Tag: statistics

Health Econ Rev. 2026 Jun 17. doi: 10.1186/s13561-026-00808-x. Online ahead of print.

ABSTRACT

BACKGROUND: The COVID-19 pandemic constituted a public health emergency in Thailand from March 2020 to October 2022, testing the resilience of the health financing system. This study establishes an analytical framework to examine Thailand’s public health financing arrangements and their subsequent impacts on public hospital financial reserves during this crisis.

METHODS: This mixed-methods study developed an analytical framework to examine Thailand’s public health financing response. The study analyzed COVID-19 public health expenditure data (Fiscal Years (FY) 2020-2022) and financial data from 866 Ministry of Public Health hospitals (FY 2015-2022) using descriptive statistics and trend analysis. These quantitative findings were integrated with a thematic analysis of 21 key informant interviews.

RESULTS: Thailand enhanced health financing resilience through adaptive revenue mobilization and flexible resource allocation. Between FY 2020 and 2022, the government expanded fiscal space by mobilizing approximately US$13.78 billion via the Emergency Loan Decrees, Central Budget, and Social Security Fund. Universal Health Coverage (UHC) mechanisms expanded service coverage and expedited provider reimbursement. During delayed loan disbursements, public hospitals used internal financial reserves to bridge funding gaps and maintain service continuity. Consequently, net hospital reserves increased substantially by the pandemic’s end compared to pre-pandemic baselines.

CONCLUSIONS: Thailand strategically leveraged its UHC system and mobilized emergency and pre-existing public funds to secure fiscal space and maintain system resilience. However, temporary funding influxes may mask localized resource strains on hospital financial reserves. To enhance future resilience, Thailand should establish a dedicated health emergency reserve fund, streamline extra-budgetary mechanisms, and adopt flexible procurement regulations.

PMID:42307858 | DOI:10.1186/s13561-026-00808-x

Bull Math Biol. 2026 Jun 17;88(7):119. doi: 10.1007/s11538-026-01684-6.

ABSTRACT

Extrusomes are extrusive organelles found in a variety of organisms, including cnidarians, dinoflagellates, and protists. These organelles typically contain a fluid-filled capsule that houses a structure, such as a coiled tubule or barb, which is rapidly ejected toward a target. Although the ejection mechanisms and morphology vary widely, a common feature is the rapid acceleration of the ejected structure through a fluid. In this paper, we develop an idealized model to simulate the collapse of an extrusome capsule, which enables the ejection of a barb or other internal structure. Specifically, we used the immersed boundary method to numerically simulate the collapse of a simplified capsule, modeled as the two sides of an elliptical shell with a flat plate along the bottom. As the capsule collapses, the elliptical sides straighten, ejecting both the internal fluid and the enclosed structure towards either free fluid or a flexible target. We investigate the effects of key model parameters, such as the size of the capsule opening. We also explore the role of the Reynolds number (Re), to consider the fluid dynamics across a range of regimes, from inertial-dominated flows relevant to some extrusome firings to viscous-dominated flows characteristic of cellular-scale processes. Our results demonstrate that decreasing the capsule opening gap size leads to increased firing velocity and shorter ejection times. Similarly, increasing the capsule’s minor axis reduces the time it takes the barb to reach the target as a larger volume of fluid is moved. The relationship between Re and the time to contact is nonmonotonic, but higher Re values generally result in faster target contact, even at longer initial distances. Furthermore, we observe that higher Re values enhance the robustness of the target contact in different configurations. Finally, we quantify how the stiffness of the barb affects its ability to reach the target. We find that the large deformations of the flexible barbs slow their trajectories and that the stiffer barbs hit their targets sooner. These findings provide a foundational understanding of the biomechanics and fluid dynamics of extrusome ejection through the collapse of a capsule. The insights gained may contribute to the development of microinjectors in drug delivery, where precise and rapid mechanical movements are critical.

PMID:42307851 | DOI:10.1007/s11538-026-01684-6

Environ Monit Assess. 2026 Jun 17;198(7):735. doi: 10.1007/s10661-026-15593-7.

