In her master’s thesis Buying Time to Save Lives: Evaluating COVID-19 Lockdown policies Using a behavioral SEIR, Lin evaluates different COVID-19 lockdown policies in the Netherlands. The key finding of her research is that even the most advanced epidemiology models fall short in their predictions. This also applies to the models used by the RIVM (National Institute for Public Health). Lin shows this happens because the models fail to take behavioural responses into account when there is a threat of infection.  Xu Lin’s SEIR model (Susceptibility-Exposure-Infection-Recovery) factors in fear of contagion. This model helps accurately predict how a pandemic will develop over time.

Better analysis

‘I wanted to develop an epidemiological model that would perform better. My thesis describes how different factors could be used.  This allows economists to better analyse health and economic outcomes during the pandemic,’ said Lin. Her model shows that failure to take COVID-19 lockdown measures would lead to more deaths and reduced economic growth.  A lockdown thus buys time by limiting the spread of the virus until vaccines arrive. This finding runs contrary to the opinions of economists who argue that lockdowns are costly and ineffective.

Jury report

The jury selected Xu Lin’s thesis (supervised by ASE professor Sweder van Wijnbergen) from 21 submissions in this category. Theses were assessed for their social relevance, originality, scientific quality and clarity. The jury report stated that Lin’s work was a ‘very clear and exceptionally well written thesis.’ The awards ceremony and the jury report can be viewed on the KHMW website.