published journal article

Analysis of Heat Exposure During Pregnancy and Severe Maternal Morbidity

JAMA Network Open

Publication Date

September 7, 2023

Author(s)

Anqi Jiao, Yi Sun, Chantal Avila, Vicki Chiu, Jeff Slezak, David A. Sacks, John T. Abatzoglou, John Molitor, Jiu-Chiuan Chen, Tarik Benmarhnia, Darios Getahun, Jun Wu

Abstract

The rate of severe maternal morbidity (SMM) is continuously increasing in the US. Evidence regarding the associations of climate-related exposure, such as environmental heat, with SMM is lacking.To examine associations between long- and short-term maternal heat exposure and SMM.This retrospective population-based epidemiological cohort study took place at a large integrated health care organization, Kaiser Permanente Southern California, between January 1, 2008, and December 31, 2018. Data were analyzed from February to April 2023. Singleton pregnancies with data on SMM diagnosis status were included.Moderate, high, and extreme heat days, defined as daily maximum temperatures exceeding the 75th, 90th, and 95th percentiles of the time series data from May through September 2007 to 2018 in Southern California, respectively. Long-term exposures were measured by the proportions of different heat days during pregnancy and by trimester. Short-term exposures were represented by binary variables of heatwaves with 9 different definitions (combining percentile thresholds with 3 durations; ie, ≥2, ≥3, and ≥4 consecutive days) during the last gestational week.The primary outcome was SMM during delivery hospitalization, measured by 20 subconditions excluding blood transfusion. Discrete-time logistic regression was used to estimate associations with long- and short-term heat exposure. Effect modification by maternal characteristics and green space exposure was examined using interaction terms.There were 3446 SMM cases (0.9%) among 403 602 pregnancies (mean [SD] age, 30.3 [5.7] years). Significant associations were observed with long-term heat exposure during pregnancy and during the third trimester. High exposure (≥80th percentile of the proportions) to extreme heat days during pregnancy and during the third trimester were associated with a 27% (95% CI, 17%-37%; P < .001) and 28% (95% CI, 17%-41%; P < .001) increase in risk of SMM, respectively. Elevated SMM risks were significantly associated with short-term heatwave exposure under all heatwave definitions. The magnitude of associations generally increased from the least severe (HWD1: daily maximum temperature >75th percentile lasting for ≥2 days; odds ratio [OR], 1.32; 95% CI, 1.17-1.48; P < .001) to the most severe heatwave exposure (HWD9: daily maximum temperature >95th percentile lasting for ≥4 days; OR, 2.39; 95% CI, 1.62-3.54; P < .001). Greater associations were observed among mothers with lower educational attainment (OR for high exposure to extreme heat days during pregnancy, 1.43; 95% CI, 1.26-1.63; P < .001) or whose pregnancies started in the cold season (November through April; OR, 1.37; 95% CI, 1.24-1.53; P < .001).In this retrospective cohort study, long- and short-term heat exposure during pregnancy was associated with higher risk of SMM. These results might have important implications for SMM prevention, particularly in a changing climate.

Suggested Citation
Anqi Jiao, Yi Sun, Chantal Avila, Vicki Chiu, Jeff Slezak, David A. Sacks, John T. Abatzoglou, John Molitor, Jiu-Chiuan Chen, Tarik Benmarhnia, Darios Getahun and Jun Wu (2023) “Analysis of Heat Exposure During Pregnancy and Severe Maternal Morbidity”, JAMA Network Open, 6(9), p. e2332780. Available at: 10.1001/jamanetworkopen.2023.32780.

published journal article

Modeling framework to analyze effect of multiple traffic information service providers on traffic network performance

Transportation Research Record

Publication Date

January 1, 2013

Abstract

Along with the increasing popularity of mobile smart devices such as smartphones and tablet personal computers, traffic information is coming to drivers through many intelligent traffic applications. Many countries have multiple traffic information service providers (ISPs), who make every effort to improve their service quality to influence more people to subscribe to their services. Because such a commercial environment is developing, a study of the effect of multiple ISPs on road network performance is necessary. Therefore, a modeling framework of day-to-day dynamics in which multiple ISPs compete and cooperate with each other to enhance their subscriber service quality is developed in this study. A realistic information acquisition and learning mechanism that ensures consistent updating of individually perceived day-by-day travel times is incorporated for driver behavior in this framework. A bounded rational behavior model was adopted for route choice decisions. The framework is capable of investigating the effects of any potential competition or cooperation of multiple ISPs in the traffic information market in terms of their information-sharing strategies. Numerical experiments on a real network were conducted to analyze the impact of such interactions on the network performance. The results showed that a cooperative system was not necessarily the best for network performance and that there was an optimal level of market penetration of traffic information services in transportation networks beyond which the benefits no longer increased or even worsened.

