scholarly journals Spatial statistics and influencing factors of the novel coronavirus pneumonia 2019 epidemic in Hubei Province, China

2020 ◽  
Author(s):  
Yongzhu Xiong ◽  
Yunpeng Wang ◽  
Feng Chen ◽  
Mingyong Zhu
Keyword(s):  
Spatial Autocorrelation ◽  
Influencing Factors ◽  
Pearson Correlation ◽  
Hubei Province ◽  
County Level ◽  
The Novel ◽  
Land Area ◽  
Novel Coronavirus ◽  
And Control ◽  
Global Spatial Autocorrelation

Abstract An in-depth understanding of the spatiotemporal dynamic characteristics of infectious diseases could be helpful for epidemic prevention and control. Based on the novel coronavirus pneumonia (NCP) data published on official websites, GIS spatial statistics and Pearson correlation methods were used to analyze the spatial autocorrelation and influencing factors of the 2019 NCP epidemic from January 30, 2020 to February 18, 2020. The following results were obtained. (1) During the study period, Hubei Province was the only significant cluster area and hotspot of cumulative confirmed cases of NCP infection at the provincial level in China. (2) The NCP epidemic in China had a very significant global spatial autocorrelation at the prefecture-city level, and Wuhan was the significant hotspot and cluster city for cumulative confirmed NCP cases in the whole country. (3) The cumulative confirmed NCP cases had a very significant global spatial autocorrelation at the county level in Hubei Province, and the county-level districts under the jurisdiction of Wuhan and neighboring Huangzhou district in Huanggang City were the significant hotspots and spatial clusters of cumulative confirmed NCP cases. (4) Based on Pearson correlation analysis, the number of cumulative confirmed NCP cases in Hubei Province had very significant and positive correlations (p<0.01) at the prefecture-city and the county levels with four population indexes (registered population, resident population, regional GDP and total retail sales of consumer goods) during the study period. (5) The number of the cumulative confirmed NCP cases in Hubei Province also had a very significant and positive correlation (p<0.01) on the prefecture-city scale with the Baidu migration index and population density but not with land area, whereas that in Hubei Province had a significant and positive correlation (p<0.05) at the county level with land area but not with population density from January 30, 2020, to February 18, 2020. It was found that the NCP epidemic in Hubei Province had distinctive characteristics of a significant centralized outbreak, significant spatial autocorrelation and complex influencing factors and that the spatial scale had a significant effect on the global spatial autocorrelation of the NCP epidemic. The findings help to deepen the understanding of spatial distribution patterns and transmission trends of the NCP epidemic and may also benefit scientific prevention and control of epidemics such as COVID-19.

scholarly journals Spatial Statistics and Influencing Factors of the Epidemic of Novel Coronavirus Pneumonia 2019 in Hubei Province, China

2020 ◽  
Author(s):  
Yongzhu Xiong ◽  
Yunpeng Wang ◽  
Feng Chen ◽  
Mingyong Zhu
Keyword(s):  
Spatial Autocorrelation ◽  
Influencing Factors ◽  
Hot Spot ◽  
Pearson Correlation ◽  
Hubei Province ◽  
Land Area ◽  
Novel Coronavirus ◽  
And Control ◽  
Global Spatial Autocorrelation ◽  
County Scale

Abstract An in-depth understanding of spatiotemporal dynamic characteristics of infectious diseases could be helpful to an epidemic prevention and control. Based on the novel coronavirus pneumonia (NCP) data published on official websites, GIS spatial statistics and Pearson correlation methods were used to analyze the spatial autocorrelation and influencing factors of the 2019 NCP epidemic from January 30, 2020 to February 18, 2020. The results of the study showed that: (1) During the study period, Hubei Province was the only significant cluster area and hot spot of the cumulative cases confirmed with the NCP infection in China on the provincial scale; (2) The epidemic of the NCP infection in China on the prefecture-city scale had a very significant global spatial autocorrelation, and Wuhan had always been the significant hot spot and cluster city of the cumulative cases confirmed with the NCP infection in the whole country; (3) The cumulative cases confirmed with the NCP infection in Hubei Province on the county scale had a very significant global spatial autocorrelation, and the county-level districts under the jurisdiction of Wuhan and its neighboring Huangzhou district in Huanggang City were the significant hot spots and spatial clusters of the cumulative cases confirmed with the NCP infection; (4) Based on Pearson correlation analysis, the number of the accumulative cases confirmed with the NCP infection in Hubei Province on the prefecture-city scale and also on the county scale had very significant and positive correlations (p < 0.01) with the four indexes of population of registration population, resident population, regional GDP and total retail sales of consumer goods, respectively, during the study period; (5) The number of the cumulative cases confirmed with the NCP infection in Hubei Province on the prefecture-city scale also had a very significant and positive correlation (p < 0.01) with Baidu migration index and population density, respectively, but not with land area, whereas that in Hubei Province on the county scale had a significant and positive correlation (p < 0.05) with land area, but not with population density from January 30, 2020 to February 18, 2020. It is found that the NCP epidemic in Hubei Province has the distinctive characteristics of significantly centralized outbreak, significantly spatial autocorrelation and complex influencing factors and that the spatial scale has a significant effect on the global spatial autocorrelation of the NCP epidemic. The findings help to deepen the understanding of spatial distribution patterns and transmission trends of the NCP epidemic and may also benefit scientific prevention and control of epidemics such as NCP 2019.

