[Epidemiologic characteristics and influencing factors of influenza outbreaks in Guangdong Province, 2015-2022].

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.

[Analysis of the impact of health management measures for entry personnel on imported Dengue fever in Guangdong Province, 2020-2022].

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.

[Progress in research of 2019-nCoV Omicron variant].

2019-nCoV Omicron (B.1.1.529) variant, which has brought new challenges to the prevention and control of COVID-19 pandemic, has the characteristics of stronger transmissibility and more rapid transmission and more significant immune evasion. It took only two months to become a predominant strain worldwide after its identification in South Africa in November 2021. Local epidemics caused by Omicron variant have been reported in several provinces in China. However, the epidemiological characteristics of highly mutated Omicron variant remain unclear. This article summarizes the progress in the research of functional mutations, transmissibility, virulence, immune evasion and cross-reactive immune responses of Omicron variant, to provide references for the effective prevention and control of COVID-19 pandemic caused by Omicron variant.

[Course of disease and related epidemiological parameters of COVID-19: a prospective study based on contact tracing cohort].

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.

[Analysis on characteristics and influencing factors of COVID-19 confirmed cases with viral nucleic acid re-positive after discharge in Guangdong Province].

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.

[Analysis on the cluster epidemic of coronavirus disease 2019 in Guangdong Province].

Objective: Analysis of clustering characteristics of coronavirus disease 2019 (COVID-19) in Guangdong Province. Methods: The COVID-19 cases in Guangdong Province onset from January 1 to February 29, 2020 were collected from Chinese information system for disease control and prevention and Emergency Public Reporting System. Obtain the epidemiological survey data of the cluster epidemic situation, and clarify the scale of cluster epidemic situation, the characteristics of the index cases, family and non-family subsequent cases. Calculate serial interval according to the onset time of the index cases and subsequent cases, secondary attack rate based on the close contacts tracking results, the characteristics of different cases in the clustered epidemic were compared. Results: A total of 283 cluster were collected, including 633 index cases, 239 subsequent cases. Families are mainly clustered, the total number involved in each cluster is in the range of 2-27, M (P25, P75) are 2.0 (2.0, 4.0). During January 15 to February 29, the secondary attack rate is 2.86% (239/8 363) in Guangdong Province, the family secondary attack rate was 4.84% (276/3 697), and the non-family secondary attack rate was 1.32% (61/4 632). According to the reporting trend of the number of cases in Guangdong Province, it can be divided into four stages, the rising stage, the high platform stage, the descending stage and the low level fluctuation period. The secondary attack rate of the four stages were 3.5% (140/3 987), 2.3% (55/2 399), 2.6% (37/1 435), 1.3% (7/542), respectively. The difference was statistically significant (P=0.003). Conclusion: COVID-19 cluster mainly occurs in families in Guangdong Province. The scale of the clustered epidemic was small; the serial interval was short; and the overall secondary attack rate was low.

[Clinical outcomes of COVID-19 cases and influencing factors in Guangdong province].

Objective: To analyze the clinical courses and outcomes of COVID-19 cases and the influencing factors in Guangdong province and provide basis for the formulation or adjustment of medical care and epidemic control strategy for COVID-19. Methods: We collected demographic data, medical histories, clinical courses and outcomes of 1 350 COVID-19 patients reported in Guangdong as of 4 March 2020 via epidemiological investigation and process tracking. Disease severity and clinical course characteristics of the patients and influencing factors of severe illness were analyzed in our study. Results: Among 1 350 cases of COVID-19 cases in Guangdong, 72 (5.3%) and 1 049 (77.7%) were mild and ordinary cases, 164 (12.1%) were severe cases, 58 (4.3%) were critical cases and 7 (0.5%) were fatal. The median duration of illness were 23 days (P(25), P(75): 18, 31 days) and the median length of hospitalization were 20 days (P(25), P(75): 15,27 days). For severe cases, the median time of showing severe manifestations was on the 12(th) day after onset (P(25), P(75): 9(th) to 15(th) days), and the median time of severe manifestation lasted for 8 days (P(25), P(75): 4, 14 days). Among 1 066 discharged/fetal cases, 36.4% (36/99) and 1.0% (1/99) of the mild cases developed to ordinary cases and severe cases respectively after admission; and 5.2% (50/968) and 0.6% (6/968) of the ordinary cases developed to severe cases, and critical cases respectively after admission. In severe cases, 11.4% developed to critical cases (10/88). The influencing factors for severe illness or worse included male (aHR=1.87, 95%CI: 1.43-2.46), older age (aHR=1.67, 95%CI: 1.51-1.85), seeking medical care on day 2-3 after onset (aHR=1.73, 95%CI: 1.20-2.50) pre-existing diabetes (aHR=1.75, 95%CI: 1.12-2.73) and hypertension (aHR=1.49, 95%CI: 1.06-2.09). Conclusions: The course of illness and length of hospitalization of COVID-19 cases were generally long and associated with severity of disease clinical outcomes. The severe cases were mainly occurred in populations at high risk. In the epidemic period, classified management of COVID-19 cases should be promoted according to needs for control and prevention of isolation and treatment for the purpose of rational allocation of medical resources.

