Community vulnerability to epidemics in Nepal: A high-resolution spatial assessment amidst COVID-19 pandemic

  • Laxman Khanal
  • Binod Kumar Paudel
  • Bipin Kumar Acharya
Keywords: COVID-19, Epidemics, Municipal units, Nepal, Vulnerability mapping

Abstract

The coronavirus disease 2019 (COVID-19), the biggest health problem at present, doesn’t have uniform transmission and severity among the countries and communities therein. Knowledge of community vulnerability to the disease would facilitate interventions aimed at transmission control by efficient deployment of available limited resources. Therefore, we assessed spatial variations and heterogeneity of disease vulnerability among the population in 753 municipal units of Nepal. We collected geospatial indicators representing the domain of socioeconomic inequalities, population dynamics, heterogeneity in accessibility and the information related to an underlying health condition which potentially affect the severity of COVID-19 transmission. Those indicators were scaled to a common measurement scale and spatially overlaid via equally weighted arithmetic mean and then assembled to create three vulnerability indices using Geographic Information System; Social Vulnerability Index (SVI), Epidemiological Vulnerability Index (EVI) and a composite of the two- Social and Epidemiological Vulnerability Index (SEVI). The indices were classified into five levels of vulnerability and the municipal units and the population within vulnerability classes were quantified and visualized in the map. The index output indicated high vulnerability to epidemics in metropolitan cities like Kathmandu, Pokhara, Bharatpur, etc.; developing cities especially in the Province No 2; and, municipal units of Karnali and Sudoorpashchim provinces. Additionally, some other municipalities such as Dhulikhel, Beshishahar, Tansen etc.  which have a higher prevalence of pulmonary and cardiovascular disorders are highly vulnerable. The SVI indicated that 174 municipal units and 41.5% population is highly vulnerable. The EVI identified 55 municipal units and 40.7% of the total population of the country highly vulnerable to COVID-19. The SEVI accounted that disease vulnerability is high in 105 municipal units and 40% population of Nepal. The vulnerability indices created are means for different tiers of the existing government in the federal system of Nepal for prioritization and improved planning for disease intervention especially in highly vulnerable municipal units where the COVID-19 transmission could have high severity.

References

Acharya, B. K., Cao, C., Lakes, T., Chen, W., Naeem, S. and Pandit, S. 2018. Modeling the spatially varying risk factors of dengue fever in Jhapa district, Nepal, using the semi-parametric geographically weighted regression model. International Journal of Biometeorology 62:1973-1986. https://doi.org/10.1007/s0-0484-018-1601-8

Adger, W. N. 2006. Vulnerability. Global Environmental Change 16:268-281. https://doi.org/10.1016/j.gloenvcha.2006.02.006

Ahmed, F., Ahmed, N. E., Pissarides, C. and Stiglitz, J. 2020. Why inequality could spread COVID-19. The Lancet Public Health 5:e240. https://doi.org/10.1016/s2468-2667(20)30085-2

Anderson, R. M., Heesterbeek, H., Klinkenberg, D. and Hollingsworth, T. D. 2020. How will country-based mitigation measures influence the course of the COVID-19 epidemic? The Lancet 395:931-934. https://doi.org/10.1016/S0140-6736(20)30567-5

Anselin, L., Syabri, I. and Kho, Y. 2006. GeoDa: An introduction to spatial data analysis. Geographical Analysis 38:5-22.

Bates, I., Fenton, C., Gruber, J., Lalloo, D., Lara, A. M., Squire, S. B., et al. 2004. Vulnerability to malaria, tuberculosis, and HIV/AIDS infection and disease. Part II: determinants operating at environmental and institutional level. The Lancet Infectious Diseases 4:368-375. https://doi.org/10.1016/s1473-3099(04)-01047-3

Baud, D., Qi, X., Nielsen-Saines, K., Musso, D., Pomar, L. and Favre, G. 2020. Real estimates of mortality following COVID-19 infection. The Lancet Infectious Diseases. https://doi.org/10.1016/s1473-3099(20)30195-x

Boe, D. M., Boule, L. A. and Kovacs, E. J. 2017. Innate immune responses in the ageing lung. Clinical and Experimental Immunology 187:16-25. https://doi.org/10.1111/cei.12881

Cannon, T. 1994. Vulnerability analysis and the explanation of ‘Natural’ disasters. In: Varley, A. (Ed.) Disasters, Development and Environment. Wiley London: pp 13-30.

