Quality-Adjusted Life-Years Lost Due to COVID-19 Mortality: Methods and Application for The Netherlands

Cost-effectiveness Analysis of Nirmatrelvir/Ritonavir for COVID-19 Among Individuals at High Risk: A Modeling Study

Background

To prevent severe disease, nirmatrelvir/ritonavir (nirmatrelvir/r) is administered to individuals infected with SARS-CoV-2 who are at high risk, and it is currently priced at approximately $1375 in the Netherlands. We aim to evaluate the health outcomes and cost-effectiveness of nirmatrelvir/r among patients with high risk of severe disease.

Methods

We used a decision-analytic model parameterized with clinical and health care utilization data from individuals at high risk who were infected with SARS-CoV-2 between September 2021 and November 2023. We assumed baseline event rates of 1% for hospitalization and 0.05% for intensive care unit admission. Nirmatrelvir/r-related factors were varied. Costs were collected from a third-party payer's perspective, and the cost-effectiveness threshold was <$88 000 per quality-adjusted life-year gained. Sensitivity analyses were performed to account for uncertainties.

Results

This study included 949 individuals at high risk who were infected with SARS-CoV-2. The sample had a median age of 65 years (IQR, 53-75), and 416 (44%) participants were female. Comorbidities included obesity (25%), hematologic malignancy (21%), solid organ/stem cell transplantation (17%), and immunosuppressive medication use (47%). With an assumed low effectiveness, nirmatrelvir/r could reduce hospitalizations and deaths (relative risk reduction, 21% and 44%, respectively). With high effectiveness, relative risk reductions of 89% and 90% were calculated for hospitalizations and deaths. Higher baseline rates for intensive care unit and hospital admission positively influenced cost-effectiveness thresholds. Nirmatrelvir/r is cost-effectively priced at <$512 with low effectiveness and <$1071 with high effectiveness.

Conclusions

With current low baseline event rates for hospitalization, nirmatrelvir/r has the potential, not only to reduce hospitalizations and deaths in individuals with COVID-19 who are at high risk, but to do so cost-effectively with a drug price reduction of 22% to 63%. These findings are relevant for policy makers and physicians and emphasize the importance of reevaluating current drug pricing.

Clinical Trials Registration

NCT05195060 (ClinicalTrials.gov).

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.

Estimating quality-adjusted life expectancy (QALE) for local authorities in Great Britain and its association with indicators of the inclusive economy: a cross-sectional study

OBJECTIVES

Quantifying area-level inequalities in population health can help to inform policy responses. We describe an approach for estimating quality-adjusted life expectancy (QALE), a comprehensive health expectancy measure, for local authorities (LAs) in Great Britain (GB). To identify potential factors accounting for LA-level QALE inequalities, we examined the association between inclusive economy indicators and QALE.

SETTING

361/363 LAs in GB (lower tier/district level) within the period 2018-2020.

DATA AND METHODS

We estimated life tables for LAs using official statistics and utility scores from an area-level linkage of the Understanding Society survey. Using the Sullivan method, we estimated QALE at birth in years with corresponding 80% CIs. To examine the association between inclusive economy indicators and QALE, we used an open access data set operationalising the inclusive economy, created by the System Science in Public Health and Health Economics Research consortium.

RESULTS

Population-weighted QALE estimates across LAs in GB were lowest in Scotland (females/males: 65.1 years/64.9 years) and Wales (65.0 years/65.2 years), while they were highest in England (67.5 years/67.6 years). The range across LAs for females was from 56.3 years (80% CI 45.6 to 67.1) in Mansfield to 77.7 years (80% CI 65.11 to 90.2) in Runnymede. QALE for males ranged from 57.5 years (80% CI 40.2 to 74.7) in Merthyr Tydfil to 77.2 years (80% CI 65.4 to 89.1) in Runnymede. Indicators of the inclusive economy accounted for more than half of the variation in QALE at the LA level (adjusted R2 females/males: 50%/57%). Although more inclusivity was generally associated with higher levels of QALE at the LA level, this association was not consistent across all 13 inclusive economy indicators.

