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Estimating rates of change to interpret quantitative wastewater surveillance of disease trends

SCIENCE OF THE TOTAL ENVIRONMENT 2024年 951卷 175687页

作者： Holcomb, David A. Christensen, Ariel Hoffman, Kelly Lee, Allison Blackwood, A. Denene Clerkin, Thomas Gallard-Gongora, Javier Harris, Angela Kotlarz, Nadine Mitasova, Helena Reckling, Stacie de los Reyes III, Francis L. Stewart, Jill R. Guidry, Virginia T. Noble, Rachel T. Serre, Marc L. Garcia, Tanya P. Engel, Lawrence S. Univ North Carolina Chapel Hill Gillings Sch Global Publ Hlth Dept Epidemiol Chapel Hill NC USA Univ North Carolina Chapel Hill Gillings Sch Global Publ Hlth Dept Environm Sci & Engn Chapel Hill NC USA North Carolina Dept Hlth & Human Serv Div Publ Hlth Occupat & Environm Epidemiol Branch Raleigh NC USA Univ North Carolina Chapel Hill Inst Marine Sci Dept Earth Marine & Environm Sci Morehead City NC USA North Carolina State Univ Dept Civil Construct & Environm Engn Raleigh NC USA North Carolina State Univ Dept Biol Sci Raleigh NC USA North Carolina State Univ Ctr Geospatial Analyt Raleigh NC USA North Carolina State Univ Dept Marine Earth & Atmospher Sci Raleigh NC USA Univ North Carolina Chapel Hill Gillings Sch Global Publ Hlth Dept Biostat Chapel Hill NC USA

Background: Wastewater monitoring data can be used to estimate disease trends to inform public health responses. One commonly estimated metric is the rate of change in pathogen quantity, which typically correlates with clinical surveillance in retrospective analyses. However, the accuracy of rate of change estimation approaches has not previously been evaluated. Objectives: We assessed the performance of approaches for estimating rates of change in wastewater pathogen loads by generating synthetic wastewater time series data for which rates of change were known. Each approach was also evaluated on real-world data. Methods: Smooth trends and their first derivatives were jointly sampled from Gaussian processes (GP) and independent errors were added to generate synthetic viral load measurements;the range hyperparameter and error variance were varied to produce nine simulation scenarios representing different potential disease patterns. The directions and magnitudes of the rate of change estimates from four estimation approaches (two established and two developed in this work) were compared to the GP first derivative to evaluate classification and quantitative accuracy. Each approach was also implemented for public SARS-CoV-2 wastewater monitoring data collected January 2021-May 2023 at 25 sites in North Carolina, USA. Results: All four approaches inconsistently identified the correct direction of the trend given by the sign of the GP first derivative. Across all nine simulated disease patterns, between a quarter and a half of all estimates indicated the wrong trend direction, regardless of estimation approach. The proportion of trends classified as plateaus (statistically indistinguishable from zero) for the North Carolina SARS-CoV-2 data varied considerably by estimation method but not by site. Discussion: Our results suggest that wastewater measurements alone might not provide sufficient data to reliably track disease trends in real-time. Instead, wastewater viral lo

关键词： Wastewater-based epidemiology Gaussian process derivatives Simulation study generalized additive model SARS-CoV-2 Time series analysis

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Differentially private and explainable boosting machine with enhanced utility

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NEUROCOMPUTING 2024年 607卷

作者： Baek, Incheol Chung, Yon Dohn Korea Univ Dept Comp Sci & Engn Seoul 02481 South Korea

In this paper, we introduce DP-EBM*, an enhanced utility version of the Differentially Private ExplainableBoosting Machine (DP-EBM). DP-EBM* offers predictions for both classification and regression tasks, providinginherent explanations for its predictions while ensuring the protection of sensitive individual information viaDifferential Privacy. DP-EBM* has two major improvements over DP-EBM. Firstly, we develop an error measureto assess the efficiency of using privacy budget, a crucial factor to accuracy, and optimize this ***, we propose a feature pruning method, which eliminates less important features during the trainingprocess. Our experimental results demonstrate that DP-EBM* outperforms the state-of-the-art differentiallyprivate explainable models.

