Cervicovaginal and Anal Self-Sampling for Human Papillomavirus Testing in a Transgender and Gender Diverse Population Assigned Female at Birth: Comfort, Difficulty, and Willingness to Use

Purpose: Transgender and gender diverse (TGD) people assigned female at birth (AFAB) face numerous barriers to preventive care, including for cervical cancer screening. At-home human papillomavirus (HPV) testing may expand access to cervical cancer screening for TGD people AFAB. This study assessed the perceptions of TGD individuals AFAB who self-collected cervicovaginal and anal samples. Methods: We recruited TGD individuals AFAB to collect cervicovaginal and anal specimens at home using self-sampling for HPV testing, and individuals reported their perceptions of self-sampling. Associations between demographic and health characteristics and each of comfort of use, ease of use, and willingness to use self-sampling were estimated using robust Poisson regression. Results: Of 137 consenting participants, 101 completed the sample collection and the surveys. The majority of participants reported that the cervicovaginal self-swab was not uncomfortable (68.3%) and not difficult to use (86.1%), and nearly all (96.0%) were willing to use the swab in the future. Fewer participants found the anal swab to not be uncomfortable (47.5%), but most participants still found the anal swab to not be difficult to use (70.2%) and were willing to use the swab in the future (89.1%). Participants were more willing to use either swab if they had not seen a medical professional in the past year. Conclusions: TGD individuals AFAB were willing to use and preferred self-sampling methods for cervicovaginal and anal HPV testing. Developing clinically approved self-sampling options for HPV testing could expand access to cancer screening for TGD populations.

Prevalence and Determinants of Cervicovaginal, Oral, and Anal Human Papillomavirus Infection in a Population of Transgender and Gender Diverse People Assigned Female at Birth

Purpose: The human papillomavirus (HPV) causes cervicovaginal, oral, and anogenital cancer, and cervical cancer screening options include HPV testing of a clinician-collected sample. Transgender and gender diverse (TGD) people assigned female at birth (AFAB) face many barriers to preventive care, including cancer screening. Self-sampling options may increase access and participation in HPV testing and cancer screening. This study estimated the prevalence of HPV in self-collected cervicovaginal, oral, and anal samples from Midwestern TGD individuals AFAB. Methods: We recruited TGD individuals AFAB for an observational study, mailing them materials to self-collect cervicovaginal, oral, and anal samples at home. We tested samples for high-risk (HR; 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59) and other HPV genotypes (6, 11, 66, 68, 73, 90) using a polymerase chain reaction mass array test. Prevalence ratios for HPV infection at each site as a function of participant characteristics were estimated in log-binomial models. Results: Out of 137 consenting participants, 102 completed sample collection. Among those with valid tests, 8.8% (HR = 6.6%; HPV 16/18 = 3.3%) were positive for oral HPV, 30.5% (HR = 26.8%; HPV 16/18 = 9.7%) for cervicovaginal HPV, and 39.6% (HR = 33.3%; HPV 16/18 = 8.3%) for anal HPV. A larger fraction of oral (71.4%) than anal infections (50.0%) were concordant with a cervicovaginal infection of the same type. Conclusions: We detected HR cervicovaginal, oral, and anal HPV in TGD people AFAB. It is essential that we reduce barriers to cancer screening for TGD populations, such as through the development of a clinically approved self-screening HPV test.

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.

Opportunities to Interrupt Transmission of Enteropathogens of Poultry Origin in Maputo, Mozambique: A Transmission Model Analysis

BACKGROUND

The burden of diarrheal diseases remains high among children in low-income countries. Enteropathogens are challenging to control because they are transmitted via multiple pathways. Chickens are an important animal protein source, but live chickens and their products are often highly contaminated with enteropathogens.

OBJECTIVES

We conducted this study to a) understand the contribution of multiple transmission pathways to the force of infection of Campylobacter spp. and nontyphoidal Salmonella spp., b) quantify the potential impact of reducing each pathway on human infection, and c) quantify hypothesized pathway reduction from the context of Maputo, Mozambique.

METHODS

We developed transmission models for Campylobacter and Salmonella that captured person-to-person, water-to-person, food-to-person, soil-to-person, animal-to-person, and all-other-sources-to-person in an urban, low-income setting in Mozambique. We calibrated these models using prevalence data from Maputo, Mozambique and estimates of attributable fraction of transmission pathways for the region. We simulated the prevalence of human infection after reducing transmission through each pathway.

RESULTS

Simulation results indicated that if foodborne transmission were reduced by 90%, the prevalence of Campylobacter and Salmonella infection would decline by [52.2%; 95% credible interval (CrI): 39.7, 63.8] and (46.9%; 95% CrI: 39, 55.4), respectively. Interruption of any other pathway did not have a substantial impact. Combined with survey and microbiology data, if contamination of broiler chicken meat at informal markets in Maputo could be reduced by 90%, the total infection of Campylobacter and Salmonella could be reduced by 21% (16-26%) and 12% (10-13%), respectively.

DISCUSSION

Our transmission models showed that the foodborne transmission has to be reduced to control enteropathogen infections in our study site, and likely in other similar contexts, but mitigation of this transmission pathway has not received sufficient attention. Our model can serve as a tool to identify effective mitigation opportunities to control zoonotic enteropathogens. https://doi.org/10.1289/EHP12314.

Changing patterns of cigarette and ENDS transitions in the USA: a multistate transition analysis of adults in the PATH Study in 2017-2019 vs 2019-2021

Introduction

The use of cigarettes and electronic nicotine delivery system (ENDS) has likely changed since 2019 with the rise of pods and disposables, the outbreak of lung injuries related to vaping THC, flavor bans, and the COVID pandemic. We analyzed patterns of initiation, cessation, and transitions between cigarettes, ENDS, and dual use before and after 2019.

Methods

Using the Population Assessment of Tobacco and Health (PATH) Study, we applied a multistate transition model to 28,061 adults in Waves 4-5 (2017-19) and 24,751 adults in Waves 5-6 (2019-21), estimating transition rates for initiation, cessation, and switching products for each period overall and by age group.

Results

Cigarette initiation among adults who never used either product decreased from 2017-19 to 2019-21, but ENDS initiation did not significantly change. Persistence of ENDS-only use remained high, with 75-80% still using ENDS only after 1 year. Cigarette-only use transitions remained similar, with about 88% remaining, 7% transitioning to non-current use, and 5% transitioning to dual or ENDS-only use. In contrast, dual use to ENDS-only transitions increased from 9.5% (95%CI: 7.3-11.7%) to 20.1% (95%CI: 17.5-22.7%) per year from 2017-19 to 2019-21, decreasing the persistence of dual use. The dual use to cigarette-only transition remained at about 25%. These changes were qualitatively similar across adult age groups, though adults ages 18-24 years exhibited the highest probability of switching from cigarette-only use to dual use and from dual use to ENDS-only use.

