Global Health Security Index Research Articles

Forging Pathways to Equity: The Nexus between Land Redistribution, Health, and Healthcare Access

This article explores the nexus between land redistribution policies and healthcare accessibility to mitigate social and economic disparities arising from inequitable land distribution. Historically, concentrated land ownership has marginalised rural communities, limiting their access to healthcare services. Land reform initiatives focusing on redistribution and secure tenure have the potential to empower marginalised groups economically and enhance their health outcomes through improved access to healthcare facilities. The study fills Gaps in existing research by investigating the interconnectedness of land tenure security, health outcomes and healthcare access, drawing insights from global contexts, including successful cases in Denmark, New Zealand, and South Korea, alongside challenges in Russia, India, and South Africa. Through a comprehensive literature review and analysis of data from the Global Health Security Index, the study highlights the critical role of equitable land distribution in fostering health equity and sustainable development. Findings suggest that countries with inclusive land policies demonstrate improved public health indicators, highlighting the importance of integrating land reform into broader health and development agendas. In conclusion, land redistribution holds promise for enhancing healthcare access and achieving health equity. Ultimately, this research advocates for strategic interventions that prioritise fair land distribution as a cornerstone for achieving universal health coverage and addressing persistent health disparities worldwide.

Comparison of the Bulut Index-Beta method and Global Health Security Index: results from the world's countries.

The Global Health Security Index (GHSI), which is used to assess the global health security preparedness levels of countries, and the Bulut Index-Beta (BI-β) method, developed as a multicriteria decision-making method, were compared in terms of global health security in the context of the world's countries. It was aimed to demonstrate the feasibility of the BI-β method by testing it on GHSI datasets and contribute to the methodological development of the GHSI. The datasets used in this study were the publicly available GHSI datasets, which allow for comparative evaluations of countries. The BI-β method and GHSI were used to compare countries in terms of global health security. In 2021, the top three best-performing countries in terms of global health security were the United States (BI-β = 85.46), Australia (BI-β = 82.53), and the United Kingdom (BI-β = 82.29). For 2019, the United States (BI-β = 85.44) and Australia (BI-β = 81.69) had the same ranks as in 2021, but the United Kingdom (BI-β = 76.63) dropped to 9th place. There was a statistically significant positive weak monotonic relationship between BI-β and GHSI rankings. Since the GHSI scoring system is not consistent or questionable, the weighting process needs to be objectively reconsidered and the reasons for the weighting process need to be explained. The GHSI was conceptualized based on a narrow and technical framework. Therefore, it is recommended that the social and political determinants of public health be taken into account in the GHSI. On the other hand, the BI-β method can be easily used in solving other multicriteria decision-making problems, especially in public health areas such as global health security.

High-Level Isolation: A Landscape Analysis of Global Capabilities and Opportunities to Advance the Field.

High-level isolation units (HLIUs) have been established by countries to provide safe and optimal medical care for patients with high-consequence infectious diseases. We aimed to identify global high-level isolation capabilities and determine gaps and priorities of global HLIUs, using a multiple method approach that included a systematic review of published and gray literature and a review of Joint External Evaluations and Global Health Security Index reports from 112 countries. A follow-up electronic survey was distributed to identified HLIUs. The landscape analysis found 44 previously designated/self-described HLIUs in 19 countries. An additional 33 countries had potential HLIUs; however, there were not enough details on capabilities to determine if they fit the HLIU definition. An electronic survey was distributed to 36 HLIUs to validate landscape analysis findings and to understand challenges, best practices, and priorities for increased networking with a global HLIU cohort; 31 (86%) HLIUs responded. Responses revealed an additional 30 confirmed HLIUs that were not identified in the landscape analysis. To our knowledge, this was the first mapping and the largest ever survey of global HLIUs. Survey findings identified major gaps in visibility of HLIUs: while our landscape analysis initially identified 44 units, the survey unveiled an additional 30 HLIUs that had not been previously identified or confirmed. The lack of formalized regional or global coordinating organizations exacerbates these visibility gaps. The unique characteristics and capabilities of these facilities, coupled with the likelihood these units serve as core components of national health security plans, provides an opportunity for increased connection and networking to advance the field of high-level isolation and address identified gaps in coordination, build an evidence base for HLIU approaches, and inform HLIU definitions and key components.

