The outbreak of 2019 novel coronavirus disease (COVID-19) is a public health emergency of international concern. • The ability to detect disease in their early stages is a key component of efficient disease control and prevention. • The research focuses to develop a transparent user-friendly method to simulate spatial-temporal disease outbreak data. • GIS techniques, resources, and methods can be used in Pakistan for more effective investigation of disease. • It is quite easy for authorities to locate the highly effected area and take appropriate actions in that particular areas.
Abstract:This study uses the data from 157 countries from 1960 to 2014 to analyze the relationship between economic growth, electricity consumption, oil prices, capital, and labor. The economic growth of developing countries with industrial infrastructure has a more significant association with electricity consumption than oil prices. We use oil prices and electricity consumption jointly to study highly predictive observations for economic growth. The data are categorized by income, OECD and regional levels. The panel cointegration, long-run parameter estimation, and Pool Mean Group testsare used to analyze the cointegration and short-run and long-run relationships between the variables. The empirical results indicate the presence of cointegration between the variables. The presence of feedback effects between electricity consumption and economic growth, oil prices and economic growth is valid. These findings confirm that inspite of the oil prices, developing countries rely heavily on electricity consumption for economic growth. In the short run, growth and feedback effects suggest that more vigorous electricity policies should be implemented to attain sustainable economic growth for the long-term.
Innovation and globalization fosters a tendency towards multiparty collaboration and strategic contacts among nations. A similar path was followed by the Chinese administration in 2013, with its “Belt and Road Initiative” (BRI). The most important objective of the present fact-finding study was to demonstrate the links between economic growth, energy consumption, urbanization, gross fixed capital formation, trade openness, financial development and carbon emissions (ecological degradation) from a panel of 47 BRI economies, over a time span of 1980 to 2016. Dynamic panel estimations (dynamic ordinary least square (DOLS) and fully modified ordinary least square (FMOLS)) were engaged to examine the long-run links between the subjected variables. Synchronized outcomes for the full panel show that energy consumption, gross fixed capital formation, economic growth, financial development, and urbanization unfavorably led to environmental degradation (CO2 emissions). However, trade openness is negatively correlated with emissions. Furthermore, pairwise panel Granger causative estimations justified bi-directional links from all regressors towards CO2 emissions, except for trade openness, which had unidirectional ties with environmental quality. In cross-country, long-run assessments, different results were found, with CO2 emissions being greatly increased by economic growth in all countries and energy consumption in 30 countries; other predictors testified to some mixed interactions with CO2 emissions in the country-level examination. The reported investigation provides some noteworthy guiding principles and policy inferences aimed at governments and ecological supervisory administrations, suggesting assertive moves towards truncated used of carbon fossil fuels and dependency on renewable energy, establishing waste and water treatment plants, familiarizing themselves with the concept of a green economy, and making the general public aware of eco-friendly investments in BRI economies.
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