BACKGROUND: The effectiveness of crisis response can be influenced by various structural, cultural, and functional aspects within a social system. This study uses a configurational approach to identify combinations of sociopolitical conditions that lead to a high case fatality rate (CFR) of COVID-19 in OECD countries.
METHODS: A Fuzzy set qualitative comparative analysis (QCA) is conducted on a sample of 38 OECD countries. The outcome to be explained is high COVID-19 CFR. The five potentially causal conditions are level of democracy, state capacity, trust in government, health expenditure per capita, and the median age of population. A comprehensive QCA robustness test protocol is applied, which includes sensitivity ranges, fit-oriented robustness, and case-oriented robustness tests.
RESULTS: None of the causal conditions in both the presence and negation form were found to be necessary for high or low levels of COVID-19 CFR. Two different combinations of sociopolitical conditions were usually sufficient for the occurrence of a high CFR of COVID-19 in OECD countries. Low state capacity and low trust in government are part of both recipes. The entire solution formula covers 84 percent of the outcome.  Some countries have been identified as contradictory cases. The explanations for their COVID-19 CFR require more in-depth case studies.
CONCLUSIONS: From a governance perspective, the weakness of government in effectively implementing policies, and the citizens\' lack of confidence in their government, combined with other structural conditions, serve as barriers to mounting an effective response to COVID-19. These findings can support the idea that the effects of social determinants of COVID-19 outcomes are interconnected and reinforcing.

Microbial toxicity tests play an important role in various scientific and technical fields including the risk assessment of chemical compounds in the environment. There is a large battery of normalized tests available that have been standardized by ISO (International Organization for Standardization) and OECD (Organization for Economic Co-operation and Development) and which are worldwide accepted and applied. The focus of this review is to provide information on microbial toxicity tests, which are used to elucidate effects in other laboratory tests such as biodegradation tests, and for the prediction of effects in natural and technical aqueous compartments in the environment. The various standardized tests as well as not normalized methods are described and their advantages and disadvantages are discussed. In addition, the sensitivity and usefulness of such tests including a short comparison with other ecotoxicological tests is presented. Moreover, the far-reaching influence of microbial toxicity tests on biodegradation tests is also demonstrated. A new concept of the physiological potential of an inoculum (PPI) consisting of microbial toxicity tests whose results are expressed as a chemical resistance potential (CRP) and the biodegradation adaptation potential (BAP) of an inoculum is described that may be helpful to characterize inocula used for biodegradation tests. KEY POINTS: • Microbial toxicity tests standardized by ISO and OECD have large differences in sensitivity and applicability. • Standardized microbial toxicity tests in combination with biodegradability tests open a new way to characterize inocula for biodegradation tests. • Standardized microbial toxicity tests together with ecotoxicity tests can form a very effective toolbox for the characterization of toxic effects of chemicals.

This study aimed to screen the inhalation toxicity of chemicals found in consumer products such as air fresheners, fragrances, and anti-fogging agents submitted to K-REACH using machine learning models. We manually curated inhalation toxicity data based on OECD test guideline 403 (Acute inhalation), 412 (Sub-acute inhalation), and 413 (Sub-chronic inhalation) for 1709 chemicals from the OECD eChemPortal database. Machine learning models were trained using ten algorithms, along with four molecular fingerprints (MACCS, Morgan, Topo, RDKit) and molecular descriptors, achieving F1 scores ranging from 51 % to 91 % in test dataset. Leveraging the high-performing models, we conducted a virtual screening of chemicals, initially applying them to data-rich chemicals generally used in occupational settings to determine the prediction uncertainty. Results showed high sensitivity (75 %) but low specificity (23 %), suggesting that our models can contribute to conservative screening of chemicals. Subsequently, we applied the models to consumer product chemicals, identifying 79 as of high concern. Most of the prioritized chemicals lacked GHS classifications related to inhalation toxicity, even though they were predicted to be used in many consumer products. This study highlights a potential regulatory blind spot concerning the inhalation risk of consumer product chemicals while also indicating the potential of artificial intelligence (AI) models to aid in prioritizing chemicals at the screening level.

