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BACKGROUND: Information on major depressive disorder (MDD) and subthreshold depressive symptoms (SDS) is rarely reported in south China. This study examines the prevalence rates and patterns of MDD and SDS of a large representative sample of adult residents in south China. METHODS: The Guangdong Mental Health Survey was conducted on adults (over 18 years) from September to December 2021. Multistage stratified cluster sampling was used and face-to-face interviews were done with a two-stage design by trained lay interviewers and psychiatrists. A total of 16,377 inhabitants were interviewed using standardized assessment tools. Data were weighted to adjust for differential probabilities of selection and differential response. RESULTS: The weighted prevalence rates of MDD and SDS were 2.5 % (95%CI: 2.2 %-2.9 %) and 14.7 % (95%CI: 14.0 %-15.5 %), respectively. Multinomial logistic regression analysis revealed that female, younger age, living in urban area, higher education, unmarried, irregular meal pattern, lack of physical exercise, chronic diseases, irregular napping pattern and short sleep were positively associated with SDS. Besides, female, younger age, unmarried, irregular meal pattern, lack of physical exercise, chronic diseases, short sleep and poor mental health were positively associated with MDD. LIMITATIONS: The cross-sectional nature of the study limited causal inferences. CONCLUSIONS: The prevalence of MDD in Guangdong province in 2021 is higher than in mainland China in 2013. Given the higher prevalence of SDS, and high burden of depression, it also offers valuable opportunities for policymakers and health-care professionals to explore the factors affecting mental health in Guangdong province, especially during the COVID-19 epidemic.
Subject(s)
COVID-19 , Depressive Disorder, Major , Sleep Wake Disorders , Adult , Humans , Female , Depressive Disorder, Major/epidemiology , Depressive Disorder, Major/psychology , Depression , Prevalence , Cross-Sectional Studies , China/epidemiology , Chronic DiseaseABSTRACT
Studying the spatiotemporal evolution of carbon emissions from the perspective of major function-oriented zones (MFOZs) is crucial for making a carbon reduction policy. However, most previous research has ignored the spatial characteristics and MFOZ influence. Using statistical and spatial analysis tools, we explored the spatiotemporal characteristics of carbon emissions in Guangdong Province from 2001 to 2021. The following results were obtained: (1) Carbon emissions fluctuated from 2020 to 2021 because of COVID-19. (2) Over the last 20 years, the proportion of carbon emissions from urbanization development zones (UDZs) has gradually decreased, whereas those of the main agricultural production zones (MAPZs) and key ecological function zones (KEFZs) have increased. (3) Carbon emissions efficiency differed significantly among the three MFOZs. (4) Carbon emissions from coastal UDZs were increasingly apparent; however, the directional characteristics of MAPZ and KEFZ emissions were not remarkable. (5) Carbon transfer existed among the three kinds of MFOZs, resulting in the economy and carbon emissions being considerably misaligned across Guangdong Province. These results indicated that the MFOZ is noteworthy in revealing how carbon emissions evolved. Furthermore, spatiotemporal characteristics, especially spatial characteristics, can help formulate carbon reduction policies for realizing carbon peak and neutrality goals in Guangdong Province.
Subject(s)
COVID-19 , Carbon , Humans , Carbon/analysis , COVID-19/epidemiology , Urbanization , Agriculture , China , Carbon Dioxide/analysis , Economic DevelopmentABSTRACT
In recent years, due to the rise in energy prices and the impact of COVID-19, energy shortages have led to unsafe power supply environments. High emissions industries which account for more than 58% of the carbon emissions of Guangdong Province have played an important role in achieving the carbon peak goal, alleviating social energy shortage and promoting economic growth. Controlling high emissions industries will help to adjust the industrial structure and increase renewable energy investment. Therefore, it is necessary to comprehensively evaluate the policies of energy security and the investments of high emission industries. This paper builds the ICEEH-GD (comprehensive assessment model of climate, economy, environment and health of Guangdong Province) model, designs the Energy Security scenario (ES), the Restrict High Carbon Emission Sector scenario (RHS) and the Comprehensive Policy scenario (CP), and studies the impact of limiting high emissions industries and renewable energy policies on the transformation of investment structure, macro-economy and society. The results show that under the Energy Security scenario (ES), carbon emissions will peak in 2029, with a peak of 681 million tons. Under the condition of ensuring energy security, the installed capacity of coal-fired power generation will remain unchanged from 2025 to 2035. Under the Restrict High Carbon Emission Sector scenario (RHS), the GDP will increase by 8 billion yuan compared with the ES scenario by 2035. At the same time, it can promote the whole society to increase 10,500 employment opportunities, and more investment will flow to the low emissions industries. In the Comprehensive Policy scenario (CP), although the GDP loss will reach 33 billion yuan by 2035 compared with the Energy Security scenario (ES), the transportation and service industries will participate in carbon trading by optimizing the distribution of carbon restrictions in the whole society, which will reduce the carbon cost of the whole society by more than 48%, and promote the employment growth of 104,000 people through industrial structure optimization. Therefore, the power sector should increase investment in renewable energy to ensure energy security, limit the new production capacity of high emissions industries such as cement, steel and ceramics, and increase the green transition and efficiency improvement of existing high emissions industries. © 2022 by the authors.
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In order to improve the speed and efficiency of the Department of epidemic prevention and control, this paper uses ARIMA model to train and fit the number of confirmed cases on the basis of the historical epidemic diagnosis information of Guangdong Province. By dealing with the stability of time series, determining the parameters of ARIMA model and testing residual white noise, the ARIMA model is established to predict the number of confirmed epidemic cases, and the number of confirmed epidemic cases in March may 2021 in Guangdong Province is accurately predicted, so as to help the epidemic prevention and control departments improve the accuracy and effectiveness of epidemic control. © 2022 SPIE.
