Globally-local-scale resilience is now a "must do"

Swiss Re and tech start-up One Concern are partnering to bring data-driven insights and Resilience-as-a-Service solutions to foster long-term sustainable societies in the face of interconnected risks.

The COVID-19 pandemic has cruelly exposed how unprepared many governments and institutions are to deal with complex, cross-border risks. During this pandemic crisis, governments have adopted a range of approaches, with differing outcomes often leading to unexpectedly high excess mortality and increasing economic costs. This fragmented response could result in the disease gaining renewed traction through the end of 2020 and beyond.

COVID-19's spread has accelerated in areas characterized by high population density, environmental degradation, poor urban infrastructure, and inadequate healthcare. This disease exacerbates the battering many urban areas have already taken recently due to climate-change-induced natural disasters. Society can no longer afford to wait until the next disaster strikes as globalization, urbanization, deforestation, and industrial food production propagate new diseases and affect nations' food, energy, and economic security. Globally-local prevention services to foster resilience are no longer a “nice to have” but a “must do.”

In the post COVID-19 “dynamically-changing normal,” society must develop deeper resilience in its institutions & processes. Against the backdrop of rapidly changing cultures, increasing digitization, growing demographic shifts, and increasing wealth inequality, the interconnected nature of health, economics, politics, and technology makes the definition of "normal" a moving target. COVID-19 is accelerating this pace and scope of change while exposing inadequacies.

More than ever, government leaders and corporate executives require better decision support. To date, robust technology-enabled, decision-support systems have been fragmented and unevenly deployed. This needs to change. In order to survive a potential economic depression, industry and government must work fist-in-glove to ensure resilient supply chains and infrastructures and prepare for scenarios in which catastrophes hit simultaneously, such as a hurricane like Cyclone Amphan and subsequent evacuation during a pandemic.
Many governments already collect massive amounts of data, and companies like Swiss Re and One Concern have developed an impressive array of risk and resilience modeling technologies. Unfortunately, relevant data are mostly not well curated, and advanced technologies are mostly not in the hands of key decision makers.
Despite these challenges, Swiss Re and One Concern are teaming up to help governments, industry, and citizens make informed decisions to boost resilience and improve responses to disasters like pandemics, floods, fires, and earthquakes. Analyzing complex risks through One Concern’s hyper-local pandemic model and Swiss Re’s risk intelligence enables a new Resilience-as-a-Service approach that helps decision-makers achieve better outcomes.

Disaster Evacuation During COVID-19

India & Bangladesh were recently hit by Cyclone Amphan, which threatened millions of lives. They are not alone. June 1 marked the start of hurricane season in the US and typhoon season in Japan. The global nature of these interconnected risks makes globally-local solutions even more essential to building resilient societies.

In the context of a pandemic, social distancing and hygiene are as important in reducing transmission in evacuation shelters, as during non-disaster situations. Unfortunately, there are much greater obstacles to compliance and enforceability. Hurricane evacuations require that people move while in close contact to each other, exacerbating contagion threat. As a result, hurricane evacuations, which are difficult in their own right, are further complicated by shelter-in-place restrictions and could reseed the pandemic. According to one model, the number of infected people can increase by up to 20% over three days during an evacuation.
Swiss Re's and One Concern's approach adapts compartmental epidemiological models to run at hyper-local scale to develop new pandemic-related solutions. These solutions model the potential impact of hurricane evacuations on the spread of COVID-19 by tracking transitions between those who are susceptible, exposed, asymptomatic, pre-symptomatic, symptomatic (mild and severe), hospitalized, and recovered to optimize disaster response.

Infection risk can then be modeled in densely populated areas, offering insight to plan re-opening schools, churches, and workplaces. By utilizing hyper-local, infection-rate data, decision-makers can assess hazards regarding the spread of infectious diseases.

Predictive Analytics Guide Safe Return to Work

Bringing back employees and customers safely is currently a key issue for business leaders. Executives need to re-think productivity and workforce strategy to better prepare for a potential second COVID-19 wave and build lasting resilience.

A recent analysis examined three US automotive factories (Tesla factory in Fremont, California, Ford factory in Chicago, Illinois, Mercedes-Benz factory in Tuscaloosa, Alabama) to predict infection rates, which would impact automotive manufacturers' decisions regarding production. We considered geography, re-opening date, number of employees, local COVID-19 case rate over two weeks, death rate in the local population, and factory age. For example, the modeled solution predicted a 99% chance that any Ford employee entering the Chicago factory would test positive for COVID-19. Two days later, employees tested positive, forcing Ford to temporarily halt production costing millions of dollars. Resilience-as-a-Service's hyper-local pandemic models can help decision-makers speed up recovery and minimize disruption.

Resilience-as-a-Service in insurance

Pandemic risk awareness has risen significantly due to COVID-19 with losses driving new policy exclusions and crippling businesses. Traditional insurance given its coverage and claim-adjustment processes is not well-suited to pandemic-caused business interruption and many argue pandemics are uninsurable. All agree that the best insurance is prevention, highlighting the need to support better decisions.
The SARS pandemic in 2004 woke parts of the world to pandemic risk. Unfortunately, at that time, technology and data were inadequate to do the type of modeling possible today. Now with new machine intelligence and data unification, we can model risks at a hyper-local level to drive predictive analytics guiding preventive services to help mitigate business interruption. Further, these tools can shape government response in real time, optimally redirecting resources and services.

COVID-19 is forcing the insurance industry to rethink pandemic risk and develop new solutions to help before, during, and after events. Government, industry, and the insurance sector can work together to minimize business interruption losses and build societal resilience.

The article was originally published on the World Economic Forum website.