Spatial Analysis of COVID-19 Potential Spread inside Sub Region of Pare, Kediri Regency
David Suwarno *
aa
Departement of Urban and Regional Planning, Diponegoro University, Professor Soedarto Street, Semarang
ABSTRACT
Pare sub-region consists of seven sub-districts namely Ngasem, Gurah, Pare, Badas, Kandangan, Kepung and Puncu, which have various characteristics in each sub-district, from Pare and Ngasem which are dense and characterized by urban areas to Kandangan which is more tenuous and traditional. These differences in characteristics will certainly affect the potential that exists in each sub-district and what actions must be taken to suppress the potential for coronavirus.
Therefore, an analysis of the potential for coronavirus and actions to deal with it need to be carried out in the Pare Sub- Region. This analysis method itself is overlay and scoring where the expected final results are a map of the potential for coronavirus, a map of the construction for a new hospital, and a map of the lockdown area. From the results of the analysis, it was found that three sub-districts with the greatest potential for coronavirus were Ngasem, Pare, and Gurah.
These three sub-districts are also sub-districts that needs to be lock down. The recommendation that can be given is to prioritize Lockdown as the main program in suppressing the potential for coronavirus. This lockdown program itself should focus on areas nearby Kediri City in Ngasem and Kampung Inggris area.
Keywords: coronavirus, potential, spatial, pare, lockdown
1. INTRODUCTION
Settlements of each part of the city or region are not the same in terms of accessibility, density, or the center of the crowd. The condition of these settlements will certainly cause differences between settlements in different regions. Of course, this difference results in differences in the susceptibility to the spread of a disease in each region. Non-natural disaster potential analysis is an analysis conducted to determine whether an area has a high potential for disaster or not.
In this case study, the authors chose Kediri district not without reason but because at the time of the research, the city of Surabaya which was close to Kediri district had the status of a black zone. One sub-district in Kediri Regency was selected as the main sub-district and six other sub-districts with various levels of density were selected to compare the condition of the sub-districts. The selection of Pare District was due to several things, namely:
1. It is the sub-district most frequently visited by tourists;
2. It is a sub-district with the highest number of strata one health facilities; and 3. It is a sub-district with a lot of trade and service activities.
The Pare sub-region consists of seven sub-districts namely Ngasem, Gurah, Pare, Badas, Kandangan, Kepung and Puncu. The Pare sub-region is an area unit that has various characteristics in each sub-district, ranging from dense and urban Pare and Ngasem to Kandangan which is more tenuous and traditional. These differences in characteristics will certainly affect the potential that exists in each sub-district and what actions must be taken to suppress the Coronavirus potential. Therefore, an analysis of the potential for Coronavirus and actions to deal with it need to be carried out in the Pare Sub-Region.
*[email protected]; phone 62 823 2223-9628;
Figure 1. Sub-Regional Pare Administration Map.
The Pare sub-region consists of seven sub-districts namely Ngasem, Gurah, Pare, Badas, Kandangan, Kepung and Puncu. The Pare sub-region is an area unit that has various characteristics in each sub-district, ranging from dense and urban Pare and Ngasem to Kandangan which is more tenuous and traditional. These differences in characteristics will certainly affect the potential that exists in each sub-district and what actions must be taken to suppress the Coronavirus potential. Therefore, an analysis of the potential for Coronavirus and actions to deal with it need to be carried out in the Pare Sub-Region.
2. THEORY
2.1 Disaster
Disaster is a phenomenon resulting from sudden changes in an ecosystem in a relatively short time. Ecosystem changes that occur and harm property and human life can also occur slowly, such as in a drought [1]. Law Number 24 of 2007 concerning Disaster Management describes disaster as an event or series of events that threatens and disrupts people's lives and livelihoods caused, both by natural factors and or non-natural factors as well as human factors that result in human casualties, environmental damage, property loss, and psychological impact [2].
Disasters can be grouped into three types of disasters, namely natural disasters, non-natural disasters, and social disasters. Indonesia is a country that has potential in all three types of disasters. Several types of natural disasters that occur in Indonesia include earthquakes, tsunamis, floods, volcanoes, land movements, droughts, abrasion, erosion, and extreme weather. Non-natural disasters can take the form of technological failures, epidemics and disease outbreaks. As for social disasters, the existing forms are social conflict and terrorism. Disaster potential is a condition in which an area has the seeds or potential for the occurrence of a certain disaster [3].
Epidemic and disease outbreaks have another name, namely Pandemic. Pandemic itself has an understanding as the spread of a disease or epidemic that moves across the territory of countries and is a large-scale epidemic. Black Plague, Asian Flu, Spanish Flu, Hong Kong Flu, HIV/AIDS, Dengue Fever, Smallpox, Cholera, Severe Acute Respiratory
Syndrome (SARS), Middle East Respiratory Syndrome (MERS), Swine Flu (H1N1), Avian Influenza (H7N9) , Ebola, Zika, are a series of cases due to viruses that have attacked throughout the history of epidemic and pandemic cases in the world [4].
