Late last year, my IIASA colleague Raya Muttarak, Roman Hoffmann from the Vienna Institute of Demography/Potsdam Institute for Climate Impact Research, and I were informed by the City of Vienna that our proposal to study “Climate, Health and Population” (CHAP) in the metropolitan area of Vienna had been granted funding for the 2020 period. Originally, we wanted to study what climate change and demographic change in the rapidly growing Austrian capital implies with regard to future vulnerability to extreme weather events. As the city is booming with economic activity and experiencing more tropical summer heat every year, the extent of the urban heat island increases as well, thus posing a steadily increasing risk to the city’s growing population, especially the elderly.
One conventional way of thinking about a population’s risk in the context of climate change is to decompose the risk and focus on its individual components. According to the famous “risk triangle” after Crichton, risk equals hazard times exposure times vulnerability. If any of the three can be taken out of the equation, the risk is reduced to zero … much like in the absence of sun, even the palest person can safely go outside without sunscreen! If, however, the hazard is there, people would be well advised to either not expose themselves to the sun or to reduce their vulnerability to skin damage and cancer by wearing sunscreen.
Now what does that have to do with our current predicament of a vast fraction of the world’s population being quarantined due to the outbreak of COVID-19? Well, as we and our CHAP colleagues were waiting for the meteorological data necessary for answering CHAP’s main research questions, we thought that we could focus on this much more imminent threat instead. In some way, the risk posed by COVID-19 can be viewed under the same lens as the above risk equation:
In terms of hazard, COVID-19 represents an unprecedented shock to social and economic systems and thus has a lot in common with climate-induced natural disasters. As humans are the carriers of the disease, the number of infected people in a local area can be considered as the hazard estimate. Meanwhile, by employing physical distancing (while remaining socially very active and helping, in particular, those around us that are in a more dire situation), we can lower exposure to that hazard a great deal and the risk can be reduced decisively. While under a business-as-usual scenario, our health system would soon find itself overwhelmed by an unbearable demand for health care, eventually having to give up lots of patients. The quarantine measures imposed in many countries serve to lower exposure and subsequently “flatten the curve”. So in order to reduce your own risk exposure and avoid increasing the risk for others, everyone who can afford to, please stay at home!
Likewise, we can to a certain extent work on lowering our vulnerability, both at the individual and at the societal level. Not everyone is equally vulnerable to the disease. As in the case of facing the challenges of climate change, populations faced with this pandemic are characterized by demographic differential vulnerability, expressed by the fact that the virus is more (but certainly not exclusively) lethal for older people, as well as those with preexisting health conditions and weakened immune systems. To reduce our individual vulnerability (in case we are exposed to the hazard), we can work on strengthening our immune systems.
At the societal level, we can reduce risks by identifying those places where the disease outbreak might have the strongest impact. For this we need suitable indicators available with sufficient spatial granularity. The initial, pre-lockdown infection hotspots, were often places that are well connected, such as travel hubs and touristic areas. In some cases, though, these hotspots were created simply as the consequence of bad luck, in other words, because there was a local “super-spreader” or a social event that brought together a large number of people. Such situations can hardly be anticipated. What we might be able to anticipate, though, are those vulnerable geographical hotspots where, given the pre-existing burden of disease, as well as the demographic and socioeconomic characteristics of the people that live there, the pandemic might cause the most havoc.
In line with the work by our IIASA colleague, Asjad Naqvi, we set out to map various indicators at the Austrian and Slovak municipal level (Slovak data courtesy of Michaela Potancokova from the IIASA World Population Program). Our indicators include things like the proportion of elderly population (>70+) or population density, but also the proportion of people with low socioeconomic status or a region’s connectedness in terms of the proportion of population commuting for work. These indicators can have varying importance in the short, medium, and long term — while mobility is no longer a big issue now that the population is in lockdown, socioeconomic characteristics, for example, may play a bigger role the longer the crisis lasts. While at the initial stages, Austrians with higher socioeconomic status were more likely to get infected due their mobility and larger social networks, the socioeconomic gradient might turn around eventually and those with lower social status might carry the brunt of the pandemic, as they are more likely to become unemployed and stay there for a longer period of time.
Our work to create a meaningful risk index from such vulnerability indicators is still in progress, but we aspire to pinpoint which areas are most likely going to need additional interventions, such as more testing or increased hospital capacities. This exercise will not only be useful at later stages of the pandemic, that is, when we slowly start moving back from the current quarantine situation (“The Hammer”) to gradual normalization (“The Dance”), but also when faced by other types of risks, such as from climatic hazards or economic shocks.
Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis
Together with a group of demographers from Latin America and the Caribbean (LAC), and endorsed by more than 250 individuals from the academic community, I contributed to a statement urging governments, the World Health Organization, and the Pan American Health Organization, to take immediate action to drastically increase the coverage of COVID-19 tests in the region. This call for action was disseminated by the British Society for Population Studies, Asociación Latino Americana de Población, Sociedad Mexicana de Demografía, Associação Brasileira de Estudos Populacionais, and the Population Association of America, among other important institutions.
I joined this initiative by invitation from Dr. Enrique Acosta and other colleagues, because I firmly believe that the prospects for the COVID-19 pandemic in the LAC region are rather dramatic. Several studies document that, apart from being globally recognized for its high levels of economic and social inequality, the region also suffers from institutional coordination failures and poor governance, a lack of appropriate resources, and presents a unique epidemiological and demographic profile of its population that escalates the negative prospects of the pandemic. I wanted to explore in more detail why these features of LAC are a source of major concern and require immediate action.
Social and economic inequality in LAC will hamper the enforcement of social distancing and isolation measures, which have proven to mitigate the COVID-19 epidemic in other settings. More than half of the population is in the informal labour market and does not have access to social safety nets. For those covered by the social security system, the benefits already proposed by a few governments of the region such as Brazil, fall short of the daily needs of families. In addition to economic inequality, social inequality, which leads to a high degree of cohabitation between adults and the elderly, increases the exposure of those with the highest risk of complications and death.
In addition, with the closure of schools, children who do not have access to day-care centres and the public- or private education system, often rely on the help of their grandparents, which again brings greater vulnerability to families. Not to mention that these children won’t have ensured their learning opportunities, because their parents are often working and not able to home-school them, thus compromising their education outcomes.
Moreover, LAC is facing a rapid demographic transition and aging process, which is temporarily increasing the prevalence of a young population, meaning that the population age-structure of potential infected individuals differs from that of other settings. However, unlike the more developed countries, LAC’s epidemiologic transition, that is, the transition in which the prevalence of infectious diseases is “substituted” by chronic and degenerative diseases, is not complete. Paradoxically, the region exhibits both the prevalence of diseases that have long been eradicated in more developed contexts (such as malaria, dengue, and tuberculosis) and diseases of richer countries (such as hypertension, diabetes, and neoplasms).
On top of all the above-mentioned vulnerabilities, crisis-management efforts in the region are uncoordinated, and lacking transparency and commitment. Taking Brazil as an example: while some mayors and governors adopt measures of social isolation and prevention against COVID-19, parts of the federal executive power not only disdain the problem, but encourages the population not to meet the requirements established by the Ministry of Health. Such conflicting rules are bound to cause misunderstandings among the LAC population. The COVID-19 pandemic is a crucial moment for institutional coordination to ensure the effective management of the crisis.
As an important and urgent call to action for the pandemic in the region, myself and other LAC researchers are calling for an increase in test coverage and measures of social isolation. As reported in the non-specialized media under the slogan “help to flatten the curve”, social isolation allows the rate of contagion of the virus to be reduced, in order to prevent overloading the capacity of the health system. Existing literature documents that while the virus does not cause major damage to health for the majority of infected persons, it brings a high cost to the health system. Furthermore, the impacts on the later lives of individuals who were hospitalized due to the disease are not yet known. Not to mention, of course, the human tragedy and the costs in terms of lives lost to the disease.
Finally, imperative and immediate action against COVID-19 in LAC will depend on the widespread and low-cost application of tests. This is required because the former rigorous isolation measures mentioned above are highly ineffective if not accompanied by aggressive strategies to detect cases of COVID-19. This highlights the relevance of data collection to better inform policymakers and provide researchers with clear diagnoses of the conditions in the region.
Deaton A (2013). Cap. 3. Escaping death in the Tropics. In The Great Escape: Health, Wealth, and the Origins of Inequality. Princeton University Press.
As researchers, the majority of our work – even if it is applied research – requires deep insight and plenty of reading and writing, which sometimes takes years. When we initiate a new method development project, for example, we never know if it will eventually prove to be useful in real life, except on very rare occasions when we are willing to step out of our academic comfort zones and explore if we are able to address the challenges that decision makers are faced with right now.
I would like to encourage my colleagues and our network to try and answer the call when decision makers ask for our help. It however requires courage to produce fast results with no time for peer review, to explore the limits of our knowledge and capabilities of our tools, and to run the risk of failure.
I share two examples with you in this blog. The first one describes a situation that played out years ago, while the second one is happening today.
When the first signs of a potential refugee crisis became visible late in 2014, the Finnish Prime Minister’s Office contacted the IIASA Advanced Systems Analysis Program (ASA) and asked whether we could produce an analysis for them. The ASA team had an idea to develop a new method for qualitative systems analysis based on an application of causal-loop-diagrams and we decided to test the approach with an expert team of 14 people from different Finnish ministries. I have to admit that the process was not exactly the best example of rigorous science, but it was able to produce results in only eight weeks.
