ABSTRACT
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. © 2023 Horizon Research Publishing. All rights reserved.
ABSTRACT
The COVID-19 outbreak was well-controlled in the state of Sarawak, Malaysia in year 2020. A surge in positive cases started in January 2021 and affected all districts including the rural areas which have relatively limited health facilities. Hence, we investigated the spatial patterns of COVID-19 spreading at district level for the first 16 epidemiological weeks of 2021 by spatial autocorrelation analysis and spatial panel regression model. The results show that there exists weak positive spatial autocorrelation of COVID-19 confirmed cases. Having said that, the spatial cluster of high values in both weekly rate of confirmed cases and its spatial lag emerged in the center part of Sarawak in the seventh epidemiological week. Six other districts were identified as high potential for spill overing the disease to its neighbouring districts. Among the six spatial panel regression models constructed, the spatial autoregressive model which includes the spatial lag of COVID-19 confirmed cases, apart from the other two independent variables (recovered and death), is a better-fitting model. This implies that the COVID-19 spreading in the neighbouring districts has a significant effect on the rate of confirmed cases in a particular district of Sarawak. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
In Malaysia, COVID-19 were first detected as imported cases on 25 January and as local infection on 4 February 2020. A surge of positive cases ensued by March 2020 which led to a series of countrywide containment and mitigation measures known as Movement Control Order (MCO). We study the direct effects of MCO on the course of epidemic by analyzing the cumulative and daily infection cases of COVID-19 up to 31 December 2020 in Malaysia and its states using piecewise linear regression and segment neighborhoods algorithm of change-point analysis, respectively. Through piecewise regression on nationwide cases, MCO were likely to almost flatten the epidemic curve in just one month after it was first initiated. While for stateswise cases, the average length of series of concave downward is six months before it turn to concave upward, indicating the period of which deceleration of new cases can be expected. However, the starting of this wave of COVID-19 can be relatively vary for three months in different states and federal territories. Together with change-point analysis on daily cases, the statewise epidemic phases could be subdivided into two to four regimes, whereby the majority of phase transitions fall in April and last quarter of 2020. Overall, the statistical modelling shows that the immediate effect of MCO appears to be effective.