Spatial statistical analysis of Coronavirus Disease 2019 (Covid-19) in China

  • Huling Li College of Public Health, Xinjiang Medical University, Urumqi, China.
  • Hui Li Central Laboratory of Xinjiang Medical University, Urumqi, China.
  • Zhongxing Ding Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
  • Zhibin Hu Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
  • Feng Chen Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
  • Kai Wang Department of Medical Engineering and Technology, Xinjiang, China. https://orcid.org/0000-0002-6224-8453
  • Zhihang Peng Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
  • Hongbing Shen | hbshen@njmu.edu.cn Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.

Abstract

The cluster of pneumonia cases linked to coronavirus disease 2019 (Covid-19), first reported in China in late December 2019 raised global concern, particularly as the cumulative number of cases reported between 10 January and 5 March 2020 reached 80,711. In order to better understand the spread of this new virus, we characterized the spatial patterns of Covid-19 cumulative cases using ArcGIS v.10.4.1 based on spatial autocorrelation and cluster analysis using Global Moran’s I (Moran, 1950), Local Moran’s I and Getis-Ord General G (Ord and Getis, 2001). Up to 5 March 2020, Hubei Province, the origin of the Covid-19 epidemic, had reported 67,592 Covid-19 cases, while the confirmed cases in the surrounding provinces Guangdong, Henan, Zhejiang and Hunan were 1351, 1272, 1215 and 1018, respectively. The top five regions with respect to incidence were the following provinces: Hubei (11.423/10,000), Zhejiang (0.212/10,000), Jiangxi (0.201/10,000), Beijing (0.196/10,000) and Chongqing (0.186/10,000). Global Moran’s I analysis results showed that the incidence of Covid-19 is not negatively correlated in space (p=0.407413>0.05) and the High-Low cluster analysis demonstrated that there were no high-value incidence clusters (p=0.076098>0.05), while Local Moran’s I analysis indicated that Hubei is the only province with High-Low aggregation (p<0.0001).

Dimensions

Altmetric

PlumX Metrics

Downloads

Download data is not yet available.

References

Anselin L, 1995. Local Indicators of Spatial Association—LISA. Geogr Anal 27(2), 93-115. doi: 10.1111/j.1538-4632.1995.tb00338.x. DOI: https://doi.org/10.1111/j.1538-4632.1995.tb00338.x

Chan JF, Kok KH, Zhu Z, et al., 2020a. Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan. Emerg Microbes Infect 9(1), 221-36. doi:10.1080/22221751.2020.1719902. DOI: https://doi.org/10.1080/22221751.2020.1719902

Chan JF, Yuan S, Kok KH, et al. , 2020b. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family. Lancet cluster [published online ahead of print Jan 24]. doi:10.1016/S0140-6736(20)30154-9. DOI: https://doi.org/10.1016/S0140-6736(20)30154-9

Holshue ML, DeBolt C, Lindquist S, Lofy KH, Wiesman J, et al., 2020. First Case of 2019 Novel Coronavirus in the United States. N Engl J Med 382(10):929-36. doi:10.1056/NEJMoa2001191. DOI: https://doi.org/10.1056/NEJMoa2001191

Hosseiny M, Kooraki S, Gholamrezanezhad A, Reddy S, Myers L, 2020. Radiology Perspective of Coronavirus Disease 2019 (COVID-19): Lessons From Severe Acute Respiratory Syndrome and Middle East Respiratory Syndrome. AJR Am J Roentgenol. 2020 Feb 28:1-5. doi: 10.2214/AJR.20.22969. [Epub ahead of print]. DOI: https://doi.org/10.2214/AJR.20.22969

Huo XN, Li H, Sun DF, Zhou LD, Li BG, 2012. Combining geostatistics with Moran's I analysis for mapping soil heavy metals in Beijing, China. Int J Environ Res Public Health 9(3), 995–1017. doi:10.3390/ijerph9030995. DOI: https://doi.org/10.3390/ijerph9030995

