Journal of Health Sciences & Surveillance System

Current Issue

By Issue

By Author

By Subject

Author Index

Keyword Index

About Journal

Aims and Scope

Editorial Board

Publication Ethics

Indexing and Abstracting

Related Links

FAQ

Peer Review Process

News

Application of Geospatial Technology for Infectious Disease Surveillance: A Study of Covid-19 Pandemic in North-east India

Document Type : Original Articles

Author

Research Scholar, Department of Geography, Cotton University, India

Abstract

Background: The COVID-19 pandemic has shattered the global health system and caused havoc worldwide. Since there is no proper medication, non-pharmaceutical intervention methods are followed to mitigate viral transmission. For its proper implementation, it is crucial to track the spatial pattern of transmission and target those areas which require immediate action to control the spread of the pandemic. The geospatial technologies have established themselves as powerful tools that have substantial ability to track outbreak patterns in real-time, identify at-risk populations, and plan targeted intervention.
Methods: The study provides a robust methodological framework with three geospatial tools: Spatial Autocorrelation (Global Moran's I), Hot Spot Analysis (Getis-Ord Gi*), and Space-time scan statistic. The quantitative study was carried out exclusively for North-East India to track the COVID-19 outbreaks from April 2020 to December 2020.
Results: The results obtained indicate a gradual change of spatial distribution of the disease from cluster to random distribution at the global scale. But, eventually, the COVID-19 cases tend to form clusters again. Kamrup Metro, the district with the highest urban population, was reported constantly as a hotspot. Moreover, space-time clusters tend to expand in size over time.
Conclusion:  The research study's findings provide an overview of the spatio-temporal pattern of COVID-19 in the study area and help the health officials and policy-makers in formulating effective management strategies and non-pharmaceutical intervention measures by targeting the high-risk areas. The study is a valuable guide towards implementing Geographic Information Science technologies in monitoring and tracking the pandemic.

