Paving initial forecasting COVID-19 spread capabilities by nonexperts: A case study.

Area of Science:

• Epidemiology
• Public Health Preparedness
• Health Resource Management

Background:

• The COVID-19 pandemic created significant uncertainty for national response efforts.
• Israel's Home Front Command (HFC) required accurate epidemic spread forecasts for resource allocation.
• A lack of predictive models posed a challenge for HFC's operational planning.

Purpose of the Study:

• To describe the initiative of a nonexpert group to generate COVID-19 spread forecasts.
• To provide timely epidemic rate of spread predictions for HFC's decision-making.
• To map healthcare challenges and resource needs during the pandemic.

Main Methods:

• A nonexpert team collected public COVID-19 data from the Israeli Ministry of Health.
• Forecasts were generated using Microsoft Excel, despite limited statistical expertise.
• Analysis focused on identifying changes in growth patterns, such as from exponential to polynomial spread.

Main Results:

• Forecasting activities successfully demonstrated the impact of lockdown measures on virus spread.
• The transition from exponential to polynomial growth was identified.
• Effective resource management was supported, aiding HFC operations during the pandemic.

Conclusions:

• Nonexpert forecasting can be a valuable, replicable tool during public health crises.
• Identifying major events like lockdowns is crucial for accurate forecasting.
• The Planning Chamber's approach offered vital resource management insights for HFC's COVID-19 response.