SARS-CoV-2 Infection, Hospitalization, and Associated Factors Among People Living With HIV in Southeastern China From December 2022 to February 2023: Cross-Sectional Survey.

BACKGROUND: Limited studies have explored the impact of the Omicron variant on SARS-CoV-2 infection, hospitalization, and associated factors among people living with HIV, particularly in China. The adjustment of preventive policies since December 2022 in China presents an opportunity to evaluate the real-world factors influencing SARS-CoV-2 infection and related hospitalization among people living with HIV. OBJECTIVE: This study aimed to investigate SARS-CoV-2 infection, hospitalization rates, and associated factors among people living with HIV following the adjustment of preventive policies from December 2022 to February 2023 in southeastern China. METHODS: A cross-sectional telephone or web-based survey was conducted among people living with HIV in 5 cities in southeastern China from December 2022 to February 2023. Demographic information, SARS-CoV-2 infection and related hospitalization, and HIV-specific characteristics were collected from existing databases and special investigations. Multivariate logistic regression analyses were conducted to determine the associated factors for infection and hospitalization rates of SARS-CoV-2. Additionally, subgroup analyses were conducted for the association between vaccination and infection across different vaccination statuses and time since the last vaccination. RESULTS: Among people living with HIV with a COVID-19 testing history, the SARS-CoV-2 infection rate was 67.13% (95% CI 65.81%-68.13%), whereas the hospitalization rate was 0.71% (95% CI 0.46%-0.97%). Factors such as age, latest CD4 cell count, latest HIV viral load, and transmission route were found to be associated with SARS-CoV-2 infection, while age, cancer, latest CD4 cell count, and latest HIV viral load were associated with SARS-CoV-2 hospitalization. In terms of SARS-CoV-2 vaccination, compared to unvaccinated people living with HIV, there was a lower infection rate among those who had been vaccinated for <3 months in the booster vaccination group (adjusted odds ratio [aOR] 0.72, 95% CI 0.53-0.98; P=.04); and there was also a lower risk of hospitalization among people living with HIV who had received vaccination in the past 6-12 months (aOR 0.33, 95% CI 0.14-0.81; P=.02) and more than 12 months ago (aOR 0.22, 95% CI 0.07-0.72; P=.01). CONCLUSIONS: After the ease of prevention and control measures in China, we observed a high SARS-CoV-2 infection rate but a low hospitalization rate. General risk factors, such as higher age and vaccination status, and HIV-related parameters, such as the latest CD4 cell count and HIV viral load, were associated with SARS-CoV-2 infection and hospitalization. A booster vaccination campaign for booster doses should be considered among people living with HIV in confronting possible COVID-19 epidemic emergencies in the near future.

A Novel Model for Evaluating the Natural Antioxidant Carnosic Acid to Improve the Stability of Rapeseed Oil in the Thermal Degradation.

The quality and stability of oil during thermal processing reflect the reactions in vegetable oil. The deterioration of the oil is close to the viscosity, fatty acid composition (FA), total polar compounds (TPC), etc. Carnosic acid (CA) is the main antioxidant component of rosemary extract; it is a natural and clean-label antioxidant that is allowed to be added to prolong oil processing and storage. To achieve a clear correlation of this situation, a novel stability evaluation model was used to predict the thermal degradation of rapeseed oil (RSO) with CA. The RSO with CA (200 mg/kg, 400 mg/kg, and 700 mg/kg), the tert-Butylhydroquinone (TBHQ, 200 mg/kg), and the fresh RSO (without additives) during thermal processing (180 ± 5 °C) were studied. The temperature dependency of viscosity fits well with the Lioumbas model (R2 ≥ 0.999). The parameter b value in the Lioumbas model showed a decrease linearly with the processing time (tP, R2 ≥ 0.965). The multiple linear regression analysis showed that the accuracy of the model in predicting viscosity was less than ±2 mPa·s-1, and the deviation% was less than ±10% in all the samples. After 32 h of thermal degradation, the addition of 700 mg/kg CA showed the lowest degradation rate (13.84%) of polyunsaturated fatty acids (PUFAs), and the TPC content was 26.00 ± 0.50%. The TPC showed a positive relationship with viscosity (r = 0.99, p < 0.01), tP (r = 0.97, p < 0.01), and effective carbon numbers (ECN, r = 0.84, p < 0.05). In conclusion, this study can make a potential prediction for the stability of RSO.