Chau, P. H., Gusmano, M. K., Cheng, J. O., Cheung, S. H. and Woo, J. 2014. Social vulnerability index for the older people-Hong Kong and New York City as examples. Journal of Urban Health 91:1048-1064. https://doi.org/10.1007/s11524-014-9901-8

Coccia, M. 2020. Factors determining the diffusion of COVID-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID. Science of the Total Environment 729:138474. https://doi.org/10.1016/j.scitotenv.2020.138474

DeCapprio, D., Burgess, T., Gartner, J., McCall, C. J., Sayed, S. and Kothari, S. 2020. Building a COVID-19 Vulnerability Index [Preprint]. medRxiv. https://doi.org/10.1101/2020.03.16.2003-6723

Dickin, S. K., Schuster-Wallace, C. J. and Elliott, S. J. 2013. Developing a vulnerability mapping methodology: applying the water-associated disease index to dengue in Malaysia. PLoS ONE 8:e63584. https://doi.org/10.1371/journal.pone.0063584

Dong, Y., Mo, X., Hu, Y., Qi, X., Jiang, F., Jiang, Z., et al. 2020. Epidemiology of COVID-19 among children in China. Pediatrics 145:e20200702. https://doi.org/10.1542/peds.2020-0702

Esri Inc. ArcMap (version 10.5). 2016. Software. Redlands, CA: Esri Inc.

Fang, L., Karakiulakis, G. and Roth, M. 2020. Are patients with hypertension and diabetes mellitus at increased risk for COVID-19 infection? The Lancet Respiratory Medicine 8:e21. https://doi.org/10.1016/s2213-2600(20)30116-8

Frankel, L. K. 2011. The relation of life insurance to public hygiene. 1910. American Journal of Public Health 101:1868-1869. https://doi.org/10.2105/ajph.2011.101101868

Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., et al. 2020. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. The Lancet 395:497-506. https://doi.org/-10.1016/s0140-6736(20)30183-5

ICIMOD. (2013). Land cover of Nepal 2010 [Data set]. ICIMOD. https://doi.org/10.26066/rds.9224

Jenks, G. 1977. Optimal data classification for choropleth maps. University of Kansas, Department of Geography, p 24.

Ji, Y., Ma, Z., Peppelenbosch, M. P. and Pan, Q. 2020. Potential association between COVID-19 mortality and health-care resource availability. The Lancet Global Health 8:e480. https://doi.org/10.1016/s2214-109x(20)30068-1

Kamel Boulos, M. N. and Geraghty, E. M. 2020. Geographical tracking and mapping of coronavirus disease COVID-19/severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic and associated events around the world: how 21st century GIS technologies are supporting the global fight against outbreaks and epidemics. International Journal of Health Geography 19:8. https://doi.org/10.1186/s12942-020-00202-8

Kang, D., Choi, H., Kim, J. H. and Choi, J. 2020. Spatial epidemic dynamics of the COVID-19 outbreak in China. International Journal of Infectious Diseases 94:96-102. https://doi.org/10.-1016/j.ijid.2020.03.076

Kassir, R. 2020. Risk of COVID-19 for patients with obesity. Obesity Reviwes 21:e13034. https://doi.org/10.1111/obr.13034

KC, S., Mishra, R., Mishra, R. and Shukla, A. 2020. Community COVID-19 vulnerability index in India. IIASA Working Paper, Laxenburg, Austria.

Kienberger, S. and Hagenlocher, M. 2014. Spatial-explicit modeling of social vulnerability to malaria in East Africa. International Journal of Health Geographics 13:e29.

