Journal of Medical Economics

COVID-19 remains a substantial public health challenge in the Netherlands. Next-generation COVID-19 vaccine, mRNA-1283, is approved in the European Union, with potential for higher relative vaccine efficacy compared with originally-licensed COVID-19 vaccines. Its potential public health and economic impact, in adults [≥]60 years and high-risk 18-59 years, was modelled versus no vaccination and originally-licensed mRNA-1273 and BNT162b2, adapting a published static Markov model with 1-year time horizon. COVID-19 burden reflected two full post-pandemic seasons. Vaccine efficacy versus mRNA-1273 was based on pivotal phase 3 NextCOVE trial data; efficacy versus BNT162b2 was derived from an indirect treatment comparison. The economically justifiable price (EJP) of mRNA-1283 versus no vaccination, and price premiums over existing vaccines, were determined at a willingness-to-pay threshold of {euro}50,000/quality-adjusted life-year (QALY) gained. Without COVID-19 vaccination, an estimated 460,000 infections, 23,800 hospitalizations and 5,300 deaths would occur. With current coverage, mRNA-1283 was estimated to prevent 68,000 infections, 5,400 hospitalizations, and 1,200 deaths, saving 9,667 QALYs and over {euro}66.5 million in treatment costs. The EJP was {euro}238 versus no vaccination. Compared with mRNA-1273 and BNT162b2, mRNA-1283 was estimated to prevent additional burden (e.g., 1,309 and 1,679 hospitalizations, respectively), and was cost-effective at an incremental EJP of {euro}62 versus mRNA-1273, and {euro}80 versus BNT162b2. The results support continued COVID-19 vaccination to mitigate the ongoing health and societal burden of SARS-CoV-2 in the Netherlands. The comparative analyses indicate that mRNA-1283 may be associated with substantial health benefits over originally-licensed mRNA vaccines; consequently, its use may further improve health outcomes and economic efficiency within COVID-19 vaccination programs.

BackgroundQuadruple therapy, comprising an angiotensin receptor-neprilysin inhibitor (ARNI), {beta}-blocker, mineralocorticoid receptor antagonist (MRA), and sodium-glucose cotransporter 2 inhibitor (SGLT2i), is guideline-recommended for heart failure with reduced ejection fraction (HFrEF). However, uptake in Singapore remains low. This study evaluated the cost-effectiveness of scaling up quadruple therapy from the current 30% uptake to realistic (80%) and stretch (100%) targets. MethodsWe developed a decision-analytic model combining a decision tree and Markov structure to simulate clinical and economic outcomes over a 10-year horizon from the Singapore healthcare system perspective. Transition probabilities were estimated using local real-world data for current regimens, and published literature for quadruple therapy. Costs were derived from hospital billing data and drug utilisation patterns. A probabilistic sensitivity analysis (1,000 simulations) assessed uncertainty. The willingness-to-pay (WTP) threshold was S$45,000 per quality-adjusted life year (QALY) gained. ResultsBoth scale-up scenarios were cost-effective. Compared to current practice, the 80% uptake scenario resulted in an incremental cost of S$2.57M and 110 additional QALYs (ICER: S$23,392/QALY) for 1000 patients over 10 years, while the 100% uptake scenario yielded 137 QALYs at an incremental cost of S$2.88M (ICER: S$21,117/QALY). Under conservative assumptions, both scenarios remained cost-effective. The probability of being cost-effective was 92% (80% uptake) and 96% (100% uptake). InterpretationScaling up quadruple therapy for HFrEF in Singapore is highly cost-effective. Implementation strategies to close the treatment gap should be prioritised to improve outcomes and maximise value in heart failure care.