Conclusions

Persistence of ENDS use among adults remained high in 2019-21, but a larger fraction of dual users transitioned to ENDS-only use compared to 2017-19. Because the fraction of cigarette-only users switching to dual use remained low, the public health implications of the increased dual use to ENDS-only transition are minimal.

Respiratory virus infections in decedents in a large, urban medical examiner's office

OBJECTIVE

Most respiratory virus surveillance relies on medically attended respiratory illness, but an understanding of the true patterns of infection independent of care-seeking behaviour would enhance clinical and public health responses to respiratory virus outbreaks. We evaluated the potential of decedent surveillance by estimating the burden of respiratory virus infection in decedents in a large, urban medical examiner's office.

STUDY DESIGN

Observational.

METHODS

In 2020-2022, we tested nasopharyngeal swabs from 4121 decedents in Detroit, Michigan for 15 respiratory viruses, including SARS-CoV-2, respiratory syncytial virus, and influenza virus A and B. We analysed infection prevalence over time and by age, sex, race/ethnicity, and manner of death.

RESULTS

Of 4113 valid tests, 30.2% were positive for at least one virus, and 6.1% were positive for multiple viruses. All viruses were detected except for influenza A/H1N1 and influenza B. The most prevalent viruses were SARS-CoV-2 (15.7%), rhinovirus (11.2%), and adenovirus (4.9%), which were detected in all months. Most viruses exhibited decreasing prevalence with age, higher prevalence among Black and Hispanic than among White decedents and lower prevalence among deaths from natural causes; SARS-CoV-2 was a notable exception to the patterns by age and manner of death, instead reflecting community trends in catchment counties.

CONCLUSIONS

There was high prevalence and diversity of respiratory viruses in decedents entering a large, urban medical examiner's office. Decedent surveillance could offer a clearer picture of the true underlying burden of infection, motivating public health priorities for intervention and vaccine development, and augmenting data for real-time response to respiratory virus outbreaks.

Longitudinal and quantitative fecal shedding dynamics of SARS-CoV-2, pepper mild mottle virus, and crAssphage

Wastewater-based epidemiology (WBE) emerged during the coronavirus disease 2019 (COVID-19) pandemic as a scalable and broadly applicable method for community-level monitoring of infectious disease burden. The lack of high-resolution fecal shedding data for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) limits our ability to link WBE measurements to disease burden. In this study, we present longitudinal, quantitative fecal shedding data for SARS-CoV-2 RNA, as well as for the commonly used fecal indicators pepper mild mottle virus (PMMoV) RNA and crAss-like phage (crAssphage) DNA. The shedding trajectories from 48 SARS-CoV-2-infected individuals suggest a highly individualized, dynamic course of SARS-CoV-2 RNA fecal shedding. Of the individuals that provided at least three stool samples spanning more than 14 days, 77% had one or more samples that tested positive for SARS-CoV-2 RNA. We detected PMMoV RNA in at least one sample from all individuals and in 96% (352/367) of samples overall. CrAssphage DNA was detected in at least one sample from 80% (38/48) of individuals and was detected in 48% (179/371) of all samples. The geometric mean concentrations of PMMoV and crAssphage in stool across all individuals were 8.7 × 104 and 1.4 × 104 gene copies/milligram-dry weight, respectively, and crAssphage shedding was more consistent for individuals than PMMoV shedding. These results provide us with a missing link needed to connect laboratory WBE results with mechanistic models, and this will aid in more accurate estimates of COVID-19 burden in sewersheds. Additionally, the PMMoV and crAssphage data are critical for evaluating their utility as fecal strength normalizing measures and for source-tracking applications. IMPORTANCE This research represents a critical step in the advancement of wastewater monitoring for public health. To date, mechanistic materials balance modeling of wastewater-based epidemiology has relied on SARS-CoV-2 fecal shedding estimates from small-scale clinical reports or meta-analyses of research using a wide range of analytical methodologies. Additionally, previous SARS-CoV-2 fecal shedding data have not contained sufficient methodological information for building accurate materials balance models. Like SARS-CoV-2, fecal shedding of PMMoV and crAssphage has been understudied to date. The data presented here provide externally valid and longitudinal fecal shedding data for SARS-CoV-2, PMMoV, and crAssphage which can be directly applied to WBE models and ultimately increase the utility of WBE.

Prevalence and determinants of cervicovaginal, oral, and anal HPV infection in a population of transgender and gender diverse people assigned female at birth

Introduction

HPV causes oral, cervicovaginal, and anogenital cancer, and cervical cancer screening options include HPV testing of a physician-collected sample. Transgender and gender diverse (TGD) people assigned female at birth (AFAB) face discrimination and stigma in many healthcare settings; are believed to be a lower risk for cervical cancer by many physicians; are less likely to be up to date on preventive health care services such as pelvic health exams; and are more likely to have inadequate results from screening tests. Self-sampling options may increase access and participation in HPV testing and cancer screening.

Methods

We recruited 137 TGD individuals AFAB for an observational study, mailing them a kit to self-collect cervicovaginal, oral, and anal samples at home. We tested samples for HPV genotypes 6, 11, 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, 68, 73 and 90 using a PCR mass array test.

Results

102 participants completed the study. Among those with valid tests, 8.8% were positive for oral HPV, 30.5% were positive for cervicovaginal HPV, and 39.6% were positive for anal HPV. A large fraction of anal (50.0%) and oral (71.4%) infections were concordant with a cervicovaginal infection of the same type.

Conclusions

HPV infection in TGD people AFAB may be just as high, if not higher, than in cisgender women. It is essential that we reduce barriers to cancer screening for TGD populations, such as through the development of a clinically approved self-screening HPV test.

Cervicovaginal and anal self-sampling for HPV testing in a transgender and gender diverse population assigned female at birth: comfort, difficulty, and willingness to use

Background

Transgender and gender diverse (TGD) people assigned female at birth (AFAB) face numerous barriers to preventive care, including for HPV and cervical cancer screening. Self-sampling options may expand access to HPV testing for TGD people AFAB.

Methods

We recruited TGD individuals AFAB to collect cervicovaginal and anal specimens at-home using self-sampling for HPV testing, and individuals reported their perceptions of self-sampling. Associations between demographic and health characteristics and each of comfort of use, ease of use, and willingness to use self-sampling were estimated using robust Poisson regression.

