Time-varying associations of patient and tumor characteristics with cancer survival: an analysis of SEER data across 14 cancer sites, 2004-2017.

PURPOSE: Surveillance, Epidemiology, and End Results (SEER) cancer registries provides information about survival duration and cause of death for cancer patients. Baseline demographic and tumor characteristics such as age, sex, race, year of diagnosis, and tumor stage can inform the expected survival time of patients, but their associations with survival may not be constant over the post-diagnosis period. METHODS: Using SEER data, we examined if there were time-varying associations of patient and tumor characteristics on survival, and we assessed how these relationships differed across 14 cancer sites. Standard Cox proportional hazards models were extended to allow for time-varying associations and incorporated into a competing-risks framework, separately modeling cancer-specific and other-cause deaths. For each cancer site and for each of the five factors, we estimated the relative hazard ratio and absolute hazard over time in the presence of competing risks. RESULTS: Our comprehensive consideration of patient and tumor characteristics when estimating time-varying hazards showed that the associations of age, tumor stage at diagnosis, and race/ethnicity with risk of death (cancer-specific and other-cause) change over time for many cancers; characteristics of sex and year of diagnosis exhibit some time-varying patterns as well. Stage at diagnosis had the largest associations with survival. CONCLUSION: These findings suggest that proportional hazards assumptions are often violated when examining patient characteristics on cancer survival post-diagnosis. We discuss several interesting results where the relative hazards are time-varying and suggest possible interpretations. Based on the time-varying associations of several important covariates on survival after cancer diagnosis using a pan-cancer approach, the likelihood of the proportional hazards assumption being met or corresponding interpretation should be considered in survival analyses, as flawed inference may have implications for cancer care and policy.

Birth cohort relative to an influenza A virus's antigenic cluster introduction drives patterns of children's antibody titers.

An individual's antibody titers to influenza A strains are a result of the complicated interplay between infection history, cross-reactivity, immune waning, and other factors. It has been challenging to disentangle how population-level patterns of humoral immunity change as a function of age, calendar year, and birth cohort from cross-sectional data alone. We analyzed 1,589 longitudinal sera samples from 260 children across three studies in Nicaragua, 2006-16. Hemagglutination inhibition (HAI) titers were determined against four H3N2 strains, one H1N1 strain, and two H1N1pdm strains. We assessed temporal patterns of HAI titers using an age-period-cohort modeling framework. We found that titers against a given virus depended on calendar year of serum collection and birth cohort but not on age. Titer cohort patterns were better described by participants' ages relative to year of likely introduction of the virus's antigenic cluster than by age relative to year of strain introduction or by year of birth. These cohort effects may be driven by a decreasing likelihood of early-life infection after cluster introduction and by more broadly reactive antibodies at a young age. H3N2 and H1N1 viruses had qualitatively distinct cohort patterns, with cohort patterns of titers to specific H3N2 strains reaching their peak in children born 3 years prior to that virus's antigenic cluster introduction and with titers to H1N1 and H1N1pdm strains peaking for children born 1-2 years prior to cluster introduction but not being dramatically lower for older children. Ultimately, specific patterns of strain circulation and antigenic cluster introduction may drive population-level antibody titer patterns in children.

A Model-Based 13C-Sucrose Breath Test Diagnostic for Gut Function Disorders Characterized by a Loss of Sucrase-Isomaltase Enzymatic Activity.