In today\'s world, where the dramatic effects of climate change continue to increase, it is critical to turn from fossil fuels to renewable energy sources to achieve the CO2 emission reduction targets that countries have committed at the Paris Climate Agreement and COP 27 conference. This study analyzes the effects of macroeconomic factors, including economic growth, investments, and unemployment, on the transition to renewable energy in OECD countries. From 1996 to 2020, long-run relationships between variables were examined using advanced econometric methodologies for empirical analysis. For this purpose, panel data analysis, second-generation panel unit root tests, cross-sectional dependence tests, and panel cointegration tests were applied. Economically, in the long run, according to panel CCEMG and AMG estimator, while economic growth enhances the renewable energy transitions, investment does not statistically promote an impact on the renewable energy transitions. Renewable energy transition increases with unemployment. Moreover, the role of the considered variables in the renewable energy transition varies among country-specific. Within the framework of the results obtained, it has been proven that before determining policies for renewable energy transformation, it is necessary to do the necessary groundwork in the economy to increase economic growth and investments and reduce unemployment.

UNASSIGNED: This study investigates the Health-Led Growth Hypothesis (HLGH) within OECD countries, examining how health expenditures influence economic growth and the role of different health financing systems in this relationship.
UNASSIGNED: Utilizing a comprehensive analysis spanning 2000 to 2019 across 38 OECD countries, advanced econometric methodologies were employed. Both second-generation panel data estimators (Dynamic CCEMG, CS-ARDL, AMG) and first-generation models (Panel ARDL with PMG, FMOLS, DOLS) were utilized to test the hypothesis.
UNASSIGNED: The findings confirm the positive impact of health expenditures on economic growth, supporting the HLGH. Significant disparities were observed in the ability of health expenditures to stimulate economic growth across different health financing systems, including the Bismarck, Beveridge, Private Health Insurance, and System in Transition models.
UNASSIGNED: This study enriches the ongoing academic dialog by providing an exhaustive analysis of the relationship between health expenditures and economic growth. It offers valuable insights for policymakers on how to optimize health investments to enhance economic development, considering the varying effects of different health financing frameworks.

Growing restrictions and bans on animal testing for chemical safety assessment under different regulations have led to an increasing use of alternative methods. Read-across is one of the major approaches used for this purpose, which relies on the identification of toxicological hazards of a data-poor or untested (target) chemical from data on other already-tested (source) similar chemicals. This requires the target substance to be first assigned to a group or category of \'similar\' chemicals. The \'similarity\' may be in terms of structural features alone, or in combination with certain rules that are based on mechanistic and/or toxicological aspects. In this regard, the OECD QSAR toolbox-a major free-access in silico platform-is widely used to derive toxicity predictions for a range of (eco) toxicological endpoints. The Toolbox allows the user to identify a set of similar chemicals (analogues) by computational \'profilers\' that incorporate different structural alerts, or a combination of structural alerts and physicochemical and/or toxicokinetic rules relevant to a specific toxicological endpoint. The overall aim of this study was to assess the performance of the in silico profilers provided in the OECD QSAR Toolbox for reliability for identifying chemical analogues for category formation in a number of high-quality databases on mutagenicity, carcinogenicity, and skin sensitisation. The study also aimed to identify the reasons for any limitations in the performance of the profilers, and propose ways to improve their overall accuracy. The results showed that whilst some structural alerts are fit-for-purpose as such within the acceptable limits, others need refinement or a consideration for their possible exclusion from the profiler. Such refinements are imperative for a reliable use of the profilers in read-across and grouping/categorisation for classification, labelling and risk assessment of chemicals.