BackgroundThe United Nations General Assembly High-level Meeting on Antimicrobial Resistance (UNGA HLM-AMR) committed to a target that 70% of global human antibiotic use (ABU) should be from the Access group of the WHO AWaRe system. MethodsWe used 2019 IQVIA MIDAS(R) global ABU Quarterly value sales, volumes (kg/SU) and average ex-manufacturer prices to evaluate price per daily defined dose (DDD) by AWaRe group across countries. IQVIA MIDAS volumes/value data reflect public, private, or mixed sectors. We estimated potential national pharmaceutical expenditure savings if i) the UNGA 70% Access target was met, and ii) national ABU aligned with the WHO Model List of Essential Medicines (EML). We evaluated 7-day treatment prices for common oral and parenteral antibiotics across AWaRe groups. We measured affordability in middle-income countries (MICs) by income group, as the percentage of the population at risk of falling below national poverty lines if paying out-of-pocket, using income distributions and generalised beta distributions of the second kind. Prices were reported in 2019 international dollars (I$). ResultsVolume-weighted ex-manufacturer prices per DDD were lower for Access (I$1{middle dot}2, IQR I$0{middle dot}7) than Watch (I$2{middle dot}6, IQR I$2{middle dot}1) and highest (I$83{middle dot}8, IQR I$80{middle dot}9) for Reserve antibiotics. Lower prices were seen in high-income countries for Access antibiotics. Meeting the 70% Access target could save countries I$0{middle dot}1 million-I$4{middle dot}9 billion annually. Global savings could reach I$10{middle dot}4 billion if only WHO EML-listed antibiotics were used. Seven-day parenteral meropenem could put 7% (IQR 9%) of the population in MICs at risk of impoverishment. ConclusionAntibiotic policies focused on achieving the UNGA-AMR 70% Access target could generate significant potential national and global expenditure savings. FundingThis work was supported by the Wellcome Trust (304681/Z/23/Z) as part of the Antibiotic Data to Inform Local Action (ADILA) project and the Global Antibiotic Policy initiative (GAPi) project (RES 2024-495).

BackgroundThe Most Favored Nation (MFN) policy is a mechanism that incorporates foreign prices to determine the maximum allowable net price for any branded drug within US government-funded healthcare. Two proposed rules, the Global Benchmark for Efficient Drug Pricing ("GLOBE") (90 Fed. Reg. 60,244) for Medicare Part B and the Guarding US Medicare Against Rising Drug Costs ("GUARD") (90 Fed. Reg. 60,338) for Medicare Part D, invoke the Center for Medicare and Medicaid Innovation Centers payment and service model demonstration and waiver authority, under Section 1115A of the Social Security Act (42 U.S.C. [§] 1315a), to calculate the US MFN price which is the lowest average price within a basket of specified foreign countries. Unlike voluntary manufacturer agreements, GLOBE and GUARD would mandate participation from all applicable manufacturers. MethodsWe derive MFNs potential impact on Medicare pricing from a proprietary dataset provided by IQVIA which contained net prices for the top 37 oncology products by total US sales from January 1, 2019 through June 30, 2025 ranked by total US sales in the following countries: Australia, Belgium, France, Germany, Ireland, Italy, South Africa, Spain, Switzerland, the UK, and the US. For each drug, we select the lowest GDP-adjusted international price from a basket of those countries within 60% of the US GDP per capita, adjusted for purchasing power parity, and calculate the reduction in US price required to match its MFN price, and hence the corresponding reduction in revenues under MFN. A retrospective Net Present Value (NPV) analysis is then used to address the counterfactual question of whether each drug would have been developed had MFN pricing been in place at the time of its FDA approval. ResultsUnder MFN, the average reduction in US prices across our drug cohort was 67%. Eighty-four percent of the 37 cancer drugs in our cohort evidenced a negative NPV if MFN had been in place at the time of their FDA approval and the commercial market is impacted. When the analysis is restricted to MFNs impact on Medicare, the indications for these lost drugs have a total US population of 2.4 million patients. When the analysis is combined across the Medicare and commercial markets, the loss of lead indications impacts over 15 million US patients. ConclusionsMandatory MFN policies reduce the financial incentives required to develop cancer medicines; our projections show a substantial decline in new cancer drug launches and will likely lead companies to pursue indications for populations outside Medicares authority. If so, MFN will reduce the number of new therapies for the very population the Executive Orders are allegedly designed to aid: the Medicare-aged population who require effective new therapies in areas of high unmet medical need, such as late-stage cancers. This creates the perverse outcome of a policy nominally designed to help Medicare beneficiaries by instead redirecting innovation away from their most urgent therapeutic needs.

The risk of esophageal adenocarcinoma (EAC) in Barretts esophagus (BE) varies substantially by segment length and dysplasia grade. This study evaluated the cost-effectiveness and health impacts of dysplasia-stratified EAC surveillance strategies for the Japanese BE population. A state-transition model was developed comparing endoscopy, sponge test, breath test, and miRNA test with no surveillance from a healthcare payer perspective over a lifetime. Non-invasive strategies were assessed as primary surveillance tools, with positive results triggering confirmatory endoscopy, and a scenario analysis evaluated AI-assisted endoscopy. Five BE populations of 50-year-old individuals were modeled: ultra-short segment BE (USSBE), short-segment BE (SSBE), long-segment nondysplastic BE (LSBE-NDBE), LSBE with low-grade dysplasia (LSBE-LGD), and LSBE with high-grade dysplasia (LSBE-HGD). Each modality was evaluated at surveillance intervals of 1, 2, 3, 4, 5, or 10 years. Primary outcomes included net monetary benefits, costs, quality-adjusted life-years, incremental cost-effectiveness ratios, and EAC deaths, with sensitivity analyses assessing parameter uncertainty. Surveillance was not cost-effective for USSBE, SSBE, or LSBE-NDBE. For LSBE-LGD, annual endoscopy was most cost-effective, averting 83 EAC deaths per 10,000 individuals, while for LSBE-HGD, annual breath testing was most cost-effective, averting 295 deaths. These findings support dysplasia-specific surveillance in LSBE with implications for global surveillance practice.