BACKGROUND: Environmental enteric dysfunction (EED) causes malnutrition in children in low-resource settings. Stable-isotope breath tests have been proposed as noninvasive tests of altered nutrient metabolism and absorption in EED, but uncertainty over interpreting the breath curves has limited their use. The activity of sucrose-isomaltase, the glucosidase enzyme responsible for sucrose hydrolysis, may be reduced in EED. We previously developed a mechanistic model describing the dynamics of the 13C-sucrose breath test (13C-SBT) as a function of underlying metabolic processes. OBJECTIVES: This study aimed to determine which breath test curve dynamics are associated with sucrose hydrolysis and with the transport and metabolism of the fructose and glucose moieties and to propose and evaluate a model-based diagnostic for the loss of activity of sucrase-isomaltase. METHODS: We applied the mechanistic model to 2 sets of exploratory 13C-SBT experiments in healthy adult participants. First, 19 participants received differently labeled sucrose tracers (U-13C fructose, U-13C glucose, and U-13C sucrose) in a crossover study. Second, 16 participants received a sucrose tracer accompanied by 0, 100, and 750 mg of Reducose, a sucrase-isomaltase inhibitor. We evaluated a model-based diagnostic distinguishing between inhibitor concentrations using receiver operator curves, comparing with conventional statistics. RESULTS: Sucrose hydrolysis and the transport and metabolism of the fructose and glucose moieties were reflected in the same mechanistic process. The model distinguishes these processes from the fraction of tracer exhaled and an exponential metabolic process. The model-based diagnostic performed as well as the conventional summary statistics in distinguishing between no and low inhibition [area under the curve (AUC): 0.77 vs. 0.66-0.79] and for low vs. high inhibition (AUC 0.92 vs. 0.91-0.99). CONCLUSIONS: Current summary approaches to interpreting 13C breath test curves may be limited to identifying only gross gut dysfunction. A mechanistic model-based approach improved interpretation of breath test curves characterizing sucrose metabolism.

Leveraging infectious disease models to interpret randomized controlled trials: Controlling enteric pathogen transmission through water, sanitation, and hygiene interventions.

Randomized controlled trials (RCTs) evaluate hypotheses in specific contexts and are often considered the gold standard of evidence for infectious disease interventions, but their results cannot immediately generalize to other contexts (e.g., different populations, interventions, or disease burdens). Mechanistic models are one approach to generalizing findings between contexts, but infectious disease transmission models (IDTMs) are not immediately suited for analyzing RCTs, since they often rely on time-series surveillance data. We developed an IDTM framework to explain relative risk outcomes of an infectious disease RCT and applied it to a water, sanitation, and hygiene (WASH) RCT. This model can generalize the RCT results to other contexts and conditions. We developed this compartmental IDTM framework to account for key WASH RCT factors: i) transmission across multiple environmental pathways, ii) multiple interventions applied individually and in combination, iii) adherence to interventions or preexisting conditions, and iv) the impact of individuals not enrolled in the study. We employed a hybrid sampling and estimation framework to obtain posterior estimates of mechanistic parameter sets consistent with empirical outcomes. We illustrated our model using WASH Benefits Bangladesh RCT data (n = 17,187). Our model reproduced reported diarrheal prevalence in this RCT. The baseline estimate of the basic reproduction number [Formula: see text] for the control arm (1.10, 95% CrI: 1.07, 1.16) corresponded to an endemic prevalence of 9.5% (95% CrI: 7.4, 13.7%) in the absence of interventions or preexisting WASH conditions. No single pathway was likely able to sustain transmission: pathway-specific [Formula: see text] for water, fomites, and all other pathways were 0.42 (95% CrI: 0.03, 0.97), 0.20 (95% CrI: 0.02, 0.59), and 0.48 (95% CrI: 0.02, 0.94), respectively. An IDTM approach to evaluating RCTs can complement RCT analysis by providing a rigorous framework for generating data-driven hypotheses that explain trial findings, particularly unexpected null results, opening up existing data to deeper epidemiological understanding.

Associations of Demographics, Dependence, and Biomarkers With Transitions in Tobacco Product Use in a Cohort of Cigarette Users and Dual Users of Cigarettes and E-cigarettes.

