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db_profiler

A profiler based on pandas-profiling but connects to postgresql and then stores metadata to mongo with an API and UI interface

detm

lockdown-paper

The ongoing pandemic of coronavirus disease 2019-2020 (COVID-19) is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). This pathogenic virus is able to spread asymptotically during its incubation stage through a vulnerable population. Given the state of healthcare, policymakers were urged to contain the spread of infection, minimize stress on the health systems and ensure public safety. Most effective tool that was at their disposal was to close non-essential business and issue a stay home order. In this paper we consider techniques to measure the effectiveness of stringency measures adopted by governments across the world. Analyzing effectiveness of control measures like lock-down allows us to understand whether the decisions made were optimal and resulted in a reduction of burden on the healthcare system. In specific we consider using a synthetic control to construct alternative scenarios and understand what would have been the effect on health if less stringent measures were adopted. We present analysis for The State of New York, United States, Italy and The Indian capital city Delhi and show how lock-down measures has helped and what the counterfactual scenarios would have been in comparison to the current state of affairs. We show that in The State of New York the number of deaths could have been 6 times higher, and in Italy, the number of deaths could have been 3 times higher by 26th of June, 2020.

ml_pipeline

model_covid_19

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\%.