Prioritizing Indicators for Rapid Response in Global Health Security: A Bayesian Network Approach

This study explored a Bayesian belief networks (BBNs) approach, developing two distinct models for prioritizing the seven indicators related to the “rapid response to and mitigation of the spread of an epidemic” category within the context of both the specific category and the Global Health Security Index (GHS index). Utilizing data from the 2021 GHS index, the methodology involves rigorous preprocessing, the application of the augmented naive Bayes algorithm for structural learning, and k-fold cross-validation. Key findings show unique perspectives in both BBN models. In the mutual value of information analysis, “linking public health and security authorities” emerged as the key predictor for the “rapid response to and mitigation of the spread of an epidemic” category, while “emergency preparedness and response planning” assumed precedence for the GHS index. Sensitivity analysis highlighted the critical role of “emergency preparedness and response planning” and “linking public health and security authorities” in extreme performance states, with “access to communications infrastructure” and “trade and travel restrictions” exhibiting varied significance. The BBN models exhibit high predictive accuracy, achieving 83.3% and 82.3% accuracy for extreme states in “rapid response to and mitigation of the spread of an epidemic” and the GHS index, respectively. This study contributes to the literature on GHS by modeling the dependencies among various indicators of the rapid response dimension of the GHS index and highlighting their relative importance based on the mutual value of information and sensitivity analyses.

Health Security and Cybersecurity: Analysis of Interdependencies

The development of medical digital platforms with data on patients, medical institutions and medicines, the growing use of IoT devices in medicine, the development of telemedicine accelerated by the COVID-19 pandemic, the growth of big data-based treatment technologies – all this makes it necessary to ensure reliable cyberdefence in the field of public health, maintain the confidentiality of financial information of clinics and health insurance companies, protect databases with patient records from hacking, and ensure secure communication. The article uses economic and mathematical modelling to study the relationship between two well-known international indexes and their components: The Global Health Security Index (GHSI) and the Global Cybersecurity Index (GCSI) for 190 countries in 2021. The input base included 6 cybersecurity subindexes and 7 health security subindexes for 2021. Based on the iterative divisive k-means method, all countries were grouped into 3 clusters. The first cluster includes 55 countries (medium levels of the studied indexes), the second – 49 (high levels), the third – 86 (low levels). The feasibility of dividing into clusters and choosing their optimal number is substantiated by means of variance analysis. Via the methods of Sigma-restricted parameterisation, Univariate Tests of Significance, Pareto Chart of t-Values and correlation analysis, all factors, without exception, proved to be relevant. Due to the OLS method, multiple linear regressions describing the relationships between various components of these indexes and their integral values are generated. The statistical significance of the factors included in the model is confirmed, and the model itself is tested for adequacy and accuracy. On the basis of correlation analysis, existence and magnitude of statistical relationship between the components of these indexes are revealed. The strongest correlations are observed between the integral values of these indexes, as well as between pairs of subindexes: 1) Legal Measures (GHSI component) and Prevention (GCSI component); 2) Technical Measures (GHSI component) and Detection and Reporting (GCSI component). To identify the causal relationship between the groups of factors, a canonical analysis was carried out, which showed the GHSI parameters are causal and the GCSI parameters are resultant. The linear regression model showed a significant positive relationship between the GHSI and GCSI indexes.