Spatiotemporal Pattern and Its Determinants for Newly Reported HIV/AIDS Among Older Adults in Eastern China From 2004 to 2021: Retrospective Analysis Study.

BACKGROUND: In recent years, the number and proportion of newly reported HIV/AIDS cases among older adults have increased dramatically. However, research on the pattern of temporal and spatial changes in newly reported HIV/AIDS among older adults remains limited. OBJECTIVE: This study analyzed the spatial and temporal distribution of HIV/AIDS cases and its influencing factors among older adults in Eastern China from 2004 to 2021, with the goal of improving HIV/AIDS prevention and intervention. METHODS: We extracted data on newly reported HIV/AIDS cases between 2004 and 2021 from a case-reporting system and used a Joinpoint regression model and an age-period-cohort model to analyze the temporal trends in HIV/AIDS prevalence. Spatial autocorrelation and geographically weighted regression models were used for spatial aggregation and influence factor analysis. RESULTS: A total of 12,376 participants with HIV/AIDS were included in the study. The newly reported HIV infections among older adults increased from 0.13 cases per 100,000 people in 2004 to 7.00 cases per 100,000 people in 2021. The average annual percent change in newly reported HIV infections was 28.0% (95% CI -21.6% to 34.8%). The results of the age-period-cohort model showed that age, period, and cohort factors affected the newly reported HIV infections among older adults. The newly reported HIV/AIDS cases among men who have sex with men (MSM) had spatial clustering, and the hotspots were mainly concentrated in Hangzhou. The disposable income of urban residents, illiteracy rate among people aged 15 years or older, and number of hospital beds per 1000 residents showed a positive association with the newly reported HIV infections among older MSM in the Zhejiang province. CONCLUSIONS: HIV/AIDS among older adults showed an increasing trend and was influenced by age, period, and cohort effects. Older MSM with HIV/AIDS showed regional clustering and was associated with factors such as the disposable income of urban residents, the illiteracy rate among people aged 15 years or older, and the number of hospital beds per 1000 people. Targeted prevention and control measures are needed to reduce HIV infection among those at higher risk.

The impact of anxiety, depression, and social support on the relationship between HIV-related stigma and mental health-related quality of life among Chinese patients: a cross-sectional, moderate-mediation study.

BACKGROUND/OBJECTIVE: People living with HIV (PLWH) are prone to mental health problems and evidence indicates that HIV-related stigma can negatively impact mental health-related quality of life. This study explored potential mechanisms between HIV-related stigma and mental health-related quality of life, specifically whether anxiety or depression mediates, and whether social support moderates, the relationship. METHOD: A total of 1197 Chinese PLWH participated in the study. The Berger HIV Stigma Scale, the Hospital Anxiety and Depression Scale (HADS), the 12-item Brief Health Survey (SF-12), and the Multidimensional Scale of Perceived Social Support (MSPSS) were employed. RESULTS: HIV-related stigma was negatively associated with mental health-related quality of life. Anxiety and depression partially mediated the relationship between HIV-related stigma and mental health-related quality of life; social support played a moderating role. CONCLUSIONS: The mental health-related quality of life in PLWH was shown to be indirectly affected by HIV-related stigma through anxiety and depression in China. The negative impact of HIV-related stigma decreased with increased social support.

Perceived social support and depression among people living with HIV in China: roles of stigma and adherence self-efficacy.

