In this article, we aim to compare the socioeconomic development (SED) of the countries listed in G7 (representing developed nations) and BRICS (Brazil, Russia, India, China and South Africa—developing countries). Further, we intend to delve into the nexus between the SED of a country and its resilience to the current pandemic, COVID-19. The initial apprehension is that a country with better SED can show better resilience. To test this assumption, we consider seven socioeconomic indicators representing income, employment status, educational level, health condition, government expenditures in essential areas, like health, research and development, and gender equality and apply a compromise solution–based multi-criteria decision analysis (MCDA) framework. Next, we consider three parameters, namely infected cases (IC), recovery rate (RR), and death rate (DR), as explanatory proxy variables to indicate the resilience of the countries to COVID-19 spread. Finally, we examine the association between the SED and resilience of the countries. The results show that the SED of a country does not lead to better resilience to COVID-19.
AbdullaF., NainZ., KarimuzzamanM., HossainM. M., AdhikariU. K., & RahmanA. (2020). Effect of preventive actions and health care factors in controlling the outbreaks of COVID-19 pandemic. medRxiv. https://doi.org/10.1101/2020.05.09.20096255.
2.
AbidinM. Z., RusliR., & ShariffA. M. (2016). Technique for Order Performance by Similarity to Ideal Solution (TOPSIS)-entropy methodology for inherent safety design decision making tool. Procedia Engineering, 148, 1043–1050.
3.
AhluwaliaM., & CheneryH. (1974). The economic framework. In M. S. Ahluwalia, C. L. G. Bell, H. Chenery, J. H. Duloy, & R. Jolly (Eds.), Redistribution with growth (pp. 38–50). Oxford University Press.
4.
BakerD. P., LeonJ., Smith GreenawayE. G., CollinsJ., & MovitM. (2011). The education effect on population health: A reassessment. Population and Development Review, 37(2), 307–332.
5.
BezruchkaS. (2009). The effect of economic recession on population health. Canadian Medical Association Journal, 181(5), 281–285.
6.
BharatiI., KumarP., & SelvaraiS. (2020). How well is India responding to COVID-19?Brookings. https://www.brookings.edu.
7.
BiswasS., BandyopadhyayG., GuhaB., & BhattacharjeeM. (2019). An ensemble approach for portfolio selection in a multi-criteria decision making framework. Decision Making: Applications in Management and Engineering, 2(2), 138–158.
8.
BuhejiM. (2020). Stopping future COVID-19 like pandemics from the source-a socio-economic perspective. American Journal of Economics, 10(3), 115–125. https://doi.org/10.5923/j.economics.20201003.01.
9.
BungeM. (1981). Development indicators. Social Indicators Research, 9(3), 369–385. https://doi.org/10.1007/BF00300662.
10.
ChandlerD. (2014). Resilience: The governance of complexity. Routledge.
11.
CvetkovićV. M., NikolićN., NenadićU. R., ÖcalA., NojiE. K., & ZečevićM. (2020). Preparedness and preventive behaviors for a pandemic disaster caused by COVID-19 in Serbia. International Journal of Environmental Research and Public Health, 17(11), 4124. https://doi.org/10.3390/ijerph17114124.
12.
DespotisD. K. (2005). A reassessment of the human development index via data envelopment analysis. Journal of the Operational Research Society, 56(8), 969–980. https://doi.org/10.1057/palgrave.jors.2601927.
13.
DijkstraA. G., & HanmerL. C. (2000). Measuring socio-economic gender inequality: Toward an alternative to the UNDP gender-related development index. Feminist Economics, 6(2), 41–75. https://doi.org/10.1080/13545700050076106.
14.
DrewnowskiJ. (1974). On measuring and planning the quality of life (Vol. 11). De Gruyter Mouton.
15.
FollandS. (2007). Does “community social capital” contribute to population health?Social Science and Medicine, 64(11), 2342–2354.
16.
GalobardesB., LynchJ. W., & SmithG. D. (2004). Childhood socioeconomic circumstances and cause-specific mortality in adulthood: Systematic review and interpretation. Epidemiologic Reviews, 26(1), 7–21. https://doi.org/10.1093/epirev/mxh008.
17.
GangemiS., BilleciL., & TonacciA. (2020). Rich at risk: Socio-economic drivers of COVID-19 pandemic spread. Clinical and Molecular Allergy, 18(1), 1–3. https://doi.org/10.1186/s12948-020-00127-4.
