The predictors of COVID-19 mortality among health systems parameters: an ecological study across 203 countries

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.

Global association between air pollution and COVID-19 mortality: A systematic review and meta-analysis

BACKGROUND

The COVID-19 pandemic presents unprecedented challenge for global public health systems and exacerbates existing health disparities. Epidemiological evidence suggested a potential linkage between particulate and gaseous pollutants and COVID-19 mortality. We aimed to summarize the overall risk of COVID-19 mortality associated with ambient air pollutants over the short- and long-term.

METHODS

For the systematic review and meta-analysis, we searched five databases for studies evaluating the risk of COVID-19 mortality from exposure to air pollution. Inclusion of articles was assessed independently on the basis of research topic and availability of effect estimates. The risk estimates (relative risk) for each pollutant were pooled with a random-effect model. Potential heterogeneity was explored by subgroup analysis. Funnel plots and trim-and-fill methods were employed to assess and adjust for publication bias.

FINDINGS

The systematic review retrieved 2059 records, and finally included 43 original studies. PM2.5 (RR: 1.71, 95 % CI: 1.40-2.08, per 10 μg/m3 increase), NO2 (RR: 1.33, 1.07-1.65, per 10 ppb increase) and O3 (RR: 1.61, 1.00-2.57, per 10 ppb increase) were positively associated with COVID-19 mortality for long-term exposures. Accordingly, a higher risk of COVID-19 mortality was associated with PM2.5 (1.05, 1.02-1.08), PM10 (1.05, 1.01-1.08), and NO2 (1.40, 1.04-1.90) for short-term exposures. There was some heterogeneity across subgroups of income level and geographical areas.

CONCLUSION

Both long-term and short-term exposures to ambient air pollution may increase the risk of COVID-19 mortality. Future studies utilizing individual-level information on demographics, exposures, outcome ascertainment and confounders are warranted to improve the accuracy of estimates.

National governance and excess mortality due to COVID-19 in 213 countries: a retrospective analysis and perspectives on future pandemics

BACKGROUND

National governance may have influenced the response of institutions to the Covid-19 pandemic, being a key factor in preparing for the next pandemics. The objective was to analyze the association between excess mortality due to COVID-19 (daily and cumulative per 100 thousand people) and national governance indicators in 213 countries.

METHOD

Multiple linear regression models using secondary data from large international datasets that are in the public domain were performed. Governance indicators corresponded to six dimensions: (i) Voice and Accountability; (ii) Political Stability and Absence of Violence/Terrorism; (iii) Government Effectiveness; (iv) Regulatory Quality; (v) Rule of Law and (vi) Control of Corruption. The statistical analysis consisted of adjusting a multiple linear regression model. Excess mortality due to COVID-19 was adjusted for potential confounding factors (demographic, environmental, health, economic, and ethnic variables).

RESULTS

The indicators Control of Corruption, Government Effectiveness, Regulatory Quality and Rule of Law had a significant inverse association (p < 0.0001) with the estimated excess mortality in 2020, 2021 and 2022. Furthermore, the governance indicators had a direct significant association (p < 0.0001) with the vaccination variables (People_fully_vaccinated; Delivered population; The total number of vaccination doses administered per 100 people at the country level), except for the variables Vaccination policies and Administration of first dose, which were inversely associated. In countries with better governance, COVID-19 vaccination was initiated earlier.

CONCLUSION

Better national governance indicators were associated with lower excess mortality due to COVID-19 and faster administration of the first dose of the COVID-19 vaccine.

Country-level predictors of COVID-19 mortality

This study aimed to identify country-level predictors of COVID-19 mortality, after controlling for diverse potential factors, and utilizing current worldwide mortality data. COVID-19 deaths, as well as geographic, demographic, socioeconomic, healthcare, population health, and pandemic-related variables, were obtained for 152 countries. Continuous variables were examined with Spearman's correlation, categorical variables with ANOVA or Welch's Heteroscedastic F Test, and country-level independent predictors of COVID-19 mortality identified by weighted generalized additive models. This study identified independent mortality predictors in six limited models, comprising groups of related variables. However, in the full model, only WHO region, percent of population ≥ 65 years, Corruption Perception Index, hospital beds/100,000 population, and COVID-19 cases/100,000 population were predictive of mortality, with model accounting for 80.7% of variance. These findings suggest areas for focused intervention in the event of similar future public health emergencies, including prioritization of the elderly, optimizing healthcare capacity, and improving deficient health sector-related governance.

Evaluation of the Global Health Security Index as a predictor of COVID-19 excess mortality standardised for under-reporting and age structure

BACKGROUND

Previous studies have observed that countries with the strongest levels of pandemic preparedness capacities experience the greatest levels of COVID-19 burden. However, these analyses have been limited by cross-country differentials in surveillance system quality and demographics. Here, we address limitations of previous comparisons by exploring country-level relationships between pandemic preparedness measures and comparative mortality ratios (CMRs), a form of indirect age standardisation, of excess COVID-19 mortality.

METHODS

We indirectly age standardised excess COVID-19 mortality, from the Institute for Health Metrics and Evaluation modelling database, by comparing observed total excess mortality to an expected age-specific COVID-19 mortality rate from a reference country to derive CMRs. We then linked CMRs with data on country-level measures of pandemic preparedness from the Global Health Security (GHS) Index. These data were used as input into multivariable linear regression analyses that included income as a covariate and adjusted for multiple comparisons. We conducted a sensitivity analysis using excess mortality estimates from WHO and The Economist.