ObjectivesDigital biomarkers offer scalable screening for type 2 diabetes, yet adoption is stalled by uncertainty regarding economic viability. This study evaluates the cost-effectiveness and budget impact of digital screening compared to opportunistic screening from a Swiss payer perspective. MethodsA probabilistic Markov cohort model was developed to simulate at-risk Swiss adults (age [≥]45, BMI [≥]25 kg/m{superscript 2}) over a 40-year horizon. The model incorporates a digital attrition parameter, inputs derived from Swiss-specific sources (e.g., the CoLaus study and FSO life tables), and statutory tariffs. Costs and outcomes were discounted at 3.0%. ResultsIn the deterministic base-case, digital screening yielded an incremental cost-effectiveness ratio of CHF 2,912 per quality-adjusted life-year gained. Probabilistic sensitivity analysis indicated a 93.2% probability of cost-effectiveness at the CHF 50,000 threshold. The budget impact analysis estimated a Year 1 gross investment budget of CHF 27 million to identify prevalent cases, followed by long-term savings from averted complications. ConclusionsDigital screening can be highly cost-effective in Switzerland. While the required Year 1 gross investment poses a liquidity challenge, reimbursement via pathway-oriented models under the Swiss tariff could align incentives with long-term complication avoidance.

BackgroundHigh-dose inactivated influenza vaccination (HD-IIV) demonstrates superior effectiveness versus standard-dose vaccination (SD-IIV) in adults aged [≥]60 years. A recent meta-analysis integrated complementary evidence sources of representing over 85 million individuals across 14 influenza seasons. MethodsA previously developed model was updated using life-time horizon and societal perspective. Updated parameters included demographics, costs, hospitalization rates, and relative vaccine effectiveness (rVE): RCT evidence (24% for ILI, 7% for cardiorespiratory hospitalizations) and RCT + real-world evidence (RWE) (15% for ILI, 8% for cardiorespiratory hospitalizations). ResultsHD-IIV resulted in incremental cost-effectiveness ratios of {euro}7,300/QALY (RCT evidence) and {euro}5,800/QALY (RCT+RWE evidence). Implementation would prevent 7,200 general practitioner visits, 6,300 cardiorespiratory hospitalizations, and 269 deaths, by using RCT evidence. Probabilistic sensitivity analysis demonstrated >99% probability of cost-effectiveness at {euro}20,000/QALY threshold for both RCT and RCT+RWE evidence. ConclusionsHD-IIV remains highly cost-effective for Dutch adults aged [≥]60 years under updated evidence scenarios, supporting implementation in the national immunization programme. HighlightsO_LIThe economic analysis of high-dose inactivated influenza vaccine was updated. C_LIO_LIRelative vaccine effectiveness of HD-IIV incorporating recent evidence was used. C_LIO_LIHD-IIV remains cost-effective in Dutch adults aged [≥]60. C_LI

OBJECTIVEOpioid misuse exacts a tremendous toll on society. Mindfulness-Oriented Recovery Enhancement (MORE) is an efficacious treatment for opioid misuse. Yet, the cost-effectiveness of this intervention remains unknown. METHODSCost-effectiveness and cost-benefit analyses of a randomized clinical trial with enrollment of 250 adults with chronic pain prescribed long-term opioid therapy who were misusing opioids. Participants were randomized to MORE (training in mindfulness, reappraisal, and savoring positive experiences) or supportive group psychotherapy across 8 weekly 2-hour groups. Incremental cost-effectiveness ratios (ICER) and benefit-to-cost ratios (BCRs) were computed using the primary outcome of opioid misuse at 9-month follow-up, as assessed by a composite measure based on self-report, clinical interview, and urine screen. RESULTS250 randomized patients (64.0% female) had an average age of 51.8 years (SD=11.9), were mostly taking oxycodone or hydrocodone (69%), and had mean morphine equivalent opioid dose of 101.0 (IQR=74) mg. At 9-mo. follow-up, the difference in the probability of having a positive Drug Misuse Index (DMI) rating was 0.24 (0.54 for MORE participants vs. 0.78 for controls). The ICER of MORE relative to supportive psychotherapy was $116.3 per averted case of opioid misuse, $8.9 per life-year, and $8.0 per quality-adjusted life-year. MORE is cost-saving vs. supportive psychotherapy after adjusting for healthcare costs. Excluding all benefits associated with averting fatal overdoses results in a BCR of 84.2. CONCLUSIONSGiven MOREs cost-effectiveness, private and public payers should consider disseminating this evidence-based therapy broadly across the nation to reduce mortality and morbidity associated with the ongoing opioid crisis. HIGHLIGHTSO_LIMindfulness-Oriented Recovery Enhancement (MORE) substantially reduced opioid misuse among adults with chronic pain on long-term opioid therapy. C_LIO_LIMORE was highly cost-effective vs. supportive psychotherapy, costing $116 per averted opioid misuse case, and MORE was cost saving when accounting for healthcare costs associated with opioid misuse. C_LIO_LIFindings suggest wide dissemination of this evidence-based treatment could yield major healthcare and other economic benefits in addressing the opioid crisis. C_LI