18.
GardnerW., StatesD., & BagleyN. (2020). The coronavirus and the risks to the elderly in long-term care. Journal of Aging and Social Policy, 32(4–5), 310–315. https://doi.org/10.1080/08959420.2020.1750543.
19.
GhoshI., & BiswasS. (2016). A comparative analysis of multi-criteria decision models for ERP package selection for improving supply chain performance. Asia-Pacific Journal of Management Research and Innovation, 12(3–4), 250–270.
20.
GuptaS., BandyopadhyayG., BhattacharjeeM., & BiswasS. (2019). Portfolio Selection using DEA-COPRAS at risk–return interface based on NSE (India). International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8(10), 4078–4086.
21.
HicksN., & StreetenP. (1979). Indicators of development: The search for a basic needs yardstick. World Development, 7(6), 567–580. https://doi.org/10.1016/0305-750X(79)90093-7.
22.
HillsM. (2020, May 27). Coronavirus: How the pandemic in US compares with rest of world. BBC News Report. https://www.bbc.com/news/world-us-canada-52771783.
23.
HsiaoF. S., & HsiaoM. C. W. (1983). Some development indicators of Taiwan: A comparative study. Journal of Economic Development, 8(1), 45–58.
24.
HughesJ. M., WilsonM. E., PikeB. L., SaylorsK. E., FairJ. N., LeBretonM., TamoufeU., DjokoC. F., RimoinA. W., & WolfeN. D. (2010). The origin and prevention of pandemics. Clinical Infectious Diseases, 50(12), 1636–1640. https://doi.org/10.1086/652860.
25.
Human Development Report. (2019). Human development data centre. UNDP. http://hdr.undp.org/en/data.
26.
KhanH. (1991). Measurement and determinants of socioeconomic development: A critical conspectus. Social Indicators Research, 24(2), 153–175. https://doi.org/10.1007/BF00300358.
27.
KhanM. G., YezdaniU., ChakravortyA., & ShuklaT. (2020). Efforts and challenges paved by India to confront of corona virus (COVID-19). Bangladesh Journal of Medical Science, S88–S92. https://doi.org/10.3329/bjms.v19i0.48198.
28.
KarmakarP., DuttaP., & BiswasS. (2018). Assessment of mutual fund performance using distance based multi-criteria decision making techniques–An Indian perspective. Research Bulletin, 44(1), 17–38.
29.
KaufmannM. (2013). Emergent self-organisation in emergencies: Resilience rationales in interconnected societies. Resilience, 1(1), 53–68.
30.
KlepacP., KucharskiA. J., ConlanA. J., KisslerS., TangM., FryH., & GogJ. R. (2020). Contacts in context: Large-scale setting-specific social mixing matrices from the BBC pandemic project. medRxiv. https://doi.org/10.1101/2020.02.16.20023754.
31.
LiX., WangK., LiuL., XinJ., YangH., & GaoC. (2011). Application of the entropy weight and TOPSIS method in safety evaluation of coal mines. Procedia Engineering, 26, 2085–2091.
32.
LiuP., & ZhangX. (2011). Research on the supplier selection of a supply chain based on entropy weight and improved ELECTRE-III method. International Journal of Production Research, 49(3), 637–646.
33.
MarkowitzS., NessonE., & RobinsonJ. J. (2019). The effects of employment on influenza rates. Economics and Human Biology, 34, 286–295.
34.
MassumiB. (2007). Potential politics and the primacy of preemption. Theory and Event, 10(2). https://muse.jhu.edu/article/218091.
35.
MazumdarK. (1995). Classification of countries: A socio-economic approach. Social Indicators Research, 34(2), 261–273. https://doi.org/10.1007/BF01079199.
36.
McGranahanD. V. (1971). Analysis of socio-economic development through a system of indicators. The Annals of the American Academy of Political and Social Science, 393(1), 65–81. https://doi.org/10.1177/000271627139300106.
37.
McGranahanD. V. (1972). Development indicators and development models. The Journal of Development Studies, 8(3), 91–102. https://doi.org/10.1080/00220387208421414.
38.
MikhaelE. M., & Al-JumailiA. A. (2020). Can developing countries alone face corona virus? The Iraqi situation. Public Health in Practice, 100004. https://doi.org/10.1016/j.puhip.2020.100004.
