ABSTRACT
There is a lack of research on the effects of acute exposure to ambient sulfur dioxide (SO2) on mortality caused by asthma, especially nationwide research in China. To explore the acute effect of exposure to ambient SO2 on asthma mortality using nationwide dataset in China from 2015 to 2020 and further evaluate the associations in subgroups with different geographical and demographic characteristics. We used data from China's Disease Surveillance Points system with 29,553 asthma deaths in China during 2015–2020. The exposure variable was the daily mean concentrations of SO2 from the ChinaHighSO2 10 km × 10 km daily grid dataset. Bilinear interpolation was used to estimate each individual's exposure to air pollutants and meteorological variables. We used a time-stratified case crossover design at the individual level to analyze the exposure response relationship between short-term exposure to SO2 and asthma mortality. Stratified analyses were carried out by sex, age group, marital status, warm season and cold season, urbanicity and region. Significant associations between short-term exposure to ambient SO2 and increased asthma mortality were found in this nationwide study. The excess risk (ER) for each 10 μg/m3 increase in SO2 concentrations at lag07 was 7.78 % (95 % CI, 4.16–11.52 %). Season appeared to significantly modify the association. The associations were stronger in cold season (ER 9.78 %, 95 % CI:5.82 −13.89 %). The association remained consistent using different lag periods, adjusting for other pollutants, and in the analysis during pre-Corona Virus Disease 2019 (COVID-19) period. Our study indicates increased risk of asthma mortality with acute exposures to SO2 in Chinese population. The current study lends support for greater awareness of the harmful effect of SO2 in China and other countries with high SO2 pollution.
ABSTRACT
China’s sustainable development goals and carbon neutrality targets cannot be achieved without revolutionary transitions of the agricultural sector. The rapid development of digital technologies is believed to play a huge role in this revolution. The ongoing prevention and control of COVID-19 has greatly boosted the penetration of digital technology services in all areas of society, and sustainable transformation driven by digital technologies and services is rapidly becoming an area of innovation and research. Studies have shown that the rapid advancement of digitalization is also accompanied by a series of new governance challenges and problems: (1) unclear strategic orientation and inadequate policy and regulatory responses;(2) various stakeholders have not formed a sustainable community of interest;(3) information explosion is accompanied by information fragmentation and digital divide between countries and populations within countries. Meanwhile, current research has focused more on the role of digital services in urban governance and industrial development and lacks systematic research on its role in sustainable agricultural and rural development. To address the realities faced by different stakeholders in the process of digital transformation of agriculture, this paper aims to propose an inclusive analytical framework based on the meta-governance theory to identify and analyze the demand, supply, actor networks, and incentives in the digital technology-and-services-driven sustainable agricultural transformation, starting from the goals and connotations of sustainable agricultural and rural transformation and the interactions among different stakeholders in governing information flows. This analytical framework is further applied to analyze the cases of China and the EU. Although China and the EU represent different development phases and policy contexts, the framework is valid for capturing the characteristics of information flows and actor networks along the flows. It is concluded that a common information platform based on the stakeholder network would benefit all stakeholders, help reach common framing of issues, and maintain a dynamic exchange of information. Depending on the country context, different types of stakeholders may play different roles in creating, supervising, and maintaining such platforms. Digital infrastructures/products as hardware and farmers digital capacity as 'software’are the two wings for digital sustainable transformation. Innovative incentives from different countries may inspire each other. In any case, farmers’actual farming behavior changes should be an important criterion for evaluating the effects and effectiveness of digital transition governance.
ABSTRACT
Objectives: To understand SARS-CoV-2 seroprevalence of convalescents and assess their the immunity. Furthermore, we intend to explore the association between antibody levels and with demographic factors. Methods: 177 COVID-19 convalescents in Sichuan Province were voluntarily participated in our study. 363 serum samples were collected from June, 2020 to November, 2020. Duration of seroprevelance in these convalescents and their demographic characteristics were described, and the risk factors to antibody levels were analysed. Results: Men had more than twice the odds of having IgM antibody positive compared with women (OR=2.419, 95% CI:[1.232, 4.751]). Participants without symptoms were nearly 0.5 times IgG seropositive than those with symptoms (OR=0.455, 95% CI: [0.220, 0.940]). People aged[≥]60 years were nearly 3 times IgG seropositive than those who aged < 20 years (OR=2.986, 95% CI: [1.058, 8.432]). Seroprevalence in asymptomatic declined quicker than symptomatic. Conclusions: Age and gender may affect the antibody levels and seroprevalence. Asymptomatic appeared more easier to turn to seronegative than symptomatic. Keywords: Seroprevalence; SARS-CoV-2; Risk Factors
Subject(s)
COVID-19ABSTRACT
Background: Evidence of the aggregation of COVID-19 symptoms was still limited. Exploration of likely cluster patterns of symptoms may be helpful.Methods: This study enrolled a total of 1067 COVID-19 cases. Symptom cluster patterns were explored by text clustering method. A multinomial logistic regression was applied to revealed its population characteristics. And time intervals between symptoms onset and the first visit was analyzed to take into account the symptoms progression over time. Results: Based on text clustering, the symptoms were summarized into 4 groups. Except for the group without obvious symptoms, the dominate individual symptoms under the other three groups were fever (68.7%), expectoration (59.4%) and fatigue (42.7%), respectively. And the most frequent symptom combinations were fever only (47.8%), expectoration only(19.8%) and fatigue accompanied with fever (4.2%), respectively. People aged 45-64 years were more likely to have symptom group 4 than those aged 65 years or older(OR = 2.66, P = 0.015) and had longer time intervals. Conclusions: The symptoms cluster patterns and common symptom combinations under each pattern may provide information for identification of the infected. Middle-aged population was a group expecting more attention, from the perspective of medical delays.