ObjectivesNon-communicable diseases (NCDs) account for almost 90% of deaths in Europe, yet comparative estimates of the productivity costs associated with premature NCD mortality across diseases and countries remain limited. This study estimates and compares productivity losses attributable to cardiovascular disease (CVD) and cancer mortality among working-age populations across Europe. Population-based data were used to estimate productivity costs for CVD and cancer deaths across 30 European countries. Sex- and age-specific mortality data for 2021 were obtained from the World Health Organization Mortality Database. Economic data, including wages, unemployment rates, and labour force participation rates, were sourced from Eurostat. Productivity losses were valued using a human capital approach incorporating an age-transition lifecycle simulation model that adjusts for lifetime wage trajectories and labour market dynamics. Costs were discounted at 3.5%. Total productivity losses from cancer and CVD mortality in working-age populations were estimated at {euro}195.7 billion, equivalent to 1.24% of European GDP. Cancer accounted for 62.5% ({euro}122.2 billion) of total productivity losses, while CVD accounted for 37.5% ({euro}73.5 billion). Total CVD-related productivity costs exceeded cancer-related costs in Central and Eastern Europe, whereas cancer productivity costs were higher in Western, Northern, and Southern Europe. Mean productivity costs per death were higher for CVD ({euro}219,848; 95% CI 165,241-270,247) than for cancer ({euro}217,744; 95% CI 166,554-273,144). A larger gender gap was observed for CVD mortality, with a male-to-female cost ratio of 2.5 compared with 1.6 for cancer. Productivity losses associated with premature cancer and CVD mortality represent a substantial economic burden across Europe, with pronounced variation by disease, region, and sex. These findings provide comparative, cross-country estimates of the human capital costs associated with major NCD causes of death.

We developed and validated a self-administered clinical vignette platform powered by a large language model (LLM), deployed through a SurveyCTO web survey, to measure primary health care provider competencies in Vietnam. In a pilot focus group, nine physicians rated LLM-simulated patient interactions as realistic (mean 3.78/5) and user-friendly. In the validation phase, 22 providers completed 132 vignette interactions across ten clinical scenarios in Vietnamese. Essential diagnostic checklist scores (human-coded from translated transcripts) correlated with expert clinician evaluations (Pearsons{rho} = 0.55-0.60). LLM-automated coding of checklist items from translated English transcripts correlated reasonably with human coding ({rho} = 0.53), and coding directly from Vietnamese transcripts performed comparably ({rho} = 0.51), suggesting that a separate translation step may not be necessary. The total cost of 132 chatbot interactions was under USD 2. LLM-driven conversational vignettes represent a low-cost and scalable method for assessing provider competencies in respondents local language, eliminating the need for extensive enumeration staffs while preserving the open-ended format critical to vignette validity, and additionally introducing flexible feature extraction from transcripts using grading rubrics. The platform is open-source and designed for replication in other health system contexts. Author summaryMeasuring the clinical skills of healthcare providers is essential for improving the quality of care, but current survey methods are expensive and require trained enumerators to travel to health facilities in person. We developed a new approach that uses large language models (LLMs) - the technology behind tools like ChatGPT and Claude - to simulate patients in realistic clinical conversations that healthcare providers can complete on their phones or laptops over the Internet in their own language. In Vietnam, we tested this tool with 31 physicians across ten clinical scenarios. Providers found the simulated patient conversations realistic and easy to use. We also tested whether LLMs could automatically score the conversations, which showed reasonable agreement with human scoring, and performed nearly as well when scoring directly from Vietnamese, without requiring a separate translation step. When we compared these results from our tool against holistic expert physician ratings of the same conversations, the scores agreed well, suggesting that automatic transcript grading based on rubrics produces meaningful measures of clinical skill. This tool costs less than two US dollars for over a hundred consultations and required no in-person surveyors, making it potentially transformative for routine, large-scale monitoring of healthcare quality in resource-limited settings. The platform and code are openly available for adaptation.