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We carried out a preliminary investigation to study the impact of COVID-19 on aquaculture in China and identify the strategies and measures that have been taken by the Chinese Government. The investigation involved questionnaire surveys designed for all stakeholders along the industrial chain, including grow-out farmers, seed producers, fish processors, fish traders, and feed companies engaged in the catfish sector in Hubei Province and the tilapia sector in Guangdong Province during the strict period of control and after these control measures were lifted. We also attempted to summarize the government interventions and measures taken by different stakeholders along the value chain to minimize the damage caused by COVID-19 and support the recovery of different sectors in the aquaculture industry. We found that due to delayed harvesting, fish stocks were held-up in ponds and normal farming was interrupted. Farmers and traders were more severely impacted by the pandemic than other sectors. Furthermore, a series of strategies and measures are recommended to cope with the pandemic and other similar risks in the future. We expect that this study will provide good evidence for international societies to support the aquaculture industry in minimizing the impact of the pandemic and the rapid recovery of the industry in the post-pandemic period.
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Novel Coronavirus Pneumonia (COVID-19) has ravaged the world since 2019, seriously affecting human production and life. Although my country has controlled the epidemic on the whole, there are still local outbreaks. To this end, a classic infectious disease SEIR model was established to study the spread of the new coronavirus pneumonia epidemic. The population was divided into four categories: susceptible population, exposed population, infected population and removed population. After the parameters of the SEIR model were determined, Python was applied to conduct drills on the SEIR model, and simulation analysis was conducted on the epidemic transmission in Taiwan and Guangdong provinces with and without control measures. The results show that there are significant differences in the number of exposed, infected, and removed numbers between the two provinces. It shows that early and timely strict prevention and control measures can effectively control the spread of the new coronavirus pneumonia epidemic. © 2021 ACM.
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Increases in ground-level ozone (O3 ) have been observed during the COVID-19 lockdown in many places around the world, primarily due to the uncoordinated emission reductions of O3 precursors. In Guangzhou, the capital of Guangdong province in South China, O3 distinctively decreased during the lockdown. Such a phenomenon was attributed to meteorological variations and weakening of local O3 formation, as indicated by chemical transport models. However, the emission-based modellings were not fully validated by observations, especially for volatile organic compounds (VOCs). In this study, we analyzed the changes of O3 and its precursors, including VOCs, from the pre-lockdown (Pre-LD) to lockdown period (LD) spanning 1 week in Guangzhou. An observation-based box model was applied to understand the evolution of in-situ photochemistry. Indeed, the ambient concentrations of O3 precursors decreased significantly in the LD. A reduction of 20.7% was identified for the total mixing ratios of VOCs, and the transportation-related species experienced the biggest declines. However, the reduction of O3 precursors would not lead to a decrease of in-situ O3 production if the meteorology did not change between the Pre-LD and LD periods. Sensitivity tests indicated that O3 formation was limited by VOCs in both periods. The lower temperature and photolysis frequencies in the LD reversed the increase of O3 that would be caused by the emission reductions otherwise. This study reiterates the fact that O3 abatement requires coordinated control strategies, even if the emissions of O3 precursors can be significantly reduced in the short term. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
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OBJECTIVE: This study aimed to analyze the distribution characteristics and influencing factors for the interval between entering mainland China and the diagnosis of imported COVID-19 cases in Guangdong province, in order to provide valuable experience for global pandemic in prevention and control. METHODS: We collected publicly reported data between March 1 and June 2, 2020. Univariate and multivariate regression analyses were performed to identify the significant associated factors with the interval between entering mainland China and diagnosis of imported COVID-19 cases. RESULTS: As of June 2, 2020, a total of 200 imported cases were reported in Guangdong province. The average interval time was 4.25 days with a median of 2 days, the interval time of 68% cases was between 1 and 3 days. The multivariate model results show that the three following factors were critical influencing factors: nationality was foreign nationality (P = 0.037), results of initial nucleic acid detection were negative (P = 0.000) and the interval between entering mainland China and the detection of positive results (T) exceeded two days (P = 0.008). CONCLUSION: The results suggested that all travelers and returning resident should be taken strict sampling and testing, and isolation measures, improved the accuracy of the initial nucleic acid test results, and the detection efficiency and shortening the interval between entering mainland China and detection of positive results.
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In December 2019, human infection with a novel coronavirus, known as SARS-CoV-2, was confirmed in Wuhan, China, and spread rapidly beyond Wuhan and around the world. By 7 May 2020, a total of 84,409 patients were infected in mainland China, with 4,643 deaths, according to a Chinese Center for Disease Control and Prevention report. Recent studies reported that critically ill patients were presented with high mortality. However, the clinical experiences of patients with coronavirus disease 2019 (COVID-19) have not been described in Guangdong Province, where by 7 May 2020, 1,589 people had been confirmed as having COVID-19 but with a very low mortality of 8 death (0.5%). Here, we describe the experience of critical care response to the outbreak of SARS-CoV-2 in Guangdong Province in the following points: Early intervention by the government, Establishment of a Multidisciplinary Working Group, Prompt intensive care interventions, Adequate ICU beds and Human resource in ICU, Infection control practices.
Subject(s)
COVID-19 , China/epidemiology , Critical Care , Disease Outbreaks/prevention & control , Humans , SARS-CoV-2ABSTRACT
With lessons learnt from the SARS outbreak in 2003, Guangdong Province is taking the lead in bringing COVID-19 under control by multiple strict regulations in combination with effective healthcare provision.