INTRODUCTION: People living with HIV (PLHIV) are a high-risk group for depression. In particular, the prevalence and burden of depression is higher and more severe among PLHIV in developing and less-developed countries. There is evidence that perceived social support has a positive impact on reducing the occurrence of depression, and high stigma and low adherence self-efficacy are barriers to the effectiveness of social support for depressed PLHIV. However, how these risks affect the effect of social support on depression still needs further identification. METHODS: Between 2017 and 2018, a total of 1139 Chinese PLHIV (74.36% male, mean age = 43.91 years) from three provinces (Shanghai, Zhejiang and Henan) in China were enrolled in the study. Data were analyzed by multiple regression, mediation model, and moderation model. RESULTS: A total of 43.99% of PLHIV had mild to severe depression. There was a significant negative association between perceived social support and depression (B = -0.049, P < 0.05). Stigma and adherence self-efficacy played a chain mediating role (B = -0.058, 95% CI: -0.078 ~ 0.039) and a moderating role in the effect of perceived social support on depression (stigma: B = -0.003, P < 0.05; adherence self-efficacy: B = 0.004, P < 0.05). CONCLUSION: Stigma and adherence self-efficacy indirectly predicted depression, and perceived social support was more effective in reducing depression among PLHIV with high stigma or low adherence self-efficacy. Enhancing multiple social support resources for PLHIV may reduce their risk of depression. Moreover, the need for social support is greater for those with high stigma or low adherence self-efficacy.

Development and validation of a risk score for predicting inconsistent condom use with women among men who have sex with men and women.

BACKGROUND: Men who have sex with men and women (MSMW) are the most important bridge population for HIV transmission. Condom use plays an important role for HIV infection. However the predictors for condom ues with females are not well characterized. METHODS: This was a cross-sectional study. Participants were enrolled by four community-based organizations (CBOs) by offline (bathrooms, bars), and online (gay applications, chat room) from April to December 2019. Electronic questionnare was fulfilled after a face-to-face training led by CBOs. We identified predictors of inconsistent condom use with females by creating a risk score based on regression coefficients. We externally validated this score via an independent cross-sectional survey conducted in Zhejiang Province in 2021. A total of 917, 615 MSMW were included in analysis in 2019 and 2021, seperately. RESULTS: Among 917 MSMW, 73.2% reported heterosexual behavior in the prior 6 months and 38.3% reported inconsistent condom use with females (ICUF) over that time. Compared with heterosexual/unsure MSMW, bisexual MSMW reported more male and female sex partners, higher proportion of inconsistent condom use with males, less commercial sex with males (p < 0.05). Four risky predictors of ICUF were identified: Duration of local residence ≦6 months; more than one male partner in the prior 6 months; inconsistent condom use with males in the prior 6 months; and never heard post-exposure prophylaxis (PEP). The proportions of respondents indicating ICUF in the low- (0), medium- (2-4) and high-risk (6-20) groups (according to our risk scoring system) were 11.7% (14/120), 26.9% (96/357), and 78.1% (125/160), respectively (Ptrend < 0.001). In the validation survey, the respective proportions of those reporting ICUF were 13.4% (15/112), 17.8% (24/185) and 87.3% (96/110) (Ptrend < 0.001). CONCLUSIONS: We developed and validated a predictive risk score for ICUF among MSMW; four factors were identified, of which inconsistent condom use with men was the most important. Risk reduction intervention programs should focus on MSM who report inconsistent condom use with males, never heard PEP, having multiple partners and living in local less than 6 months.

Combining molecular network analysis and field epidemiology to quantify local HIV transmission and highlight ongoing epidemics.