Subject(s)
COVID-19ABSTRACT
Background: The COVID-19 spread worldwide quickly. Exploring the epidemiological characteristics could provide a basis for responding to imported cases abroad and to formulate prevention and control strategies in areas where COVID-19 is still spreading rapidly. Methods: : The number of confirmed cases, daily growth, incidence and length of time from the first reported case to the end of the local cases (i.e., non-overseas imported cases) were compared by spatial (geographical) and temporal classification and visualization of the development and changes of the epidemic situation by layers through maps. Results: : In the first wave, a total of 539 cases were reported in Sichuan, with an incidence rate of 0.6462/100,000. The closer to Hubei the population centres were, the more pronounced the epidemic was. The peak in Sichuan Province occurred in the second week. Eight weeks after the Wuhan lockdown, the health crisis had eased. The longest epidemic length at the city level in China (except Wuhan, Taiwan, and Hong Kong) was 53 days, with a median of 23 days. Spatial autocorrelation analysis of China showed positive spatial correlation (Moran's Index >0, p<0.05). Most countries outside China began to experience a rapid rise in infection rates 4 weeks after their first case. Some European countries experienced that rise earlier than the USA. The pandemic in Germany, Spain, Italy, and China took 28, 29, 34, and 18 days, respectively, to reach the peak of daily infections, after their daily increase of up to 20 cases. During this time, countries in the African region and Southeast Asian region were at an early stage of infections, those in the Eastern Mediterranean region and region of the Americas were in a rapid growth phase. Conclusions: : After the closure of the outbreak city, appropriate isolation and control measures in the next 8 weeks were key to control the outbreak, which reduced the peak value and length of the outbreak. Some countries with improved epidemic situations need to develop a continuous "local strategy at entry checkpoints" to to fend off imported COVID-19.
Subject(s)
COVID-19 , AphasiaABSTRACT
Objective Allocation of medical resource is essential to a strong public health system in response to COVID-19. Analysis of confirmed COVID-19 patients' hospital length of stay in Sichuan can be informative to decision-making in other regions of the world. Design A retrospective cross-sectional study. Data and Method Data from confirmed COVID-19 cases in Sichuan Province were obtained from the National Notifiable Diseases Reporting System (NNDRS) and field survey. We collected information on demographic, epidemiological, clinical characteristics, and the length of hospital stay for confirmed patients. We conducted an exploratory analysis using adjusted multivariate cox-proportional models. Participants A total of 538 confirmed patients of COVID-19 infection in Sichuan Province from January to March 2020. Outcome measure The length of hospital stay after admissions for confirmed patients. Results From January 16, 2020 to March 4, 2020, 538 human cases of COVID-19 infection were laboratory-confirmed, and were hospitalized for treatment. Among these, 271 (50%) were 45 years of age or above, 285 (53%) were male, 450 (84%) were considered as having mild symptoms. The median hospital length of stay was 19 days (interquartile range (IQR): 14-23, Range: 3-41). Adjusted multivariate analysis showed that longer hospital length of stay was associated with factors aged 45 and over (HR: 0.74, 95% CI: 0.60-0.91), those admitted to provincial hospital (HR: 0.73, 95% CI: 0.54-0.99), and those with serious illness (HR: 0.66, 95% CI: 0.48-0.90); living in areas with more than 5.5 healthcare workers per 1000 population (HR: 1.32, 95% CI: 1.05-1.65) was associated with shorter hospital length of stay. There was no gender difference. Conclusions Preparation control measures of COVID-19 should involve the allocation of sufficient medical resources, especially in areas with older vulnerable populations and in areas that lack basic medical resources.