Results

The majority of the 101 participants who completed the study reported that the cervicovaginal self-swab was not uncomfortable (68.3%) and not difficult to use (86.1%), and nearly all (96.0%) were willing to use the swab in the future. Fewer participants found the anal swab to not be uncomfortable (47.5%), but most participants still found the anal swab to not be difficult to use (70.2%) and were willing to use the swab in the future (89.1%). Participants were more willing to use either swab if they had not seen a medical professional in the past year. About 70% of participants who reported negative experiences with either self-swab were still willing to use that swab in the future.

Conclusions

TGD AFAB individuals were willing to use and preferred self-sampling methods for cervicovaginal and anal HPV testing. Developing clinically approved self-sampling options for cancer screening could expand access to HPV screening for TGD AFAB populations.

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.

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.

Long-term projections of the impacts of warming temperatures on Zika and dengue risk in four Brazilian cities using a temperature-dependent basic reproduction number

For vector-borne diseases the basic reproduction number [Formula: see text], a measure of a disease's epidemic potential, is highly temperature-dependent. Recent work characterizing these temperature dependencies has highlighted how climate change may impact geographic disease spread. We extend this prior work by examining how newly emerging diseases, like Zika, will be impacted by specific future climate change scenarios in four diverse regions of Brazil, a country that has been profoundly impacted by Zika. We estimated a [Formula: see text], derived from a compartmental transmission model, characterizing Zika (and, for comparison, dengue) transmission potential as a function of temperature-dependent biological parameters specific to Aedes aegypti. We obtained historical temperature data for the five-year period 2015-2019 and projections for 2045-2049 by fitting cubic spline interpolations to data from simulated atmospheric data provided by the CMIP-6 project (specifically, generated by the GFDL-ESM4 model), which provides projections under four Shared Socioeconomic Pathways (SSP). These four SSP scenarios correspond to varying levels of climate change severity. We applied this approach to four Brazilian cities (Manaus, Recife, Rio de Janeiro, and São Paulo) that represent diverse climatic regions. Our model predicts that the [Formula: see text] for Zika peaks at 2.7 around 30°C, while for dengue it peaks at 6.8 around 31°C. We find that the epidemic potential of Zika will increase beyond current levels in Brazil in all of the climate scenarios. For Manaus, we predict that the annual [Formula: see text] range will increase from 2.1-2.5, to 2.3-2.7, for Recife we project an increase from 0.4-1.9 to 0.6-2.3, for Rio de Janeiro from 0-1.9 to 0-2.3, and for São Paulo from 0-0.3 to 0-0.7. As Zika immunity wanes and temperatures increase, there will be increasing epidemic potential and longer transmission seasons, especially in regions where transmission is currently marginal. Surveillance systems should be implemented and sustained for early detection.

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.

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.

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 R 0 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 R 0 s 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.

Structural identifiability of compartmental models for infectious disease transmission is influenced by data type

If model identifiability is not confirmed, inferences from infectious disease transmission models may not be reliable, so they might result in misleading recommendations. Structural identifiability analysis characterises whether it is possible to obtain unique solutions for all unknown model parameters, given the model structure. In this work, we studied the structural identifiability of some typical deterministic compartmental models for infectious disease transmission, focusing on the influence of the data type considered as model output on the identifiability of unknown model parameters, including initial conditions. We defined 26 model versions, each having a unique combination of underlying compartmental structure and data type(s) considered as model output(s). Four compartmental model structures and three common data types in disease surveillance (incidence, prevalence and detected vector counts) were studied. The structural identifiability of some parameters varied depending on the type of model output. In general, models with multiple data types as outputs had more structurally identifiable parameters, than did models with a single data type as output. This study highlights the importance of a careful consideration of data types as an integral part of the inference process with compartmental infectious disease transmission models.

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.

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.

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.

Sociodemographic Survival Disparities for Lung Cancer in the United States, 2000-2016

BACKGROUND

Understanding the impact of patient and tumor characteristics on lung cancer survival can help build personalized prognostic models and identify health disparities.

METHODS

We identified 557 555 patients aged 25 years and older diagnosed with lung or bronchus carcinoma from the Surveillance, Epidemiology, and End Results database, 2000-2016. We estimated hazard ratios (HR) for demographic (sex, age, race and ethnicity), tumor (stage, histology, year of diagnosis), and geographic characteristics (census tract-level urbanicity, socioeconomic status [SES]), as well as selected interactions, on the rate of lung cancer-specific death using multivariable proportional hazards models.

RESULTS

Women had a higher survival (lower hazard) of lung cancer-specific death than men (HR = 0.83, 95% confidence interval [CI] = 0.82 to 0.83). Hazards differed by race and ethnicity. Regional (HR = 2.41, 95% CI = 2.37 to 2.44) and distant (HR = 6.61, 95% CI = 6.53 to 6.69) tumors were associated with a lower survival (higher hazard) than localized tumors. Small cell tumors were associated with a lower survival (HR = 1.19, 95% CI = 1.18 to 1.20) than non-small cell tumors. Patients diagnosed after 2009 had lower hazards (HR = 0.86, 95% CI = 085 to 0.86) than those diagnosed 2000-2009. Lung cancer-specific survival did not depend on urbanicity after adjusting for census tract-level SES, but survival decreased with decreasing census tract-level SES. Differences in survival between non-Hispanic Black and White patients were greater for younger patients and localized tumors and increased with census tract-level SES. Differences by sex were greatest for young patients and localized tumors.

CONCLUSIONS

Disparities in survival after lung cancer diagnosis remain, with intersectional patterns suggesting differential access to and quality of care. Efforts are needed to ensure that high-risk groups receive guideline-concordant treatment.

