Examining the UK Covid-19 mortality paradox: Pandemic preparedness, healthcare expenditure, and the nursing workforce

Exploring US Nursing Leadership During the Initial COVID-19 Pandemic Response: A Qualitative Descriptive Study to Guide Leadership Development for Future Emergent Situations

OBJECTIVE

This study aimed to describe the experiences of nurse leaders during the 1st wave of the COVID-19 pandemic to enhance understanding in preparation for future disasters.

BACKGROUND

The COVID-19 pandemic has posed significant challenges to the healthcare system globally. Nurse leaders play an essential part and have a significant impact on the efficacy of disaster management in future emergent situations.

METHODS

The parent study conducted interviews with 100 nurses in the United States across specialty areas. This article presents a subgroup analysis of interview data from 13 self-identified nurse leaders. The research team used qualitative descriptive methodology and thematic analysis to identify patterns within the data.

RESULTS

Five themes were identified for effective nurse leadership during an emerging pandemic: 1) responsiveness; 2) anticipating needs; 3) care innovations; 4) collaboration; and 5) adaptability.

CONCLUSION

Supporting nurse leaders to exhibit effective leadership during periods of crisis is imperative to increase preparedness for future health events, protect population health, and create a pipeline of future nursing leadership. Involving nursing in developing and reforming policy is integral.

Upstream Policy Changes to Improve Population Health and Health Equity: A Priority Agenda

Policy Points Upstream factors-social structures/systems, cultural factors, and public policy-are primary forces that drive downstream patterns and inequities in health that are observed across race and locations. A public policy agenda that aims to address inequities related to the well-being of children, creation and perpetuation of residential segregation, and racial segregation can address upstream factors. Past successes and failures provide a blueprint for addressing upstream health issues and inhibit health equity.

Global Nurse Involvement in ethical decision-making during pandemics: a concept analysis

Background

During pandemics, there are considerable ethical dilemmas. It is imperative that nurses are involved in ethical decision-making bringing nursing theory, practice and perspectives to better advocate for patients. In order to prepare nurses to be partners in ethical dilemma decision-making during pandemics, it is vital to understand the extent that nurses are involved in such decision-making during the COVID-19 pandemic.

Aim

The purpose of this concept analysis is to identify nurse involvement in ethical decision-making during pandemics.

Method

Concept analysis methodology based on literature searches used bibliographic databases: PubMed - 20 papers; Google Scholar - 8120 papers; EMBASE - 25 papers; Science Direct - 246 papers and hand searches.

Results

Nurse involvement in ethical decision-making during pandemics focused on nurses' physical and emotional stress, communication challenges, saturation and collapse of limited resources and allocation of scarce resources. Additional dilemmas included, changing nature of nurses' relationships with patients and families, questionable ethical equipoise preforming COVID-19 research, triage patient decisions receiving scarce resources, partner participation during labour and delivery and end-of-life decisions.

Conclusion

In order to protect and sustain nurses' well-being and competency, nurses should establish a framework for nurses' involvement in ethical policy development in emergencies, pandemics, education and preparedness and decision-making to be able to deal with public health emergencies.

A large-scale machine learning study of sociodemographic factors contributing to COVID-19 severity

Understanding sociodemographic factors behind COVID-19 severity relates to significant methodological difficulties, such as differences in testing policies and epidemics phase, as well as a large number of predictors that can potentially contribute to severity. To account for these difficulties, we assemble 115 predictors for more than 3,000 US counties and employ a well-defined COVID-19 severity measure derived from epidemiological dynamics modeling. We then use a number of advanced feature selection techniques from machine learning to determine which of these predictors significantly impact the disease severity. We obtain a surprisingly simple result, where only two variables are clearly and robustly selected-population density and proportion of African Americans. Possible causes behind this result are discussed. We argue that the approach may be useful whenever significant determinants of disease progression over diverse geographic regions should be selected from a large number of potentially important factors.

