Characterization of trajectories of physical activity and cigarette smoking from early adolescence to adulthood

BACKGROUND

Cigarette smoking and physical inactivity are two critical risk factors for noncommunicable diseases and all-cause mortality. However, few studies have compared the long-term trajectories of both behaviors, as well as multilevel factors associated with trajectory patterns. Using the National Longitudinal Study of Adolescent to Adult Health (Add Health) Wave I through V survey data, this study characterized distinct subgroups of the population sharing similar behavioral patterns from adolescence to adulthood, as well as predictors of subgroup membership for physical activity (PA) and cigarette smoking behavior respectively.

METHODS

Using the Add Health Wave I through V survey data, we identified the optimal number of latent classes and class-specific trajectories of PA and cigarette smoking from early adolescence to adulthood, fitting latent growth mixture models with standardized PA score and past 30-day cigarette smoking intensity as outcome measures and age as a continuous time variable. Associations of baseline sociodemographic factors, neighborhood characteristics, and sociopsychological factors with trajectory class membership were assessed using multinomial logistic regression.

RESULTS

We identified three distinct subgroups of non-linear PA trajectories in the study population: moderately active group (N = 1067, 5%), persistently inactive group (N = 14,257, 69%) and worsening activity group (N = 5410, 26%). Foror cigarette smoking, we identified three distinct non-linear trajectory subgroups: persistent non-smoker (N = 14,939, 72%), gradual quitter (N = 2357, 11%), and progressing smoker (N = 3393, 16%). Sex, race/ethnicity, neighborhood environment and perceived peer support during adolescence were significant predictors of both physical activity and cigarette smoking trajectory subgroup membership from early adolescence to adulthood.

CONCLUSIONS

There are three distinct subgroups of individuals sharing similar PA and cigarette smoking behavioral profile respectively from adolescence to adulthood in the Add Health study population. Behavioral interventions that focus on neighborhood environment (e.g. establish community-based activity center) and relationship to peers during adolescence (e.g. peer counseling) could be key to long-term PA promotion and cigarette smoking cessation.

The association between cannabis vaping and other substance use

Introduction

The popularity of cannabis vaping has increased rapidly, especially among adolescents and young adults. We posit some possible explanations and, to evaluate them, examine whether cannabis vapers differ from non-vaping cannabis users in other substance use.

Methods

Using nationally representative data from the Population Assessment of Tobacco and Health (PATH) Study wave 5 (Dec. 2018-Nov. 2019), we assessed the association between cannabis vaping and other substance use. A total of 1,689 adolescents and 10,620 adults who reported cannabis use in the past 12 months were included in the study. We employed multivariable logistic regressions to assess the association between cannabis vaping and other substance use.

Results

Among past 12-month cannabis users, compared with those who do not vape cannabis, participants who vape cannabis had higher risks of using alcohol (adjusted relative risk [aRR] = 1.04, 95 % CI, 1.01-1.07), cigarettes (aRR = 1.09, 95 % CI, 1.02-1.15), cigars (aRR = 1.17, 95 % CI, 1.06-1.30), other tobacco products (aRR = 1.29, 95 % CI, 1.14-1.45), electronic nicotine products (aRR = 4.64, 95 % CI, 4.32-4.99), other illicit drugs (aRR = 1.53, 95 % CI, 1.29-1.80), and misuse of prescription drugs (aRR = 1.43, 95 % CI, 1.19-1.72). Compared to older cannabis vapers, younger cannabis vapers were at risk of using more other substances. Cannabis vaping was associated with all seven measures of substance use among young adults.

Conclusions

Compared to non-vaping cannabis users, cannabis vapers have higher likelihood of using other substances. Research is needed to understand why, as well as the implications of the association.

The evolution of age-specific smoking cessation rates in the United States from 2009 to 2017: a Kalman filter based approach

BACKGROUND

Tracking the US smoking cessation rate over time is of great interest to tobacco control researchers and policymakers since smoking cessation behaviors have a major effect on the public's health. Recent studies have employed dynamic models to estimate the US cessation rate through observed smoking prevalence. However, none of those studies has provided annual estimates of the cessation rate by age group. Hence, the primary objective of this study is to estimate annual smoking cessation rates specific to different age groups in the US from 2009 to 2017.

METHODS

We employed a Kalman filter approach to investigate the annual evolution of age-group-specific cessation rates, unknown parameters of a mathematical model of smoking prevalence, during the 2009-2017 period using data from the 2009-2018 National Health Interview Surveys. We focused on cessation rates in the 25-44, 45-64 and 65 + age groups.

RESULTS

The findings show that cessation rates followed a consistent u-shaped curve over time with respect to age (i.e., higher among the 25-44 and 65 + age groups, and lower among 45-64-year-olds). Over the course of the study, the cessation rates in the 25-44 and 65 + age groups remained nearly unchanged around 4.5% and 5.6%, respectively. However, the rate in the 45-64 age group exhibited a substantial increase of 70%, from 2.5% to 2009 to 4.2% in 2017. The estimated cessation rates in all three age groups tended to converge to the weighted average cessation rate over time.

CONCLUSIONS

The Kalman filter approach offers a real-time estimation of cessation rates that can be helpful for monitoring smoking cessation behavior.

Are the Relevant Risk Factors Being Adequately Captured in Empirical Studies of Smoking Initiation? A Machine Learning Analysis Based on the Population Assessment of Tobacco and Health Study

INTRODUCTION

Cigarette smoking continues to pose a threat to public health. Identifying individual risk factors for smoking initiation is essential to further mitigate this epidemic. To the best of our knowledge, no study today has used machine learning (ML) techniques to automatically uncover informative predictors of smoking onset among adults using the Population Assessment of Tobacco and Health (PATH) study.

