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Perceived Health Inequalities in OECD Countries: A Macro-Level Cluster Analysis
(Pergamon-Elsevier Science Ltd, 2026-06) Bulut, Tevfik
Although perceived health inequalities remain a persistent problem across the OECD, the interaction of socioeconomic factors with sex and their structural differences have not yet been sufficiently investigated. Existing one-dimensional analyses are inadequate in explaining the complex nature of these inequalities at the macro level. This study examines perceived health inequalities in terms of socioeconomic status and sex and develops a novel typology that groups countries according to their inequality profiles. The analysis uses aggregated data from 39 countries covering the period 2003-2024. Linear Mixed Effects Models were used for regression analyses, and the K-means clustering algorithm was used to construct the country typology. The results show that at the macro level, higher income is strongly associated with better perceived health (beta = 20.60, p < 0.001). Remarkably, the positive relationship between education and health is significantly stronger in females compared to males. The negative interaction coefficient obtained (beta(interaction) = -10.79, p < 0.001) indicates that the sex-based health gap narrows at higher education levels. Cluster analysis identified two distinct groups of countries: High Inequality Profile and Low Inequality Profile. These findings highlight the potential equalizing role of education and reveal that health inequalities are not homogeneous. Consequently, policy interventions should target disadvantaged groups intersectionally and be designed according to the specific structural characteristics of each country.
Estimating the Time-Varying Effectiveness of COVID-19 Preparedness in WHO European Region: A Biorisk-Focused Wavelength (BFW) Model Approach
(KeAi Communications Co., 2026-03) Bulut, Tevfik
This study analyses how the time-varying predictive power of national preparedness capacities over the impact of the coronavirus disease 2019 (COVID-19) pandemic has changed over time. Building on the ‘preparedness paradox’ in the literature, the hypothesis that preparedness is a dynamic process whose effectiveness varies across different stages of the pandemic, rather than remaining a static state, was tested. To this end, a repeated cross-sectional analysis covering the period from 2020 to 2024 was conducted on a fixed cohort of 34 countries in the World Health Organization (WHO) European Region. The study utilised a comprehensive dataset integrating COVID-19 incidence from Our World in Data, annual preparedness scores from the WHO e-State Parties’ Self-Assessment Annual Reporting portal, socio-economic resilience indicators from the United Nations Development Programme Human Development Reports and population density metrics from the United Nations Population Division. The impact of the pandemic was quantified using the epidemiological wavelength model and its associated derivative frameworks. The annual explanatory power (adjusted R2) of three frameworks was compared: a Baseline Model representing general socio-economic resilience (indexed by the Human Development Index) and two specialised Biorisk-Focused Wavelength (BFW) Models (Core and Extended), which isolate specific biosecurity capacities. The results demonstrated that the predictive power of preparedness varied significantly across pandemic stages. During the initial phase in 2020, the Core BFW model, which focuses on basic strategic biorisk capacities, was the most effective predictor (adjusted R2 = 11.2%, p = 0.030). In contrast, as the pandemic reached a mature phase in 2022, the biorisk models lost all explanatory power, while the Baseline Model of systemic resilience emerged as a robust predictor (adjusted R2 = 24.4%, p = 0.002). This trend persisted into the endemic phase of 2024, where systemic resilience maintained a significant, albeit weaker, association (p = 0.032). Out-of-sample validation confirmed these findings: the Core BFW Model showed the highest forecast accuracy in 2020, whereas the Baseline Model demonstrated superior performance during the chronic phase of 2022. These results suggest that while technical biosecurity is critical during an initial shock, its influence is eventually superseded by overall systemic resilience. Consequently, future pandemic preparedness strategies must focus not only on static technical checklists but also on holistic approaches that enhance a nation's ability to adapt to prolonged crises. © 2026 The Author

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