标题: Cultivating Resilience During the COVID-19 Pandemic: A Socioecological Perspective

作者: Ning Zhang, Shujuan Yang and Peng Jia

来源出版物: Annual Review of Psychology DOI: https://doi.org/10.1146/annurev-psych-030221-031857出版时间：January 2022

摘要: The coronavirus disease 2019 (COVID-19) pandemic poses wide-ranging impacts on the physical and mental health of people around the world, increasing attention from both researchers and practitioners on the topic of resilience. In this article, we review previous research on resilience from the past several decades, focusing on how to cultivate resilience during emerging situations such as the COVID-19 pandemic at the individual, organizational, community, and national levels from a socioecological perspective. Although previous research has greatly enriched our understanding of the conceptualization, predicting factors, processes, and consequences of resilience from a variety of disciplines and levels, future research is needed to gain a deeper and comprehensive understanding of resilience, including developing an integrative and interdisciplinary framework for cultivating resilience, developing an understanding of resilience from a life span perspective, and developing scalable and cost-effective interventions for enhancing resilience and improving pandemic preparedness.

地址:

[Ning Zhang]School of Public Health and the Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310058, China

Center for Disease Control and Prevention of Hangzhou, Hangzhou 310016, China

[Shujuan Yang]West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China; email: rekiny@126.com

[Peng Jia]School of Resources and Environmental Science, Wuhan University, Wuhan 430072, China; email: jiapengff@hotmail.com

[Ning Zhang, Shujuan Yang and Peng Jia]International Institute of Spatial Lifecourse Epidemiology (ISLE), Wuhan University, Wuhan 430072, China

通讯作者地址:Jia, P (通讯作者)，Wuhan Univ, Sch Resources & Environm Sci, Wuhan, Peoples R China.

电子邮件地址: jiapengff@hotmail.com

影响因子：24.137

标题: The epidemiology, pathophysiological mechanisms, and management toward COVID-19 patients with Type 2 diabetes: A systematic review

作者: Yun Yin, Kristen E.Rohli, Pengyue Shen, Haonan Lu, Yuenan Liu, Qingyu Dou, Lin Zhang, Xiangyi Kong, Shujuan Yang, Peng Jia

来源出版物: Primary Care Diabetes期：15卷：6页数：899-909出版时间：December 2021

摘要: This review comprehensively summarizes epidemiologic evidence of COVID-19 in patients with Type 2 diabetes, explores pathophysiological mechanisms, and integrates recommendations and guidelines for patient management. We found that diabetes was a risk factor for diagnosed infection and poor prognosis of COVID-19. Patients with diabetes may be more susceptible to adverse outcomes associated with SARS-CoV-2 infection due to impaired immune function and possible upregulation of enzymes that mediate viral invasion. The chronic inflammation caused by diabetes, coupled with the acute inflammatory reaction caused by SARS-CoV-2, results in a propensity for inflammatory storm. Patients with diabetes should be aware of their increased risk for COVID-19.

作者关键词: COVID-19DiabetesEpidemiologyPathophysiological mechanismManagementSARS-CoV-2

通讯作者地址: Shujuan Yang, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.

Peng Jia, School of Resources and Environmental Science, Wuhan University, Wuhan, China.

电子邮件地址: jiapengff@hotmail.com

影响因子：2.459

标题: New Approaches to Anticipate the Risk of Reverse Zoonosis

作者: Jia, P (Jia, Peng); Dai, SQ (Dai, Shaoqing); Wu, T (Wu, Tong); Yang, SJ (Yang, Shujuan)

来源出版物: TRENDS IN ECOLOGY & EVOLUTION卷: 36期: 7页: 580-590 DOI: 10.1016/j.tree.2021.03.012出版年: JUL 2021

摘要: The coronavirus disease 2019 (COVID-19) pandemic can cause reverse zoonoses (i.e., human-animal transmission of COVID-19). It is vital to utilize up-to-date methods to improve the control, management, and prevention of reverse zoonoses. Awareness of reverse zoonoses should be raised at both individual and regional/national levels for better protection of both humans and animals.