Prevalence and determinants of oral and cervicogenital HPV infection: Baseline analysis of the Michigan HPV and Oropharyngeal Cancer (MHOC) cohort study

We determined baseline oral and cervicogenital human papillomavirus (HPV) prevalence and determinants of infection in the Michigan HPV and Oropharyngeal Cancer (MHOC) study. We enrolled 394 college-age and older participants of both sexes in Ann Arbor, Michigan and the surrounding area. All participants provided an oral sample at baseline, and 130 females provided a cervicogenital sample. Samples were tested for 18 HPV genotypes using polymerase chain reaction (PCR) MassArray. Participants filled out sociodemographic and behavioral questionnaires. Prevalence ratios for HPV oral or cervicogenital prevalence by predictor variables were estimated in univariable log-binomial models. Analysis was conducted 2018–20. In the full cohort, baseline oral HPV prevalence was 10.0% for any detected genotype (among the 338 valid oral tests at baseline) and 6.5% for high-risk types, and cervicogenital prevalence was 20.0% and 10.8%, respectively (among the 130 first valid cervicogenital tests). Oral HPV prevalence did not vary by sex, with 10.5% of women and 9.0% of men having an infection. We found a high prevalence of oral and cervicogenital HPV infection in college-age participants reporting no lifetime sexual partners. Reporting a single recent partner was associated with a lower oral HPV prevalence (PR 0.39, 95% CI: 0.16, 0.96) than reporting no recent (but at least one ever) partner. No similar protective effect was seen for cervicogenital HPV. Both oral and cervicogenital prevalence increased with the number of recent partners for most sexual behaviors. We observed an ecological fallacy masking the direction of impact of vaccination on HPV prevalence in the full cohort compared to the college-aged and the age 23+ populations considered separately. Substance use was not significantly associated with oral or cervicogenital HPV infection. Many studies report substantially higher oral HPV infection prevalence in men than in women. That difference may not be uniform across populations in the US.

The role of time-varying viral shedding in modelling environmental surveillance for public health: revisiting the 2013 poliovirus outbreak in Israel

Environmental pathogen surveillance is a sensitive tool that can detect early-stage outbreaks, and it is being used to track poliovirus and other pathogens. However, interpretation of longitudinal environmental surveillance signals is difficult because the relationship between infection incidence and viral load in wastewater depends on time-varying shedding intensity. We developed a mathematical model of time-varying poliovirus shedding intensity consistent with expert opinion across a range of immunization states. Incorporating this shedding model into an infectious disease transmission model, we analysed quantitative, polymerase chain reaction data from seven sites during the 2013 Israeli poliovirus outbreak. Compared to a constant shedding model, our time-varying shedding model estimated a slower peak (four weeks later), with more of the population reached by a vaccination campaign before infection and a lower cumulative incidence. We also estimated the population shed virus for an average of 29 days (95% CI 28-31), longer than expert opinion had suggested for a population that was purported to have received three or more inactivated polio vaccine (IPV) doses. One explanation is that IPV may not substantially affect shedding duration. Using realistic models of time-varying shedding coupled with longitudinal environmental surveillance may improve our understanding of outbreak dynamics of poliovirus, SARS-CoV-2, or other pathogens.

Oral human papillomavirus prevalence, persistence, and risk-factors in HIV-positive and HIV-negative adults

Background

HIV has been shown to increase the likelihood of oral HPV infection. In this study, we evaluated the risk of oral HPV in HIV infected patients compared with HIV-negative controls.

Methods

101 healthy adult volunteers (HIV-) and 245 adults living with HIV infection (HIV+) were recruited from 5 academic medical centers. Questionnaires and saliva samples were obtained every 3–8 months over a period of 2 years (2015–2017). DNA was isolated from the saliva samples and tested for 18 high- and low-risk genotypes.

Results

Oral HPV was detected in 23% of HIV + vs. 10% of HIV- participants (p < 0.0001). Men had a higher oral HPV prevalence than women (27% vs. 15% HIV+, p = 0.03, 16% vs. 5% HIV-, p = 0.01). Risk factors among HIV + participants included more lifetime deep kissing and oral sex partners, and history of AIDS. Persistent oral HPV was detected in 23% of HIV + vs. 5% of HIV- participants (p < 0.001). Among 8 HIV + participants with CD4 counts <200 cell/μL none had cleared their HPV infection during the study.

Conclusions

Risk of oral HPV infection and persistence was significantly higher in HIV + adults with a history of poorly controlled HIV, which may put them at increased risk of HPV-associated cancer.

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.

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.

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.

Abstract GS4-06: Estimation of breast cancer overdiagnosis in a US breast screening cohort

Background. Breast cancer screening is subject to overdiagnosis, that is the mammographic detection of cancers that would not become symptomatic or otherwise cause harm in the absence of screening. The risk of overdiagnosis associated with screening mammography is a concern but there is no consensus about its magnitude. Estimates based on excess incidence are prone to bias, and estimates based on models have been criticized for not explicitly accommodating indolent tumors. Methods. We obtained individual mammography screening and breast cancer diagnosis records from the Breast Cancer Surveillance Consortium (BCSC), an authoritative data source in the US. Women aged 50-74 years who had their first mammogram in the BCSC between 2000-2018 were included. We fit a mathematical model that accounts for the transition from healthy to preclinical and clinical disease while allowing for a fraction of indolent preclinical tumors. We performed Bayesian inference using the Hamiltonian Monte Carlo sampler Stan to estimate model parameters and predict overdiagnosis rates under biennial and annual screening between ages 50 and 74. We defined the breast cancer overdiagnosis rate as the fraction of screen-detected cancers that would not have been symptomatically detected in the woman’s remaining lifetime. Overdiagnosis arises from two possible scenarios: the screen-detection of indolent cancers, and the screen-detection of progressive cancers that do not progress to clinical disease before the woman dies from causes unrelated to breast cancer. To calculate the second contribution, we determined the risk of other-cause death using age-cohort-adjusted annual mortality risks. Results. The analytic cohort included 35,986 women, 82,677 screens and 718 breast cancer diagnoses. The mean fraction of indolent cancers among all preclinical cases (detected and undetected) was 3.6% (95% credible interval [CI]: 0.2% to 13.8%), the mean preclinical sojourn time was 6.5 years (CI: 4.9 to 8.6) and the mean test sensitivity was 81.7% (CI: 72.6% to 89.0%). For a program of biennial screening from age 50 to 74, the predicted overdiagnosis rate among screen-detected cases was 15.3% (95% prediction interval [PI]: 9.7% to 25.2%), where 6.0% (PI: 0.2% to 19.0%) was due to the detection of indolent cancers and 9.3% (PI: 5.8%-13.6%) was due to competing mortality. For a program of annual screening from age 50 to 74, the overall predicted overdiagnosis rate was 14.6% (PI: 9.4% to 23.9%). Discussion. Our results indicate that overdiagnosis among screen-detected cancers is less frequent than estimated by excess-incidence studies and more frequent than estimated by previous modeling studies that did not account for indolent tumors.

Citation Format: Marc D Ryser, Jane Lange, Lurdes Inoue, Ellen S O'Meara, Charlotte Gard, Diana L Miglioretti, Jean-Luc Bulliard, Andrew F Brouwer, E. Shelley Hwang, Ruth B Etzioni. Estimation of breast cancer overdiagnosis in a US breast screening cohort [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr GS4-06.

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.