关键词： Differential privacy Data privacy generalized additive model Explainable AI

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A Flexible Approach to Age Dependence in Organizational Mortality: Comparing the Life Duration for Cooperative and Non-Cooperative Enterprises Using a Bayesian generalized additive Discrete Time Survival model

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JOURNAL OF QUANTITATIVE ECONOMICS 2019年第4期17卷 829-855页

作者： Rousseliere, Damien INRA AGROCAMPUS OUEST SMART LERECO F-49045 Angers France

This paper proposes a new estimation model to capture the complex effect of age on organization survival. Testing various theoretical propositions on organizational mortality, we study the survival of French agricultural cooperatives in comparison with other firms with which they compete. The relationship between age and mortality in organizations is analyzed using a Bayesian generalized discrete-time semi-parametric hazard model incorporating unobserved heterogeneity, isolating the various effects of time and identifying within-effects and between-effects of the time-varying covariates. This analysis emphasizes the specificity of the temporal dynamics of cooperatives in relation to their special role in agriculture.

关键词： Bayesian estimation Bayesian model selection Cooperatives Hybrid model generalized additive model Survival analysis C11 C41 Q13 L25

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Rescue intracytoplasmic sperm injection improved cumulative live birth rate for cycles with second polar body extrusion rate <50% in young women: generalized addictive model

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FERTILITY AND STERILITY 2025年第3期123卷 415-427页

作者： Chen, Xiaolei Wang, Yanan Yang, Chaoyan Li, Cheng Yin, Changjian Zhao, Maoning Wu, Keliang Zho, Han Shandong Univ Inst Women Children & Reprod Hlth Jinan 250012 Shandong Peoples R China Shandong Univ State Key Lab Reprod Med & Offspring Hlth Jinan Shandong Peoples R China Shandong Univ Natl Res Ctr Assisted Reprod Technol & Reprod Gene Jinan Shandong Peoples R China Shandong Univ Minist Educ Key Lab Reprod Endocrinol Jinan Shandong Peoples R China Shandong Technol Innovat Ctr Reprod Hlth Jinan Shandong Peoples R China Shandong Prov Clin Res Ctr Reprod Hlth Jinan Shandong Peoples R China Shandong First Med Univ Shandong Prov Hosp Shandong Key Lab ofReproduct Med and Jinan Shandong Peoples R China Chinese Acad Med Sci 2021RU001 Res Unit Gametogenesis & Hlth ART Offspring Jinan Shandong Peoples R China

Objective: To determine the indications for early rescue intracytoplasmic sperm injection (ICSI) application. Design: A retrospective cohort study. Subjects: The study included 19,808 patients who underwent conventional in vitro fertilization (IVF) or rescue ICSI for their first cycles between February 2017 and December 2021. Exposure: Rescue ICSI cycles constituted the study group, where oocytes that had not extruded the second polar body 4-6 hours after insemination were rescued by ICSI. The control group consisted of conventional IVF cycles with no interventions to rescue oocytes without the second polar body. generalized additive models were constructed to describe the relationship between the second polar body extrusion rate and cumulative live birth rate in conventional IVF and rescue ICSI cycles, respectively. The cutoff value of the second polar body extrusion rate guiding rescue ICSI application was determined from the intersection point of generalized additive models. Maternal age range applicable to rescue ICSI was further analyzed using the same method. Clinical outcomes were compared between conventional IVF and rescue ICSI cycles across different second polar body extrusion rate and maternal age subgroups. Main Outcome Measures: The second polar body extrusion rate and maternal age range for rescue ICSI application, normal fertilization rate, and cumulative live birth rate. Results: generalized additive models showed that the cutoff value for the second polar body extrusion rate about rescue ICSI application was 50%. When the rate <50%, normal fertilization rate and cumulative live birth rate (63.7% vs. 46.1%;odds ratio, 1.609;95% confidence interval, 1.276-2.030) were significantly higher in rescue ICSI cycles than conventional IVF cycles. When the rate >= 50%, rescue ICSI cycles had similar normal fertilization rate and cumulative live birth rate compared with conventional IVF cycles. Further analysis on maternal age in cycles with second polar body

关键词： Early rescue ICSI second polar body extrusion rate age generalized additive model

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Estimating and characterizing spatiotemporal distributions of elemental PM2.5 using an ensemble machine learning approach in Taiwan

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ATMOSPHERIC POLLUTION RESEARCH 2025年第5期16卷