From prevention to response: A holistic exploration of factors shaping Global Health Security

In the face of global challenges, ensuring robust health security is paramount for safeguarding populations against emerging threats. Using country-level data on the Global Health Security (GHS) index covering 195 countries, this study employs Bayesian Belief Networks (BBNs) to explore probabilistic dependencies among various indicators that can influence health security outcomes. The findings reveal distinct probabilities of low performance for certain components within main indicators such as ‘prevention’, ‘early detection and reporting’, and ‘sufficient and robust health sector’, significantly shaping overall health security outcomes. Particularly noteworthy is the identification of ‘early detection and reporting’ as the most critical indicator, showing an 87% probability improvement, followed closely by ‘prevention’ at 81%. The latter part of the study delves into the sub-indicators associated with ‘early detection and reporting’. This analysis uncovers varying probabilities of extreme performance states, with ‘laboratory supply chains’ emerging as the most crucial sub-indicator, presenting an 84% probability improvement. Conversely, the ‘epidemiology workforce’ is deemed less influential in impacting overall health security outcomes. Assessing the mutual value of information sheds light on the informative nature of ‘prevention’ and ‘sufficient and robust health sector’ within the main indicators, while in sub-indicators, ‘surveillance data accessibility and transparency’ take precedence.

Pandemic preparedness improves national-level SARS-CoV-2 infection and mortality data completeness: a cross-country ecologic analysis

BackgroundHeterogeneity in national SARS-CoV-2 infection surveillance capabilities may compromise global enumeration and tracking of COVID-19 cases and deaths and bias analyses of the pandemic’s tolls. Taking account of heterogeneity in data completeness may thus help clarify analyses of the relationship between COVID-19 outcomes and standard preparedness measures.MethodsWe examined country-level associations of pandemic preparedness capacities inventories, from the Global Health Security (GHS) Index and Joint External Evaluation (JEE), on SARS-CoV-2 infection and COVID-19 death data completion rates adjusted for income. Analyses were stratified by 100, 100–300, 300–500, and 500–700 days after the first reported case in each country. We subsequently reevaluated the relationship of pandemic preparedness on SARS-CoV-2 infection and age-standardized COVID-19 death rates adjusted for cross-country differentials in data completeness during the pre-vaccine era.ResultsEvery 10% increase in the GHS Index was associated with a 14.9% (95% confidence interval 8.34–21.8%) increase in SARS-CoV-2 infection completion rate and a 10.6% (5.91–15.4%) increase in the death completion rate during the entire observation period. Disease prevention (infections: β = 1.08 [1.05–1.10], deaths: β = 1.05 [1.04–1.07]), detection (infections: β = 1.04 [1.01–1.06], deaths: β = 1.03 [1.01–1.05]), response (infections: β = 1.06 [1.00–1.13], deaths: β = 1.05 [1.00–1.10]), health system (infections: β = 1.06 [1.03–1.10], deaths: β = 1.05 [1.03–1.07]), and risk environment (infections: β = 1.27 [1.15–1.41], deaths: β = 1.15 [1.08–1.23]) were associated with both data completeness outcomes. Effect sizes of GHS Index on infection completion (Low income: β = 1.18 [1.04–1.34], Lower Middle income: β = 1.41 [1.16–1.71]) and death completion rates (Low income: β = 1.19 [1.09–1.31], Lower Middle income: β = 1.25 [1.10–1.43]) were largest in LMICs. After adjustment for cross-country differences in data completeness, each 10% increase in the GHS Index was associated with a 13.5% (4.80–21.4%) decrease in SARS-CoV-2 infection rate at 100 days and a 9.10 (1.07–16.5%) decrease at 300 days. For age-standardized COVID-19 death rates, each 10% increase in the GHS Index was with a 15.7% (5.19–25.0%) decrease at 100 days and a 10.3% (− 0.00–19.5%) decrease at 300 days.ConclusionsResults support the pre-pandemic hypothesis that countries with greater pandemic preparedness capacities have larger SARS-CoV-2 infection and mortality data completeness rates and lower COVID-19 disease burdens. More high-quality data of COVID-19 impact based on direct measurement are needed.

The synergistic impact of Universal Health Coverage and Global Health Security on health service delivery during the Coronavirus Disease-19 pandemic: A difference-in-difference study of childhood immunization coverage from 192 countries.

