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1.
Front Public Health ; 11: 1151038, 2023.
Article in English | MEDLINE | ID: covidwho-2305534

ABSTRACT

Background: In the early stage of COVID-19 epidemic, the Chinese mainland once effectively controlled the epidemic, but COVID-19 eventually spread faster and faster in the world. The purpose of this study is to clarify the differences in the epidemic data of COVID-19 in different areas and phases in Chinese mainland in 2020, and to analyze the possible factors affecting the occurrence and development of the epidemic. Methods: We divided the Chinese mainland into areas I, I and III, and divided the epidemic process into phases I to IV: limited cases, accelerated increase, decelerated increase and containment phases. We also combined phases II and III as outbreak phase. The epidemic data included the duration of different phases, the numbers of confirmed cases, asymptomatic infections, and the proportion of imported cases from abroad. Results: In area I, II and III, only area I has a Phase I, and the Phase II and III of area I are longer. In Phase IV, there is a 17-day case clearing period in area I, while that in area II and III are 2 and 0 days, respectively. In phase III or the whole outbreak phase, the average daily increase of confirmed cases in area I was higher than that in areas II and III (P = 0.009 and P = 0.001 in phase III; P = 0.034 and P = 0.002 in the whole outbreak phase), and the average daily in-hospital cases were most in area I and least in area III (P = 0.000, P = 0.000, and P = 0.000 in phase III; P = 0.000, P = 0.000, and P = 0.009 in the whole outbreak phase). The average number of daily in-hospital COVID-19 cases in phase III was more than that in phase II in each area (P = 0.000, P = 0.000, and P = 0.001). In phase IV, from March 18, 2020 to January 1, 2021, the increase of confirmed cases in area III was higher than areas I and II (both P = 0.000), and the imported cases from abroad in Chinese mainland accounted for more than 55-61%. From June 16 to July 2, 2020, the number of new asymptomatic infections in area III was higher than that in area II (P = 0.000), while there was zero in area I. From July 3, 2020 to January 1, 2021, the increased COVID-19 cases in area III were 3534, while only 14 and 0, respectively, in areas I and II. Conclusions: The worst epidemic areas in Chinese mainland before March 18, 2020 and after June 15, 2020 were area I and area III, respectively, and area III had become the main battlefield for Chinese mainland to fight against imported epidemic since March 18, 2020. In Wuhan, human COVID-19 infection might occur before December 8, 2019, while the outbreak might occur before January 16 or even 10, 2020. Insufficient understanding of COVID-19 hindered the implementation of early effective isolation measures, leading to COVID-19 outbreak in Wuhan, and strict isolation measures were effective in controlling the epidemic. The import of foreign COVID-19 cases has made it difficult to control the epidemic of area III. When humans are once again faced with potentially infectious new diseases, it is appropriate to first and foremost take strict quarantine measures as soon as possible, and mutual cooperation between regions should be explored to combat the epidemic.


Subject(s)
COVID-19 , Epidemics , SARS-CoV-2 , Humans , Asymptomatic Infections/epidemiology , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/transmission , Morbidity , Epidemics/prevention & control , Epidemics/statistics & numerical data , China/epidemiology , Disease Outbreaks/prevention & control , Disease Outbreaks/statistics & numerical data , Communicable Disease Control/methods
2.
Heliyon ; 8(11): e11830, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2210356