ObjectiveTo evaluate modifiable antepartum and intrapartum factors associated with nulliparous, term, singleton, vertex (NTSV) cesarean delivery and to model risk stratified induction timing strategies that minimize cesarean risk across maternal risk profiles. Study DesignThis retrospective cohort study included all NTSV deliveries at a tertiary care center from January 2015 through August 2025 (overall cohort n=10,525; limited risk cohort n=5,663). Machine learning identified key predictors of cesarean delivery, with maternal age and pre pregnancy body mass index (BMI) used to define low, moderate, and high risk strata. Logistic regression estimated the association between induction and cesarean delivery, and a Monte Carlo simulation compared elective induction at 39, 40, or 41 weeks versus expectant management to 42 weeks within each stratum. ResultsCesarean delivery occurred in 20.1% of the overall cohort and 19.0% of the limited risk cohort, with a U shaped relationship between gestational age and cesarean risk and lowest rates at 38-39 weeks. Induction was associated with higher cesarean rates than spontaneous labor in both cohorts (overall: 24.1% vs. 17.1%; limited risk: 22.9% vs. 15.7%) after adjustment for age, BMI, and gestational age. No single induction policy minimized cesarean risk across all strata. For high risk patients (age >=35 years and BMI >=35), induction at 39 weeks yielded the lowest modeled cesarean rate, whereas later delivery (40 to 41 weeks or expectant management to 41 weeks) was favored for low and moderate risk patients. A universal 39 week induction policy for low and moderate risk strata modestly increased modeled cesarean rates, adding an estimated 46 cesarean deliveries. ConclusionGestational age at delivery and induction strategy are key modifiable determinants of NTSV cesarean delivery, but optimal timing varies by maternal age and BMI risk profile, supporting risk stratified rather than universal 39 week induction policies.

ObjectivesTo examine associations between cardiometabolic conditions and health-related quality of life (HRQoL) and to evaluate whether condition-associated HRQoL changed from 2001 to 2022. MethodsWe analyzed nationally representative data from U.S. adults aged [≥]18 years in the Medical Expenditure Panel Survey, 2001-2022. Survey years without BMI data (2017, 2019, 2021) were excluded. EQ-5D utilities were mapped from SF-12 scores using a validated algorithm. For each survey year, survey-weighted multivariable regression models estimated associations of sociodemographic characteristics, BMI, and cardiometabolic conditions (diabetes, heart disease, high blood pressure, high cholesterol, obesity, stroke) with HRQoL measured by EQ-5D. Temporal changes in condition-associated HRQoL decrements were assessed using meta-regression across years. Associations in recent survey years were summarized using pooled estimates from 2015, 2016, 2018, and 2022. ResultsOverall HRQoL improved from 2001 to 2022 across age groups, with the largest improvement among older adults. In pooled analyses, stroke was associated with the largest adjusted HRQoL decrement (-0.0714), followed by heart disease (-0.0503), diabetes (-0.0427), high blood pressure (-0.0328), obesity (-0.0305), and high cholesterol (-0.0236). Additional adjustment for BMI attenuated condition-associated decrements, most notably for obesity (-0.0305 to -0.0183), diabetes (-0.0427 to -0.0414), and high blood pressure (-0.0328 to -0.0316). Over time, diabetes- and heart disease-associated decrements attenuated linearly (diabetes: - 0.0489 in 2001 to -0.0406 in 2022; heart disease: -0.0591 to -0.0493). High blood pressure (-0.0337 in 2001, -0.0415 in 2012, -0.0306 in 2022) and obesity (-0.0305 in 2001, -0.0283 in 2012, -0.0367 in 2022) showed nonlinear patterns. ConclusionsCondition-associated HRQoL decrements varied over time, and recent-year utility estimates are recommended for population health research. HRQoL decrements for diabetes and heart disease attenuated, consistent with improvements in treatment and survival. High blood pressure-associated were lowest around 2012, and obesity-associated became more negative after 2012, consistent with worsening blood pressure control and obesity severity.