OBJECTIVES: This study aimed to establish a collaborative approach to quantify local HIV transmission, which is an issue of great concern to public health. METHODS: We linked HIV-1 pol gene sequences to demographic information and epidemiological investigations in Hangzhou (a central city in East China). We estimated local acquisition rates from a collaboration of molecular network analysis (with a distance-based approach) and epidemiological investigations. RESULTS: Among 1064 newly diagnosed patients with HIV, 857 pol sequences were acquired and subsequently analyzed. Multiple subtypes were identified, with circulating recombinant form (CRF)07_BC (42.5%) and CRF01_AE (39.2%) predominating, followed by 13 other subtypes and 26 unique recombinant forms. By integrating the molecular network analysis and epidemiological investigations, we estimated that the proportion of local infection was 63.2%. The multivariable analyses revealed that individuals in clusters were more likely to be local residents, be aged 50 years or older, work as farmers, and have a higher first cluster of differentiation 4 count level (P <0.05). The proportions of local acquisitions over 70% were observed in local residents (79.9%, 242/303), individuals aged 50 years or older (73.6%, 181/246), and farmers (75.6%, 99/131). CONCLUSION: The molecular network analysis can augment traditional HIV epidemic surveillance. This study establishes a paradigm for quantifying local HIV transmission for generalization in other areas.

Identification and genomic characterization of a novel HIV-1 unique recombinant form (CRF01_AE/CRF07_BC) in Zhejiang Province, China.

Mutation and recombination are important mechanisms leading to the frequent evolution and genetic diversity of viruses as HIV-1. In this study, we identified the near full-length genomic characterization of a novel HIV-1 unique recombinant form (URF) strain (Sample ID: ZJ20202195/ZJ/CHN/2020, hereafter referred to as ZJ20202195) isolated during the HIV-1 molecular surveillance in 2020 in Zhejiang Province, China, through different recombination analysis tools and phylogenetic analysis. Our results amply proved that the near full-length genome (NFLG) sequence of ZJ20202195 was a novel HIV-1 unique recombinant form (URF) consisting of CRF01_AE and CRF07_BC subtype, and delimited three recombinant segments, of which the Segment I (HXB2:776-5559 nucleotide (nt)) and Segment III (HXB2:6224-9412 nt) were mainly originated from CRF01_AE cluster g4a strains prevalent in China and Segment II (HXB2:5560-6223 nt) was from CRF07_BC subtype. Overall, our findings provide insight and a scientific basis in the genetic diversity and accurate determination of HIV-1 recombinant strains in China.

Development and Validation of a Risk Prediction Tool to Identify People at Greater Risk of Having Hepatitis C among Drug Users.

BACKGROUND: People who use drugs (PWUD) are among those with the highest risk for hepatitis C virus (HCV) infection. Highly effective direct-acting antiviral agents offer an opportunity to eliminate HCV. A simple tool for the prediction of HCV infection risk in PWUD is urgently needed. This study aimed to develop and validate a risk prediction tool to identify people at greater risk of having hepatitis C among PWUD that is applicable in resource-limited settings. METHODS: We extracted data from national HIV/AIDS sentinel surveillance in PWUD (Zhejiang Province, 2016-2021) and developed and validated a risk score to improve HCV testing in PWUD. This risk score consists of seven risk factors identified using multivariable logistic regression modeling (2016-2020, exploratory group). We validated this score using surveillance data for 2021 (validation group). The accuracy of the model was determined using C-statistics. RESULTS: We identified seven risk factors, including sex, age, marital status, educational attainment, and the use of heroin, morphine, and methamphetamine. In the exploratory group, the positive rates of detecting the HCV antibody in the low-risk (0-9 points), intermediate-risk (10-16 points), and high-risk (≥17 points) groups were 6.72%, 17.24%, and 38.02%, respectively (Ptrend < 0.001). In the validation group, the positive rates in the low-, medium-, and high-risk groups were 4.46%, 12.23%, and 38.99%, respectively (Ptrend < 0.001). CONCLUSIONS: We developed and validated a drug-specific risk prediction tool for identifying PWUD at increased risk of HCV infection. This tool can complement and integrate the screening strategy for the purpose of early diagnosis and treatment.

