Different countries have adopted different policies in their fight against the COVID-19 outbreak. In this work we aim to model these approaches with respect to the first wave of COVID-19 (from January to October 2020) in the five Central Asian republics (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan). By means of a multivariate approach based on principal component analysis and cluster analysis, we derived three clusters. Each of these represents a different strategy adopted by a group of governments in a given period of the first wave: pre-pandemic, initial reaction, and emergency scenarios. The contribution of these results is two-fold: on the one hand they may help us to understand differences and similarities among Central Asian republics during the first wave of the COVID-19 outbreak and guide future quantitative or qualitative studies; on the other hand, our findings suggest that, with the exception of Turkmenistan, the different countries adopted very similar strategies and that deaths, more than cases, pushed governments to impose restrictions.
AbrahamA.HassanienA. E.SnášelV. (2009). Foundations of computational intelligence: Volume 6: Data mining. Springer.
2.
AdamsonC. S.ChibaleK.GossR. J. M.JasparsM.NewmanD. J.DorringtonR. A. (2021). Antiviral drug discovery: Preparing for the next pandemic. Chemical Society Reviews, 50(6), 3647–3655.
3.
AlfanoV. (2022a). The effects of school closures on COVID-19: A cross-country panel analysis. Applied Health Economics and Health Policy, 20(2), 223–233.
4.
AlfanoV. (2022b). COVID-19 diffusion before awareness: The role of football match attendance in Italy. Journal of Sports Economics, 23(5), 503–523.
5.
AlfanoV. (2022c). COVID-19 in Central Asia: exploring the relationship between governance and non-pharmaceutical intervention. Health Policy and Planning, 37(8), 952–962.
6.
AlfanoV.CicatielloL.ErcolanoS. (2021). School openings and the COVID-19 outbreak in Italy. A provincial-level analysis using the synthetic control method. Health Policy, 125(9), 1200–1207.
7.
AlfanoV.ErcolanoS. (2020). The efficacy of lockdown against COVID-19: A cross-country panel analysis. Applied Health Economics and Health Policy, 18(4), 509–517.
8.
AlfanoV.ErcolanoS.PintoM. (2022). Fighting the COVID pandemic: National policy choices in non-pharmaceutical interventions. Journal of Policy Modelling, 44(1), 22–40.
9.
AlfanoV.SgobbiM. (2021). A peste, fame et bello libera nos Domine!Journal of Family History, 47(1), 24–40.
10.
AmodioE.BattistiM.KourtellosA.MaggioG.MaidaC. M. (2021). Schools opening and Covid-19 diffusion: Evidence from geolocalized microdata. Covid Economics, 65, 47–77.
11.
AwasthiA.LechevallierY.ParentM.ProthJ. M. (2006).Using hybrid clustering to approximate fastest paths on urban networks. Journal of Data Science, 4(1), 39–66.
12.
BeckerG. S. (1993). Nobel lecture: The economic way of looking at behavior. Journal of Political Economy, 101(3), 385–409.
13.
BlankS. (2008). The strategic importance of Central Asia: An American view. Army War Coll Carlisle.
14.
CooleyW. W.LohnesP. R. (1971). Multivariate data analysis. Wiley.
15.
De SimoneE.ErcolanoS.GaetaG. L. (2012). Exploring public social expenditure trends in the globalization era. European Research Studies Journal, 15(1), 23–42.
16.
ErcolanoS.RomanoO. (2013). Who makes the most? Measuring the “urban environmental virtuosity”. Social Indicators Research, 112(3), 709–724.
17.
ErcolanoS.RomanoO. (2018). Spending for the environment: General government expenditure trends in Europe. Social Indicators Research, 138(3), 1145–1169.
18.
EverittB. S. (1974). Cluster analysis. Wiley.
19.
FigueiredoA. M.CodinaA. D.FigueiredoD. C. M. M.SaezM.LeónA. C. (2020, April6). Impact of lockdown on COVID-19 incidence and mortality in China: An interrupted time series study. Bull World Health Organ.
20.
FischerK. (2022). Thinning out spectators: Did football matches contribute to the second COVID-19 wave in Germany? German Economic Review, 23(4), 595–640.
21.
HaleT.AngristN.Cameron-BlakeE.HallasL.KiraB.MajumdarS.PetherickA.PhillipsT.TatlowH.WebsterS. (2020). Oxford COVID-19 government response tracker. Blavatnik School of Government.
