Diagnostic model for the society safety under COVID-19 pandemic conditions

Journal article


Varotsos, Costas A., Krapivin, Vladimir F. and Xue, Yong 2021. Diagnostic model for the society safety under COVID-19 pandemic conditions. Safety Science. 136, p. 105164. https://doi.org/10.1016/j.ssci.2021.105164
AuthorsVarotsos, Costas A., Krapivin, Vladimir F. and Xue, Yong
Abstract

The aim of this paper is to develop an information-modeling method for assessing and predicting the consequences of the COVID-19 pandemic. To this end, a detailed analysis of official statistical information provided by global and national organizations is carried out. The developed method is based on the algorithm of multi-channel big data processing considering the demographic and socio-economic information. COVID-19 data are analyzed using an instability indicator and a system of differential equations that describe the dynamics of four groups of people: susceptible, infected, recovered and dead. Indicators of the global sustainable development in various sectors are considered to analyze COVID-19 data. Stochastic processes induced by COVID-19 are assessed with the instability indicator showing the level of stability of official data and the reduction of the level of uncertainty. It turns out that the number of deaths is rising with the Human Development Index. It is revealed that COVID-19 divides the global population into three groups according to the relationship between Gross Domestic Product and the number of infected people. The prognosis for the number of infected people in December 2020 and January-February 2021 shows negative events which will decrease slowly.

KeywordsData Science; Covid-19
Year2021
JournalSafety Science
Journal citation136, p. 105164
PublisherElsevier BV
ISSN0925-7535
Digital Object Identifier (DOI)https://doi.org/10.1016/j.ssci.2021.105164
Web address (URL)http://hdl.handle.net/10545/625567
https://www.elsevier.com/tdm/userlicense/1.0/
http://creativecommons.org/licenses/by-nc-nd/4.0/
hdl:10545/625567
Publication dates11 Jan 2021
Publication process dates
Deposited01 Feb 2021, 09:53
Accepted05 Jan 2021
Rights

© 2021 Elsevier Ltd. All rights reserved.

Attribution-NonCommercial-NoDerivatives 4.0 International

ContributorsUniversity of Athens, Greece, Kotelnikov’s Institute of Radioengineering and Electronics, Russian Academy of Sciences, University of Mining and Technology, Xuzhou, China and University of Derby
File
File Access Level
Open
File
File Access Level
Open
File
Permalink -

https://repository.derby.ac.uk/item/9520x/diagnostic-model-for-the-society-safety-under-covid-19-pandemic-conditions

Download files

  • 31
    total views
  • 10
    total downloads
  • 2
    views this month
  • 1
    downloads this month