ObjectiveTo retrospectively validate an electronic health record (EHR) implementation of the patient-initiated PreMA screener and compare its association with severe maternal morbidity (SMM) outcomes against established obstetric comorbidity indices. MethodsWe conducted a retrospective observational study using UCSF (single center) and UC-wide (multi-center) de-identified EHR data, identifying live-birth deliveries with documented preconception data. PreMA and established comorbidity index (Bateman and Leonard) scores were computed from preconception diagnoses, standardized to z-scores, and modeled as continuous predictors of SMM and non-transfusion SMM (NT-SMM) using logistic and Poisson regression models, with stratified analyses by race, ethnicity, and neighborhood deprivation. To examine the relationship between individual PreMA questionnaire domains and outcomes, we used adjusted Poisson regression to estimate the association of each domain with SMM and NT-SMM. ResultsAcross both cohorts, higher standardized PreMA, Bateman, and Leonard scores were consistently significantly associated with increased risk of SMM and NT-SMM, with relative risk estimates generally in the [~]1.2-1.4 range per standard deviation (adj. p < 0.001), and similar magnitude across indices and cohorts. Significant associations persisted across racial, ethnic, and socioeconomic, and item-level analyses suggested heterogeneity across PreMA domains, with cardiovascular domains showing the strongest adjusted associations. ConclusionAn EHR-derived PreMA score demonstrated robust, generalizable associations with severe maternal morbidity outcomes comparable to established clinician-facing indices, supporting PreMAs validity as a scalable, patient-centered preconception risk assessment tool.

As programs for azithromycin mass drug administration to reduce child mortality have begun in some parts of West Africa, it is imperative to understand their financial costs. We combined a micro-costing framework and observations from an implementation-focused sub-study within the AVENIR trials in 80 communities in the Dosso region of Niger to estimate the national health sector costs of a scaled-up programmatic approach for azithromycin biannual distribution to children aged 1-59 months of age living in nonurban areas, using the door-to-door modality. Our outcomes of interest were the annual budget at the regional and national levels for Niger and the cost per dose delivered. We found that the annual national budget required for azithromycin mass drug administration (MDA) achieving 90% average coverage would be $12.5M (95% Uncertainty Interval (UI) $12.2M, $13.0M) translating to $1.59 (95% UI $1.40, $2.30) per dose delivered. Across regions, cost per dose would vary from $1.17 (95% UI $1.03, $1.69) to $3.61 (95% UI $3.20, $5.16), with higher cost per dose expected for more sparsely populated regions. Training costs represented a large fraction (16.4%) of total costs, and integration of training with that for existing health interventions may provide opportunities for efficiency.

BackgroundMaternal participation in neurodevelopmental research involving neuroimaging and diverse biological samples is essential for understanding prenatal influences on early brain development, yet willingness in low-resource settings remains underexplored. MethodWe surveyed 300 mothers using a structured questionnaire to assess willingness to undergo brain health testing (with a focus on electroencephalography [EEG] and brain magnetic resonance imaging [MRI]), provide biological samples (blood, stool, urine, breast milk, placenta, amniotic fluid, vaginal/nasal fluid, saliva, tears), and consent to 10-year storage. Responses were analysed to examine associations between maternal sociodemographic factors and willingness to consent for each research component. ResultsNinety-two percent of participants expressed willingness for brain health testing, including [~]82% and [~]88% interest in EEG and MRI, respectively, even for untreatable conditions. Self-reported histories of foetal defects (5.3%) and birth defects (7.3%) were notably low. Biospecimen acceptance was highest (>95%) for routine samples (blood, stool, urine) but significantly low for sensitive specimens (breast milk, placenta, amniotic fluid: 51-55%) including (vaginal fluid, saliva, tears: 16-47%). Higher levels of maternal education consistently predicted consent across modalities, while being in a relationship increased willingness for stool, urine, placenta, amniotic fluid, MRI, and EEG. Low income reduced uptake for placenta, amniotic fluid, MRI, and EEG. Only 48% consented to 10-year storage of images and samples for future research. ConclusionThis study demonstrates high maternal willingness for neurodevelopmental research involving brain health testing and routine biospecimens in a low-resource setting. The findings highlight the feasibility of such protocols in a low-resource setting while exposing persistent inequities that risk underrepresenting disadvantaged mothers in maternal-child brain research. Contextually tailored consent models and capacity-building initiatives will be essential to ensure equitable, sustainable engagement across diverse LMIC populations.

