A COMPARISON OF ESTIMATED LAND SURFACE TEMPERATURE FROM LANDSAT 8 BETWEEN DKI JAKARTA AND PEKAT VILLAGE

Land Surface Temperature (LST) shows the general temperature condition of environment and many factors may affect it such as weather, cloud coverage, and sun exposure time. During the Corona Virus pandemic, Indonesia implemented the Pemberlakuan Pembatasan Kegiatan Masyarakat (PPKM) system that restricted many activities and suspected of influencing LST in one or another way. PPKM system itself does not cover every province in Indonesia;thus, it is suspected that LST between areas either do or do not implement PPKM may differ. This paper aims to map and analyze LST between Jakarta Province and Pekat Village before and during implementation of PPKM using descriptive research method with a quantitative approach. The results show that there is a significant temperature change in Jakarta when the PPKM level changes transpires. Pekat Village also experiences temperature changes although it is not affected by PPKM system. Even though there are some data anomalies, the temperature changes are within expectation. Therefore, this concludes that PPKM brought some slight effects toward LST and its changes. © 2023 ICIC International. All rights reserved.

Multiregional, multi-industry impacts of fairness on pandemic policies.

The health and economic crisis caused by the COVID-19 pandemic highlights the necessity for a deeper understanding and investigation of state- and industry-level mitigation policies. While different control strategies in the early stages, such as lockdowns and school and business closures, have helped decrease the number of infections, these strategies have had an adverse economic impact on businesses and some controversial impacts on social justice. Therefore, optimal timing and scale of closure and reopening strategies are required to prevent both different waves of the pandemic and the negative socioeconomic impact of control strategies. This article proposes a novel multiobjective mixed-integer linear programming formulation, which results in the optimal timing of closure and reopening of states and industries in each. The three objectives being pursued include: (i) the epidemiological impact of the pandemic in terms of the percentage of the infected population; (ii) the social vulnerability index of the pandemic policy based on the vulnerability of communities to getting infected, and for losing their job; and (iii) the economic impact of the pandemic based on the inoperability of industries in each state. The proposed model is implemented on a dataset that includes 50 states, the District of Columbia, and 19 industries in the United States. The Pareto-optimal solutions suggest that for any control decision (state and industry closure or reopening), the economic impact and the epidemiological impact change in the opposite direction.

Modeling social, economic, and health perspectives for optimal pandemic policy decision-making.

While different control strategies in the early stages of the COVID-19 pandemic have helped decrease the number of infections, these strategies have had an adverse economic impact on businesses. Therefore, optimal timing and scale of closure and reopening strategies are required to prevent both different waves of the pandemic and the negative economic impact of control strategies. This paper proposes a novel multi-objective mixed-integer linear programming (MOMILP) formulation, which results in the optimal timing of closure and reopening of states and industries in each state to mitigate the economic and epidemiological impact of a pandemic. The three objectives being pursued include: (i) the epidemiological impact, (ii) the economic impact on the local businesses, and (iii) the economic impact on the trades between industries. The proposed model is implemented on a dataset that includes 11 states, the District of Columbia, and 19 industries in the US. The solved by augmented ε-constraint approach is used to solve the multi-objective model, and a final strategy is selected from the set of Pareto-optimal solutions based on the least cubic distance of the solution from the optimal value of each objective. The Pareto-optimal solutions suggest that for any control decision (state and industry closure or reopening), the economic impact and the epidemiological impact change in the opposite direction, and it is more effective to close most states while keeping the majority of industries open during the planning horizon.

NPC1 as a Modulator of Disease Severity and Viral Entry of SARSCoV- 2.

The COVID-19 plague is hitting mankind. Several viruses, including SARS-CoV-1, MERS-CoV, EBOV, and SARS-CoV-2, use the endocytic machinery to enter the cell. Genomic variants in NPC1, which encodes for the endo-lysosomal Niemann-Pick type C1 protein, restricts the host-range of viruses in bats and susceptibility to infections in humans. Lack of NPC1 and its pharmacological suppression inhibits many viral infections including SARS-CoV-1 and Type I Feline Coronavirus Infection. Antiviral effects of NPC1-inhibiting drugs for COVID-19 treatment should be explored.