Keywords

References
1. World Health Organization. Listing of WHO's response to COVID-19. Available from https://www.who.int/news/item/29-06-2020-covidtimeline. Published on June 29, 2020. Accessed on January 5, 2021.
2. M.A. Shereen, S Khan, A Kazmi, Bashir N, Siddique R. “COVID-19 infection: origin, transmission and characteristics of human coronaviruses”. J. Adv. Res, 24:91-98, 2020. 
3. Singhal T.A review of Coronavirus Disease-2019 (COVID-19). Indian J. Pediatr. 2020; 87(4): 281-286.
4. Fraser E. Long term respiratory complications of Covid-19. BMJ. 2020; 370.
5. Deng G, Yin M, Chen X, Zeng F. Clinical determinants for fatality of 44,672 patients with COVID-19.Crit. Care. 2020; 24.
6. World Health Organization .WHO Coronavirus Disease (COVID-19) Dashboard. Available from https://covid19.who.int/. Accessed on January 5, 2021.
7. United Nations Development Programme.Covid-19 and Human Development. Assessing the Crisis,   Envisioning   the Recovery. Available from http://hdr.undp.org/sites/default/files/covid-19_and_human_development_0.pdf. Accessed on January 8, 2021.
8. The World Bank. COVID-19 to Plunge Global Economy into Worst Recession since World War II. Available from https://www.worldbank.org/en/news/press-release/2020/06/08/covid-19-to-plunge-global-economy-into-worst-recession-since-world-war-ii . Published on June 8, 2020. Accessed on January 8, 2021.
9. International Labour Organization. Impact of COVID-19 on people’s livelihoods, their health and our food systems. Available from https://www.ilo.org/global/about-the- ilo/newsroom/statements-and-speeches/WCMS_757974/lang--en/index.htm. Published on October 13, 2020.Accessed on January 10, 2021.
10. Javed B, Sarwer A, Soto EB, Mashwani ZR. The coronavirus (COVID‐19) pandemic's impact on mental            health. Int. J Health Plann. Manag. 2020; 35(5).
11. World Health Organization. WHO Coronavirus Disease (COVID-19) Dashboard. Available from  https://covid19.who.int/. 2020. Accessed January 5, 2021.
12. Andrews MA, Areekal B, Rajesh KR, Krishnan J, Suryakala R, Krishnan B, Muraly CP, Santhosh PV. First confirmed case of COVID-19 infection in India: A case report. Indian J. Med. Res. 2020; 151(5):490-492.
13. Chu DK, Akl EA, Duda S, Solo K, Yaacoub S, Schünemann HJ, et al. Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS CoV-2 and COVID-19: a systematic review and meta-analysis. Lancet. 2020; 395(10242):1973–87.
14. Gross B, Zheng Z, Liu S, et al. Spatio-temporal propagation of COVID-19 pandemics. EPL. 2020; 131(6).
15. Clarke KC, Mchafferty SL, Tempalski B J. On Epidemiology and Geographic Information System: A review and   Discussion of Future Directions. Emerg. Infect. Dis. 1996; 2, 85-92.
16. Gao S, Mioc D, Anton F, Yi X, Coleman DJ. Online GIS services for mapping and sharing disease information. Int. J. Health Geogr. 2008; 7(8).
17. Liu Y, Wang W, Li X, et al. Geographic Distribution and Risk Factor of the Initial Adult Hospitalized Cases of 2009 Pandemic Influenza A (H1N1) Virus Infection in Mainland China. PLoS ONE .2011; 6(10).
18. Rahman MR, Islam AHMH, Islam MN. Geospatial modelling on the spread and dynamics of 154 day outbreak of the novel coronavirus (COVID-19) pandemic in Bangladesh towards vulnerability zoning and management approaches. Model. Earth Syst. Environ. 2020.
19. Yao HW, Yang Y, Liu K, et al. The Spatiotemporal Expansion of Human Rabies and its Probable Explanation in Mainland China, 2004-2013. PLoS Negl. Trop. Dis. 2015; 9 (2).
20. Ma J, Xiao J, Gao X, Liu B, Chen H, Wang H. Spatial pattern of foot-and-mouth diseases in animals in China, 2010-2016. Peer. J. 2017; 5.
21. Tewara MA, Fongkimeh PNM, Dayimu A, Kang F, Xue F. Small-area spatial statistical analysis of malaria cluster and hotspots in Cameroon, 2000-2015. BMC Infect. Dis. 2018; 18.
22. Bhunia GS, Kesari S ,Chatterjee N, Kumar V, Das P. Spatial and temporal variation and hotspot detection of kala-azar disease in Vaishali district (Bihar), India. BMC Infect. Dis. 2013; 13.
23. Guan WJ, Ni ZY, Hu Y, et al. Clinical characteristics of Coronavirus Disease 2019 in China. N. Engl. J. Med. 2020; 382, 1708-1720.
24. Mollalo A, Bahedi B, Rivera KM. GIS-based spatial modelling of COVID-19 incidence rate  in continental United States. Sci. Total Environ. 2020; 728.
25. Rees GH, Quispe FP, Scotter C. The implications of COVID‐19 for health workforce planning and policy: the case of Peru. Int. J. Health Plann. Manag
26. Roy S, Bhunia GS, Shit PK. Spatial prediction of COVID-19 epidemic using ARIMA techniques in India. Model. Earth Syst. Environ. 2020 (July).
27. Jen TH, Chien TW, Yeh YT, Lin JC, Kuo SC, Chou W. Geographic risk assessment of COVID-19 transmission using recent data. Medicine. 2020; 99 (24).
28. Census of India Census Digital Library. 2011. Available from https://censusindia.gov.in/DigitalLibrary/TablesSeries2001.aspx. Accessed on January 10, 2021.
29. howindialives.com. District wise Corona Tracker - India. 2020. Available from https://howindialives.com/gram/coronadistricts/. Accessed on January 10, 2021.
30. Jackson MC, Huang L, Xie Q, Tiwari RC. A modified version of Moran's I. 2010. Int J Health Geogr; 9 (33).
31. Ord J.K., Getis A. Local Spatial Autocorrelation Statistics: Distributional Issues and an Application. Geogr. Anal. 1995; 27(4).
32. Kulldorff M. Prospective time periodic geographical disease surveillance using a scan statistic. J. R. Stat. Soc.: Series A. 2002.164(1), 61–72.
33. Gross B, Zheng Z, Liu S, et al. Spatio-temporal propagation of COVID-19 pandemics. EPL. 2020; 131(6).
34. Shariati M, Mesgari T, Kasraee M, Jahangiri-rad M. Spatiotemporal analysis and hotspots detection of COVID-19 using geographic information system. J. Environ Health Sci. Eng. 2020; 18 (2):1499–507.
35. Wang Q, Dong W, Yang K, Ren Z, Huang D, Zhang P, et al. Temporal and spatial analysis of COVID-19 transmission in China and its influencing factors. Int. J. Infect. Dis. 2021; 105:675–685.
36. Bo Y, Guo C, Lin C, Zeng Y, Bi H, Zhang Y, et al. International Journal of Infectious Diseases Effectiveness of non-pharmaceutical interventions on COVID-19 transmission in 190 countries from 23 January to 13 April 2020. Int. J. Infect. Dis . 2021;102:247–253.
37. Mishra SV, Gayen A, Haque SM. COVID-19 and urban vulnerability in India. Habitat Int. 2020;103(May):102230.
38. Desjardins MR, Hohl A, Delmelle EM. Rapid surveillance of COVID-19 in the United States using a prospective space time scan statistic: Detecting and evaluating emerging clusters. Appl. Geogr. 2020; 118.
39. Gomes DS, Andrade LA, Ribeiro CJN, et al. Risk clusters of COVID-19 transmission in northeastern Brazil: prospective space–time modelling. Epidemiol. Infect. 2020; 148.
40. Hu B, Guo H, Zhou P, Shi ZL. Characteristics of SARS-CoV-2 and COVID-19. Nat. Rev. Microbiol. 2021; 19(3):141–54.
Journal of Health Sciences & Surveillance System
Volume 10, Issue 2
April 2022
Pages 158-167
Files
Share
How to cite
Statistics