地址: [Jia, Peng] Wuhan Univ, Sch Resources & Environm Sci, Wuhan, Peoples R China.

[Jia, Peng] Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Hong Kong, Peoples R China.

[Jia, Peng; Dai, Shaoqing; Wu, Tong; Yang, Shujuan] Int Inst Spatial Lifecourse Epidemiol ISLE, Hong Kong, Peoples R China.

[Wu, Tong] Chinese Acad Sci, Res Ctr Ecoenvironm Sci, Beijing, Peoples R China.

[Yang, Shujuan] Sichuan Univ, West China Sch Publ Hlth, Chengdu, Peoples R China.

[Yang, Shujuan] Sichuan Univ, West China Fourth Hosp, Chengdu, Peoples R China.

通讯作者地址: Jia, P (通讯作者)，Wuhan Univ, Sch Resources & Environm Sci, Wuhan, Peoples R China.

Jia, P (通讯作者)，Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Hong Kong, Peoples R China.

Jia, P (通讯作者)，Int Inst Spatial Lifecourse Epidemiol ISLE, Hong Kong, Peoples R China.

电子邮件地址:jiapengff@hotmail.com

影响因子：17.712

标题: Spatial Lifecourse Epidemiology and Infectious Disease Research

作者: Jia, P (Jia, Peng); Dong, WH (Dong, Weihua); Yang, SJ (Yang, Shujuan); Zhan, ZC (Zhan, Zhicheng); Tu, L (Tu, La); Lai, SJ (Lai, Shengjie)

来源出版物: TRENDS IN PARASITOLOGY卷: 36期: 3页: 235-238 DOI: 10.1016/j.pt.2019.12.012出版年: MAR 2020

摘要: Spatial lifecourse epidemiology aims to utilize advanced spatial, location-aware, and artificial intelligence technologies to investigate long-term effects of measurable biological, environmental, behavioral, and psychosocial factors on individual risk for chronic diseases. It could also further the research on infectious disease dynamics, risks, and consequences across the life course.

地址: [Jia, Peng] Wuhan Univ, Sch Resources & Environm Sci, Wuhan, Peoples R China.

[Jia, Peng] Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Hong Kong, Peoples R China.

[Jia, Peng; Yang, Shujuan] Int Initiat Spatial Lifecourse Epidemiol ISLE, Hong Kong, Peoples R China.

[Dong, Weihua; Zhan, Zhicheng] Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.

[Dong, Weihua; Zhan, Zhicheng] Beijing Normal Univ, Fac Geog, Beijing 100875, Peoples R China.

[Yang, Shujuan] Sichuan Univ, West China Sch Publ Hlth, West China Fourth Hosp, Chengdu 610041, Sichuan, Peoples R China.

[Tu, La] Tsinghua Univ, Dept Informat Art & Design, Beijing 100084, Peoples R China.

[Lai, Shengjie] Univ Southampton, WorldPop, Sch Geog & Environm Sci, Southampton SO17 1BJ, Hants, England.

[Lai, Shengjie] Flowminder Fdn, SE-11355 Stockholm, Sweden.

[Lai, Shengjie] Fudan Univ, Key Lab Publ Hlth Safety, Sch Publ Hlth, Minist Educ, Shanghai 200032, Peoples R China.

通讯作者地址: Jia, P (通讯作者)，Wuhan Univ, Sch Resources & Environm Sci, Wuhan, Peoples R China.

Jia, P (通讯作者)，Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Hong Kong, Peoples R China.

Jia, P (通讯作者)，Int Initiat Spatial Lifecourse Epidemiol ISLE, Hong Kong, Peoples R China.