INTRODUCTION: It is uncertain whether e-cigarettes facilitate smoking cessation in the real world. We aimed to understand whether and how transitions among cigarette, e-cigarette, and dual use are associated with sociodemographics, dependence measures, and biomarkers. AIMS AND METHODS: We followed 380 adult daily cigarette users and dual users every 2 months for up to 2 years. We estimated transition rates between noncurrent, cigarette-only, e-cigarette-only, and dual use states using a multistate transition model. We estimated univariable hazard ratios (HR) for demographics, dependence measures for cigarettes and e-cigarettes, biomarkers, spousal or partner behaviors, and other measures. RESULTS: We estimated that participants transitioned from cigarette-only to e-cigarette-only through a period of dual use. Dual users ceased smoking (transitioning to e-cigarette-only use) at a greater rate than cigarette-only users did (HR 2.44, 95% CI: 1.49, 4.02). However, of the 60% of dual users estimated to transition to single product use in 1 year, 83% would transition to cigarette-only use and only 17% to e-cigarette-only use. E-cigarette dependence measures were generally associated with reduced e-cigarette cessation rather than enhanced cigarette cessation. E-cigarette users motivated by harm or toxicity reduction or because of restrictions on where or when they could smoke had reduced rates of smoking relapse. Cigarette dependence and spousal smoking were barriers to cigarette cessation for dual users, while using e-cigarettes first in the morning, motivation to quit smoking, and sensory, social, and emotional enjoyment of e-cigarettes (secondary dependence motives) were facilitators of smoking cessation among dual users. CONCLUSIONS: Tobacco control policy and interventions may be informed by the barriers and facilitators of product transitions. IMPLICATIONS: Although e-cigarettes have the potential to promote smoking cessation, their real-world impact is uncertain. In this cohort, dual users were more likely to quit smoking than cigarette-only users, but the overall impact was small because most dual users returned to cigarette-only use. Moreover, e-cigarette dependence promoted continued dual use rather than smoking cessation. Yet, high motivation to quit smoking and the sensory, social, and emotional enjoyment of e-cigarettes facilitated smoking cessation in dual users. Better understanding the barriers and facilitators of transitions can help to develop regulations and interventions that lead to more effective use of e-cigarettes for smoking cessation.

Patterns of poly tobacco use among adults in the Population Assessment of Tobacco and Health (PATH) study, 2013-2017: a multistate Markov transition analysis.

BACKGROUND: A better understanding of sociodemographic transition patterns between single, dual and poly tobacco product use may help improve tobacco control policy interventions. METHODS: HRs of transition between never, non-current (no past 30-day use), cigarette, e-cigarette, other combustible, smokeless tobacco (SLT), dual and poly tobacco use states in adults were estimated for age, sex, race/ethnicity, education and income using a multistate model for waves 1-4 of the Population Assessment of Tobacco and Health study (2013-2017), a US-based cohort study, accounting for complex survey design. RESULTS: Sole cigarette and SLT use were persistent, with 77% and 78% of adults continuing use after one wave. Other use states were more transient, with 29%-48% of adults reporting the same pattern after one wave. If single-product users transitioned, it was most likely to non-current use while dual or poly cigarette users were most likely to transition to exclusive cigarette use. Males were more likely than females to initiate combustible product use after a history of no use, and after a period of tobacco use cessation. Hispanic and non-Hispanic black participants initiated cigarette use at higher rates than non-Hispanic white participants, and had higher rates of experimentation with tobacco products between study waves. Lower socioeconomic status was associated with higher rates of transition into combustible tobacco use. CONCLUSIONS: Dual and poly tobacco use is largely transient, while single-use patterns are more stable over time. Transitions differ by age, sex, race/ethnicity, education and income, which may influence the impact of current and future tobacco control efforts.

Changing patterns of cigarette and ENDS transitions in the USA: a multistate transition analysis of youth and adults in the PATH Study in 2015-2017 vs 2017-2019.

