[1]
|
A. Remuzzi, G. Remuzzi, COVID-19 and Italy: What next? Lancet, 395 (2020), 1225-1228. https://doi.org/10.1016/S0140-6736(20)30627-9 doi: 10.1016/S0140-6736(20)30627-9
|
[2]
|
World Health Organization, WHO Director General's Statement on IHR Emergency Committee on Novel Coronavirus (2019-nCoV), 2021. Available from: https://www.sunupauto.com/114755.html.
|
[3]
|
World Health Organization, Coronavirus Disease (COVID-19) Dashboard, 2021. Available from: https://covid19.who.int.
|
[4]
|
A. Barnawi, P. Chhikara, R. Tekchandani, N. Kumar, B. Alzahrani, Artificial intelligence-enabled Internet of Things-based system for COVID-19 screening using aerial thermal imaging, Future Gener. Comput. Syst., 124 (2021), 119-132. https://doi.org/10.1016/j.future.2021.05.019 doi: 10.1016/j.future.2021.05.019
|
[5]
|
K. K. Lella, P. J. A. Alphonse, A literature review on COVID-19 disease diagnosis from respiratory sound data, AIMS Bioeng., 8 (2021), 140-153. https://doi.org/10.3934/bioeng.2021013 doi: 10.3934/bioeng.2021013
|
[6]
|
K. K. Lella, P. J. A. Alphonse, Automatic COVID-19 disease diagnosis using 1D convolutional neural network and augmentation with human respiratory sound based on parameters: Cough, breath, and voice, AIMS Public Health, 8 (2021), 240-264. https://doi.org/10.3934/publichealth.2021019 doi: 10.3934/publichealth.2021019
|
[7]
|
K. K. Lella, P. J. A. Alphonse, Automatic diagnosis of COVID-19 disease using deep convolutional neural network with multi-feature channel from respiratory sound data: Cough, voice, and breath, Alexandria Eng. J., 61 (2021), 1110-0168, https://doi.org/10.1016/j.aej.2021.06.024 doi: 10.1016/j.aej.2021.06.024
|
[8]
|
K. K. Lella, P. J. A. Alphonse, COVID-19 disease diagnosis with light-weight CNN using modified MFCC and enhanced GFCC from human respiratory sounds, Eur. Phys. J. Spec. Top., (2022), 1-18. https://doi.org/10.1140/epjs/s11734-022-00432-w doi: 10.1140/epjs/s11734-022-00432-w
|
[9]
|
A. K. Thakur, R. Sathyamurthy, R. Velraj, I. Lynch, R. Saidur, A. K. Pandey, et al., Secondary transmission of SARS-Cov-2 through wastewater: Concerns and tactics for treatment to effectively control the pandemic, J. Environ. Manage., 290 (2021), 112668. https://doi.org/10.1016/j.jenvman.2021.112668 doi: 10.1016/j.jenvman.2021.112668
|
[10]
|
J. Paananen, J. Rannikko, M. Harju, J. Pirhonen, The impact of Covid-19-related distancing on the well-being of nursing home residents and their family members: A qualitative study, Int. J. Nurs. Stud. Adv., 3 (2021), 100031. https://doi.org/10.1016/j.ijnsa.2021.100031 doi: 10.1016/j.ijnsa.2021.100031
|
[11]
|
C. Betsch, L. Korn, L. Felgendreff, S. Eitze, H. Thaiss, School opening during the SARS-CoV-2 pandemic: Public acceptance of wearing fabric masks in class, Public Health Pract., 2 (2021), 100115. https://doi.org/10.1016/j.puhip.2021.100115 doi: 10.1016/j.puhip.2021.100115
|
[12]
|
M. Shen, Z. Zeng, B. Song, H. Yi, T. Hu, Y. Zhang, et al., Neglected microplastics pollution in global COVID-19: Disposable surgical masks, Sci. Total Environ., 790 (2021), 148130. https://doi.org/10.1016/j.scitotenv.2021.148130 doi: 10.1016/j.scitotenv.2021.148130
|
[13]
|
U. A. Eke, A. C. Eke, Personal protective equipment in the siege of respiratory viral pandemics: strides made and next steps, Expert Rev. Respir. Med., 15 (2020), 441-452. https://doi.org/10.1080/17476348.2021.1865812 doi: 10.1080/17476348.2021.1865812
|
[14]
|
Y. Jiang, Y. Li, Y. Zhao, Mask dilemma and innovation for production and operation mode of public health products, Sci. Res. Manage., 41 (2020), 37-46.
