Search

Drawing on a recent online survey combined with city-level data, this paper examines the impact of the COVID-19 on consumers' online food purchase behavior in the short term. To address the potential endogeneity issues, we adopt an instrumental variable (IV) strategy, using the distance from the surveyed city to Wuhan as the instrumental variable. We show that our IV method is effective in minimizing potential bias. It is found that the share of confirmed COVID-19 cases increases the possibility of consumers purchasing food online. This is more likely to be the case for young people having a lower perceived risk of online purchases and living in large cities. Despite some limitations, this paper has policy implications for China and other countries that have been influenced by the COVID-19 epidemic. Specifically, government support and regulation should focus on (i) ensuring the safety of food sold on the internet, (ii) protecting the carrier from becoming infected, and (iii) providing financial support to the poor since they may have difficulties in obtaining access to food living in small cities. Moreover, how to help those who are unable to purchase food online because of their technical skills (e.g., the elderly who are not familiar with smart phones or the internet) also deserves more attention for the government and the public. [ABSTRACT FROM AUTHOR]

The Coronavirus Disease 2019 (COVID-19) has proved a globally prevalent outbreak since December 2019. As a focused country to alleviate the epidemic impact, China implemented a range of public health interventions to prevent the disease from further transmission, including the pandemic lockdown in Wuhan and other cities. This paper establishes China's mobility network by a flight dataset and proposes a model without epidemiological parameters to indicate the spread risks through the network, which is termed as epidemic strength. By simply adjusting an intervention parameter, traffic volumes under different travel-restriction levels can be simulated to analyze how the containment strategy can mitigate the virus dissemination through traffic. This approach is successfully applied to a network of Chinese provinces and the epidemic strength is smoothly interpreted by flow maps. Through this node-to-node interpretation of transmission risks, both overall and detailed epidemic hazards are properly analyzed, which can provide valuable intervention advice during public health emergencies. [ABSTRACT FROM AUTHOR]

Background: Creating National Sanitary City (CNSC) promotes appearance, environment sanitation and public health including vector management of cities in China. However, vector management especially mosquito management and the related administrative productivity of Patriotic Health Campaign System (PHCS) of National Sanitary Cities (NSCs) were questioned by many pest control professionals and citizens. In this study, we studied mosquito management of NSCs taking Wuhan as an example. The study aimed to (1) determine the distribution and abundance of immature mosquito habitats in built-up areas of Wuhan and (2) better understand the related administration procedure in CNSC. Methods: Immature mosquito habitat surveillance was carried out in randomly selected premises of driving schools (DSs), schools or kindergartens (SKs), property management residential areas (PMRAs), construction sites (CSs), wide roads with storm drains (WRSDs) and urban creeks (UCs) in built-up areas of Wuhan from July to October 2015 followed by questionnaire interviews with one each of premise occupants and district departments responsible for mosquito management in these premises. Results: Total of 64.1 km of route were inspected in 36 DSs, 36 SKs, 36 PMRAs, 36 CSs and 36 segments of WRSD and 2,158 potential mosquito habitats with 749 (35%) mosquito-positive habitats were found. The route index (RI) was 11.7, which was 14.6 times higher than the grade C criteria for vector density control (RI = 0.8 positive habitats/km) in CNSC. Occupants of 36 DSs, 36 SKs, 36 PMRAs, 34 CSs were interviewed and 77% of them reported no difference in mosquito infestation in their premises since 2013 and 80% of them knew about the responsibility and arrangements of PHCS of mosquito management in their premises. Only 15% had the awareness of larval source reduction strategy and 14% had implemented it. Receipt the electronic/paper edition of CNSC vector management specifications from the PHCS was very low (13%) and an official notification or bulletin for rectification mosquito-positive habitats was also very low (5%). Of the 75 responsible district departments interviewed, about half (55%) reported that they had held training courses/meetings related to CNSC vector management, the majority (96%) reported that they had not carried out independent on-site supervision of premises under their jurisdiction. No differences in larval indices were found between premises which were administrative intervened and with no administrative intervention. Conclusions: The administrative intervention of PHCS had not evidently improved mosquito management of the premises in built-up areas in Wuhan. It is a violation of the original intention of the National Patriotic Health Campaign Committee in organizing CNSC programs. To combat mosquito borne diseases, and to improve the quality of life of residents, we recommend that PHCS honestly reveals defects in urban mosquito management and seriously takes those exposed defects. The PHCS should strengthen Patriotic Health Campaign activities by strict adherence to NSC standards. Further research on sustained promotion of urban mosquito management of NSCs, which focus on effective administration, as well as on improvement of related sectors of NSC standards should be carried out. [ABSTRACT FROM AUTHOR]