22.
HotezP. J. (2021). Preventing the next pandemic: Vaccine diplomacy in a time of anti-science. Johns Hopkins University Press.
23.
KubicekP. (1997), Regionalism, nationalism, and Realpolitik in Central Asia. Europe-Asia Studies, 49(4), 637.
24.
LauH.KhosrawipourV.KocbachP.MikolajczykA.SchubertJ.BaniaJ.KhosrawipourT. (2020). The positive impact of lockdown in Wuhan on containing the COVID-19 outbreak in China. Journal of Travel Medicine, 27(3), 37.
25.
LauerS. A.GrantzK. H.BiQ.JonesF. K.ZhengQ.MeredithH.AzmanA. S.ReichN. G.LesslerJ. (2020). The incubation period of coronavirus disease 2019 (COVID-19) from publicly reported confirmed cases: Estimation and application. Annals of Internal Medicine, 172(9), 577–582.
26.
MahmoudiM. R.BaleanuD.MansorZ.TuanB. A.PhoK. H. (2020). Fuzzy clustering method to compare the spread rate of Covid-19 in the high risks countries. Chaos, Solitons & Fractals, 140, 110230.
27.
MégarbaneB.BourassetF.ScherrmannJ. M. (2021). Is lockdown effective in limiting SARS-CoV-2 epidemic progression?—a cross-country comparative evaluation using epidemiokinetic tools. Journal General Internal Medicine, 36, 746–752.
28.
MeilaM.HeckermanD. (1998). An experimental comparison of several clustering and initialization methods. In Proceedings of the Uncertainty in Artificial Intelligence (pp. 386–395).
29.
TallonJ. M.GomesP.Bacelar–NicolauL. (2020). Profiling European countries on COVID–19 prevalence and association with non–pharmaceutical interventions. Biometrics & Biostatistics International Journal, 9(4), 118–130.
30.
OECD. (2008). Handbook on constructing composite indicators: Methodology and user guide.
31.
PearsonK. (1901). Principal components analysis. The London, Edinburgh and Dublin Philosophical Magazine and Journal, 6(2), 566.
32.
PintoM. (2019). Exploring activation: A cross-country analysis of active labour market policies in Europe. Social Science Research, 81, 91–105.
33.
RakhimovM. (2010). Internal and external dynamics of regional cooperation in Central Asia. Journal of Eurasian Studies, 1, 96.
34.
RiccardoF.AjelliM.AndrianouX.BellaA.Del MansoM.FabianiM.BellinoS.BorosS.UrdialesA. M.MarzianoV.RotaM. C.FiliaA.D’AnconaF. P.SidduA.PunzoO.TrentiniF.GuzzettaG.PolettiP.StefanelliP., . . . the COVID-19 working group. (2020). Epidemiological characteristics of COVID-19 cases in Italy and estimates of the reproductive numbers one month into the epidemic. https://www.medrxiv.org/content/10.1101/2020.04.08.20056861v1
35.
SardarT.NadimS. S.ChattopadhyayJ. (2020). Assessment of 21 days lockdown efect in some states and overall India: A predictive mathematical study on COVID-19 outbreak. https://arxiv.org/abs/2004.03487
36.
ShlensJ. (2005). A tutorial on principal component analysis. Salk Institute for Biological Studies La Jolla; Systems Neurobiology Laboratory.
37.
SimpsonS.KaufmannM. C.GlozmanV.ChakrabartiA. (2020). Disease X: Accelerating the development of medical countermeasures for the next pandemic. The Lancet Infectious Diseases, 20(5), 108–115.
38.
StathisD.MyronidisD. (2009). Principal component analysis of precipitation in Thessaly region (Central Greece). Global NEST Journal, 11(4), 467–476.
39.
TabachnickB. G.FidellL. S. (2007). Using multivariate statistics (5th ed.). Allyn & Bacon.
40.
WardJ. H. (1963). Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association, 58(301), 236–244.
41.
XuW.LiX.DozierM.HeY.KirolosA.LangZ.MathewsC.SiegfriedN.TheodoratouE., & UNCOVER. (2020). What is the evidence for transmission of COVID-19 by children in schools? A living systematic review. Journal of Global Health, 10(2). https://doi.org/10.7189/jogh.10.021104
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