ABSTRACT

This study presents a comprehensive spatiotemporal assessment of key ambient air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, NH_3, O₃, and CO) across seven urban and semi-urban districts of the Uttar Pradesh National Capital Region (UP-NCR), India, during 2019-2023. Despite an overall decline of approximately 23% in particulate matter concentrations over the study period, annual mean PM_2.5 (88 ± 15 µg/m³) and PM₁₀ (185 ± 28 µg/m³) levels consistently exceeded the National Ambient Air Quality Standards. Land use and land cover (LULC) analysis revealed a 7.06% expansion in built-up areas, reflecting rapid urbanization and its influence on local emission patterns. This urban growth was associated with persistent NO₂ enrichment, particularly in Noida, where concentrations increased by 22%. Pronounced seasonal variability was observed, with PM_2.5 concentrations peaking during the post-monsoon season particularly in Noida (200 ± 102 µg/m³) and Ghaziabad (178 ± 99 µg/m³), identified as the regional pollution hotspot. Meteorological analysis revealed strong seasonal influences on pollutant concentrations. Relative humidity exhibited positive correlations with particulate matter during winter (r ≈ 0.44-0.59), reflecting hygroscopic growth and stagnant atmospheric conditions, but strong negative correlations during the monsoon (r ≈ -0.72 to -0.95) due to efficient wet scavenging. Bivariate polar plot analysis identified stagnation-driven pollutant accumulation in densely urbanized districts and wind-induced resuspension of agricultural and crustal dust in peripheral regions. HYSPLIT backward-trajectory clustering further demonstrated substantial contributions from long-range transport originating from western and northwestern source regions during pollution episodes. These findings highlight pronounced spatial heterogeneity and seasonal dynamics in air quality, emphasizing the need for region-specific, airshed-based mitigation strategies across rapidly urbanizing peri-urban corridors.

PMID:42307838 | DOI:10.1007/s10661-026-15593-7

J Pharmacokinet Pharmacodyn. 2026 Jun 17;53(4):31. doi: 10.1007/s10928-026-10047-6.

ABSTRACT

BACKGROUND: Reliable population pharmacokinetic (PopPK) estimation is often compromised by outliers under Gaussian error models. While post hoc filtering using conditional weighted residuals (CWRES) is common, this approach is often insensitive due to model “masking” from variance inflation.

METHODS: We implemented a one-compartment model in Monolix using a custom likelihood workaround to benchmark four distributions: Normal, Laplace, Generalized Error Distribution (GED), and Student’s t. We assessed CWRES sensitivity under extreme contamination and compared estimation performance using theoretical tail-behavior analysis, controlled simulation studies spanning multiple contamination severities, and a real-world caffeine PK case study with influential terminal-phase deviations.

RESULTS: Simulations revealed that CWRES-based diagnostics are unreliable; extreme outliers frequently produced |CWRES| < 6 because the Normal model inflated residual variance, masking the contamination. Exponential-tail models (Laplace, GED) improved robustness for moderate outliers but failed under extreme deviations due to insufficiently heavy tails. Conversely, the Student’s t model, utilizing power-law tail behavior, maintained stable and minimally biased structural parameter estimates across the contamination settings examined. These patterns were confirmed in the caffeine case study.

CONCLUSIONS: Reliance on CWRES-driven residual screening alone is methodologically fragile. Among the models evaluated, exponential-tail distributions are insufficient for extreme outliers, whereas the Student’s t distribution provided the most consistent stability across the contamination settings examined here and showed the most robust overall performance among the residual-error models evaluated when influential outliers were present.

PMID:42307836 | DOI:10.1007/s10928-026-10047-6

Acta Neurochir (Wien). 2026 Jun 17. doi: 10.1007/s00701-026-06859-7. Online ahead of print.

ABSTRACT

BACKGROUND: The Coalition (Globus Medical) hybrid PEEK-titanium cage has been widely utilized in our practice for Anterior Cervical Discectomy and Fusion (ACDF) over a 5-year period. A preliminary review of all the cases that we performed in these five years show to us an unexpectedly high rate of postoperative cage subsidence with the Coalition (Globus Medical) stand-alone cage. This prompted a formal investigation, the purpose of this study was, therefore, to systematically determine the true rate of subsidence for the Coalition cage in our cohort and to identify the independent risk factors that could explain this finding.

METHODS: We conducted a retrospective analysis of 70 consecutive patients who underwent ACDF with the Coalition cage between 2018 and 2023. Data on demographic, clinical, and surgical variables were collected. The primary outcome was cage subsidence (≥ 3 mm) assessed on lateral radiographs at a mean follow-up of 28.8 months (range 12-48). Independent predictors were identified through a multivariable logistic regression model constructed using the purposeful selection of covariates strategy, a multi-step iterative process that accounts for both statistical significance and confounding effects.

