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11.1 BackgroundThe outbreak of the new coronavirus infection broke out in Wuhan City, Hubei Province in December 2019, and has spread to 97 countries and regions around the world. Apart from China, there are currently three other severely affected areas, namely Italy, South Korea, and Iran. This poses a huge threat to Chinas and even global public health security, challenges scientific research work such as disease surveillance and tracking, clinical treatment, and vaccine development, and it also brings huge uncertainty to the global economy. As of March 11, 2020, the epidemic situation in China is nearing its end, but the epidemic situation abroad is in the outbreak period. Italy has even taken measures to close the city nationwide, with a total of 118,020 cases of infection worldwide. 1.2 MethodThis article selects the data of newly confirmed cases of COVID-19 at home and abroad as the data sample. Among them: the data of newly confirmed cases abroad is represented by Italy, and the span is from February 13 to March 10. The data of newly confirmed cases at home are divided into two parts: Hubei Province and other provinces except Hubei Province, spanning from January 23 to March 3, and with February 12 as the cutting point, it"s divided into two periods, the growth period and the recession period. The rescaled range (R / S) analysis method and the dimensionless fractal Hurst exponent are used to measure the correlation of time series to determine whether the time series conforms to the fractal Brownian motion, that is, a biased random process. Contrast analysis of the meaning of H value in different stages and different overall H values in the same stage. 1.3 ResultsBased on R / S analysis and calculated Hurst value of newly confirmed cases in Hubei and non-Hubei provinces, it was found that the H value of Hubei Province in the first stage was 0.574, which is greater than 0.5, indicating that the future time series has a positive correlation and Fractal characteristics; The H value in the second stage is 1.368, which is greater than 1, which indicates that the future epidemic situation is completely preventable and controllable, and the second stage has a downward trend characteristic, which indicates that there is a high probability that the future time series will decline. The H values of the first and second stages of non-Hubei Province are 0.223 and 0.387, respectively, which are both less than 0.5, indicating that the time series of confirmed cases in the future is likely to return to historical points, and the H value in the second stage is greater than that in the first stage, indicating that the time series of confirmed cases in the second stage is more long-term memory than the time series of confirmed cases in the first stage. The daily absolute number of newly confirmed cases in Italy was converted to the daily growth rate of confirmed cases to eliminate the volatility of the data. The H value was 1.853, which was greater than 1, indicating that the time series of future confirmed cases is similar to the trend of historical changes. The daily rate of change in cases will continue to rise. 1.4 ConclusionAccording to the different interpretation of the H value obtained by the R / S analysis method, hierarchical isolation measures are adopted accordingly. When the H value is greater than 0.5, it indicates that the development of the epidemic situation in the area has more long-term memory, that is, when the number of confirmed cases in the past increases rapidly, the probability of the time series of confirmed cases in the future will continue the historical trend. Therefore, it is necessary to formulate strict anti-epidemic measures in accordance with the actual conditions of various countries, to detect, isolate, and treat early to reduce the base of infectious agents.
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BACKGROUNDThe outbreak of the new coronavirus infection in Wuhan City, Hubei Province in December 2019, poses a huge threat to China and even global public health security. Respiratory droplets and contact transmission are the main routes of transmission of new coronaviruses. Compared with SARS and Ebola viruses, new coronavirus infections are infectious during the incubation period. Traditional SEIR (susceptibility-exposure-infection-Removal) There are some differences in conditions for the prediction of the epidemic trend of new coronavirus infection. The outbreak of the new coronavirus infection coincided with the Spring Festival before and after the Chinese Spring Festival.It is necessary to make appropriate optimization and amendments to the traditional model to meet the actual evolution of the epidemic situation. METHODSThe traditional SEIR model assumes that the virus-infected person is not infectious during the incubation period and that the infected person did not take isolation measures during the illness. The transmission of the new coronavirus no longer meets the basic assumptions of the classical kinetic system. Therefore, this article first establishes a modified SEIR model. Predict and analyze the changing trend of the epidemic situation, then estimate the parameters involved in the infection dynamics model, and then use Matlab to simulate the established dynamic equations based on public data and analyze the results. Recommendations for universal prevention and control of infectious diseases. RESULTSThe first case of new coronavirus infection was confirmed in Wuhan on December 8, 2019. When Wuhan City took no action, assuming the average daily number of contacts per infected person k = 5, the number of infected persons will reach about 2,384,803 people; If wuhan adopts the measures of sealing the city on January 22, 2020, under the premise of k=2, the number of infected people decreases by 19,773 compared with that on January 23, and there is no significant change in the time when the number of infected people reaches the peak. Under the premise of k = 1, the number of infected persons was reduced by 14,330 compared with the closure on January 23, and the time to reach the peak of the number of infected persons was reduced by 2 days. If Wuhan City is closed for one day, the number of infected persons will increase from 106,145 to 130,626 under the premise of k = 2; the number of infected persons will increase from 74,369 to 92,010 under the premise of k = 1. CONCLUSIONSComparing the number of confirmed diagnoses actually notified by the department with the number of infected people obtained from the simulation of the model, it can be seen that the city closure measures adopted by the Wuhan Municipal Government on January 23 and the first-level response measures adopted by the country are effective for the epidemic Prevention and control play a vital role. Wearing a mask when going out and avoiding close contact with people can effectively reduce the infection rate.