Suggested Citation
Inchul Yang and R. Jayakrishnan (2013) “Modeling framework to analyze effect of multiple traffic information service providers on traffic network performance”, Transportation Research Record, 2333(1), pp. 55–65. Available at: 10.3141/2333-07.

published journal article

Performance evaluation of adaptive ramp-metering algorithms using microscopic traffic simulation model

Journal of Transportation Engineering

Abstract

Adaptive ramp metering has undergone significant theoretical developments in recent years. However, the applicability and potential effectiveness of such algorithms depend on a number of complex factors that are best investigated during a planning phase prior to any decision on their implementation. The use of traffic simulation models can provide a quick and cost-effective way to evaluate the performance of such algorithms prior to implementation on the target freeway network. In this paper, a capability-enhanced PARAMICS simulation model has been used in an evaluation study of three well-known adaptive ramp-metering algorithms: ALINEA, BOTTLENECK, and ZONE. ALINEA is a local feedback-control algorithm, and the other two are areawide coordinated algorithms. The evaluation has been conducted in a simulation environment over a stretch of the I-405 freeway in California, under both recurrent congestion and incident scenarios. Simulation results show that adaptive ramp-metering algorithms can reduce freeway congestion effectively compared to the fixed-time control. ALINEA shows good performance under both recurrent and nonrecurrent congestion scenarios. BOTTLENECK and ZONE can be improved by replacing their native local occupancy control algorithms with ALINEA. Compared to ALINEA, the revised BOTTLENECK and ZONE algorithms using ALINEA as the local control algorithm are found to be more efficient in reducing traffic congestion than ALINEA alone. The revised BOTTLENECK algorithm performs robustly under all scenarios. The results also indicate that ramp metering becomes less effective when traffic experiences severe congestion under incident scenarios.

Suggested Citation
Lianyu Chu, Henry X. Liu, Will Recker and H. Michael Zhang (2004) “Performance evaluation of adaptive ramp-metering algorithms using microscopic traffic simulation model”, Journal of Transportation Engineering, 130(3), pp. 330–338. Available at: 10.1061/(asce)0733-947x(2004)130:3(330).

research report

The Requirements and Recommendations for Development of a California Weigh-in-Motion Test Facility

Publication Date

May 1, 2014

Author(s)

Wei-bin Zhang, Jihua Huang, Andre (Yeow Chern) Tok, Ching-Yao Chang, Stephen Ritchie

Abstract

This report documents a research effort to develop requirements and recommendations for establishing a Weigh-in-Motion Test Facility (WIMTF) in California. This study finds that the effectiveness of existing WIM stations needs to be improved. A WIMTF can facilitate an in-depth understanding of the characteristics of various WIM technologies, as well as the development of new methods for dynamic calibration of WIM scales in order to improve the WIM measurement accuracy, which is critical to the effectiveness and efficiency of WIM stations. To prepare for a WIMTF, several sets of requirements, including non-functional and functional requirements, interface requirements, and data requirements for the WIMTF were developed. Potential sites for the WIMTF were evaluated. Based on the requirements, a site recommendation was made. The study also evaluated the benefits and costs of a WIMTF, concluding that the benefits will far outweigh the costs of a WIMTF.