Liu, Y., Gayle, A. A., Wilder-Smith, A. and Rocklov, J. 2020. The reproductive number of COVID-19 is higher compared to SARS coronavirus. Journal of Travel Medicine 27:1-4. https://doi.org/-10.1093/jtm/taaa021

Macharia, P. M., Joseph, N. K. and Okiro, E. A. 2020. A vulnerability index for COVID-19: spatial analysis to inform equitable response in Kenya [Preprint]. medRxiv. https://doi.org/10.1-101/2020.05.27.20113803

Mayala, B. K., Dontamsetti, T., Fish, T. D. and Croft, T. N. 2019. Interpolation of DHS survey data at subnational administrative Level 2. ICF, Rockville, Maryland, USA.

Miller, J. 2020. The overstated COVID-19 blame on urban density in favor of suburban living. Forbes. https://www.forbes.com/sites. Accessed on 14 May 2020.

MoHP, G. o. N. 2020. Ministry of health and popultion, government of Nepal. Retrieved from https://covid-19.mohp.gov.np/#/. Accessed on 18 June 2020.

Mollalo, A., Vahedi, B. and Rivera, K. M. 2020. GIS-based spatial modeling of COVID-19 incidence rate in the continental United States. Science of the Total Environment 728:138884. https://doi.org/10.1016/j.scitotenv.2020.138884

Mwarumba, N. 2017. Global social vulnerability to pandemics: An examinationn of social determinants of H1N1 2009 mortality. PhD Thesis, Oklahoma State University, Oklahoma, p 150.

Ndah, A. B. and Ngoran, S. D. 2015. Liaising Water Resources Consumption, Urban Sanitation and Cholera Epidemics in Douala, Cameroon: A Community Vulnerability Assessment. Journal of Resources Development and Management 8:63-78.

Olago, D., Marshall, M., Wandiga, S. O., Opondo, M., Yanda, P. Z., Kangalawe, R., et al. 2007. Assessment of the potential of ecolabels to promote agrobiodiversity. Ambio 36:551-558. https://doi.org/10.1579/0044-7447(2007)36[551:aotpoe]2.0.co;2

Platt, L. and Warwick, R. 2020. Are some ethnic groups more vulnerable to COVID-19 than others? The Institute for Fiscal Studies, Nuffield Foundation.

Pringle, D. G. 1996. Mapping disease risk estimates based on small numbers: An assessment of empirical Bayes techniques. Economic and Social Review 27:341–363.

Rader, B., Astley, C. M., Sy, K. T. L., Sewalk, K., Hswen, Y., Brownstein, J. S., et al. 2020. Geographic access to United States SARS-CoV-2 testing sites highlights healthcare disparities and may bias transmission estimates. Journal of Travel Medicine. https://doi.org/10.1093/jtm/taaa076

Rader, B., Astley, C. M., Sy, K. T. L., Sewalk, K., Hswen, Y., Brownstein, J. S., et al. 2020. Increased travel times to United States SARS-CoV-2 testing sites: A spatial modeling study [Preprint]. medRxiv. https://doi.org/10.1101/2020.04.25.20074419

Ray, N. and Ebener, S. 2008. AccessMod 3.0: computing geographic coverage and accessibility to health care services using anisotropic movement of patients. International Journal of Health Geographics 7:63. https://doi.org/10.1186/1476-072X-7-63

Rocklöv, J. and Sjödin, H. 2020. High population densities catalyse the spread of COVID-19. Journal of Travel Medicine 27:taaa038. https://doi.org/10.1093/jtm/taaa038

Rothan, H. A. and Byrareddy, S. N. 2020. The epidemiology and pathogenesis of coronavirus disease (COVID-19) outbreak. Journal of Autoimmunity 109:102433. https://doi.org/10.1016/j.j-aut.2020.102433

Sarwar, S., Waheed, R., Sarwar, S. and Khan, A. 2020. COVID-19 challenges to Pakistan: Is GIS analysis useful to draw solutions? Science of the Total Environment 730:139089. https://doi.org/1-0.1016/j.scitotenv.2020.139089

