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Open Access Publications from the University of California

Department of Statistics

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Open Access Policy Deposits

This series is automatically populated with publications deposited by UC Irvine Donald Bren School of Information and Computer Sciences Department of Statistics researchers in accordance with the University of California’s open access policies. For more information see Open Access Policy Deposits and the UC Publication Management System.

Piecewise Linear and Stochastic Models for the Analysis of Cyber Resilience


We model a vehicle equipped with an autonomous cyber-defense system in addition to its inherent physical resilience features. When attacked, this ensemble of cyber-physical features (i.e., 'bonware') strives to resist and recover from the performance degradation caused by the malware's attack. We model the underlying differential equations governing such attacks for piecewise linear characterizations of malware and bonware, develop a discrete time stochastic model, and show that averages of instantiations of the stochastic model approximate solutions to the continuous differential equation. We develop a theory and methodology for approximating the parameters associated with these equations.

Cover page of Semi-parametric modeling of SARS-CoV-2 transmission using tests, cases, deaths, and seroprevalence data.

Semi-parametric modeling of SARS-CoV-2 transmission using tests, cases, deaths, and seroprevalence data.


Mechanistic models fit to streaming surveillance data are critical to understanding the transmission dynamics of an outbreak as it unfolds in real-time. However, transmission model parameter estimation can be imprecise, and sometimes even impossible, because surveillance data are noisy and not informative about all aspects of the mechanistic model. To partially overcome this obstacle, Bayesian models have been proposed to integrate multiple surveillance data streams. We devised a modeling framework for integrating SARS-CoV-2 diagnostics test and mortality time series data, as well as seroprevalence data from cross-sectional studies, and tested the importance of individual data streams for both inference and forecasting. Importantly, our model for incidence data accounts for changes in the total number of tests performed. We model the transmission rate, infection-to-fatality ratio, and a parameter controlling a functional relationship between the true case incidence and the fraction of positive tests as time-varying quantities and estimate changes of these parameters nonparametrically. We compare our base model against modified versions which do not use diagnostics test counts or seroprevalence data to demonstrate the utility of including these often unused data streams. We apply our Bayesian data integration method to COVID-19 surveillance data collected in Orange County, California between March 2020 and February 2021 and find that 32--72\% of the Orange County residents experienced SARS-CoV-2 infection by mid-January, 2021. Despite this high number of infections, our results suggest that the abrupt end of the winter surge in January 2021 was due to both behavioral changes and a high level of accumulated natural immunity.

Determinants of exposure to Aedes mosquitoes: A comprehensive geospatial analysis in peri-urban Cambodia.


Aedes mosquitoes are some of the most important and globally expansive vectors of disease. Public health efforts are largely focused on prevention of human-vector contact. A range of entomological indices are used to measure risk of disease, though with conflicting results (i.e. larval or adult abundance does not always predict risk of disease). There is a growing interest in the development and use of biomarkers for exposure to mosquito saliva, including for Aedes spp, as a proxy for disease risk. In this study, we conduct a comprehensive geostatistical analysis of exposure to Aedes mosquito bites among a pediatric cohort in a peri‑urban setting endemic to dengue, Zika, and chikungunya viruses. We use demographic, household, and environmental variables (the flooding index (NFI), land type, and proximity to a river) in a Bayesian geostatistical model to predict areas of exposure to Aedes aegypti bites. We found that hotspots of exposure to Ae. aegypti salivary gland extract (SGE) were relatively small (< 500 m and sometimes < 250 m) and stable across the two-year study period. Age was negatively associated with antibody responses to Ae. aegypti SGE. Those living in agricultural settings had lower antibody responses than those living in urban settings, whereas those living near recent surface water accumulation were more likely to have higher antibody responses. Finally, we incorporated measures of larval and adult density in our geostatistical models and found that they did not show associations with antibody responses to Ae. aegypti SGE after controlling for other covariates in the model. Our results indicate that targeted house- or neighborhood-focused interventions may be appropriate for vector control in this setting. Further, demographic and environmental factors more capably predicted exposure to Ae. aegypti mosquitoes than commonly used entomological indices.