作者： Huang, Chun-Sheng Lo, Kang Wu, Yee-Lin Wang, Fu-Cheng Shiu, Yi-Shiang Chen, Chu-Chih Lin, Yuan-Chien Kuo, Cheng-Pin Liao, Ho-Tang Lin, Tang-Huang Wu, Chang-Fu Natl Taiwan Univ Inst Environm & Occupat Hlth Sci Coll Publ Hlth Taipei Taiwan Natl Cheng Kung Univ Coll Engn Dept Environm Engn Tainan Taiwan Natl Cent Univ Ctr Space & Remote Sensing Res Taoyuan City Taiwan Feng Chia Univ Coll Construct & Dev Dept Urban Planning & Spatial Informat Taichung Taiwan Natl Hlth Res Inst Inst Populat Hlth Sci Div Biostat & Bioinformat Zhunan Taiwan Natl Cent Univ Coll Engn Dept Civil Engn Taoyuan City Taiwan Ind Technol Res Inst Green Energy & Environm Res Labs Zhudong Taiwan Natl Hlth Res Inst Natl Inst Environm Hlth Sci Zhunan Taiwan Natl Taiwan Univ Coll Publ Hlth Dept Publ Hlth Taipei Taiwan

This paper presents an ensemble machine learning approach that combines generalized additive model (GAM) with eXtreme Gradient Boosting (XGBoost) to estimate and characterize the spatiotemporal distributions of elemental PM2.5 in Taiwan. Daily field measurements of 12 PM2.5 elemental components were collected from 28 air quality monitoring stations between June 2021 and May 2022. Time-variant meteorological factors and timeinvariant land-use patterns were incorporated as predictors. Results showed that the ensemble model effectively captured spatial variations in elemental PM2.5 levels, as demonstrated by the identification of numerous timeinvariant features using Shapley additive explanations analysis. A comparative analysis was conducted with a model using only XGBoost, which outperformed the ensemble model with higher cross-validated R2 and lower prediction errors. While the XGBoost-only model is recommended for exposure prediction, the ensemble model offers superior interpretability for investigating air pollution sources and aids in formulating air quality strategies from a spatial perspective.

关键词： eXtreme gradient boosting generalized additive model Particle composition Air pollution

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Flexible nonlinear modeling reveals age-related differences in resting-state functional brain connectivity in autistic males from childhood to mid-adulthood

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MOLECULAR AUTISM 2025年第1期16卷 1-14页

作者： Feldman, Daniel Prigge, Molly Alexander, Andrew Zielinski, Brandon Lainhart, Janet King, Jace Univ Utah Dept Biomed Engn Salt Lake City UT 84112 USA Univ Utah Dept Radiol & Imaging Sci Salt Lake City UT 84112 USA Univ Wisconsin Waisman Ctr Madison WI USA Univ Wisconsin Dept Psychiat Madison WI 53706 USA Univ Wisconsin Dept Med Phys Madison WI 53706 USA Univ Florida Dept Pediat Neurol & Neurosci Gainesville FL 32611 USA

Background Divergent age-related functional brain connectivity in autism spectrum disorder (ASD) has been observed using resting-state fMRI, although the specific findings are inconsistent across studies. Common statistical regression approaches that fit identical models across functional brain networks may contribute to these inconsistencies. Relationships among functional networks have been reported to follow unique nonlinear developmental trajectories, suggesting the need for flexible modeling. Here we apply generalized additive models (GAMs) to flexibly adapt to distinct network trajectories and simultaneously describe divergent age-related changes from childhood into mid-adulthood in ASD. Methods 1107 males, aged 5-40, from the ABIDE I & II cross-sectional datasets were analyzed. Functional connectivity was extracted using a network-based template. Connectivity values were harmonized using COMBAT-GAM. Connectivity-age relationships were assessed with thin-plate spline GAMs. Post-hoc analyses defined the age-ranges of divergent aging in ASD. Results Typically developing (TD) and ASD groups shared 15 brain connections that significantly changed with age (FDR-corrected p < 0.05). Network connectivity exhibited diverse nonlinear age-related trajectories across the functional connectome. Comparing ASD and TD groups, default mode to central executive between-network connectivity followed similar nonlinear paths with no group differences. Contrarily, the ASD group had chronic hypoconnectivity throughout default mode-ventral attentional (salience) and default mode-somatomotor aging trajectories. Within-network somatomotor connectivity was similar between groups in childhood but diverged in adolescence with the ASD group showing decreased within-network connectivity. Network connectivity between the somatomotor network and various other functional networks had fully disrupted age-related pathways in ASD compared to TD, displaying significantly different model curvatures