CONCLUSIONS

QALE can be estimated for LAs in GB, enabling further research into area-level health inequalities. The associations we identified between inclusive economy indicators and QALE highlight potential policy priorities for improving population health and reducing health inequalities.

Quantifying income inequality in years of life lost to COVID-19: a prediction model approach using Dutch administrative data

BACKGROUND

Low socioeconomic status and underlying health increase the risk of fatal outcomes from COVID-19, resulting in more years of life lost (YLL) among the poor. However, using standard life expectancy overestimates YLL to COVID-19. We aimed to quantify YLL associated with COVID-19 deaths by sex and income quartile, while accounting for the impact of individual-level pre-existing health on remaining life expectancy for all Dutch adults aged 50+.

METHODS

Extensive administrative data were used to model probability of dying within the year for the entire 50+ population in 2019, considering age, sex, disposable income and health care use (n = 6 885 958). The model is used to predict mortality probabilities for those who died of COVID-19 (had they not died) in 2020. Combining these probabilities in life tables, we estimated YLL by sex and income quartile. The estimates are compared with YLL based on standard life expectancy and income-stratified life expectancy.

RESULTS

Using standard life expectancy results in 167 315 YLL (8.4 YLL per death) which is comparable to estimates using income-stratified life tables (167 916 YLL with 8.2 YLL per death). Considering pre-existing health and income, YLL decreased to 100 743, with 40% of years lost in the poorest income quartile (5.0 YLL per death). Despite individuals in the poorest quartile dying at younger ages, there were minimal differences in average YLL per COVID-19 death compared with the richest quartile.

CONCLUSIONS

Accounting for prior health significantly affects estimates of YLL due to COVID-19. However, inequality in YLL at the population level is primarily driven by higher COVID-19 deaths among the poor. To reduce income inequality in the health burden of future pandemics, policies should focus on limiting structural differences in underlying health and exposure of lower income groups.

Societal costs of sepsis in the Netherlands

BACKGROUND

Sepsis is a life-threatening syndrome characterized by acute loss of organ function due to infection. Sepsis survivors are at risk for long-term comorbidities, have a reduced Quality of Life (QoL), and are prone to increased long-term mortality. The societal impact of sepsis includes its disease burden and indirect economic costs. However, these societal costs of sepsis are not fully understood. This study assessed sepsis's disease-related and indirect economic costs in the Netherlands.

METHODS

Sepsis prevalence, incidence, sepsis-related mortality, hospitalizations, life expectancy, QoL population norms, QoL reduction after sepsis, and healthcare use post-sepsis were obtained from previous literature and Statistics Netherlands. We used these data to estimate annual Quality-adjusted Life Years (QALYs), productivity loss, and increase in healthcare use post-sepsis. A sensitivity analysis was performed to analyze the burden and indirect economic costs of sepsis under alternative assumptions, resulting in a baseline, low, and high estimated burden. The results are presented as a baseline (low-high burden) estimate.

RESULTS

The annual disease burden of sepsis is approximately 57,304 (24,398-96,244; low-high burden) QALYs. Of this, mortality accounts for 26,898 (23,166-31,577) QALYs, QoL decrease post-sepsis accounts for 30,406 (1232-64,667) QALYs. The indirect economic burden, attributed to lost productivity and increased healthcare expenditure, is estimated at €416.1 (147.1-610.7) million utilizing the friction cost approach and €3.1 (0.4-5.7) billion using the human capital method. Cumulatively, the combined disease and indirect economic burdens range from €3.8 billion (friction method) to €6.5 billion (human capital method) annually within the Netherlands.

CONCLUSIONS

Sepsis and its complications pose a substantial disease and indirect economic burden to the Netherlands, with an indirect economic burden due to production loss that is potentially larger than the burden due to coronary heart disease or stroke. Our results emphasize the need for future studies to prevent sepsis, saving downstream costs and decreasing the economic burden.

Projections of costs and quality adjusted life years lost due to dementia from 2020 to 2050: A population-based microsimulation study

INTRODUCTION

Efficient healthcare planning requires reliable projections of the future increase in costs and quality-adjusted life years (QALYs) lost due to dementia.