Tracing the origin of an imported HIV-1 sub-subtype A6 strain first identified in Zhejiang Province, China.

Human migration and mobility have been identified as key drivers of HIV dissemination among nations, which increases the problem of genetic diversity. Here, we report the near full-length genome of HIV-1 A6 identified in a female patient in the remote mountain area of Lishui, Zhejiang Province, which is the first time A6 has been reported in China. The near full-length genome was amplified with two large amplicons of 5.5 kb and 3.7 kb, and then target PCR products were sequenced by Sanger sequencing. The A6 strain was confirmed by the Basic Local Alignment Search Tool (BLAST) and a maximum-likelihood (ML) phylogenetic tree. The time to the most recent common ancestor (tMRCA) was inferred to be 2004 (95% HPD interval: 2003-2006). The sequence harbored the L74I mutation, which is a key characteristic genetic marker of A6. Combining the above evidence with epidemiological investigations, this A6 strain was determined to be from Ukraine, which was supported by phylogenetic analysis. This study identified a foreign imported strain, indicating a trend of increasing complication in the HIV-1 epidemic in Zhejiang, China.

Application of machine learning algorithms in predicting HIV infection among men who have sex with men: Model development and validation.

Background: Continuously growing of HIV incidence among men who have sex with men (MSM), as well as the low rate of HIV testing of MSM in China, demonstrates a need for innovative strategies to improve the implementation of HIV prevention. The use of machine learning algorithms is an increasing tendency in disease diagnosis prediction. We aimed to develop and validate machine learning models in predicting HIV infection among MSM that can identify individuals at increased risk of HIV acquisition for transmission-reduction interventions. Methods: We extracted data from MSM sentinel surveillance in Zhejiang province from 2018 to 2020. Univariate logistic regression was used to select significant variables in 2018-2019 data (P < 0.05). After data processing and feature selection, we divided the model development data into two groups by stratified random sampling: training data (70%) and testing data (30%). The Synthetic Minority Oversampling Technique (SMOTE) was applied to solve the problem of unbalanced data. The evaluation metrics of model performance were comprised of accuracy, precision, recall, F-measure, and the area under the receiver operating characteristic curve (AUC). Then, we explored three commonly-used machine learning algorithms to compare with logistic regression (LR), including decision tree (DT), support vector machines (SVM), and random forest (RF). Finally, the four models were validated prospectively with 2020 data from Zhejiang province. Results: A total of 6,346 MSM were included in model development data, 372 of whom were diagnosed with HIV. In feature selection, 12 variables were selected as model predicting indicators. Compared with LR, the algorithms of DT, SVM, and RF improved the classification prediction performance in SMOTE-processed data, with the AUC of 0.778, 0.856, 0.887, and 0.942, respectively. RF was the best-performing algorithm (accuracy = 0.871, precision = 0.960, recall = 0.775, F-measure = 0.858, and AUC = 0.942). And the RF model still performed well on prospective validation (AUC = 0.846). Conclusion: Machine learning models are substantially better than conventional LR model and RF should be considered in prediction tools of HIV infection in Chinese MSM. Further studies are needed to optimize and promote these algorithms and evaluate their impact on HIV prevention of MSM.

Molecular genetics and epidemiological characteristics of HIV-1 epidemic strains in various sexual risk behaviour groups in developed Eastern China, 2017-2020.