|
[15]
|
G. Chua, K. Yuen, X. Wang, Y. Wong, The determinants of panic buying during COVID-19, Int. J. Environ. Res. Public Health , 18 (2021), 3247. https://doi.org/10.3390/ijerph18063247 doi: 10.3390/ijerph18063247
|
[16]
|
G. Tirkes, C. Guray, N. Celebi, Demand forecasting: A comparison between the Holt-Winters, trend analysis and decomposition models, Teh. Vjesn., 24 (2017), 503-509. https://doi.org/10.17559/TV-20160615204011 doi: 10.17559/TV-20160615204011
|
[17]
|
H. Yang, H. Jing, Forecasting of fresh agricultural products demand based on the ARIMA model, Guangdong Agric. Sci., 5 (2013), 855-858. https://doi.org/10.16768/j.issn.1004-874x.2013.11.001 doi: 10.16768/j.issn.1004-874x.2013.11.001
|
[18]
|
K. K. Chandriah, R. V. Naraganahalli, RNN/LSTM with modified Adam optimizer in deep learning approach for automobile spare parts demand forecasting, Multimedia Tools Appl., 80 (2021), 26145-26159. https://doi.org/10.1007/s11042-021-10913-0 doi: 10.1007/s11042-021-10913-0
|
[19]
|
L. Si, Y. Wang, G. Xu, Logistics demand forecasting based on improved grey model, Comput. Simul., 29 (2012), 192-194,213.
|
[20]
|
X. Xu, Y. Qi, Z. Hua, Forecasting demand of commodities after natural disasters, Expert Syst. Appl., 37 (2010), 4313-4317. https://doi.org/10.1016/j.eswa.2009.11.069 doi: 10.1016/j.eswa.2009.11.069
|
[21]
|
E. Shin, J. E. Lee, What makes consumers purchase apparel products through social shopping services that social media fashion influencers have worn, J. Bus. Res., 132 (2021), 416-428. https://doi.org/10.1016/j.jbusres.2021.04.022 doi: 10.1016/j.jbusres.2021.04.022
|
[22]
|
A. S. Al-Adwan, G. Sammour, What makes consumers purchase mobile apps: Evidence from Jordan, J. Theor. Appl. Electron. Comm., 16 (2020), 562-583. https://doi.org/10.3390/jtaer16030034 doi: 10.3390/jtaer16030034
|
[23]
|
C. Li, Y. Wang, H. Qu, Study on spatial and temporal characteristics of textile intangible cultural heritage and its communication strategy: An empirical analysis based on Baidu index, J. Silk, 58 (2021), 52-58.
|
[24]
|
J. Wei, W. Zhan, X. Guo, D. Marinova, Public attention to the great smog event: A case study of the 2013 smog event in Harbin, China, Nat. Hazards, 89 (2017), 923-938. https://doi.org/10.1007/s11069-017-3000-6 doi: 10.1007/s11069-017-3000-6
|
[25]
|
X. Gong, Y. Han, M. Hou, R. Guo, Online public attention during the early days of the COVID-19 pandemic: Infoveillance study based on Baidu index, JMIR Public Health Surveill., 6 (2020), 225-237. https://doi.org/10.2196/23098 doi: 10.2196/23098
|
[26]
|
Q. Feng, H. Wei, J. Hu, F. Li, P. Lv, P. Wu, Analysis of the attention to COVID-19 epidemic based on visibility graph network, Mod. Phys. Lett. B, 35 (2021), 2150316. https://doi.org/10.1142/S0217984921503164 doi: 10.1142/S0217984921503164
|
[27]
|
C. Zhang, X. Ma, Y. Zhou, R. Guo, Analysis of public opinion evolution in COVID-19 pandemic from a perspective of sentiment variation, J. Geo-Inf. Sci., 23 (2021), 341-350.