Understanding risk factors of a new variant outburst through global analysis of Omicron transmissibility

The emergence of a new virus variant is generally recognized by its usually sudden and rapid spread (outburst) in a certain world region. Due to the near-exponential rate of initial expansion, the new strain may not be detected at its true geographical origin but in the area with the most favorable conditions leading to the fastest exponential growth. Therefore, it is crucial to understand better the factors that promote such outbursts, which we address in the example of analyzing global Omicron transmissibility during its global emergence/outburst in November 2021-February 2022. As predictors, we assemble a number of potentially relevant factors: vaccinations (both full and boosters), different measures of population mobility (provided by Google), estimated stringency of measures, the prevalence of chronic diseases, population age, the timing of the outburst, and several other socio-demographic variables. As a proxy for natural immunity (prevalence of prior infections in population), we use cumulative numbers of COVID-19 deaths. As a response variable (transmissibility measure), we use the estimated effective reproduction number (R_e) averaged in the vicinity of the outburst maxima. To select significant predictors of R_e, we use machine learning regressions that employ feature selection, including methods based on ensembles of decision trees (Random Forest and Gradient Boosting). We identify the young population, earlier infection onset, higher mobility, low natural immunity, and low booster prevalence as likely direct risk factors. Interestingly, we find that all these risk factors were significantly higher for Africa, though curiously somewhat lower in Southern African countries (where the outburst emerged) compared to other African countries. Therefore, while the risk factors related to the virus transmissibility clearly promote the outburst of a new virus variant, specific regions/countries where the outburst actually happens may be related to less evident factors, possibly random in nature.

Analyzing the GHSI puzzle of whether highly developed countries fared worse in COVID-19

Global Health Security Index (GHSI) categories are formulated to assess the capacity of world countries to deal with infectious disease risks. Thus, higher values of these indices were expected to translate to lower COVID-19 severity. However, it turned out to be the opposite, surprisingly suggesting that higher estimated country preparedness to epidemics may lead to higher disease mortality. To address this puzzle, we: (i) use a model-derived measure of COVID-19 severity; (ii) employ a range of statistical learning approaches, including non-parametric machine learning methods; (iii) consider the overall excess mortality, in addition to official COVID-19 fatality counts. Our results suggest that the puzzle is, to a large extent, an artifact of oversimplified data analysis and a consequence of misclassified COVID-19 deaths, combined with the higher median age of the population and earlier epidemics onset in countries with high GHSI scores.

Global mapping of epidemic risk assessment toolkits: A scoping review for COVID-19 and future epidemics preparedness implications

Preparedness and responses to infectious disease epidemics and pandemics require the understanding of communities’ and multisectoral systems’ characteristics with regards to diseases transmission and population’s vulnerabilities. This study aimed to summarize measurement profiles of existing risk assessment toolkits to inform COVID-19 control at global and national levels. An online search in different databases and online sources was performed to identify all epidemic risk and vulnerability assessment instruments. Medline/PubMed, Web of Science databases, and websites of public health organizations were used for the searching process. Of 14 toolkits, levels of setting were mostly at the global or nation level. Components such as Governance and Legislation, Financing, Health Service Provision, and Human Resources are key domains in almost all toolkits. Some important issues for disease detection and surveillance, such as laboratory or capacity of the community for disease control, were not adequately addressed in several toolkits. Limited studies were found that validated the toolkits. Only five toolkits were used in COVID-19 studies. This study provides a summary of risk assessment toolkits to inform epidemic responses. We call for global and national efforts in developing more contextualized and responsive epidemic risk assessment scales incorporating specific-disease and -country factors to inform operational decisions making and strengthen countries’ capacities in epidemic responses.