In this study, we conducted a detailed molecular epidemiological analysis of HIV-1 epidemic strains in various sexual risk behaviour groups in a developed area in eastern China based on phylogenetic inference, molecular transmission networks, and Bayesian analyses. A total of 1083 pol sequences (91.23%, 1083/1187) from newly diagnosed HIV-1-positive patients from 2017 to 2020 were successfully obtained and involved thirteen HIV-1 subtypes, in which the major HIV-1 subtypes were CRF07_BC (36.10%, 391/1083) and CRF01_AE (34.63%, 375/1083). 485 individuals (44.78%,485/1083) formed 146 clusters in the network. Of which CRF07_BC showed extensive clustering driven by men who have sex with men (MSM) within larger networks, CRF01_AE and other subtypes were generally driven by small clusters (SCs) and medium clusters (MCs) among various risk groups. Through Sankey diagrams, the MSM group infected with CRF07_BC had a greater impact on the non-commercial heterosexual group among all cross-risk groups. In addition, a higher number of key individuals infected with CRF07_BC (40.22%, 74/127), suggests the crucial role of CRF07_BC-infected individuals as a local epidemic driver in the context of a mixed HIV-1 epidemic. Further Bayesian analysis confirmed that CRF07_BC was introduced into Jiaxing city from other provinces multiple times and spread rapidly among MSM and heterosexual individuals. Overall, our study provided some insights and information to explore the local transmission dynamics of HIV-1 epidemic strains involving various sexual risk groups, and emphasize that it is necessary to conduct in-depth research and precise intervention targeting key clusters/ individuals to effectively block the continued transmission of AIDS.

Natural Language to Visualization by Neural Machine Translation.

Supporting the translation from natural language (NL) query to visualization (NL2VIS) can simplify the creation of data visualizations because if successful, anyone can generate visualizations by their natural language from the tabular data. The state-of-the-art NL2VIS approaches (e.g., NL4DV and FlowSense) are based on semantic parsers and heuristic algorithms, which are not end-to-end and are not designed for supporting (possibly) complex data transformations. Deep neural network powered neural machine translation models have made great strides in many machine translation tasks, which suggests that they might be viable for NL2VIS as well. In this paper, we present ncNet, a Transformer-based sequence-to-sequence model for supporting NL2VIS, with several novel visualization-aware optimizations, including using attention-forcing to optimize the learning process, and visualization-aware rendering to produce better visualization results. To enhance the capability of machine to comprehend natural language queries, ncNet is also designed to take an optional chart template (e.g., a pie chart or a scatter plot) as an additional input, where the chart template will be served as a constraint to limit what could be visualized. We conducted both quantitative evaluation and user study, showing that ncNet achieves good accuracy in the nvBench benchmark and is easy-to-use.

TSMG: A Deep Learning Framework for Recognizing Human Learning Style Using EEG Signals.

Educational theory claims that integrating learning style into learning-related activities can improve academic performance. Traditional methods to recognize learning styles are mostly based on questionnaires and online behavior analyses. These methods are highly subjective and inaccurate in terms of recognition. Electroencephalography (EEG) signals have significant potential for use in the measurement of learning style. This study uses EEG signals to design a deep-learning-based model of recognition to recognize people's learning styles with EEG features by using a non-overlapping sliding window, one-dimensional spatio-temporal convolutions, multi-scale feature extraction, global average pooling, and the group voting mechanism; this model is named the TSMG model (Temporal-Spatial-Multiscale-Global model). It solves the problem of processing EEG data of variable length, and improves the accuracy of recognition of the learning style by nearly 5% compared with prevalent methods, while reducing the cost of calculation by 41.93%. The proposed TSMG model can also recognize variable-length data in other fields. The authors also formulated a dataset of EEG signals (called the LSEEG dataset) containing features of the learning style processing dimension that can be used to test and compare models of recognition. This dataset is also conducive to the application and further development of EEG technology to recognize people's learning styles.

Design and Implementation of an EEG-Based Learning-Style Recognition Mechanism.

Existing methods for learning-style recognition are highly subjective and difficult to implement. Therefore, the present study aimed to develop a learning-style recognition mechanism based on EEG features. The process for the mechanism included labeling learners' actual learning styles, designing a method to effectively stimulate different learners' internal state differences regarding learning styles, designing the data-collection method, designing the preprocessing procedure, and constructing the recognition model. In this way, we designed and verified an experimental method that can effectively stimulate learning-style differences in the information-processing dimension. In addition, we verified the effectiveness of using EEG signals to recognize learning style. The recognition accuracy of the learning-style processing dimension was 71.2%. This result is highly significant for the further exploration of using EEG signals for effective learning-style recognition.