|
[28]
|
K. Hou, T. Hou, L. Cai, Public attention about COVID-19 on social media: An investigation based on data mining and text analysis, Pers. Individ. Differ., 175 (2021), 110701. https://doi.org/10.1016/j.paid.2021.110701 doi: 10.1016/j.paid.2021.110701
|
[29]
|
Y. Zhao, S. Cheng, X. Yu, H. L. Xu, Chinese public's attention to the COVID-19 epidemic on social media: Observational descriptive study, J. Med. Internet Res., 22 (2020), e18825. http://preprints.jmir.org/preprint/18825
|
[30]
|
T. L. Phan, C. T. S. Ching, A reusable mask for coronavirus disease 2019 (COVID-19), Arch. Med. Res., 51 (2020), 455-457. https://doi.org/10.1016/j.arcmed.2020.04.001 doi: 10.1016/j.arcmed.2020.04.001
|
[31]
|
H. Wu, J. Huang, C. Zhang, Z. L. He, W. K. Ming, Facemask shortage and the novel coronavirus disease (COVID-19) outbreak: Reflections on public health measures, E Clin. Med., 21 (2020), 100329. https://doi.org/10.1016/j.eclinm.2020.100329 doi: 10.1016/j.eclinm.2020.100329
|
[32]
|
C. E. Rodriguez-Martinez, M. P. Sossa-Briceo, J. A. Cortes, Decontamination and reuse of N95 filtering facemask respirators: A systematic review of the literature, Am. J. Infect. Control, 48 (2020), 1520-1532. https://doi.org/10.1016/j.ajic.2020.07.004 doi: 10.1016/j.ajic.2020.07.004
|
[33]
|
Y. Tao, F. You, Can decontamination and reuse of N95 respirators during COVID-19 pandemic provide energy, environmental, and economic benefits? Appl. Energy, 304 (2021), 117848. https://doi.org/10.1016/j.apenergy.2021.117848 doi: 10.1016/j.apenergy.2021.117848
|
[34]
|
E. Deniz, S. Sibar, O. Kilic, S. Ayhan, Comparison of effectiveness of four facial masks used during the COVID-19 pandemic using indocyanine green and fluorescent angiography device: A plastic surgeon perspective, Turk. J. Plast. Surg., 29 (2021), 166-171. https://doi.org/10.4103/tjps.tjps_105_20 doi: 10.4103/tjps.tjps_105_20
|
[35]
|
L. Wang, X. Zhao, J. Zhang, W. Ma, H. Zhao, Rational selection and application of medical masks, Chin. J. Nosocomiol., 21 (2011), 3908-3909.
|
[36]
|
R. K. Goel, S. Haruna, Unmasking the demand for masks: Analytics of mandating coronavirus masks, Metroeconomica, 72 (2021), 580-591. https://doi.org/10.1111/meca.12334 doi: 10.1111/meca.12334
|
[37]
|
T. Zhang, Q. Wang, W. Shi, T. Sheng, J. X. Liu, J. J. Zhao, et al., Achieving universal wearing of face masks during the COVID-19 pandemic: A practical solution from Shanghai, China, Risk Manage. Healthcare Policy, 13 (2020), 3067-3077. https://doi.org/10.2147/RMHP.S280672 doi: 10.2147/RMHP.S280672
|
[38]
|
F. J. Siyal, Z. A. Shaikh, S. Z. Ahmed, M. A. Shahid, F. Agha, M. Khoso, et al., Anxiety among COVID-19 physicians during the pandemic in the health care center of the rural region, Arch. Pharm. Pract., 11 (2020), 91-93.
