Democracy and case fatality rate of COVID-19 at early stage of pandemic: a multicountry study

Molecular dynamic simulation reveals spider antimicrobial peptide Latarcin-1 and human eosinophil cationic protein as peptide inhibitors of SARS-CoV-2 variants

COVID-19 has rapidly proliferated around 180 countries, and new cases are reported frequently. No peptide medication has been developed that can reliably block SARS-CoV-2 infection. The investigation focuses on the crucial host receptors angiotensin-converting enzyme 2 (ACE2) , which can bind receptor-binding domain (RBD) on the SARS-CoV-2 spike protein (S). To investigate the inhibitory effects of human Eosinophil Cationic Protein (hECP) and Latarcin-1 (L1)on SARS-CoV-2 infection, we have selected them as research subjects. Further, we ran extensive molecular dynamics simulations to bring the docked peptide-ACE2 complex into its equilibrium state. The outcomes were then evaluated with g_MMPBSA and interaction analysis. We have also considered the Delta and Omicron variants to examine these peptides' inhibitory effects. The experimental findings revealed an enhanced capability of L1 and hECP as SARS-CoV-2 inhibitors, occupying hot spots and numerous key residues in ACE2. These include ASP30, ASP38, GLU35 and GLU75, which significantly inhibit the binding of RBD and ACE2 and are effective against two common variants in a similar manner. In addition, this study can serve as a springboard for future research on SARS-CoV-2 inhibitors.Communicated by Ramaswamy H. Sarma.

The determinants of COVID-19 case reporting across Africa

Background

According to study on the under-estimation of COVID-19 cases in African countries, the average daily case reporting rate was only 5.37% in the initial phase of the outbreak when there was little or no control measures. In this work, we aimed to identify the determinants of the case reporting and classify the African countries using the case reporting rates and the significant determinants.

Methods

We used the COVID-19 daily case reporting rate estimated in the previous paper for 54 African countries as the response variable and 34 variables from demographics, socioeconomic, religion, education, and public health categories as the predictors. We adopted a generalized additive model with cubic spline for continuous predictors and linear relationship for categorical predictors to identify the significant covariates. In addition, we performed Hierarchical Clustering on Principal Components (HCPC) analysis on the reporting rates and significant continuous covariates of all countries.

Results

21 covariates were identified as significantly associated with COVID-19 case detection: total population, urban population, median age, life expectancy, GDP, democracy index, corruption, voice accountability, social media, internet filtering, air transport, human development index, literacy, Islam population, number of physicians, number of nurses, global health security, malaria incidence, diabetes incidence, lower respiratory and cardiovascular diseases prevalence. HCPC resulted in three major clusters for the 54 African countries: northern, southern and central essentially, with the northern having the best early case detection, followed by the southern and the central.

Conclusion

Overall, northern and southern Africa had better early COVID-19 case identification compared to the central. There are a number of demographics, socioeconomic, public health factors that exhibited significant association with the early case detection.

Democratic quality and excess mortality during the COVID-19 pandemic

The aim of this study is to analyse the relationship between democratic quality and excess mortality produced in the year 2020 before COVID-19 vaccinations were generalised. Using cross-sectional data from 80 countries on five continents, multiple linear regression models between excess mortality, the general democracy index and its disaggregation into five categories: electoral process and pluralism, government functioning, political participation, political culture and civil liberties were estimated. The analysis also considered, public health spending per capita, overweight inhabitants, the average temperature of the country, population over 65 years of age, The KOF Globalisation Index, and the Gross National Income per capita as control variables. It was possible to establish a strong inverse association between excess mortality per million inhabitants and the general democracy index and four of its five categories. There was a particularly strong relationship between excess mortality and the political culture dimension (-326.50, p < 0.001). The results suggest that the higher the democratic quality of the political institutions of a State and particularly of their political culture the more improved the response and management of the pandemic was in preventing deaths and protecting their citizens more effectively. Conversely, countries with lower democracy index values have higher excess mortality. Quality democratic political institutions provide more effective public health policies in the face of the COVID-19 pandemic.

COVID-19 and democracy: a scoping review

BACKGROUND

The resilience of democracy is tested under exogenous shocks such as crises. The COVID-19 pandemic has recently tested the resilience of democratic institutions and practices around the world.