Universal Health Coverage (UHC) and Global Health Security (GHS) are two high-priority global health agendas that seek to foster health system resilience against health emergencies. Many countries have had to prioritize one agenda over the other due to scarce resources and political pressures. To aid policymakers' decision-making, this study investigated the individual and synergistic effects of countries' UHC and GHS capacities in safeguarding essential health service delivery during the COVID-19 pandemic. We used a quasi-experimental difference-in-difference methodology to quantify the relationship between 192 countries' progress towards UHC and GHS and those countries' abilities to provide 12 essential childhood immunization services between 2015 and 2021. We used the 2019 UHC Service Coverage Index (SCI) to divide countries into a "high UHC group" (UHC SCI≥75) and the rest (UHC SCI 75), and similarly used the 2019 GHS Index (GHSI) to divide countries into a "high GHS group" (GHSI≥65) and the rest (GHSI<65). All analyses were adjusted for potential confounders. Countries with high UHC scores prevented a 1.14% (95% CI: 0.39%, 1.90%) reduction in immunization coverage across 2020 and 2021 whereas countries with high GHSI scores prevented a 1.10% (95% CI: 0.57%, 1.63%) reduction in immunization coverage over the same time period. The stratified DiD models showed that across both years, high UHC capacity needed to be augmented with high GHS capacity to prevent a decline in immunization coverage while high GHS alone was able to safeguard immunization coverage. This study found that greater progress towards both UHC and GHS capacities safeguarded essential health service delivery during the pandemic but only progress towards GHS capacity was both a necessary and likely sufficient element for yielding this protective effect. Our results call for strategic investments into both health agendas and future research into possible synergistic effects of the two health agendas.

Selection of Key Socio-Economic Factors for Establishing Relese Criteria Patients after Radioioidine Therapy

Purpose: To assess the association between socioeconomic factors and release criteria after iodine-131 radionuclide therapy in different countries. Material and methods: 15 countries and 104 socioeconomic characteristics were selected for the study. The association between characteristics and the residual activity level at which a patient may be released for different countries was established according to the value of Pearson product moment correlation coefficient (r&gt;0.3). A linear regression model was constructed for the selected characteristics using Microsoft Excel analysis package. The model was used to calculate the acceptable activity level at which a patient may be released for Russia. Results: A fundamental difference between the model used for calculation of release criteria after radionuclide therapy with iodine-131 in Russia and the model recommended by the Nuclear Regulatory Commission was shown: the use of the effective half-life in the second one. Replacing the physical halflife by the effective half life allows increasing the discharge criteria of patients after therapy with Na131I by 30 %. A moderate correlation was found between the value of acceptable activity at patient discharge after radioactive iodine therapy and the following socioeconomic characteristics: scientific activity (r=0.32), quality of higher education (r=0.36), Global Health Security Index (r=0.34), length of roads (r=0.36), population growth rate (r=0.36), average housing area (r=0.38), and average salary per year (r=–0.33). A linear regression was constructed using the factors listed above. The following recommended value of activity and effective dose rate at patient discharge from hospital was obtained: 0.6 GBq and 30 µSv/hour. Conclusion: The study demonstrates that the release criteria for radioactive iodine therapy used in the Russian Federation (0.4 GBq and 20 µSv/h) do not correspond to the standard of living achieved in Russia, which is reflected by the socio-economic factors considered in the paper. The proposed arguments raise the task of revising the currently used model with a consequent increase in the discharge criteria. It was observed that the release criteria in the world are independent of some factors that are directly related to population exposure. The need to develop a unified objective algorithm for establishing release criteria, which takes into account different socio-economic status of states and can be applied for different radionuclides and radiopharmaceuticals, including innovative ones, has been identified.

China’s Compliance to International Health Law and Its Implication to Global Health Security

The Covid 19 pandemic presented a defining challenge to public health and global security. The outbreak of the pandemic in China and its global implications raised persistent doubts of states’ compliance to international health laws. The pandemic therefore, provides an opportunity for us to ascertain the extent to which China adhered to the International Health Regulations. Though a great deal of experts have scrutinized Chinese public health policies in the aftermath of the pandemic, China’s compliance to the 2005 International Health Regulation and its implication to global health security remained unclear. The analysis is largely derived from the Global Health Security-GHS Index and other primary legal texts. The GHS Index represents the first comprehensive unit of measurement of global health security across 195 countries that are parties to the 2005 International Health Regulations. The outcome of the analysis exposed significant gaps in China’s compliance to international health laws. It also indicates that, though international health laws provide useful guidance to prevent, respond and manage pandemics, they are implemented in an ad hoc manner and generally have few tools at their disposal to enforce compliance. China’s failure to timely and adequately discharge its duties under the International Health Regulation prior to and in the wake of Covid 19 shows that the international community needs a new legal enforcement mechanism to ensure that states act promptly, transparently and effectively to protect the world’s population against pandemics. The challenge of a lack of statutory enforcement mechanism is insurmountable and it remains uncertain what the future holds for global health security.