Preparedness of countries to face COVID-19 pandemic crisis: Strategic positioning and factors supporting effective strategies of prevention of pandemic threats

The Coronavirus Disease 2019 (COVID-19) continues to generate a constant pandemic threat with new mutations of the viral agent (SARS-CoV-2) that create socioeconomic issues. One of the fundamental problems is the evaluation of the preparedness of countries to cope with COVID-19 pandemic crisis to detect and support factors associated with the reduction of mortality and the growth of vaccinations in society. The study here confronts this problem by developing two basic indexes, which measure the performance of countries to face pandemic threats. In particular, the Index r (as resilience) detects the countries having the best performance in the reduction of the negative impact of mortality related to COVID-19 pandemic and the Index p (as preparedness and prevention) assesses best-performer countries to support COVID-19 vaccinations in order to constrain future pandemic threats and support the recovery of socioeconomic systems. Index of resilience is a composite measure based on three indicators associated with COVID-19, given by average mortality, hospital occupancy and Intensive Care Units occupancy per 100 000 people, producing an overall score; Index of preparedness/prevention is a composite measure of two indicators related to COVID-19 vaccinations (i.e., doses of vaccines administered and total vaccinates per 100 000 people), producing also an overall score of performance. The application of these indexes on a case study of European countries, having a homogenous socioeconomic area, shows the strategic positioning of countries to cope with a major pandemic threat. Findings reveal that all countries have some weaknesses and no country has a high preparedness to cope with a major epidemic or pandemic. Moreover, results suggest that best-performer countries to cope with COVID-19 pandemic crisis have a smaller size of population and/or better public governance, associated with high expenditures in health system. These indexes can help policymakers for designing effective strategies to improve preparedness and prevention of countries to face future pandemic threats.

High health expenditures and low exposure of population to air pollution as critical factors that can reduce fatality rate in COVID-19 pandemic crisis: a global analysis

One of the problems hardly clarified in Coronavirus Disease 2019 (COVID-19) pandemic crisis is to identify factors associated with a lower mortality of COVID-19 between countries to design strategies to cope with future pandemics in society. The study here confronts this problem by developing a global analysis based on more than 160 countries. This paper proposes that Gross Domestic Product (GDP) per capita, healthcare spending and air pollution of nations are critical factors associated with fatality rate of COVID-19. The statistical evidence seems in general to support that countries with a low average COVID-19 fatality rate have high expenditures in health sector >7.5% of GDP, high health expenditures per capita >$2,300 and a lower exposure of population to days exceeding safe levels of particulate matter (PM2.5). Another relevant finding here is that these countries have lower case fatality rates (CFRs) of COVID-19, regardless a higher percentage of population aged more than 65 years. Overall, then, this study finds that an effective and proactive strategy to reduce the negative impact of future pandemics, driven by novel viral agents, has to be based on a planning of enhancement of healthcare sector and of environmental sustainability that can reduce fatality rate of infectious diseases in society.

Are we ready to deal with a global COVID-19 pandemic? Rethinking countries' capacity based on the Global Health Security Index

BACKGROUND

The Global Health Security (GHS) Index has been developed to measure a country's capacity to cope with a public health emergency; however, evidence for whether it corresponds to the response to a global pandemic is lacking. This study performed a multidimensional association analysis to explore the correlation between the GHS Index and COVID-19-associated morbidity, mortality, and disease increase rate (DIR) in 178 countries (regions).

METHODS

The GHS Index and COVID-19 pandemic data - including total cases per million (TCPM), total deaths per million (TDPM), and daily growth rate - were extracted from online databases. The Spearman correlation coefficient was applied to describe the strength of the association between the GHS Index, sociological characteristics, and the epidemic situation of COVID-19. DIRs were compared, and the impact of the GHS Index on the DIR by the time of "lockdown" was visualized.

RESULTS

The overall GHS Index was positively correlated with TCPM and TDPM, with coefficients of 0.34 and 0.41, respectively. Countries categorized into different GHS Indextiers had different DIRs before implementing lockdown measures. However, no significant difference was observed between countries in the middle and upper tiers after implementing lockdown measures. The correlation between GHS Index and DIR was positive five days before lockdown measures were taken, but it became negative 13 days later.

CONCLUSIONS

The GHS Index has limited value in assessing a country's capacity to respond to a global pandemic. Nevertheless, it has potential value in determining the country's ability to cope with a local epidemic situation.