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Objective To explore the distribution and antimicrobial resistance of pathogens causing healthcare-associated infection(HAI) in a hospital,and provide theoretical basis for rational use of antimicrobial agents and control of HAL Methods HAI occurred in patients in this hospital between 2011 and 2015 were chosen,distribution of major pathogens causing HAI and antimicrobial resistance were analyzed.Results A total of 852 pathogenic strains were isolated,including 458 (53.75 ％) strains of gram-negative bacteria,259 (30.40 ％) fungi,and 135 (15.85 ％) gram-positive bacteria,the top 4 pathogens were Klebsiella pneumoniae (n =159,18.66 ％),Candida albicans (n =119,13.97％),Acinetobacter baumannii (n =81,9.51％),and Escherichia coli (n =74,8.69 ％).Isolation rate of gram-negative bacteria increased from 47.41 ％ in 2012 to 61.57％ in 2015,fungi increased from 24.78％ in 2011 to 34.45％ in 2014 (2015 was 27.95％),gram-positive bacteria decreased from 26.55％ in 2011 to 10.48％ in 2015.Resistance rates of Escherichia coli and Klebsiella pneumoniae to imipenem and meropenem were 8.11％-12.58％;Acinetobacter baumannii had the lowest resistance rate to cefoperazone/sulbactam(23.46％),resistance rate of Candida albicans to fluconazole was up to 59.66％,vancomycin-resistant gram-positive bacteria was not found.Conclusion The major pathogens causing HAI are opportunistic pathogens,antimicrobial resistance is serious,the species and distribution varies with different years,it is necessary to enhance specimen detection rate,strengthen the monitoring on pathogen resistance,and use antimicrobial agents rationally.
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Objective To identify and analyze the homology of Ochrobactrum isolated from clinical blood samples of children.Methods The 26 strains of Ochrobactrum anthropi were identified by Vitek 2 Compact and test strips of API 20 NE bacterial identification system.The biochemical phenotypes were identified by manual tests.The 16S rRNA and recA gene were amplified by PCR and sequenced.The drug sensitivity tests of Ochrobactrum anthropi were performed by Vitek 2 Compact and matched GN13 card.The homology was analyzed by pulsed field gel electrophoresis.Results Based on the identification of the instruments and the manual tests for biochemical phenotype,all the 26 experimental strains were Ochrobactrum anthropi.The results of sequencing for 16S rRNA and recA gene amplification products showed 25 strains were Pseudochrobactrum saccharolyticum and the other 1 was O.grignonensein.Drug sensitivity analysis showed that the all the 26 strains were resistant to aztreonam,but the sensitive rates to quinolones,aminoglycosides,trimethoprim sulfamethoxazole,four generation of cephalosporins and the antibiotics compound of piperacillin/tazobactam were all more than 80％.Pulsed field gel electrophoresis analysis showed that the 25 strains were highly homologous with differences of only 1 to 3 bands in fingerprint profiles.Conclusion Based on the biochemical phenotype and the sequencing of 16S rRNA and recA gene,the Ochrobactrum-like bacteria could be identified to the level of species.The highly homologous strains of Pseudochrobactrum saccharolyticum may be sourced from a clustered infection.
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Objective To explore the feasibility of patient health questionnaire-9 (PHQ-9) in a general hospital outpatients and analyze the risk factors of depressive syndromes.Methods Two hundred fifty-eight outpatients filled out PHQ-9 and the World Health Questionnaire Quality of Life Brief Questionnaire(WHOQOL-BREF) by themselves.Then they were evaluated by professionals with Hamilton Depression Rating Scale (HAMD-17).Ninety-seven of them were further interviewed with the Structured Clinical Interview for DSM-Ⅳ Disorders(SCID) for the diagnosis of major depression which in order to analyze the validity of the PHQ-9.All patients were divided into the depressive group and non-depressive group according the score of PHQ-9,and then analyzed the risk factors of depression.Results ①The sensitivity of PHQ-9 was 98％,the specificity was 67％ and Kappa was 0.664.The total score of PHQ-9 was high correlated with the total score of HAMD,the coefficient was 0.75(P＜0.01).②The Univariate analysis showed that the depressive symptom was associated with age,monthly income,health status,the quality of life.Logistic regression analysis showed that age,health status,the quality of life were the main factors of depression.Conclusion PHQ-9 may svere as a screening tool to increase the recognition of depression and age,health status,the quality of life were the main factors of depression.
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OBJECTIVE To develop a rapid system for bacteria identification and susceptibility test in 24 hours,and provide bacteriological evidence for the control of nosocomial infection and the timely diagnosis and treatment.METHODS The simple constant temperature box was replaced by revolving constant temperature box;2,3,5-triphenyltetrazolium chloride(TTC) and succinate were added to the culture bottle and the culture medium of drug susceptibility;the concentration of the reactive substrate in the bacterial biochemical tube and the number of the inoculated bacteria were increased at the same time.RESULTS The time of positive blood culture in the revolving constant temperature box was significantly shorter than that in the simple one(?2=74.92,P