A SURVEY ON MATHEMATICAL, MACHINE LEARNING AND DEEP LEARNING MODELS FOR COVID-19 TRANSMISSION AND DIAGNOSIS

Abstract : COVID-19 is a life threatening disease which has a enormous global impact. As the cause of the disease is a novel coronavirus whose gene information is unknown, drugs and vaccines are yet to be found. For the present situation, disease spread analysis and prediction with the help of mathematical and data driven model will be of great help to initiate prevention and control action, namely lockdown and qurantine. There are various mathematical and machine-learning models proposed for analyzing the spread and prediction. . Each model has its own limitations and advantages for a particluar scenario. This article reviews the state-of-the art mathematical models for COVID19, including compartment models, statistical models and machine learning models to provide more insight, so that an appropriate model can be well adopted for the disease spread analysis. Furthermore, accurate diagnose of COVID19 is another essential process to identify the infected person and control further spreading. . As the spreading is fast, there is a need for quick auotomated diagnosis mechanism to handle large population. Deep-learning and machinelearning based diagnostic mechanism will be more appropriate for this purpose. In this aspect, a comprehensive review on the deep learning models for the diagnosis of the disease is also provided in this article.
 EXISTING SYSTEM :
 ? There are various mathematical and machine-learning models proposed for analyzing the spread and prediction. Each model has its own limitations and advantages for a particluar scenario. This article reviews the state-of-the art mathematical models for COVID19, including compartment models, statistical models and machine learning models to provide more insight, so that an appropriate model can be well adopted for the disease spread analysis. Considering the countries as individuals, a model describing spread between the countries and within the country is proposed in . The name of this model is BeCoDis, which characterize disease initiation, epidemic strength, and spread per country
 DISADVANTAGE :
 ? Considering the countries as individuals, a model describing spread between the countries and within the country is proposed in . The name of this model is BeCoDis, which characterize disease initiation, epidemic strength, and spread per country. ? The variation of BeCoDis model was employed by authors to find the international spread of the novel coronavirus outbreak. ? A method to estimate the parameters of epidemiological models, through multi objective problem formulation and its optimization is proposed
 PROPOSED SYSTEM :
 ? Chinese government has informed the world health organization (WHO) about severe acute cases of pneumonia with unfamiliar etiology . This outbreak originates from the seafood market in the city of Wuhan, China and started infecting more than 50 people. ? The live animals, namely, frogs, snakes, marmots, rabbits and bats are usually sold at the Hunan sea market. On 12 January 2020, an order was released from the National Health Commission of China stating that there is an epidemic of viral Pneumonia. Using sequence-based analysis, the Government has identified that the cause of the disease is due to a novel coronavirus.
 ADVANTAGE :
 ? The bayesian SEIR epidemiological model is used to perform a parametric regression on the COVID-19 outbreak data . A compartmental SEIR model for epidemic in India is reported by modeling the flow of individuals using a set of differential equations ? To solve the multi objective function, authors have used Achievement Scalarizing Function Genetic AlgorithmThis number is used to assess alternative interventions to control an outbreak . ? The work models the dynamics of COVID-19. The details about the transmission of infection among bats and people is briefly described in the work. In this work, bats are considered as the hosts, while the seafood market is assumed to be the source for which the mathematical results are presented followed by a formulation of the fractional model.
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