Huo XN, Zhang WW, Sun DF, Li H, Zhou LD, Li BG, 2011. Spatial pattern analysis of heavy metals in Beijing agricultural soils based on spatial autocorrelation statistics. Int J Environ Res Public Health 8(6), 2074–89. doi:10.3390/ijerph8062074. DOI: https://doi.org/10.3390/ijerph8062074

Li Q, Guan X, Wu P, Wang X, Zhou L, et al., 2020. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia. N Engl J Med [published online ahead of print, 2020 Jan 29]. doi:10.1056/NEJMoa2001316. DOI: https://doi.org/10.1056/NEJMoa2001316

Lai CC, Shih TP, Ko WC, Tang HJ, Hsueh PR, 2020. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease-2019 (COVID-19): The epidemic and the challenges [published online ahead of print]. Int J Antimicrob Agents 105924. doi:10.1016/j.ijantimicag.2020.105924 DOI: https://doi.org/10.1016/j.ijantimicag.2020.105924

Liu W, Yang K, Qi X, Xu K, Ji H, et al. 2013. Spatial and temporal analysis of human infection with avian influenza A(H7N9) virus in China. Euro Surveill 18(47), 20640. doi:10.2807/1560-7917.es2013.18.47.20640 DOI: https://doi.org/10.2807/1560-7917.ES2013.18.47.20640

Mazzulla G, Forciniti C, 2012. Spatial association techniques for analysing trip distribution in an urban area. Eur Transp Res Rev 4(4), 217-33. doi:10.1007/s12544-012-0082-9. DOI: https://doi.org/10.1007/s12544-012-0082-9

Moran PAP, 1950. Notes on Continuous Stochastic Phenomena. Biometrika 371,17-23. doi:10.2307/2332142. JSTOR 2332142. DOI: https://doi.org/10.2307/2332142

National Health Commission of the People’s Republic of China, 2020. Latest update on outbreak prevention and control. Available at: http://www.nhc.gov.cn/xcs/yqtb/202003/b59dbcc84ed1498292714975039dcdc9.shtmlAccessed on 7 March 2020.

Nishiura H, Jung SM, Linton NM, Kinoshita R, Yang Y, Hayashi K, Kobayashi T, Yuan B, Akhmetzhanov AR, 2020. The Extent of Transmission of Novel Coronavirus in Wuhan, China, 2020. J Clin Med. Published Jan 24;9(2). pii: E330. doi:10.3390/jcm9020330. DOI: https://doi.org/10.3390/jcm9020330

Ord K, Getis A, 2001. Testing for Local Spatial Autocorrelation in the Presence of Global Spatial Autocorrelation. J Reg Sci 41(3), 411-32. doi:10.1111/0022-4146.00224. DOI: https://doi.org/10.1111/0022-4146.00224

Páez A, Scott DM; 2005, 2005. Spatial statistics for urban analysis: A review of techniques with examples. GeoJournal 61(1), 53-67. doi:10.1007/s10708-005-0877-5. DOI: https://doi.org/10.1007/s10708-005-0877-5

Paules CI, Marston HD, Fauci AS, 2020. Coronavirus Infections-More Than Just the Common Cold. JAMA [published online ahead of print, 2020 Jan 23]. doi:10.1001/jama.2020.0757. DOI: https://doi.org/10.1001/jama.2020.0757

Rothe C, Schunk M, Sothmann P, Bretzel G, Froeschl G, et al., 2020. Transmission of 2019-nCoV infection from an asymptomatic contact in Germany. N Engl J Med. 2020:NEJMc2001468. doi.org/10.1056/NEJMc 2001468 DOI: https://doi.org/10.1056/NEJMc2001468