ObjectivesGiven the widespread use of period-tracking applications and evidence that some users rely on fertile-window predictions for pregnancy prevention, we aimed to quantify pregnancy risk arising from misclassification of biologically fertile days by period-tracking applications, and to compare this risk across calendar-based and basal body temperature (BBT)-supported period tracking and a digital contraceptive regulated as a medical device. MethodsWe conducted an observational analysis of cycles of mobile fertility application users who logged urinary luteinizing hormone (LH) tests. Biologically fertile days were defined using an LH-based reference fertile window (days -5 to 0 relative to ovulation). Three approaches were evaluated: a calendar-based period tracking application, a BBT-supported period tracking application, and a FDA-cleared digital contraceptive. Outcomes included day-specific frequency of fertile days misclassified as safe, cycle-level misclassification, and predicted pregnancy risk per cycle. Analyses were repeated in a subgroup of irregular cycles. Results543,167 menstrual cycles with a clear LH surge signature were included in the analysis. Calendar-based period tracking frequently misclassified fertile days as safe, with 67% of cycles containing at least one at-risk day and 25% containing at least one high-risk day. The mean predicted pregnancy risk per cycle was 22%, increasing to 65% in irregular cycles. BBT-supported period tracking reduced misclassification but remained associated with substantial risk (41% of cycles with at least one at-risk day; mean predicted pregnancy risk 9%). In contrast, the digital contraceptive showed consistently low misclassification (3% of cycles with any at-risk day and a mean predicted pregnancy risk of 0.5%). ConclusionsBoth calendar-based and BBT-supported period-tracking applications not intended for contraception frequently misclassify biologically fertile days and should not be considered reliable tools for pregnancy prevention. Regulated digital contraceptives demonstrate substantially lower pregnancy risk. Short condensationPeriod-tracking apps frequently misclassify fertile days as safe, including days with high pregnancy risk. In a large real-world analysis, both calendar- and BBT-supported trackers showed substantial risk, unlike digital contraception methods regulated as a medical device.

PurposeGenetic diseases often present and are first diagnosed in the neonatal intensive care unit (NICU). Accurate identification of neonates with genetic diagnoses (GDs) in electronic health records (EHR) would enable a more complete understanding of their phenotypic spectrum, advancing care and personalized medicine. Prior research has used International Classification of Diseases (ICD) billing codes as proxies for GDs, though their accuracy for detecting confirmed GDs is uncertain. We evaluate the ICD codes for neonates with confirmed GDs and compare ICD billing code patterns between neonates with and without GD in two independent NICU cohorts. MethodsRetrospective analysis of patients admitted to the Boston Childrens Hospital (BCH) level IV NICU (1,344 neonates) and Nationwide Childrens Hospital (NCH)s neonatal network (33,315 neonates, mixed Level III/IV). For both cohorts, GDs captured by phecodes, aggregates of ICD codes, were compared with confirmed GDs. Two separate phenome-wide association studies (PheWAS) compared phecode patterns between neonates with GDs and those without, adjusting for sex, age at admission, gestational age, and NICU length of stay. ResultsGenetic phecodes were able to correctly identify 43.5% of neonates that received a GD in the BCH or NCH NICUs. Among 719 individuals with two or more genetic phecodes at BCH or NCH, 566 (78.72%) had a true GD. The BCH PheWAS analysis revealed a statistically significant positive association with atrioventricular septal defects and a negative association with bronchopulmonary dysplasia. The NCH pheWAS revealed 179 significantly associated phecodes, including many congenital anomalies. ConclusionThe use of ICD codes to identify NICU infants with GDs is neither sensitive nor accurate, though phecode analysis demonstrated stronger accuracy than sensitivity. Our data highlight clinical features of NICU infants more commonly seen in those that receive a GD (congenital heart defects) and those that are not (BPD). Our results can help to better predict and identify NICU neonates that receive a GD.

Since the cessation of real-time monitoring of COVID-19 hospitalizations in early 2024, the burden of and vaccine effectiveness (VE) against severe COVID-19 in the Netherlands was largely unknown. Recently, hospitalization data from 2024 were made available for the purpose of monitoring and evaluating the COVID-19 vaccination campaigns. These data were linked to the population registry, vaccination registry and healthcare use data (for classification into medical risk groups). We analyzed the number and incidence of COVID-19 hospitalizations in 2023 and 2024 by age and medical risk group. VE against hospitalisation of the autumn booster of 2023 (by time since vaccination, 25 September 2023 to 16 September 2024) and of the autumn booster of 2024 (16 September to 31 December 2024) were estimated by medical risk group among persons aged 60 years and older using Cox proportional hazards models with calendar time as underlying time scale and vaccination status as time-varying exposure. Models were adjusted for age, sex, region and household socio-economic status. From around age 60 onward, intermediate and high medical risk groups had a markedly higher incidence than younger age groups, increasing with age. Persons in the low medical risk group had a low incidence up to the age of 80. In 2024, incidence was lower than in 2023. For both autumn booster rounds, estimated VE against hospitalisation was moderate at 55-67% in the first 3 months post-vaccination. In the high medical risk group, 2023 VE decreased fast and was no longer significant at 6 months post-vaccination. For both years, estimates of the number of averted hospitalizations and number needed to vaccinate to prevent one hospitalization indicated that significant health benefit can be achieved by vaccinating the intermediate and high medical risk groups aged 60 years and older. Efforts to increase the moderate vaccine uptake among risk groups could potentially prevent a considerable disease- and healthcare burden. Highlights- In 2023 and 2024, incidence of COVID-19 hospitalization was highest among medical risk groups aged 60 years and older, despite vaccination campaigns. - Estimated VE against hospitalisation of the 2023 and 2024 autumn booster campaigns was moderate (55-67%) in the first year-quarter post-vaccination among persons aged 60 years and older. - Estimated VE of the 2023 autumn booster decreased over the year, and faster among persons with a medical risk condition. Data availability precluded estimates of 2024 VE beyond the first 3 months since the start of the campaign. - Despite lower and waning VE, the estimated number needed to vaccinate to prevent one COVID-19 hospitalization was much lower among intermediate and high medical risk groups compared with the low medical risk group.

