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On predicting the novel COVID-19 human infections by using Infectious Disease modelling method in the Indian State of Tamil Nadu during 2020
Ayubali Arsath Abbasali.
Satheesh Sara Roshini.
Acceso Abierto
Atribución-NoComercial-SinDerivadas
10.1101/2020.04.05.20054593
Since the introduction of the novel Corona Virus (The COVID 19) to the Chinese city Wuhan in the Hubei province during the late December 2019, the effectiveness of the deadly disease, its human infection, spreading severity and the mortality rate of the infection has been an issue of debate. The outbreak of the virus along the time has become a massive threat to the global public health security and has been declared as a pandemic. Accounting the radical number of increases in the infected cases and the death due to COVID 19 infections around the globe, there is a need to predict the infections among the people by making proper optimization and using various Infectious Disease modelling (IDM) methods, in order to challenge the outcome. In comparison with previous diseases like SARS and Ebola viruses, the new corona virus (COVID 19) infections are infectious during the incubation period. In addition to that, naturally produced droplets from humans (e.g. droplets produced by breathing, talking, sneezing, coughing) and Person-to-person contact transmission are reported to be the foremost ways of transmission of novel corona virus. By considering the above two factors, a modified SEIR (Susceptibility Exposure Infection Recovery) method have been used for predicting the spread of the infections in the state of Tamil Nadu which is located in the southern part of India. Further, we have utilized the current surveillance data from Health and Family Welfare Department, Government of Tamil Nadu to accurately predict the spreading trend of the infection on a state level.
www.medrxiv.org
2020
Artículo
https://www.medrxiv.org/content/medrxiv/early/2020/04/07/2020.04.05.20054593.full.pdf
Inglés
VIRUS RESPIRATORIOS
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