1.Construction of the clinical diagnosis and treatment model during the “pre-disease to disease” window period in traditional Chinese medicine: integration of objective multimodal data from the perspective of traditional Chinese medicine stateology
Danyang Li ; Min Ai ; Pai Zhou ; Ying Deng ; Chaoyang Yang ; Qinghua Peng
Digital Chinese Medicine 2026;9(2):173-183
The philosophy of “treating disease before its onset” is a fundamental concept of traditional Chinese medicine (TCM), permeating its diagnostic and therapeutic framework, and is central to clinical practice. However, current TCM diagnostic and treatment models for the “pre-disease to disease” window period face several limitations, including the lack of comprehensive clinical parameters, difficulties in characterizing and integrating heterogeneous multimodal data, and insufficient dynamic precision in interventions and efficacy evaluations. To address these issues, guided by Professor Candong Li’s theory of TCM stateology, this study focuses on integrating objective multimodal data. It proposes a new model for personalized TCM diagnosis and treatment targeting the “pre-disease to disease” window period. This approach first proposes the idea of restructuring the conceptual framework of “symptom” and integrating multi-source heterogeneous data at macroscopic, mesoscopic, and microscopic levels to form a three-dimensional assessment indicator system. By integrating graph neural networks, convolutional neural networks, attention mechanisms, and knowledge graph-guided weight allocation, this approach enables collaborative representation, alignment, and fusion of multi-source data. Subsequently, it plans to construct a multimodal fusion model at both feature and decision levels, in order to establish mappings between indicators and TCM state elements, and to screen key indicators characterizing pathological evolution during the window period. Furthermore, it proposes a technical path for enhancing model interpretability using methods such as SHapley Additive exPlanations (SHAP) and Ablation-CAM++. Finally, with state assessment as the core, it proposes the concept of constructing a dynamic evaluation method for individualized diagnosis and treatment based on time-series data analysis using algorithms such as long short-term memory (LSTM) networks and gated recurrent units (GRUs). Moreover, a causal inference framework and semi-supervised learning strategies are introduced to enable quantitative evaluation of individual intervention effects and to provide interpretable therapeutic feedback, forming a complete technical path from data representation and fusion, weight adjustment, and interpretability analysis, to dynamic diagnosis feedback. This study aims to address deficiencies in the current TCM diagnosis and treatment model during the “pre-disease to disease” window period and to provide an operational framework for the clinical practice of TCM’s “treating disease before its onset”.
2.National clinical three-tiered surveillance and stratified precision detection report on respiratory infectious pathogens in 2024
Jingwen AI ; Jikui DENG ; Min DONG ; Xiaohong GAO ; Jiawei GENG ; Xiaoli HU ; Zhu JIN ; Hongyan LIU ; Yongzhong LI ; Xi LIU ; Yuanwang QIU ; Lihong QU ; Binhuang SUN ; Wei SONG ; Hongyu WANG ; Junping WANG ; Sen WANG ; Xiaoming XIONG ; Daokun YANG ; Liaoyun ZHANG ; Yanliang ZHANG ; Xianghong ZHOU ; Wenhong ZHANG
Chinese Journal of Infectious Diseases 2025;43(2):79-89
Objective:To analyze the epidemiological and clinical characteristics of respiratory pathogens in China.Methods:This study was a cross-sectional study, which encompassed 19 core units of the clinical pathogen network and established a three-tiered clinical pathogen surveillance system. Thirty respiratory samples were collected every two weeks from various units from January to December 2024, and the clinical and pathogen diagnostic information were gathered. A total of 11 864 samples were tested using this system. The tier-1 clinical pathogen surveillance system covered influenza A virus (Flu-A), influenza B virus (Flu-B), respiratory syncytial virus (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The tier-2 clinical pathogen surveillance system focused on 18 key respiratory pathogens. The tier-3 clinical pathogen surveillance system further clarified whether any emerging infectious diseases had occurred.Results:The tier-1 clinical pathogen surveillance system showed Flu-A predominated in December, Flu-B predominated in January, SARS-CoV-2 peaked in March and August, whereas RSV circulated sporadically throughout the year. Geographic trends were broadly consistent across the seven major regions, although Flu-A detection in December was notably higher in Northeast China (48.1%(111/231)) and East China (36.2%(148/409)), and RSV detection was concentrated in the Northwest and South China from January to March. Data from the tier-2 clinical pathogen surveillance system indicated that Streptococcus pneumoniae, Mycoplasma pneumoniae, rhinovirus, and adenovirus were detected year-round, of these, Streptococcus pneumoniae and rhinovirus showed elevated positive detection rates from August to September, while adenovirus peaked in January. Legionella pneumophila was not detected throughout the year, and other pathogens fluctuated throughout the year without a consistent pattern. The predominant etiologic agents of pediatric pneumonia were Mycoplasma pneumoniae (35.0%(105/300)), rhinovirus (25.7%(77/300)), and adenovirus (17.3%(52/300)), whereas adult pneumonia was mainly caused by Streptococcus pneumoniae (10.5%(29/277)), Staphylococcus aureus (6.9%(19/277)), Mycoplasma pneumoniae (6.9%(19/277)), and Flu-A (6.1%(17/277)). The tier-3 clinical pathogen surveillance system did not identify any emerging respiratory pathogens. Conclusion:Respiratory pathogens in China in 2024 exhibit distinct temporal and spatial distribution patterns and vary among different populations.
3.National clinical three-tiered surveillance and stratified precision detection report on respiratory infectious pathogens in 2024
Jingwen AI ; Jikui DENG ; Min DONG ; Xiaohong GAO ; Jiawei GENG ; Xiaoli HU ; Zhu JIN ; Hongyan LIU ; Yongzhong LI ; Xi LIU ; Yuanwang QIU ; Lihong QU ; Binhuang SUN ; Wei SONG ; Hongyu WANG ; Junping WANG ; Sen WANG ; Xiaoming XIONG ; Daokun YANG ; Liaoyun ZHANG ; Yanliang ZHANG ; Xianghong ZHOU ; Wenhong ZHANG
Chinese Journal of Infectious Diseases 2025;43(2):79-89
Objective:To analyze the epidemiological and clinical characteristics of respiratory pathogens in China.Methods:This study was a cross-sectional study, which encompassed 19 core units of the clinical pathogen network and established a three-tiered clinical pathogen surveillance system. Thirty respiratory samples were collected every two weeks from various units from January to December 2024, and the clinical and pathogen diagnostic information were gathered. A total of 11 864 samples were tested using this system. The tier-1 clinical pathogen surveillance system covered influenza A virus (Flu-A), influenza B virus (Flu-B), respiratory syncytial virus (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The tier-2 clinical pathogen surveillance system focused on 18 key respiratory pathogens. The tier-3 clinical pathogen surveillance system further clarified whether any emerging infectious diseases had occurred.Results:The tier-1 clinical pathogen surveillance system showed Flu-A predominated in December, Flu-B predominated in January, SARS-CoV-2 peaked in March and August, whereas RSV circulated sporadically throughout the year. Geographic trends were broadly consistent across the seven major regions, although Flu-A detection in December was notably higher in Northeast China (48.1%(111/231)) and East China (36.2%(148/409)), and RSV detection was concentrated in the Northwest and South China from January to March. Data from the tier-2 clinical pathogen surveillance system indicated that Streptococcus pneumoniae, Mycoplasma pneumoniae, rhinovirus, and adenovirus were detected year-round, of these, Streptococcus pneumoniae and rhinovirus showed elevated positive detection rates from August to September, while adenovirus peaked in January. Legionella pneumophila was not detected throughout the year, and other pathogens fluctuated throughout the year without a consistent pattern. The predominant etiologic agents of pediatric pneumonia were Mycoplasma pneumoniae (35.0%(105/300)), rhinovirus (25.7%(77/300)), and adenovirus (17.3%(52/300)), whereas adult pneumonia was mainly caused by Streptococcus pneumoniae (10.5%(29/277)), Staphylococcus aureus (6.9%(19/277)), Mycoplasma pneumoniae (6.9%(19/277)), and Flu-A (6.1%(17/277)). The tier-3 clinical pathogen surveillance system did not identify any emerging respiratory pathogens. Conclusion:Respiratory pathogens in China in 2024 exhibit distinct temporal and spatial distribution patterns and vary among different populations.
4.A multi-center epidemiological study on pneumococcal meningitis in children from 2019 to 2020
Cai-Yun WANG ; Hong-Mei XU ; Gang LIU ; Jing LIU ; Hui YU ; Bi-Quan CHEN ; Guo ZHENG ; Min SHU ; Li-Jun DU ; Zhi-Wei XU ; Li-Su HUANG ; Hai-Bo LI ; Dong WANG ; Song-Ting BAI ; Qing-Wen SHAN ; Chun-Hui ZHU ; Jian-Mei TIAN ; Jian-Hua HAO ; Ai-Wei LIN ; Dao-Jiong LIN ; Jin-Zhun WU ; Xin-Hua ZHANG ; Qing CAO ; Zhong-Bin TAO ; Yuan CHEN ; Guo-Long ZHU ; Ping XUE ; Zheng-Zhen TANG ; Xue-Wen SU ; Zheng-Hai QU ; Shi-Yong ZHAO ; Lin PANG ; Hui-Ling DENG ; Sai-Nan SHU ; Ying-Hu CHEN
Chinese Journal of Contemporary Pediatrics 2024;26(2):131-138
Objective To investigate the clinical characteristics and prognosis of pneumococcal meningitis(PM),and drug sensitivity of Streptococcus pneumoniae(SP)isolates in Chinese children.Methods A retrospective analysis was conducted on clinical information,laboratory data,and microbiological data of 160 hospitalized children under 15 years old with PM from January 2019 to December 2020 in 33 tertiary hospitals across the country.Results Among the 160 children with PM,there were 103 males and 57 females.The age ranged from 15 days to 15 years,with 109 cases(68.1% )aged 3 months to under 3 years.SP strains were isolated from 95 cases(59.4% )in cerebrospinal fluid cultures and from 57 cases(35.6% )in blood cultures.The positive rates of SP detection by cerebrospinal fluid metagenomic next-generation sequencing and cerebrospinal fluid SP antigen testing were 40% (35/87)and 27% (21/78),respectively.Fifty-five cases(34.4% )had one or more risk factors for purulent meningitis,113 cases(70.6% )had one or more extra-cranial infectious foci,and 18 cases(11.3% )had underlying diseases.The most common clinical symptoms were fever(147 cases,91.9% ),followed by lethargy(98 cases,61.3% )and vomiting(61 cases,38.1% ).Sixty-nine cases(43.1% )experienced intracranial complications during hospitalization,with subdural effusion and/or empyema being the most common complication[43 cases(26.9% )],followed by hydrocephalus in 24 cases(15.0% ),brain abscess in 23 cases(14.4% ),and cerebral hemorrhage in 8 cases(5.0% ).Subdural effusion and/or empyema and hydrocephalus mainly occurred in children under 1 year old,with rates of 91% (39/43)and 83% (20/24),respectively.SP strains exhibited complete sensitivity to vancomycin(100% ,75/75),linezolid(100% ,56/56),and meropenem(100% ,6/6).High sensitivity rates were also observed for levofloxacin(81% ,22/27),moxifloxacin(82% ,14/17),rifampicin(96% ,25/26),and chloramphenicol(91% ,21/23).However,low sensitivity rates were found for penicillin(16% ,11/68)and clindamycin(6% ,1/17),and SP strains were completely resistant to erythromycin(100% ,31/31).The rates of discharge with cure and improvement were 22.5% (36/160)and 66.2% (106/160),respectively,while 18 cases(11.3% )had adverse outcomes.Conclusions Pediatric PM is more common in children aged 3 months to under 3 years.Intracranial complications are more frequently observed in children under 1 year old.Fever is the most common clinical manifestation of PM,and subdural effusion/emphysema and hydrocephalus are the most frequent complications.Non-culture detection methods for cerebrospinal fluid can improve pathogen detection rates.Adverse outcomes can be noted in more than 10% of PM cases.SP strains are high sensitivity to vancomycin,linezolid,meropenem,levofloxacin,moxifloxacin,rifampicin,and chloramphenicol.[Chinese Journal of Contemporary Pediatrics,2024,26(2):131-138]
5.Influencing factors for surgical site infection after gastrointestinal perfora-tion repair surgery:analysis based on decision tree and logistic regression model
Deng-Min HU ; Run XU ; Jian LI ; Yu AI
Chinese Journal of Infection Control 2024;23(7):826-832
Objective To analyze the influencing factors for surgical site infection(SSI)after gastrointestinal per-foration repair surgery by decision tree and logistic regression model.Methods Patients who underwent gastroin-testinal perforation repair surgery at a hospital of Mianyang City from January 2018 to January 2023 were selected as the research subjects.Clinical data of the patients were collected.Patients were divided into the SSI(+)group(n-41)and the SSI(-)group(n-322)based on whether SSI occurred after surgery.Influencing factors for SSI after gastrointestinal perforation repair surgery were analyzed by univariate and multivariate logistic regression.Re-levant decision tree prediction model was constructed.Results Among the 363 patients who underwent gastrointes-tinal perforation repair surgery,41 developed postoperative SSI,with