This paper attempts to ascertain the impacts of population density on the spread and severity of COVID-19 in Malaysia. Besides describing the spatio-temporal contagion risk of the virus, ultimately, it seeks to test the hypothesis that higher population density results in exacerbated COVID-19 virulence in the community. The population density of 143 districts in Malaysia, as per data from Malaysia’s 2010 population census, was plotted against cumulative COVID-19 cases and infection rates of COVID-19 cases, which were obtained from Malaysia’s Ministry of Health official website. The data of these three variables were collected between 19 January 2020 and 31 December 2020. Based on the observations, districts that have high population densities and are highly inter-connected with neighbouring districts, whether geographically, socio-economically, or infrastructurally, tend to experience spikes in COVID-19 cases within weeks of each other. Using a parametric approach of the Pearson correlation, population density was found to have a moderately strong relationship to cumulative COVID-19 cases (p-value of 0.000 and R2 of 0.415) and a weak relationship to COVID-19 infection rates (p-value of 0.005 and R2 of 0.047). Consequently, we provide several non-pharmaceutical lessons, including urban planning strategies, as passive containment measures that may better support disease interventions against future contagious diseases.

A 27-yr-old lady with a past history of prolonged ventilation presented with worsening respiratory distress caused by tracheal stenosis. She required urgent tracheal resection and reconstruction. Because of the risk of an acute respiratory obstruction, spinal anaesthesia was used to establish cardiopulmonary bypass by cannulating the femoral artery and femoral vein. Adequate gas exchange was possible with full flow rate. Thoracotomy was then carried out to mobilize the left main bronchus. After successfully securing an airway by intubation of the left main bronchus, cardiopulmonary bypass was discontinued and tracheal resection and anastomosis was done under conventional one lung anaesthesia.

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Analyzing population and employment sizes at the local finer geographic scale of transit station areas offers valuable insights for cities in terms of developing better decision-making skills to support transit-oriented development. Commonly, the station area population and employment have been derived from census tract or even block data. Unfortunately, such detailed census data are hardly available and difficult to access in cities of developing countries. To address this problem, this paper explores an alternative technique in remote estimation of population and employment by using building floor space derived from an official administrative geographic information system (GIS) dataset. Based on the assumption that building floor space is a proxy to a number of residents and workers, we investigate to what extent they can be used for estimating the station area population and employment. To assess the model, we employ five station areas with heterogeneous environments in Tokyo as our empirical case study. The estimated population and employment are validated with the actual population and employment as reported in the census. The results indicate that building floor space, together with the city level aggregate information of building morphology, the density coefficient, demographic attributes, and real estate statistics, are able to generate a reasonable estimation.

This paper attempts to examine the factors affecting the COVID-19 pandemic situation in Malaysia. It investigates three major factors (social, economy and environment). Thirteen States and two Federal Territories of Malaysia were considered; and the data for the attributes of each major factor are derived from the official reports from the Department of Statistics Malaysia. Meanwhile, the infection rate and mortality rate of COVID-19 cases were obtained from the Ministry of Health, Malaysia. Using non-parametric statistical approach, the several interesting results are identified. Firstly, for the social factor, we found that the percentage of non-citizens has a positive relationship with both COVID-19 infection rate and mortality rate. Further, the number of students per teacher have a positive relationship with COVID-19 infection rate. Second, in terms of the economy factor, primary industry has a negative relationship with COVID-19 infection rate. Third, in the matter of social factor, it is found that population density and percentage of high-rise residential unit are positively related with COVID-19 infection rate. The result from this study can provides an insight for policymakers to understand factors contribute on the spread and severity of COVID-19 to informing better mitigation policy and control measures.

This paper outlines the lessons learnt through the multidisciplinary 'Science-to-Action' approach to formulating, mainstreaming and implementing the Low Carbon Society Blueprint for Iskandar Malaysia 2025 (LCSBP-IM2025). Iskandar Malaysia (IM) is a rapidly developing urban region in southern Peninsular Malaysia that was institutionalised in 2006 with a view to spurring Malaysia's economic growth up to 2025. In pursuing rapid economic growth to become a developed, high-income nation by 2020, Malaysia is conscious of its global responsibility in environmental protection and global climate change mitigation, hence the country's commitment to reducing its carbon emission intensity of GDP by up to 40 % by 2020 based on the 2005 level. Being a premier economic region in Malaysia, IM seeks to develop a low carbon society (LCS) and lead the way to cutting its carbon emission intensity by up to 58 % by 2025 based on the 2005 level through the implementation of the LCSBP-IM2025. The LCSBP-IM2025 is the outcome of an internationally funded joint research under the SATREPS programme that brings together Universiti Teknologi Malaysia (UTM), Kyoto University, Japan's National Institute for Environmental Studies (NIES), Okayama University and the Iskandar Regional Development Authority (IRDA), in a unique 'academia-policymaker' partnership, towards crafting an LCS pathway to guide and sustainably manage the projected rapid development in IM up to 2025. To that end, a multidisciplinary research team that comprises the above research institutions and IRDA, led by UTM, has been set up. A methodology has

Prior to the COVID-19 outbreak, obesity is already a pandemic illness on its own. It has been a public health priority in developing countries especially Malaysia where the obesity rate in the country is one of the highest in South East Asia. Early studies have concurred that the presence of COVID-19 makes anatomising the obesity pandemic even more urgent as impaired metabolic health increase complications and mortality in COVID-19 patients. COVID-19 induced movement restriction orders and related policies by the Malaysia government are believed to have altered the country’s food and physical activity environments. The paper expanded the original Neighbourhood Environment, Health Behaviours and BMI (NEHB-BMI Model) where the pathways of neighbourhood obesogenic environment that reflects COVID-19 induced changes to the constructs from the perspective of Malaysia is presented. Through the discussion, three key variables were added to the model: 1) government environment; 2) establishment/business environment; and 3) individual psychosocial factors. Exploring the impacts of COVID-19 to the obesogenic environment constructs paves way to gauging insights by allowing associations between the presented variables to be tested in future studies, especially in the South East Asian region where such studies are very limited.