Abstract
The virus COVID-19 is regarded as infectious and has been classified as a pandemic. Each country is taking precautions to lessen the rate of transmission after the virus spread to several countries. So far, a variety of strategies have been employed to combat the infection. Current broad-treatment, such as few limited vaccines are utilized as the main approaches in India, while the efficacy of various medications is yet uncertain. This research involved an exhaustive literature analysis, followed by interaction with healthcare specialists to identify the underlying vulnerabilities with the COVID-19 pandemic outbreak in Indian context. In this chapter, a novel effort was made by combining two ‘multi-criteria decision-making (MCDM)’ methods, such as the ‘Best-Worst Method (BWM) and Step-Wise-Assessment and Ratio-Analysis (SWARA)’ in order to rank the significant variables that contribute to the spread of COVID-19. Initially, considering the existing availability, the main preferences of COVID-19’s vaccines (such as COVISHIELD, COVAXIN, and Sputnik-V) among the Indian community was done by the use of SWARA approach. Further, in order to rank the essential and significant variables that contribute to the spread of COVID-19 and according to how best to prioritize them, the associated significant variables were ranked using the BWM technique, and the associated sub-variables were ranked using the SWARA approach, which took into account the variable’s optimized-weight values when determining the final weight values of the corresponding sub-variables.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abdelwahab, S.F., Issa, U.H., Ashour, H.M.: A novel vaccine selection decision-making model (VSDMM) for COVID-19. Vaccine. 9, 718 (2021). https://doi.org/10.3390/vaccines9070718
Adolph, C., Amano, K., Bang-Jensen, B., Fullman, N., Wilkerson, J.: Pandemic politics: timing state-level social distancing responses to COVID-19. J. Health Polit. Policy Law. 46(2), 211–233 (2021)
Ahmad, T., Khan, M., Haroon, T.H.M., Nasir, S., Hui, J., Bonilla-Aldana, D.K., Rodriguez-Morales, A.J.: COVID-19: zoonotic aspects. Travel Med. Infect. Dis. 36, 101607 (2020)
Ahmadi, M., Sharifi, A., Dorosti, S., Ghoushchi, S.J., Ghanbari, N.: Investigation of effective climatology parameters on COVID-19 outbreak in Iran. Sci. Total Environ. 729, 138705 (2020)
Ahmed, Q.A., Memish, Z.A.: The cancellation of mass gatherings (MGs)? Decision making in the time of COVID-19. Travel Med. Infect. Dis. 34, 101631 (2020)
Alimardani, M., Zolfani, S.H., Aghdaie, M.H., Tamošaitienė, J.: A novel hybrid SWARA and VIKOR methodology for supplier selection in an agile environment. Technol. Econ. Dev. Econ. 19, 533–548 (2013)
Alsalem, M.A., Mohammed, R., Albahri, O.S., Zaidan, A.A., Alamoodi, A.H., Dawood, K., Alnoor, A., Albahri, A.S., Zaidan, B.B., Aickelin, U., Alsattar, H., Alazab, M., Jumaah, F.: Rise of multiattribute decision-making in combating COVID-19: a systematic review of the state-of-the-art literature. Int. J. Intell. Syst. 37, 3514–3624 (2022). https://doi.org/10.1002/int.22699
Anastassopoulou, C., Russo, L., Tsakris, A., Siettos, C.: Databased analysis, modelling and forecasting of the novel coronavirus [2019-nCoV] outbreak. medRxiv. Preprint (2020). Available from: https://doi.org/10.1101/2020.02.11.20022186
Anderson, R.M., Heesterbeek, H., Klinkenberg, D., Hollingsworth, T.D.: How will country-based mitigation measures influence the course of the COVID-19 epidemic? Lancet. 395, 931–934 (2020)