39.
MilenkovicN., VukmirovicJ., BulajicM., & RadojicicZ. (2014). A multivariate approach in measuring socio-economic development of MENA countries. Economic Modelling, 38, 604–608. http://dx.doi.org/10.1016/j.econmod.2014.02.011.
40.
NaganoH., de OliveiraJ. A. P., BarrosA. K., & JuniorA. D. S. C. (2020). The “Heart Kuznets Curve”? Understanding the relations between economic development and cardiac conditions. World Development, 132, 104953. https://doi.org/10.1016/j.worlddev.2020.104953.
41.
NowroozpoorA., ChooE. K., & FaustJ. S. (2020). Why the United States failed to contain COVID-19. https://doi.org/10.1002/emp2.12155.
42.
OshitaniH., KamigakiT., & SuzukiA. (2008). Major issues and challenges of influenza pandemic preparedness in developing countries. Emerging Infectious Diseases, 14(6), 875–880. https://doi.org/10.3201/eid1406.070839.
43.
OthickJ. (1983). Development indicators and the historical study of human welfare: Towards a new perspective. The Journal of Economic History, 43(1), 63–70. https://doi.org/10.1017/S0022050700029004.
44.
PrakashK. B., ImambiS. S., IsmailM., KumarT. P., & PawanY. N. (2020). Analysis, prediction and evaluation of covid-19 datasets using machine learning algorithms. International Journal of Emerging Trends in Engineering Research, 8(5), 2199–2204.
45.
PrestonS. H. (1975). The changing relation between mortality and level of economic development. Population Studies, 29(2), 231–248.
46.
ShannonC. E. (1948). A mathematical theory of communication. The Bell System Technical Journal, 27(3), 379–423.
47.
SharmaA. (2020). Why government thinks India has done better than other countries on COVID. https://economictimes.indiatimes.com/news/politics.
48.
ShujaJ., AlanaziE., AlasmaryW., & AlashaikhA. (2020). Covid-19 open source data sets: A comprehensive survey. Applied Intelligence, 1–30. https://doi.org/10.1007/s10489-020-01862-6.
49.
StankovićM., StevićŽ., DasD. K., SubotićM., & PamučarD. (2020). A new fuzzy MARCOS method for road traffic risk analysis. Mathematics, 8(3), 457. https://doi.org/10.3390/math8030457.
50.
StevićŽ., & BrkovićN. (2020). A novel integrated FUCOM-MARCOS model for evaluation of human resources in a transport company. Logistics, 4(1), 4. https://doi.org/10.3390/logistics4010004.
51.
StevićŽ., PamučarD., PuškaA., & ChatterjeeP. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to compromise solution (MARCOS). Computers and Industrial Engineering, 140, 106231. https://doi.org/10.1016/j.cie.2019.106231.
52.
The Hindustan Times. (2020, April 13). Covid-19: 3 big reasons why so many have died in New York. https://www.hindustantimes.com/world-news/covid-19-3-big-reasons-why-so-many-have-died-in-new-york/story-AIWaKzj7qXrp9APBDCNPWL.html.
53.
UdjoE. O., SimelaneS., & BooysenD. (2000, May). Socio-economic indicators of development progress within the OECD framework in South Africa. In Millennium Conference of Commonwealth Statisticians, pp. 1–5.
54.
WalkerJ., & CooperM. (2011). Genealogies of resilience: From systems ecology to the political economy of crisis adaptation. Security Dialogue, 42(2), 143–160.
55.
WHO. (2019). Global health expenditure database. WHOhttps://apps.who.int/nha/database/Select/Indicators/en.
56.
World Bank. (2019). GNI per capita, Atlas method (current US$). World Bank Group. https://data.worldbank.org/indicator/NY.GNP.PCAP.CD.
57.
ZanakisS. H., AlvarezC., & LiV. (2007). Socio-economic determinants of HIV/AIDS pandemic and nations efficiencies. European Journal of Operational Research, 176(3), 1811–1838.
58.
ZebrowskiC. (2016). The value of resilience: Securing life in the twenty-first century. Routledge.
59.
ZouZ. H., YiY., & SunJ. N. (2006). Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment. Journal of Environmental Sciences, 18(5), 1020–1023.