Cover page of Triboelectric backgrounds to radio-based polar ultra-high energy neutrino (UHEN) experiments

Triboelectric backgrounds to radio-based polar ultra-high energy neutrino (UHEN) experiments


In the hopes of observing the highest-energy neutrinos (E>1 EeV) populating the Universe, both past (RICE, AURA, ANITA) and current (RNO-G, ARIANNA, ARA and TAROGE-M) polar-sited experiments exploit the impulsive radio emission produced by neutrino interactions. In such experiments, rare single event candidates must be unambiguously identified above backgrounds. Background rejection strategies to date primarily target thermal noise fluctuations and also impulsive radio-frequency signals of anthropogenic origin. In this paper, we consider the possibility that ‘fake’ neutrino signals may also be generated naturally via the ‘triboelectric effect.’ This broadly describes any process in which force applied at a boundary layer results in displacement of surface charge, leading to the production of an electrostatic potential difference ΔV. Wind blowing over granular surfaces such as snow can induce such a potential difference, with subsequent coronal discharge. Discharges over timescales as short as nanoseconds can then lead to radio-frequency emissions at characteristic MHz–GHz frequencies. Using data from various past (RICE, AURA, SATRA, ANITA) and current (RNO-G, ARIANNA and ARA) neutrino experiments, we find evidence for such backgrounds, which are generally characterized by: (a) a threshold wind velocity which likely depends on the experimental trigger criteria and layout; for the experiments considered herein, this value is typically O(10 m/s), (b) frequency spectra generally shifted to the low-end of the frequency regime to which current radio experiments are typically sensitive (100–200 MHz), (c) for the strongest background signals, an apparent preference for discharges from above-surface structures, although the presence of more isotropic, lower amplitude triboelectric discharges cannot be excluded.

Cover page of Posterior white matter hyperintensities are associated with reduced medial temporal lobe subregional integrity and long-term memory in older adults.

Posterior white matter hyperintensities are associated with reduced medial temporal lobe subregional integrity and long-term memory in older adults.


White matter hyperintensities are a marker of small vessel cerebrovascular disease that are strongly related to cognition in older adults. Similarly, medial temporal lobe atrophy is well-documented in aging and Alzheimer's disease and is associated with memory decline. Here, we assessed the relationship between lobar white matter hyperintensities, medial temporal lobe subregional volumes, and hippocampal memory in older adults. We collected MRI scans in a sample of 139 older adults without dementia (88 females, mean age (SD) = 76.95 (10.61)). Participants were administered the Rey Auditory Verbal Learning Test (RAVLT). Regression analyses tested for associations among medial temporal lobe subregional volumes, regional white matter hyperintensities and memory, while adjusting for age, sex, and education and correcting for multiple comparisons. Increased occipital white matter hyperintensities were related to worse RAVLT delayed recall performance, and to reduced CA1, dentate gyrus, perirhinal cortex (Brodmann area 36), and parahippocampal cortex volumes. These medial temporal lobe subregional volumes were related to delayed recall performance. The association of occipital white matter hyperintensities with delayed recall performance was fully mediated statistically only by perirhinal cortex volume. These results suggest that white matter hyperintensities may be associated with memory decline through their impact on medial temporal lobe atrophy. These findings provide new insights into the role of vascular pathologies in memory loss in older adults and suggest that future studies should further examine the neural mechanisms of these relationships in longitudinal samples.

Cover page of The role of parental health and distress in assessing children's health status.

The role of parental health and distress in assessing children's health status.



The purpose of the study was to examine the contributions of parents' health and distress to parent's and children's assessments of children's health.


We used baseline data from a longitudinal study of 364 children (ages 4-12) about to undergo surgery and their parents in a Southern California pediatric hospital. We used the 20-item child self-reported CHRIS 2.0 general health and the parallel parent-reported measure of the child's health, along with a measure of parental distress about the child's health were administered in the perioperative period. Other measures included parents' physical and mental health, quality of life, distress over their child's health, and number and extent of other health problems of the child and siblings.


On average, parents' reports about the child were consistently and statistically significantly higher than children's self-reports across all sub-dimensions of the CHRIS 2.0 measure. Parents' personal health was positively associated with their reports of the child's health. More distressed parents were closer to the child's self-reports, but reported poorer personal health.


Parent-child differences in this study of young children's health were related to parental distress. Exploring the nature of the gap between parents and children in assessments of children's health could improve effective clinical management for the child and enhance family-centered pediatric care. Future studies are needed to assess the generalizability of CHRIS 2.0 to other health settings and conditions and to other racial/ethnic groups.

