Open Access Open Access  Restricted Access Subscription or Fee Access

Spatio-Temporal Spread of Covid-19 in Children Aged 0-11 Years at Central Java Province Indonesia Using Geographical Weight Regression


(*) Corresponding author


Authors' affiliations


DOI: https://doi.org/10.15866/iremos.v15i6.22048

Abstract


During the COVID-19 pandemic, children under the age of 12 are the most vulnerable age group to health concerns. The goal of this study was to conduct a spatiotemporal analysis of the distribution of COVID-19 cases in Central Java children using the GWR (Geographically Weighted Regression) approach. The data source is the Central Java Provincial Health Office, and the study objects are 35 cities and districts in Central Java province. The data obtained are the number of COVID-19 cases in children aged 0-11 years, the total number of Covid-19 cases, the number of PCR tests per day, the number of vaccinations and the number of health care facilities per city and district per month from March 2020 to November 2021. Hotspot analysis and the GWR approach were used to examine data in semesters 1–4 (S1–S4). From S1 to S4, the number of COVID-19 cases in children increased. Areas that became hotspots for more than two semesters were Semarang City, Semarang Regency, Banyumas, Cilacap, Kendal, and Demak. According to the GWR analysis in S1-S4, the total number of COVID-19 cases, PCR tests per day, vaccinations, and health care facilities all affect the number of COVID-19 patients in children by more than 75%. The total number of COVID-19 cases has a significant impact on the number of COVID-19 cases in children but the number of health care facilities has no effect. The results of the GWR prediction of COVID-19 cases in children show that the cities of Semarang and Banyumas became areas with a larger number of COVID-19 cases in two semesters.  According to the hotspot and GWR analysis, the cities of Semarang and Banyumas are regions to be on the lookout for in the spread of COVID-19 cases in S1-S4.
Copyright © 2022 Praise Worthy Prize - All rights reserved.

Keywords


Spatio Temporal; Hotspot; GWR; COVID-19; Children

Full Text:

PDF


References


WHO, "WHO Coronavirus (COVID-19) Dashboard," , 2022 [cited 2022 Mar 14]. Available from:
https://covid19.who.int/table

Satgas Penanganan Covid, Peta Sebaran, 2022 [cited 2022 Mar 14]. Available from: https://covid19.go.id/peta-sebaran

A. A. Kelvin and S. Halperin, COVID-19 in children: the link in the transmission chain, Lancet Infect. Dis., vol. 20, no. 6, pp. 633-634, 2020.
https://doi.org/10.1016/S1473-3099(20)30236-X

Kompas, IDAI: Kematian Anak Indonesia Akibat Covid-19 Tertinggi di Dunia, Kompas.com, 2021.

T. Singh et al., Lessons from COVID-19 in Children: Key Hypotheses to Guide Preventative and Therapeutic Strategies, Clin. Infect. Dis., vol. 71, no. 8, pp. 2006-2013, 2020.
https://doi.org/10.1093/cid/ciaa547

Y. Dong et al., Epidemiology of COVID-19 among children in China, Pediatrics, vol. 145, no. 6, pp. 1-10, 2020.
https://doi.org/10.1542/peds.2020-0702

T. Nie, G. Dong, X. Jiang, and Y. Lei, Spatio-temporal changes and driving forces of vegetation coverage on the loess plateau of Northern Shaanxi, Remote Sens., vol. 13, no. 4, pp. 1-17, 2021.
https://doi.org/10.3390/rs13040613

N. Khotimah, D. R. S. Sumunar, S. Purwantara, N. Arif, and N. Nayan, Spatial Analysis of Covid-19 Distribution: Case studies in Indonesia and Malaysia, IOP Conf. Ser. Earth Environ. Sci., vol. 884, no. 1, pp. 1-11, 2021.
https://doi.org/10.1088/1755-1315/884/1/012059

Q. Wang et al., Temporal and spatial analysis of COVID-19 transmission in China and its influencing factors, Int. J. Infect. Dis., vol. 105, pp. 675-685, 2021.
https://doi.org/10.1016/j.ijid.2021.03.014

Santosh, K.C. COVID-19 Prediction Models and Unexploited Data. J Med Syst 44, 170 (2020).
https://doi.org/10.1007/s10916-020-01645-z

Y. Liu, Z. He, and X. Zhou, Space-Time variation and spatial differentiation of COVID-19 confirmed cases in Hubei Province based on extended GWR, ISPRS Int. J. Geo-Information, vol. 9, no. 9, p. 536, 2020.
https://doi.org/10.3390/ijgi9090536

X. Wu and J. Zhang, Exploration of spatial-temporal varying impacts on COVID-19 cumulative case in Texas using geographically weighted regression (GWR), Environ. Sci. Pollut. Res., vol. 28, no. 32, pp. 43732-43746, 2021.
https://doi.org/10.1007/s11356-021-13653-8