scholarly journals Spatial Statistics and Influencing Factors of the COVID-19 Epidemic at Both Prefecture and County Levels in Hubei Province, China

2020 ◽  
Vol 17 (11) ◽  
pp. 3903 ◽  
Author(s):  
Yongzhu Xiong ◽  
Yunpeng Wang ◽  
Feng Chen ◽  
Mingyong Zhu
Keyword(s):  
Spatial Autocorrelation ◽  
Influencing Factors ◽  
Multiple Scales ◽  
Open Data ◽  
Rank Correlation ◽  
Hubei Province ◽  
Spatiotemporal Patterns ◽  
County Level ◽  
Negatively Associated ◽  
Spearman’S Rank Correlation

The coronavirus disease 2019 (COVID-19) epidemic has had a crucial influence on people’s lives and socio-economic development. An understanding of the spatiotemporal patterns and influencing factors of the COVID-19 epidemic on multiple scales could benefit the control of the outbreak. Therefore, we used spatial autocorrelation and Spearman’s rank correlation methods to investigate these two topics, respectively. The COVID-19 epidemic data reported publicly and relevant open data in Hubei province were analyzed. The results showed that (1) at both prefecture and county levels, the global spatial autocorrelation was extremely significant for the cumulative confirmed COVID-19 cases (CCC) in Hubei province from 30 January to 18 February 2020. Further, (2) at both levels, the significant hotspots and cluster/outlier areas were observed solely in Wuhan city and most of its districts/sub-cities from 30 January to 18 February 2020. (3) At the prefecture level in Hubei province, the number of CCC had a positive and extremely significant correlation (p < 0.01) with the registered population (RGP), resident population (RSP), Baidu migration index (BMI), regional gross domestic production (GDP), and total retail sales of consumer goods (TRS), respectively, from 29 January to 18 February 2020 and had a negative and significant correlation (p < 0.05) with minimum elevation (MINE) from 2 February to 18 February 2020, but no association with the land area (LA), population density (PD), maximum elevation (MAXE), mean elevation (MNE), and range of elevation (RAE) from 23 January to 18 February 2020. (4) At the county level, the number of CCC in Hubei province had a positive and extremely significant correlation (p < 0.01) with PD, RGP, RSP, GDP, and TRS, respectively, from 27 January to 18 February 2020, and was negatively associated with MINE, MAXE, MNE, and RAE, respectively, from 26 January to 18 February 2020, and negatively associated with LA from 30 January to 18 February 2020. It suggested that (1) the COVID-19 epidemics at both levels in Hubei province had evident characteristics of significant global spatial autocorrelations and significant centralized high-risk outbreaks. (2) The COVID-19 epidemics were significantly associated with the natural factors, such as LA, MAXE, MNE, and RAE, -only at the county level, not at the prefecture level, from 2 February to 18 February 2020. (3) The COVID-19 epidemics were significantly related to the socioeconomic factors, such as RGP, RSP, TRS, and GDP, at both levels from 26 January to 18 February 2020. It is desired that this study enrich our understanding of the spatiotemporal patterns and influencing factors of the COVID-19 epidemic and benefit classified prevention and control of the COVID-19 epidemic for policymakers.

scholarly journals A deterministic epidemic model for the emergence of COVID-19 in China

2020 ◽  
Author(s):  
Meng Wang ◽  
Jingtao Qi
Keyword(s):  
Prevention And Control ◽  
Reproduction Number ◽  
Chinese Mainland ◽  
Hubei Province ◽  
Control Measures ◽  
The Novel ◽  
Health Authorities ◽  
Prevention And Control Measures ◽  
Novel Coronavirus ◽  
And Control

AbstractCoronavirus disease (COVID-19) broke out in Wuhan, Hubei province, China, in December 2019 and soon after Chinese health authorities took unprecedented prevention and control measures to curb the spreading of the novel coronavirus-related pneumonia. We develop a mathematical model based on daily updates of reported cases to study the evolution of the epidemic. With the model, on 95% confidence level, we estimate the basic reproduction number, R0 = 2.82 ± 0.11, time between March 19 and March 21 when the effective reproduction number becoming less than one, the epidemic ending after April 2 and the total number of confirmed cases approaching 14408 ± 429 on the Chinese mainland excluding Hubei province.