METHODS

We used the microsimulation model MISCAN-Dementia to simulate life histories and dementia occurrence using population-based Rotterdam Study data and nationwide birth cohort demographics. We estimated costs and QALYs lost in the Netherlands from 2020 to 2050, incorporating literature estimates of cost and utility for patients and caregivers by dementia severity and care setting.

RESULTS

Societal costs and QALYs lost due to dementia are estimated to double between 2020 and 2050. Costs are incurred predominantly through institutional (34%), formal home (31%), and informal home care (20%). Lost QALYs are mostly due to shortened life expectancy (67%) and, to a lesser extent, quality of life with severe dementia (14%).

DISCUSSION

To limit healthcare costs and quality of life losses due to dementia, interventions are needed that slow symptom progression and reduce care dependency.

Economic Evaluation of Wastewater Surveillance Combined with Clinical COVID-19 Screening Tests, Japan

The COVID-19 pandemic has imposed substantial burdens on the global society. To find an optimal combination of wastewater surveillance and clinical testing for tracking COVID-19, we evaluated the economic efficiency of hypothetical screening options at a single facility in Japan. To conduct cost-benefit analyses, we developed standard decision models in which we assumed model parameters from literature and primary data, such as screening policies used at the Tokyo Olympic and Paralympic Village in 2021. We compared hypothetical 2-step screening options that used clinical PCR to diagnose COVID-19 after a positive result from primary screening using antigen tests (option 1) or wastewater surveillance (option 2). Our simulation results indicated that option 2 likely would be economically more justifiable than option 1, particularly at lower incidence levels. Our findings could help justify and promote the use of wastewater surveillance as a primary screening at a facility level for COVID-19 and other infectious diseases.

Health Outcomes and Cost-effectiveness of Monoclonal SARS-CoV-2 Antibodies as Pre-exposure Prophylaxis

Importance

Pre-exposure prophylaxis with neutralizing SARS-CoV-2 monoclonal antibodies (mAbs PrEP) prevents infection and reduces hospitalizations and the duration thereof for COVID-19 and death among high-risk individuals. However, reduced effectiveness due to a changing SARS-CoV-2 viral landscape and high drug prices remain substantial implementation barriers.

Objective

To assess the cost-effectiveness of mAbs PrEP as COVID-19 PrEP.

Design, Setting, and Participants

For this economic evaluation, a decision analytic model was developed and parameterized with health care outcome and utilization data from individuals with high risk for COVID-19. The SARS-CoV-2 infection probability, mAbs PrEP effectiveness, and drug pricing were varied. All costs were collected from a third-party payer perspective. Data were analyzed from September 2021 to December 2022.

Main Outcomes and Measures

Health care outcomes including new SARS-CoV-2 infections, hospitalization, and deaths. The cost per death averted and cost-effectiveness ratios using a threshold for prevention interventions of $22 000 or less per quality-adjusted life year (QALY) gained.

Results

The clinical cohort consisted of 636 individuals with COVID-19 (mean [SD] age 63 [18] years; 341 [54%] male). Most individuals were at high risk for severe COVID-19, including 137 (21%) with a body mass index of 30 or higher, 60 (9.4%) with hematological malignant neoplasm, 108 (17%) post-transplantation, and 152 (23.9%) who used immunosuppressive medication before COVID-19. Within the context of a high (18%) SARS-CoV-2 infection probability and low (25%) effectiveness the model calculated a short-term reduction of 42% ward admissions, 31% intensive care unit (ICU) admissions, and 34% deaths. Cost-saving scenarios were obtained with drug prices of $275 and 75% or higher effectiveness. With a 100% effectiveness mAbs PrEP can reduce ward admissions by 70%, ICU admissions by 97%, and deaths by 92%. Drug prices, however, need to reduce to $550 for cost-effectiveness ratios less than $22 000 per QALY gained per death averted and to $2200 for ratios between $22 000 and $88 000.