RESULTS: The overall patient-based subsidence rate was 38.6% (27 of 70 patients) at a mean radiographic follow-up of 28.8 months. Interrater reliability for subsidence assessment was substantial (Kappa = 0.759). In the multivariable analysis, preoperative diagnosis of radiculopathy was identified as the only independent predictor of subsidence, with an Adjusted Odds Ratio of 3.51 (95% CI: 1.13-10.91, p = 0.029). Contrary to initial assumptions, multi-level surgery (p = 0.441), smoking status (p = 0.615), and implant dimensions were not significant predictors in this cohort.

CONCLUSION: The Coalition cage demonstrated a high rate of subsidence in this series. A preoperative diagnosis of radiculopathy was the primary independent risk factor for this outcome, rather than multi-level fusion or specific implant characteristics. These findings suggest that the biomechanical requirements of disc height restoration in patients with radiculopathy may predispose them to higher subsidence rates when utilizing this specific standalone integrated fixation device.

PMID:42307831 | DOI:10.1007/s00701-026-06859-7

Oral Health Prev Dent. 2026 Jun 17;24:405-415. doi: 10.3290/j.ohpd.c_2714.

ABSTRACT

PURPOSE: To explore the relationship between dental caries and non-alcoholic fatty liver disease (NAFLD) and its advanced stage of liver fibrosis, and to confirm causality by employing a bidirectional two-sample Mendelian Randomization (MR) analysis to confirm causality.

MATERIALS AND METHODS: 6650 participants of the National Health and Nutrition Examination Survey (NHANES), 2017-2020 were included. Two multivariable logistic regression models were used to evaluate the relationship between untreated dental caries (UDC) and liver conditions of NAFLD and fibrosis, with adjustments for demographics, lifestyle, and medical history. Furthermore, two-sample MR was performed with caries as exposure and NAFLD with NAFLD-related conditions as outcome, and vice versa for bidirectional causality validation.

RESULTS: In observational research, UDC was notably associated with NAFLD (OR [odds ratio]: 1.40, 95% CI [confidence interval]: 1.06-1.86) and significant fibrosis (SF) (OR: 1.29, 95% CI: 1.03-1.62). NAFLD and SF were statistically significantly associated with UDC (OR: 1.40, 95% CI: 1.08-1.83; OR: 1.62, 95% CI: 1.26-2.08). In the MR analysis, caries posed a statistically non-significant risk for liver conditions. In contrast, liver conditions non-significantly protected against caries (NAFLD: OR: 0.99, 95% CI: 0.98-1.01; fibrosis: OR: 0.99, 95% CI: 0.99-1.00; cirrhosis: OR: 0.99, 95% CI: 0.99-1.00; fibrosis/cirrhosis: OR: 1.00, 95% CI: 0.98-1.02).

CONCLUSION: Observational studies suggested a statistically significant association between UDC and liver conditions of NAFLD and fibrosis. However, MR suggested a statistically non-significant causal relationship between caries and liver conditions; in contrast, liver conditions had a non-significant protective effect on caries.

PMID:42306875 | DOI:10.3290/j.ohpd.c_2714

Food Funct. 2026 Jun 8. doi: 10.1039/d6fo00295a. Online ahead of print.

ABSTRACT

Synbiotic and functional food formulations modulate gut microbiota, SCFA production, immune signalling and metabolic pathways, yet current development pipelines remain largely empirical and constrained by nonlinear trade-offs among probiotic viability, prebiotic functionality and sensory acceptance. Artificial Intelligence (AI) and machine learning (ML) approaches offer data-driven strategies to support formulation, multi-objective optimization and functional assessment. This review systematically identified and critically synthesized literature published between 2020 and 2025 across five thematic domains: (i) formulation and ingredient selection; (ii) viability and shelf-life modelling; (iii) functional and antioxidant bioactivity assessment; (iv) sensory and consumer prediction; and (v) personalization and precision nutrition. Studies were identified through database searches and screened for relevance to synbiotics, functional foods, microbiome modulation and nutrition outcomes, following PRISMA 2020 guidelines. Current evidence indicates that AI can assist ingredient pairing, viability forecasting, sensory modelling and functional property prediction, often complementing conventional statistical tools such as Response Surface Methodology in multivariate design spaces. However, most implementations remain computational or pilot-scale, with minimal integration of microbiome-informed personalization, clinical endpoints or adherence outcomes. Major translational gaps include data heterogeneity, model interpretability, regulatory substantiation and scarcity of longitudinal evidence. AI should therefore be considered a complementary decision-support tool that can accelerate hypothesis generation and formulation refinement rather than substitute mechanistic validation or human trials. Bridging computational modelling with microbiome science and nutritional evidence may enable precision synbiotic strategies and next-generation functional food innovation.