Incidence and clearance of oral and cervicogenital HPV infection: longitudinal analysis of the MHOC cohort study

OBJECTIVES

The Michigan HPV and Oropharyngeal Cancer study aimed to evaluate patterns of oral and cervicogenital human papillomavirus (HPV) infection prevalence, incidence, and clearance as well as their relationship to sexual behaviours.

DESIGN

Cohort SETTING: General public in and around Ann Arbor, Michigan.

PARTICIPANTS

394 college-age and older-adult participants of both sexes provided oral samples, and 325 completed at least 2 visits. 130 who provided a cervicogenital samples, and 127 completed at least 2 visits.

OUTCOMES

Incidence and clearance rates as well as HRs for oral and cervicogenital HPV.

RESULTS

Oral HPV infections were transient, with only 16% of genotypes persisting to the next visit. The mean time to clearance of a genotype was 46 days (95% CI 37 to 58). In contrast, cervicogenital infections were more persistent, with 56% of genotypes persisting to the next visit. The mean time to clearance of a genotype was 87 days (95% CI 74 to 102). HPV vaccination was associated with reduced incidence of cervicogenital HPV infection (HR 0.63; 95% CI 0.47 to 0.83) but not oral HPV infection. Incidence of oral HPV infection was associated with 2+ recent deep kissing partners (HR 2.00; 95% CI 1.13 to 3.56). Incidence of both oral (HR: 1.70; 95% CI 1.08 to 2.68) and cervicogenital (HR 2.46; 95% CI 1.69 to 3.59) was associated with 2+ recent sexual partners.

CONCLUSIONS

Detection of oral HPV was highly transient, but incidence was associated with recent deep kissing and sexual partners. Detection of cervicogenital HPV was more persistent, and incidence was positively associated with recent sexual partners and negatively associated with HPV vaccination.

Estimating vaccination threshold and impact in the 2017-2019 hepatitis A virus outbreak among persons experiencing homelessness or who use drugs in Louisville, Kentucky, United States

BACKGROUND

Between September 2017 and June 2019, an outbreak of hepatitis A virus (HAV) occurred in Louisville, Kentucky, resulting in 501 cases and 6 deaths, predominantly among persons who experience homelessness or who use drugs (PEH/PWUD). The critical vaccination threshold (Vc) required to achieve herd immunity in this population is unknown. We investigated Vc and vaccination impact using epidemic modeling.

METHODS

To determine which population subgroups had high infection risks, we employed a technique based on comparing the proportion of cases arising before and after the epidemic peak, across subgroups. We also developed a dynamic deterministic model of HAV transmission among PEH/PWUD to estimate the basic reproduction number (R0), herd immunity threshold, Vc and the effect of timing of the vaccination intervention on epidemic and economic outcomes.

RESULTS

Of the 501 confirmed or probable cases, 385 (76.8%) were among PEH/PWUD. Among PEH/PWUD and within the general population, homelessness was a significant risk factor for infection in the initial stages of the outbreak (odds ratios for homeless versus not homeless: 2.62; 95% confidence interval (CI): 1.62-4.25 for PEH/PWUD and 2.39; 95% CI: 1.51-3.78 for all detected cases). Our estimate for R0 ranges between 2.85 and 3.54, corresponding to an estimate of 69% (95% CI: 65-72) for herd immunity threshold and 76% (95% CI: 72%-80%) for Vc, assuming a vaccine with 90% efficacy. The observed vaccination program was estimated to have averted 30 hospitalizations (95% CI: 19-43), associated with over US$490 000 (95% CI: $310 000-700 000) in hospitalization cost. Greater impact was observed with earlier and faster vaccination implementation.

CONCLUSIONS

Vaccination coverage of at least 77% is likely required to prevent outbreaks of HAV among PEH/PWUD in Louisville, assuming a 90% vaccine efficacy. Proactive hepatitis A vaccination programs among PEH/PWUD will maximize health and economic benefits of these programs and reduce the likelihood of another outbreak.

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.

Comparison of e-cigarette use prevalence and frequency by smoking status among youth in the United States, 2014-19

BACKGROUND AND AIMS

Reports of youth e-cigarette use often do not disaggregate by underlying smoking status. This study compared annual 2014-19 youth estimates of past 30-day e-cigarette use prevalence and frequency by smoking status in the United States.

DESIGN

Nationally representative, cross-sectional, school-based survey [National Youth Tobacco Surveys (NYTS)]. General linear models accounting for complex survey design compared e-cigarette use prevalence by smoking status by year, overall and stratified by frequency, separately for high school (HS) and middle school (MS) students. The 2019 survey was analyzed separately because of its change in survey methodology.

SETTING

MSs and HSs in the United States.

PARTICIPANTS

A total of 116 704 students from 1268 schools, ages 9-19.

MEASUREMENTS

Students self-reported (paper 2014-18, electronic 2019) ever and past 30-day (current) use of e-cigarettes and cigarettes, as well as frequent use (20-30 days of month).

FINDINGS

From 2014 to 2018, current e-cigarette use prevalence increased among never, current and former smokers in HS, but only among never and current smokers in MS (each P-value < 0.001). E-cigarette use increases for current HS smokers were primarily among frequent e-cigarette users. In 2018, the absolute number of HS frequent users who were never or former smokers (420 000 combined) surpassed current smokers (370 000). In 2019, current e-cigarette use prevalence for never, former and current smokers was 17.5% [95% confidence interval (CI) = 16.0-19.0], 53.6% (95% CI = 45.2-61.9) and 85.8% (95% CI = 81.6-89.9) for HS students, respectively, and 6.8% (95% CI = 5.9-7.7), 40.8% (95% CI = 34.7-47.0) and 78.0% (95% CI = 71.9-84.2) for MS students. That year, the number of HS never (420 000) and former smokers (570 000) using e-cigarettes frequently eclipsed that of current smokers (390 000).

CONCLUSIONS

E-cigarette use prevalence and frequency among youth vary by smoking status, with highest levels of use among current smokers. However frequent e-cigarette use among never smokers and former smokers has increased.

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

Background

SARS-CoV-2 has become a global pandemic. Given the challenges in implementing widespread SARS-CoV-2 testing, 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 by a COVID-19 checklist, and decedents flagged by the checklist (298) were preferentially tested. A random sample of decedents not flagged by the checklist were also tested (796). We statistically analyzed the characteristics of decedents (age, sex, race, and manner of death), differentiating between those flagged by 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 to 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). 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: despite no statistical difference in the racial distribution between those flagged and not, SARS-CoV-2 positive decedents were substantially more likely to be Black (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 may serve as a possible early outbreak warning sign.

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.