2.2 Corona Virus
Corona itself is characterized by symptoms of a dry cough and fever then within seven to 14 days the condition gets worse and has difficulty breathing. Humans with a good immune system will recover faster, but it is different with the condition of the immune system that is not good or in a bad condition coupled with improper handling or even one that is not handled at all [5].
There are several factors in determining the potential for non-natural disasters of the Corona virus, namely ([5]:
1. Number of Population Infected with Covid
The increasing number of residents and the closer distance causes the interaction of the population to be higher.
Thus, the potential for transmission from these areas is also getting higher and this must be watched out for [6].
2. Population Density
High population density indicates the frequent interaction of people with one another. This high density also indicates the wide area available for small people so that the distance between one person and another is quite close [7]. This makes it easier for Coronavirus to spread [5].
3. Proximity to Market
Market is the center of the crowd that is often visited by the community to meet their daily needs. Crowd centers are one of the places that are prone to the spread of Coronavirus [8].
4. Accessibility
Easy accessibility makes people more inclined to travel. This traveling activity can lead to the spread of Coronavirus [9].
5. Proximity to Hospital
The existence of the hospital will cause residents who feel sick to be quickly quarantined and not cause further spread. Proximity to the hospital will result in the distance that needs to be reached from the settlement closer so that the spread that occurs is also less likely than distant places [5].
This analysis is carried out with geographic information systems or GIS, more specifically, overlay techniques. GIS (Geographic Information System) is an organized collection of computer hardware, software, and geographic data, designed to obtain, store, repair, manipulate, analyze, and display all forms of geographically referenced information.
The principle of data processing in GIS can be described by means of overlaying several thematic maps drawn on transparency paper placed on an overhead projector (OHP). The overlay technique is a data handling system in a digital way, namely by combining several maps that contain the information required for a type of analysis required [10].
3. METHODOLOGY
Data acquisition was done through the web of geospatial information agencies, residents exposed to Coronavirus published by Kediri, and Google Maps. The analysis performed is overlay and scoring, with the score values as follows:
Table 1. Corona Virus Potential Scoring.
Parameter Values Score Weight
Number of Population Infected with Covid
Very Low 1
20%
Low 2
Medium 3
High 4
Very High 5
Population Density
<10 souls/Ha 1
25%
10-20 souls/Ha 2
20-30 souls/Ha 3
30-40 souls/Ha 4
>40 souls/Ha 5
Proximity to Market
0-300 m 5
300-750 m 3 20%
>750 m 1
Accessibility
0-100 m 5
100-300 m 3 20%
>300 m 1
Proximity to Hospital
0-400 m 1
400-1000 m 3 15%
>1000 m 5
Analysis of proximity to the market, accessibility, and proximity to hospitals was carried out using multiple ring buffer analysis. The population density analysis itself is obtained from the number of residents of the village or kelurahan divided by the area of the village or kelurahan. To get the number of people exposed to Coronavirus, this is done by analyzing the kernel density data of the existing Coronavirus and reclassifying it into five classes. Kernel Density Method Kernel density is one type of calculation model that is used to measure the density of a certain thing non- parametrically that can be done in GIS applications [11]. The final results of the existing weighting are as follows:
Table 2. Corona Virus Potential Scoring Results.
Score Corona Virus Potentiality
1 Very Low
2 Low
3 Medium
4 High
5 Very High
Figure 2. The Process of Analyzing the Potential for Coronavirus in the Pare Sub-Region.
The map of the location for the construction of a new hospital as a step to reduce the potential for Coronavirus was obtained by looking at areas with high Coronavirus potential, few hospitals, and land use of shrubs or settlements. Rice fields are not changed because this land is counted as a non-renewable resource by some experts. This lockdown area map is obtained by looking at the location of the road with a radius of 150 m which is in a high potential location.
4. RESULTS AND DISCUSSION
Figure 3. The Process of Analyzing the Potential for Coronavirus in the Pare Sub-Region.
Table 3. Area and Percentage of Coronavirus Potentiality.
Sub-Distict Potentiality of Coronavirus Area (Ha) Coronavirus Potentiality Percentage
Very Low Low Medium High Very
High Very
Low Low Medium High Very
High Badas 10,77 3176,35 1064,37 10,76 - 0,25% 74,52% 24,97% 0,25% 0,00%
Gurah 0,14 4309,74 1012,59 107,11 - 0,00% 79,38% 18,65% 1,97% 0,00%
Kandangan 1091,12 4447,34 434,85 - - 18,27% 74,45% 7,28% 0,00% 0,00%
Kepung 2246,64 5673,4 1090,56 7,24 - 24,91% 62,91% 12,09% 0,08% 0,00%
Ngasem - 188,58 1539,67 620,49 45,39 0,00% 7,88% 64,31% 25,92
% 1,90%
Pare 2,44 2426,71 2341,59 227,92 - 0,05% 48,55% 46,84% 4,56% 0,00%
Puncu 2310 6597,53 555,16 4,63 - 24,40% 69,69% 5,86% 0,05% 0,00%
The results of the analysis of the potential for Coronavirus in the Pare Sub-Region show that the sub-district with the most Coronavirus potential is Ngasem District, while the sub-district with the lowest Coronavirus potential is Kandangan District. This Ngasem sub-district is also the only sub-district in the Pare sub-region that has a very high Covid potential.