EFFECT OF HEALTH SYSTEM PERFORMANCE ON VOLATILITY DURING THE COVID-19 PANDEMIC: A NEURAL NETWORK APPROACH

The study proposes an assessment of the link between the performance of national health systems and volatility during the COVID-19 pandemic. Data from the World Health Organization was accessed regarding the Global Health Security Index of the states considered in the analysis as well as the categories based on which it is determined. To characterise volatility, a representative stock market index was considered for each of the 60 states analysed. Data processing was carried out using an artificial neural network. The main results show that: i) before the pandemic, the link between market volatility and the performance of national health systems was weak; ii) during the pandemic, the connection between the two variables is much stronger; iii) between the six categories that define the Global Health Security Index, norms, health, and prevention had the greatest influence on volatility.

High Global Health Security Index is a determinant of early detection and response to monkeypox: A cross-sectional study.

Recent outbreaks of monkeypox (Mpox) have occurred in countries outside of Africa, with large numbers of cases spreading rapidly to almost every continent. We aimed to analyze the correlation between the Global Health Security (GHS) Index (categories and indicators) and the Mpox case rate in different regions and globally. In this cross-sectional study, we used data from Mpox cases from the WHO, and the GHS categories and indicators for detection, prevention, reporting, health system, rapid response, international norms compliance, and risk environment. Outcome measures were the relationship between GHS index (categories and indicators) and Mpox case rate using crude and adjusted non-linear regression models. After performing adjusted analyses, only risk environment and detection and reporting index were associated with Mpox case rates in the 99 countries and the Region of the Americas, respectively. Antimicrobial resistance (AMR) indicators of the prevention category, risk communication of the rapid response category, the joint external evaluation and performance veterinary services of the norms category, and the infrastructure adequacy of the risk environment category were associated with Mpox case rates in the 99 countries (p<0.05). Laboratory systems strength and quality indicator of the detection and reporting category, and emergency response operation indicator of the response rapid category were associated with Mpox case rates in the countries of the region of the Americas (p<0.05). AMR indicator of the prevention of the emergence category, and the infrastructure adequacy of the risk environment category were associated with Mpox case rates in the countries of the European Region (p<0.05). In the countries of the other regions, only the trade and travel restrictions indicator of the rapid response category was associated with Mpox case rates (p<0.05). Countries, particularly in the Americas region, with high levels of infrastructure adequacy and laboratory system strength and quality as measured by the GHS index are better equipped to detect more Mpox cases. Therefore, they have higher Mpox case detection rates and can successfully respond to Mpox outbreaks.

Present and Future Infectious Diseases Challenges for the Greek State and Society

The current pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) has redefined normality in many social parameters, and has imposed (and continues to) a significant additional burden on health settings, economy, and state resilience worldwide. On the other hand, the SARS-CoV-2 pandemic has highlighted the vulnerabilities that pre-existed in our planning for facing major health-related events. One wonders though whether these lessons are learned, and whether they can be implemented in real life, particularly in a country like Greece, that is still under the shadow of the financial distraught of the previous decade. Based on the Global Health Security Index,1 which measures individual countries’ capability and infrastructure adequacy to deal with epidemics and pandemics, Greece has not exhibited systematic progress in improving aspects of health security that lagged behind the global average. For example, the Greek score for immunization exhibited a significant decline between 2019 and 2021. Other aspects that improved, or remained steady, between the 2019 and 2021 evaluations have not yet reached the global average, as is for example the zoonotic disease, emergency preparedness and response planning, dual-use research and culture of responsible science, real-time surveillance and reporting, case-based investigation, risk communication, medical countermeasures and personnel deployment, healthcare access, communications with health-care workers during a public health emergency, specific funding for correcting gaps identified by Joint External Evaluation or Performance of Veterinary Sciences, financing health, commitment to sharing of genetic and biological data and specimens, infrastructure adequacy, and environmental risks. That’s a lot of work to be done, and it has to be performed in times with significant infectious disease risks, either circulating or anticipated.