Dinas Kesehatan Provinsi Jawa Tengah., Buku Data Dasar Puskesmas & Rumah Sakit, 2022 [cited 2022 Mar 17]. Available from:
http://dinkesjatengprov.go.id/v2018/data-dasar-2/

S. MohammadEbrahimi et al., Geospatial epidemiology of hospitalized patients with a positive influenza assay: A nationwide study in Iran, 2016-2018, PLoS One, vol. 17, no. 12, p. e0278900, 2022.
https://doi.org/10.1371/journal.pone.0278900

M. Fatima, I. Butt, and S. Arshad, Geospatial clustering and hot spot detection of malaria incidence in Bahawalpur district of Pakistan, GeoJournal, vol. 87, no. 16, pp. 4791-4806, 2021.
https://doi.org/10.1007/s10708-021-10535-x

A. Comber et al., A Route Map for Successful Applications of Geographically Weighted Regression, Geogr. Anal., pp. 155-178, 2022.
https://doi.org/10.1111/gean.12316

J. Mallick et al., Evaluating the ndvi-rainfall relationship in bisha watershed, saudi arabia using non-stationary modeling technique, Atmosphere (Basel)., vol. 12, no. 5, p. 593, 2021.
https://doi.org/10.3390/atmos12050593

L. M. Pfiester, R. G. Thompson, and L. Zhang, Spatiotemporal exploration of Melbourne pedestrian demand, J. Transp. Geogr., vol. 95, no. April, p. 103151, 2021.
https://doi.org/10.1016/j.jtrangeo.2021.103151

J. Liu, M. Yue, Y. Liu, D. Wen, and Y. Tong, The Impact of Tourism on Ecosystem Services Value: A Spatio-Temporal Analysis Based on BRT and GWR Modeling, Sustain., vol. 14, no. 5, pp. 1-17, 2022.
https://doi.org/10.3390/su14052587

M. T. Rahman, A. Jamal, and H. M. Al-Ahmadi, Examining hotspots of traffic collisions and their spatial relationships with land use: A GIS-based geographically weighted regression approach for Dammam, Saudi Arabia, ISPRS Int. J. Geo-Information, vol. 9, no. 9, pp. 1-22, 2020.
https://doi.org/10.3390/ijgi9090540

M. Malahayati, T. Masui, and L. Anggraeni, An assessment of the short-term impact of COVID-19 on economics and the environment: A case study of Indonesia, EconomiA, vol. 22, no. 3, pp. 291-313, 2021.
https://doi.org/10.1016/j.econ.2021.12.003

D. Aldila, B. M. Samiadji, G. M. Simorangkir, S. H. A. Khosnaw, and M. Shahzad, Impact of early detection and vaccination strategy in COVID-19 eradication program in Jakarta, Indonesia, BMC Res. Notes, vol. 14, no. 1, pp. 1-7, 2021.
https://doi.org/10.1186/s13104-021-05540-9

Howard‐Jones, COVID‐19 in children I Epidemiology prevention and indirect impacts.pdf, J Paediatr. Child Heal., vol. 58, pp. 39-45, 2022.
https://doi.org/10.1111/jpc.15791

P. Purwanto et al., Spatiotemporal analysis of COVID-19 spread with emerging hotspot analysis and space-time cube models in East Java, Indonesia, ISPRS Int. J. Geo-Information, vol. 10, no. 3, p. 133, 2021.
https://doi.org/10.3390/ijgi10030133

T. P. A. P. Mursito, M. C. Berlianto, Yoosove, I. S. Edbert, and M. C. Berlianto, Modeling the Amount of Poverty in Central Java using Geographically Weighted Regression, 2022 Int. Conf. Sci. Technol. IEEE, vol. February, p. 17, 2022.
https://doi.org/10.1109/ICOSTECH54296.2022.9828815

Baliś, B., Byrski, A., Dekster, L., Frącz, W., Giebułtowicz, J., Kisiel-Dorohinicki, M., Mendyk, A., Pawlik, M., Piotrowski, R., Turek, W., Wiśniowska, B., Polak, S., Drug Therapy Optimization System Based on a Hybrid Approach Combining Clinical Data and In Silico Modeling - Perspective View and Concept Description, (2020) International Review on Modelling and Simulations (IREMOS), 13 (4), pp. 234-242.
https://doi.org/10.15866/iremos.v13i4.19200

Midoun, M., Amrani-Midoun, A., Analysis of Spatiotemporal Pattern for COVID‐19 in Algeria Using Space‐Time-Cubes, (2022) International Review on Modelling and Simulations (IREMOS), 15 (1), pp. 27-35.
https://doi.org/10.15866/iremos.v15i1.21282


Refbacks

  • There are currently no refbacks.



Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize