The interaction of disease transmission, mortality, and economic output over the first 2 years of the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic has caused over 7.02 million deaths as of January 2024 and profoundly affected most countries' Gross Domestic Product (GDP). Here, we study the interaction of SARS-CoV-2 transmission, mortality, and economic output between January 2020 and December 2022 across 25 European countries. METHODS: We use a Bayesian mixed effects model with auto-regressive terms to estimate the temporal relationships between disease transmission, excess deaths, changes in economic output, transit mobility and non-pharmaceutical interventions (NPIs) across countries. RESULTS: Disease transmission intensity (logRt) decreases GDP and increases excess deaths, where the latter association is longer-lasting. Changes in GDP as well as prior week transmission intensity are both negatively associated with each other (-0.241, 95% CrI: -0.295 - -0.189). We find evidence of risk-averse behaviour, as changes in transit and prior week transmission intensity are negatively associated (-0.055, 95% CrI: -0.074 to -0.036). Our results highlight a complex cost-benefit trade-off from individual NPIs. For example, banning international travel is associated with both increases in GDP (0.014, 0.002-0.025) and decreases in excess deaths (-0.014, 95% CrI: -0.028 - -0.001). Country-specific random effects, such as the poverty rate, are positively associated with excess deaths while the UN government effectiveness index is negatively associated with excess deaths. INTERPRETATION: The interplay between transmission intensity, excess deaths, population mobility and economic output is highly complex, and none of these factors can be considered in isolation. Our results reinforce the intuitive idea that significant economic activity arises from diverse person-to-person interactions. Our analysis quantifies and highlights that the impact of disease on a given country is complex and multifaceted. Long-term economic impairments are not fully captured by our model, as well as long-term disease effects (Long COVID).

A precise performance-based reimbursement model for the multi-centre NAPKON cohorts - development and evaluation.

Fair allocation of funding in multi-centre clinical studies is challenging. Models commonly used in Germany - the case fees ("fixed-rate model", FRM) and up-front staffing and consumables ("up-front allocation model", UFAM) lack transparency and fail to suitably accommodate variations in centre performance. We developed a performance-based reimbursement model (PBRM) with automated calculation of conducted activities and applied it to the cohorts of the National Pandemic Cohort Network (NAPKON) within the Network of University Medicine (NUM). The study protocol activities, which were derived from data management systems, underwent validation through standardized quality checks by multiple stakeholders. The PBRM output (first funding period) was compared among centres and cohorts, and the cost-efficiency of the models was evaluated. Cases per centre varied from one to 164. The mean case reimbursement differed among the cohorts (1173.21€ [95% CI 645.68-1700.73] to 3863.43€ [95% CI 1468.89-6257.96]) and centres and mostly fell short of the expected amount. Model comparisons revealed higher cost-efficiency of the PBRM compared to FRM and UFAM, especially for low recruitment outliers. In conclusion, we have developed a reimbursement model that is transparent, accurate, and flexible. In multi-centre collaborations where heterogeneity between centres is expected, a PBRM could be used as a model to address performance discrepancies.Trial registration: https://clinicaltrials.gov/ct2/show/NCT04768998 ; https://clinicaltrials.gov/ct2/show/NCT04747366 ; https://clinicaltrials.gov/ct2/show/NCT04679584 .

Depression and assets during the COVID-19 pandemic: A longitudinal study of mental health across income and savings groups.

The prevalence of depression in U.S. adults during the COVID-19 pandemic has been high overall and particularly high among persons with fewer assets. Building on previous work on assets and mental health, we document the burden of depression in groups based on income and savings during the first two years of the COVID-19 pandemic. Using a nationally representative, longitudinal panel study of U.S. adults (N = 1,271) collected in April-May 2020 (T1), April-May 2021 (T2), and April-May 2022 (T3), we estimated the adjusted odds of reporting probable depression at any time during the COVID-19 pandemic with generalized estimating equations (GEE). We explored probable depression-defined as a score of ≥10 on the Patient Health Questionnaire-9 (PHQ-9)-by four asset groups, defined by median income (≥$65,000) and savings (≥$20,000) categories. The prevalence of probable depression was consistently high in Spring 2020, Spring 2021, and Spring 2022 with 27.9% of U.S. adults reporting probable depression in Spring 2022. We found that there were four distinct asset groups that experienced different depression trajectories over the COVID-19 pandemic. Low income-low savings asset groups had the highest level of probable depression across time, reporting 3.7 times the odds (95% CI: 2.6, 5.3) of probable depression at any time relative to high income-high savings asset groups. While probable depression stayed relatively stable across time for most groups, the low income-low savings group reported significantly higher levels of probable depression at T2, compared to T1, and the high income-low savings group reported significantly higher levels of probable depression at T3 than T1. The weighted average of probable depression across time was 42.9% for low income-low savings groups, 24.3% for high income-low savings groups, 19.4% for low income-high savings groups, and 14.0% for high income-high savings groups. Efforts to ameliorate both savings and income may be necessary to mitigate the mental health consequences of pandemics.

Capital structure and financial performance of China's energy industry: What can we infer from COVID-19?

The study aims to uncover the impact of COVID-19 and capital structure on the financial performance of 1787 renewable and nonrenewable energy firms in China from 2010 to 2022. Using the fixed effect approach, our study found that financial leverage negatively affected the return on assets and equity ratios for both renewable and nonrenewable energy. On the other hand, the study shows that COVID-19 adversely affected the financial performances of non-renewable energy firms. Conversely, COVID-19 positively affected the financial performances of renewable energy firms. The conclusions drawn by the present study are helpful for the policymakers in making corresponding financial decisions. The study suggests that policymakers must adopt profitable capital structure strategies for firms and shareholders in this context. Finally, policymakers must design more policies to overcome the adverse influence of the COVID-19 pandemic crisis and avoid any future unforeseeable pandemics.

Can major public health emergencies increase the participation of commercial insurance? Evidence from China.

Background: Public health emergencies have a lasting impact on a country's economic and social development. However, commercial insurance can disperse these negative consequences and reduce risk losses. Method: Based on the Chinese Household Tracking Survey and Peking University Digital Inclusive Finance Index, this study employed a difference-in-differences model to test the impact of the COVID-19 outbreak on commercial insurance participation and the impact mechanism. Results: The analysis showed that the outbreak of COVID-19 improved residents' risk perception, risk preference and digital finance and promoted their participation in commercial insurance, commercial endowment insurance, and commercial medical insurance. Conclusion: Major public health emergencies can increase commercial insurance participation, but the promotional effect of commercial insurance on rural and low-income individuals is relatively limited. To tap into potential customers, financial institutions should focus on vulnerable societal groups. This study supplements the relevant literature on the impact of major public health emergencies on commercial insurance participation.

The economic case for scaling up health research and development: Lessons from the COVID-19 pandemic.

In response to the COVID-19 pandemic, governments directly funded vaccine research and development (R&D), quickly leading to multiple effective vaccines and resulting in enormous health and economic benefits to society. We develop a simple economic model showing this feat could potentially be repeated for other health challenges. Based on inputs from the economic and medical literatures, the model yields estimates of optimal R&D spending on treatments and vaccines for known diseases. Taking a global and societal perspective, we estimate the social benefits of such spending and a corresponding rate of return. Applications to Streptococcus A vaccines and Alzheimer's disease treatments demonstrate the potential of enhanced research and development funding to unlock massive global health and health-related benefits. We estimate that these benefits range from 2 to 60 trillion (2020 US$) and that the corresponding rates of return on R&D spending range from 12% to 23% per year for 30 y. We discuss the current shortfall in R&D spending and public policies that can move current funding closer to the optimal level.

Associations between BMI and hospital resource use in patients hospitalised for COVID-19 in England: a community-based cohort study.