AIM

The purpose of this article is to scope the early research literature that discusses democracy and the COVID-19 pandemic. We review scientific journal articles published during the first two years of the pandemic. We ask three research questions in scoping this body of literature: (1) what are the key topic areas of all published research that associates itself with both democracy and COVID-19, (2) what kinds of conceptual and theoretical contributions has research literature that more specifically discusses democracy under the pandemic produced, and (3) what are the impacts of democracy to the pandemic and vice versa according to empirical research?

METHODS

The scoping review methodology draws on systematic literature search strategies, computational methods, and manual coding. The systematic Web of Science search produced 586 articles for which we conducted a Correlated Topic Model. After technical and manual screening, we identified 94 journal articles that were manually coded.

RESULTS

The early research on democracy and the COVID-19 pandemic offers a versatile body of scholarship. The topic modeling shows that the scholarship discusses issues of crises, governance, rights, society, epidemiology, politics, electorate, technology, and media. The body of papers with conceptual and theoretical contributions has offered new insights on the difficulties, possibilities, and means to maintain democracy under a pandemic. Empirical research on democracy's impact on the COVID-19 pandemic and vice versa varies in terms of methodology, geographical scope, and scientific contributions according to the direction of influence studied. Democracy appears to have a significant impact on some aspects of policy responses and epidemiological characteristics of the pandemic. In most parts of the world, the scope, franchise, and authenticity of democracy narrowed down due to the pandemic, albeit in most cases only temporarily.

CONCLUSIONS

A significant number of papers show that the pandemic has accentuated democratic backsliding but is unlikely to have undermined established democracies that have proved resilient in face of the pandemic. But empirical research has also made visible some weak signals of antidemocratic tendencies that may become more accentuated in the longer run.

Individualism, economic development, and democracy as determinants of COVID-19 risk information on 132 government websites

Little is known about how governments transparently communicate about COVID-19. This study conducted a content analysis of 132 government COVID-19 websites to identify the salience of health messages (i.e., perceived threat, perceived efficacy, and perceived resilience) and cross-national determinants of information provision. Multinomial logistic regression was used to estimate the relationship between country-level predictors (i.e., economic development, democracy scores, and individualism index) and information salience. The numbers of deaths, discharged patients, and daily new cases were prevalent on the main webpages. Subpages provided information about vulnerability statistics, government responses, and vaccination rates. Less than 10% of governments included messages that may instill self-efficacy. Democratic countries had higher chances of providing threat statistics on subpages, including daily new cases (Relative Risk Ratio, RRR = 1.66, 95% CI: 1.16-2.37), mortalities (RRR = 1.69, 95% CI: 1.23-2.33), hospitalizations (RRR = 1.63, 95% CI: 1.12-2.37), and positivity rates (RRR = 1.55, 95% CI: 1.07-2.23). On subpages, democratic governments emphasized information about perceived vulnerability (RRR = 2.36, 95% CI: 1.50-3.73), perceived response efficacy (RRR = 1.48, 95% CI: 1.06-2.06), recovery numbers (RRR = 1.84, 95% CI: 1.31-2.60), and vaccinations (RRR = 2.14, 95% CI: 1.39-3.30). Developed countries reported the number of daily new cases, perceived response efficacy, and vaccination rates on their COVID-19 main pages. Individualism scores predicted the salience of vaccination rates on main pages and the omission of information related to perceived severity and perceived vulnerability. Democracy levels were more predictive of reporting information about perceived severity, perceived response efficacy, and perceived resilience on subpages of dedicated websites. Improving public health agencies' communication about COVID-19 is warranted.

Associations between institutional-social-ecological factors and COVID -19 case-fatality: Evidence from 134 countries using multiscale geographically weighted regression (MGWR)

