Health and Social Security

Chapter 8 Health and Social Security Anikó Bíró, Zsófia Kollányi, Piotr Romaniuk, Šime Smolić Abstract This chapter shows evidence that population health in EEE countries lagged behind the EU average before the start of the Covid-19 pandemic. We then analyse the direct health impacts of the pandemic in EEE and how that differed from other European countries. We also provide early evidence on Covid-19 vaccination rates in EEE. We analyse the policy responses implemented by the governments to mitigate the consequences of the Covid-19 shock and discuss the indirect health impacts and the impact on social security of the pandemic. Finally, we draw conclusions for health policy. 8.1 Health status, healthcare and social security, 2009-2019 This section analyses the health status of the population and the general properties of the healthcare systems in the EEE, such as financing, service structure, and certain quality indicators. For all these dimensions, we provide information that are relevant from three, somewhat different perspectives. The first perspective is the baseline — we give a general overview on the state of health and healthcare at the moment Covid-19 first hit the EEE countries. The second perspective is to characterise the EEE societies from the point of view of their probable vulnerability in case of a widespread pandemic. And the third is the aspect of the longer term future — we Anikó Bíró Center for Economic and Regional Studies, Budapest, e-mail: [email protected] Zsófia Kollányi Eötvös Loránd University, Budapest, e-mail: kollanyi.zsofi[email protected] Piotr Romaniuk Medical University of Silesia, Katowice, e-mail: [email protected] Šime Smolić University of Zagreb, Zagreb, e-mail: [email protected] 1 2 Bíró et al. give information on the characteristics we believe to be important factors from the point of view of how successfully the EEE countries can adapt to a post-Covid-19 reality, however little we know about what this reality is going to be like. International literature points out three main risk areas related to healthcare systems and the Covid-19 pandemic. The first is the general vulnerability of countries facing the pandemic. According to the European Investment Bank’s Covid-19 Eco- nomic Vulnerability Index (Davradakis, Santos, Zwart, & Marchitto, 2020), this is mostly related to a wide array of economic conditions (which are analysed in other chapters of this volume), but also to the demographic and health status of the populations and the structure and available capacities of the healthcare systems. The second risk area is the issue of access to healthcare, which is related to the individual affordability (and the change in affordability) of health services, e.g., insurance cov- erage (see for example (Blumenthal, Fowler, Abrams, & Collins, 2020; Syed, Ajisola, Azeem, & On behalf of the Improving Health in Slums Collaborative, 2020)); to the overall and changing relative availability of these services, which is closely related to the issue of baseline capacities; and to other aspects that may affect one’s access to healthcare like postponing a medical treatment out of fear from getting infected, or healthcare institutions rejecting the acceptance of a patient out of the same fear (Syed et al., 2020). And the third issue is the financial sustainability of healthcare in general as well as that of individual providers (Barnett, Mehrotra, & Landon, 2020), under the economic recession and officially administered restrictive measures due to the pandemic (which, again, are interrelated). In the background of all these aspects lies the concern that the pandemic threats to increase social inequalities all over the world and in every society as a consequence of its complex effects channeled through the economic, educational, social and health systems (Berkhout et al., 2021; Shadmi et al., 2020). Another aspect to consider is the fact that health-related consequences of the pandemic, for example excess mortality, are not restricted to those directly affected by (infected with) Covid-19. As described in this chapter later, experienced excess mortality rates are not entirely in line with Covid-19 mortality, which can the result of inaccurate measurement as well as of an increase in mortality due to other causes during the pandemic. This also corresponds to international experience (see for example (Faust et al., 2021)). Regardless of the pandemic and the initiated restrictive measures, people keep having most of their health needs: they have their chronic diseases requiring continuous care, with occasional acute episodes requiring immediate health interventions. The fulfilment of both of these needs may be constrained because of the pandemic — either because of administrative restrictions affecting healthcare or mobility in general, or because of the overload of healthcare due to the pandemic. It also has to be noted that, based on the limited data that are available regarding the experiences of countries