关键词： Autism fMRI Functional connectivity Age-related Cross-sectional generalized additive model

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CPUE Standardization and Socioeconomic Influences on Red Snow Crab (Chionoecetes japonicus) Fisheries in Korean Waters

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JOURNAL OF MARINE SCIENCE AND ENGINEERING 2025年第4期13卷 711-711页

作者： Kim, Moo-Jin Kang, Heejoong Yoon, Sang Chul Choi, Ji-Hoon Kim, Hyun Woo Natl Inst Fisheries Sci Coastal Water Fisheries Resources Res Div Busan 46083 South Korea

The standardization of catch per unit effort (CPUE) is essential for accurate stock assessment in fisheries management. This study focuses on CPUE standardization for red snow crab (Chionoecetes japonicus) in South Korea, incorporating both spatiotemporal and socioeconomic factors into a generalized additive model (GAM) framework. Using fishery-dependent data from 2009 to 2023, we analyzed the influence of variables such as the proportion of live catch, oil prices, global export prices, and the COVID-19 pandemic on CPUE trends. To quantify the contribution of each variable, a stepwise exclusion analysis was conducted. The results show that excluding socioeconomic variables leads to a more stable CPUE trajectory, indicating that nominal CPUE fluctuations are partially driven by economic conditions rather than changes in biological abundance. These findings highlight the importance of accounting for external drivers, particularly socioeconomic factors when standardizing CPUE. By doing so, the year effect extracted from the model can more accurately reflect relative stock abundance. The approach presented here offers a practical solution for improving CPUE estimates in data-limited fisheries and supports adaptive, evidence-based fisheries management.

关键词： red snow crab catch per unit effort standardization socioeconomic generalized additive model

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Drivers of wildfire spatial expansion: modeling insights from semi-arid oak forests of W Iran

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ADVANCES IN SPACE RESEARCH 2025年第10期75卷 7184-7194页

作者： Sadeghi, Akram Nadoushan, Mozhgan Ahmadi Sani, Naser Ahmadi Islamic Azad Univ Dept Environm Sci Isfahan Khorasgan Branch Esfahan Iran Islamic Azad Univ Waste & Wastewater Res Ctr Dept Environm Sci Isfahan Khorasgan Branch Esfahan Iran Islamic Azad Univ Fac Agr & Nat Resources Mahabad Branch Mahabad Iran

Wildfires are becoming increasingly recurrent in Iran, threatening vulnerable ecosystems, particularly the non-fire-adapted semi-arid oak forests in the western regions. This study investigates the environmental drivers influencing wildfire size in these forests, focusing on the years 2018-2020. To analyze the environmental drivers, a circular buffer of 314 ha was applied around each wildfire location, enabling the collection of predictive variables through remote sensing and in-situ measurements across three categories: topography, climate, and vegetation. Employing a non-linear generalized additive model (R2 = 0.822, explained deviance = 75.9 %), Land Surface Temperature (LST) emerged as the most significant factor in determining wildfire size, exhibiting a robust correlation with larger and faster-spreading fires. Furthermore, steep slopes and high-speed winds were associated with larger wildfires, enabling rapid fire spread and upslope progression. Wildfires were largest in areas with spatially consistent vegetation cover and peaked in April and May due to warmer temperatures and lower humidity. These findings underscore the need for the development of more proactive, adaptive, and effective strategies, ultimately reducing the toll of the destructive impacts on the integrity of these forests. (c) 2025 COSPAR. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

关键词： generalized additive model Land Surface Temperature Wildfire size Oak forest

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Spatial differentiation of the leaf area index in forests in ecological transition zones and its environmental response

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EUROPEAN JOURNAL OF FOREST RESEARCH 2024年第5期143卷 1307-1320页

作者： Li, Geyang Zhao, Chengzhang Liu, Dingyue Ling, Lei Huang, Chenglu Zhang, Peixian Wang, Suhong Wu, Xianshi Northwest Normal Univ Coll Geog & Environm Sci Gansu Prov Wetland Resources Protect & Ind Dev Eng Lanzhou 730100 Gansu Peoples R China Xinglongshan Forest Ecosyst Natl Positioning Obser Lanzhou 730100 Peoples R China