During the period in which the Omicron coronavirus variant was rapidly spreading, the impact of the institutional-social-ecological dimensions on the case-fatality rate was rarely afforded attention. By adopting the diagnostic social-ecological system (SES) framework, the present paper aims to identify the impact of institutional-social-ecological factors on the case-fatality rate of COVID-19 in 134 countries and regions and test their spatial heterogeneity. Using statistical data from the Our World In Data website, the present study collected the cumulative case-fatality rate from 9 November 2021 to 23 June 2022, along with 11 country-level institutional-social-ecological factors. By comparing the goodness of fit of the multiple linear regression model and the multiscale geographically weighted regression (MGWR) model, the study demonstrated that the effects of SES factors exhibit significant spatial heterogeneity in relation to the case-fatality rate of COVID-19. After substituting the data into the MGWR model, six SES factors were identified with an R square of 0.470 based on the ascending effect size: COVID-19 vaccination policy, age dependency ratio, press freedom, gross domestic product (GDP), COVID-19 testing policy, and population density. The GWR model was used to test and confirm the robustness of the research results. Based on the analysis results, it is suggested that the world needs to meet four conditions to restore normal economic activity in the wake of the COVID-19 pandemic: (i) Countries should increase their COVID-19 vaccination coverage and maximize COVID-19 testing expansion. (ii) Countries should increase public health facilities available to provide COVID-19 treatment and subsidize the medical costs of COVID-19 patients. (iii) Countries should strictly review COVID-19 news reports and actively publicize COVID-19 pandemic prevention knowledge to the public through a range of media. (iv) Countries should adopt an internationalist spirit of cooperation and help each other to navigate the COVID-19 pandemic. The study further tests the applicability of the SES framework to the field of COVID-19 prevention and control based on the existing research, offering novel policy insights to cope with the COVID-19 pandemic that coexists with long-term human production and life for a long time.

Effects of strict containment policies on COVID-19 pandemic crisis: lessons to cope with next pandemic impacts

The goal of the study here is to analyze and assess whether strict containment policies to cope with Coronavirus Disease 2019 (COVID-19) pandemic crisis are effective interventions to reduce high numbers of infections and deaths. A homogenous sample of 31 countries is categorized in two sets: countries with high or low strictness of public policy to cope with COVID-19 pandemic crisis. The findings here suggest that countries with a low intensity of strictness have average confirmed cases and fatality rates related to COVID-19 lower than countries with high strictness in containment policies (confirmed cases are 24.69% vs. 26.06% and fatality rates are 74.33% vs. 76.38%, respectively, in countries with low and high strictness of COVID-19 public policies of containment). What this study adds is that high levels of strict restriction policies may not be useful measures of control in containing the spread and negative impact of pandemics similar to COVID-19 and additionally a high strictness in containment policies generates substantial social and economic costs. These findings can be explained with manifold socioeconomic and environmental factors that support transmission dynamics and circulation of COVID-19 pandemic. Hence, high levels of strictness in public policy (and also a high share of administering new vaccines) seem to have low effectiveness to stop pandemics similar to COVID-19 driven by mutant viral agents. These results here suggest that the design of effective health policies for prevention and preparedness of future pandemics should be underpinned in a good governance of countries and adoption of new technology, rather than strict and generalized health polices having ambiguous effects of containment in society.

A Comparative Analysis on the Social Determinants of COVID-19 Vaccination Coverage in Fragile and Conflict Affected Settings and Non-fragile and Conflict Affected Settings

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has coerced various resources of all the countries. While the high-income nations redirected financial and human resources to understand specific determinants of vaccination coverage, fragile and conflict-affected setting (FCS) nations were waiting for global bodies to cater to their ever-growing need for vaccines and other lifesaving drugs. This study aimed to determine various factors influencing vaccine coverage in the FCS context.

METHODS

World Bank's classification of FCS states was the primary source for country classification. The study utilized data from various other open sources. The study models cross-country inequities in COVID-19 vaccine coverage and we have employed multi-variate log-linear regressions to understand the relationship between COVID-19 vaccine coverage and cross-country macro-level determinants. The analysis was conducted on two samples, non-FCS Countries and the FCS countries.

RESULTS

Socio-economic determinants such as gross domestic product (GDP) per capita, socioeconomic resilience; health system determinants such as density of human resources, government spending on health expenditure; and political determinants such as effective government, more power to regional governments, political stability and absence of violence play a pivotal role in vaccine coverage. We also found that FCS countries with a higher share of people strongly believing in the vaccine effectiveness have a positive association with COVID-19 vaccine coverage.

CONCLUSION

The study confirmed that political factors, government effectiveness and political stability are also important determinants of vaccine coverage. The result further draws attention to few policy implications such as promoting future research to explore the linkages between the perceived equality before the law and individual liberty and its effect on vaccination coverage in the FCS.