scholarly journals Multi-Objective Optimization of Integrated Civilian-Military Scheduling of Medical Supplies for Epidemic Prevention and Control

Healthcare ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 126
Author(s):  
Hai-Feng Ling ◽  
Zheng-Lian Su ◽  
Xun-Lin Jiang ◽  
Yu-Jun Zheng
Keyword(s):  
Prevention And Control ◽  
Large Scale ◽  
Medical Services ◽  
The Novel ◽  
Multi Objective ◽  
Medical Supplies ◽  
Problem Instances ◽  
Novel Coronavirus ◽  
And Control ◽  
Minimum Ratio

In a large-scale epidemic, such as the novel coronavirus pneumonia (COVID-19), there is huge demand for a variety of medical supplies, such as medical masks, ventilators, and sickbeds. Resources from civilian medical services are often not sufficient for fully satisfying all of these demands. Resources from military medical services, which are normally reserved for military use, can be an effective supplement to these demands. In this paper, we formulate a problem of integrated civilian-military scheduling of medical supplies for epidemic prevention and control, the aim of which is to simultaneously maximize the overall satisfaction rate of the medical supplies and minimize the total scheduling cost, while keeping a minimum ratio of medical supplies reservation for military use. We propose a multi-objective water wave optimization (WWO) algorithm in order to efficiently solve this problem. Computational results on a set of problem instances constructed based on real COVID-19 data demonstrate the effectiveness of the proposed method.

scholarly journals A Study On Financial Self-Efficacy During Covid-19

2021 ◽  
Vol 23 (08) ◽  
pp. 472-483
Author(s):  
Sitangshu Khatua ◽  
◽  
Debdulal Dutta Roy ◽  
Keyword(s):  
Self Efficacy ◽  
Principal Component ◽  
The Novel ◽  
The Great Depression ◽  
Online Mode ◽  
Personal Finances ◽  
Study Results ◽  
Financial Goal ◽  
Novel Coronavirus ◽  
And Control

Financial Self-efficacy is defined as a person’s observed capability to control his/her personal finances (Lapp, 2010; Postmus, 2011). It refers to one’s beliefs in the abilities to accomplish a financial goal or task. It is the “knowledge and ability to influence and control one’s financial matters” by Fox and Bartholomae (2008). Financial efficacy pattern of people during very critical moment is unknown. The world is experiencing one of the deepest recessions since the Great Depression in the 1930s owing to the novel coronavirus, World Bank President David Malpass has said, terming the COVID-19 pandemic a “catastrophic event” for many developing and the poorest countries. Aim of the study is to examine financial efficacy pattern of people during lockdown period for COVID-19. Data were collected through online mode using financial efficacy scale developed by authors for the study. Results of principal component analysis revealed that during lockdown, financial efficacy is more concerned with financial planning, planned payment and financial coping.

Application of Early Warning Nursing System During COVID-19 Epidemic in Children’s Hospital

Nano LIFE ◽  
2021 ◽  
pp. 2140004
Author(s):  
Wenying Yao ◽  
Jinxia Yang ◽  
Xin Wang ◽  
Min Shen
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Popular Science ◽  
The Novel ◽  
Children's Hospital ◽  
Hospital Nursing ◽  
Children’S Hospital ◽  
Novel Coronavirus ◽  
And Control

Aim: To develop a nursing early warning system in children’s hospital during the outbreak of the novel coronavirus pneumonia, and to accomplish the construction and application of this system, so as to provide decision-support of the prevention and control for COVID-19 in children’s medical institutions. Method: Children’s hospital nursing early warning system was divided into three modules: hospital nursing early warning platform includes internal and external early warning platform, nursing staff early warning program includes protection, human resources early warning plan and patient early warning program includes outpatient, emergency and ward early warning plan. The data of epidemic training, assessment, prevention and control screening from January to June 2020 were collected from the nursing early warning system to evaluate the application effect of the system. Results: A total of 18 procedures and specifications were formulated, nine hospital-level trainings and about 1000 department-level trainings were organized, two hospital-level assessments (pass rate 95.6% and 98.2%), and 78 nurses were reserved, and 10 popular science articles, five popular science videos were published during the application of the nursing early warning system. A total of 583,435 children and 139,308 caregivers were screened in outpatient, emergency and wards during pre-checks, 2385 suspected cases of novel coronavirus pneumonia were confirmed (0.41%) after the screening and 1 case (0.0002%) was finally confirmed. Conclusion: The nursing early warning system of children’s hospital can prevent and control the novel coronavirus pneumonia epidemic from each module, ensure early warning and triage of suspected infected patients, reduce the risk of cross-infection in hospital and improve the safety of the children’s hospital medical environment.

