farmers (40.00%). The main clinical manifestations included fever (95.00%), cough (35.00%), and diarrhea (15.00%). The proportion of confirmed severe cases was 32.50%. The incidence curve showed that the incidence peak occurred on 31 January, 2020. Among the 40 cases, 6(15.00%) were department store employees, 19(47.50%) were customers and 15(37.50%) were close contacts (secondary cases). The first case occurred on 21 January, 2020, this case was a department store employee who had a purchasing history at whole sale markets in other provinces and cities before the onset, and 3 employees were still on duty after symptom onsets. The median of the incubation period of customer cases was 6 days, and the median of the interval between onset and medical treatment of customer cases was 7 days. Conclusion This was a cluster epidemic of COVID-19, which might be associated with the exposure in the department store. By now, the current prevention and control measures have achieved satisfied effects.

The outbreak of COVID-19 has spread quickly across 114 countries/territories/areas in six continents worldwide and has been announced as a pandemic by WHO. This study analyzed global COVID-19 epidemiological trends, examined impact of the pandemic on global health security, diplomacy, and social environment in China, and provided short- and long-term strategic policy recommendations for China’s subsequent preparedness and responses.

A recent study based on the use of experimental artificial intelligence (AI) tool showed 70%–80% accuracy in predicting development of severe disease in coronavirus disease 2019 (COVID-19) based on predictive parameters alanine aminotransferase (ALT), myalgia and hemoglobin, whilst only 5 of 53 patients developed acute respiratory distress syndrome (ARDS), 2 of whom reporting myalgia.[1] It is commonly advocated that myalgia may reflect generalized inflammation and cytokine response.[1] Multiple studies showed that myalgia is a common symptom at onset of COVID-19, seen in up to 36% of such patients.[2] Therefore, in this short article we aim to further assess whether myalgia may be a reliable predictor of severe COVID-19 disease.

Objective: To understand the possible transmission route of a family cluster of COVID-19 in Zhengzhou and the potential infectivity of COVID-19 in incubation period, and provide scientific evidence for the timely control of infectious source and curb the spread of the epidemic. Methods: Epidemiological investigation was conducted for a family cluster of COVID-19 (8 cases) with descriptive epidemiological method, and respiratory tract samples of the cases were collected for the nucleic acid detection of 2019-nCoV by RT-PCR. Results: Two primary cases, which occurred on 31 January and 1 February, 2020, respectively, had a common exposure history in Wuhan. The other six family members had onsets on 30 January, 31 January, 1 February (three cases) and 3 February, 2020. Conclusions In this family cluster of COVID-19, six family members were infected through common family exposure to the 2 primary cases. Five secondary cases had onsets earlier than or on the same day as the primary cases, indicating that COVID-19 is contagious in incubation period, and the home isolation in the early phase of the epidemic might lead to the risk of family cluster of COVID-19.

Objective To confirm the epidemiological characteristics of coronavirus disease COVID-19 reported in Qianjiang city and provide a scientific basis for establishing and implementing effective infection prevention and control. Methods The cases of COVID-19 reported in Qianjiang were retrospectively collected and the epidemiological characteristics, including time, spatial and population distribution, clinical symptoms and exposure history, were analyzed using descriptive epidemiological method. Results A total of 198 confirmed cases of COVID-19, including 102 imported cases, were reported in Qianjiang city by March 31, 2020. Of the 198 patients, 9 died, and 189 were discharged. The male-to-female ratio was 1.2:1. Among the reported patients, most of the patients were aged 30-69. In the early stage, only imported cases were reported, subsequently, imported cases and local cases were prevalent together, and the peak of confirmed cases was appeared on February 15, 2020. Among the clinical types for admitted diagnosis, the common type (67.17%) was dominant, and fever (82.83%) and cough (67.17%) were the predominant clinical manifestations for primary diagnosis. The median time from illness onset to first visit was 3 days, the median time from first visit to confirmed diagnosis was 7 days, and the median interval from illness onset to diagnosis was 11 days. Conclusions With comprehensive measures taken, the pandemic of COVID-19 in Qianjiang have been brought under control. However, it is necessary to be alert to the potential risks brought by the resumption of work, production, education, as well as the outbound imported cases. Various prevention and control measures should continue to be strictly implemented.

The World Health Organization (WHO) has initially categorised COVID-19 infection as a Public Health Emergency of International Concern (PHEIC) in late January 2020 and later on declared the outbreak as a pandemic on March 11, 2020. On February 4, 2020 the first Malaysian positive COVID-19 patients was detected. It was estimated through a thorough decision tree technique, cumulatively 22,000 positive patients were expected to be infected nationwide. At the current rate of disease detection, screening yield and clinical capacity in Malaysia, the identification of the positive patients will have to be continuously done until middle of May 2020. In addition, a prediction with the forecasted testing capacity was also conducted. In contrast with the earlier estimation, massive testing causes the number of positive patients to be saturated earlier, by the end of April 2020. Based on the projection, 346, 307 cumulative tests will be conducted with 225,100 cumulative positive cases will be identified. Of the numbers, the cumulative number of patients in care would be 17,631 with 705 cumulative number of admission to intensive care unit and 353 cumulative patients required for ventilator. The cumulative death and cumulative discharge are expected to be 394 and 6008 respectively. Currently, it is challenging for Malaysia to flatten the epidemic curve due to the constraints of healthcare resources. These challenges potentially highlight the need for realistic strategies with regard to the country’s capacity.