Factors Associated with Health-Seeking Preference Among People Who Were Supposed to Cough for More Than 2 Weeks: A Cross-Sectional Study in Southeast China.

BACKGROUND: The health-seeking preference of people with a cough >2 weeks had not been extensively researched in southeast China. The study aimed to explore factors associated with health-seeking preference, which could provide more evidence to improve individuals' appropriate health-seeking behavior. MATERIALS AND METHODS: From October 2018 to December 2018, this cross-sectional study was conducted in Zhejiang, China. A questionnaire was used to collect information on sociodemographic characteristics, knowledge of tuberculosis (TB), and health-seeking preference. The chi-square test and multivariable logistic regression were performed to evaluate factors associated with health-seeking preference. RESULTS: Of the 7174 participants, 3321 (46.3%) were men, 6148 (85.7%) were married, and 6013 (83.8%) knew about TB. Appropriate health-seeking preference was reported by 6229 (86.8%) participants. Respondents knowing about TB were more likely to seek appropriate care than those did not (89.6% vs 72.4%, p<0.001). Of the 6013 participants knowing about TB, respondents with higher scores on five key items of TB knowledge were more likely to get appropriate health-seeking preference. About 805 (96.6%) participants with 5 scores on TB knowledge had appropriate care preference. Only 97 (72.4%) participants with a score of 0 reported an appropriate preference. Multivariable logistic regression showed residence, marital status, education level, occupation, and awareness of TB knowledge were predictors of appropriate health-seeking preference. Compared to participants with a score of 0 on five TB key knowledge, participants with a score of 5 were 8.57 times more likely to have appropriate health-seeking preference (95% confidence interval [CI]: 4.97-14.78), followed by a score of 4 (odds ratio [OR]=5.99, 95% CI, 3.23-8.03); 3 (OR=3.74, 95% CI, 2.44-5.74); 2 (OR=1.99, 95% CI, 1.30-3.02) and 1 (OR=1.17, 95% CI, 0.76-1.80). CONCLUSION: Participants with little knowledge of TB had a low level of appropriate health-seeking preference. Appropriate health-seeking preference of the participants improved with increased key knowledge level of TB.

Potential transmission of SARS-CoV-2 on a flight from Singapore to Hangzhou, China: An epidemiological investigation.

BACKGROUND: Between January 24, 2020 and February 15, 2020, an outbreak of COVID-19 occurred among 335 passengers on a flight from Singapore to Hangzhou in China. This study aimed to investigate the source of the outbreak and assess the risk of transmission of COVID-19 during the flight. METHOD: Using a standardized questionnaire, we collected information on the travelers' demographic characteristics and illness before, during, and after the flight. We also collected data on factors potentially associated with COVID-19 transmission during the flight. RESULTS: A total of 16 COVID-19 patients were diagnosed among all passengers; the overall attack rate was 4.8%. The attack rate among passengers who had departed from Wuhan was significantly higher than that among those who had departed from other places. One passenger without an epidemiological history of exposure before boarding developed COVID-19. During the flight, he was seated near four infected passengers from Wuhan for approximately an hour and did not wear his facemask correctly during the flight. CONCLUSIONS: COVID-19 transmission may have occurred during the flight. However, the majority of the cases in the flight-associated outbreak could not be attributed to transmission on the flight but were associated with exposure to the virus in Wuhan or to infected members in a single tour group.

Multidrug-resistant tuberculosis transmission among middle school students in Zhejiang Province, China.