BACKGROUND: Excess weight is a major risk factor for severe disease after infection with SARS-CoV-2. However, the effect of BMI on COVID-19 hospital resource use has not been fully quantified. This study aimed to identify the association between BMI and hospital resource use for COVID-19 admissions with the intention of informing future national hospital resource allocation. METHODS: In this community-based cohort study, we analysed patient-level data from 57 415 patients admitted to hospital in England with COVID-19 between April 1, 2020, and Dec 31, 2021. Patients who were aged 20-99 years, had been registered with a general practitioner (GP) surgery that contributed to the QResearch database for the whole preceding year (2019) with at least one BMI value measured before April 1, 2020, available in their GP record, and were admitted to hospital for COVID-19 were included. Outcomes of interest were duration of hospital stay, transfer to an intensive care unit (ICU), and duration of ICU stay. Costs of hospitalisation were estimated from these outcomes. Generalised linear and logit models were used to estimate associations between BMI and hospital resource use outcomes. FINDINGS: Patients living with obesity (BMI >30·0 kg/m2) had longer hospital stays relative to patients in the reference BMI group (18·5-25·0 kg/m2; IRR 1·07, 95% CI 1·03-1·10); the reference group had a mean length of stay of 8·82 days (95% CI 8·62-9·01). Patients living with obesity were more likely to be admitted to ICU than the reference group (OR 2·02, 95% CI 1·86-2·19); the reference group had a mean probability of ICU admission of 5·9% (95% CI 5·5-6·3). No association was found between BMI and duration of ICU stay. The mean cost of COVID-19 hospitalisation was £19 877 (SD 17 918) in the reference BMI group. Hospital costs were estimated to be £2736 (95% CI 2224-3248) higher for patients living with obesity. INTERPRETATION: Patients admitted to hospital with COVID-19 with a BMI above the healthy range had longer stays, were more likely to be admitted to ICU, and had higher health-care costs associated with hospital treatment of COVID-19 infection as a result. This information can inform national resource allocation to match hospital capacity to areas where BMI profiles indicate higher demand. FUNDING: National Institute for Health Research.

Use of Early Ketamine Sedation and Association With Clinical and Cost Outcomes Among Mechanically Ventilated Patients With COVID-19: A Retrospective Cohort Study.

OBJECTIVES: To describe the utilization of early ketamine use among patients mechanically ventilated for COVID-19, and examine associations with in-hospital mortality and other clinical outcomes. DESIGN: Retrospective cohort study. SETTING: Six hundred ten hospitals contributing data to the Premier Healthcare Database between April 2020 and June 2021. PATIENTS: Adults with COVID-19 and greater than or equal to 2 consecutive days of mechanical ventilation within 5 days of hospitalization. INTERVENTION: The exposures were early ketamine use initiated within 2 days of intubation and continued for greater than 1 day. MEASUREMENTS: Primary was hospital mortality. Secondary outcomes included length of stay (LOS) in the hospital and ICUs, ventilator days, vasopressor days, renal replacement therapy (RRT), and total hospital cost. The propensity score matching analysis was used to adjust for confounders. MAIN RESULTS: Among 42,954 patients, 1,423 (3.3%) were exposed to early ketamine use. After propensity score matching including 1,390 patients in each group, recipients of ketamine infusions were associated with higher hospital mortality (52.5% vs. 45.9%, risk ratio: 1.14, [1.06-1.23]), longer median ICU stay (13 vs. 12 d, mean ratio [MR]: 1.15 [1.08-1.23]), and longer ventilator days (12 vs. 11 d, MR: 1.19 [1.12-1.27]). There were no associations for hospital LOS (17 [10-27] vs. 17 [9-28], MR: 1.05 [0.99-1.12]), vasopressor days (4 vs. 4, MR: 1.04 [0.95-1.14]), and RRT (22.9% vs. 21.7%, RR: 1.05 [0.92-1.21]). Total hospital cost was higher (median $72,481 vs. $65,584, MR: 1.11 [1.05-1.19]). CONCLUSIONS: In a diverse sample of U.S. hospitals, about one in 30 patients mechanically ventilated with COVID-19 received ketamine infusions. Early ketamine may have an association with higher hospital mortality, increased total cost, ICU stay, and ventilator days, but no associations for hospital LOS, vasopressor days, and RRT. However, confounding by the severity of illness might occur due to higher extracorporeal membrane oxygenation and RRT use in the ketamine group. Further randomized trials are needed to better understand the role of ketamine infusions in the management of critically ill patients.

