Spatial Panel Data Modelling of COVID-19 Spreading at District Level in Sarawak, Malaysia

Phang, Piau; Labadin, Jane; Rahman, Shapiee Abd

doi:10.1007/978-981-16-8515-6_34

Cited by 2 publications

(2 citation statements)

References 23 publications

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“…Although several spatial modelling and regression studies had been conducted at the district level in Malaysia [ 30 – 32 ], they only investigated the diseases evolution until February 2021. Therefore, this present study not only extends our previous work [ 33 ] on Sarawak by analyzing four different temporal periods throughout 2021, but also considers several potential socio-demographic indicators suggested in previous work [ 31 ].…”

Section: Introductionmentioning

confidence: 69%

Exploration of spatiotemporal heterogeneity and socio-demographic determinants on COVID-19 incidence rates in Sarawak, Malaysia

et al. 2023

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Background In Sarawak, 252 300 coronavirus disease 2019 (COVID-19) cases have been recorded with 1 619 fatalities in 2021, compared to only 1 117 cases in 2020. Since Sarawak is geographically separated from Peninsular Malaysia and half of its population resides in rural districts where medical resources are limited, the analysis of spatiotemporal heterogeneity of disease incidence rates and their relationship with socio-demographic factors are crucial in understanding the spread of the disease in Sarawak. Methods The spatial dependence of district-wise incidence rates is investigated using spatial autocorrelation analysis with two orders of contiguity weights for various pandemic waves. Nine determinants are chosen from 14 covariates of socio-demographic factors via elastic net regression and recursive partitioning. The relationships between incidence rates and socio-demographic factors are examined using ordinary least squares, spatial lag and spatial error models, and geographically weighted regression. Results In the first 8 months of 2021, COVID-19 severely affected Sarawak’s central region, which was followed by the southern region in the next 2 months. In the third wave, based on second-order spatial weights, the incidence rate in a district is most strongly influenced by its neighboring districts’ rate, although the variance of incidence rates is best explained by local regression coefficient estimates of socio-demographic factors in the first wave. It is discovered that the percentage of households with garbage collection facilities, population density and the proportion of male in the population are positively associated with the increase in COVID-19 incidence rates. Conclusion This research provides useful insights for the State Government and public health authorities to critically incorporate socio-demographic characteristics of local communities into evidence-based decision-making for altering disease monitoring and response plans. Policymakers can make well-informed judgments and implement targeted interventions by having an in-depth understanding of the spatial patterns and relationships between COVID-19 incidence rates and socio-demographic characteristics. This will effectively help in mitigating the spread of the disease.

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Section: Introductionmentioning

confidence: 69%

Exploration of spatiotemporal heterogeneity and socio-demographic determinants on COVID-19 incidence rates in Sarawak, Malaysia

et al. 2023

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“…Although several spatiotemporal modeling on district-wise aggregated COVID-19 data were carried out in Malaysia [18][19][20] and specifically for Sarawak [21], to our best knowledge, no such geo-visualization and geospatial analysis were performed for COVID-19 exposed location point data within a division in Sarawak. Motivated by several studies on examining the distribution of the contagion by COVID-19 in urban environments of a city in Spain [22] and China [23] using authentic but anonymized microdata of infected people, this paper illustrates the utility of QGIS on geospatial visualization and analysis for the communication of publicly available COVID-19 exposed location data in Kuching, Sarawak.…”

Section: Introductionmentioning

confidence: 99%

Geo-visualization of Sarawak COVID-19 Publicly Available Data Employing Open-source Geospatial Software

Phang¹,

Yap²,

Zakaria³

et al. 2023

ujph

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The state government of Sarawak with the help of the Sarawak Disaster Management Committee (SDMC) has continuously made the updated information on the state COVID-19 situation and its ensuing control measures available to general public in the form of daily press statements. However, these statements are merely providing textual information on daily basis though the data are in fact rich in temporal and spatial properties. Since the onset of COVID-19 pandemic, spatiotemporal analysis becomes the key element to better understand the spread of COVID-19 in various spatial levels worldwide. Hence, there is an urgent need to convert this textual information into more valuable insights by applying geo-visualization techniques and geospatial statistics. The paper demonstrates the prospect of retrieving geospatial data from publicly available document to locate, map and analyze the spread of COVID-19 up to division level of Sarawak. Specifically, map visualization and geospatial statistical analysis are performed for the list of exposed locations, which are indeed locations visited by COVID-19 patients prior to being tested positive in Kuching division, using open-source geospatial software QGIS. It is found that these exposed locations concentrate on the build-up areas in the division and are in south-west to north-east direction of the center of Kuching in September and October 2021. Despite the number of exposed locations published is relatively small compared to the number of confirmed cases reported, both are nearly strongly correlated. The insights gained from such geospatial analysis may assist the local public health authorities to impose applicable disease control interventions at division level.

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Spatial Panel Data Modelling of COVID-19 Spreading at District Level in Sarawak, Malaysia

Cited by 2 publications

References 23 publications

Exploration of spatiotemporal heterogeneity and socio-demographic determinants on COVID-19 incidence rates in Sarawak, Malaysia

Exploration of spatiotemporal heterogeneity and socio-demographic determinants on COVID-19 incidence rates in Sarawak, Malaysia

Geo-visualization of Sarawak COVID-19 Publicly Available Data Employing Open-source Geospatial Software

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