MiR-92b inhibited cells EMT by targeting Gabra3 and predicted prognosis of triple negative breast cancer patients.

OBJECTIVE: Triple negative breast cancer (TNBC) is a subtype of breast cancer without the three markers, which has a poor prognosis than other types. Recently, studies have identified that microRNA-92b (miR-92b) acted as potential oncogene in tumor progression, however, the biological roles of miR-92b in TNBC remain unknown. The purpose of this study was to investigate the functions of miR-92b and verify its effect on the regulation of Gabra3 in TNBC. MATERIALS AND METHODS: Dual-Luciferase reporter assay was recruited to confirm whether miR-92b directly binds to the 3'-untranslated region (3'-UTR) of Gabra3 mRNA in TNBC. Transwell assay was employed to analyze the capacities of migration and invasion. Western blot was applied to evaluate the expression of the special proteins that including Gabra3, epithelial-mesenchymal transition (EMT) markers and GAPDH. RESULTS: We demonstrated that miR-92b was remarkably low expressed in TNBC tissues and cell lines, and particularly in inhibiting the migration, invasion and EMT of TNBC cells. On the contrary, Gabra3 was significantly overexpressed in TNBC tissues and cell lines in comparison with the corresponding paracancerous tissues and the normal breast epithelial cell line. The expression of miR-92b had a negative correlation with the expression of Gabra3 in TNBC tissues. Downregulation of Gabra3 could inhibit the migration, invasion and EMT of TNBC cells. MiR-92b mediated the expression of Gabra3 through directly binding to the 3'-UTR of Gabra3 mRNA. In addition, low expression of miR-92b or overexpression of Gabra3 predicted poor prognosis of TNBC patients. CONCLUSIONS: MiR-92b inhibited the migration and invasion-mediated EMT through directly targeting the 3'-UTR of Gabra3 mRNA in triple negative breast cancer. The newly identified miR-92b/Gabra3 axis may make it to be a new target for clinical diagnosis and treatment of TNBC.

CD31 induces inflammatory response by promoting hepatic inflammatory response and cell apoptosis.

OBJECTIVE: To investigate whether CD31 could regulate paracetamol-induced liver injury, thereby providing a new direction for the prevention and treatment of drug-induced hepatitis. MATERIALS AND METHODS: Wild-type (WT) mice were treated with acetaminophen (APAP) (250 mg/kg) or isodose of phosphate-buffered saline (PBS). 1, 3, 6 and 12 h after the treatment, the messenger RNA (mRNA) and protein expression level of CD31 in the liver of mice were determined by Real-time reverse transcription polymerase chain reaction (RT-PCR) and Western blotting, respectively. Once CD31 was confirmed to be involved in APAP-induced liver injury, the acute liver injury model in WT mice and CD31 gene deficient (CD31-/-) mice induced by APAP was established. Serum samples were collected at 8 and 24 h after APAP injection (250 mg/kg), and the activity of serum alanine aminotransferase (ALT) was measured. The liver tissues of mice were isolated and analyzed by hematoxylin and eosin (HE) staining. Meanwhile, mononuclear cells (MNCs) were isolated from the liver tissues of mice. The number of infiltrating macrophages and neutrophils was detected by flow cytometry, and the activation level of these cells was analyzed. The expression levels of proinflammatory cytokines in liver tissues, such as TNF-α, IL-1ß, keratinocyte chemoattractant (KC), MCP-1 and IL-6, were determined by RT-PCR. The expression levels of cytokines in serum were detected by enzyme-linked immunosorbent assay (ELISA). Moreover, the protein expression levels of JNK, Caspase-3, and cytochrome P450 2E1 (CYP2E1) in liver tissues were detected by Western blotting. RESULTS: After APAP treatment, we found that WT mice were more sensitive to APAP-induced liver injury. The level of ALT in WT mice was significantly higher than that of CD31-/- mice, meanwhile, more necrotic or apoptotic cells were found in WT mice. Results also indicated that the expression levels of inflammatory cytokines, including KC, IL-1ß, MCP-1 and IL-6, were significantly higher in WT mice. Meanwhile, the number of infiltrating macrophages and neutrophils in the liver tissues of WT mice were much more than that of CD31-/- mice. CONCLUSIONS: APAP-treated CD31-/- mice exhibited less liver injury when compared with WT mice. We also confirmed that CD31 was greatly involved in APAP-induced inflammatory response by promoting hepatic inflammatory and cell apoptosis, which might provide a new strategy for the prevention and treatment of drug-induced hepatitis.