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Modeling risk of infectious diseases: a case of Coronavirus outbreak in four countries
Md. Mazharul Islam.
Md. Monirul Islam.
Md. Jamal Hossain.
Faroque Ahmed.
Acceso Abierto
Atribución-NoComercial-SinDerivadas
10.1101/2020.04.01.20049973
Background The novel coronavirus (2019-nCOV) outbreak has been a serious concern around the globe. Since people are in tremor due to the massive spread of Coronavirus in the major parts of the world, it requires to predict the risk of this infectious disease. In this situation, we develop a model to measure the risk of infectious disease and predict the risk of 2019-nCOV transmission by using data of four countries - United States, Australia, Canada and China. Methods The model underlies that higher the population density, higher the risk of transmission of infectious disease from human to human. Besides, population size, case identification rate and travel of infected passengers in different regions are also incorporated in this model. Results According to the calculated risk index, our study identifies New York State in United States (US) to be the most vulnerable area affected by the novel Coronavirus. Besides, other areas (province/state/territory) such as Hubei (China, 2nd), Massachusetts (US, 3rd), District of Columbia (US, 4th), New Jersey (US, 5th), Quebec (Canada, 20th), Australian Capital Territory (Australia, 29th) are also found as the most risky areas in US, China, Australia and Canada. Conclusion The study suggests avoiding any kind of mass gathering, maintaining recommended physical distances and restricting inbound and outbound flights of highly risk prone areas for tackling 2019-nCOV transmission.
www.medrxiv.org
2020
Artículo
https://www.medrxiv.org/content/10.1101/2020.04.01.20049973v1.full.pdf
Inglés
VIRUS RESPIRATORIOS
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