From the results of this analysis, it is necessary to implement policies in sub-districts with high Coronavirus potential, namely Ngasem, Pare, and Gurah sub-districts; because these three sub-districts have the highest potential among the seven sub-districts in the Pare Sub-District. This policy of suppressing the potential for Coronavirus can be in the form of building new hospitals or locking certain areas. The subject of building a new hospital is beyond this scope, in order to be able to build a new hospital we will also need the land price map, the geological structure, type of soil map, and the approximate price for building it.
Figure 4. Lockdown Area Map.
Table 4. Lockdown Area.
Sub-disrict Lockdown Area (Ha)
Badas 10,76
Gurah 83,86
Kandangan -
Kepung 7,24
Ngasem 481,51
Pare 219,32
Puncu 4,63
Lockdown in order to suppress the potential for Coronavirus should be carried out in Ngasem District near urban areas.
This is because this sub-district is directly adjacent to the city of Kediri so that there are frequent inflows and outflows of residents. The lockdown area of Ngasem District itself, according to the results of the analysis that has been carried out, is the widest (481.51 Ha) compared to other sub-districts in Pare Sub-District. The results of this analysis also show that the lockdown in Pare District itself was carried out in the Kampung Inggris area (219.32 Ha) which is often passed by tourists from inside and outside. The Lockdown of Gurah District itself is only in a relatively small area compared to the other two sub-districts, which is 83.86 Ha.
5. CONCLUSION
The highest potential for Coronavirus in the Pare Sub-District is Ngasem District, Pare District, and Gurah District.
These three sub-districts need further action with the construction of new hospitals and a lockdown. The lockdown itself is located close to the City of Kediri in Ngasem District, the Kampung Inggris Area in Pare District, and several small areas of Gurah District. The recommendation that can be given is the procurement of Lockdown as the main program in suppressing the potential for Coronavirus because it is considered cheaper than the construction of a new hospital. This lockdown program itself should focus on areas near Ngasem city and Kampung Inggris.
REFERENCES
[1] N. S. Sinaga, “Peran Petugas Kesehatan Dalam Manajamen Penanganan Bencana Alam,” J. Ilm.
“INTEGRITAS” Vol, vol. 1, no. 1, 2015.
[2] B. N. P. Bencana, “Undang-Undang Nomor 24 Tahun 2007 Tentang Penanggulangan Bencana,” Jakarta Badan Nas. Penanggulangan Bencana, 2007.
[3] A. Z. Rahman, “Kajian mitigasi bencana tanah longsor di Kabupaten Banjarnegara,” Gema Publica J. Manaj.
dan Kebijak. Publik, vol. 1, no. 1, pp. 1–14, 2015.
[4] A. R. C. Muis, “Transparansi Kebijakan Publik Sebagai Strategi Nasional Dalam Menanggulangi Pandemi Covid-19,” SALAM J. Sos. dan Budaya Syar-i. core. ac. uk. https//core. ac. uk/download/pdf/325992704. pdf, 2020.
[5] A. Yusup, “PEMETAAN SEBARAN, POTENSI DAN KERENTANAN PANDEMI COVID-19 DI KECAMATAN LEMBANG KABUPATEN BANDUNG BARAT,” Academia, 2020.
[6] S. Fadjarajani, “Peranan Geografi dalam Analisis Sebaran Covid-19,” in Prosiding Seminar Nasional Hardiknas, 2020, vol. 1, pp. 71–78.
[7] B. Supraptono, B. Sumiarto, and D. Pramono, “Interaksi 13 Faktor Risiko Leptospirosis,” Ber. Kedokt. Masy., vol. 27, no. 2, pp. 55–65, 2011.
[8] N. Widyaningrum, Y. D. Putri, and others, “GAMBARAN PENERAPAN PHYSICAL DISTANCING SEBAGAI UPAYA MENEKAN PERSEBARAN COVID-19 DI PROVINSI DAERAH ISTIMEWA YOGYAKARTA,” Nusant. J. Ilmu Pengetah. Sos., vol. 7, no. 2, pp. 470–481, 2020.
[9] D. N. Yuzar, “Penyakit Menular Dan Wabah Penyakit Covid-19,” 2020.
[10] D. L. Setyowati, “Kajian Evaluasi Kesesuaian Lahan Permukiman dengan Teknik Sistem Informasi Geografis (SIG),” J. Geogr. Media Inf. Pengemb. dan Profesi Kegeografian, vol. 4, no. 1, 2007.
[11] I. Iwan Rudiarto, “Dinamika Persebaran Penduduk Jawa Tengah: Perumusan Kebijakan Perwilayahan Dengan Metode Kernel Density,” Din. Persebaran Pendud. Jawa Teng. Perumusan Kebijak. Perwilayahan Dengan Metod. Kernel Density, 2016.
ATTACHMENT
Figure 5. Coronavirus Spread Map
Figure 6. Population Density Map
Figure 7. Accessibility Map
Figure 8. Market Accessibility Map
Figure 9. Hospital Accessibility Map
Figure 10. Landuse Map