INTRODUCTION: It is unknown how recent changes in the tobacco product marketplace have impacted transitions in cigarette and electronic nicotine delivery system (ENDS) use. METHODS: A multistate transition model was applied to 24 242 adults and 12 067 youth in waves 2-4 (2015-2017) and 28 061 adults and 12 538 youth in waves 4 and 5 (2017-2019) of the Population Assessment of Tobacco and Health Study. Transition rates for initiation, cessation and product transitions were estimated in multivariable models, accounting for gender, age group, race/ethnicity and daily versus non-daily product use. RESULTS: Changes in ENDS initiation/relapse rates depended on age, including among adults. Among youth who had never established tobacco use, the 1-year probability of ENDS initiation increased after 2017 from 1.6% (95% CI 1.4% to 1.8%) to 3.8% (95% CI 3.4% to 4.2%). Persistence of ENDS-only use (ie, 1-year probability of continuing to use ENDS only) increased for youth from 40.7% (95% CI 34.4% to 46.9%) to 65.7% (95% CI 60.5% to 71.1%) and for adults from 57.8% (95% CI 54.4% to 61.3%) to 78.2% (95% CI 76.0% to 80.4%). Persistence of dual use similarly increased for youth from 48.3% (95% CI 37.4% to 59.2%) to 60.9% (95% CI 43.0% to 78.8%) and for adults from 40.1% (95% CI 37.0% to 43.2%) to 63.8% (95% CI 59.6% to 67.6%). Youth and young adults who used both products became more likely to transition to ENDS-only use, but middle-aged and older adults did not. CONCLUSIONS: ENDS-only and dual use became more persistent. Middle-aged and older adults who used both products became less likely to transition to cigarette-only use but not more likely to discontinue cigarettes. Youth and young adults became more likely to transition to ENDS-only use.

Public health impact of a US ban on menthol in cigarettes and cigars: a simulation study.

INTRODUCTION: The US Food and Drug Administration most recently announced its intention to ban menthol cigarettes and cigars nationwide in April 2021. Implementation of the ban will require evidence that it would improve public health. This paper simulates the potential public health impact of a ban on menthol in cigarettes and cigars through its impacts on smoking initiation, smoking cessation and switching to nicotine vaping products (NVPs). METHODS: After calibrating an established US simulation model to reflect recent use trends in cigarette and NVP use, we extended the model to incorporate menthol and non-menthol cigarette use under a status quo scenario. Applying estimates from a recent expert elicitation on the behavioural impacts of a menthol ban, we developed a menthol ban scenario with the ban starting in 2021. We estimated the public health impact as the difference between smoking and vaping-attributable deaths and life-years lost in the status quo scenario and the menthol ban scenario from 2021 to 2060. RESULTS: As a result of the ban, overall smoking was estimated to decline by 15% as early as 2026 due to menthol smokers quitting both NVP and combustible use or switching to NVPs. These transitions are projected to reduce cumulative smoking and vaping-attributable deaths from 2021 to 2060 by 5% (650 000 in total) and reduce life-years lost by 8.8% (11.3 million). Sensitivity analyses showed appreciable public health benefits across different parameter specifications. CONCLUSIONS AND RELEVANCE: Our findings strongly support the implementation of a ban on menthol in cigarettes and cigars.

Mechanistic inference of the metabolic rates underlying [Formula: see text]C breath test curves.

Carbon stable isotope breath tests offer new opportunities to better understand gastrointestinal function in health and disease. However, it is often not clear how to isolate information about a gastrointestinal or metabolic process of interest from a breath test curve, and it is generally unknown how well summary statistics from empirical curve fitting correlate with underlying biological rates. We developed a framework that can be used to make mechanistic inference about the metabolic rates underlying a 13C breath test curve, and we applied it to a pilot study of 13C-sucrose breath test in 20 healthy adults. Starting from a standard conceptual model of sucrose metabolism, we determined the structural and practical identifiability of the model, using algebra and profile likelihoods, respectively, and we used these results to develop a reduced, identifiable model as a function of a gamma-distributed process; a slower, rate-limiting process; and a scaling term related to the fraction of the substrate that is exhaled as opposed to sequestered or excreted through urine. We demonstrated how the identifiable model parameters impacted curve dynamics and how these parameters correlated with commonly used breath test summary measures. Our work develops a better understanding of how the underlying biological processes impact different aspect of 13C breath test curves, enhancing the clinical and research potential of these 13C breath tests.

Estimation of Breast Cancer Overdiagnosis in a U.S. Breast Screening Cohort.

