Oxygen exchange resource: https://datastudio.google.com/u/0/reporting/f9ed7551-36cc-46d9-afbe-252ac7e500cf/page/OhYIC

Motivation                   

a. In an unprecedented outpouring and a swift response, the Government of India, PSUs, Private Companies and charitable organizations have come together to procure 250,000+ Oxygen Concentrators (OCs) from around the world;                  
b. While acting on war-footing helped us secure the funding and supply, there has been little time for the multiple stakeholders to coordinate deployment. This becomes critically important to ensure minimal overlap                  
d. This model has been built to provide the basis of an “Oxygen Exchange”, an efficient and unbiased, matching platform, to minimize wastage of precious medical resources being imported and maximize the lives being saved in this fight against Covid-19e. We also aim to get feedback from donors on their deployments and update the same in the model so that all parties may have an updated picture of the residual demand.                  
Aim

Based on conversations with medical professionals and modelling of progression of Covid, the aim of the model is two-fold:                   

a. Conduct a bottom-up estimation of the demand for OCs from individual states, districts and hospitals
b. Estimate the current and upcoming stressed districts and states, to prioritise deployment

Method

a. Severe cases have been estimated from past hospitalization rates during the 1st wave and early part of the 2nd wave at 15-18%b. Oxygenated beds have been calculated from various government disclosures as HDU, ICU and ventilator beds. Where data is unavailable, an estimate has been made basis averages
c. Peak estimated cases date is from the IITK Sutra model
d. The excess cases over oxygenated beds has been estimated as the OC demand. Please note that this is the OC demand equivalent – and may be met by OCs or other means like LMO, PSA plants, etc. that increases the capacity of oxygenated beds
Dashboardsa. Statewise OC demand – to broadly prioritise states – either based on current demand or future demandb. District-wise OC demand – to drill down into the statesc. Hospital-wise OC demand – to drill down to the hospital level (where data is available). Note that those hospitals have been prioritised that have a healthy mix of General:HDU:ICU beds to deal with patient degradation

Copyright Oxygen Exchange/Covid Relief India Alliance. The authors assert their moral right to the piece of work. Data, where used may be under copyright of the respective owners. The Sutra model is owned by its authors (being professors at the Indian Institute of Kanpur). The output sheets may be freely shared.

Disclaimer
The authors have attempted to use publicly available data to create the dashboard and made judicious assumptions, where necessary, in a bid to aid Covid relief attempts. By using the data in this dashboard you agree to use your judgement in decision making and hold the authors harmless for decisions made basis the information, including errors, in the dashboards. 
Contact: oxygentoindia@gmail.com

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