Kenya Noronha's study analyzes pressure on the Brazilian health system from COVID -19. The work presents simulations estimating demand for hospital beds, ICU beds, and mechanical ventilators across health micro-regions and macro-regions under varying infection rates and time horizons. The results reveal critical capacity shortfalls in numerous regions.
Use Cases
- Modeling regional healthcare capacity shortfalls based on simulated infection rates and time horizons.
- Planning field hospital deployment based on identified 'hospital deserts' and demand pressure.
- Analyzing the combined capacity of public and private health sectors under pandemic scenarios.
Strengths
- Simulations cover three distinct infection rate scenarios (0.01, 0.1, and 1 case per 100 inhabitants).
- Analysis is performed at two geographic levels: health micro-regions and macro-regions.
- Scenarios consider three different time horizons (1, 3, and 6 months).
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Data may reflect simulation bias inherent to the modeling approach.
Provenance
- Source
- Kenya Noronha
- Collection Method
- Series of simulations estimating demand for hospital resources.
- Time Range
- Time horizons of 1, 3, and 6 months are simulated.
- Freshness
- Last update date is unknown; freshness unverified.
- Geography
- Brazil, analyzed at health micro-region and macro-region levels.