This workshop will feature some of the research conducted by LIDAM members on issues related to the new coronavirus and its consequences.
This in an online event.
>14:00 Welcome/Opening remarks
> 14:10 Sandy Tubeuf Who should get it first? Public preferences for prioritising a COVID-19 vaccine
Once a safe COVID-19 vaccine is available, supply will not be sufficient to vaccinate all. Policy makers at national and international level are currently developing vaccine prioritization strategies based on vulnerabilities such as age, occupation and health status. However, there are many value judgments involved in the rationing of a vaccine and for a successful engaged COVID-19 vaccination policy one require sufficient levels of public support. We conducted a discrete choice experiment and a best-worst ranking exercise on a representative sample of 2,000 Belgians in order to elicit their views on setting fair COVID-19 vaccine priorities across the population. The respondents ranked three priority strategies as fairest: vaccinate those with pre-existing conditions, essential professions, and the elderly. However, when asked to choose between concrete individuals competing for a vaccine, virus spreaders became much more important whereas those over 60 years of age became low priority. The respondents divided within two clusters. While both wanted to vaccinate individuals with an essential profession in the second place, cluster one (N=1058) primarily wanted to target virus spreaders whereas cluster two (N=886) wanted to prioritize the ill. Other strategies such as allocating the vaccine using a ‘lottery’, ‘first-come, first-served’ approach or willingness-to-pay received little support. While vaccine access plans are taking place and targeting health workers and old and ill people at high risk of severe COVID-19 or death, societal preferences lean towards a vaccination strategy simultaneously prioritizing medically vulnerable groups, high virus spreaders, and essential professions but excluding older people.
> 14:40 Eugen Pircalabelu A poor man’s modeling of the burden of disease for COVID-19
In this talk we will present a flexible modeling framework based on smoothing splines and generalized additive models in order to evaluate and assess the burden of disease. The models use most often over-dispersed families of distributions and are fitted on publicly available indicators such as ‘Number of infections’, ‘Number of hospitalized patients and in ICU’, ‘Number of deaths’ and ‘Positivity rate’. One of the goals is to anticipate their evolution one week ahead of time. Next, a novel time-dependent measure for the reproduction number R0(t) is proposed and compared to Sciensano’s publicly released figure. Our estimator is obtained from a quasi-Poisson model and the rationale behind the proposition is first, the fact that to a general growth rate across time one can substitute the derivative of a flexible function of time that can adapt better to fluctuations and the evolution of the pandemic and secondly, a classical Poisson assumption might be too simple and thus, not an appropriate one due to the overdispersion phenomenon that is quite prominent for such data. The idea of introducing a time-varying R0(t) based on the derivative of a spline model with over-dispersion is a novel approach that has not, to our knowledge, been explored so far.
> 15:10 Donatien Hainaut An actuarial approach for modeling pandemic risk
This work proposes a model for pandemic risk and two stochastic extensions. It is designed for actuarial valuation of insurance plans providing healthcare and death benefits. The core of our approach relies on a deterministic model that is an efficient alternative to the susceptible-Infected-Recovered (SIR) method. This model explains the evolution of the first waves of COVID-19 in Belgium, Germany, Italy and Spain. Furthermore, it is analytically tractable for fair pure premium calculation. In a first extension, we replace the time by a Gamma stochastic clock. This approach randomizes the timing of the epidemic peak. A second extension consists in adding a Brownian noise and a jump process to explain the erratic evolution of the population of confirmed cases. The jump component allows for local resurgences of the epidemic.
> 15:40 Round table discussion Part 1
> 16:00 Break
> 16:15 Philipp Kircher
An Economic Model of the Covid-19 Pandemic with Young and Old Agents: Behavior, Testing and Policies
This paper investigates the importance of the age composition in the Covid-19 pandemic. We augment a standard SIR epidemiological model with individual choices on work and non-work social distancing. Infected individuals are initially uncertain unless they are tested. We find that older individuals socially distance themselves substantially in equilibrium. Con-fining the old even more reduces their welfare. Confining the young extends the duration of the epidemic, with negative consequences on the old if the epidemic cannot be controlled after confinement. Testing and quarantines save lives, even if conducted just on the young, as does separation of activities by age. Combining policies can increase the welfare of both the young and the old.
> 16:45 Bertrand CandelonEconomic consequences of the COVID
This presentation proposes to analyse the economic impacts of the on-going COVID crisis. It highlights the present but also the future challenges economies, and in particular Belgium, will have to face: A low potential growth (extended “new normality”), a huge public debt, the potential transmission to the financial sector, the rising inequalities or social unrests. To mitigate these negative effects, the foundations of “great reset” recovery plan are proposed to make economies “greener, smarter and fairer”.
> 17:15 Round table discussion Part 2
> 17:30 Concluding remarks