DOI: http://dx.doi.org/10.18203/2394-6040.ijcmph20203415

Factors influencing COVID-19 case burden and fatality rates findings from secondary data analysis of major urban agglomerations in India

Deodatt M. Suryawanshi, Raghuram Venugopal, Ramchandra Goyal

Abstract


In December 2019, SARS COV-2 which originated in the Chinese city of Wuhan achieved pandemic proportions and spread rapidly to countries through International air traffic causing acute respiratory infection and deaths. Presence of International airports, demography, health financing and human developments factors were assumed to influence COVID-19 cases burden and case fatality rate (CFR). So, this study was undertaken to find a association between these factors and COVID-19 cases and deaths. The study used 48 districts using purposive sampling as proxy for cities and used secondary data analysis. Data was obtained for various variables like demographic, Health Financing, Indices and Testing infrastructure, COVID cases burden and case fatality from trusted sources. Descriptive statistics correlational statistics using Pearsons coefficient students T was used to describe, correlate and find significant difference in the data. The analysis found a significant difference between COVID cases burden in districts with International Airports (p<0.039) and those without it. Positive correlation of population density (r=0.65) with COVID-19 case burden and negative correlation of case fatality rate with NITI Aayogs health index (r=-0.12), human development index (HDI) (r=-0.18), per-capita expenditure on health (r=-0.072) and a correlation of r=0.16 was observed for gross state domestic product. Decongestion of cities through perspective urban planning is the need of the hour. Stricter quarantine measures in those districts with international airports can help reduce the transmission. Negative correlation of HDI and NITI Aayogs health index with CFR emphasizes the importance of improvements in social determinants of health.


Keywords


COVID-19, Urban area, Case fatality, Population density, Per capita health expenditure, Human development index

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References


WHO. Coronavirus disease (COVID-19) outbreak; 2020. Available at: https://www.who.int/emerg-encies/diseases/novel-coronavirus-2019. Accessed on 30 May 2020.

Epidemiology Working Group for NCIP Epidemic Response, Chinese Center for Disease Control and Prevention. The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China. Zhonghua Liu Xing Bing Xue Za Zhi. 2020;41(2):145-51.

WHO COVID-19 Situation reports. Available at: https://www.who.int/emergencies/diseases/novel-coronavirus 2019/situation-reports/ Accessed on 08 May 2020.

Ruan S. Likelihood of survival of coronavirus disease 2019. Lancet Infect Dis. 2020;20(6):630‐1.

Desai DD. Urban Densities and the Covid-19 Pandemic: Upending the Sustainability Myth of Global Megacities. ORF Occasional Paper No. 244, 2020.

Class 1 Urban agglomerations. Available at: http://mohua.gov.in/cms/number-of-cities--towns-by-city-size-class.php. Accessed on 29 May 2020.

Lau H, Khosrawipour V, Kocbach P, Mikolajczyk A, Ichii H, Zacharski M, et al. The association between international and domestic air traffic and the corona virus (COVID-19) outbreak. J Microbiol Immunol Infection. 2020;53(3):467-72.

Covid-19 Status Update. Available at: https://www.covid19india.org. Accessed on 30 May 2020.

Airports Authority of India. Available at: https://www.aai.aero/ Accessed on 30 May 2020.

Population density & slum population. Available at: https://censusindia.gov.in/2011-Common/Census Data2011.html. Accessed on 29 May 2020.

National health profile. Central Bureau of health intelligence publication. MOHFW. Issue 14. Available at: https://www.cbhidghs.nic.in/index1 .php?lang=1&level=1&sublinkid=75&lid=1135 Accessed on 29 May 2020.

NITI AAYOG. Healthy States Progressive India Report on the Ranks of States and Union Territories. Available at: http://social.niti.gov.in/ Accessed on 29 May 2020.

"Sub-national HDI - Area Database - Global Data Lab". Available at: https://globaldatalab.org/ shdi/shdi/IND/?levels=1%2B4&interpolation=0&extrapolation=0&nearest_real=0.Accessed on 30 May 2020.

Sub national Huna development index. Available at: https://qphs.fs.quoracdn.net/main-qimg- 9f57b25 5c4d971c9cd579d7a6f2dc70f. Accessed on 31 May 2020

Testing Laboratories in various states. Available at: https://www.thehindu.com/data/article31254727.ece/inline/ Accessed on 30 May 2020.

Total Operational (initiated independent testing) Laboratories reporting to ICMR. Available at: https://www.icmr.gov.in/arcctestlab.html. Accessed on 30 May 2020.

Niti Aayogs Health Index. Available at: https://pib.gov.in/PressReleasePage.aspx?PRID=1575588#:~:text=The%20Health%20Index%20is%20a,been%20equally%20distributed%20among%20indicators. Accessed on 03 June 2020.

Human development index definition. Available at: https://economictimes.indiatimes.com/definition/human-development-index. Accessed on 03 June 2020.

Data Wrapper. Available at: https://app.datawrap-per.de/mycharts/. Accessed on 31 May 2020

Bump, Philip, “New York City Is the Epicentre Of Coronavirus in The U.S. – Is This Due to Density Or Testing?”, The Washington Post, 2020. Available at https://www.washingtonpost.com/politics/2020/03/19/new-yorkcity-is-epicenter-coronavirus-us-is-this-due-density-or-testing. Accessed on 29 May 2020

Official UK Cases & Deaths – Accurate as of April 27, The Sun, 27 April 2020, Available at https://www.thesun.co.uk/wp-content/uploads/2020/ 04/GLUK- CORONAVIRUS-MAP-DEATHS-IN-OUT-27-APRIL-1730.jpg. Accessed on 29 May 2020.

Trust for London (2017). London’s geography and population. Available at https://www.trustforlondon .org.uk/data/londons-geography/. Accessed on 29 May 2020.