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Capacity-need gap in hospital resources for varying mitigation and containment strategies in India in the face of COVID-19 pandemic.
Verma, Veenapani Rajeev; Saini, Anuraag; Gandhi, Sumirtha; Dash, Umakant; Koya, Shaffi Fazaludeen.
  • Verma VR; Humanities and Social Sciences, Indian Institute of Technology Madras, 600036, Chennai, India.
  • Saini A; Vantage Research, 600004, Chennai, India.
  • Gandhi S; Humanities and Social Sciences, Indian Institute of Technology Madras, 600036, Chennai, India.
  • Dash U; Humanities and Social Sciences, Indian Institute of Technology Madras, 600036, Chennai, India.
  • Koya SF; Boston University, 02215, Massachusetts, USA.
Infect Dis Model ; 5: 608-621, 2020.
Article in English | MEDLINE | ID: covidwho-733820
ABSTRACT

BACKGROUND:

Due to uncertainties encompassing the transmission dynamics of COVID-19, mathematical models informing the trajectory of disease are being proposed throughout the world. Current pandemic is also characterized by surge in hospitalizations which has overwhelmed even the most resilient health systems. Therefore, it is imperative to assess health system preparedness in tandem with need projections for comprehensive outlook.

OBJECTIVE:

We attempted this study to forecast the need for hospital resources for one year period and correspondingly assessed capacity and tipping points of Indian health system to absorb surges in need due to COVID-19.

METHODS:

We employed age-structured deterministic SEIR model and modified it to allow for testing and isolation capacity to forecast the need under varying scenarios. Projections for documented cases were made for varying degree of containment and mitigation strategies. Correspondingly, data on health resources was collated from various government records. Further, we computed daily turnover of each of these resources which was then adjusted for proportion of cases requiring mild, severe and critical care to arrive at maximum number of COVID-19 cases manageable by health care system of India.

FINDINGS:

Our results revealed pervasive deficits in the capacity of public health system to absorb surge in need during peak of epidemic. Also, model suggests that continuing strict lockdown measures in India after mid-May 2020 would have been ineffective in suppressing total infections significantly. Augmenting testing to 1,500,000 tests per day during projected peak (mid-September) under social-distancing measures and current test to positive rate of 9.7% would lead to more documented cases (60, 000, 000 to 90, 000, 000) culminating to surge in demand for hospital resources. A minimum allocation of 13x, 70x and 37x times more beds for mild cases, ICU beds and mechanical ventilators respectively would be required to commensurate with need under that scenario. However, if testing capacity is limited to 9,000,000 tests per day (current situation as of 19th August 2020) under continued social-distancing measures, documented cases would plummet significantly, still requiring 5x, 31x and 16x times the current allocated resources (beds for mild cases, ICU beds and mechanical ventilators respectively) to meet unmet need for COVID-19 treatment in India.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Infect Dis Model Year: 2020 Document Type: Article Affiliation country: J.idm.2020.08.011

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Infect Dis Model Year: 2020 Document Type: Article Affiliation country: J.idm.2020.08.011