Please use this identifier to cite or link to this item: https://covid-19.conacyt.mx/jspui/handle/1000/3475
Healthcare impact of COVID-19 epidemic in India: A stochastic mathematical model
Chatterjee Kaustuv.
Chatterjee Kaushik.
Kumar Arun.
Shankar Subramanian.
Acceso Abierto
Atribución-NoComercial-SinDerivadas
10.1016/j.mjafi.2020.03.022
Background:In India, the SARS-CoV2 COVID-19 epidemic has grown to 1,251 cases and 32 deaths as on 30 Mar 2020. The healthcare impact of the epidemic in India was studied with a stochastic mathematical model. Methods:A compartmental SEIR model was developed, in which the flow of individuals through compartments is modeled using a set of differential equations. Different scenarios were modeled with 1000 runs of Monte Carlo simulation each using MATLAB. Hospitalization, ICU requirements and deaths were modeled on SimVoi software. The impact of Non-Pharmacological Interventions (NPI) including social distancing and lockdown on checking the epidemic was estimated. Results:Uninterrupted epidemic in India would have resulted in over 364 million cases and 1.56 million deaths with peak by mid-July. As per the model, at growth rate of 1.15, India is likely to reach approximately 3 million cases by 25 May, implying 125,455 (±18,034) hospitalizations, 26,130 (±3,298) ICU admissions and 13,447 (±1,819) deaths. This would overwhelm India's healthcare system. The model shows that with immediate institution of NPIs, the epidemic might still be checked by mid-April 2020. It would then result in 241,974 (±33,735) total infections, 10,214 (±1,649) hospitalizations, 2,121 (±334) ICU admissions and 1,081(±169) deaths. Conclusion:At current growth rate of epidemic, India's healthcare resources will be overwhelmed by end-May. With the immediate institution of NPIs, total cases, hospitalizations, ICU requirements and deaths can be reduced by almost 90%.
Medical Journal Armed Forces India
2020
Artículo
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126697/pdf/main.pdf
Inglés
VIRUS RESPIRATORIOS
Appears in Collections:Artículos científicos

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