Export as

Related outputs

An Improved Geographically and Temporally Weighted Regression for Surface Ozone Estimation from Satellite-Based Precursor Data
Wang, X., Xue, Y., Sun, Y., Jin, C. and Wu, S. 2023. An Improved Geographically and Temporally Weighted Regression for Surface Ozone Estimation from Satellite-Based Precursor Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. pp. 1-14. https://doi.org/10.1109/JSTARS.2023.3327881
Studying the Regional Transmission of Air Pollution Based on Spatiotemporal Multivariable Data
Lu, X., Xue, Y., He, B., Jiang, X., Wu, S. and Wang, X. 2023. Studying the Regional Transmission of Air Pollution Based on Spatiotemporal Multivariable Data. Atmosphere. 14 (9), pp. 1-17. https://doi.org/10.3390/atmos14091438
Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization
Jin, Chunlin, Jiang, Xingxing, Sun, Yuxin, Wu, Shuhui and Xue, Yong 2021. Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization. Remote Sensing. 13 (22), p. 4689. https://doi.org/10.3390/rs13224689
Estimation of the PM2.5 and PM10 Mass Concentration over Land from FY-4A Aerosol Optical Depth Data
Xue, Yong 2021. Estimation of the PM2.5 and PM10 Mass Concentration over Land from FY-4A Aerosol Optical Depth Data. Remote Sensing. 13 (21), p. 4276. https://doi.org/10.3390/rs13214276
COVID-19 pandemic decision support system for a population defense strategy and vaccination effectiveness
Varotsos, Costas A, Krapivin, Vladimir F, Xue, Yong, Soldatov, Vladimir and Voronova, Tatiana 2021. COVID-19 pandemic decision support system for a population defense strategy and vaccination effectiveness. Safety Science. 142, p. 105370. https://doi.org/10.1016/j.ssci.2021.105370
Nowcasting of air pollution episodes in megacities: A case study for Athens, Greece
Varotsos, Costas A., Mazei, Yuri, Saldaev, Damir, Efstathiou, Maria, Voronova, Tatiana and Xue, Yong 2021. Nowcasting of air pollution episodes in megacities: A case study for Athens, Greece. Atmospheric Pollution Research. 12 (7), p. 101099. https://doi.org/10.1016/j.apr.2021.101099
Remote sensing evaluation of total suspended solids dynamic with markov model: a case study of inland reservoir across administrative boundary in south China
Zhao, Jing, Zhang, Fujie, Chen, Shuisen, Wang, Chongyang, Chen, Jinyue, Zhou, Hui and Xue, Yong 2020. Remote sensing evaluation of total suspended solids dynamic with markov model: a case study of inland reservoir across administrative boundary in south China. Sensors. 20 (23), p. 6911. https://doi.org/10.3390/s20236911
Polarimetric SAR image semantic segmentation with 3D discrete wavelet transform and Markov random field
Bi, Haixia, Xu, Lin, Cao, Xiangyong, Xue, Yong and Xu, Zongben 2020. Polarimetric SAR image semantic segmentation with 3D discrete wavelet transform and Markov random field. IEEE Transactions on Image Processing. https://doi.org/10.1109/TIP.2020.2992177
Deriving a global and hourly data set of aerosol optical depth over land using data from four geostationary satellites: goes-16, msg-1, msg-4, and himawari-8
Xie, Yanqing, Xue, Yong, Guang, Jie, Mei, Linlu, She, Lu, Li, Ying, Che, Yahui and Fan, Cheng 2019. Deriving a global and hourly data set of aerosol optical depth over land using data from four geostationary satellites: goes-16, msg-1, msg-4, and himawari-8. IEEE Transactions on Geoscience and Remote Sensing. https://doi.org/10.1109/TGRS.2019.2944949
An active deep learning approach for minimally supervised polsar image classification
Xue, Yong 2019. An active deep learning approach for minimally supervised polsar image classification. IEEE Transactions on Geoscience and Remote Sensing. 57 (11), pp. 9378-9395. https://doi.org/10.1109/TGRS.2019.2926434
A Heterogeneous and Interactive Big Earth Data Framework
Bi, H., Xue, Y., Merritt, P., Windmill, C. and Davis, B. 2019. A Heterogeneous and Interactive Big Earth Data Framework. 2019 International Conference on Big Data Engineering. IEEE. https://doi.org/10.1145/3341620.3341628
Big earth data: a comprehensive analysis of visualization analytics issues
Merritt, Patrick, Bi, Haixia, Davis, Bradley, Windmill, Christopher and Xue, Yong 2019. Big earth data: a comprehensive analysis of visualization analytics issues. Big Earth Data. 2 (4), pp. 321-350. https://doi.org/10.1080/20964471.2019.1576260
High Performance Time Series Quantitative Retrieval from Satellite Images on a GPU Cluster
Liu, J., Xue, Y., Ren, K., Song, J., Windmill, C. and Merritt, P. 2019. High Performance Time Series Quantitative Retrieval from Satellite Images on a GPU Cluster. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 12 (8). https://doi.org/10.1109/JSTARS.2019.2920077
Joint retrieval of aerosol optical depth and surface reflectance over land using geostationary satellite data.
She, Lu, Xue, Yong, Yang, Xihua, Leys, John, Guang, Jie, Che, Yahui, Fan, Cheng, Xie, Yanqing and Li, Ying 2018. Joint retrieval of aerosol optical depth and surface reflectance over land using geostationary satellite data. IEEE Transactions on Geoscience and Remote Sensing. https://doi.org/10.1109/TGRS.2018.2867000
Evaluation of the AVHRR DeepBlue aerosol optical depth dataset over mainland China.
Che, Yahui, Xue, Yong, Guang, Jie, She, Lu and Guo, Jianping 2018. Evaluation of the AVHRR DeepBlue aerosol optical depth dataset over mainland China. ISPRS Journal of Photogrammetry and Remote Sensing. https://doi.org/10.1016/j.isprsjprs.2018.09.004