Auler, A.C., Cássaro, F.A.M., da Silva, V.O., Pires, L.F.: Evidence that high temperatures and intermediate relative humidity might favor the spread of COVID-19 in tropical climate: a case study for the most affected Brazilian cities. Sci. Total Environ. 729, 139090 (2020)
Bai, Y., Yao, L., Wei, T., Tian, F., Jin, D.Y., Chen, L., Wang, M.: Presumed asymptomatic carrier transmission of COVID-19. JAMA. 323(14), 1406 (2020)
Bansal, P., Raj, A., Shukla, D.M., Sunder, N.: COVID-19 vaccine preferences in India. Vaccine. 40, 2242–2246 (2022). https://doi.org/10.1016/j.vaccine.2022.02.077
Bashir, M.F., Ma, B., Komal, B., Bashir, M.A., Tan, D., Bashir, M.: Correlation between climate indicators and COVID-19 pandemic in New York, USA. Sci. Total Environ. 728, 138835 (2020)
Bavel, J.J.V., Baicker, K., Boggio, P.S., Capraro, V., Cichocka, A., Cikara, M., Crockett, M.J., Crum, A.J., Douglas, K.M., Druckman, J.N., Drury, J.: Using social and behavioural science to support COVID-19 pandemic response. Nat. Hum. Behav. 4(5), 460–471 (2020)
Berger, L., Berger, N., Bosetti, V., Gilboa, I., Hansen, L.P., Jarvis, C., Marinacci, M., Smith, R.D.: Rational policymaking during a pandemic. Proc. Natl. Acad. Sci. 118(4), e2012704118 (2021). https://doi.org/10.1073/pnas.2012704118
Bokemper, S.E., Huber, G.A., Gerber, A.S., James, E.K., Omer, S.B.: Timing of COVID-19 vaccine approval and endorsement by public figures. Vaccine. 39, 825–829 (2021)
Briscese, G., Lacetera, N., Macis, M., Tonin, M.: Compliance with Covid-19 Social-Distancing Measures in Italy: The Role of Expectations and Duration, vol. 27. National Bureau of Economic Research, Cambridge, MA (2020)
Chakraborty, I., Maity, P.: COVID-19 outbreak: migration, effects on society, global environment and prevention. Sci. Total Environ. 728, 138882 (2020)
Chakraborty, C., Ranjan, A., Bhattacharya, M., Agoramoorthy, G., Lee, S.S.: The current second wave and COVID-19 vaccination status in India. Brain Behav. Immun. 96, 1–4 (2021). https://doi.org/10.1016/j.bbi.2021.05.018
Chan, J.F.-W., Yuan, S., Kok, K.-H., et al.: A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 395(10223), 514–523 (2020)
Chatterji, S.: Covid-19 vaccine diplomacy in India’s outreach plan. Hindustan Times (2020)
Che Mat, N.F., Edinur, H.A., Abdul Razab, M.K.A., Safuan, S.: A single mass gathering resulted in massive transmission of COVID-19 infections in Malaysia with further international spread. J. Travel Med. 27(3), taaa059 (2020)
Chen, J.: Pathogenicity and transmissibility of 2019-nCoV—a quick overview and comparison with other emerging viruses. Microbes Infect. 22(2), 69–71 (2020)
Chen, N., Zhou, M., Dong, X., et al.: Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 395(10223), 507–513 (2020a)
Chen, S., Yang, J., Yang, W., Wang, C., Bärnighausen, T.: COVID-19 control in China during mass population movements at New Year. Lancet. 395(10226), 764–766 (2020b)
Chinazzi, M., Davis, J.T., Ajelli, M., Gioannini, C., Litvinova, M., Merler, S., et al.: The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID- 19) outbreak. Science. 368(6489), 395–400 (2020)
Chowdhury, S.R., et al.: Covid-19 vaccine hesitancy: trends across states, over time (2021). Available at: https://www.ideasforindia.in/topics/human-development/covid-19-vaccine-hesitancy-trends-across-states-over-time.html