In December 2019, the outbreak of a new coronavirus-caused pneumonia (COVID-19) in Wuhan attracted close attention in China and the world. The Chinese government took strong national intervention measures on January 23 to control the spread of the epidemic. We are trying to show the impact of these controls on the spread of the epidemic. We proposed an SEIR(Susceptible-Exposed-Infectious-Removed) model to analyze the epidemic trend in Wuhan and use the AI model to analyze the epidemic trend in non-Wuhan areas. We found that if the closure was lifted, the outbreak in non-Wuhan areas of mainland China would double in size. Our SEIR and AI model was effective in predicting the COVID-19 epidemic peaks and sizes. The epidemic control measures taken by the Chinese government, especially the city closure measures, reduced the scale of the COVID-19 epidemic. [ABSTRACT FROM AUTHOR]

In late 2019, the emergence of COVID-19 in Wuhan, China, led to the implementation of stringent measures forming the zero-COVID policy aimed at eliminating transmission. Zero-COVID policy basically aimed at completely eliminating the transmission of COVID-19. However, the relaxation of this policy in late 2022 reportedly resulted in a rapid surge of COVID-19 cases. The aim of this work is to investigate the factors contributing to this outbreak using a new SEIR-type epidemic model with time-dependent level of immunity. Our model incorporates a time-dependent level of immunity considering vaccine doses administered and time-post-vaccination dependent vaccine efficacy. We find that vaccine efficacy plays a significant role in determining the outbreak size and maximum number of daily infected. Additionally, our model considers under-reporting in daily cases and deaths, revealing their combined effects on the outbreak magnitude. We also introduce a novel Physics Informed Neural Networks (PINNs) approach which is extremely useful in estimating critical parameters and helps in evaluating the predictive capability of our model. [ABSTRACT FROM AUTHOR]

Background: Wuhan was the epicenter of the Coronavirus Disease 2019 (COVID-19), outbreak in China. We aimed at surveying the general public in China to better understand their levels of psychological state and its influencing factors after the Wuhan shutdown on January 23. Methods: The cross-sectional survey was conducted online and 4,701 respondents participated in this survey. Of them, 3,803 respondents were considered for final analysis. Data on subjective indicators of daily life changes were collected, and individual scores on changes in anxiety, depression, and stress were tested by 8-item, 11-item, and 6-item questionnaires, respectively. Results: Multivariable regression analyses showed that living in the rural areas, living in the other regions except Hubei, and higher education were independent correlates of less negative emotions. Besides, the level of attention, self-assessed infection risk, impact on the daily life and mental health help-seeking tended to be positively associated with the scores of anxiety, depression, and stress. Conclusions: City of residence, education, marital status, monthly income, level of attention, self-assessed infection risk, impact on daily life and mental health help-seeking were important correlates of anxiety, depression, and stress scores. [ABSTRACT FROM AUTHOR]

Transparency of Chinese media coverage became an international controversy when the COVID-19 outbreak initially emerged in Wuhan, the eventual crisis epicenter in China. Unlike studies characterizing mass media in authoritarian contexts as government mouthpieces during a crisis, this study aims to disaggregate Chinese media practices to uncover differences in when, where, and how the severity of COVID-19 was reported. We examine differences in how media institutions reported the severity of the COVID-19 epidemic in China during the pre-crisis period from 1 January 2020 to 20 January 2020 in terms of both the "vertical" or hierarchical positions of media institutions in the Chinese media ecosystem and the "horizontal" positions of media institutions' social proximity to Wuhan in terms of geographical human traffic flows. We find that the coverage of crisis severity is negatively associated with the media's social proximity to Wuhan, but the effect varies depending on the positional prominence of a news article and situation severity. Implications of the institutions' differentiated reporting strategies on future public health reporting in an authoritarian context are also discussed. [ABSTRACT FROM AUTHOR]

In February 2020, the Novel Coronavirus (COVID-19) was raging in Wuhan, China and quickly spreading to the rest of the world. This period was fraught with uncertainty for those in the affected areas. The present investigation examined the role of two potential coping resources during this stressful period of uncertainty: flow and mindfulness. Participants in Wuhan and other major cities affected by COVID-19 (N = 5115) completed an online survey assessing subjective experiences of flow, mindfulness, and well-being. Longer quarantine was associated with poorer well-being; flow and mindfulness were associated with better well-being on some measures. However, flow—but not mindfulness—moderated the link between quarantine length and well-being, such that people who experienced high levels flow showed little or no association between quarantine length and poorer well-being. These findings suggest that experiencing flow (typically by engaging in flow-inducing activities) may be a particularly effective way to protect against potentially deleterious effects of a period of quarantine. [ABSTRACT FROM AUTHOR]

