Optimizing Hospital Resource Allocation Through Epidemiological Forecasting: A Joint Clinical And Public Health Strategy For Surge Capacity

Abstract

Background:
Healthcare systems worldwide increasingly experience demand surges driven by infectious disease outbreaks, seasonal epidemics, and large-scale public health emergencies. Traditional hospital resource allocation models are often reactive, relying on historical utilization patterns rather than anticipatory planning. This disconnect limits the ability of hospitals to respond effectively to sudden increases in patient volume.

Objective:
This study aims to evaluate how epidemiological forecasting can be systematically integrated into hospital resource allocation processes through a joint clinical and public health strategy to enhance surge capacity preparedness.

Methods:
A systems-based modeling approach was applied using retrospective epidemiological surveillance data and hospital utilization indicators. Forecast-driven resource allocation scenarios were compared with conventional allocation approaches to assess differences in surge capacity performance.

Results:
Forecast-informed allocation demonstrated improved alignment between predicted demand and available hospital resources, including inpatient beds, intensive care capacity, and clinical staffing. Hospitals utilizing epidemiological projections showed earlier surge activation, reduced occupancy saturation, and improved coordination between clinical operations and public health authorities.

Conclusion:
Integrating epidemiological forecasting into hospital resource planning offers a proactive strategy for optimizing surge capacity. A joint clinical and public health framework strengthens health system resilience by translating population-level disease intelligence into operational hospital decisions. Adoption of such models may improve patient safety, system efficiency, and preparedness for future public health emergencies.