Coccia, M.: Factors determining the diffusion of COVID-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID. Sci. Total Environ. 729, 138474 (2020)
Coşkun, H., Yıldırım, N., Gündüz, S.: The spread of COVID-19 virus through population density and wind in Turkey cities. Sci. Total Environ. 751, 141663 (2021)
Danabal, K.G.M., Magesh, S.S., Saravanan, S., Gopichandran, V.: Attitude towards COVID 19 vaccines and vaccine hesitancy in urban and rural communities in Tamil Nadu, India–a community-based survey. BMC Health Serv. Res. 21(1), 1–10 (2021)
de Bruin, Y.B., Lequarre, A.S., McCourt, J., Clevestig, P., Pigazzani, F., Jeddi, M.Z., et al.: Initial impacts of global risk mitigation measures taken during the combating of the COVID-19 pandemic. Saf. Sci. 128, 104773 (2020)
Devakumar, D., Shannon, G., Bhopal, S.S., Abubakar, I.: Racism and discrimination in COVID-19 responses. Lancet. 395(10231), 1194 (2020)
Foy, B.H., Wahl, B., Mehta, K., Shet, A., Menon, G.I., Britto, C.: Comparing COVID-19 vaccine allocation strategies in India: a mathematical modelling study. Int. J. Infect. Dis. 103, 431–438 (2021)
Gao, J., Tian, Z., Yang, X.: Breakthrough: chloroquine phosphate has shown apparent efficacy in treatment of COVID-19 associated pneumonia in clinical studies. Biosci. Trends. 14(1), 72–73 (2020)
Ghernaout, D., Elboughdiri, N.: Urgent proposals for disinfecting hospital wastewaters during COVID-19 pandemic. Open Access Libr. J. 7(5), 1–18 (2020)
Ghosh, A., Roy, S., Mondal, H., Biswas, S., Bose, R.: Mathematical modelling for decision making of lockdown during COVID-19. Appl. Intell. 52, 699–715 (2022). https://doi.org/10.1007/s10489-021-02463-7
Gilardin, L., Bayry, J., Kaveri, S.V.: Intravenous immunoglobulin as clinical immune-modulating therapy. Can. Med. Assoc. J. 187(4), 257–264 (2015)
Gondauri, D., Batiashvili, M.: The study of the effects of mobility trends on the statistical models of the COVID-19 virus spreading. Electron. J. Gen. Med. 17(6), em243 (2020)
Gorbalenya, A.E., Baker, S.C., Baric, R.S., de Groot, R.J., Drosten, C., Gulyaeva, A.A., Haagmans, B.L., Lauber, C., Leontovich, A.M., Neuman, B.W., Penzar, D.: Severe acute respiratory syndrome-related coronavirus: the species and its viruses–a statement of the Coronavirus Study Group. bioRxiv. (2020). https://doi.org/10.1101/2020.02.07.937862
Gössling, S., Scott, D., Hall, C.M.: Pandemics, tourism and global change: a rapid assessment of COVID-19. J. Sustain. Tour. 29(1), 1–20 (2020)
Guo, Z.D., Wang, Z.Y., Zhang, S.F., Li, X., Li, L., Li, C., Cui, Y., Fu, R.B., Dong, Y.Z., Chi, X.Y., Zhang, M.Y.: Aerosol and surface distribution of severe acute respiratory syndrome coronavirus 2 in hospital wards, Wuhan, China, 2020. Emerg. Infect. Dis. 26(7), 1586 (2020)
Gupta, R., Rathore, B., Srivastava, A., Biswas, B.: Decision-making framework for identifying regions vulnerable to transmission of COVID-19 pandemic. Comput. Ind. Eng. 169, 108207 (2022). https://doi.org/10.1016/j.cie.2022.108207
Halilova, J.G., Fynes-Clinton, S., Green, L., Myerson, J., Wu, J., Ruggeri, K., Addis, D.R., Rosenbaum, R.S.: Short-sighted decision-making by those not vaccinated against COVID-19. Sci. Rep. 12, 11906 (2022). https://doi.org/10.1038/s41598-022-15276-6
Hansen, L.P.: Nobel lecture: uncertainty outside and inside economic models. J. Polit. Econ. 122, 945–987 (2014)
Hansen, L.P., Marinacci, M.: Ambiguity aversion and model misspecification: an economic perspective. Stat. Sci. 31, 511–515 (2016)