Transitions between cigarette, ENDS and dual use in adults in the PATH study (waves 1-4): multistate transition modelling accounting for complex survey design

INTRODUCTION

Even prior to 2018, electronic nicotine delivery systems (ENDS) began to dramatically change the landscape of tobacco products and product use patterns in the USA.

METHODS

Using a Markov multistate transition model accounting for complex survey design, transition rates between never, non-current, cigarette, ENDS and dual use states were estimated for 23 253 adult participants in waves 1-4 (approximately 2013-2017) of the Population Assessment of Tobacco and Health study. We made short-term transition projections and estimated HRs for age, sex, race/ethnicity, education and income.

RESULTS

Cigarette use was persistent among adults, with 89.7% (95% CI 89.1% to 90.3%) of exclusive cigarette users and 86.1% (95% CI 84.4% to 87.9%) of dual users remaining cigarette users (either exclusive or dual) after one wave. In contrast, ENDS use was less persistent, with 72.1% (95% CI 69.6% to 74.6%) of exclusive ENDS users and 50.5% (95% CI 47.8% to 53.3%) of dual users remaining ENDS users (with or without cigarettes) after one wave. Exclusive ENDS users were more likely to start cigarette use after one wave than either never users (HR 25.2; 95% CI 20.9 to 30.5) or non-current users (HR 5.0; 95% CI 4.3 to 5.8). Dual users of ENDS and cigarettes were more likely to stop using cigarettes than exclusive cigarette users (HR 1.9; 95% CI 1.6 to 2.3). Transition rates varied among sociodemographic groups.

CONCLUSIONS

Multistate transition models are an effective tool for uncovering and characterising longitudinal patterns and determinants of tobacco use from complex survey data. ENDS use among US adults was less persistent than cigarette use prior to 2018.

The Impact of Vaccination Efforts on the Spatiotemporal Patterns of the Hepatitis A Outbreak in Michigan, 2016-2018

BACKGROUND

The United States is currently experiencing the largest hepatitis A virus (HAV) outbreak since the introduction of a vaccine in 1996. More than 31,000 cases have been reported since 2016. Although HAV had largely been considered a foodborne pathogen in recent years, this outbreak has been spread primarily through person-to-person transmission in urban settings and has been associated with homelessness and substance use. Michigan was one of the first states to report an outbreak, with 910 reported cases between August 2016 and December 2018.

METHODS

We analyzed surveillance and vaccination data from Michigan using a disease transmission model to investigate how vaccine timing and coverage influenced the spatiotemporal patterns of the outbreak, distinguishing between Southeast Michigan, where the outbreak began, and the rest of the state.

RESULTS

We estimated that vaccination had little impact in Southeast Michigan (3% cases averted [95% confidence interval (CI) = 1%, 8%]) but had a substantial impact in the rest of the state, preventing a larger outbreak (91% cases averted [95% CI = 85%, 97%]) lasting several more years.

CONCLUSIONS

Our results emphasize the value of targeting populations where local transmission is not yet sustained rather than populations where transmission is already waning. Simulation modeling can aid in proactive rather than reactive decision-making and may help direct the response to outbreaks emerging in other states. See video abstract: http://links.lww.com/EDE/B704.

Integrating measures of viral prevalence and seroprevalence: a mechanistic modelling approach to explaining cohort patterns of human papillomavirus in women in the USA

Incidence of human papillomavirus (HPV) related cancers is increasing, generating substantial interest in understanding how trends in population prevalence of HPV infection are changing. However, there are no direct, population-scale measurements of HPV prevalence prior to 2003. Previous work using models to reconstruct historical trends have focused only on genital infection or seroprevalence (prevalence of antibodies) separately, and the results of these single-measure studies have been hard to reconcile. Here, we develop a mechanistic disease model fit jointly to cervicogential prevalence and seroprevalence in unvaccinated women in the USA using National Health and Nutrition Examination Survey data (2003-2010) and compare it to fits of statistical age-cohort models. We find that including a latent HPV state in our model significantly improves model fit and that antibody waning may be an important contributor to observed patterns of seroprevalence. Moreover, we find that the mechanistic model outperforms the statistical model and that the joint analysis prevents the inconsistencies that arise when estimating historical cohort trends in infection from genital prevalence and seroprevalence separately. Our analysis suggests that while there is substantial uncertainty associated with the estimation of historic HPV trends, there has likely been an increase in the force of infection for more recent birth cohorts. This article is part of the theme issue 'Silent cancer agents: multi-disciplinary modelling of human DNA oncoviruses'.

Case Studies of Gastric, Lung, and Oral Cancer Connect Etiologic Agent Prevalence to Cancer Incidence

Obtaining detailed individual-level data on both exposure and cancer outcomes is challenging, and it is difficult to understand and characterize how temporal aspects of exposures translate into cancer risk. We show that, in lieu of individual-level information, population-level data on cancer incidence and etiologic agent prevalence can be leveraged to investigate cancer mechanisms and to better characterize and predict cancer trends. We use mechanistic carcinogenesis models [multistage clonal expansion (MSCE) models] and data on smoking, Helicobacter pylori (H. pylori), and HPV infection prevalence to investigate trends of lung, gastric, and HPV-related oropharyngeal cancers. MSCE models are based on the initiation-promotion-malignant conversion paradigm and allow for interpretation of trends in terms of general biological mechanisms. We assumed the rates of initiation depend on the prevalence of the corresponding risk factors. We performed two types of analysis, using the agent prevalence and cancer incidence data to estimate the model parameters and using cancer incidence data to infer the etiologic agent prevalence as well as the model parameters. By including risk factor prevalence, MSCE models with as few as three parameters closely reproduced 40 years of age-specific cancer incidence data. We recovered trends of H. pylori prevalence in the United States and demonstrated that cohort effects can explain the observed bimodal, age-specific pattern of oral HPV prevalence in men. Our results demonstrate the potential for joint analyses of population-level cancer and risk factor data through mechanistic modeling. This approach can be a first step in systematically testing relationships between exposures and cancer risk when individual-level data is lacking.Significance: Analysis of trends in risk-factor prevalence and cancer incidence can shed light on cancer mechanisms and the way that carcinogen exposure through time shapes the risk of cancer at different ages.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/12/3386/F1.large.jpg Cancer Res; 78(12); 3386-96. ©2018 AACR.

HPV vaccination has not increased sexual activity or accelerated sexual debut in a college-aged cohort of men and women

Background

The human papillomavirus (HPV) is the most common sexually transmitted infection and is linked to several types of cancer. HPV vaccination uptake in the U.S. is relatively low, despite the vaccine’s high efficacy. Some parents of adolescents have concerns that vaccination will encourage sexual behavior and therefore choose not to vaccinate. Previous studies investigating vaccination and sexual behavior have included only young women and girls.