Mortality in Four Waves of COVID-19 Is Differently Associated with Healthcare Capacities Affected by Economic Disparities

Background: The greatest challenges are imposed on the overall capacity of disease management when the cases reach the maximum in each wave of the pandemic. Methods: The cases and deaths for the four waves of COVID-19 in 119 countries and regions (CRs) were collected. We compared the mortality across CRs where populations experience different economic and healthcare disparities. Findings: Among 119 CRs, 117, 112, 111, and 55 have experienced 1, 2, 3, and 4 waves of COVID-19 disease, respectively. The average mortality rates at the disease turning point were 0.036, 0.019. 0.017, and 0.015 for the waves 1, 2, 3, and 4, respectively. Among 49 potential factors, income level, gross national income (GNI) per capita, and school enrollment are positively correlated with the mortality rates in the first wave, but negatively correlated with the rates of the rest of the waves. Their values for the first wave are 0.253, 0.346 and 0.385, respectively. The r value for waves 2, 3, and 4 are −0.310, −0.293, −0.234; −0.263, −0.284, −0.282; and −0.330, −0.394, −0.048, respectively. In high-income CRs, the mortality rates in waves 2 and 3 were 29% and 28% of that in wave 1; while in upper-middle-income CRs, the rates for waves 2 and 3 were 76% and 79% of that in wave 1. The rates in waves 2 and 3 for lower-middle-income countries were 88% and 89% of that in wave 1, and for low-income countries were 135% and 135%. Furthermore, comparison among the largest case numbers through all waves indicated that the mortalities in upper- and lower-middle-income countries is 65% more than that of the high-income countries. Interpretation: Conclusions from the first wave of the COVID-19 pandemic do not apply to the following waves. The clinical outcomes in developing countries become worse along with the expansion of the pandemic.

Variations of COVID-19 mortality are affected by economic disparities across countries

BACKGROUND

When the COVID-19 case number reaches a maximum in a country, its capacity and management of health system face greatest challenge.

METHODS

We performed a cross-sectional study on data of turning points for cases and deaths for the first three waves of COVID-19 in countries with more than 5000 cumulative cases, as reported by Worldometers and WHO Coronavirus (COVID-19) Dashboard. We compared the case fatality rates (CFRs) and time lags (in unit of day) between the turning points of cases and deaths among countries in different development stages and potential influence factors. As of May 10, 2021, 106 out of 222 countries or regions (56%) reported more than 5000 cases. Approximately half of them have experienced all the three waves of COVID-19 disease. The average mortality rate at the disease turning point was 0.038 for the first wave, 0.020 for the second wave, and 0.023 for wave 3. In high-income countries, the mortality rates during the first wave are higher than that of the other income levels. However, the mortality rates during the second and third waves of COVID-19 were much lower than those of the first wave, with a significant reduction from 5.7% to 1.7% approximately 70%. At the same time, high-income countries exhibited a 2-fold increase in time lags during the second and the third waves compared to the first wave, suggesting that the periods between the cases and deaths turning point extended. High rates in the first wave in developed countries are associated to multiple factors including transportation, population density, and aging populations. In upper middle- and lower middle-income countries, the decreasing of mortality rates in the second and third waves were subtle or even reversed, with increased mortality during the following waves. In the upper and lower middle-income countries, the time lags were about 50% of the durations observed from high-income countries.

INTERPRETATION

Economy and medical resources affect the efficiency of COVID-19 mitigation and the clinical outcomes of the patients. The situation is likely to become even worse in the light of these countries' limited ability to combat COVID-19 and prevent severe outcomes or deaths as the new variant transmission becomes dominant.

Government Reactions, Citizens' Responses, and COVID-19 around the World

We analyze the relationship between different dimensions of the quality of the political system and the outcome of the COVID-19 pandemic. Data are retrieved from open-access databases for 98 countries. We apply a multivariable regression model to identify the relationship between various factors likely to affect the number of COVID-19 deaths, in addition to different dimensions of the quality of the political system. We find that the high quality of the electoral process in a country is associated with more COVID-19 deaths, while good political culture is associated with fewer deaths. As expected, we also find that trust in government and experiences with pandemics in the past is negatively related to COVID-19 deaths. Finally, a high GDP per capita is significantly associated with more COVID-19 deaths. Our findings illustrate that rapid, effective, and comprehensive government measures can protect society from the spread of a virus, but citizen compliance is also essential to policy success.