Harapan, H., Itoh, N., Yufika, A., Winardi, W., Keam, S., Te, H., et al.: Coronavirus disease 2019 (COVID-19): a literature review. J. Infect. Public Health. 13, 667–673 (2020)
He, X., Lau, E.H., Wu, P., Deng, X., Wang, J., Hao, X., Lau, Y.C., Wong, J.Y., Guan, Y., Tan, X., Mo, X.: Temporal dynamics in viral shedding and transmissibility of COVID-19. Nat. Med. 26, 1–4 (2020)
Ho, C.S., Chee, C.Y., Ho, R.C.: Mental health strategies to combat the psychological impact of COVID-19 beyond paranoia and panic. Ann. Acad. Med. Singap. 49(1), 1–3 (2020)
Hossain, M.A.: Is the spread of COVID-19 across countries influenced by environmental, economic and social factors? medRxiv (2020)
Hu, Z., Song, C., Xu, C., Jin, G., Chen, Y., Xu, X., et al.: Clinical characteristics of 24 asymptomatic infections with COVID-19 screened among close contacts in Nanjing, China. Sci. China Life Sci. 63(5), 706–711 (2020)
Islam, A.R.M.T., Hasanuzzaman, M., Shammi, M., Salam, R., Bodrud-Doza, M., Rahman, M.M., et al.: Are meteorological factors enhancing COVID-19 transmission in Bangladesh? Novel findings from a compound Poisson generalized linear modeling approach. Environ. Sci. Pollut. Res. 28(9), 11245–11258 (2021)
Issa, U., Balabel, A., Abdelhakeem, M., Osman, M.: Developing a risk model for assessment and control of the spread of COVID-19. Risks. 9, 38 (2021)
Jadhav, V.R., Aher, J.S., Bhagare, A.M., Dhaygude, A.C.: COVID-19 era: what’s impact of the lockdown on India’s environment? J. Chem. Environ. Sci. Appl. 7(1), 1–6 (2020)
Jaffé, R., Ortiz, M., Jaffé, K.: Globalized low-income countries may experience higher COVID-19 mortality rates. medRxiv (2020)
Jha, S., Goyal, M.K., Gupta, B., Gupta, A.K.: A novel analysis of COVID 19 risk in India incorporating climatic and socioeconomic Factors. Technol. Forecast. Soc. Change. 167, 120679 (2021)
Johnson, E.J., Hariharan, S.: Public health awareness: knowledge, attitude and behaviour of the general public on health risks during the H1N1 influenza pandemic. J. Public Health. 25(3), 333–337 (2017)
Kaushal, J., Mahajan, P.: Asia’s largest urban slum-Dharavi: a global model for management of COVID-19. Cities. 111, 103097 (2021)
Keršuliene, V., Zavadskas, E.K., Turskis, Z.: Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). J. Bus. Econ. Manag. 11, 243–258 (2010)
Khanmohammadi, S., Rezaeiahari, M.: AHP based classification algorithm selection for clinical decision support system development. Procedia Comput. Sci. 36, 328–334 (2014)
Khubchandani, J., Sharma, S., Price, J.H., Wiblishauser, M.J., Sharma, M., Webb, F.J.: COVID-19 vaccination hesitancy in the United States: a rapid national assessment. J. Community Health. 46(2), 270–277 (2021)
Kim, D., Hong, S., Choi, S., Yoon, T.: Analysis of transmission route of MERS coronavirus using decision tree and Apriori algorithm. In: 2016 18th International Conference on Advanced Communication Technology (ICACT), pp. 559–565. IEEE (2016)
Kludge, H.H.P., Jakab, Z., Bartovic, J., D’Anna, V., Severoni, S.: Refugee and migrant health in the COVID-19 response. Lancet. 395(10232), 1237–1239 (2020)
Koo, J.R., Cook, A.R., Park, M., et al.: Interventions to mitigate early spread of SARSCoV-2 in Singapore: a modelling study. Lancet Infect. Dis. 20, 678 (2020). https://doi.org/10.1016/S1473-3099(20)30162-6
Kraemer, M.U., Yang, C.H., Gutierrez, B., Wu, C.H., Klein, B., Pigott, D.M., Open COVID-19 Data Working Group†, Du Plessis, L., Faria, N.R., Li, R., Hanage, W.P.: The effect of human mobility and control measures on the COVID-19 epidemic in China. Science. 368(6490), 493–497 (2020)
Kroumpouzos, G., Gupta, M., Jafferany, M., Lotti, T., Sadoughifar, R., Sitkowska, Z., et al.: COVID-19: a relationship to climate and environmental conditions? Dermatol. Ther. 33(4), e13399 (2020)
Ku, P.K., Holsinger, F.C., Chan, J.Y., Yeung, Z.W., Chan, B.Y., Tong, M.C., Starmer, H.M.: Management of dysphagia in the patient with head and neck cancer during COVID-19 pandemic: practical strategy. Head Neck. 42(7), 1491–1496 (2020)
Kulkarni, H., Khandait, H., Narlawar, U.W., Rathod, P., Mamtani, M.: Independent association of meteorological characteristics with initial spread of Covid-19 in India. Sci. Total Environ. 764, 142801 (2021)
Kumar, A., Roy, R.: Application of mathematical modeling in public health decision making pertaining to control of COVID-19 pandemic in India. Epidemiol. Int. 5(2), 23–26 (2020)
Kwok, K.O., Li, K.-K., Wei, W.I., Tang, A., Wong, S.Y.S., Lee, S.S.: Influenza vaccine uptake, COVID-19 vaccination intention and vaccine hesitancy among nurses: a survey. Int. J. Nurs. Stud. 114, 103854 (2021)
Lakshmi Priyadarshini, S., Suresh, M.: Factors influencing the epidemiological characteristics of pandemic COVID 19: a TISM approach. Int. J. Healthc. Manag. 13(3), 1–10 (2020)
Li, Q., Guan, X., Wu, P., et al.: Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N. Engl. J. Med. 382(13), 1199–1207 (2020)
Lipsitch, M., Swerdlow, D.L., Finelli, L.: Defining the epidemiology of Covid-19—studies needed. N. Engl. J. Med. 382(13), 1194–1196 (2020)
Liu, H.W., Wang, G.J.: Multi-criteria decision-making methods based on intuitionistic fuzzy sets. Eur. J. Oper. Res. 179(1), 220–233 (2007)
Lu, H.: Drug treatment options for the 2019-new coronavirus (2019-nCoV). Biosci. Trends. 14(1), 69–71 (2020)
Marinacci, M.: Model uncertainty. J. Eur. Econ. Assoc. 13, 1022–1100 (2015)
McCloskey, B., Zumla, A., Lim, P.L., Endericks, T., Arbon, P., Cicero, A., et al.: A risk-based approach is best for decision making on holding mass gathering events. Lancet. 395(10232), 1256–1257 (2020)
McPhedran, R., Toombs, B.: Efficacy or delivery? An online Discrete Choice Experiment to explore preferences for COVID-19 vaccines in the UK. Econ. Lett. 200, 109747 (2021)
Mint: For COVID vaccine distribution in India, govt boosting tracking mechanism. Mint (2020a)
Mint: For COVID vaccine delivery, govt to map out cold chain storage facilities. Mint (2020b)
Mishra, D., Satapathy, S.: MCDM approach for mitigation of flooding risks in Odisha (India) based on information retrieval. Int. J. Cognit. Inform. Nat. Intell. 14, 77–91 (2020). https://doi.org/10.4018/IJCINI.2020040105
Mishra, D., Satapathy, S.: SWARA approach for ranking of agricultural supply chain risks of Odisha in India. Int. J. Inf. Decis. Sci. 13, 85–109 (2021)
Mohammad, M., Pratishtha, S., Mohsina, P., Faheem, P., Rajiv, K., Rakesh, P.: Covid-19 vaccines available in India. Comb. Chem. High Throughput Screen. 25(14), 2391 (2022). https://doi.org/10.2174/1386207325666220315115953
Mohanty, K., Das, A.: Coronavirus vaccine: how long before you can get a Covid-19 vaccine? Times of India (2020)
Morgan, O.: How decision makers can use quantitative approaches to guide outbreak responses. Philos. Trans. R. Soc. Lond. B Biol. Sci. 374, 20180365 (2019)
Moriarty, L.F., Plucinski, M.M., Marston, B.J., Kurbatova, E.V., Knust, B., Murray, E.L., Pesik, N., Rose, D., Fitter, D., Kobayashi, M., Toda, M.: Public health responses to COVID-19 outbreaks on cruise ships—worldwide, February–March 2020. Morb. Mortal. Wkly Rep. 69(12), 347 (2020)
Mubarak, N., Zin, C.S.: Religious tourism and mass religious gatherings—the potential link in the spread of COVID-19. Current perspective and future implications. Travel Med. Infect. Dis. 36, 101786 (2020)
Mufsin, P.P., Muhsin, P.P.: Sociocultural and religious factors complicate India’s COVID-19 response. The Diplomat (2020)
Mustafa, S., Balkhy, H., Gabere, M.N.: Current treatment options and the role of peptides as potential therapeutic components for Middle East Respiratory Syndrome (MERS): a review. J. Infect. Public Health. 11(1), 9–17 (2018)
Nicola, M., Alsafi, Z., Sohrabi, C., Kerwan, A., Al-Jabir, A., Iosifidis, C., Agha, M., Agha, R.: The socio-economic implications of the coronavirus pandemic (COVID-19): a review. Int. J. Surg. 78, 185–193 (2020)
Noorimotlagh, Z., Jaafarzadeh, N., Martínez, S.S., Mirzaee, S.A.: A systematic review of possible airborne transmission of the COVID-19 virus (SARS-CoV-2) in the indoor air environment. Environ. Res. 193, 110612 (2020)
Our World in Data: Statistics and research: coronavirus (COVID-19) vaccinations-India (2021). Available at: https://ourworldindata.org/covid-vaccinations?country¼IND
Öztürk, N., Karacan, I., Tozan, H., Vayvay, Ö.: Defining criteria weights by AHP in health technology assessment. Value Health. 20, A698 (2017)
Papageorge, N.W., Zahn, M.V., Belot, M., Van den Broek-Altenburg, E., Choi, S., Jamison, J.C., et al.: Socio-demographic factors associated with self-protecting behavior during the Covid-19 pandemic. J. Popul. Econ. 34(2), 691–738 (2021)
Piguillem, F., Shi, L.: Optimal COVID-19 quarantine and testing policies. Econ. J. 132(647), 2534–2562 (2022)
Pramanik, M., Udmale, P., Bisht, P., Chowdhury, K., Szabo, S., Pal, I.: Climatic factors influence the spread of COVID-19 in Russia. Int. J. Environ. Health Res. 32(4), 723–737 (2022)
Press Information Bureau: Multilateral Cooperation Is the Key to Overcoming Global Challenges Such as COVID-19: Dr. Harsh Vardhan. Press Information Bureau, Government of India (2020)
Qu, G., Li, X., Hu, L., Jiang, G.: An imperative need for research on the role of environmental factors in transmission of novel coronavirus (COVID-19). Environ. Sci. Technol. 54(7), 3730–3732 (2020). https://doi.org/10.1021/acs.est.0c01102
Rezaei, J.: Best-worst multi-criteria decision-making method. Omega. 53, 49–57 (2015)
Rezaei, J.: Best-worst multi-criteria decision-making method: some properties and a linear model. Omega. 64, 126–130 (2016)
Rezaei, J., Nispeling, T., Sarkis, J., Tavasszy, L.: A supplier selection life cycle approach integrating traditional and environmental criteria using the best worst method. J. Clean. Prod. 135, 577–588 (2016)
Roger, F., Delabouglise, A., Roche, B., Peyre, M., Chevalier, V.: Origin of the Covid-19 virus: the trail of mink farming. The Conversation (2021)
Rothe, C., Schunk, M., Sothmann, P., et al.: Transmission of 2019-nCoV infection from an asymptomatic contact in Germany. N. Engl. J. Med. 382(10), 970–971 (2020)
Roy, D., Tripathy, S., Kar, S.K., Sharma, N., Verma, S.K., Kaushal, V.: Study of knowledge, attitude, anxiety & perceived mental healthcare need in Indian population during COVID-19 pandemic. Asian J. Psychiatr. 51, 102083 (2020)
