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Geospatial Mapping of COVID-19 Cases, Risk and Agriculture Hotspots in Decision-Making of Lockdown Relaxation in Nepal

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Geospatial Mapping of COVID-19 Cases, Risk and Agriculture Hotspots in Decision-Making of Lockdown Relaxation in Nepal Applied Science and Technology Annals. Vol.1, No.1 (2020); 01–08 ISSN: 2717-5014 (Print). Available online at www.recast.tu.edu.np DOI: https://doi.org/10.3126/asta.v1i1.30263 Research Article Geospatial mapping of COVID-19 cases, risk and agriculture hotspots in decision-making of lockdown relaxation in Nepal Bijaya Maharjan 1*, Alina Maharjan 2, Shanker Dhakal 3, Manash Gadtaula 4, Sunil B. Shrestha 3, and Rameshwar Adhikari 5* 1 Lumbini International Academy of Science and Technology, Lumbini Buddhist University, Lalitpur, Nepal 2 Central Department of Environment Science, Tribhuvan University, Kathmandu, Nepal 3 Nepal Academy of Science and Technology (NAST), Lalitpur, Nepal 4 Civil/Hydropower Engineer; Kathmandu, Nepal 5 Research Centre for Applied Science and Technology (RECAST); Tribhuvan University, Kathmandu, Nepal Received: May 23, 2020; Accepted: June 14, 2020; Published: June 25, 2020 Abstract: The study has explored the risk scenario via geospatial mapping of temporal transmission trend of COVID-19 in 77 districts of Nepal focusing on the district-wise risk analyses based on present active cases, population density and land entry points from neighboring countries. In overall, low to very high risk zones have been identified. Jhapa, Morang and Sunsari districts of Province 1; Dhanusa, Mahottari, Sarlahi, Rautahat, Bara and Parsa districts of Province 2; Kathmandu district of Bagmati Province, Nawalparasi West, Rupandehi, Kapilbastu and Banke districts of Province 5, as well as Kailali of Sudurpanchim Province are identified to have very high risk for COVID-19 spread. The rapid growth in the number of cases has made many districts remarkably susceptible to the infection. The vulnerability analysis has been then followed by identification of agriculture hotspots across the country in terms of major crops. 42 districts with moderate to high crop productivities have been recognized as being not in very high risk zones where the government should allow farmers to do their agriculture activities with well-maintained social distance and other safety precautions. The results when combined would suggest an urgent decision by the Government for gradual lockdown relaxation for agro-economic reinstatement what is commonly called the latent comparative advantage for Nepalese economy after tourism. Keywords: COVID-19, GIS, risk analysis, agriculture, lockdown relaxation, agro-economy ;f/f+z: of] cg';Gwfgkqdf ef}uf]lns ;"rgf k|0ffnL -GIS_ sf] k|of]uåf/f g]kfnsf && lhNnfx?df sf]le8 - !( /f]usf] ;+qmd0fsf] cfjlws k|j[lQsf] n]vfhf]vf u/]/ ;+efljt hf]lvdsf] kl/b[Zosf] cfsng ug]{ k|of; ul/Psf] 5 . ljleGg lhNnfdf xfn hfgsf/Ldf /x]sf la/fdLsf] ;+Vof, hg3gTj / l5d]sL b]zx?jf6 g]kfn cfpg] k|j]z laGb'df cfwfl/t eP/ lhNnfut hf]lvdsf] ljZn]if0f ul/Psf] 5 . ;du|df sdb]lv pRr hf]lvddf kg{ ;Sg] lhNnfx¿sf] klxrfg ul/Psf] 5 . k|b]z ! df cjl:yt emfkf, df]/+u tyf ;'g;/L; k|b]z @ sf wg'iff, dxf]Q/L, ;nf{xL, /f}tx6, af/f / k;f{; afudtL k|b]zsf] sf7df8f}+ tyf k|b]z % sf gjnk/f;L, ?kGb]x-klZrd, slknj:t' / afFs] tyf ;'b'/ klZrd k|b]zsf] s}nfnL sf]le8 -!( ;+qmd0fsf] w]/} pRr hf]lvdsf] klxrfg ul/Psf] 5 . ;+qmd0fsf] ;+Vofdf ePsf] ›'t a[l4n] w]/} lhNnfx¿nfO{ pNn]vlgo ?kdf hf]lvdo'Qm agfPsf] 5 . cWoogsf] bf];|f] vG8df b]zsf] k|d'v afnLsf] ;Gbe{df b]zel/sf s[lif x6:k6x¿sf] klxrfg u/]/ afnLgfnLsf] cj:yfsf] ljZn]if0f k|:t't ul/Psf] 5. dWodb]lv pRr dfqfdf km;n pTkfbsTj ;fdy{\o ePsf t/ sf]le8-!( ;+qmd0fsf] lx;fjn] ;fx|} pRr hf]lvddf gkg]{ $@ j6f lhNnf klxrfg ul/Psf] 5 hxfF ;/sf/n] ls;fgx¿nfO{ ef}lts;fdflhs b"/L sfod u/L ;'/Iff / ;fjwfgLsf ;fy s[lif ultljlw ;+rfng ug{ ;xh u/fpg' kg]{ b]lvG5 . g]kfnsf] cy{tGqdf ko{6g kl5 t'ngfTds nfesf] b[il6n] w]/} of]ubfg k'/fpg] s[lifhGo s[ofsnfksf] k'g;{\yfkgfsf] nflu ;/sf/n] qmlds ?kdf ns-8fpgnfO{ v's'nf] agfpg] lgtL lng' nfebfoL x'g] of] cg';Gwfgsf] lg:sif{ 5 . * Corresponding authors, E-mail: [email protected] (BM), [email protected] (RA); Tel.: +977- 9841837036 (BM) © RECAST/TU 1 1. Introduction per COVID-19 affected from an isolated household The outbreak of novel coronavirus disease to spread over community and nationwide (New (COVID-19), first discovered in Wuhan, China in Zealand [NZ], 2020). The alert level might be December 2019, declared as a public health different for different regions of country and allow emergency of international concern which had activities as per alert level with necessary infected more than 5.4 million cases and 346,434 precautions. deaths in more than 200 countries and territories The present statistics of active cases, geographic around the world as of 24 May 2020 (World Health distribution along with international exposure, Organization [WHO], 2020). The first epicenter of movement (Wells et al., 2020) and high population COVID-19, Wuhan, issued a city lockdown order on density directed towards the necessity of scientific 23 January 2020, in order to avoid spreading