RESULTS

The GHS Index was negatively associated with excess COVID-19 CMRs (table 2; β= -0.21, 95% CI= -0.35 to -0.08). Greater capacities related to prevention (β= -0.11, 95% CI= -0.22 to -0.00), detection (β= -0.09, 95% CI= -0.19 to -0.00), response (β = -0.19, 95% CI= -0.36 to -0.01), international commitments (β= -0.17, 95% CI= -0.33 to -0.01) and risk environments (β= -0.30, 95% CI= -0.46 to -0.15) were each associated with lower CMRs. Results were not replicated using excess mortality models that rely more heavily on reported COVID-19 deaths (eg, WHO and The Economist).

CONCLUSION

The first direct comparison of COVID-19 excess mortality rates across countries accounting for under-reporting and age structure confirms that greater levels of preparedness were associated with lower excess COVID-19 mortality. Additional research is needed to confirm these relationships as more robust national-level data on COVID-19 impact become available.

Variation in Global Policy Responses to COVID-19: A Bidirectional Analysis

Against the unprecedented outbreaks of the COVID-19 variants, countries have introduced restrictive measures with discretion, ranging from lifting the closure thoroughly to implementing stringent policies, but all together guarding the global public health. Under the changing circumstances, we firstly apply the panel data vector autoregression (PVAR) model, using a sample of 176 countries/territories from 15 June 2021 to 15 April 2022, to estimate the potential associations among the policy responses, the progression of COVID-19 in deaths and vaccination, and medical resources possessed. Furthermore, we use the random effect method and the fixed effect speculation, to examine the determinants of policy variances across regions and over time. Our work has four main findings. Firstly, it showed the existence of a bidirectional relationship between the policy stringency and variables of interest including new daily deaths, the fully vaccinated percentage and health capacity. Secondly, conditional on the availability of vaccines, the sensitivity of policy responses to the death numbers tends to decline. Thirdly, the role of health capacity matters in coexisting with the virus mutation. Fourthly, regarding the variance in policy responses over time, the impact of new deaths tends to be seasonal. As to geographical differences in policy responses, we present the analysis for Asia, Europe, and Africa, and they show different levels of dependencies on the determinants. These findings suggest that bidirectional correlations exist in the complex context of wrestling with the COVID-19, as government interventions exert influence on the virus spread, the policy responses also progress alongside multiple factors evolving in the pandemic. This study will help policymakers, practitioners, and academia to formulate a comprehensive understanding of the interactions between policy responses and the contextualized implementation factors.

Outcome prediction in hospitalized COVID-19 patients: Comparison of the performance of five severity scores

Background

The aim of our study was to externally validate the predictive capability of five developed coronavirus disease 2019 (COVID-19)-specific prognostic tools, including the COVID-19 Spanish Society of Infectious Diseases and Clinical Microbiology (SEIMC), Shang COVID severity score, COVID-intubation risk score-neutrophil/lymphocyte ratio (IRS-NLR), inflammation-based score, and ventilation in COVID estimator (VICE) score.

Methods

The medical records of all patients hospitalized for a laboratory-confirmed COVID-19 diagnosis between May 2021 and June 2021 were retrospectively analyzed. Data were extracted within the first 24 h of admission, and five different scores were calculated. The primary and secondary outcomes were 30-day mortality and mechanical ventilation, respectively.

Results

A total of 285 patients were enrolled in our cohort. Sixty-five patients (22.8%) were intubated with ventilator support, and the 30-day mortality rate was 8.8%. The Shang COVID severity score had the highest numerical area under the receiver operator characteristic (AUC-ROC) (AUC 0.836) curve to predict 30-day mortality, followed by the SEIMC score (AUC 0.807) and VICE score (AUC 0.804). For intubation, both the VICE and COVID-IRS-NLR scores had the highest AUC (AUC 0.82) compared to the inflammation-based score (AUC 0.69). The 30-day mortality increased steadily according to higher Shang COVID severity scores and SEIMC scores. The intubation rate exceeded 50% in the patients stratified by higher VICE scores and COVID-IRS-NLR score quintiles.

Conclusion

The discriminative performances of the SEIMC score and Shang COVID severity score are good for predicting the 30-day mortality of hospitalized COVID-19 patients. The COVID-IRS-NLR and VICE showed good performance for predicting invasive mechanical ventilation (IMV).

Current Impact and Long-Term Influence of the COVID-19 Pandemic on Iraqi Healthcare Systems: A Case Study

Decades of wars, sanctions, and internal conflicts have compromised Iraq's health system, which once was the best system in the region. National and international efforts to revitalize the system have been successful to some extent; however, significant challenges still exist. The COVID-19 pandemic has exposed new vulnerabilities and exacerbated the existing ones, affecting the quality and the quantity of the health services delivered. This case study explored the baseline function of Iraq's health system within the context of the World Health Organization (WHO) health system framework. The paper also examined the country's response to the COVID-19 pandemic and some of its impacts. Results show that the system was not functioning optimally nor was it prepared to address the immediate impact of the current pandemic and other emerging public health issues. While mitigating the pandemic's short-term and long-term impacts are essential, it should not divert the focus from restructuring and strengthening the health system. Iraq may need to prioritize the health information system and leadership/governance as they provide the basis for health policies and regulations for all other health system building blocks.