General Morphological Analysis in Public Health Emergency Management: An Environmental Scan

Abstract

Background:

Uncertainty is inherent in public health emergency management (PHEM) due to the unpredictable nature of emergencies and interplay of public health threats and their drivers. PHEM practitioners must continually develop and adapt methods to manage this uncertainty. General morphological analysis (GMA) is a computer-aided scenario modelling method that effectively addresses issues where uncertainty exists. GMA examines possible components of a complex problem and allows practitioners to consider potential connections and outcomes. Through iterative steps, GMA can generate new knowledge and insights in the development of scenarios to aid in decision-making and planning within PHEM. 

Method:

An environmental scan was designed to identify articles that utilized GMA as one of the primary methodologies across different natural hazards within the context of PHEM. Academic databases included PubMed and Research Gate. A broad search strategy was applied to scan grey literature which included Google Scholar.

Results:

This environmental scan identified ten examples of GMA employed in PHEM across multiple countries and organizations. Examples in the literature targeted either a specific natural hazard or broadly targeted all known natural hazards. The findings can be divided into three interconnected categories: (a) scenario modelling for managing natural disasters, (b) strategy development and prioritization tools, and (c) decision-making support tools for emergency management teams.

Conclusions:

GMA is a decision-making and planning tool in PHEM that can be extended beyond scenario modelling to address uncertainties. This modelling method leverages subject matter experts to uncover innovative connections and outcomes when navigating complex problems like those observed within PHEM. Future research can involve applying GMA to PHEM in a Canadian context. Currently, the Public Health Agency of Canada is applying GMA to cyclical events (e.g., wildfires, floods, extreme heat events, and extreme weather events) to create scenarios using a PHEM lens. Future practice should involve integrating GMA with other PHEM methodologies to enhance strategies to prevent, prepare, respond and recover from future public health emergencies.