ABSTRACT

Background: Since December 2019, an unexplained pneumonia has broken out in Wuhan, Hubei Province, China. In order to prevent the rapid spread of this disease, quarantine or lockdown measures were taken by the Chinese government. These measures turned out to be effective in containing the contagious disease. In spite of that, social distancing measures, together with disease itself, would potentially cause certain health risks among the affected population, such as sleep disorder. We herein conducted this web search analysis so as to examine the temporal and spatial changes of public search volume of the mental health topic of "insomnia" during COVID-19 pandemic in China. Methods: The data sources included Baidu Index (BDI) to analyze related search terms and the official website of the National Health Commission of the People's Republic of China to collect the daily number of newly confirmed COVID-19 cases. Following a descriptive analysis of the overall search situation, Spearman's correlation analysis was used to analyze the relationship between the daily insomnia-related search values and the daily newly confirmed cases. The means of search volume for insomnia-related terms during the COVID-19 outbreak period (January 23rd, 2020 to April 8th, 2020) were compared with those during 2016-2019 using Student's t test. Finally, by analyzing the overall daily mean of insomnia in various provinces, we further evaluated whether there existed regional differences in searching for insomnia during the COVID-19 outbreak period. Results: During the COVID-19 outbreak period, the number of insomnia-related searches increased significantly, especially the average daily the BDI for the term "1 min to fall asleep immediately". Spearman's correlation analysis showed that 6 out of the 10 insomnia-related keywords were significantly positively related to the daily newly confirmed cases. Compared with the same period in the past four years, a significantly increased search volume was found in 60.0% (6/10) insomnia-related terms during the COVID-19 outbreak period. We also found that Guangdong province had the highest number of searches for insomnia-related during the pandemic. Conclusions: The surge in the number of confirmed cases during the COVID-19 pandemic has led to an increase in concern and online searches on this topic of insomnia. Further studies are needed to determine whether the search behavior truly reflect the real-time prevalence profile of relevant mental disorders, and further to establish a risk prediction model to determine the prevalence risk of psychopathological disorders, including insomnia, using insomnia-related BDI and other well-established risk factors.

3.
Heliyon ; 2022.
Article in English | EuropePMC | ID: covidwho-2124799

ABSTRACT

Background Since December 2019, an unexplained pneumonia has broken out in Wuhan, Hubei Province, China. In order to prevent the rapid spread of this disease, quarantine or lockdown measures were taken by the Chinese government. These measures turned out to be effective in containing the contagious disease. In spite of that, social distancing measures, together with disease itself, would potentially cause certain health risks among the affected population, such as sleep disorder. We herein conducted this web search analysis so as to examine the temporal and spatial changes of public search volume of the mental health topic of “insomnia” during COVID-19 pandemic in China. Methods The data sources included Baidu Index (BDI) to analyze related search terms and the official website of the National Health Commission of the People's Republic of China to collect the daily number of newly confirmed COVID-19 cases. Following a descriptive analysis of the overall search situation, Spearman's correlation analysis was used to analyze the relationship between the daily insomnia-related search values and the daily newly confirmed cases. The means of search volume for insomnia-related terms during the COVID-19 outbreak period (January 23rd, 2020 to April 8th, 2020) were compared with those during 2016–2019 using Student's t test. Finally, by analyzing the overall daily mean of insomnia in various provinces, we further evaluated whether there existed regional differences in searching for insomnia during the COVID-19 outbreak period. Results During the COVID-19 outbreak period, the number of insomnia-related searches increased significantly, especially the average daily the BDI for the term “1 min to fall asleep immediately”. Spearman's correlation analysis showed that 6 out of the 10 insomnia-related keywords were significantly positively related to the daily newly confirmed cases. Compared with the same period in the past four years, a significantly increased search volume was found in 60.0% (6/10) insomnia-related terms during the COVID-19 outbreak period. We also found that Guangdong province had the highest number of searches for insomnia-related during the pandemic. Conclusions The surge in the number of confirmed cases during the COVID-19 pandemic has led to an increase in concern and online searches on this topic of insomnia. Further studies are needed to determine whether the search behavior truly reflect the real-time prevalence profile of relevant mental disorders, and further to establish a risk prediction model to determine the prevalence risk of psychopathological disorders, including insomnia, using insomnia-related BDI and other well-established risk factors. COVID-19;Internet;Baidu index;Insomnia;Web search.