Methods

The objective of this study is to assess associations between HPV-vaccination and sexual behavior in a college-age cohort of both men and women. We analyzed questionnaire data collected from the Michigan HPV and Oropharyngeal Cancer Study, a cohort study designed to investigate HPV infection and its association with sexual behavior (data collected 2015–17, Ann Arbor, MI). Here, we consider vaccination status, sexual behavior, and substance use among 241 college-aged men and women. Logistic, Poisson, and Cox regression were used to determine the relationship between probability of sexual debut, number of sexual partners, and HPV vaccination status at baseline as well as between age at sexual debut and vaccination status at debut.

Results

HPV vaccination status was not significantly associated with an increased likelihood of sexual debut (odds ratio: 0.80 (95% CI: 0.41–1.58), decreased age of sexual debut (hazard ratio: 0.81 (95% CI: 0.65–1.00), nor an increased number of sexual partners (per year sexually active; incidence rate ratio: 1.27 (95% CI: 0.86–1.87)) in this cohort, after controlling for age, race, sex, and substance use. Instead, race or alcohol use were independent predictors of sexual behavior.

Conclusions

Concerns about the influence of the HPV vaccine on sexual behavior are likely unfounded for both men and women. These results can aid in increasing vaccine acceptability, inform and strengthen physician recommendations, and ultimately reduce the burden of HPV and HPV-related cancers in the U.S.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-7134-1) contains supplementary material, which is available to authorized users.

Quantitative Microbial Risk Assessment and Infectious Disease Transmission Modeling of Waterborne Enteric Pathogens

PURPOSE OF REVIEW

Waterborne enteric pathogens remain a global health threat. Increasingly, quantitative microbial risk assessment (QMRA) and infectious disease transmission modeling (IDTM) are used to assess waterborne pathogen risks and evaluate mitigation. These modeling efforts, however, have largely been conducted independently for different purposes and in different settings. In this review, we examine the settings where each modeling strategy is employed.

RECENT FINDINGS

QMRA research has focused on food contamination and recreational water in high-income countries (HICs) and drinking water and wastewater in low- and middle-income countries (LMICs). IDTM research has focused on large outbreaks (predominately LMICs) and vaccine-preventable diseases (LMICs and HICs). Human ecology determines the niches that pathogens exploit, leading researchers to focus on different risk assessment research strategies in different settings. To enhance risk modeling, QMRA and IDTM approaches should be integrated to include dynamics of pathogens in the environment and pathogen transmission through populations.

Multisite HPV infections in the United States (NHANES 2003-2014): An overview and synthesis

HPV is the most common sexually transmitted infection in the U.S., infecting both anogenital and oral sites. Nationally representative data are collected through the National Health and Nutrition Examination Survey (NHANES). However, changing designations of HPV genotypes as high or low risk and varying underlying populations as new results are reported have made direct comparison of results difficult. We reanalyzed HPV data from NHANES derived from self-collected cervicovaginal swabs (women ages 18-59, 2003-14), penile swabs (men ages 18-59, 2013-14), and oral rinses (men and women ages 18-69, 2009-14), using consistent populations and definitions across NHANES cycles. These data strengthen our understanding of age trends in HPV prevalence: cervicovaginal prevalence decreases with age, penile prevalence increases with age, and oral prevalence is bimodal but with an earlier first peak in women. There is strong evidence for reduced prevalence of vaccine genotypes (6, 11, 16, 18) in vaccinated men and women (ages 18-24) at both genital (RR 0.2 (0.1-0.3) in women and 0.7 (0.1-5.4) in men) and oral sites (RR 0.1 (0.0-1.3) in women; no infections detected in vaccinated men). A more complete picture of the burden of HPV in the U.S. is emerging, including evidence for reduced HPV genital and oral prevalence in vaccinated individuals.

Phenotypic variations in persistence and infectivity between and within environmentally transmitted pathogen populations impact population-level epidemic dynamics

BACKGROUND

Human pathogens transmitted through environmental pathways are subject to stress and pressures outside of the host. These pressures may cause pathogen pathovars to diverge in their environmental persistence and their infectivity on an evolutionary time-scale. On a shorter time-scale, a single-genotype pathogen population may display wide variation in persistence times and exhibit biphasic decay.

METHODS

We use a transmission modeling framework to develop an infectious disease model with biphasic pathogen decay. We take a differential algebra approach to assessing model identifiability, calculate basic reproduction numbers by the next generation method, and use simulation to explore model dynamics.

RESULTS

For both long and short time-scales, we demonstrate that epidemic-potential-preserving trade-offs have implications for epidemic dynamics: less infectious, more persistent pathogens cause epidemics to progress more slowly than more infectious, less persistent (labile) pathogens, even when the overall risk is the same. Using identifiability analysis, we show that the usual disease surveillance data does not sufficiently inform these underlying pathogen population dynamics, even when combined with basic environmental monitoring data. However, risk could be indirectly ascertained by developing methods to separately monitor labile and persistent subpopulations. Alternatively, determining the relative infectivity of persistent pathogen subpopulations and the rates of phenotypic conversion will help ascertain how much disease risk is associated with the long tails of biphasic decay.

CONCLUSION

A better understanding of persistence-infectivity trade-offs and associated dynamics can improve our ecological understanding of environmentally transmitted pathogens, as well as our risk assessment and disease control strategies.

Dynamics and Determinants of HPV Infection: The Michigan HPV and Oropharyngeal Cancer (M-HOC) Study

INTRODUCTION

Human papillomavirus (HPV) is the primary cause of cervical and other anogenital cancers and is also associated with head and neck cancers. Incidence of HPV-related oropharyngeal squamous cell cancers (OPSCCs) is increasing, and HPV-related OPSCCs have surpassed cervical cancer as the most common HPV-related cancer in the USA. Given the multisite nature of HPV, there is strong interest in collecting data from both genital and oral sites, as well as associated data on social and sexual behaviours. The overarching goal of this study is to evaluate patterns of oral HPV infection incidence, clearance and persistence and their relationship to sexual behaviour history.

METHODS AND ANALYSIS

Participants are recruited from two populations: college students at a large public university and general population from the surrounding area. At the first study visit, participants complete a detailed sexual history, health and behaviour questionnaire. Follow-up visits occur every 3-4 months over 3 years, when participants complete an abbreviated questionnaire. All participants provide a saliva sample at each visit, and eligible participants may provide a cervicovaginal self-swab. Genetic material isolated from specimens is tested for 15 high-risk and 3 low-risk HPV types. Statistical analyses will examine outcome variables including HPV prevalence, incidence, persistence and clearance. Logistic regression models will be used to estimate odds ratios and 95% confidence intervals for associations between the outcomes of interest and demographic/behavioural variables collected in the questionnaires. The longitudinal HPV infection data and detailed sexual history data collected in the questionnaires will allow us to develop individual-based network models of HPV transmission and will be used to parameterise multiscale models of HPV-related OPSC carcinogenesis.

ETHICS AND DISSEMINATION

This study has been approved by the University of Michigan Institutional Review Board. All participants are consented in person by trained study staff. Study results will be disseminated through peer-reviewed publications.

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.

A Systematic Approach to Determining the Identifiability of Multistage Carcinogenesis Models

Multistage clonal expansion (MSCE) models of carcinogenesis are continuous-time Markov process models often used to relate cancer incidence to biological mechanism. Identifiability analysis determines what model parameter combinations can, theoretically, be estimated from given data. We use a systematic approach, based on differential algebra methods traditionally used for deterministic ordinary differential equation (ODE) models, to determine identifiable combinations for a generalized subclass of MSCE models with any number of preinitation stages and one clonal expansion. Additionally, we determine the identifiable combinations of the generalized MSCE model with up to four clonal expansion stages, and conjecture the results for any number of clonal expansion stages. The results improve upon previous work in a number of ways and provide a framework to find the identifiable combinations for further variations on the MSCE models. Finally, our approach, which takes advantage of the Kolmogorov backward equations for the probability generating functions of the Markov process, demonstrates that identifiability methods used in engineering and mathematics for systems of ODEs can be applied to continuous-time Markov processes.

Dose-response relationships for environmentally mediated infectious disease transmission models

Environmentally mediated infectious disease transmission models provide a mechanistic approach to examining environmental interventions for outbreaks, such as water treatment or surface decontamination. The shift from the classical SIR framework to one incorporating the environment requires codifying the relationship between exposure to environmental pathogens and infection, i.e. the dose-response relationship. Much of the work characterizing the functional forms of dose-response relationships has used statistical fit to experimental data. However, there has been little research examining the consequences of the choice of functional form in the context of transmission dynamics. To this end, we identify four properties of dose-response functions that should be considered when selecting a functional form: low-dose linearity, scalability, concavity, and whether it is a single-hit model. We find that i) middle- and high-dose data do not constrain the low-dose response, and different dose-response forms that are equally plausible given the data can lead to significant differences in simulated outbreak dynamics; ii) the choice of how to aggregate continuous exposure into discrete doses can impact the modeled force of infection; iii) low-dose linear, concave functions allow the basic reproduction number to control global dynamics; and iv) identifiability analysis offers a way to manage multiple sources of uncertainty and leverage environmental monitoring to make inference about infectivity. By applying an environmentally mediated infectious disease model to the 1993 Milwaukee Cryptosporidium outbreak, we demonstrate that environmental monitoring allows for inference regarding the infectivity of the pathogen and thus improves our ability to identify outbreak characteristics such as pathogen strain.

Parameter estimation for multistage clonal expansion models from cancer incidence data: A practical identifiability analysis

Many cancers are understood to be the product of multiple somatic mutations or other rate-limiting events. Multistage clonal expansion (MSCE) models are a class of continuous-time Markov chain models that capture the multi-hit initiation–promotion–malignant-conversion hypothesis of carcinogenesis. These models have been used broadly to investigate the epidemiology of many cancers, assess the impact of carcinogen exposures on cancer risk, and evaluate the potential impact of cancer prevention and control strategies on cancer rates. Structural identifiability (the analysis of the maximum parametric information available for a model given perfectly measured data) of certain MSCE models has been previously investigated. However, structural identifiability is a theoretical property and does not address the limitations of real data. In this study, we use pancreatic cancer as a case study to examine the practical identifiability of the two-, three-, and four-stage clonal expansion models given age-specific cancer incidence data using a numerical profile-likelihood approach. We demonstrate that, in the case of the three- and four-stage models, several parameters that are theoretically structurally identifiable, are, in practice, unidentifiable. This result means that key parameters such as the intermediate cell mutation rates are not individually identifiable from the data and that estimation of those parameters, even if structurally identifiable, will not be stable. We also show that products of these practically unidentifiable parameters are practically identifiable, and, based on this, we propose new reparameterizations of the model hazards that resolve the parameter estimation problems. Our results highlight the importance of identifiability to the interpretation of model parameter estimates.

Parameter estimation from data is an important part of mathematical modeling, and structural identifiability is the study of what parametric information exists, for a given model, in ideal data. Unfortunately, for a variety of reasons, there is often less information available in our real data sets. The study of these problems is called practical identifiability. In this study, we consider a family of models of cancer biology that are commonly used to explain cancer incidence in terms of underlying biological parameters. Using profile likelihoods, a widely applicable numerical tool, we demonstrate that even though the more complex models we consider have theoretically more identifiable parameters, the data contains only three pieces of practically identifiable information for each model: the product of the initiating mutation rates, the net cell proliferation rate, and the scaled malignant conversion rate. This result can be interpreted biologically: we can determine only the product of cell mutation rates not the intermediate rates themselves. Our result limits the interpretability of previous work, but we propose a novel parameterization to resolve the identifiability issue. Ultimately, our analysis demonstrates the importance of verifying the practical identifiability of parameters before assigning too much weight to the interpretation of their estimated values.

Modeling Biphasic Environmental Decay of Pathogens and Implications for Risk Analysis

As the appreciation for the importance of the environment in infectious disease transmission has grown, so too has interest in pathogen fate and transport. Fate has been traditionally described by simple exponential decay, but there is increasing recognition that some pathogens demonstrate a biphasic pattern of decay-fast followed by slow. While many have attributed this behavior to population heterogeneity, we demonstrate that biphasic dynamics can arise through a number of plausible mechanisms. We examine the identifiability of a general model encompassing three such mechanisms: population heterogeneity, hardening off, and the existence of viable-but-not-culturable states. Although the models are not fully identifiable from longitudinal sampling studies of pathogen concentrations, we use a differential algebra approach to determine identifiable parameter combinations. Through case studies using Cryptosporidium and Escherichia coli, we show that failure to consider biphasic pathogen dynamics can lead to substantial under- or overestimation of disease risks and pathogen concentrations, depending on the context. More reliable models for environmental hazards and human health risks are possible with an improved understanding of the conditions in which biphasic die-off is expected. Understanding the mechanisms of pathogen decay will ultimately enhance our control efforts to mitigate exposure to environmental contamination.