Samphutthanon R, Tripathi N, Ninsawat S, Duboz R, 2013. Spatio-temporal distribution and hotspots of hand, foot and mouth disease (HFMD) in northern Thailand. Int J Environ Res Public Health 11(12), 312-36. DOI: https://doi.org/10.3390/ijerph110100312

Sheng G, Chen P, Wei Y, Yue H, Chu J, Zhao J, Wang Y, Zhang W, Zhang HL, 2019. Viral infection increases the risk of idiopathic pulmonary fibrosis: a meta-analysis. Chest doi.org/10.1016/j.chest.2019.10.032 DOI: https://doi.org/10.1016/j.chest.2019.10.032

Sun SH, Gao ZD, Zhao F, et al. Zhonghua Liu Xing Bing Xue Za Zhi. 2018;39(6):816-820. doi:10.3760/cma.j.issn.0254-6450.2018.06.023

Sun P, Lu X, Xu C, Sun W, Pan B, 2020. Understanding of COVID-19 based on current evidence [published online ahead of print, 2020 Feb 25]. J Med Virol doi:10.1002/jmv.25722. DOI: https://doi.org/10.1002/jmv.25722

Velavan TP, Meyer CG, 2020. The COVID-19 epidemic [published online ahead of print, 2020 Feb 12]. Trop Med Int Health. doi:10.1111/tmi.13383 DOI: https://doi.org/10.1111/tmi.13383

Wang FS, Zhang C, 2020. What to do next to control the 2019-nCoV epidemic? Lancet 395(10222), 391-3. doi.org/10.1016/ S0140-6736(20)30300-7 DOI: https://doi.org/10.1016/S0140-6736(20)30300-7

Wang C, Horby PW, Hayden FG, Gao GF, 2020. A novel coronavirus outbreak of global health concern [published online ahead of print, 2020 Jan 24]. Lancet doi:10.1016/S0140-6736(20)30185-9. DOI: https://doi.org/10.1016/S0140-6736(20)30185-9

Weeberb JR Jr, Koutrakis P, Roig H L, 2015. Spatial distribution of vehicle emission inventories in the Federal District, Brazil. Atmos Environ 112, 32-9. DOI: https://doi.org/10.1016/j.atmosenv.2015.04.029

WHO, 2020. Situation report 'Coronavirus disease (COVID-19)', released on March 6, 2020. Available at: https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200306-sitrep-46-covid-19.pdf?sfvrsn=96b04adf_4 Accessed on 7 March 2020.

Yang Y, Shang W, Rao X, 2020. Facing the COVID-19 outbreak: What should we know and what could we do? [published online ahead of print, 2020 Feb 24]. J Med Virol doi:10.1002/jmv.25720 DOI: https://doi.org/10.1002/jmv.25720

Zhao S, Lin Q, Ran J, Musa SS, Yang G, Wang W, Lou Y, Gao D, Yang L, He D, Wang MH, 2020. Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCov) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak. Int J Infect Dis 92:214-7. doi:10.1016/j.ijid.2020.01.050. DOI: https://doi.org/10.1016/j.ijid.2020.01.050

Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, Zhao X, Huang B, Shi W, Lu R, Niu P, Zhan F, Ma X, Wang D, Xu W, Wu G, Gao GF, Tan W, 2020. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med 382(8), 727-33. doi:10.1056/NEJMoa2001017. DOI: https://doi.org/10.1056/NEJMoa2001017

Published
2020-06-15
Info
Issue
Section
Original Articles
Keywords:
Coronavirus disease 2019 (COVID-19), Hubei province area, Spatial statistics, China
Statistics
  • Abstract views: 2992

  • PDF: 1395
  • HTML: 0
How to Cite
Li, H., Li, H., Ding, Z., Hu, Z., Chen, F., Wang, K., Peng, Z., & Shen, H. (2020). Spatial statistical analysis of Coronavirus Disease 2019 (Covid-19) in China. Geospatial Health, 15(1). https://doi.org/10.4081/gh.2020.867