This study integrates the daily intercity migration data with the classic Susceptible-Exposed-Infected-Removed (SEIR) model to construct a new model suitable for describing the dynamics of epidemic spreading of Coronavirus Disease 2019 (COVID-19) in China. Daily intercity migration data for 367 cities in China were collected from Baidu Migration, a mobile-app based human migration tracking data system. Early outbreak data of infected, recovered and death cases from official source (from January 24 to February 16, 2020) were used for model fitting. The set of model parameters obtained from best data fitting using a constrained nonlinear optimisation procedure was used for estimation of the dynamics of epidemic spreading in the following months. The work was completed on February 19, 2020. Our results showed that the number of infections in most cities in China would peak between mid February to early March 2020, with about 0.8%, less than 0.1% and less than 0.01% of the population eventually infected in Wuhan, Hubei Province and the rest of China, respectively. Moreover, for most cities outside and within Hubei Province (except Wuhan), the total number of infected individuals is expected to be less than 300 and 4000, respectively. [ABSTRACT FROM AUTHOR]

In December 2019, the novel coronavirus pneumonia (COVID-19) occurred in Wuhan, Hubei Province, China. The epidemic quickly broke out and spread throughout the country. Now it becomes a pandemic that affects the whole world. In this study, three models were used to fit and predict the epidemic situation in China: a modified SEIRD (Susceptible-Exposed-Infected-Recovered-Dead) dynamic model, a neural network method LSTM (Long Short-Term Memory), and a GWR (Geographically Weighted Regression) model reflecting spatial heterogeneity. Overall, all the three models performed well with great accuracy. The dynamic SEIRD prediction APE (absolute percent error) of China had been ≤ 1.0% since Mid-February. The LSTM model showed comparable accuracy. The GWR model took into account the influence of geographical differences, with R2 = 99.98% in fitting and 97.95% in prediction. Wilcoxon test showed that none of the three models outperformed the other two at the significance level of 0.05. The parametric analysis of the infectious rate and recovery rate demonstrated that China's national policies had effectively slowed down the spread of the epidemic. Furthermore, the models in this study provided a wide range of implications for other countries to predict the short-term and long-term trend of COVID-19, and to evaluate the intensity and effect of their interventions. [ABSTRACT FROM AUTHOR]

Backgroud: Effective communication of accurate information through social media constitutes an important component of public health interventions in modern time, when traditional public health approaches such as contact tracing, quarantine and isolation are among the few options for the containing the disease spread in the population. The success of control of COVID-19 outbreak started from Wuhan, the capital city of Hubei Province of China relies heavily on the resilience of residents to follow public health interventions which induce substantial interruption of social-economic activities, and evidence shows that opinion leaders have been playing significant roles in the propagation of epidemic information and public health policy and implementations. Methods: We design a mathematical model to quantify the roles of information superspreaders in single specific information which outbreaks rapidly and usually has a short duration period, and to examine the information propagation dynamics in the Chinese Sina-microblog. Our opinion-leader susceptible-forwarding-immune (OL-SFI) model is formulated to track the temporal evolution of forwarding quantities generated by opinion leaders and normal users. Results: Data fitting from the real data of COVID-19 obtained from Chinese Sina-microblog can identify the different contact rates and forwarding probabilities (and hence calculate the basic information forwarding reproduction number of superspreaders), and can be used to evaluate the roles of opinion leaders in different stages of the information propagation and the outbreak unfolding. Conclusions: The parameterized model can be used to nearcast the information propagation trend, and the model-based sensitivity analysis can help to explore important factors for the roles of opinion leaders. [ABSTRACT FROM AUTHOR]