an incidence of 11.29%.Univariate analysis results showed that there were statistically significant differences between two groups of patients in body mass index(BMI),albumin level,preoperative antimicrobial use,duration of preoperative abdominal pain,and duration of sur-gery(all P<0.05).Multivariate logistic regression analysis showed that higher BMI(OR=2.059,95%CI:1.103-3.842),albumin levels<35 g/L(OR=2.761,95%CI:1.312-5.811),duration of preoperative abdominal pain≥24 hours(OR=3.589,95%CI:1.659-7.763),and duration of surgery ≥2 hours(OR=3.314,95%CI:1.477-7.435)were independent risk factors for postoperative SSI in patients after gastrointestinal perforation re-pair surgery(P<0.05),while preoperative antimicrobial use was a protective factor(OR=0.338,95%CI:0.166-0.690,P<0.05).The decision tree model based on the above factors was constructed to predict the risk of SSI in patients after gastrointestinal perforation repair surgery.Validation of the model showed that the area under the re-ceiver operating characteristic(ROC)curve(AUC)was 0.811(95%CI:0.794-0.825).Conclusion The risk factors for postoperative SSI in patients after gastrointestinal perforation repair surgery include high BMI,albumin level<35 g/L,duration of preoperative abdominal pain ≥24 hours,and duration of surgery ≥2 hours.The pro-tective factor is antimicrobial use before surgery.The decision tree model constructed based on the influencing factors has good predictive ability for the risk of postoperative SSI in patients after gastrointestinal perforation repair surgery.
6.Epidemiologic characteristics and influencing factors of influenza outbreaks in Guangdong Province, 2015-2022.
Ya Li ZHUANG ; Jie LU ; Shu Kai WU ; Zhan Hui ZHANG ; Zhi Mei WEI ; Yi Hong LI ; Ting HU ; Min KANG ; Ai Ping DENG
Chinese Journal of Epidemiology 2023;44(6):942-948
Objective: To grasp the epidemiological characteristics of influenza outbreaks in Guangdong Province by analyzing the outbreaks of influenza-like cases reported in Guangdong Province from January 2015 to the end of August 2022. Methods: In response to the outbreak of epidemics in Guangdong Province from 2015 to 2022, information on on-site epidemic control was collected, and epidemiological analysis was conducted to describe the characteristics of the epidemics. The factors that influence the intensity and duration of the outbreak were determined through a logistic regression model. Results: A total of 1 901 influenza outbreaks were reported in Guangdong Province, with an overall incidence of 2.05%. Most outbreak reports occurred from November to January of the following year (50.24%, 955/1 901) and from April to June (29.88%, 568/1 901). A total of 59.23% (1 126/1 901) of the outbreaks were reported in the Pearl River Delta region, and primary and secondary schools were the main places where outbreaks occurred (88.01%, 1 673/1 901). Outbreaks with 10-29 cases were the most common (66.18%, 1 258/1 901), and most outbreaks lasted less than seven days (50.93%,906/1 779). The size of the outbreak was related to the nursery school (aOR=0.38, 95%CI:0.15-0.93), the Pearl River Delta region (aOR=0.60, 95%CI:0.44-0.83), the time interval between the onset of the first case and the time of report (>7 days compared with ≤3 days: aOR=3.01, 95%CI:1.84-4.90), the influenza A(H1N1) (aOR=2.02, 95%CI:1.15-3.55) and the influenza B (Yamagata) (aOR=2.94, 95%CI: 1.50-5.76). The duration of outbreaks was related to school closures (aOR=0.65, 95%CI: 0.47-0.89), the Pearl River Delta region (aOR=0.65, 95%CI: 0.50-0.83) and the time interval between the onset of the first case and the time of report (>7 days compared with ≤3 days: aOR=13.33, 95%CI: 8.80-20.19; 4-7 days compared with ≤3 days: aOR=2.56, 95%CI: 1.81-3.61). Conclusions: An influenza outbreak in Guangdong Province exhibits two peaks, one in the winter and spring seasons and the other in the summer. Primary and secondary schools are high-risk areas, and early reporting of outbreaks is critical for controlling influenza outbreaks in schools. Furthermore, comprehensive measures should be taken to prevent the spread of the epidemic.
Humans
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Influenza A Virus, H1N1 Subtype
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Influenza, Human/epidemiology*
;
Disease Outbreaks
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Epidemics
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China/epidemiology*
7.Analysis of the impact of health management measures for entry personnel on imported Dengue fever in Guangdong Province, 2020-2022.