Cover page of Tryptophan metabolism is a physiological integrator regulating circadian rhythms.

Tryptophan metabolism is a physiological integrator regulating circadian rhythms.



The circadian clock aligns physiology with the 24-hour rotation of Earth. Light and food are the main environmental cues (zeitgebers) regulating circadian rhythms in mammals. Yet, little is known about the interaction between specific dietary components and light in coordinating circadian homeostasis. Herein, we focused on the role of essential amino acids.


Mice were fed diets depleted of specific essential amino acids and their behavioral rhythms were monitored and tryptophan was selected for downstream analyses. The role of tryptophan metabolism in modulating circadian homeostasis was studied using isotope tracing as well as transcriptomic- and metabolomic- analyses.


Dietary tryptophan depletion alters behavioral rhythms in mice. Furthermore, tryptophan metabolism was shown to be regulated in a time- and light- dependent manner. A multi-omics approach and combinatory diet/light interventions demonstrated that tryptophan metabolism modulates temporal regulation of metabolism and transcription programs by buffering photic cues. Specifically, tryptophan metabolites regulate central circadian functions of the suprachiasmatic nucleus and the core clock machinery in the liver.


Tryptophan metabolism is a modulator of circadian homeostasis by integrating environmental cues. Our findings propose tryptophan metabolism as a potential point for pharmacologic intervention to modulate phenotypes associated with disrupted circadian rhythms.

Multidisciplinary Investigations of Sustained Malaria Transmission in the Greater Mekong Subregion.


In the course of malaria elimination in the Greater Mekong Subregion (GMS), malaria epidemiology has experienced drastic spatiotemporal changes with residual transmission concentrated along international borders and the rising predominance of Plasmodium vivax. The emergence of Plasmodium falciparum parasites resistant to artemisinin and partner drugs renders artemisinin-based combination therapies less effective while the potential spread of multidrug-resistant parasites elicits concern. Vector behavioral changes and insecticide resistance have reduced the effectiveness of core vector control measures. In recognition of these problems, the Southeast Asian International Center of Excellence for Malaria Research (ICEMR) has been conducting multidisciplinary research to determine how human migration, antimalarial drug resistance, vector behavior, and insecticide resistance sustain malaria transmission at international borders. These efforts allow us to comprehensively understand the ecology of border malaria transmission and develop population genomics tools to identify and track parasite introduction. In addition to employing in vivo, in vitro, and molecular approaches to monitor the emergence and spread of drug-resistant parasites, we also use genomic and genetic methods to reveal novel mechanisms of antimalarial drug resistance of parasites. We also use omics and population genetics approaches to study insecticide resistance in malaria vectors and identify changes in mosquito community structure, vectorial potential, and seasonal dynamics. Collectively, the scientific findings from the ICEMR research activities offer a systematic view of the factors sustaining residual malaria transmission and identify potential solutions to these problems to accelerate malaria elimination in the GMS.

Cover page of CAPITAL: Optimal subgroup identification via constrained&nbsp;policy tree search.

CAPITAL: Optimal subgroup identification via constrained policy tree search.


Personalized medicine, a paradigm of medicine tailored to a patient's characteristics, is an increasingly attractive field in health care. An important goal of personalized medicine is to identify a subgroup of patients, based on baseline covariates, that benefits more from the targeted treatment than other comparative treatments. Most of the current subgroup identification methods only focus on obtaining a subgroup with an enhanced treatment effect without paying attention to subgroup size. Yet, a clinically meaningful subgroup learning approach should identify the maximum number of patients who can benefit from the better treatment. In this article, we present an optimal subgroup selection rule (SSR) that maximizes the number of selected patients, and in the meantime, achieves the pre-specified clinically meaningful mean outcome, such as the average treatment effect. We derive two equivalent theoretical forms of the optimal SSR based on the contrast function that describes the treatment-covariates interaction in the outcome. We further propose a constrained policy tree search algorithm (CAPITAL) to find the optimal SSR within the interpretable decision tree class. The proposed method is flexible to handle multiple constraints that penalize the inclusion of patients with negative treatment effects, and to address time to event data using the restricted mean survival time as the clinically interesting mean outcome. Extensive simulations, comparison studies, and real data applications are conducted to demonstrate the validity and utility of our method.