Empowering citizens in conservation of family medicinal plants through processing rosella flowers into tea

The quality of health in Indonesia is included in the low category compared to other countries. Based on the results of the GHSI (Global Health Security Index) report, the average global health score is 38.9 points out of a score of 100 points. Meanwhile, Indonesia's global health security index ranks 13th compared to other G20 countries. One of the factors causing a country's low quality of health is caused by the level of a country's economy. This program aims to empower people in the fields of health, economy, and human resources by conserving family medicinal plants from roselle flowers that are processed into tea. The method used in this program is participatory, where environmental scanning is integral to empowering communities through building self-reliance with the power of resources and products. Program results are achieved from the fulfillment of success indicators prepared based on the objectives of the implementation of the program. There are nine main points in the indicators of success that can be achieved. In conclusion, the community empowerment program in Jatimalang Village, Klirong District, Kebumen Regency, has been built from the fulfillment of village-based SDGs and the awareness of the superiority of natural potential owned.

Associations of diabetes, hypertension and obesity with COVID-19 mortality: a systematic review and meta-analysis

IntroductionDespite a growing body of scholarly research on the risks of severe COVID-19 associated with diabetes, hypertension and obesity, there is a need for estimating pooled risk estimates with adjustment...

The application of policy composite indicators to predicting the health risk and recovery: a global comparative investigation

ObjectivesThere emerges increasing doubt regarding whether the policy composite indicators are applicable to the COVID-19 pandemic. A few early studies demonstrate that the association between some composite indicators of policy preparedness and the risk of COVID-19 is statistically insignificant, and the relation between any composite indicators and recovery process (e.g., vaccination coverage) remains unexplored. To examine the relation between composite indicators and pandemic risk (as well as the vaccination coverage) with robustness, this study applies different policy preparedness indicators by using data from multi-sources. Study designA cross-sectional analysis was performed. MethodRegression analysis is adopted to examine the relation between four policy preparedness indicators (i.e., [1] International Health Regulations core capacity index, [2] Global Health Security Index, [3] epidemic preparedness index, and [4] World Governance Index) and COVID-19-confirmed cases/death/vaccination coverage at different time points. The linear regression is performed, and the spatial distribution of indicators are illustrated. ResultsCountries with higher ranking in policy preparedness indexes can experience less severity of pandemic risk (e.g., confirmed cases and mortality) and faster recovery process (e.g., higher vaccination coverage). However, slight disparity in effectiveness exists across different indicators. ConclusionResults show that the policy preparedness indicators have predictive value of the confirmed cases, mortality, and vaccination coverage of COVID-19 pandemic, given sufficiently long-time span is observed.

Research on the Compilation of a Composite Index from the Perspective of Public Value—The Case of the Global Health Security Index

The Global Health Security Index (GHSI), the first report on the world’s defensive capabilities against major infectious diseases, released in 2019, deviated from the actual performance of countries globally during COVID-19. Principal component analysis is used to deconstruct the multiple dimensions of public value on the GHSI index; reasons are explored for the deviation between the GHSI scoring results of countries worldwide and their performance in the COVID-19 pandemic, and the logical principles of composite index compilation are analyzed. The results show that the dimensions selected for inclusion in the GHSI are relatively isometric, and omissions of important values are the fundamental reason for the deviation. The composite index is the quantification of qualitative values, and public value affects the process of compiling the composite index in at least four respects: dimension selection, specific indicators, weight-setting, and evaluation-scoring. Therefore, public value should become the theoretical basis for compiling a composite index. This study effectively combines qualitative and quantitative research, provides theoretical explanations and practical guidance for further iterative updates of the GHSI and the optimization of world health and security governance tools, and provides a broader research perspective for the development of composite indices.