电子邮件地址:jiapengff@hotmail.com

影响因子：9.014

标题: Cross-disciplinary approaches to assist with nucleic acid testing for SARS-CoV-2

作者: Yang, SJ (Yang, Shujuan); Pan, XF (Pan, Xiongfeng); Yuan, D (Yuan, Dan); Zeng, PB (Zeng, Peibin); Jia, P (Jia, Peng)

来源出版物: APPLIED MICROBIOLOGY AND BIOTECHNOLOGY卷: 105期: 16-17页: 6291-6299 DOI: 10.1007/s00253-021-11498-2提前访问日期: AUG 2021出版年: AUG 2021

摘要: Improving the capacity of detecting positive severe acute respiratory syndrome coronavirus 2 is critical for identifying the infection of coronavirus disease 2019 (COVID-19) precisely and thereby curbing the pandemic. Cross-disciplinary approaches may improve the efficiency of COVID-19 diagnosis by compensating to some extent the limitations encountered by traditional test methods during the COVID-19 pandemic. Combining computed tomography (CT), serum-specific antibody detection, and nanopore sequencing with nucleic acid testing for individual testing may improve the accuracy of identifying COVID-19 patients. At community or even regional/national levels, the combination of pooled screening and spatial epidemiological strategies may enable the detection of early transmission of epidemics in a cost-effective way, which is also less affected by restricted access to diagnostic tests and kit supplies. This would significantly advance our capacity of curbing epidemics as soon as possible, and better prepare us for entering a new era of high-impact and high-frequency epidemics.

文献类型: Review

作者关键词: SARS-CoV-2; COVID-19; Nucleic acid testing; Sampling; CT; Spatial epidemiology

KeyWords Plus: EPIDEMIOLOGY

地址: [Yang, Shujuan; Zeng, Peibin] Sichuan Univ, West China Sch Publ Hlth, Chengdu, Peoples R China.

[Yang, Shujuan; Zeng, Peibin] Sichuan Univ, West China Hosp 4, Chengdu, Peoples R China.

[Yang, Shujuan; Pan, Xiongfeng; Jia, Peng] Wuhan Univ, Int Inst Spatial Lifecourse Epidemiol ISLE, Wuhan, Peoples R China.

[Pan, Xiongfeng] Cent South Univ, Xiangya Sch Publ Hlth, Changsha, Peoples R China.

[Yuan, Dan] Sichuan Ctr Dis Control & Prevent, Chengdu, Peoples R China.

[Jia, Peng] Wuhan Univ, Sch Resources & Environm Sci, Wuhan, Peoples R China.

通讯作者地址: Zeng, PB (通讯作者)，Sichuan Univ, West China Sch Publ Hlth, Chengdu, Peoples R China.

Zeng, PB (通讯作者)，Sichuan Univ, West China Hosp 4, Chengdu, Peoples R China.

Jia, P (通讯作者)，Wuhan Univ, Int Inst Spatial Lifecourse Epidemiol ISLE, Wuhan, Peoples R China.

Jia, P (通讯作者)，Wuhan Univ, Sch Resources & Environm Sci, Wuhan, Peoples R China.

电子邮件地址: zengpeibin@live.cn;jiapengff@hotmail.com

影响因子：4.813

标题: Changes in patterns of take-away food ordering among youths before and after COVID-19 lockdown in China: the COVID-19 Impact on Lifestyle Change Survey (COINLICS)

作者: Luo, MY (Luo, Miyang); Wang, QJ (Wang, Qinjian); Yang, SJ (Yang, Shujuan); Jia, P (Jia, Peng)

来源出版物: EUROPEAN JOURNAL OF NUTRITION DOI: 10.1007/s00394-021-02622-z提前访问日期: JUL 2021

摘要: Background The lockdown due to COVID-19 may have led to changes in food ordering patterns among youths, which could affect their dietary patterns and the operation of the restaurant industry. Objectives This study aimed to examine the impacts of COVID-19 lockdown on patterns of take-away food ordering among youth in China. Methods The COVID-19 Impact on Lifestyle Change Survey (COINLICS) was conducted among youths at three educational levels (high or vocational school, college, and graduate school) in China in early May 2020. Information on patterns of take-away food ordering in the months immediately before and after the COVID-19 lockdown period (23 January to 8 April 2020) was collected through an online questionnaire survey. Results A total of 10,082 participants were included in the analysis. Participants ordering food more than once per week dropped from 15.4 to 9.2%, while 81.1% of participants have never ordered food at both time points. Graduate students, although experiencing a decrease in food ordering for more than once per week (from 33.3 to 10.7%), were more likely to order food compared to undergraduate and high school students. A slight increase was observed for ordering fried food or hamburgers and for breakfast and midnight snacks. Conclusions The youth have generally ordered take-away food less frequently after COVID-19 lockdown, and the times and types of ordering have both changed. These findings would contribute solid evidence to the current knowledge pool for reference of health promotion communities to keep youth's lifestyles healthy and of the restaurant industry to achieve more cost-effective operation in China during future health emergencies.