Sallam, M.: COVID-19 vaccine hesitancy worldwide: a concise systematic review of vaccine acceptance rates. Vaccine. 9(2), 160 (2021). https://doi.org/10.3390/vaccines9020160
Schippers, M.C., Rus, D.C.: Optimizing decision-making processes in times of COVID-19: using reflexivity to counteract information-processing failures. Front. Psychol. 12, 650525 (2021). https://doi.org/10.3389/fpsyg.2021.650525
Schoch-Spana, M., Brunson, E.K., Long, R., Ruth, A., Ravi, S.J., Trotochaud, M., Borio, L., Brewer, J., Buccina, J., Connell, N., et al.: The public’s role in COVID-19 vaccination: human-centered recommendations to enhance pandemic vaccine awareness, access, and acceptance in the United States. Vaccine. 39(40), 6004–6012 (2020)
Selcuk, M., Gormus, S., Guven, M.: Impact of weather parameters and population density on the COVID-19 transmission: evidence from 81 provinces of Turkey. Earth Syst. Environ. 5(1), 87–100 (2021)
Setti, L., Passarini, F., De Gennaro, G., Barbieri, P., Perrone, M.G., Miani, A.: Airborne transmission route of COVID-19: why 2 meters/6 feet of inter-personal distance could not be enough. Int. J. Environ. Res. Public Health. 17(8), 2932 (2020). https://doi.org/10.3390/ijerph17082932
Shah, M.: India’s digital divide is hampering its mass Covid-19 vaccination campaign (2021). Available at: https://www.scmp.com/week-asia/health-environment/article/3141180/indias-digital-divide-hampering-its-mass-covid-19
Shao, S., Zhou, D., He, R., Li, J., Zou, S., Mallery, K., et al.: Risk assessment of airborne transmission of COVID-19 by asymptomatic individuals under different practical settings. J. Aerosol Sci. 151, 105661 (2021)
Sheth, J., Prasad, K., Puwar, T.: An objective overview of Covid-19 vaccine situation in India. Natl. J. Community Med. 13(5), 342–345 (2022). https://doi.org/10.55489/njcm.1305202261
Sobel, D., Gn, M., O’Rourke Jr., T.K., Tucci, C., Pareek, G., Golijanin, D., et al.: Personal protective equipment for common urologic procedures before and during the United States COVID-19 pandemic: a single institution study. Urology. 141, 1–6 (2020)
Sohrabi, C., Alsafi, Z., O’neill, N., Khan, M., Kerwan, A., Al-Jabir, A., Iosifidis, C., Agha, R.: World Health Organization declares global emergency: a review of the 2019 novel coronavirus (COVID-19). Int. J. Surg. 76, 71–76 (2020)
Stanujkic, D., Karabasevic, D., Zavadskas, E.K.: A framework for the selection of a packaging design based on the SWARA method. Eng. Econ. 26, 181–187 (2015)
Sungheetha, A.: COVID-19 risk minimization decision making strategy using data-driven model. J. Inf. Technol. Digit. World. 3(1), 57–66 (2021). https://doi.org/10.36548/jitdw.2021.1.006
Tack, J., Schol, J., Geeraerts, A., Huang, I.H., Mori, H., Scarpellini, E., et al.: A survey on the impact of the COVID-19 pandemic on motility and functional investigations in Europe and considerations for recommencing activities in the early recovery phase. Neurogastroenterol. Motil. 32, e13926 (2020)
The Hindu: India approves COVID-19 vaccines Covishield and Covaxin for emergency use. The Hindu (2021)
Thiagarajan, K.: Why is India having a covid-19 surge? BMJ. 373, n1124 (2021). https://doi.org/10.1136/bmj.n1124
Times of India: COVID-19 vaccine India: 8 coronavirus vaccines at various trial stages in India: key details. Times of India (2020)
Umakanthan, S., Patil, S., Subramaniam, N., Sharma, R.: COVID-19 vaccine hesitancy and resistance in India explored through a population-based longitudinal survey. Vaccine. 9(10), 1064 (2021)