All-cause Excess Mortality Cross-sectional Correlation Analysis at Global Scale during COVID-19, 2020-22

The excess mortality during COVID-19 is significantly higher than the reported death due to COVID-19 infections. This study conducts a cross-sectional correlation analysis between excess mortality and reported COVID-19 death, aging rate, GHS (Global Health Security) index, and government response stringency index in the timeframe from January 2020 to September 2022. This study aims to explore the main contributors to excess mortality, hence to provide guidance on future diagnosis and control of the pandemic. A cross-sectional log-linear model is fitted with 79 observations to estimate the explanatory power of reported COVID-19 death, aging rate, GHS index and stringency index on excess mortality at a global scale. The correlation between excess mortality and reported COVID-19 death is also examined on a nation level by calculating the Spearman correlation coefficient on the time series of the two. The cross-sectional log-linear model has adjusted . The estimate for log of reported COVID death is ; aging rate is ; GHS index is ; stringency index is not significant. On a nation level, Brazil and United States have high correlations between reported and excess death (), the reported death takes up 85% and 86% respectively, of excess death. India and Japan, similarly, have high correlation coefficient (), but with COVID-19 death accounting 9% and 47% of excess death. Germany and China have relatively small correlations between reported and excess death (), but Germany has reported death taking up 89% of excess death, whereas in China the ratio is 4%. At a global scale, the reported COVID-19 death has the most explanatory power in excess mortality, which means that most of excess mortality is attributed to death from COVID-19 infections. Aging rate has a negative correlation between excess mortality, this is partly because of the preference of aged population to live in countries with better health care capacities. There is no significant explanatory power of stringency index on excess mortality, suggesting that the impact of government responses on COVID-19 vary by each nation. On a country level, the correlation between COVID-19 death and excess mortality can also vary, mostly due to the different levels of health care disruptions, efficiency and impact of government measures and other COVID-19 unrelated events such as wars and heat waves.

Exploring the relationship between the Global Health Security Index and monkeypox: an analysis of preparedness and response capacities

Exploring the relationship between the Global Health Security Index and monkeypox: an analysis of preparedness and response capacities

The Impact of the Organization of Public Health Systems on the Ability of Countries to Resist the COVID-19 Pandemic: The Experience of Developed Countries of the World and Ukraine.

The purpose of the study is to analyze the presence of functional interrelationships between the level of funding of the healthcare sector and the country's ability to withstand any pandemic, using the example of the COVID-19 pandemic. Official indicators presented by the WHO, analytical reports by Numbeo (the world's largest cost-of-living database), and the Global Health Security Index were used for the study. Using these indicators, the authors analyzed the following: the level of the spread of coronavirus infections in the world's countries, the share of public expenditures on the development of the medical sphere in the GDP of the countries, and the development of the healthcare sector in 12 developed countries and Ukraine. These countries were grouped into three groups, based on the model of the organization of the healthcare sector (Beveridge model, Bismark model, Market (private) model). The Farrar-Glauber method was used to check for multicollinearity in the input dataset, and thirteen relevant indicators were selected. These indicators took part in the formation of the generalized characteristics of the country's medical sphere and the ability to resist the pandemic. The state of readiness of countries to resist the spread of coronavirus infections was assessed using the country's index of vulnerability to COVID-19 and the integral index of the development of medicine. Additive convolution was used in combination with sigma-limited parameterization to form an integral index of the country's vulnerability to COVID-19 and to determine the weights of each indicator. The convolution of indicators according to the Kolmogorov-Gabor polynomial was used to construct an integral index of the development of medicine. Thus, while analyzing the ability of countries to resist the pandemic in terms of models of organization of the healthcare sector, it should be noted that none of the models demonstrated absolute effectiveness in the fight against the mass spread of COVID-19. The calculations made it possible to determine the nature of the relationship between the integral indices of the development of medicine and the vulnerability of countries to COVID-19, as well as a country's potential ability to resist any pandemic and prevent the mass spread of infectious diseases.