BACKGROUND: Mammography screening can lead to overdiagnosis-that is, screen-detected breast cancer that would not have caused symptoms or signs in the remaining lifetime. There is no consensus about the frequency of breast cancer overdiagnosis. OBJECTIVE: To estimate the rate of breast cancer overdiagnosis in contemporary mammography practice accounting for the detection of nonprogressive cancer. DESIGN: Bayesian inference of the natural history of breast cancer using individual screening and diagnosis records, allowing for nonprogressive preclinical cancer. Combination of fitted natural history model with life-table data to predict the rate of overdiagnosis among screen-detected cancer under biennial screening. SETTING: Breast Cancer Surveillance Consortium (BCSC) facilities. PARTICIPANTS: Women aged 50 to 74 years at first mammography screen between 2000 and 2018. MEASUREMENTS: Screening mammograms and screen-detected or interval breast cancer. RESULTS: The cohort included 35 986 women, 82 677 mammograms, and 718 breast cancer diagnoses. Among all preclinical cancer cases, 4.5% (95% uncertainty interval [UI], 0.1% to 14.8%) were estimated to be nonprogressive. In a program of biennial screening from age 50 to 74 years, 15.4% (UI, 9.4% to 26.5%) of screen-detected cancer cases were estimated to be overdiagnosed, with 6.1% (UI, 0.2% to 20.1%) due to detecting indolent preclinical cancer and 9.3% (UI, 5.5% to 13.5%) due to detecting progressive preclinical cancer in women who would have died of an unrelated cause before clinical diagnosis. LIMITATIONS: Exclusion of women with first mammography screen outside BCSC. CONCLUSION: On the basis of an authoritative U.S. population data set, the analysis projected that among biennially screened women aged 50 to 74 years, about 1 in 7 cases of screen-detected cancer is overdiagnosed. This information clarifies the risk for breast cancer overdiagnosis in contemporary screening practice and should facilitate shared and informed decision making about mammography screening. PRIMARY FUNDING SOURCE: National Cancer Institute.

Dilution of Epidemic Potential of Environmentally Transmitted Infectious Diseases for Species with Partially Overlapping Habitats.

AbstractSpecies diversity may play an important role in the modulation of pathogen transmission through the dilution effect. Infectious disease models can help elucidate mechanisms that may underlie this effect. While many modeling studies have assumed direct host-to-host transmission, many pathogens are transmitted through the environment. We present a mathematical modeling analysis exploring conditions under which we observe the dilution effect in systems with environmental transmission where host species interact through fully or partially overlapping habitats. We measure the strength of the dilution effect by the relative decrease in the basic reproduction number of two-species assemblages compared with that of a focal host species. We find that a dilution effect is most likely when the pathogen is environmentally persistent (frequency-dependent-like transmission). The magnitude of this effect is strongest when the species with the greater epidemic potential is relatively slow to pick up pathogens in the environment (density-dependent transmission) and the species with the lesser epidemic potential is efficient at picking up pathogens (frequency-dependent transmission). These findings suggest that measurable factors, including pathogen persistence and the host's relative efficiency of pathogen pickup, can guide predictions of when biodiversity might lead to a dilution effect and may thus give concrete direction to future ecological work.

Understanding the mechanisms of HPV-related carcinogenesis: Implications for cell cycle dynamics.

The role of human papillomavirus (HPV) as a causative agent for epithelial cancers is well-known, but many open questions remain regarding the downstream gene regulatory effects of viral proteins E6 and E7 on the cell cycle. Here, we extend a cell cycle model originally presented by Gérard and Goldbeter (2009) in order to capture the effects of E6 and E7 on key actors in the cell cycle. Results suggest that E6 is sufficient to reverse p53-induced quiescence, while E7 is sufficient to reverse p16INK4a-induced quiescence; both E6 and E7 are necessary when p53 and p16INK4a are both active. Moreover, E7 appears to play a role as a "growth factor substitute", inducing cell division in the absence of growth factor. Low levels of E7 may permit regular cell division, but the results suggest that higher levels of E7 dysregulate the cell cycle in ways that may destabilize the cellular genome. The mechanisms explored here provide opportunities for developing new treatment targets that take advantage of the cell cycle regulatory system to prevent HPV-related cancer effects.

The Impact of Current Tobacco Product Use Definitions on Estimates of Transitions Between Cigarette and ENDS Use.