Conclusions and Relevance

In this study, use of mAbs PrEP for preventing SARS-CoV-2 infections was cost-saving at the beginning of an epidemic wave (high infection probability) with 75% or higher effectiveness and drug price of $275. These results are timely and relevant for decision-makers involved in mAbs PrEP implementation. When newer mAbs PrEP combinations become available, guidance on implementation should be formulated ensuring a fast rollout. Nevertheless, advocacy for mAbs PrEP use and critical discussion on drug prices are necessary to ensuring cost-effectiveness for different epidemic settings.

Estimating the health impact of delayed elective care during the COVID -19 pandemic in the Netherlands

BACKGROUND

The COVID-19 pandemic had a major impact on the continuity of healthcare provision. Appointments, treatments and surgeries for non-COVID patients were often delayed, with associated health losses for patients involved.

OBJECTIVE

To develop a method to quantify the health impact of delayed elective care for non-COVID patients.

METHODS

A model was developed that estimated the backlog of surgical procedures in 2020 and 2021 using hospital registry data. Quality-adjusted life years (QALYs) were obtained from the literature to estimate the non-generated QALYs related to the backlog. In sensitivity analyses QALY values were varied by type of patient prioritization. Scenario analyses for future increased surgical capacity were performed.

RESULTS

In 2020 and 2021 an estimated total of 305,374 elective surgeries were delayed. These delays corresponded with 319,483 non-generated QALYs. In sensitivity analyses where QALYs varied by type of patient prioritization, non-generated QALYs amounted to 150,973 and 488,195 QALYs respectively. In scenario analyses for future increased surgical capacity in 2022-2026, the non-generated QALYs decreased to 311,220 (2% future capacity increase per year) and 300,710 (5% future capacity increase per year). Large differences exist in the extent to which different treatments contributed to the total health losses.

CONCLUSIONS

The method sheds light on the indirect harm related to the COVID-19 pandemic. The results can be used for policy evaluations of COVID-19 responses, in preparations for future waves or other pandemics and in prioritizing the allocation of resources for capacity increases.

Model-based estimation of burden of COVID-19 with disability-adjusted life years and value of statistical life in West Bengal, India

OBJECTIVES

The COVID-19 pandemic has posed unprecedented challenges to health systems and populations, particularly in India. Comprehensive, population-level studies of the burden of disease could inform planning, preparedness and policy, but are lacking in India. In West Bengal, India, we conducted a detailed analysis of the burden caused by COVID-19 from its onset to 7 January 2022.

SETTING

Open-access, population-level and administrative data sets for West Bengal were used.

PRIMARY AND SECONDARY OUTCOME MEASURES

Disability-adjusted life years (DALYs), years of potential productive life lost (YPPLL), cost of productivity lost (CPL: premature mortality and absenteeism), years of potential life lost (YPLL), premature years of potential life lost, working years of potential life lost (WYPLL) and value of statistical life (VSL) were estimated across scenarios (21 for DALY and 3 each for YPLL and VSL) to evaluate the effects of different factors.

RESULTS

COVID-19 had a higher impact on the elderly population with 90.2% of deaths arising from people aged above 45. In males and females, respectively, DALYs were 190 568.1 and 117 310.0 years, YPPLL of the productive population was 28 714.7 and 16 355.4 years, CPL due to premature mortality was INR3 198 259 615.6 and INR583 397 335.1 and CPL due to morbidity was INR2 505 568 048.4 and INR763 720 886.1. For males and females, YPLL ranged from 189 103.2 to 272 787.5 years and 117 925.5 to 169 712.0 years for lower to higher age limits, and WYPLL was 54 333.9 and 30 942.2 years. VSL (INR million) for the lower, midpoint and upper life expectancies was 883 330.8; 882 936.4; and 880 631.3, respectively. Vaccination was associated with reduced mortality.

CONCLUSIONS

The losses incurred due to COVID-19 in terms of the computed estimates in West Bengal revealed a disproportionately higher impact on the elderly and males. Analysis of various age-gender subgroups enhances localised and targeted policymaking to minimise the losses for future pandemics.