The intervention of local public authorities and the impact of the COVID-19 pandemic in Romania: a subnational analysis.

The COVID-19 pandemic had a strong territorial dimension, with a highly asymmetric impact among Romanian counties, depending on pre-existing vulnerabilities, regions' economic structure, exposure to global value chains, specialization, and overall ability to shift a large share of employees to remote working. The aim of this paper is to assess the role of Romanian local authorities during this unprecedented global medical emergency by capturing the changes of public spending at the local level between 2010 and 2021 and amid the COVID-19 pandemic, and to identify clusters of Romanian counties that shared similar characteristics in this period, using a panel data quantitative model and hierarchical cluster analysis. Our empirical analysis shows that between 2010-2021, the impact of social assistance expenditures was higher than public investment (capital spending and EU funds) on the GDP per capita at county level. Additionally, based on various macroeconomic and structural indicators (health, labour market performance, economic development, entrepreneurship, and both local public revenues and several types of expenditures), we determined seven clusters of counties. The research contributes to the discussion regarding the increase of economic resilience but also to the evidence-based public policies implementation at local level.

Not Only How Much But How: The Importance Of Diversifying Funding Streams In A Reimagined Public Health System.

Revenue diversification may be a synergistic strategy for transforming public health, yet few national or trend data are available. This study quantified and identified patterns in revenue diversification in public health before and during the COVID-19 pandemic. We used National Association of County and City Health Officials' National Profile of Local Health Departments study data for 2013, 2016, 2019, and 2022 to calculate a yearly diversification index for local health departments. Respondents' revenue portfolios changed fairly little between 2016 and 2022. Compared with less-diversified local health departments, well-diversified departments reported a balanced portfolio with local, state, federal, and clinical sources of revenue and higher per capita revenues. Less-diversified local health departments relied heavily on local sources and saw lower revenues. The COVID-19 period exacerbated these differences, with less-diversified departments seeing little revenue growth from 2019 to 2022. Revenue portfolios are an underexamined aspect of the public health system, and this study suggests that some organizations may be under financial strain by not having diverse revenue portfolios. Practitioners have ways of enhancing diversification, and policy attention is needed to incentivize and support revenue diversification to enhance the financial resilience and sustainability of local health departments.

Deciphering the link between healthcare expenditure, corruption, and COVID-19 mortality.

This paper analyzes the determinants of COVID-19 mortality across over 140 countries in 2020, with a focus on healthcare expenditure and corruption. It finds a positive association between COVID-19 deaths and aging populations, obesity rates, and healthcare expenditure while noting a negative association with rural residency and corruption perception. The study further reveals that mortality is positively associated with aging populations in high-income countries and positively associated with obesity in upper-middle to high-income countries. Mortality is positively associated with healthcare expenditure, which likely reflects a country's preparedness and ability to better track, document, and report COVID-19 deaths. On the other hand, mortality is negatively associated with corruption perception in upper-middle-income countries. Further analyses based on 2021 data reveal COVID-19 deaths are positively associated with the proportion of the population aged 65 and older in low to lower-middle-income countries, with obesity in high-income countries, and with tobacco use across most countries. Interestingly, there is no evidence linking COVID-19 deaths to healthcare expenditure and corruption perception, suggesting a post-2020 convergence in preparedness likely due to proactive pandemic responses, which might have also mitigated corruption's impact. Policy recommendations are proposed to aid the elderly, address obesity, and combat tobacco use.

