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The author presents a comparative analysis of old-age pension systems in Estonia, Latvia and Lithuania using a method of retrospective simulation run on a self-developed model. The model baseline case is a person retiring in December 2014 after 40 years of service with nationwide average salary. Other cases include low and high-earners, funded schemes participants and simulations for modified notional capital valorisation formulae. Three study countries return very dissimilar results, which is caused by differences in their pension systems’ designs. Lack of non-contributory element (basic pension) in Latvia leads to a low degree of progressivity, with inexcusably low pensions to low-earners and excessively generous pensions to high-earners. Participation in funded pillar II schemes has not brought any significant gains to pension plan sharers. Notional capital valorisation rules adopted in different countries that use the NDC-system significantly influence pension amount.

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The coronavirus disease 2019 (COVID-19) was declared a pandemic by the WHO on March 11, 2020, due to its high infection rate, which caused thousands of deaths worldwide and expanding. The evolving outbreak of COVID-19 requires health-protective behavior that can alleviate the severity of an epidemic. Therefore, recognizing the underlying drivers of health-protective behavior against COVID-19 is urgently needed to form policy responses. The purpose of this study was to investigate the individual-level underlying drivers affecting the formation of knowledge, attitudes, and COVID-19-related health-protective behavior among individuals aged 50 and older who are more vulnerable to complications of infection because of their age. The factors making individuals more vulnerable are also associated with the ability to access and understand information, make well-informed decisions, and take health-protective and promoting actions, especially when information itself is not timely, trusted, consistent, or actionable. The researchers used data from a representative population sample consisting of 50-80-year-old individuals, obtained from in-depth, semi-structured telephone interviews during July – August 2020, between the first and second waves of COVID-19. For conducting qualitative data analyses, the Grounded Theory (GT) approach for developing code structure was used.