Suggested Citation
Wei-bin Zhang, Jihua Huang, Andre Tok, Ching-Yao Chang and Stephen Ritchie (2014) The Requirements and Recommendations for Development of a California Weigh-in-Motion Test Facility. University of California, Berkeley / California Partners for Advanced Transit and Highways, p. 130p.

conference paper

Numerical Investigation of Fracture Propagation in Geomaterials

AGU Fall Meeting Abstracts

Publication Date

December 1, 2015

Author(s)

P. Newell, Elisa Borowski, J. R. Major, P. Eichhubl

Abstract

Fracture in geomaterials is a critical behavior that affects the long-term structural response of geosystems. The processes involving fracture initiation and growth in rocks often span broad time scales and size scales, contributing to the complexity of these problems. To better understand fracture behavior, the authors propose an initial investigation comparing the fracture testing techniques of notched three-point bending (N3PB), short rod (SR), and double torsion (DT) on geomaterials using computational analysis. Linear softening cohesive fracture modeling (LCFM) was applied using ABAQUS to computationally simulate the three experimental set-ups. By applying material properties obtained experimentally, these simulations are intended to predict single-trace fracture growth. The advantages and limitations of the three testing techniques were considered for application to subcritical fracture propagation taking into account the accuracy of constraints, load applications, and modes of fracture. This work is supported as part of the Geomechanics of CO2 Reservoir Seals, a DOE-NETL funded under Award Number DE-FOA-0001037. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000.

Suggested Citation
P. Newell, E. Borowski, J. R. Major and P. Eichhubl (2015) “Numerical Investigation of Fracture Propagation in Geomaterials”, pp. MR41B–2629. Available at: https://ui.adsabs.harvard.edu/abs/2015AGUFMMR41B2629N (Accessed: August 21, 2025).

working paper

Things Won't Get a Lot Worse: The Future of U.S. Traffic Congestion

Publication Date

June 1, 1991

Author(s)

Working Paper

UCI-ITS-WP-90-2

Abstract

Our current alarm about traffic congestion stems in large part from perception of trends: thirty years ago traffic flowed smoothly; today it crawls. If this trend continues, congestion will become gridlock. These perceptions lead to statements such as: “There is no point to building highways, new lanes fill up as soon as they are opened.”It present evidence to show that such trend-based thinking is wrong because it ignores structural shifts in the demographics of auto ownership and use. At this time, auto ownership is effectively saturated: we are very close to the point where all the potential drivers have auto access. The ratio of autos per driver can continue to grow, but since it is only possible to drive one vehicle at a time, the growth rate of auto-use must decline to about the rate of population growth — a rate which is 2.9 times lower than the rate we have experienced in the period since 1960.Thus, fatalistic prophesies about future gridlock have overstated the potential growth of demand for auto travel. That growth has already declined and it should level off to a rate which is only one-third as large as we are used to. This is a manageable rate, planning is possible. And, specifically, it is appropriate to think about building new roads to solve our deficiency of highway capacity.

Suggested Citation
Charles Lave (1991) Things Won't Get a Lot Worse: The Future of U.S. Traffic Congestion. Working Paper UCI-ITS-WP-90-2. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/67c7d41k.

published journal article

Appreciation to Robert Herman

Transportation Science

Publication Date

January 1, 1974

Author(s)

Leslie C. Edie, Denos C. Gazis, Walter Helly, Richard Rothery, Ernst G. Frankel, Alfred Blumstein, John D.C. Little, John L. Schlaefli, Albert Brown, Thomas Golob
Suggested Citation
Leslie C. Edie, Denos C. Gazis, Walter Helly, Richard Rothery, Ernst G. Frankel, Alfred Blumstein, John D.C. Little, John L. Schlaefli, Albert Brown and Thomas Golob (1974) “Appreciation to Robert Herman”, Transportation Science, 8(1), pp. 1–1. Available at: http://www.jstor.org/stable/25767719.

conference paper

Paramics simulation of periodic oscillations caused by network geometry

TRAFFIC FLOW THEORY 2005

Publication Date

January 1, 2005

Author(s)

Abstract

Traffic oscillations such as stop-and-go waves in a traffic system can occur for a variety of reasons, such as instabilities. This paper describes a study of a type of periodic oscillations caused by network geometry with a microscopic simulation model, Paramics. With careful tuning in Paramics, periodic oscillations in which traffic states change periodically between a diverging junction and a merging junction are successfully simulated. The formation process is discussed in detail. The study suggests that, given an appropriate network structure and traffic conditions, the local oscillations caused by randomness in car-following and lane-changing models in Paramics can be maintained and can become periodic and global. Finally, the consistencies between a macroscopic kinematic wave model and Paramics are discussed, and future research topics and the implications of the findings of the study are presented.