Vordos, N., Gkika, D.A., Maliaris, G., Tilkeridis, K.E., Antoniou, A., Bandekas, D.V., et al.: How 3D printing and social media tackles the P.P.E. shortage during Covid-19 pandemic. Saf. Sci. 130, 104870 (2020)
Wang, J., Du, G.: COVID-19 may transmit through aerosol. Ir. J. Med. Sci. (1971-). 189(4), 1143–1144 (2020)
Wang, C., Pan, R., Wan, X., Tan, Y., Xu, L., McIntyre, R.S., et al.: A longitudinal study on the mental health of general population during the COVID-19 epidemic in China. Brain Behav. Immun. 87, 40–48 (2020)
Wells, C.R., Townsend, J.P., Pandey, A., Moghadas, S.M., Krieger, G., Singer, B., et al.: Optimal COVID-19 quarantine and testing strategies. Nat. Commun. 12(1), 1–9 (2021)
WHO: (2020). Retrieved from https://covid19.who.int/ on Nov 26 2022
World Health Organization: Situation updates on March 26, 2020 (2020). https://covid19.who.int/
Xu, S., Li, Y.: Beware of the second wave of Covid-19. Lancet. 395(10233), 1321–1322 (2020)
Yi, Y., Lagniton, P.N.P., Ye, S., Li, E., Xu, R.-H.: COVID-19: what has been learned and to be learned about the novel coronavirus disease. Int. J. Biol. Sci. 16(10), 1753–1766 (2020)
Yichi, L., Wang, B., Peng, R., Zhou, C., Zhan, Y., Liu, Z., Jiang, X., Zhao, B.: Mathematical modeling and epidemic prediction of COVID-19 and its significance to epidemic prevention and control measures. Ann. Infect. Dis. Epidemiol. 5(1), 1–9 (2020)
Yildirim, F.S., Sayan, M., Sanlidag, T., Uzun, B., Ozsahin, D.U., Ozsah, I.: Comparative evaluation of the treatment of COVID-19 with multicriteria decision-making techniques. J. Healthc. Eng. 2021, 1–11, 8864522 (2021). https://doi.org/10.1155/2021/8864522
Zhai, P., Ding, Y., Wu, X., Long, J., Zhong, Y., Li, Y.: The epidemiology, diagnosis and treatment of COVID-19. Int. J. Antimicrob. Agents. 55, 105955 (2020)
Zhong, B.L., Luo, W., Li, H.M., Zhang, Q.Q., Liu, X.G., Li, W.T., et al.: Knowledge, attitudes, and practices towards COVID-19 among Chinese residents during the rapid rise period of the COVID-19 outbreak: a quick online cross-sectional survey. Int. J. Biol. Sci. 16(10), 1745 (2020)
Zolfani, S.H., Bahrami, M.: Investment prioritizing in high tech industries based on SWARA-COPRAS approach. Technol. Econ. Dev. Econ. 20, 534–553 (2014). https://doi.org/10.3846/20294913.2014.881435
Zolfani, S.H., Chatterjee, P.: Comparative evaluation of sustainable design based on step-wise weight assessment ratio analysis (SWARA) and best worst method (BWM) methods: a perspective on household furnishing materials. Symmetry. 11, 74 (2019). https://doi.org/10.3390/sym11010074
Conflict-of-Interest Statement
The authors declare of having no conflict of interest.
Funding Information
There was no funding for this research.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Mishra, D., Lahby, M. (2023). COVID-19 Combating Strategies and Associated Variables for Its Transmission: An Approach with Multi-Criteria Decision-Making Techniques in the Indian Context. In: Hammouch, Z., Lahby, M., Baleanu, D. (eds) Mathematical Modeling and Intelligent Control for Combating Pandemics. Springer Optimization and Its Applications, vol 203. Springer, Cham. https://doi.org/10.1007/978-3-031-33183-1_13
Download citation
DOI: https://doi.org/10.1007/978-3-031-33183-1_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-33182-4
Online ISBN: 978-3-031-33183-1
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)