The spread of COVID-19 has been statistically analyzed with meteorological factors such as varying ecogeographical regions and climatic conditions i.e., the temperature of India. Although the transmission of the virus can be mainly detected by the humidity, still the temperature imparts a moderate effect on the COVID-19 pandemic. The number of confirmed COVID-19 cases in coastal and non-coastal regions of Kerala have been analyzed statistically with the change in climatic condition and its interaction during the pandemic period i.e., March 2020 to May 2021. The analysis is carried out by bifurcating the number of confirmed COVID-19 cases based on different regions. The data spectrum of the regions under consideration has shown the impact with temperature by ANOVA analysis. The present study can be utilized to frame a strict guideline to restrict the spread of COVID-19 cases. The intellectual awareness developed among the individuals could overcome the pandemic situation.
The article is regarding infectious disease, which has been affecting people all around the world since December 2019. Write-up gives a brief introduction of the Coronavirus from its emergence to the final solution of its exit. It gives us a glimpse of the biological structure of the virus, precautions to be taken in care to reduce the spread of the disease. The description shows us the consequences of the virus-like the mortality rate and the life expectancy rate. The article also presents a few vaccines development projects as a whole to fight COVID-19. It also describes the efficacy of vaccination and the post-vaccination symptoms. In the end, the write-up presents real-time neural network-based applications to fight COVID-19 and a few machine learning and deep learning techniques to diagnose a COVID-19 infected person. The final part of the article concludes with an artificial neural network and statistical neural network-based approaches to identify the rate of infection risk in a country.
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