virus to and technological support for efficient risk zoning to other cities of the country. Unfortunately, over the manage and prevent of COVID-19 for economic next 2 months, the virus has been spread globally restoration. GIS and spatial data models have very speedily and each country had resorted to capabilities to identify the spatial transmission of nationwide lockdown to hold transmission and epidemic, spatial control and prevention, resource necessary treatment. Italy made nationwide allocation (Zhou et al., 2020), risk analysis lockdown while U.S. had closed nonessential (Pathirana, 2009), major economic hotspots along businesses and ordered residents to stay home (Ren, with geographic correlation between these variables 2020). It is observed that the simply locking down with disease outbreaks (Mollalo et al,, 2020). the peoples without other interventions is not the The major objective of this paper is to focus on final solution. It might be problematic because of spatial temporal analysis of transmission trend of high unemployment rates and closing of businesses COVID-19, district-wise risk analysis and activity. The economy of every sector will be identification of agriculture hotspots for decision definitely affected adversely. Agriculture sector is making in lockdown relaxation and agro-economic also affected from this pandemic (Sahoo and Rath, reinstatement within country Nepal with limited 2020), when agriculture productivity plays vital role infrastructures and resources to fight against this among main contributors to GDP. These lockdown pandemic. days are also coincided with season of harvesting winter crops and plantation of new summer crops. 2. Materials and Methods So, the lag in any one phase, may simply terminate The study was conducted in 77 districts of whole the entire process of farming thereby leading to Nepal. The updated geometric shapefile of political massive loss in food production (Hossain, 2020). and administrative boundary of Nepal was obtained The higher density of population and potential from Survey Department under Government of mass movement are one of the driven factor for Nepal (DoS, 2020). The study area is geographically spread of pandemic influenza (Merler and Ajelli, located between 26° to 31°N latitudes and 80° to 2009); (Glass and Glass, 2008) whereas restriction in 89°E longitudes. The everyday updated data of travel and/or border control slow-down international COVID-19 cases throughout the nation are collected transmission at early stage (Bajardi et al., 2011; from Ministry of Health and Population daily press Tomba and Wallinga, 2008). Later on, controlled release (MoHP, 2020). The nationwide population internal border plays important role in minimization and population density data of each districts are of patients within domestic region (Wood et al., available on Central Bureau of Statistics for the year 2007). Likewise, effectiveness of quarantine at every of 2011 (CBS, 2014). The major border entry points border entry point relatively reduce risk of releasing are compiled as per establishment of entry/exit infectious individuals into community (Nishiura et points under Department of Immigration. Other land al., 2009). In case of Nepal, for the prevention and entry points at border are digitized with the control of COVID-19, Nepal Government had issued intersection of road network and international a nationwide lockdown order from 24 March 2020 boundary of Nepal. The data related to agriculture and still continues (as of 24 May 2020). Low and productivity of each district for the recent year of middle-income countries are suffering rapid and 2018 was collected from the report of Inter significant economic crisis from spread of COVID- Provincial Dependency for Agricultural 19 and consequent lockdown measures. The experts Development under Department of Agriculture and economists have regularly suggested to (MoALD, 2018). authorities about the gradual relaxation of lockdown, As of 24 May 2020, there are not exact vaccines commencing from agriculture sector (Shrestha, developed for treatment of COVID-19. However, 2020). The New Zealand government had introduced many ongoing scientific trials are evaluating four level alert system, named as PREPARE, potential treatments. The well informed about the REDUCE, RESTRICT and finally LOCKDOWN as symptoms of corona virus disease and keep social 2 distancing slow down its spread locally as well as weighted sum model (WSM) is the simplest and best globally. But COVID-19 has been spread more than multi-criteria decision analysis (MCDA) approach 200 countries around the world and still remains for evaluating number of ranked options from low to unknown about the trajectory of transmission. The high as a decision possibility (Triantaphyllou, 2000; flow of people from foreign countries via land Abdulahi 2020). So, the multi-criteria spatial transportation without necessary medical measures analysis under GIS platform is based on concept of and densely populated urban area having active weighted sum of assigned weights of each region of cases of COVID patients may lead region to high multiple layers.
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