handling the Covid-19 relatively successfully (meaning, successfully slowing the spread of the disease and keeping the mortality rate low), the role of the traditional healthcare system seems to be rather limited. On the one hand, certain exogenous variables may lie behind the success, which are out of reach 8 Health and Social Security 3 not only of the traditional healthcare systems but – in the short run – public policies in general, as well. Such factors could be the demographic structure or the population of a country, or the prior familiarity of the populations with other coronavirus types. On the other hand, the common feature in these countries is the implementation of strict, extensive and immediate measures, aiming to prevent the spread of the disease: extensive contact tracking and testing, initiating strict lockdowns in a timely manner, and so on. Many of these characteristics are outside of the scope of healthcare system, but not all: the testing capacities and practice, for instance, is closely related to structural properties of the healthcare system. In the first part of this chapter, we provide an overview of the general health status of EEE countries’ population, as well as the main properties of healthcare systems. 8.1.1 Health status and demographic structure based on composite indicators General health status and demographic composition of the population both affect the size of the population directly at risk to Covid-19, as well as of the possible amount of unmet needs and resulting health loss due to restrictions. In terms of health status, the distribution of health across the population (in other words, existing health inequalities), the prevalence of certain chronic conditions and generally frail clinical status are of special importance (Tehrani, Killander, Åstrand, Jakobsson, & Gille-Johnson, 2021), as these indicate the size of especially vulnerable groups in the society. This vulnerability is multifaceted, manifesting not only in worse health status and increased risk of a severe outcome of a Covid-19 infection, but, based on our knowledge on the social determinants of health, also in disadvantages in access to healthcare and other resources. Life expectancy (LE) of EEE countries are among the lowest in the EU (only with Latvia and Lithuania being in worse position) (Figure 8.1). Also, with the exemptions of Croatia and Slovenia, the EEE countries have lower life expectancy than what would be acceptable at the given level of GDP/capita. This lag is the consequence of many and complex social and economic factors, in general reflecting the inefficient utilisation of social resources from the point of view of health. Moreover, this ‘stock’ of health is very unevenly distributed across the society (Figure 8.2). 4 Bíró et al. Fig. 8.1: Life expectancy at birth and GDP/capita (PPS), total population, in EU28 countires, 2018 Data: (Eurostat, 2021e, 2021i, 2021n). Note: PPS (purchasing power standard) is the technical term for common currency accounting for the different purchasing power of money in different countries - the Eurostat-version of PPP (purchasing power parity), with the same meaning. The dashed trendline is the fitted regression line of life expectancy on log GDP/capita. 85 IT CYES SE MT NL IE LU 80 FR EL FI BE ATDK PT SI EU28 DE CZ 75 HR SKPL EE HU BG RO LT LV 70 Life expectancy at birth, total population 65 10000 20000 30000 40000 50000 60000 70000 80000 90000 GDP/capita, PPS 8 Health and Social Security 5 Fig. 8.2: Life expectancy at birth by educational attainment level, 2017 Data: (Eurostat, 2021j). Note: EU28 countries shown with data available; data for Denmark: 2016 (a) Females BG HR HU EEE PL RO SI SK DK FI North NO SE EL South IT PT 60 70 80 90 Life expectancy at birth Primary education Secondary education Tertiary education (b) Males BG HR HU EEE PL RO SI SK DK FI North NO SE EL South IT PT 60 70 80 90 Life expectancy at birth Primary education Secondary education Tertiary education 6 Bíró et al. In the Visegrád (V4) countries presented in Figure 8.2, huge inequalities can be detected according to educational attainment level in the life prospects especially for males: lowly educated men compared to highly educated counterparts are expected to die almost 16 years earlier in Slovakia, 12.5 years earlier in Poland, and more than 11 years earlier in Hungary. This means that people with lower social status are probably more vulnerable in the pandemic, being – in general – in worse health status. The same deep inequalities, however, can not be detected in the other four EEE countries, but with a different underlying pattern: in Bulgaria and Romania even the highly educated have relatively low life expectancies, while in Croatia and Slovenia, greater equity means better health even for the poorly educated. Regarding the causes of death, the leading causes are cardiovascular diseases and malignant neoplasms (cancers) in all the EEE countries as well as EU28.

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