文献类型: Article; Early Access

作者关键词: COVID-19; Youth; Lockdown; Food ordering; Take-away food

地址: [Luo, Miyang] Cent South Univ, Xiangya Sch Publ Hlth, Changsha, Peoples R China.

[Wang, Qinjian; Yang, Shujuan] Sichuan Univ, West China Sch Publ Hlth, Chengdu, Peoples R China.

[Wang, Qinjian; Yang, Shujuan] Sichuan Univ, West China Hosp 4, Chengdu, Peoples R China.

[Jia, Peng] Wuhan Univ, Sch Resources & Environm Sci, Wuhan, Peoples R China.

[Luo, Miyang; Yang, Shujuan; Jia, Peng] Int Inst Spatial Lifecourse Epidemiol ISLE, Hong Kong, Peoples R China.

通讯作者地址: Yang, SJ (通讯作者)，Sichuan Univ, West China Sch Publ Hlth, Chengdu, Peoples R China.

Yang, SJ (通讯作者)，Sichuan Univ, West China Hosp 4, Chengdu, Peoples R China.

Jia, P (通讯作者)，Wuhan Univ, Sch Resources & Environm Sci, Wuhan, Peoples R China.

Yang, SJ; Jia, P (通讯作者)，Int Inst Spatial Lifecourse Epidemiol ISLE, Hong Kong, Peoples R China.

电子邮件地址: rekiny@126.com;jiapengff@hotmail.com

影响因子：5.619

标题: Exploring Fuzzy Local Spatial Information Algorithms for Remote Sensing Image Classification

作者: Madhu, A (Madhu, Anjali); Kumar, A (Kumar, Anil); Jia, P (Jia, Peng)

来源出版物: REMOTE SENSING卷: 13期: 20文献号: 4163 DOI: 10.3390/rs13204163出版年: OCT 2021

摘要: Fuzzy c-means (FCM) and possibilistic c-means (PCM) are two commonly used fuzzy clustering algorithms for extracting land use land cover (LULC) information from satellite images. However, these algorithms use only spectral or grey-level information of pixels for clustering and ignore their spatial correlation. Different variants of the FCM algorithm have emerged recently that utilize local spatial information in addition to spectral information for clustering. Such algorithms are seen to generate clustering outputs that are more enhanced than the classical spectral-based FCM algorithm. Nonetheless, the scope of integrating spatial contextual information with the conventional PCM algorithm, which has several advantages over the FCM algorithm for supervised classification, has not been explored much. This study proposed integrating local spatial information with the PCM algorithm using simpler but proven approaches from available FCM-based local spatial information algorithms. The three new PCM-based local spatial information algorithms: Possibilistic c-means with spatial constraints (PCM-S), possibilistic local information c-means (PLICM), and adaptive possibilistic local information c-means (ADPLICM) algorithms, were developed corresponding to the available fuzzy c-means with spatial constraints (FCM-S), fuzzy local information c-means (FLICM), and adaptive fuzzy local information c-means (ADFLICM) algorithms. Experiments were conducted to analyze and compare the FCM and PCM classifier variants for supervised LULC classifications in soft (fuzzy) mode. The quantitative assessment of the soft classification results from fuzzy error matrix (FERM) and root mean square error (RMSE) suggested that the new PCM-based local spatial information classifiers produced higher accuracies than the PCM, FCM, or its local spatial variants, in the presence of untrained classes and noise. The promising results from PCM-based local spatial information classifiers suggest that the PCM algorithm, which is known to be naturally robust to noise, when integrated with local spatial information, has the potential to result in more efficient classifiers capable of better handling ambiguities caused by spectral confusions in landscapes.

