The influences of global geographical climate towards COVID-19 spread and death

ABSTRACT

As the world’s coronavirus disease 2019 (COVID-19) case total and death toll continue to climb, an increasing data collection and analysis are providing insights into the pandemic. Although outbreaks continue to develop rapidly, and researchers' understanding of the virus is increasing, a consensus is emerging on certain main aspects of the spread, symptoms, and deadliness of the virus. Enormous global data distribution on COVID-19 is made available online with a combination of global climate data, which creates an opening for further analysis to be conducted. To date, the global climate change has been studied widely, particularly regarding its influences on the distribution of species. This reflects the need for an analysis that is best suited to big data analysis which offers high performance and efficiency in understanding this pandemic issue. The state-of-art in data mining and statistics areas show that the adaptation of these methods could be the most suitable candidate for this purpose. We, therefore, proposed to investigate the influences of the global geographical climate towards the COVID-19 spread and death using a technique of Artificial Neural Network (ANN). It is believed that the proposed study could introduce a new suggestive strategy in improving the precaution measures, enhancing the new normal living activities, and to increase the performance scalability of big data processing comprehensively. © 2020, World Academy of Research in Science and Engineering. All rights reserved.