scholarly journals Consideration of the Management of Pediatric Fever Clinics During the Novel Coronavirus Pneumonia Outbreak

2020 ◽  
pp. 1-7
Author(s):  
Hui Ding ◽  
Zhaoling Shi ◽  
Zhen Ruan ◽  
Xiaoning Cheng ◽  
Ruying Li ◽  
...  
Keyword(s):  
Medical Staff ◽  
Prevention And Control ◽  
Cross Infection ◽  
The Novel ◽  
Wuhan City ◽  
Control Programs ◽  
Treatment And Prevention ◽  
Epidemic Period ◽  
Novel Coronavirus ◽  
And Control

ABSTRACT Since the outbreak of 2019 novel coronavirus (2019-nCoV) infection in Wuhan City, China, pediatric cases have gradually increased. It is very important to prevent cross-infection in pediatric fever clinics, to identify children with fever in pediatric fever clinics, and to strengthen the management of pediatric fever clinics. According to prevention and control programs, we propose the guidance on the management of pediatric fever clinics during the nCoV pneumonia epidemic period, which outlines in detail how to optimize processes, prevent cross-infection, provide health protection, and prevent disinfection of medical staff. The present consideration statement summarizes current strategies on the pre-diagnosis, triage, diagnosis, treatment, and prevention of 2019-nCoV infection, which provides practical suggestions on strengthening the management of pediatric fever clinics during the nCoV pneumonia epidemic period.

scholarly journals The Online Education Mode and Reopening Plans for Chinese Schools During the COVID-19 Pandemic: A Mini Review

2020 ◽  
Vol 8 ◽  
Author(s):  
Xuanzhen Cen ◽  
Dong Sun ◽  
Ming Rong ◽  
Gusztáv Fekete ◽  
Julien S. Baker ◽  
...  
Keyword(s):  
Online Education ◽  
Prevention And Control ◽  
World Health ◽  
Classroom Teaching ◽  
Full Time ◽  
The Novel ◽  
The World ◽  
Novel Coronavirus ◽  
Health Organization ◽  
And Control

Recently, an unprecedented coronavirus pandemic has emerged and has spread around the world. The novel coronavirus termed COVID-19 by the World Health Organization has posed a huge threat to human safety and social development. This mini review aimed to summarize the online education mode and plans for schools to resume full-time campus study in China during COVID-19. Chinese schools have made significant contributions to the prevention and control of the transmission of COVID-19 by adopting online learning from home. However, normal opening and classroom teaching have been affected. For education systems at all levels, online education may be an effective way to make up for the lack of classroom teaching during the epidemic. To protect staff and students from COVID-19, the timing of students returning to full-time campus study needs to be considered carefully. Reviewing and summarizing of the Chinese education system's response to the virus would be of great value not only in developing educational policy but also in guiding other countries to formulate educational countermeasures.

scholarly journals Exploring the role and mechanism of COVID-19 apps in fighting the current pandemic

2020 ◽  
Vol 0 ◽  
pp. 1-6
Author(s):  
Karthikeyan P. Iyengar ◽  
Rachit Jain ◽  
David Ananth Samy ◽  
Vijay Kumar Jain ◽  
Raju Vaishya ◽  
...  
Keyword(s):  
Data Privacy ◽  
Viral Transmission ◽  
Contact Tracing ◽  
The Novel ◽  
Test Track ◽  
The World ◽  
Novel Coronavirus ◽  
And Control ◽  
Second Wave ◽  
Transmission Test

As COVID-19 pandemic spread worldwide, policies have been developed to contain the disease and prevent viral transmission. One of the key strategies has been the principle of “‘test, track, and trace” to minimize spread of the virus. Numerous COVID-19 contact tracing applications have been rolled around the world to monitor and control the spread of the disease. We explore the characteristics of various COVID-19 applications and especially the Aarogya Setu COVID-19 app from India in its role in fighting the current pandemic. We assessed the current literature available to us using conventional search engines, including but not limited to PubMed, Google Scholar, and Research Gate in May 2020 till the time of submission of this article. The search criteria used MeSH keywords such as “COVID-19,” “pandemics,” “contact tracing,” and “mobile applications.” A variable uptake of different COVID-19 applications has been noted with increasing enrolment around the world. Security concerns about data privacy remain. The various COVID-19 applications will complement manual contact tracing system to assess and prevent viral transmission. Test, track, trace, and support policy will play a key role in avoidance of a “second wave” of the novel coronavirus severe acute respiratory syndrome coronavirus 2 outbreak.

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