项目作者： subhaskghosh
项目描述 ：
In this work we define a modified SEIR model that accounts for the spread of infection during the latent period, infections from asymptomatic or pauci-symptomatic infected individuals, potential loss of acquired immunity, people’s increasing awareness of social distancing and the use of vaccination as well as non-pharmaceutical interventions like social confinement. We estimate model parameters in three different scenarios - in Italy, where there is a growing number of cases and re-emergence of the epidemic, in India, where there are significant number of cases post confinement period and in Victoria, Australia where a re-emergence has been controlled with severe social confinement program. Our result shows the benefit of long term confinement of 50\% or above population and extensive testing. With respect to loss of acquired immunity, our model suggests higher impact for Italy. We also show that a reasonably effective vaccine with mass vaccination program can be successful in significantly controlling the size of infected population. We show that for India, a reduction in contact rate by 50\% compared to a reduction of 10\% in the current stage can reduce death from 0.0268\% to 0.0141\% of population. Similarly, for Italy we show that reducing contact rate by half can reduce a potential peak infection of 15\% population to less than 1.5\% of population, and potential deaths from 0.48\% to 0.04\%. With respect to vaccination, we show that even a 75\% efficient vaccine administered to 50\% population can reduce the peak number of infected population by nearly 50\% in Italy. Similarly, for India, a 0.056\% of population would die without vaccination, while 93.75\% efficient vaccine given to 30\% population would bring this down to 0.036\% of population, and 93.75\% efficient vaccine given to 70\% population would bring this down to 0.034\%.
高级语言： Python
项目地址: git://github.com/subhaskghosh/model_covid_19.git