Investing in health preparedness, response and resilience: a genomics costing tool focused on next generation sequencing.

The world has seen unprecedented gains in the global genomic surveillance capacities for pathogens with pandemic and epidemic potential within the last 4 years. To strengthen and sustain the gains made, WHO is working with countries and partners to implement the Global Genomic Surveillance Strategy for Pathogens with Pandemic and Epidemic Potential 2022-2032. A key technical product developed through these multi-agency collaborative efforts is a genomics costing tool (GCT), as sought by many countries. This tool was developed by five institutions - Association of Public Health Laboratories, FIND, The Global Fund to Fight AIDS, Tuberculosis and Malaria, UK Health Security Agency, and the World Health Organization. These institutions developed the GCT to support financial planning and budgeting for SARS-CoV-2 next-generation sequencing activities, including bioinformatic analysis. The tool costs infrastructure, consumables and reagents, human resources, facility and quality management. It is being used by countries to (1) obtain costs of routine sequencing and bioinformatics activities, (2) optimize available resources, and (3) build an investment case for the scale-up or establishment of sequencing and bioinformatics activities. The tool has been validated and is available in English and Russian at https://www.who.int/publications/i/item/9789240090866. This paper aims to highlight the rationale for developing the tool, describe the process of the collaborative effort in developing the tool, and describe the utility of the tool to countries.

Evaluating the influence of taxation and social security policies on psychological distress: A microsimulation study of the UK during the COVID-19 economic crisis.

Economic determinants are important for population health, but actionable evidence of how policies can utilise these pathways remains scarce. This study employs a microsimulation framework to evaluate the effects of taxation and social security policies on population mental health. The UK economic crisis caused by the COVID-19 pandemic provides an informative context involving an economic shock accompanied by one of the strongest discretionary fiscal responses amongst OECD countries. The analytical setup involves a dynamic, stochastic, discrete-time microsimulation model (SimPaths) projecting changes in psychological distress given predicted economic outcomes from a static tax-benefit microsimulation model (UKMOD) based on different policy scenarios. We contrast projections of psychological distress for the working-age population from 2017 to 2025 given the observed policy environment against a counterfactual scenario where pre-crisis policies remained in place. Levels of psychological distress and potential cases of common mental disorders (CMDs) were assessed with the 12-item General Health Questionnaire (GHQ-12). The UK policy response to the economic crisis is estimated to have prevented a substantial fall (over 12 percentage points, %pt) in the employment rate in 2020 and 2021. In 2020, projected psychological distress increased substantially (CMD prevalence increase >10%pt) under both the observed and the counterfactual policy scenarios. Through economic pathways, the policy response is estimated to have prevented a further 3.4%pt [95%UI 2.8%pt, 4.0%pt] increase in the prevalence of CMDs, approximately 1.2 million cases. Beyond 2021, as employment levels rapidly recovered, psychological distress returned to the pre-pandemic trend. Sustained preventative effects on poverty are estimated, with projected levels 2.1%pt [95%UI 1.8%pt, 2.5%pt] lower in 2025 than in the absence of the observed policy response. The study shows that policies protecting employment during an economic crisis are effective in preventing short-term mental health losses and have lasting effects on poverty levels. This preventative effect has substantial public health benefits.

A time-varying analysis between economic uncertainty and tourism development in Singapore.