A physically based PM 2.5 estimation method using AERONET data in Beijing Area
Chen, Guili, Guang, Jie, Xue, Yong, Li, Ying, Che, Yahui and Gong, Shaoqi 2018. A physically based PM 2.5 estimation method using AERONET data in Beijing Area. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. https://doi.org/10.1109/JSTARS.2018.2817243
Dust detection and intensity estimation using Himawari-8/AHI observation.
She, Lu, Xue, Yong, Yang, Xihua, Guang, Jie, Li, Ying, Che, Yahui, Fan, Cheng and Xie, Yanqing 2018. Dust detection and intensity estimation using Himawari-8/AHI observation. Remote Sensing. https://doi.org/10.3390/rs10040490
SAHARA: A Simplified AtmospHeric Correction AlgoRithm for Chinese gAofen Data: 1. Aerosol Algorithm.
She, Lu, Mei, Linlu, Xue, Yong, Che, Yahui and Guang, Jie 2017. SAHARA: A Simplified AtmospHeric Correction AlgoRithm for Chinese gAofen Data: 1. Aerosol Algorithm. Remote Sensing. https://doi.org/10.3390/rs9030253
Validation of aerosol products from AATSR and MERIS/AATSR synergy algorithms—Part 1: Global Evaluation.
Che, Yahui, Mei, Linlu, Xue, Yong, Guang, Jie, She, Lu and Li, Ying 2018. Validation of aerosol products from AATSR and MERIS/AATSR synergy algorithms—Part 1: Global Evaluation. Remote Sensing. https://doi.org/10.3390/rs10091414
Improved aerosol optical depth and ångstrom exponent retrieval over land From MODIS based on the non-lambertian forward model
Leiku, Yang, Xue, Yong, Guang, Jie, Hassan, Kazemian, Zhang, Jiahua and Li, Chi 2014. Improved aerosol optical depth and ångstrom exponent retrieval over land From MODIS based on the non-lambertian forward model. IEEE Geoscience and Remote Sensing Letters. https://doi.org/10.1109/LGRS.2014.2303317
Using SeaWiFS measurements to evaluate radiometric stability of pseudo-invariant calibration sites at top of atmosphere
Li, Chi, Xue, Yong, Liu, Quanhua, Ouazzane, Karim and Zhang, Jiahua 2014. Using SeaWiFS measurements to evaluate radiometric stability of pseudo-invariant calibration sites at top of atmosphere. IEEE Geoscience and Remote Sensing Letters. https://doi.org/10.1109/LGRS.2014.2329138
Ensemble of ESA/AATSR aerosol optical depth products based on the likelihood estimate method with uncertainties
Xie, Yanqing, Xue, Yong, Che, Yahui, Guang, Jie, Mei, Linlu, Voorhis, Dave, Fan, Cheng, She, Lu and Xu, Hui 2017. Ensemble of ESA/AATSR aerosol optical depth products based on the likelihood estimate method with uncertainties. IEEE Transactions on Geoscience and Remote Sensing. https://doi.org/10.1109/TGRS.2017.2757910
Long-time series aerosol optical depth retrieval from AVHRR data over land in North China and Central Europe
Xue, Yong, He, Xingwei, de Leeuw, Gerrit, Mei, Linlu, Che, Yahui, Rippin, Wayne, Guang, Jie and Hu, Yincui 2017. Long-time series aerosol optical depth retrieval from AVHRR data over land in North China and Central Europe. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2017.06.036
Multicore processors and graphics processing unit accelerators for parallel retrieval of aerosol optical depth from satellite data: Implementation, performance, and energy efficiency
Liu, Jia, Feld, Dustin, Xue, Yong, Garcke, Jochen and Soddemann, Thomas 2015. Multicore processors and graphics processing unit accelerators for parallel retrieval of aerosol optical depth from satellite data: Implementation, performance, and energy efficiency. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. https://doi.org/10.1109/JSTARS.2015.2438893
High-throughput geocomputational workflows in a grid environment
Liu, Jia, Xue, Yong, Palmer-Brown, Dominic, Chen, Ziqiang and He, Xingwei 2015. High-throughput geocomputational workflows in a grid environment. Computer. https://doi.org/10.1109/MC.2015.331
An efficient geosciences workflow on multi-core processors and GPUs: a case study for aerosol optical depth retrieval from MODIS satellite data
Liu, Jia, Feld, Dustin, Xue, Yong, Garcke, Jochen, Soddemann, Thomas, Pan, Peiyuan and Fraunhofer Institute of Algorhithms and Scientific Computing 2016. An efficient geosciences workflow on multi-core processors and GPUs: a case study for aerosol optical depth retrieval from MODIS satellite data. International Journal of Digital Earth. https://doi.org/10.1080/17538947.2015.1130087
Technical note: Intercomparison of three AATSR Level 2 (L2) AOD products over China
Che, Yahui, Xue, Yong, Mei, Linlu, Guang, Jie, She, Lu, Guo, Jianping, Hu, Yincui, Xu, Hui, He, Xingwei, Di, Aojie and Fan, Cheng 2016. Technical note: Intercomparison of three AATSR Level 2 (L2) AOD products over China. Atmospheric Chemistry and Physics. https://doi.org/10.5194/acp-16-9655-2016
Dust aerosol optical depth retrieval and dust storm detection for Xinjiang Region using Indian National Satellite Observations
Di, Aojie, Xue, Yong, Yang, Xihua, Leys, John, Guang, Jie, Mei, Linlu, Wang, Jingli, She, Lu, Hu, Yincui, He, Xingwei, Che, Yahui and Fan, Cheng 2016. Dust aerosol optical depth retrieval and dust storm detection for Xinjiang Region using Indian National Satellite Observations. Remote Sensing. https://doi.org/10.3390/rs8090702
Grid workflow validation using ontology-based tacit knowledge: A case study for quantitative remote sensing applications
Liu, Jia, Liu, Longli, Xue, Yong, Dong, Jing, Hu, Yincui, Hill, Richard, Guang, Jie and Li, Chi 2016. Grid workflow validation using ontology-based tacit knowledge: A case study for quantitative remote sensing applications. Computers & Geosciences. https://doi.org/10.1016/j.cageo.2016.10.002