4.
Environ Int ; 158: 106918, 2022 01.
Article in English | MEDLINE | ID: covidwho-1458879

ABSTRACT

BACKGROUND: Ambient and household air pollution are found to lead to premature deaths from all-cause or cause-specific death. The national lockdown measures in China during COVID-19 were found to lead to abrupt changes in ambient surface air quality, but indoor air quality changes were neglected. In this study, we aim to investigate the impacts of lockdown measures on both ambient and household air pollution as well as the short-term health effects of air pollution changes. METHODS: In this study, an up-to-date emission inventory from January to March 2020 in China was developed based on air quality observations in combination with emission-concentration response functions derived from chemical transport modeling. These emission inventories, together with the emissions data from 2017 to 2019, were fed into the state-of-the-art regional chemistry transport model to simulate the air quality in the North China Plain. A hypothetical scenario assuming no lockdown effects in 2020 was also performed to determine the effects of the lockdown on air quality in 2020. A difference-to-difference approach was adopted to isolate the effects on air quality due to meteorological conditions and long-term decreasing emission trends by comparing the PM2.5 changes during lockdown to those before lockdown in 2020 and in previous years (2017-2019). The short-term premature mortality changes from both ambient and household PM2.5 changes were quantified based on two recent epidemiological studies, with uncertainty of urban and rural population migration considerations. FINDINGS: The national lockdown measures during COVID-19 led to a reduction of 5.1 µg m-3 in ambient PM2.5 across the North China Plain (NCP) from January 25th to March 5th compared with the hypothetical simulation with no lockdown measures. However, a difference-to-difference method showed that the daily domain average PM2.5 in the NCP decreased by 9.7 µg m-3 between lockdown periods before lockdown in 2020, while it decreased by 7.9 µg m-3 during the same periods for the previous three-year average from 2017 to 2019, demonstrating that lockdown measures may only have caused a 1.8 µg m-3 decrease in the NCP. We then found that the integrated population-weighted PM2.5, including both ambient and indoor PM2.5 exposure, increased by 5.1 µg m-3 during the lockdown periods compared to the hypothetical scenario, leading to additional premature deaths of 609 (95% CI: 415-775) to 2,860 (95% CI: 1,436-4,273) in the short term, depending on the relative risk chosen from the epidemiological studies. INTERPRETATION: Our study indicates that lockdown measures in China led to abrupt reductions in ambient PM2.5 concentration but also led to significant increases in indoor PM2.5 exposure due to confined indoor activities and increased usages of household fuel for cooking and heating. We estimated that hundreds of premature deaths were added as a combination of decreased ambient PM2.5 and increased household PM2.5. Our findings suggest that the reduction in ambient PM2.5 was negated by increased exposure to household air pollution, resulting in an overall increase in integrated population weighted exposure. Although lockdown measures were instrumental in reducing the exposure to pollution concentration in cities, rural areas bore the brunt, mainly due to the use of dirty solid fuels, increased population density due to the large-scale migration of people from urban to rural areas during the Chinese New Year and long exposure time to HAP due to restrictions in outdoor movement.


Subject(s)
Air Pollutants , Air Pollution, Indoor , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , Air Pollution, Indoor/analysis , China , Communicable Disease Control , Humans , Particulate Matter/analysis , SARS-CoV-2
5.
Atmospheric Chemistry and Physics ; 21(11):8693-8708, 2021.
Article in English | ProQuest Central | ID: covidwho-1262651

ABSTRACT

In response to the coronavirus disease of 2019 (COVID-19), California issued statewide stay-at-home orders, bringing about abrupt and dramatic reductions in air pollutant emissions. This crisis offers us an unprecedented opportunity to evaluate the effectiveness of emission reductions in terms of air quality. Here we use the Weather Research and Forecasting model with Chemistry (WRF-Chem) in combination with surface observations to study the impact of the COVID-19 lockdown measures on air quality in southern California. Based on activity level statistics and satellite observations, we estimate the sectoral emission changes during the lockdown. Due to the reduced emissions, the population-weighted concentrations of fine particulate matter (PM2.5) decrease by 15 % in southern California. The emission reductions contribute 68 % of the PM2.5 concentration decrease before and after the lockdown, while meteorology variations contribute the remaining 32 %. Among all chemical compositions, the PM2.5 concentration decrease due to emission reductions is dominated by nitrate and primary components. For O3 concentrations, the emission reductions cause a decrease in rural areas but an increase in urban areas;the increase can be offset by a 70 % emission reduction in anthropogenic volatile organic compounds (VOCs). These findings suggest that a strengthened control on primary PM2.5 emissions and a well-balanced control on nitrogen oxides and VOC emissions are needed to effectively and sustainably alleviate PM2.5 and O3 pollution in southern California.

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