“Experts that participated in the process from the government side accepted that the process was a pilot and exploratory in nature. In the end, the group was however able to develop a shared language for the different aspects of the refugee situation in Finland. The method produced comprised a shared understanding of the events and their interdependencies and we were able to assess the systemic impact of different policies, including unintended consequences. That was a lot in that situation,” said Sari Löytökorpi, Secretary General and Chief Specialist of the Finnish Prime Minister’s Office when reflecting on that experience recently.
The second case I want to describe here is the current coronavirus pandemic. The COVID-19 virus reached Finland at the end of January when a Chinese tourist was diagnosed. The first fatality in Finland was recorded on 20 March. This time, the challenge we are presented with is to look beyond the pandemic. The two research questions presented to us by the Prime Minister’s Office and the Ministry of Economic Affairs are: ‘How can the resilience of the national economy be enhanced in this situation?’ and secondly ‘What will the world look like after the pandemic?’
Pekka Lindroos, Director of Foresight and Policy Planning in the Finnish Ministry of Economic Affairs is confident, “We know that the pandemic will have a huge impact on the economy. The global outcome of current national policy measures is a major unknown and traditional economic analysis is not able to cover the dynamics of the numerous dimensions of the rupture. That is why we are exploring a combination of novel qualitative analysis and foresight methods with researchers in the IIASA ASA Program.”
I have been working on the implementation of the systems perspective to the coronavirus situation with a few close colleagues around the world who are experts in resilience and risk. We were able to deliver the first report on Friday, 27 March. Among other things, it emphasized the role of social capital and society’s resilience. A more detailed report is currently in production.
A simple systems map (causal loop diagram) representing a preliminary understanding of the world after COVID-19 from a one country perspective.
Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
Since the outbreak of COVID-19 in Wuhan, China back in January, we have learnt a lot about the virus: we know how to detect the symptoms, and a vaccination is currently being developed. However, there are still many uncertainties:
We for example don’t know enough about the disease’s fatality rate – mainly because we don’t precisely know how many people are infected, which is the denominator. We also don’t know exactly how the virus spreads. Generally, it is assumed that the virus spreads from person-to-person through close contact (within about 1 meter) and through respiratory droplets produced when an infected person coughs or sneezes. It is also thought that COVID-19 can spread from contact with contaminated surfaces or objects.
In addition, knowledge about the timing of infectiousness is still uncertain. There is evidence that the transmission can happen before the onset of symptoms, although it is commonly thought that people are most contagious when they are most symptomatic. This information is crucial, because if we know the timing patterns of the transmission, we could adopt better measures around when to quarantine an infected person.
Lastly, we don’t yet know whether the spread of the disease will slow down once the weather gets warmer.
We learnt from an epidemiological transmission model that public efforts to curb the transmission of the disease should be directed towards flattening the epidemic curve. This is crucial, since the treatment of severe lung failure caused by COVID-19 requires ventilators to help patients breathe in intensive care units (ICUs). Not a single country in the world has the capacity to absorb the large number of people who would need intensive care at the same time. Experience from Italy shows that about 10% of all patients who test positive for COVID-19 require intensive care. Although efforts have been made to increase ICU capacity, the rapidly growing number of infected patients is overloading the healthcare system. Measures to reduce transmission in order to slow down the epidemic over the course of the year will therefore significantly mitigate the impact of COVID-19.
A transmission model with and without intervention. Source: CDC. (2007). Interim Pre-pandemic Planning Guidance: Community Strategy for Pandemic Influenza Mitigation in the United States—. Centers for Disease Control and Prevention.
The figure above shows the distribution of infectious cases with and without intervention. If the outbreak peak can be delayed, this allows the health system and healthcare professionals to bring the number of persons that require hospitalization and intensive care in line with the nation’s capacity to provide medical care. To flatten the epidemic curve and lower peak morbidity and mortality, calls for both government response and individual actions.
We will have to follow the protocol of the Austrian Health Ministry, but certain practices such as social distancing, washing hands, and avoiding gathering in crowded places, can help reduce the transmission of the disease. While it is true that young and healthy people are less likely to get sick and die from COVID-19, they can still be a virus carrier and thus transmit the disease to other vulnerable subgroups of the population, such as older people and those with underlying health conditions. An article recently published in The Lancet provides helpful information to better understand the current situation and explains why fighting against COVID-19 will take collective action.
Anderson R, Heesterbeek H, Klinkenberg D, & Hollingsworth T (2020). How will country-based mitigation measures influence the course of the COVID-19 epidemic? The Lancet 0(0) DOI: 10.1016/S0140-6736(20)30567-5
Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.