Tourism development (TO) is seen as a viable solution to address economic policy uncertainty (EPU) risks. However, previous studies have largely ignored the relationship between short, medium, and long term by decomposing TO and EPU index at different time-frequency scales, especially in Singapore. In this study, the Wavelet tools analysis and a rolling window algorithm are employed to re-visit the causal relationship between EPU, industrial production index (IPI), government revenue (GR), and tourism development (TO) in Singapore from January 2003 to February 2022. The findings revealed the heterogeneous effects of EPU on TO at different time horizons in terms of importance and magnitude over time. A rise in EPU results in a decline in TO at the low frequencies, indicating that EPU has a detrimental effect on TO over the short term. Conversely, in the long term, an increase in TO results in a decrease in EPU. Furthermore, the outcome also indicated that there is a uni-directional causality running from TO to EPU, GR and IPI. Expressly, we confirm that the negative co-movement is more pronounced in the aftermath of the COVID-19 crisis, particularly for EPU, and GR at low-medium frequencies throughout the research period. The findings provide tourism policymakers with insight to develop strategic plans for tourism development that consider the effects of economic policy uncertainty. By understanding how uncertainty impacts tourism, governments can tailor development strategies to mitigate risks and capitalize on opportunities.

Evaluating private hospital performance before and during COVID-19 in China.

The coronavirus disease 2019 (COVID-19) pandemic had a tremendous impact on the global medical system. The development of private hospitals is an important measure to deepen the reform of China's medical and health system, and an important driving force to improve the effective supply of medical services. This study aims to compare the performance of China's private hospitals before and during COVID-19 and determine the factors that affect hospital profitability between the 2 periods. Data are collected from 10 private listed hospitals from 2017 to 2022, and ratio analysis is used to measure hospital performance in 5 aspects, namely profitability, liquidity, leverage, activity (efficiency), and cost coverage. Multiple regression analysis is used to determine the influencing factors of hospital profitability. The results show a negative impact of COVID-19 on private hospital performance. Specifically, regardless of region, hospital profitability, liquidity, and cost coverage were reduced due to COVID-19, while hospital leverage was increased. COVID-19 had also an impact on hospital efficiency. In addition, before COVID-19, current ratio and cost coverage ratio were the determinants of hospital profitability, while only cost coverage ratio affected hospital profitability during the COVID-19 outbreak. We provide evidence that COVID-19 had an impact on China private hospitals, and the findings will aid private hospitals in improving their performance in the post-COVID-19 era.

Lessons Learned from Model-based Economic Evaluations of COVID-19 Drug Treatments Under Pandemic Circumstances: Results from a Systematic Review.

BACKGROUND: Following clinical research of potential coronavirus disease 2019 (COVID-19) treatments, numerous decision-analytic models have been developed. Due to pandemic circumstances, clinical evidence was limited and modelling choices were made under great uncertainty. This study aimed to analyse key methodological characteristics of model-based economic evaluations of COVID-19 drug treatments, and specifically focused on modelling choices which pertain to disease severity levels during hospitalisation, model structure, sources of effectiveness and quality of life and long-term sequelae. METHODS: We conducted a systematic literature review and searched key databases (including MEDLINE, EMBASE, Web of Science, Scopus) for original articles on model-based full economic evaluations of COVID-19 drug treatments. Studies focussing on vaccines, diagnostic techniques and non-pharmaceutical interventions were excluded. The search was last rerun on 22 July 2023. Results were narratively synthesised in tabular form. Several aspects were categorised into rubrics to enable comparison across studies. RESULTS: Of the 1047 records identified, 27 were included, and 23 studies (85.2%) differentiated patients by disease severity in the hospitalisation phase. Patients were differentiated by type of respiratory support, level of care management, a combination of both or symptoms. A Markov model was applied in 16 studies (59.3%), whether or not preceded by a decision tree or an epidemiological model. Most cost-utility analyses lacked the incorporation of COVID-19-specific health utility values. Of ten studies with a lifetime horizon, seven adjusted general population estimates to account for long-term sequelae (i.e. mortality, quality of life and costs), lasting for 1 year, 5 years, or a patient's lifetime. The most often reported parameter influencing the outcome of the analysis was related to treatment effectiveness. CONCLUSION: The results illustrate the variety in modelling approaches of COVID-19 drug treatments and address the need for a more standardized approach in model-based economic evaluations of infectious diseases such as COVID-19. TRIAL REGISTRY: Protocol registered in PROSPERO under CRD42023407646.