Suggested Citation
WL Jin and Y Zhang (2005) “Paramics simulation of periodic oscillations caused by network geometry”, in TRAFFIC FLOW THEORY 2005. TRANSPORTATION RESEARCH BOARD NATL RESEARCH COUNCIL, pp. 188–196.

published journal article

Association between particulate air pollution and hypertensive disorders in pregnancy: A retrospective cohort study

PLOS Medicine

Publication Date

April 26, 2024

Author(s)

Yi Sun, Rashmi Bhuyan, Anqi Jiao, Chantal C. Avila, Vicki Y. Chiu, Jeff M. Slezak, David A. Sacks, John Molitor, Tarik Benmarhnia, Jiu-Chiuan Chen, Darios Getahun, Jun Wu

Abstract

Background Epidemiological findings regarding the association of particulate matter ≤2.5 μm (PM2.5) exposure with hypertensive disorders in pregnancy (HDP) are inconsistent; evidence for HDP risk related to PM2.5 components, mixture effects, and windows of susceptibility is limited. We aimed to investigate the relationships between HDP and exposure to PM2.5 during pregnancy. Methods and findings A large retrospective cohort study was conducted among mothers with singleton pregnancies in Kaiser Permanente Southern California from 2008 to 2017. HDP were defined by International Classification of Diseases-9/10 (ICD-9/10) diagnostic codes and were classified into 2 subcategories based on the severity of HDP: gestational hypertension (GH) and preeclampsia and eclampsia (PE-E). Monthly averages of PM2.5 total mass and its constituents (i.e., sulfate, nitrate, ammonium, organic matter, and black carbon) were estimated using outputs from a fine-resolution geoscience-derived model. Multilevel Cox proportional hazard models were used to fit single-pollutant models; quantile g-computation approach was applied to estimate the joint effect of PM2.5 constituents. The distributed lag model was applied to estimate the association between monthly PM2.5 exposure and HDP risk. This study included 386,361 participants (30.3 ± 6.1 years) with 4.8% (17,977/373,905) GH and 5.0% (19,381/386,361) PE-E cases, respectively. In single-pollutant models, we observed increased relative risks for PE-E associated with exposures to PM2.5 total mass [adjusted hazard ratio (HR) per interquartile range: 1.07, 95% confidence interval (CI) [1.04, 1.10] p < 0.001], black carbon [HR = 1.12 (95% CI [1.08, 1.16] p < 0.001)] and organic matter [HR = 1.06 (95% CI [1.03, 1.09] p < 0.001)], but not for GH. The population attributable fraction for PE-E corresponding to the standards of the US Environmental Protection Agency (9 μg/m3) was 6.37%. In multi-pollutant models, the PM2.5 mixture was associated with an increased relative risk of PE-E ([HR = 1.05 (95% CI [1.03, 1.07] p < 0.001)], simultaneous increase in PM2.5 constituents of interest by a quartile) and PM2.5 black carbon gave the greatest contribution of the overall mixture effects (71%) among all individual constituents. The susceptible window is the late first trimester and second trimester. Furthermore, the risks of PE-E associated with PM2.5 exposure were significantly higher among Hispanic and African American mothers and mothers who live in low- to middle-income neighborhoods (p < 0.05 for Cochran’s Q test). Study limitations include potential exposure misclassification solely based on residential outdoor air pollution, misclassification of disease status defined by ICD codes, the date of diagnosis not reflecting the actual time of onset, and lack of information on potential covariates and unmeasured factors for HDP. Conclusions Our findings add to the literature on associations between air pollution exposure and HDP. To our knowledge, this is the first study reporting that specific air pollution components, mixture effects, and susceptible windows of PM2.5 may affect GH and PE-E differently.

Suggested Citation
Yi Sun, Rashmi Bhuyan, Anqi Jiao, Chantal C. Avila, Vicki Y. Chiu, Jeff M. Slezak, David A. Sacks, John Molitor, Tarik Benmarhnia, Jiu-Chiuan Chen, Darios Getahun and Jun Wu (2024) “Association between particulate air pollution and hypertensive disorders in pregnancy: A retrospective cohort study”, PLOS Medicine, 21(4), p. e1004395. Available at: 10.1371/journal.pmed.1004395.