|
[39]
|
E. M. Kleiman, A. L. Yeager, J. L. Grove, J. K. Kellerman, J. S. Kim, Real-time mental health impact of the COVID-19 pandemic on college students: Ecological momentary assessment study, JMIR Mental Health, 7 (2020), e24815. https://doi.org/10.2196/24815 doi: 10.2196/24815
|
[40]
|
Y. P. Hsieh, C. Yen, C. Wu, P. Wang, Nonattendance at scheduled appointments in outpatient clinics due to COVID-19 and related factors in Taiwan: A health belief model approach, Int. J. Environ. Res. Public Health, 18 (2021), 4445. https://doi.org/10.3390/ijerph18094445 doi: 10.3390/ijerph18094445
|
[41]
|
C. Zhou, X. Yue, X. Zhang, F. Shangguan, X. Zhang, Self-efficacy and mental health problems during COVID-19 pandemic: A multiple mediation model based on health belief model, Pers. Individ. Differ., 179 (2021), 110893. https://doi.org/10.1016/j.paid.2021.110893 doi: 10.1016/j.paid.2021.110893
|
[42]
|
M. Aval, A. Ansari-Moghadam, G. Masoudy, Educational intervention based on health belief model on the adoption of preventive behaviors of Crimean-Congo hemorrhagic fever in ranchers, Health Scope, 8 (2019), e14112. https://doi.org/10.5812/jhealthscope.14112 doi: 10.5812/jhealthscope.14112
|
[43]
|
L. E. Bechard, M. Bergelt, B. Neudorf, T. C. DeSouza, L. E. Middleton, Using the health belief model to understand age differences in perceptions and responses to the COVID-19 pandemic, Front. Psychol., 12 (2021), 609893. https://doi.org/10.3389/fpsyg.2021.609893 doi: 10.3389/fpsyg.2021.609893
|
[44]
|
A. B. Coe, M. H. Elliott, S. B. S. Gatewood, J. R. Goode, L. R. Moczygemba, Perceptions and predictors of intention to receive the COVID-19 vaccine, Res. Soc. Adm. Pharm., 18 (2021), 2593-2599. https://doi.org/10.1016/j.sapharm.2021.04.023 doi: 10.1016/j.sapharm.2021.04.023
|
[45]
|
A. R. Mercadante, A. V. Law, Will they, or won't they? Examining patients' vaccine intention for flu and COVID-19 using the health belief model, Res. Soc. Adm. Pharm., 17 (2020), 1596-1605. https://doi.org/10.1016/j.sapharm.2020.12.012 doi: 10.1016/j.sapharm.2020.12.012
|
[46]
|
S. G. Tan, A. S. Raamkumar, H. L. Wee, Users' beliefs toward physical distancing in Facebook pages of public health authorities during COVID-19 pandemic in early 2020, Health Educ. Behav., 48 (2021), 404-411. https://doi.org/10.1177/10901981211014428 doi: 10.1177/10901981211014428
|
[47]
|
N. Li, Z. Tang, Cognition and demand for health education of rural residents for public health emergencies and common infectious diseases, J. Catastrophology, 35 (2020), 33-37.
|
[48]
|
J. Cao, X. Yang, S. Wang, Key scientific problems in public emergency management, J. Public Manage., 4 (2007), 84-93.
|
[49]
|
J. Dono, K. Ettridge, M. Wakefield, S. Pettigrew, J. Coveney, D. Roder, et al., Intentions to reduce sugar-sweetened beverage consumption: The importance of perceived susceptibility to health risks, Public Health Nutr., 24 (2021), 5663-5672. https://doi.org/10.1017/S1368980021000239 doi: 10.1017/S1368980021000239
|
[50]
|
J. Joo, Exploration of structural relations on health behavior related to particulate matter: Focused on multi-dimensional health locus of control, perceived susceptibility and severity, and health behavioral intention, J. Korea Convergence Soc., 8 (2017), 413-421. https://doi.org/10.15207/JKCS.2017.8.11.413 doi: 10.15207/JKCS.2017.8.11.413
|
[51]
|
A. Almehmadi, COVID-19 pandemic data predict the stock market, Comput. Syst. Sci. Eng., 36 (2021), 451-460. https://doi.org/10.32604/csse.2021.015309 doi: 10.32604/csse.2021.015309
|
[52]
|
M. Wang, L. Huang, X. Liang, B. Li, Consumer knowledge, risk perception and food-handling behaviors—A national survey in China, Food Control, 122 (2021), 107789. https://doi.org/10.1016/j.foodcont.2020.107789 doi: 10.1016/j.foodcont.2020.107789