Xiao Hua TAN ; Ai Ping DENG ; Ying Tao ZHANG ; Min LUO ; Hui DENG ; Yu Wei YANG ; Jin Hua DUAN ; Zhi Qiang PENG ; Meng ZHANG
Chinese Journal of Epidemiology 2023;44(6):954-959
Objective: To explore the impact of health management measures for entry personnel (entry management measures) against COVID-19 on the epidemiological characteristics of imported Dengue fever in Guangdong Province from 2020 to 2022. Methods: Data of imported Dengue fever from January 1, 2016 to August 31, 2022, mosquito density surveillance from 2016 to 2021, and international airline passengers and Dengue fever annual reported cases from 2011 to 2021 in Guangdong were collected. Comparative analysis was conducted to explore changes in the epidemic characteristics of imported Dengue fever before the implementation of entry management measures (from January 1, 2016 to March 20, 2020) and after the implementation (from March 21, 2020 to August 31, 2022). Results: From March 21, 2020, to August 31, 2022, a total of 52 cases of imported Dengue fever cases were reported, with an imported risk intensity of 0.12, which were lower than those before implementation of entry management measures (1 828, 5.29). No significant differences were found in the characteristics of imported cases before and after implementation of entry management measures, including seasonality, sex, age, career, and imported countries (all P>0.05). 59.62% (31/52) of cases were found at the centralized isolation sites and 38.46% (20/52) at the entry ports. However, before implementation of entry management measures, 95.08% (1 738/1 828) of cases were found in hospitals. Among 51 cases who had provided entry dates, 82.35% (42/51) and 98.04% (50/51) of cases were found within seven days and fourteen days after entry, slightly higher than before implementation [(72.69%(362/498) and 97.59% (486/498)]. There was significant difference between the monthly mean values of Aedes mosquito larval density (Bretto index) from 2020 to 2021 and those from 2016 to 2019 (Z=2.83, P=0.005). There is a strong positive correlation between the annual international airline passengers volume in Guangdong from 2011 to 2021 and the annual imported Dengue fever cases (r=0.94, P<0.001), and a positive correlation also existed between the international passenger volume and the annual indigenous Dengue fever cases (r=0.72, P=0.013). Conclusions: In Guangdong, the entry management measures of centralized isolation for fourteen days after entry from abroad had been implemented, and most imported Dengue fever cases were found within fourteen days after entry. The risk of local transmission caused by imported cases has reduced significantly.
Animals
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Humans
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COVID-19
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Aedes
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Epidemics
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China/epidemiology*
;
Dengue/epidemiology*
8.Bipedicled scrotal flaps combined with keystone-design perforator island flaps in repairing postoperative large-area defects in 6 male patients with extramammary Paget′s disease of the perineum
Min WANG ; Yong AI ; Hui ZHANG ; Yuyu DENG ; Weiqi LEI
Chinese Journal of Dermatology 2023;56(1):64-66
Objective:To evaluate clinical efficacy of bipedicled scrotal flaps combined with keystone-design perforator island flaps in repairing postoperative large-area defects in male patients with extramammary Paget′s disease of the perineum.Methods:Clinical data were collected from 6 male patients with extramammary Paget′s disease of the perineum in Dermatology Hospital of Jiangxi Province from February 2018 to March 2019, and analyzed retrospectively. These patients were aged from 70 to 84 years (median, 77.5 years) , skin lesions involved the mons pubis, penis and scrotum, and the area of postoperative skin defects varied from 18 to 133 cm 2 (median, 96 cm 2) in size. In all the patients, mons pubis defects after tumor resection were repaired with abdominal keystone-design perforator island flaps, and scrotal and penile defects were repaired with bipedicled scrotal flaps using the remaining scrotal tissues. These patients were followed up at 1 and 3 months after surgery and every 3 months thereafter. Results:All the 6 patients were followed up for 3 - 36 months, with an average of 10 months. All flaps survived with a good color and texture match, and favorable function and appearance were achieved in both the donor and recipient sites.Conclusions:The bipedicled scrotal flaps combined with keystone-design perforator island flaps can repair postoperative large-area defects in male patients with extramammary Paget′s disease of the perineum. Moreover, the operation is simple, and good blood supply can be achieved.
9.Analysis on characteristics and influencing factors of COVID-19 confirmed cases with viral nucleic acid re-positive after discharge in Guangdong Province.
