Abstract

Abstract. Having a common framework for early action to cope with complex disasters can make it easier for authorities and other stakeholders, including populations at risk, to understand the full spectrum of secondary and tertiary effects and thus where to focus preparedness efforts, and how best to provide more targeted warnings and response services. Meteorological and hydrological services world-wide have developed and implemented Multi-Hazard Early Warning Systems (MHEWS) for weather and climate related hazards that are now being expanded and transitioned towards Multi-Hazard Impact-based Early Warning Systems (MHIEWS). While it is still early days it is becoming clear that there are useful lessons from this approach in the COVID-19 global pandemic, and some valuable insight to be gained in risk communication, risk analysis and monitoring methodologies and approaches. The ability to understand and respond effectively to warnings through appropriate behaviours and actions is central to resilient societies and communities. By avoiding physical, societal and economic harm to the greatest extent possible, recovery from a hazard is likely to be faster, less costly and more complete. MHIEWS can be a common approach for all hazards and therefore more likely to become a trusted tool that everyone can understand and use as a basic element of their national disaster risk management system. The interconnectedness of hazards and their impacts is a strong motivator for a common approach. One of the lessons from the COVID-19 pandemic and extreme weather events is the need to understand the vulnerability of individuals, communities and societies so as to provide reliable, targeted guidance and warnings and the willingness and capacity to prepare for a reasonable worst-case scenario based on informed long-term planning. Meteorology and hydrology are making good progress in this direction and the process can be readily applied to health and other sectors.

Highlights

  • The COVID-19 crisis and extreme weather events provide important lessons in understanding risk and creating effective multi-hazard impact-based early warning systems (MHIEWS)

  • The scramble in many countries to acquire personnel protective equipment during the high probability phase of the hazard highlights the failure to act on the low probability scenario and the dire consequences for frontline workers. These basic concepts must be kept in mind as we explore MHIEWS in more detail

  • As an example, did this for the measles outbreak that affected the country in December 2019 which in turn enabled them to take early action as COVID-19 started spreading into the Pacific

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Summary

Introduction

The COVID-19 crisis and extreme weather events provide important lessons in understanding risk and creating effective multi-hazard impact-based early warning systems (MHIEWS). Detection and early warning enable early action, but the latter will only occur if there is a clear understanding of the potential impact that is based on rigorous risk assessment and includes the range of environmental and societal consequences and complete understanding and acceptance of the need to act on high impact events, even if the probability of occurrence is very low. The different response of countries to the COVID19 pandemic, especially those having difficulties managing caseloads, suggests that a more rigorous approach to understanding the full spectrum of risk is needed This inability to accept low probability high impact situations must be overcome if the benefits of MHIEWS are to be realised and high adverse impacts avoided or mitigated. Decision making for low probability and high impact events is often hindered by the fact that government decision-makers are focused day-to-day on solving high probability, relatively minor, but media relevant, problems that divert attention from the potential catastrophic impact of low likelihood events

Multi hazard impact-based early warning systems and services
Basic elements of a MHIEWS
A common framework for visualizing warnings
Hazard identification
Exposure and vulnerability assessments
Development of risk matrices
Decision support
Conclusions
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