INTRODUCTION: Definitions of current tobacco and nicotine delivery product use vary and depend on frequency of use, established-use criteria, and the product type. Previous research has not considered how transition rates between current use of different products depend on the current use definition. AIMS AND METHODS: We applied a multistate transition model to data on U.S. adults from waves 1-4 (2013-2017) of the Population Assessment of Tobacco and Health (PATH) study. We estimated transition rates between never, non-current, cigarette, electronic nicotine delivery systems (ENDS), and dual use states with and without established-use criteria (has smoked 100+ cigarettes in their lifetime; ever fairly regularly used ENDS) and different frequency thresholds (1+, 10+, 20+, and 30 days of the past 30 days). We considered use below a frequency threshold as either non-current use or a distinct, infrequent use category. RESULTS: When treating use below a frequency threshold as non-current use, transition probability estimates were largely robust to the choice of use frequency threshold, although sole ENDS users were more likely to transition to non-current use or dual use as the current use threshold increased. Removing the established-use criterion for ENDS reduced the estimates of sole ENDS and dual users staying in their use state. When treating infrequent use as a separate category, transition probability estimates were dependent on the use frequency threshold, particularly transitions among the dual use states. CONCLUSIONS: Product use definitions have important implications for assessing product use transitions and thus the public health implications of cigarette and ENDS control strategies. IMPLICATIONS: How we define "current use" of tobacco and nicotine delivery products changes our estimates of how individuals transition to, between, and from different patterns of use. We show that the robustness of transition estimates to whether or not non-established users are included as current users and to different frequency-of-use threshold depends in part on whether low-frequency users are categorized as non-current users or as a distinct category. Our results emphasize the importance of intentional definitions of product use that reflect the larger goals of public health and tobacco control.

Why the Spectral Radius? An intuition-building introduction to the basic reproduction number.

The basic reproduction number [Formula: see text] is a fundamental concept in mathematical epidemiology and infectious disease modeling. Loosely speaking, it describes the number of people that an infectious person is expected to infect. The basic reproduction number has profound implications for epidemic trajectories and disease control strategies. It is well known that the basic reproduction number can be calculated as the spectral radius of the next generation matrix, but why this is the case may not be intuitively obvious. Here, we walk through how the discrete, next generation process connects to the ordinary differential equation disease system of interest, linearized at the disease-free equilibrium. Then, we use linear algebra to develop a geometric explanation of why the spectral radius of the next generation matrix is an epidemic threshold. Finally, we work through a series of examples that help to build familiarity with the kinds of patterns that arise in parameter combinations produced by the next generation method. This article is intended to help new infectious disease modelers develop intuition for the form and interpretation of the basic reproduction number in their disease systems of interest.

Scalable proximal methods for cause-specific hazard modeling with time-varying coefficients.

Survival modeling with time-varying coefficients has proven useful in analyzing time-to-event data with one or more distinct failure types. When studying the cause-specific etiology of breast and prostate cancers using the large-scale data from the Surveillance, Epidemiology, and End Results (SEER) Program, we encountered two major challenges that existing methods for estimating time-varying coefficients cannot tackle. First, these methods, dependent on expanding the original data in a repeated measurement format, result in formidable time and memory consumption as the sample size escalates to over one million. In this case, even a well-configured workstation cannot accommodate their implementations. Second, when the large-scale data under analysis include binary predictors with near-zero variance (e.g., only 0.6% of patients in our SEER prostate cancer data had tumors regional to the lymph nodes), existing methods suffer from numerical instability due to ill-conditioned second-order information. The estimation accuracy deteriorates further with multiple competing risks. To address these issues, we propose a proximal Newton algorithm with a shared-memory parallelization scheme and tests of significance and nonproportionality for the time-varying effects. A simulation study shows that our scalable approach reduces the time and memory costs by orders of magnitude and enjoys improved estimation accuracy compared with alternative approaches. Applications to the SEER cancer data demonstrate the real-world performance of the proximal Newton algorithm.