Xiao Hua TAN ; Min KANG ; Ai Ping DENG ; Bai Sheng LI ; Min LUO ; Yao YI ; YaLi ZHUANG ; YingTao ZHANG ; Tie SONG
Chinese Journal of Preventive Medicine 2022;56(1):49-55
Objective: To analyze the epidemiological characteristics and influencing factors of COVID-19 confirmed cases with viral nucleic acid re-positive in anal and/or throat swabs after discharge during the domestic imported epidemic stage in Guangdong Province in early 2020. Methods: The COVID-19 confirmed cases with the onset time before March 1, 2020 in Guangdong Province were collected to analyze the demographic data, epidemiological characteristics, and specimen collection and testing data after discharge. Logistic regression model was used for influencing factors analysis of re-positive cases. Results: A total of 1 286 COVID-19 confirmed cases were included, the M(Q1,Q3) of age was 44(32,58)years, 617 cases were male, 224 cases were re-positive in anal and/or throat swabs with the re-positive rate 17.42%. The M(Q1,Q3) of age of re-positive cases was 35(23, 50) years, which was younger than that of re-negative cases age was those 46(33, 59) years (P<0.001). With the increase of age, re-positive rate decreased (χ2trend=52.73, P<0.001). 85.27% (191/224) of re-positive cases were found in 14 d after discharge, the duration time of re-positive status was 13(7, 24) d, and 81.69% (183/224) of re-positive cases were re-tested negative in 28 d after re-positive date. No fever and other symptoms had been observed among re-positive cases during the whole follow-up. No secondary infectious cases had been found among close contacts after 14 d of centralized isolation and sampling screening. Univariate logistic regression model analysis revealed that the influencing factors of the re-positive cases included age, occupation, clusters, clinical types, and admission time. Multivariate logistic regression model analysis revealed that age was an independent risk factor. Conclusions: SARS-CoV-2 viral nucleic acid re-positive is found in COVID-19 confirmed cases after discharge in Guangdong Province. Most re-positive cases are confirmed among 14 d after discharge and re-test to negative among 28 d after re-positive date. Age is an risk factor for re-positive cases after discharge.
COVID-19
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China/epidemiology*
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Epidemics
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Humans
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Male
;
Nucleic Acids
;
SARS-CoV-2
10.Course of disease and related epidemiological parameters of COVID-19: a prospective study based on contact tracing cohort.
Yan ZHOU ; Wen Jia LIANG ; Zi Hui CHEN ; Tao LIU ; Tie SONG ; Shao Wei CHEN ; Ping WANG ; Jia Ling LI ; Yun Hua LAN ; Ming Ji CHENG ; Jin Xu HUANG ; Ji Wei NIU ; Jian Peng XIAO ; Jian Xiong HU ; Li Feng LIN ; Qiong HUANG ; Ai Ping DENG ; Xiao Hua TAN ; Min KANG ; Gui Min CHEN ; Mo Ran DONG ; Hao Jie ZHONG ; Wen Jun MA
Chinese Journal of Preventive Medicine 2022;56(4):474-478
Objective: To analyze the course of disease and epidemiological parameters of COVID-19 and provide evidence for making prevention and control strategies. Methods: To display the distribution of course of disease of the infectors who had close contacts with COVID-19 cases from January 1 to March 15, 2020 in Guangdong Provincial, the models of Lognormal, Weibull and gamma distribution were applied. A descriptive analysis was conducted on the basic characteristics and epidemiological parameters of course of disease. Results: In total, 515 of 11 580 close contacts were infected, with an attack rate about 4.4%, including 449 confirmed cases and 66 asymptomatic cases. Lognormal distribution was fitting best for latent period, incubation period, pre-symptomatic infection period of confirmed cases and infection period of asymptomatic cases; Gamma distribution was fitting best for infectious period and clinical symptom period of confirmed cases; Weibull distribution was fitting best for latent period of asymptomatic cases. The latent period, incubation period, pre-symptomatic infection period, infectious period and clinical symptoms period of confirmed cases were 4.50 (95%CI:3.86-5.13) days, 5.12 (95%CI:4.63-5.62) days, 0.87 (95%CI:0.67-1.07) days, 11.89 (95%CI:9.81-13.98) days and 22.00 (95%CI:21.24-22.77) days, respectively. The latent period and infectious period of asymptomatic cases were 8.88 (95%CI:6.89-10.86) days and 6.18 (95%CI:1.89-10.47) days, respectively. Conclusion: The estimated course of COVID-19 and related epidemiological parameters are similar to the existing data.
COVID-19
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Cohort Studies
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Contact Tracing
;
Humans
;
Incidence
;
Prospective Studies

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