BACKGROUND: Despite significant advancements in the treatment and diagnosis of tuberculosis (TB) over the past decade, drug-resistant TB remains an increasing threat to public health. TB outbreaks are most commonly reported in schools considering the delay in TB diagnosis, sustained contact, and overcrowding observed in schools. This report describes multidrug-resistant TB (MDR-TB) transmission in a school in Zhejiang Province. We aimed to raise awareness regarding MDR-TB transmission among students. CASE PRESENTATION: The index patient was a 16-year-old girl in the second year of junior middle school in Zhejiang Province, China, who had been experiencing persistent cough and expectoration for 37 days since 1 March 2014. She tested positive for smear pulmonary and extrapulmonary TB on 8 April 2014 and was subsequently diagnosed with MDR-TB on 1 May 2014. However, the patient was resistant to isoniazid, rifampicin, ethambutol, and streptomycin. Thus, she was suspended from school for anti-TB treatment. All 54 students who were in close contact with the index patient in the same class were screened, and 5 tested positive on the tuberculin skin test. Their exposure time to the index patient was approximately 37 days. Three classmates were subsequently diagnosed with MDR-TB, with similar resistance profiles nearly two years later. Their average discovery delay was 55 days. These three classmates were also suspended from school for anti-TB treatment. During the treatment period, four students visited the local TB-designated hospital for further consultation every month and were followed up once a month by the local community health service center until they were completely cured. CONCLUSIONS: Discovery delay for an index patient played a primary role in MDR-TB transmission inside the school. To immediately detect TB, morning examinations in schools should be performed. TB trackers and case managers should work closely with public health workers and physicians in cases of TB outbreaks or transmissions involving students. Moreover, individuals who are in close contact with MDR-TB patients should undergo careful clinical follow-up for at least two years. Implementing a joint examination strategy to ensure early detection, diagnosis, and treatment of MDR-TB transmission is recommended.

Identification and Prediction of Tuberculosis in Eastern China: Analyses from 10-year Population-based Notification Data in Zhejiang Province, China.

Tuberculosis, a severe infectious disease caused by the Mycobacterium tuberculosis, arouses huge concerns globally. In this study, a total of 331,594 TB cases in Zhejiang Province were notified during the period of 2009-2018 with the gender ratio of male to female 2.16:1. The notified TB incidences demonstrated a continuously declining trend from 75.38/100,000 to 52.25/100,000. Seasonally, the notified TB cases presented as low in January and February closely followed an apparent rise in March and April. Further stratification analysis by both genders demonstrated the double peak phenomenon in the younger population ("15-35") and the elders (">55") of the whole group. Results from the rate difference (RD) analysis showed that the rising TB incidence mainly presented in the young group of "15-20" and elder group of "65-70", implying that some implementations such as the increased frequency of checkup in specific student groups and strengthening of elder health examination could be explored and integrated into available health policy. Finally, the SARIMA (2,0,2) (0,1,1)12 was determined as the optimal prediction model, which could be used in the further prediction of TB in Zhejiang Province.

Public Awareness of Tuberculosis in Southeast China: A Population-Based Study.

Few provinces in China have recently conducted population-based surveys on tuberculosis (TB) awareness at the provincial level. Hence, we conducted a population-based, cross-sectional study to evaluate the level of awareness of TB knowledge among residents of Zhejiang Province, China from October 2018 to December 2018. A total of 7174 individuals were randomly selected to participate in this survey. The rate of awareness of key information on TB was found to be 48.0%. The study's participants exhibited a good understanding of the transmission route (80.8%), curable outcome (78.3%), and designated treatment sites (67.0%) of TB. The rate of awareness of suspicious TB symptoms (36.1%) and the relief policy on diagnosis and first-line therapeutic drugs (38.0%) were found to be relatively low among the respondents. People living in rural areas, those who were less educated, and students all showed a low level of awareness of key knowledge about TB. In conclusion, residents in Zhejiang Province generally lacked key information about TB, which is not conducive to the early detection and treatment of TB. Corresponding efforts should be made for different groups of people to achieve favorable effects on the prevention and control of TB.