0.05). There was no difference between various historical types neither. But it was found that there was a trend that AgNOR counts would increase as the increase of the historical grade and there was a significant difference (P

The use of the Internet big data to discriminate the early symptoms of unexpected biological events has be-come a frontier research area in biosurveillance .This paper mainly introduces the principle , method, practical applications of big data based biosurveillance , and the future development of this new research field .

Modeling biosecurity events based on mathematical theories to reveal the inherent mechanism can shed light on the development of biosecurity events and offer accurate scientific support to emergency preparation and response , con-tributing much to national biodefense capability .This paper reviews the applications of mathematical theories as a research and analytic tool in biosecurity and discusses the trends of development in this field .

To explore the transmission patterns and advise public health departments , this paper establishes a dynamic model on the peculiarity of avian influenza A (H7N9) virus and analyzes the dynamic feature of this type of bird flu trans-mission between humans and birds .Results show that this type of bird flu can be controled , and that closing down live-bird markets is the most effective method .

Human behavior significantly affects the spreading dynamics of infectious diseases in large populations .The study of the interplay between the adaptive behavior and the epidemic dynamics underlies the professional information release and psychological counseling mechanism and is conducive to disease control and social panic elimination .This paper aims at the investigation of the effect of adaptive behaviors on the spreading dynamics of epidemics in structured populations .We analyzed the empirical data on adaptive behavior from several large epidemics after the outbreak of SARS in 2003 and confirmed the induction effect of two main information sources on adaptive behavior , e.g., public available information and local perceived information .Then we investigated the effect of adaptive behavior on epidemic dynamics in a structured population based on two primary models , e.g., health-belief model and network model .The results showed that the individual adaptive behavior had significantly decreased the chance of infection and thus mitigated the epidemics . Human adaptive behavior has a significant effect on spreading dynamics of epidemics .An effective information release mechanism will induce human adaptive behavior and is thus conducive to control of epidemics .

Emerging large-scale epidemics not only cause heavy casualties , but have a huge impact on economy .This paper analyzes the characteristics and manners of the economic impact of emerging large -scale epidemics .Economic losses and the national economic impact of emerging large-scale epidemics are analyzed at three levels: microscopic , supply and demand , and macroscopic .Then the relationship between the these levels is discussed .This research is expected to play an important role in the construction of an appropriate economic model for analysis and calculation of economic losses of emerging large-scale epidemics , and in the formulation of the best cost-effective ratio for preventin and control measures against emerging large-scale epidemics .

Syndromic surveillance , based on non-specific pre-diagnosis and other information , is capable of nearly real-time detection and early warning of potential bioterrorism and emerging infectious threats .Developed countries , led by the U.S., have conducted in-depth and front research in this area while China has just started syndromic surveillance re -search in the exploratory trial stage .The Chinese army is facing an urgent need for syndromic surveillance .This paper makes a case study of foreign military syndromic surveillance practices , typically the U.S.representative system ESSENSE , which was developed by the U .S.Department of Defense and deployed in all military treatment facilities .Some suggestions for the Chinese army are also discussed .

Computational epidemiology is a fast-developing and interdisciplinary research area .Through comprehensive computation-analysis of multi-uncertain factors affecting the epidemic process , this method may add to our knowledge about epidemic patterns and help design reasonable response plans and emergency strategies .This article briefly summarizes the idea and theory of computational epidemiology based on related researches in the recent years , introduces the application of this method in case of smallpox bioterrorism and influenza pandemic , and predicts the development of this area .

Objective: To investigate a cluster of coronavirus disease 2019(COVID-19)caused by latent infection in Haikou,so as to provide reference for the prevention and control of COVID-19 clusters. Methods: An epidemiological investigation was conducted according to the COVID-19 Prevention and Control Program(Fourth Edition). The course of diagnosis and treatment,clinical characteristics and field investigation data were collected to analyze the transmission chain and the intergeneration between cases. Results : Among 39 people involved,five confirmed cases and two asymptomatic infections were found,with an attack rate of 17.95%. The cases aged from 40 to 65 years and lived in the dormitories near the farm of Dongshan. The first case(named Case 1)closely contacted with a confirmed case of COVID-19 in Chengmai from January 28 to February 10,was isolated on February 13 and developed symptoms on February 16. The other six cases(Case 2 to Case 7)shared the water source with Case 1 from January 28 to February 13(within the incubation period of Case 1). They needed to open the power switch outside Case 1's room and the water valve in Case 1's washroom before the use of water. They might be infected by contacting the doorknob and the water valve contacted by Case 1,or by the aerosol formed after Case 1 used the washroom,then infected each other when living together. The onset of Case 2 to Case 7 was earlier than Case 1,and they had no travelling history in Hubei Province 14 days before and contacted no confirmed cases except Case 1. Therefore,Case 1 was the source of the cluster during his incubation period of COVID-19. Conclusion This was a cluster of COVID-19 due to latent transmission by living in the same area and touching the same objects indirectly,which indicated that COVID-19 was infectious in the incubation period.

Objective:To explore the causes of high noise exposure in PICU, and to provide reference for formulating effective intervention measures to improve the status of noise exposure.Methods:With phenomenological method, eleven nurses of Xinhua Hospital, Shanghai Jiaotong University School of Medicine from August to September 2020 were enrolled by purposive sampling method, and joined face-to-face and semi-structured interviews with researchers. Interview data were analyzed by Colaizzi 7-step analysis method.Results:Four themes were extracted, including the characteristics of PICU, difficulty in equipment alarm management, the crying of children which was difficult to appease, and the low level of knowledge, attitude and practice of noise management of medical staff.Conclusions:High noise exposure of PICU is caused by many reasons. Researchers and managers can optimize the equipment alarm management, implement ideal analgesia and sedation and humanistic care, and carry out noise management training to improve the noise exposure in PICU and the quality of clinical nursing.