The leaf area index (LAI) is a crucial vegetation parameter that characterizes leaf sparsity and canopy structure, and the study of the spatial distribution pattern of the forest LAI and its environmental response can help to reveal the adaptive capacity of forest vegetation to climate change in semiarid areas. In this paper, a remote sensing inversion model of the LAI, which pertains to the forest ecosystem of Xinglong Mountain in the transition zone between the Qinghai-Tibet Plateau and Loess Plateau, was established by combining an optical instrumentation method, a remote sensing inversion method, and a generalized additive model (GAM). The results showed that (1) the Meris terrestrial chlorophyll index (MTCI) linear regression model provided the greatest explanatory power for the LAI in the Xinglong Mountain forest, with R-2= 0.88 and RMSE = 0.32. (2) The LAI was influenced mainly by the altitude, slope, profile curvature, aspect, planform curvature, temperature, precipitation, and evapotranspiration. According to the single-factor GAM, altitude (R-2 = 0.43) explained most of the total variation in the LAI, followed by precipitation (R-2= 0.36). According to the multifactor GAM, the above influencing factors could explain 84.2% of the total variation in the LAI, which was significant (P < 0.001). (3) Interaction analysis revealed that the LAI was significantly influenced by the interaction between topographic and meteorological factors (P < 0.001). It was revealed that the topography of Xinglong Mountain is fragmented, the vertical band spectrum of vegetation is notable, and the forest LAI exhibits high spatial heterogeneity under the interaction between topographic and meteorological factors, reflecting the environmental response mechanism of vegetation growth in forest ecosystems in ecological transition zones.

关键词： Leaf area index Spatial heterogeneity Remote sensing inversion generalized additive model Environmental response Transition zone between the Qinghai-Tibet plateau and Loess plateau

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Association Between Systolic Blood Pressure and in-Hospital Mortality Among Congestive Heart Failure Patients with Chronic Obstructive Pulmonary Disease in the Intensive Care Unit: A Retrospective Cohort Study

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INTERNATIONAL JOURNAL OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE 2024年 19卷 2023-2034页

作者： Zhang, Kai Han, Yu Gao, Yu Xuan Gu, Fang Ming Gu, Zhao Xuan Liang, Jia Ying Zhao, Jia Yu Zhang, Tianqi Gao, Min Cai, Tian Yi Hu, Rui Liu, Tian Zhou Li, Bo Zhang, Yixin Second Hosp Jilin Univ Cardiovasc Surg Dept Changchun Jilin Peoples R China First Hosp Jilin Univ Dept Ophthalmol Changchun Jilin Peoples R China First Hosp Jilin Univ Dept Canc Ctr Changchun Jilin Peoples R China Second Hosp Jilin Univ Dept Gastrointestinal Surg Changchun Jilin Peoples R China

Background: There has been a growing body of research focusing on patients with Congestive Heart Failure (CHF) and chronic obstructive pulmonary disease (COPD) admitted to the intensive care unit (ICU). However, the optimal blood pressure (BP) level for such patients remains insufficiently explored. This study aimed to investigate the associations between systolic blood pressure (SBP) and in-hospital mortality among ICU patients with both CHF and COPD. Methods: This retrospective cohort study enrolled 6309 patients from the Medical Information Mart for Intensive Care IV (MIMIC- IV) database. SBP was examined as both a continuous and categorical variable, with the primary outcome being in-hospital mortality. The investigation involved multivariable logistic regression, restricted cubic spline regression, and subgroup analysis to determine the relationship between SBP and mortality. Results: The cohort consisted of 6309 patients with concurrent CHF and COPD (3246 females and 3063 males), with an average age of 73.0 +/- 12.5 years. The multivariate analysis revealed an inverse association between SBP and in-hospital mortality, both as a continuous variable (odds ratio = 0.99 [95% CI, 0.99 similar to 1]) and as a categorical variable (divided into quintiles). Restricted cubic spline analysis demonstrated an L-shaped relationship between SBP and mortality risk (P nonlinearity < 0.001), with an inflection point at 99.479 mmHg. Stratified analyses further supported the robustness of this correlation. Conclusion: The relationship between SBP and in-hospital mortality in patients with both CHF and COPD follows an L-shaped pattern, with an inflection point at approximately 99.479 mmHg.

关键词： systolic blood pressure in-hospital mortality congestive heart failure chronic obstructive pulmonary disease generalized additive model

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