Since the first suspected case of coronavirus disease-2019 (COVID-19) on December 1st, 2019, in Wuhan, Hubei Province, China, a total of 40,235 confirmed cases and 909 deaths have been reported in China up to February 10, 2020, evoking fear locally and internationally. Here, based on the publicly available epidemiological data for Hubei, China from January 11 to February 10, 2020, we provide estimates of the main epidemiological parameters. In particular, we provide an estimation of the case fatality and case recovery ratios, along with their 90% confidence intervals as the outbreak evolves. On the basis of a Susceptible-Infectious-Recovered-Dead (SIDR) model, we provide estimations of the basic reproduction number (R0), and the per day infection mortality and recovery rates. By calibrating the parameters of the SIRD model to the reported data, we also attempt to forecast the evolution of the outbreak at the epicenter three weeks ahead, i.e. until February 29. As the number of infected individuals, especially of those with asymptomatic or mild courses, is suspected to be much higher than the official numbers, which can be considered only as a subset of the actual numbers of infected and recovered cases in the total population, we have repeated the calculations under a second scenario that considers twenty times the number of confirmed infected cases and forty times the number of recovered, leaving the number of deaths unchanged. Based on the reported data, the expected value of R0 as computed considering the period from the 11th of January until the 18th of January, using the official counts of confirmed cases was found to be ∼4.6, while the one computed under the second scenario was found to be ∼3.2. Thus, based on the SIRD simulations, the estimated average value of R0 was found to be ∼2.6 based on confirmed cases and ∼2 based on the second scenario. Our forecasting flashes a note of caution for the presently unfolding outbreak in China. Based on the official counts for confirmed cases, the simulations suggest that the cumulative number of infected could reach 180,000 (with a lower bound of 45,000) by February 29. Regarding the number of deaths, simulations forecast that on the basis of the up to the 10th of February reported data, the death toll might exceed 2,700 (as a lower bound) by February 29. Our analysis further reveals a significant decline of the case fatality ratio from January 26 to which various factors may have contributed, such as the severe control measures taken in Hubei, China (e.g. quarantine and hospitalization of infected individuals), but mainly because of the fact that the actual cumulative numbers of infected and recovered cases in the population most likely are much higher than the reported ones. Thus, in a scenario where we have taken twenty times the confirmed number of infected and forty times the confirmed number of recovered cases, the case fatality ratio is around ∼0.15% in the total population. Importantly, based on this scenario, simulations suggest a slow down of the outbreak in Hubei at the end of February. [ABSTRACT FROM AUTHOR]

The analysis of traffic collisions is essential for urban safety and the sustainable development of the urban environment. Reducing the road traffic injuries and the financial losses caused by collisions is the most important goal of traffic management. In addition, traffic collisions are a major cause of traffic congestion, which is a serious issue that affects everyone in the society. Therefore, traffic collision analysis is essential for all parties, including drivers, pedestrians, and traffic officers, to understand the road risks at a finer spatio-temporal scale. However, traffic collisions in the urban context are dynamic and complex. Thus, it is important to detect how the collision hotspots evolve over time through spatio-temporal clustering analysis. In addition, traffic collisions are not isolated events in space. The characteristics of the traffic collisions and their surrounding locations also present an influence of the clusters. This work tries to explore the spatio-temporal clustering patterns of traffic collisions by combining a set of network-constrained methods. These methods were tested using the traffic collision data in Jianghan District of Wuhan, China. The results demonstrated that these methods offer different perspectives of the spatio-temporal clustering patterns. The weighted network kernel density estimation provides an intuitive way to incorporate attribute information. The network cross K-function shows that there are varying clustering tendencies between traffic collisions and different types of POIs. The proposed network differential Local Moran’s I and network local indicators of mobility association provide straightforward and quantitative measures of the hotspot changes. This case study shows that these methods could help researchers, practitioners, and policy-makers to better understand the spatio-temporal clustering patterns of traffic collisions. [ABSTRACT FROM AUTHOR]

Background: Millions of people move from rural areas to urban areas in China to pursue new opportunities while leaving their spouses and children at rural homes. Little is known about the impact of migration-related separation on mental health of these rural migrants in urban China. Methods: Survey data from a random sample of rural-to-urban migrants (n = 1113, aged 18–45) from Wuhan were analyzed. The Domestic Migration Stress Questionnaire (DMSQ), an instrument with four subconstructs, was used to measure migration-related stress. The relationship between spouse/child separation and stress was assessed using survey estimation methods to account for the multi-level sampling design. Results: 16.46% of couples were separated from their spouses (spouse-separation only), 25.81% of parents were separated from their children (child separation only). Among the participants who married and had children, 5.97% were separated from both their spouses and children (double separation). Spouse-separation only and double separation did not scored significantly higher on DMSQ than those with no separation. Compared to parents without child separation, parents with child separation scored significantly higher on DMSQ (mean score = 2.88, 95% CI: [2.81, 2.95] vs. 2.60 [2.53, 2.67], p < .05). Stratified analysis by separation type and by gender indicated that the association was stronger for child-separation only and for female participants. Conclusion: Child-separation is an important source of migration-related stress, and the effect is particularly strong for migrant women. Public policies and intervention programs should consider these factors to encourage and facilitate the co-migration of parents with their children to mitigate migration-related stress. [ABSTRACT FROM AUTHOR]