Healthcare professionals have first-hand experience with patients in clinical practice and the dynamics in the healthcare system, which can be of great value in the design, implementation, data analysis and dissemination of research study results. Primary care professionals are particularly important as they provide first contact, accessible, coordinated, comprehensive and continuous people-focused care. However, in-depth examination of the engagement of health professionals in health system research and planning activities-how professionals are engaged and how this varies across national contexts- is limited, particularly in international initiatives. There is a need to identify gaps in the planning of engagement activities to inform the design and successful implementation of future international efforts to improve the responsiveness of health systems to the changing needs of patients and professionals. The aim of this study was to explore how primary care professionals were engaged in the design and implementation plans of an international health policy study led by the Organisation for Economic Co-operation and Development (OECD). The OECD\'s international PaRIS survey measures and disseminates information on patient-reported outcome and experience measures (PROMs and PREMs) of people living with chronic conditions who are managed in primary care. A documentary analysis of 17 written national implementation plans (country roadmaps) was conducted between January and June 2023. Two reviewers independently performed the screening and data abstraction and resolved disagreements by discussion. We reported the intended target primary care professionals, phase of the study, channel of engagement, level of engagement, and purpose of engagement. All 17 countries aimed to engage primary care professionals in the execution plans for the international PaRIS survey. While organisations of primary care professionals, particularly of family doctors, were the most commonly targeted group, variation was found in the timing of engagement activities during the different phases of the study and in the level of engagement, ranging from co-development (half of the countries co-developed the survey together with primary care professionals) to one-off consultations with whom. International guidance facilitated the participation of primary care professionals. Continuous collaborative efforts at the international and national levels can foster a culture of engagement with primary care organisations and individual professionals and enhance meaningful engagement of primary care professionals.

The OECD has approved two similar methods for testing the phototoxic potency of chemicals. The first method, OECD 432, is based on the cytotoxicity properties of materials to the mouse 3T3 (clone A31) cell line (fibroblasts) after exposure to light. The second method, OECD 498, is based on the same properties but using reconstructed human epidermis - EpiDerm (stratified keratinocytes). The aim of this study was to compare these two methods using statistical tests (specificity, sensitivity, negative predictive value, positive predictive value and accuracy) and non-statistical characteristics (e.g. price and experimental duration, amount of material, level of complications, cell type, irradiation dose). Both tests were performed according to the relevant guidelines using the same 11 control substances. Higher performance values were observed for OECD 432 in both phototoxic and non-phototoxic classifications. The accuracy of OECD 432 was 90.9%, while that of OECD 498 was 72.7%. OECD 432 was also shorter and less expensive. On the other hand, OECD 498 was less complicated, and used human cells with stratum corneum, which better reflects real skin. This method can also be used with oily substances that are poorly soluble in water. However, both methods are important for testing the phototoxic properties of materials, and can be used alone or in a tiered strategy.

Green growth is of great importance in terms of solving environmental problems and achieving sustainable development goals. However, the existing literature has not investigated how green growth affects environmental degradation and environmental sustainability variables. In light of this gap, this study aims to analyse the impact of green growth and institutional quality on CO2 emissions, ecological footprint and inverse load capacity factor in OECD countries by constructing three different models. The results of the analysis indicate that (i) green growth exerts a significant mitigating and differentiating effect on CO2, ecological footprint and inverted load capacity factor in the long run. This is evidenced by a 1% increase in green growth reducing CO2, ecological footprint and inverted load capacity factor by 0.563%, 0.373% and 0.198%, respectively. (i) The impact of green growth on CO2 and inverted load capacity factor in the long run is negative and statistically significant; (ii) the impact of green growth on CO2 and inverted load capacity factor in the short run is negative and statistically significant; (iii) the impact of institutional quality on deterioration is positive and significant in the long run; (iv) the impact of population on deterioration and sustainability is significant and mixed. The findings indicate that decision-makers in OECD countries should review green energy policies when setting the sustainable development goals, as environmental sustainability is more challenging than reducing pollution.

In the current knowledge-based economy, the abilities of the national research system are a key driver of the country\'s competitiveness and socio-economic development. This paper compares the scientific standing of the OECD countries and eight other relevant economies. We use a bibliometric indicator of research performance, applied first at the individual level. This approach avoids the distortions of the aggregate-level analyses extant in literature and practice, which overlook the different publication intensities across research fields. We find a strong correlation between research performance and the economic competitiveness of nations and a moderate but significant correlation between research performance and the propensity to spend on research.