In December 2019, an outbreak of viral pneumonia began in Wuhan, Hubei Province, which caused the spread of infectious pneumonia to a certain extent in China and neighboring countries and regions, and triggered the epidemic crisis. The coronavirus disease 2019(COVID-19) is an acute respiratory infectious disease listed as a B infectious disease, which is managed according to standards for A infectious disease. Traditional Chinese medicine and integrated traditional Chinese and Western medicine have played an active role in the prevention and control of this epidemic. China's ethnomedicine has recognized infectious diseases since ancient times, and formed a medical system including theory, therapies, formula and herbal medicines for such diseases. Since the outbreak of the COVID-19 epidemic, Tibet Autonomous Region, Qinghai Province, Inner Mongolia Autonomous Region, Xinjiang Uygur Autonomous Region and Chuxiong Autonomous Prefecture of Yunnan, Qiandongnan Autonomous Prefecture of Guizhou have issued the prevention and control programs for COVID-19 using Tibetan, Mongolian, Uygur, Yi and Miao medicines. These programs reflect the wisdom of ethnomedicine in preventing and treating diseases, which have successfully extracted prescriptions and preventive measures for the outbreak of the epidemic from their own medical theories and traditional experiences. In this paper, we summarized and explained the prescriptions and medicinal materials of ethnomedicine in these programs, and the origin of Tibetan medicine prescriptions and Mongolian medicine prescriptions in ancient books were studied. These become the common characteristics of medical prevention and treatment programs for ethnomedicine to formulate therapeutic programs under the guidance of traditional medicine theories, recommend prescriptions and prevention and treatment methods with characteristics of ethnomedicine, and focus on the conve-nience and standardization. However, strengthening the support of science and technology and the popularization to the public, and improving the participation of ethnomedicine in national public health services and the capacity-building to deal with sudden and critical diseases are key contents in the development of ethnomedicine in the future.
Betacoronavirus ; China ; Coronavirus Infections ; drug therapy ; Humans ; Medicine, Traditional ; Pandemics ; Pneumonia, Viral ; drug therapy ; Tibet

Objective To investigate the epidemiological characteristics of a family clustering of COVID-19. Methods Field epidemiological survey was conducted. Result Case 1 of the long-term residents from Hubei province was the source of infection of this family clustering. There were 6 cases (from case 2 to case 7) infected in the whole incubation period. The incubation period was more than 14 days for 3 of the second-generation cases. Routes of transmission include respiratory droplets (from case 1 transmitted to case 6, from case 1 to her family members) and closecontact (from case 1 to other cases in her family). All the age groups were generally susceptible, while elderly were easier to progress to critically ill. Besides respiratory symptoms, there were also gastrointestinal symptoms, of which diarrhea was the most common one. Conclusion Family clustering had been an important part for COVID-19 cases.

Objective To understand the epidemiological characteristics of the cases of COVID-19 epidemic clusters, and explore the influence of family factors and social factors such as group activities on the spread of the disease. Methods The data of cases of COVID-19 epidemic clusters from 19 January, 2020 to 25 February, 2020 were collected from the official platforms of 36 cities in 6 provinces in China. Descriptive statistical methods, χ 2 test and curve fitting were used to analyze the epidemiological characteristics of the clustered cases. Results By 25 February, 2020, the data of 1 052 cases in 366 epidemic clusters were collected. In these clustered cases, 86.9%(914/1 050) occurred in families. Among the 1 046 cases with gender information, 513 were males (49.0%) and 533 were females (51.0%). The cases were mainly young adults between 18 and 59 years old, accounting for 68.5% (711/1 038). In the 366 epidemic clusters , the clusters in which the first confirmed cases with the history of sojourn in Wuhan or Hubei accounted for 47.0%(172/366). From 19 January to 3 February, 2020, the first confirmed cases with Wuhan or Hubei sojourn history accounted for 66.5%. From 4 to 25 February, the first confirmed cases who had Wuhan or Hubei sojourn history accounted for only 18.2%. The median of interval between the first generation case onset and the second generation case onset was 5 (2-8) days. The median of onset- diagnosis interval of the initial cases was 6 (3-9) days, and the median of onset-diagnosis interval of the secondary cases was 5 (3-8) days. Conclusions Epidemic clusters of COVID-19 were common in many cities outside Wuhan and Hubei. Close contact in family was one of the main causes for the spread of household transmission of the virus. After 4 February, the epidemic clusters were mainly caused by the first generation or second generation cases in local areas, and the time for diagnosis became shorter.

In December 2019, an outbreak of pneumonia associated with a novel coronavirus (SARS-CoV-2）emerged in Wuhan and spread rapidly throughout China and beyond. As the first-line imaging modality, thin-section chest CT is easy to perform, fast, available. Combined with epidemiological history and clinical manifestations, positive CT findings can highly suggest the early diagnosis of Coronavirus Disease 2019 (COVID-19) with high sensitivity, so that timely isolation and intervention can be implemented for suspected and confirmed patients. CT can also help assess the disease severity, and surveil disease course, so as to guide clinical decision and provide prognostic information. This paper outlines the CT imaging features of COVID-19 and highlights the value of chest CT in its diagnosis and treatment with the reference to the official documents and latest researches.