Severe Acute Respiratory Syndrome Coronavirus 2 Surveillance in Decedents in a Large, Urban Medical Examiner's Office.

BACKGROUND: Given the challenges in implementing widespread testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is increasing interest in alternative surveillance strategies. METHODS: We tested nasopharyngeal swabs from 1094 decedents in the Wayne County Medical Examiner's Office for SARS-CoV-2. All decedents were assessed using a coronavirus disease 2019 (COVID-19) checklist, and decedents flagged using the checklist (298) were preferentially tested. A random sample of decedents not flagged using the checklist were also tested (796). We statistically analyzed the characteristics of decedents (age, sex, race, and manner of death), differentiating between those flagged using the checklist and not and between those SARS-CoV-2-positive and not. RESULTS: A larger percentage of decedents overall were male (70% vs 48%) and black (55% vs 36%) compared with the catchment population. Seven-day average percent positivity among flagged decedents closely matched the trajectory of percent positivity in the catchment population, particularly during the peak of the outbreak (March and April 2020). After a lull in May to mid-June, new positive tests in late June coincided with increased case detection in the catchment. We found large racial disparities in test results; SARS-CoV-2-positive decedents were substantially more likely to be black than SARS-CoV-2-negative decedents (82% vs 51%). SARS-CoV-2-positive decedents were also more likely to be older and to have died of natural causes, including of COVID-19 disease. CONCLUSIONS: Disease surveillance through medical examiners and coroners could supplement other forms of surveillance and serve as a possible early outbreak warning sign.

Latent class analysis of use frequencies for multiple tobacco products in US adults.

A persistent challenge is characterizing patterns of tobacco use in terms of product combinations and frequency. Using Wave 4 (2016-17) Population Assessment of Tobacco and Health Study adult data, we conducted latent class analyses (LCA) of past 30-day frequency of use for 9 tobacco products. One-step LCA with joint multinomial logistic regression models compared sociodemographic factors between users (n = 13,716) and non-users (n = 17,457), and between latent classes of users. We accounted for survey design and weights. Our analyses identified 6 classes: in addition to non-users (C0: 75.7%), we found 5 distinct latent classes of users: daily exclusive cigarette users (C1: 15.5%); occasional cigarette and polytobacco users (C2: 3.8%); frequent e-product and occasional cigarette users (C3: 2.2%); daily smokeless tobacco (SLT) and infrequent cigarette users (C4: 2.0%); and occasional cigar users (C5: 0.8%). Compared to C1: C2 and C3 had higher odds of being male (versus female), younger (especially 18-24 versus 55 years), and having higher education; C2 had higher, while C3 and C4 had lower, odds of being a racial/ethnic minority (versus Non-Hispanic White); C4 and C5 had much higher odds of being male (versus female) and heterosexual (versus sexual minority) and having higher income; and C5 had higher odds of college or more education. We identified three classes of daily or frequent users of a primary product (cigarettes, SLT or e-products) and two classes of occasional users (cigarettes, cigars and polytobacco). Sociodemographic differences in class membership may influence tobacco-related health disparities associated with specific patterns of use.

Modeling environmentally mediated rotavirus transmission: The role of temperature and hydrologic factors.

Rotavirus is considered a directly transmitted disease due to its high infectivity. Environmental pathways have, therefore, largely been ignored. Rotavirus, however, persists in water sources, and both its surface water concentrations and infection incidence vary with temperature. Here, we examine the potential for waterborne rotavirus transmission. We use a mechanistic model that incorporates both direct and waterborne transmission pathways, coupled with a hydrological model, and we simulate rotavirus transmission between two communities with interconnected water sources. To parameterize temperature dependency, we estimated temperature-dependent decay rates in water through a meta-analysis. Our meta-analysis suggests that rotavirus decay rates are positively associated with temperature (n = 39, P [Formula: see text] 0.001). This association is stronger at higher temperatures (over 20 °C), consistent with tropical climate conditions. Our model analysis demonstrates that water could disseminate rotavirus between the two communities for all modeled temperatures. While direct transmission was important for disease amplification within communities, waterborne transmission could also amplify transmission. In standing-water systems, the modeled increase in decay led to decreased disease, with every 1 °C increase in temperature leading to up to a 2.4% decrease in incidence. These effect sizes are consistent with prior meta-analyses, suggesting that environmental transmission through water sources may partially explain the observed associations between temperature and rotavirus incidence. Waterborne rotavirus transmission is likely most important in cooler seasons and in communities that use slow-moving or stagnant water sources. Even when indirect transmission through water cannot sustain outbreaks, it can seed outbreaks that are maintained by high direct transmission rates.