|
[53]
|
J. L. Marle, F. Parmentier, F. Vinchon, M. Torme, X. Borteyrou, T. Lubart, Evolution and impact of self-efficacy during French COVID-19 confinement: A longitudinal study, J. Gen. Physiol., 148 (2021), 360-381. https://doi.org/10.1080/00221309.2021.1904815 doi: 10.1080/00221309.2021.1904815
|
[54]
|
H. T. Duong, H. T. Nguyen, S. J. Mcfarlane, L. T. V. Nguyen, Risk perception and COVID-19 preventive behaviors: Application of the integrative model of behavioral prediction, Soc. Sci. J., (2021), 1-14. https://doi.org/10.1080/03623319.2021.1874176 doi: 10.1080/03623319.2021.1874176
|
[55]
|
M. Morishima, K. Kishida, M. Fukagawa, Investigating facemask problems associated with wearing comfort and fit, Int. J. Clothing Sci. Technol., (2021). https://doi.org/10.1108/IJCST-05-2020-0067 doi: 10.1108/IJCST-05-2020-0067
|
[56]
|
Y. Lin, C. Chen, Thermoregulation and thermal sensation in response to wearing tight-fitting respirators and exercising in hot-and-humid indoor environment, Build. Environ., 160 (2019), 106158. https://doi.org/10.1016/j.buildenv.2019.05.036 doi: 10.1016/j.buildenv.2019.05.036
|
[57]
|
A. A. Sadore, D. W. Handiso, T. E. Wontamo, D. E. Mekango, S. Moges, Influence of social media use on practice of Covid-19 preventive measures among Ethiopian residents: An online cross-sectional study, Disaster Med. Public, (2021), 1-6. https://doi.org/10.1017/dmp.2021.184 doi: 10.1017/dmp.2021.184
|
[58]
|
E. Kendal, Public health crises in popular media: How viral outbreak films affect the public's health literacy, Med. Humanit., 47 (2019), 11-19. https://10.1136/medhum-2018-011446
|
[59]
|
Y. Ye, R. Wang, D. Feng, R. J. Wu, Z. F. Li, C. X. Long, et al., The recommended and excessive preventive behaviors during the COVID-19 pandemic: A community-based online survey in China, Int. J. Environ. Res. Public Health, 17 (2020), 6953. https://doi.org/10.3390/ijerph17196953 doi: 10.3390/ijerph17196953
|
[60]
|
Z. Liu, T. Huynh, P. Dai, The impact of COVID-19 on the stock market crash risk in China, Res. Int. Bus. Finance, 57 (2021), 101419. https://doi.org/10.1016/j.ribaf.2021.101419 doi: 10.1016/j.ribaf.2021.101419
|
[61]
|
X. Zhu, C. Xia, Visual network analysis of the Baidu-index data on greenhouse gas, Int. J. Mod. Phys. B, 35 (2021), 2150115. https://doi.org/10.1142/S0217979221501150 doi: 10.1142/S0217979221501150
|
[62]
|
Y. Yuan, X. Wang, Exploring the effectiveness of location-based social media in modeling user activity space: A case study of Weibo, Trans. GIS., 22 (2018), 930-957. https://doi.org/10.1111/tgis.12450 doi: 10.1111/tgis.12450
|
[63]
|
T. Kawada, Indices of insulin sensitivity and resistance: Adequate logarithmic transformation is needed to keep mathematical equivalence, Early Hum. Dev., 89 (2013), 515. https://doi.org/10.1016/j.earlhumdev.2013.03.010 doi: 10.1016/j.earlhumdev.2013.03.010
|
[64]
|
R. Zhang, J. Liu, L. Zhang, J. D. Lin, Q. Q. Wu, The distorted power of medical surgical masks for changing the human thermal psychology of indoor personnel in summer, Indoor Air, 31 (2021), 1645-1656. https://doi.org/10.1111/ina.12830 doi: 10.1111/ina.12830
|
[65]
|
R. Johnston, K. Jones, D. Manley, Confounding and collinearity in regression analysis: A cautionary tale and an alternative procedure, illustrated by studies of British voting behaviour, Qual. Quant., 52 (2018), 1957-1976. https://doi.org/10.1007/s11135-017-0584-6 doi: 10.1007/s11135-017-0584-6
|
[66]
|
T. J. Wang, H. J. Wang, Y. J. Zeng, X. Q. Cai, L. D. Xie, Health beliefs associated with preventive behaviors against non-communicable diseases, Patient Educ. Couns., 105 (2022), 173-181. https://doi.org/10.1016/j.pec.2021.05.024 doi: 10.1016/j.pec.2021.05.024
|