Background and Objective: High concentrations of air pollutants have been linked to increased incidence of stroke in North America and Europe but not yet assessed in mainland China. The aim of this study is to evaluate the association between stroke hospitalization and short-term elevation of air pollutants in Wuhan, China. Methods: Daily mean NO2, SO2 and PM10 levels, temperature and humidity were obtained from 2006 through 2008. Data on stroke hospitalizations (ICD 10: I60–I69) at four hospitals in Wuhan were obtained for the same period. A time-stratified case-crossover design was performed by season (April-September and October-March) to assess effects of pollutants on stroke hospital admissions. Results: Pollution levels were higher in October-March with averages of 136.1 µg/m3 for PM10, 63.6 µg/m3 for NO2 and 71.0 µg/m3 for SO2 than in April-September when averages were 102.0 µg/m3, 41.7 µg/m3 and 41.7 µg/m3, respectively (p<.001). During the cold season, every 10 µg/m3 increase in NO2 was associated with a 2.9% (95%C.I. 1.2%–4.6%) increase in stroke admissions on the same day. Every 10 ug/m3 increase in PM10 daily concentration was significantly associated with an approximate 1% (95% C.I. 0.1%–1.4%) increase in stroke hospitalization. A two-pollutant model indicated that NO2 was associated with stroke admissions when controlling for PM10. During the warm season, no significant associations were noted for any of the pollutants. Conclusions: Exposure to NO2 is significantly associated with stroke hospitalizations during the cold season in Wuhan, China when pollution levels are 50% greater than in the warm season. Larger and multi-center studies in Chinese cities are warranted to validate our findings. [ABSTRACT FROM AUTHOR]

This study aimed to examine the experience and knowledge of mild cognitive impairment (MCI) among Chinese family caregivers of individuals with MCI. The sample was recruited from memory clinics in Zhongnan Hospital in Wuhan, China. In-depth semi-structured interviews were used. Thirteen family members of individuals diagnosed with MCI participated in the study. Data analysis revealed three themes: 1) initial recognition of cognitive decline; 2) experience of the diagnosis of MCI; 3) perception of cognitive decline as a normal part of aging. While family members recognized the serious consequences of memory loss (e.g. getting lost), they would typically not take their family members to see a doctor until something specific triggered their access to the medical care system. The Chinese traditional perception of dementia as part of normal aging may serve to lessen the stigma of individuals with MCI, while the term "laonian chidai" which literally translates to "stupid, demented elderly" may exacerbate the stigma associated with individuals with MCI. It is suggested that family members' worries may be relieved by improving their access to accurate knowledge of the disease, community-based and institutional care services, and culturally appropriately words are needed for MCI. [ABSTRACT FROM AUTHOR]

Objective: To compare HCV and HIV infection among heroin addicts in MMT and not in MMT in two large cities in central China. Methods: A total of 541 heroin addicts were recruited from MMT clinics and voluntary detoxification centers in Changsha and Wuhan, China. Structured questionnaires collected data on their socio-demographics, clinical status, risk behaviors, and their knowledge of HIV. Their HIV serostatus and Hepatitis C virus (HCV) serostatus were determined by testing antibodies in blood serum. Results: We observed a higher prevalence of HCV infection among MMT heroin addicts (82.3%) than that in the non-MMT group (50.6%). However, our findings indicated that the heroin addicts in MMT had less drug or sexual HIV/HCV risk behaviors and more knowledge about HIV than non-MMT addicts. The heroin addicts in MMT had a significantly higher percentage of individuals who always used condoms (44.9%) compared with patients in the non-MMT group (14.6%, p = 0.039), and they had more knowledge about HIV than non-MMT individuals (p<.001). The percentage of HIV-positive addicts in the MMT group (0.7%) and non-MMT group (0.8%) were almost same. Conclusion: Our study indicated that the rate of HCV infection among heroin addicts among MMT or non-MMT settings in central China is very high. The non-MMT heroin addicts have higher risk of becoming infected with HCV in the future, while at present they have lower rates of HCV infection than MMT heroin addicts. Although rates of HIV infection among MMT and non-MMT heroin addicts are low now, they are all at great risk of becoming infected with HIV in the future, especially for non-MMT heroin addicts. We should use the MMT sites as a platform to improve the control of HCV and HIV infection in heroin addicts. [ABSTRACT FROM AUTHOR]