作者关键词: fuzzy classification; sub-pixel; fuzzy c-means (FCM); possibilistic c-means (PCM); local spatial information; spatial context; local information; remote sensing; image classification; spectral-spatial; neighborhood

地址: [Madhu, Anjali; Jia, Peng] Wuhan Univ, Int Inst Spatial Lifecourse Epidemiol ISLE, Wuhan 430072, Peoples R China.

[Madhu, Anjali; Kumar, Anil] ISRO, Indian Inst Remote Sensing, 4 Kalidas Rd, Dehra Dun 248001, Uttarakhand, India.

[Madhu, Anjali] Univ Twente, Fac Geoinformat Sci & Earth Observat ITC, NL-7500 AE Enschede, Netherlands.

[Jia, Peng] Wuhan Univ, Sch Resources & Environm Sci, Wuhan 430072, Peoples R China.

通讯作者地址: Jia, P (通讯作者)，Wuhan Univ, Int Inst Spatial Lifecourse Epidemiol ISLE, Wuhan 430072, Peoples R China.

Jia, P (通讯作者)，Wuhan Univ, Sch Resources & Environm Sci, Wuhan 430072, Peoples R China.

影响因子：4.848

标题: The Modified Normalized Urban Area Composite Index: A Satelliate-Derived High-Resolution Index for Extracting Urban Areas

作者: Li, F (Li, Feng); Liu, XY (Liu, Xiaoyang); Liao, SB (Liao, Shunbao); Jia, P (Jia, Peng)

来源出版物: REMOTE SENSING卷: 13期: 12文献号: 2350 DOI: 10.3390/rs13122350出版年: JUN 2021

摘要: The accurate and efficient extraction of urban areas is of great significance for better understanding of urban sprawl, built environment, economic activities, and population distribution. Night-Time Light (NTL) data have been widely used to extract urban areas. However, most of the existing NTL indexes are incapable of identifying non-luminous built-up areas. The high-resolution NTL imagery derived from the Luojia 1-01 satellite, with low saturation and the blooming effect, can be used to map urban areas at a finer scale. A new urban spectral index, named the Modified Normalized Urban Areas Composite Index (MNUACI), improved upon the existing Normalized Urban Areas Composite Index (NUACI), was proposed in this study, which integrated the Human Settlement Index (HSI) generated from Luojia 1-01 NTL data, the Normalized Difference Vegetation Index (NDVI) from Landsat 8 imagery, and the Modified Normalized Difference Water Index (MNDWI). Our results indicated that MNUACI improved the spatial variability and differentiation of urban components by eliminating the NTL blooming effect and increasing the variation of the nighttime luminosity. Compared to urban area classification from Landsat 8 data, the MNUACI yielded better accuracy than NTL, NUACI, HSI, and the EVI-Adjusted NTL Index (EANTLI) alone. Furthermore, the quadratic polynomial regression analysis showed the model based on MNUACI had the best R-2 and Root-Mean Square Error (RMSE) compared with NTL, NUACI, HSI, and EANTLI in terms of estimation of impervious surface area. It is concluded that MNUACI could improve the identification of urban areas and non-luminous built-up areas with better accuracy.

作者关键词: nighttime light; MNUACI; urban area; urban remote sensing

地址: [Li, Feng; Liu, Xiaoyang; Liao, Shunbao] Inst Disaster Prevent, Sch Ecol Environm, Sanhe 065201, Peoples R China.

[Jia, Peng] Wuhan Univ, Sch Resources & Environm Sci, Wuhan 430079, Peoples R China.

[Jia, Peng] Int Inst Spatial Lifecourse Epidemiol ISLE, Hong Kong, Peoples R China.

通讯作者地址: Jia, P (通讯作者)，Wuhan Univ, Sch Resources & Environm Sci, Wuhan 430079, Peoples R China.

Jia, P (通讯作者)，Int Inst Spatial Lifecourse Epidemiol ISLE, Hong Kong, Peoples R China.

电子邮件地址: lifeng@cidp.edu.cn; liuxiaoyang@cidp.edu.cn; liaoshunbao@cidp.edu.cn;jiapengff@hotmail.com

影响因子：4.848