Epidemiology of the silent polio outbreak in Rahat, Israel, based on modeling of environmental surveillance data.

Israel experienced an outbreak of wild poliovirus type 1 (WPV1) in 2013-2014, detected through environmental surveillance of the sewage system. No cases of acute flaccid paralysis were reported, and the epidemic subsided after a bivalent oral polio vaccination (bOPV) campaign. As we approach global eradication, polio will increasingly be detected only through environmental surveillance. We developed a framework to convert quantitative polymerase chain reaction (qPCR) cycle threshold data into scaled WPV1 and OPV1 concentrations for inference within a deterministic, compartmental infectious disease transmission model. We used this approach to estimate the epidemic curve and transmission dynamics, as well as assess alternate vaccination scenarios. Our analysis estimates the outbreak peaked in late June, much earlier than previous estimates derived from analysis of stool samples, although the exact epidemic trajectory remains uncertain. We estimate the basic reproduction number was 1.62 (95% CI 1.04-2.02). Model estimates indicate that 59% (95% CI 9-77%) of susceptible individuals (primarily children under 10 years old) were infected with WPV1 over a little more than six months, mostly before the vaccination campaign onset, and that the vaccination campaign averted 10% (95% CI 1-24%) of WPV1 infections. As we approach global polio eradication, environmental monitoring with qPCR can be used as a highly sensitive method to enhance disease surveillance. Our analytic approach brings public health relevance to environmental data that, if systematically collected, can guide eradication efforts.

Time-varying survival effects for squamous cell carcinomas at oropharyngeal and nonoropharyngeal head and neck sites in the United States, 1973-2015.

BACKGROUND: Anatomical site is strongly associated with head and neck cancer etiology, and etiology and patient sociodemographic characteristics are prognostic factors for survival. It is not known whether the effects of these predictors persist over the postdiagnosis period or are strongest proximal to the time of diagnosis. METHODS: Using survival times and causes of death for 180,434 patients with head and neck cancer in the Surveillance, Epidemiology, and End Results cancer registry (1973-2015), the empirical cumulative incidences of cancer-specific death and other-cause death were calculated with a competing risks framework, and the time-dependent effects (hazard ratios) of anatomical tumor site (oropharynx, oral cavity, or hypopharynx/larynx), age, sex, race, and year of diagnosis on cancer-specific death and other-cause death, stratified by tumor stage, were estimated. RESULTS: All effects were significantly time-varying (P < .001). Patients with nonoropharyngeal cancer had a higher hazard of cancer-specific death but a similar cumulative fraction of deaths because of a higher rate of death from other causes. Cancer-specific survival has not changed for patients with nonoropharyngeal cancer over the past decades but has improved since 2000 for patients with oropharyngeal cancer. The effects of age and sex on cancer survival were strongest proximal to the diagnosis, whereas the effect of race persisted over time. CONCLUSIONS: Recent improvements in survival for patients with oropharyngeal cancer may be due more to an increasing fraction of cancers attributable to human papillomavirus than to increasing treatment effectiveness. The prognostic strength of anatomical site and other predictors changes over the postdiagnosis period. LAY SUMMARY: It is generally assumed that the effects of tumor and personal characteristics on the survival of patients with head and neck cancer are fixed over time, but this study shows that many factors are most important only in the first few years after diagnosis. Also, recent improvements in the survival of patients with head and neck cancer appear to benefit only patients with cancers of the oropharynx. The improvements may be due more to an increasing fraction of cancers caused by human papillomavirus (which generally have better outcomes) than to advances in head and neck cancer treatment overall.