Despite numerous reforms and initiatives within the healthcare system, Nigerias performance on universal health coverage (UHC) indicators remains sub-optimal. This study aims to empirically examines multidimensional access to healthcare and identifies the key determinants influencing levels of access among rural households in Nigeria. We utilize cross-sectional data from 625 rural households collected between June and October 2022. Multidimensional access to healthcare was measured using a 10-item instrument capturing participants psychological experiences of access. Data were analyzed using Confirmatory Factor Analysis (CFA) and an Instrumental Variable ordered probit (IV-Oprobit) model.Two items were excluded from the scale due to non-convergence and high residual correlations. The resulting eight-item scale demonstrated acceptable internal consistency (Cronbachs = 0.70). Among the four dimensions of access, availability recorded the lowest mean score, while geographical accessibility had the highest. Overall, only one in eight rural households achieved adequate access to healthcare, with the majority either vulnerable to or experiencing inadequate access. Monthly per capita expenditure (MPCE), household size, educational attainment, region of residence, facility operating hours, perceived quality of care, and waiting time are all significantly associated with the probability of reporting adequate, moderate, or inadequate access to healthcare. While expanding financial protection through broader health insurance coverage for rural populations remains critical, such efforts must be complemented by interventions that address persistent supply-side constraints to healthcare access. Key messagesO_LIAt 38, Nigeria has one of the lowest Universal Healthcare Coverage (UHC) index in sub-Saharan Africa suggesting under-performance in healthcare system. C_LIO_LIAn important but under-explored challenge in the pursuit of UHC particularly in LMIC countries is the conceptualization and measurement of healthcare access. C_LIO_LIFindings show that, overall access to healthcare remains inadequate with one out of eights households in rural Nigeria achieved adequate access. C_LIO_LIThe strong influence of consumption expenditure underscores the continued dominance of out-of-pocket (OOP) financing, emphasizing the need to expand financial protection through health insurance coverage. C_LIO_LIDistinguishing nominal from quality-adjusted access and embedding multidimensional access measures into routine health surveys can strengthen evidence-based planning and support targeted efforts to reduce rural health inequities. C_LI

Healthcare inequality remains a major challenge for health systems globally. While previous studies have examined inequalities in specific healthcare services or sub-domains of care, evidence on disparities in access across formal inpatient healthcare settings in Nigeria remains limited. This study examines income-related inequalities and inequities in access to inpatient healthcare among rural households in Nigeria. The study used cross-sectional data from 624 rural households collected in 2022 as part of a human capital research project commissioned by the African Economic Research Consortium (AERC). Information on demographic characteristics, household income, consumption expenditure, health conditions, region of residence, and access to inpatient care was analyzed. Income-related inequalities and need-adjusted inequities were assessed using the Concentration Index (CI) and the Horizontal Inequity (HI) index. Overall, 81.4%, 49.9%, and 18.4% of respondents reported access to inpatient care at public primary, secondary, and tertiary health facilities, respectively, while 32.7% accessed inpatient care at private facilities. Access to public primary and secondary inpatient care decreased with household wealth, whereas access to public tertiary and private inpatient care increased with wealth. Significant pro-poor inequalities and inequities were observed in access to public primary (CI = -0.1054; HI = -0.0374) and secondary (CI = -0.1063; HI = -0.0377) inpatient care. In contrast, access to tertiary (CI = 0.2382; HI = 0.3660) and private (CI = 0.1502; HI = 0.2180) inpatient care exhibited significant pro-rich inequalities and inequities. Decomposition analysis indicated that non-need factors--particularly household economic status and region of residence--were the largest contributors to inequalities in access across all inpatient care types. ConclusionInequalities in access to inpatient healthcare were driven mainly by economic status and region of residence.