Semenza, J. C. and Giesecke, J. 2008. Intervening to reduce inequalities in infections in Europe. American Journal of Public Health 98:787-792. https://doi.org/10.2105/AJPH.2007.120329)

Simon, D. 2020. Cities are at centre of coronavirus pandemic - understanding this can help build a sustainable, equal future. The Conversation, 23 April 2020. https://theconversation.com

Smith, J. A. and Judd, J. 2020. COVID-19: Vulnerability and the power of privilege in a pandemic. Health Promotion Journal of Australia 31:158-160. https://doi.org/10.1002/hpja.333

Sominsky, L., Walker, D. W. and Spencer, S. J. 2020. One size does not fit all - Patterns of vulnerability and resilience in the COVID-19 pandemic and why heterogeneity of disease matters. Brain, Behavior, and Immunity. https://doi.org/10.1016/j.bbi.2020.0-3.016

Sullivan, C. A. and Meigh, J. 2006. Integration of the biophysical and social sciences using an indicator approach: Addressing water problems at different scales. Water Resources Management 21:111-128. https://doi.org/10.1007/s11269-006-9044-0

Tharu, T., Gahatraj, R., Shahi, M. and Gautam, G. 2020. Community transmission of COVID-19 in Nepalgunj city, Nepal (in Nepali language). Kantipur National Daily, http://www.ekantipur.com. Accessed on 04 May 2020.

Tuite, A., Ng, V., Rees, E. and Fisman, D. 2020. Estimation of COVID-19 outbreak size in Italy based on international case exportations [Preprint]. medRxiv 20030049. https://doi.org/10.1101/2020.0-3.02.20030049

Wadhera, R. K., PriyaWadhera, Gaba, P., Figueroa, J. F., Maddox, K. E. J., Yeh, R., et al. 2020. Variation in COVID-19 hospitalizations and deaths across New York city boroughs. JAMA 323:2194-2195. https://doi.org/10.1001/jama.2020.6887

Weiss, D. J., Nelson, A., Gibson, H. S., Temperley, W., Peedell, S., Lieber, A., et al. 2018. A global map of travel time to cities to assess inequalities in accessibility in 2015. Nature 553:333-336. https://doi.org/10.1038/nature25181

WHO. 2020a. Report of the World Health Organization-China Joint Mission on Coronavirus Disease 2019 (COVID-19). Retreived from: https://www.who.int/docs/default-source/coronaviruse/who-china-joint-mission-on-covid-19-final-report.pdf

WHO. 2020b. Coronavirus Disease 2019 (COVID-19) Situation Report- 157. World Health Organization. Retrieved from: https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200625-covid-19-sitrep-157.pdf?sfvrsn=423f4a82_2

Wu, Z. and McGoogan, J. M. 2020. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China summary of a report of 72314 cases from the Chinese Center for Disease Control and Prevention. JAMA 323:1239-1242. https://doi.org/10.1001/jama.2020.2648

Yang, Y., Peng, F., Wang, R., Guan, K., Jiang, T., Xu, G., et al. 2020. The deadly coronaviruses: The 2003 SARS pandemic and the 2020 novel coronavirus epidemic in China. Journal of Autoimmunity 109:102434. https://doi.org/10.1016/j.jaut.2020.-102434

You, D., Lindt, N., Allen, R., Hansen, C., Beise, J. and Blume, S. 2020. Migrant and displaced children in the age of COVID-19: How the pandemic is impacting them and what we can do to help. Migration Policy Practice X:32-39

Zheng, Y. Y., Ma, Y. T., Zhang, J. Y. and Xie, X. 2020. COVID-19 and the cardiovascular system. Nature Reveiws Cardiology 17:259-260. https://doi.org/10.1038/s41569-020-0360-5

Published
2020-08-18
How to Cite
Khanal, L., Paudel, B. K., & Acharya , B. K. (2020). Community vulnerability to epidemics in Nepal: A high-resolution spatial assessment amidst COVID-19 pandemic. Nepalese Journal of Zoology , 4(1), 23-35. Retrieved from https://www.cdztu.edu.np/njz/index.php/NJZ/article/view/79
Section
Research Articles