PMID:42306833 | DOI:10.1039/d6fo00295a

Health Promot J Austr. 2026 Jul;37(3):e70207. doi: 10.1002/hpja.70207.

ABSTRACT

ISSUE ADDRESSED: For people in rural and remote areas, government-funded travel subsidy schemes provide vital financial assistance and equitable access to specialist healthcare in city centres. However, few studies have examined users’ experiences of these schemes.

METHODS: Adults travelling for healthcare in Queensland, Australia, completed an online survey capturing their most recent experience applying for the Patient Travel Subsidy Scheme (PTSS). Participants’ responses were analysed using descriptive statistics and thematic analysis.

RESULTS: From 69 respondents (aged 29-80 years, 60% female, 88% most recent application for cancer-related care), 57% agreed information about the scheme was easy to access, although only 39% found the initial registration process easy. Most indicated that local hospital staff and PTSS officers were knowledgeable and helpful (65%-70%). Less agreed that staff were available to assist (48%) or that processes were well-coordinated across hospitals (42%). Of those who sought reimbursement for travel costs (75%), almost two-thirds (63%) were out-of-pocket post-reimbursement (mean = AU$725; range = AU$20-10 000). Delayed reimbursement was relatively common (60%) and contributed to financial hardship (36%). For some (13%), challenges accessing the scheme impacted treatment decisions. User feedback included improved visibility of online application and reimbursement status, and fast-tracking of high-risk, urgent and ongoing cases.

CONCLUSIONS: While information about the scheme and interactions with frontline staff were viewed positively by most, several system-level challenges remain. SO WHAT?: Substantial out-of-pocket costs and reimbursement delays contribute to financial hardship and can affect treatment decisions. Increased subsidy reflecting actual travel costs, timely reimbursement, fast-tracking, and greater application assistance and coordination would improve user experiences.

PMID:42306832 | DOI:10.1002/hpja.70207

Biometrics. 2026 Jun 17:ujag113. doi: 10.1093/biomtc/ujag113. Online ahead of print.

ABSTRACT

This discussion provides commentary on the paper “INTACT: A method for integration of longitudinal physical activity data from multiple sources” by Jingru Zhang, Erjia Cui, Hongzhe Li, and Haochang Shou. The authors introduce an FPCA-based approach for integrating information from multiple sources with longitudinal measurements. We focus on the paper’s covariance-eigensystem assumptions and discuss how covariance alignment facilitates knowledge integration and transfer in functional and longitudinal settings.

PMID:42306831 | DOI:10.1093/biomtc/ujag113

Geohealth. 2026 Jun 15;10(6):e2026GH001854. doi: 10.1029/2026GH001854. eCollection 2026 Jun.

ABSTRACT

Due to legacy leaded products, soil Pb is generally higher in older urban centers triggering substantial implications for environmental equity. By integrating a gridded soil Pb analysis of about 150 samples each in two historically industrial cities (Hartford, CT and Springfield, MA) with block-level census data, we tested the hypotheses that (a) high soil Pb areas correlate spatially with older housing, (b) historical processes of discrimination have caused long-lasting environmental injustices with respect to Pb exposure, and (c) multiple social, demographic and geographic factors intersect in determining areas in need of targeted remediation efforts. Our data and geospatial analysis showed higher Pb concentrations in Hartford than Springfield and confirmed the prevalence of elevated (>200 ppm) Pb in soils closer to older homes in both cities. Using a decision tree statistical partition, we show that exposure to elevated soil Pb was most prevalent in communities with children population higher than the city median, who live in multi-family housing. In Springfield, ethnicity was a significant factor in exposure as census blocks populated by non-Hispanic Whites were least likely to contain lead in soils above 200 ppm. Our analysis highlights that historical discriminatory practices, including redlining, have anchored environmental injustices in the studied communities, creating an invisible legacy challenge recorded in the land and carried across decades. The use of decision trees in the context of soil lead contamination provides a new method to help identify vulnerabilities of marginalized populations, providing quantitative tools to advocate for targeted mitigation and remediation.

PMID:42306802 | PMC:PMC13267425 | DOI:10.1029/2026GH001854