Humanitarian Practice Network (HPN)
By Emily Wilkinson, Katie Peters and Sarah Opitz-Stapleton
Covid-19 is a crisis that we must get to grips with, and fast. To do this, governments need to understand the way different threats and risks intersect. We all respond to risks and policies in different ways, and we all have different preferences and make different choices. Understanding these is critical to effectively managing this emergency.
In 2015 the scientific community urged signatories to the Sendai Framework for Disaster Risk Reduction to substantially reduce disaster mortality, the number of people affected by disasters and economic losses by 2030. For biological hazards, this includes strengthening health systems, drawing up contingency plans and improving access for those most at risk. But five years on, progress has been slow.
Too often, governments deprioritise investment in risk management in favour of other economic and development priorities, particularly if the threat is seen as highly unlikely and the consequences are unclear. Even measures that are proven to protect against the impacts of threats lack political and financial support. Counter-intuitively, political interest in supporting preparedness ramps up in the aftermath of a disaster.
While few would have predicted the Covid-19 outbreak, epidemics and pandemics routinely appear high up in government risk registers. However, as with the effect of Ebola on health systems, volcanic eruptions of Eyjafjallajökull on aviation and the impact of floods in Thailand on global supply chains, too often policy-makers fail to recognise how systems interact globally, and the potential for single threats to intersect and derail sustainable development. Not only are these events more common than governments think, they can also have more dire and far-reaching consequences than most have considered – so there’s a collective global responsibility to prepare better.
In risk management, authorities are most interested in forecasting the threat or hazard – in the case of Covid-19, on predicting how the virus will behave. But the effectiveness of disaster risk management rests mainly on understanding human behaviour and people’s risk preferences, and recognising that there are trade-offs between individual needs and the collective needs of wider society.
First, there is no one-size-fits-all approach: reactions to government policies will differ depending on people’s risk preferences. Enforcing a lockdown or forcing people out of their homes and into shelters when a disaster is about to strike may work in China, but it won’t work everywhere.
In 1999, when the Tungurahua volcano in Ecuador became active, nearby residents were forced out of their homes by the military. The compulsory evacuation was disruptive and chaotic, generating high levels of mistrust in scientists and the authorities. Today, people in Tungurahua self-evacuate: the government cannot instruct them to do so because it doesn’t work. In authoritarian regimes with high levels of social control, like China and Singapore, it does.
Second, livelihoods matter. When governments prioritise safety over all else, this can have perverse effects. A complete Covid-19 lockdown will save lives, but it will also have severe consequences, and some will lose their livelihoods completely. In the UK, the government has instructed people to stay in their homes, but some will (rationally) ignore that advice, confounding the government’s strategy to manage the spread.
There is a trade-off here between individual needs and priorities and the collective good. This trade-off is not easy to resolve, particularly when those in the most precarious economic circumstances are likely to suffer disproportionately from government decisions to prioritise immediate safety over longer-term jobs and livelihoods.
Third, in managing risks, there are winners and losers, and there is no one exemplary model of how to do it. Disaster events expose pre-existing social inequalities, which policy responses often reinforce. Covid-19 is no different: while the people most vulnerable to its impacts include those with underlying health issues, there are also social dimensions – impacts on those without access to adequate social safety nets, who cannot afford testing and medical care and who are living in places with chronically underfunded health systems.
Global hyper-connectedness allows risks to propagate more widely and more quickly than ever before. Yet options for limiting their spread and impact rely hugely on the resources and options available at international, national and, critically, individual level.
Many high-risk individuals must eventually leave their homes, for instance for ongoing medical care, even if this might expose them to the virus. For instance, one of this blog’s authors has a severe autoimmune disorder requiring regular chemotherapy. She cannot forgo treatment, which is only available in hospital. She’s dreading her next round of chemotherapy.
Cancer patients and people with autoimmune disorders, diabetes, asthma, heart disease and other chronic illnesses are being directly affected by the virus, and are indirectly facing increased morbidity and mortality due to potential disruptions in care for their underlying conditions. The true costs, in terms of loss of life, lost incomes and permanent disability due to Covid-19 complications and/or worsening underlying conditions, remain unknown.
These times of crisis highlight the strengths and weaknesses in planning, prioritisation and action, now and in the near future. These are culminating in immediate trade-offs affecting individuals and families – in some instances, healthcare professionals are having to choose which of the most critically ill Covid-19 patients can be put on ventilators, because there are only so many machines and supplies available. There are also trade-offs for individual nations, and potentially for international relationships.
Understanding options, resources, risk preferences and outcomes is critical for mitigating risk and averting the most dire outcomes, both for individuals and governments.
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