Universal Health Coverage to counteract the economic impact of the COVID-19 infection: current practices and ethical challenges

Impact of good governance, economic growth and universal health coverage on COVID-19 infection and case fatality rates in Africa

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has disrupted lives across all countries and communities. It significantly reduced the global economic output and dealt health systems across the world a serious blow. There is growing evidence showing the progression of the COVID-19 pandemic and the impact it has on health systems, which should help to draw lessons for further consolidating and realizing universal health coverage (UHC) in all countries, complemented by more substantial government commitment and good governance, and continued full implementation of crucial policies and plans to avert COVID-19 and similar pandemic threats in the future. Therefore, the objective of the study was to assess the impact of good governance, economic growth and UHC on the COVID-19 infection rate and case fatality rate (CFR) among African countries.

METHODS

We employed an analytical ecological study design to assess the association between COVID-19 CFR and infection rate as dependent variables, and governance, economic development and UHC as independent variables. We extracted data from publicly available databases (i.e., Worldometer, Worldwide Governance Indicators, Our World in Data and WHO Global Health Observatory Repository). We employed a multivariable linear regression model to examine the association between the dependent variables and the set of explanatory variables. STATA version 14 software was used for data analysis.

RESULTS

All 54 African countries were covered by this study. The median observed COVID-19 CFR and infection rate were 1.65% and 233.46%, respectively. Results of multiple regression analysis for predicting COVID-19 infection rate indicated that COVID-19 government response stringency index (β = 0.038; 95% CI 0.001, 0.076; P = 0.046), per capita gross domestic product (GDP) (β = 0.514; 95% CI 0.158, 0.87; P = 0.006) and infectious disease components of UHC (β = 0.025; 95% CI 0.005, 0.045; P = 0.016) were associated with COVID-19 infection rates, while noncommunicable disease components of UHC (β = -0.064; 95% CI -0.114; -0.015; P = 0.012), prevalence of obesity among adults (β = 0.112; 95% CI 0.044; 0.18; P = 0.002) and per capita GDP (β = -0.918; 95% CI -1.583; -0.254; P = 0.008) were associated with COVID-19 CFR.

CONCLUSIONS

The findings indicate that good governance practices, favourable economic indicators and UHC have a bearing on COVID-19 infection rate and CFR. Effective health system response through a primary healthcare approach and progressively taking measures to grow their economy and increase funding to the health sector to mitigate the risk of similar future pandemics would require African countries to move towards UHC, improve governance practices and ensure economic growth in order to reduce the impact of pandemics on populations.

Universal health care and political economy, neoliberalism and effects of COVID-19: A view of systems and complexity

Sturmberg and Martin's application of systems and complexity theory to understanding Universal Health Care (UHC) and Primary Health Care (PHC) is evaluated in the light of the influence of political economy on health systems. Furthermore, the role that neoliberal approaches to governance have had in creating increased inequities is seen as a key challenge for UHC. COVID-19 has emphasized long standing discrepancies in health and these disadvantages require government will and cooperation together with adequate social services to redress these discrepancies in UHC.

Effect of COVID-19 on the Number of CT-scans and MRI Services of Public Hospitals in Iran: An Interrupted Time Series Analysis

Background

In February 2020, the Ministry of Health and Medical Education in Iran announced the first case of COVID-19. The aim of this study was to investigate the impact of COVID-19 on the number of CT-Scans and MRI services in public hospitals in western Iran.

Methods

We collected CT-scans and MRI services data from 18 public hospitals via Vice-Chancellor Office, Lorestan University of Medical Sciences from January 2017 to February 2021. Interrupted time series analysis (ITSA) was conducted to assess the impact of COVID-19 on CT-Scans and MRI services. More specifically, ITSA was conducted using ordinary least squares regression with the number of CT-Scans and MRI services per 1,000 registered persons per month as dependent variable.

Results

At the beginning of the observation period, the monthly rate of CT-Scans was constant (p for trend = 0.267) at 291.9 (from 95%CI 240.5 to 343.4) per 1,000 registered patients. The first case of COVID-19 coincided with an abrupt increase by 211.8 (from 95%CI 102.9 to 320.7) per 1,000 patients. Thereafter, the trend of CT-Scans did not change (p=0.576) compared to the pre-pandemic period. The rate of MRI services was 363.5 per 1,000 per registered patients per month (P = <0.0001) with a slightly decreasing trend (coefficient=-5; 95%CI, -6.9 to -3.1).

Conclusion

The findings of this study showed that crises such as COVID-19 can affect the service delivery process. Health policymakers and decision makers should work to prevent potential reductions in health care during events such as COVID-19.

Recombinant Protein Expression and Purification of N, S1, and RBD of SARS-CoV-2 from Mammalian Cells and Their Potential Applications

The coronavirus disease 2019 (COVID-19) pandemic has reached an unprecedented level. There is a strong demand for diagnostic and serological supplies worldwide, making it necessary for countries to establish their own technologies to produce high-quality biomolecules. The two main viral antigens used for the diagnostics for severe acute respiratory syndrome coronavirus (SARS-CoV-2) are the structural proteins spike (S) protein and nucleocapsid (N) protein. The spike protein of SARS-CoV-2 is cleaved into S1 and S2, in which the S1 subunit has the receptor-binding domain (RBD), which induces the production of neutralizing antibodies, whereas nucleocapsid is an ideal target for viral antigen-based detection. In this study, we designed plasmids, pcDNA3.1/S1 and pcDNA3.1/N, and optimized their expression of the recombinant S1 and N proteins from SARS-CoV-2 in a mammalian system. The RBD was used as a control. The antigens were successfully purified from Expi293 cells, with high yields of the S1, N, and RBD proteins. The immunogenic abilities of these proteins were demonstrated in a mouse model. Further, enzyme-linked immunosorbent assays with human serum samples showed that the SARS-CoV-2 antigens are a suitable alternative for serological assays to identify patients infected with COVID-19.

Path Analysis to Assess Socio-Economic and Mitigation Measure Determinants for Daily Coronavirus Infections

(1) Background: With the rapid global spread of the coronavirus disease 2019 (COVID-19) and the relatively high daily cases recorded in a short time compared to other types of seasonal flu, the world remains under continuous threat unless we identify the key factors that contribute to these unexpected records. This identification is important for developing effective criteria and plans to reduce the spread of the COVID-19 pandemic and can guide national authorities to tighten or reduce mitigation measures, in addition to spreading awareness of the important factors that contribute to the propagation of the disease. (2) Methods: The data represents the daily infections (210 days) in four different countries (China, Italy, Iran, and Lebanon) taken approximately in the same duration, between January and March 2020. Path analysis was implemented on the data to detect the significant factors that affect the daily COVID-19 infections. (3) Results: The path coefficients show that quarantine commitment (β = −0.823) and full lockdown measures (β = −0.775) have the largest direct effect on COVID-19 daily infections. The results also show that more experience (β = −0.35), density in society (β = −0.288), medical resources (β = 0.136), and economic resources (β = 0.142) have indirect effects on daily COVID-19 infections. (4) Conclusions: The COVID-19 daily infections directly decrease with complete lockdown measures, quarantine commitment, wearing masks, and social distancing. COVID-19 daily cases are indirectly associated with population density, special events, previous experience, technology used, economic resources, and medical resources.