AIMS AND METHODS

In this work, we employed random forest paired with Recursive Feature Elimination to identify relevant PATH variables that predict smoking initiation among adults who have never smoked at baseline between two consecutive PATH waves. We included all potentially informative baseline variables in wave 1 (wave 4) to predict past 30-day smoking status in wave 2 (wave 5). Using the first and most recent pairs of PATH waves was found sufficient to identify the key risk factors of smoking initiation and test their robustness over time. The eXtreme Gradient Boosting method was employed to test the quality of these selected variables.

RESULTS

As a result, classification models suggested about 60 informative PATH variables among many candidate variables in each baseline wave. With these selected predictors, the resulting models have a high discriminatory power with the area under the specificity-sensitivity curves of around 80%. We examined the chosen variables and discovered important features. Across the considered waves, two factors, (1) BMI, and (2) dental and oral health status, robustly appeared as important predictors of smoking initiation, besides other well-established predictors.

CONCLUSIONS

Our work demonstrates that ML methods are useful to predict smoking initiation with high accuracy, identifying novel smoking initiation predictors, and to enhance our understanding of tobacco use behaviors.

IMPLICATIONS

Understanding individual risk factors for smoking initiation is essential to prevent smoking initiation. With this methodology, a set of the most informative predictors of smoking onset in the PATH data were identified. Besides reconfirming well-known risk factors, the findings suggested additional predictors of smoking initiation that have been overlooked in previous work. More studies that focus on the newly discovered factors (BMI and dental and oral health status,) are needed to confirm their predictive power against the onset of smoking as well as determine the underlying mechanisms.

The Association Between Cannabis Use and Subsequent Nicotine Electronic Cigarette Use Among US Adolescents

PURPOSE

The current study assessed the association between cannabis use among youth never e-cigarette users and subsequent e-cigarette use.

METHODS

The Population Assessment of Tobacco and Health Study is a nationally representative cohort study. Participants aged 12 years and older were selected using a 4-stage, stratified probability sample design from the US civilian, noninstitutionalized population. We included adolescents who participated in both wave 4.5 (2017-2018) and wave 5 (2018-2019) of Population Assessment of Tobacco and Health, and were never e-cigarette users at baseline (N = 9,925). Through multivariable logistic regressions, we examined the prospective association between cannabis use and subsequent e-cigarette use.

RESULTS

E-cigarette use at wave five was significantly more common among youth cannabis users at wave 4.5. The adjusted relative risks between ever cannabis use and subsequent past 12-month, past 30-day, and frequent e-cigarette use (≥20 days per month) were 1.53 (95% CI, 1.26-1.81), 1.70 (95% CI, 1.25-2.15), and 2.10 (95% CI, 1.17-3.03), respectively. The adjusted relative risks between past 30-day cannabis use and subsequent past 12-month, past 30-day, and frequent e-cigarette use were 1.54 (95% CI, 1.04-2.28), 2.01 (95% CI, 1.23-3.29), and 2.87 (95% CI, 1.44-5.71), respectively. We also found significant associations between ever cannabis vaping with subsequent e-cigarette use.

DISCUSSION

While previous research associates e-cigarette use with subsequent onset of cannabis use, we identify a reverse directional effect, where adolescent cannabis use is associated with increased likelihood of future e-cigarette use.

The Evolution of Age-Specific Smoking Cessation Rates in the United States From 2009 to 2018

Objective

Tracking the US smoking cessation rate over time is of great interest to tobacco control researchers and policymakers since smoking cessation behaviors have a major effect on the public's health. A couple of recent studies have employed dynamic models to estimate the US cessation rate through observed smoking prevalence. However, none of those studies has provided recent annual estimates of the cessation rate by age group.

Methods

We employed a Kalman filter approach to investigate the annual evolution of age-group-specific cessation rates, unknown parameters of a mathematical model of smoking prevalence, during the 2009-2018 period using data from the National Health Interview Survey. We focused on cessation rates in the 24-44, 45-64 and 65 + age groups.

Results

The findings show that cessation rates follow a consistent u-shaped curve over time with respect to age (i.e., higher among the 25-44 and 65 + age groups, and lower among 45-64-year-olds). Over the course of the study, the cessation rates in the 25-44 and 65 + age groups remained nearly unchanged around 4.5% and 5.6%, respectively. However, the rate in the 45-64 age group exhibited a substantial increase of 70%, from 2.5% in 2009 to 4.2% in 2017. The estimated cessation rates in all three age groups tended to converge to the weighted average cessation rate over time.

Conclusions

The Kalman filter approach offers a real-time estimation of cessation rates that would be helpful for monitoring smoking cessation behavior, of interest in general but also for tobacco control policymakers.

Machine learning application for predicting smoking cessation among US adults: An analysis of waves 1-3 of the PATH study

Identifying determinants of smoking cessation is critical for developing optimal cessation treatments and interventions. Machine learning (ML) is becoming more prevalent for smoking cessation success prediction in treatment programs. However, only individuals with an intention to quit smoking cigarettes participate in such programs, which limits the generalizability of the results. This study applies data from the Population Assessment of Tobacco and Health (PATH), a United States longitudinal nationally representative survey, to select primary determinants of smoking cessation and to train ML classification models for predicting smoking cessation among the general population. An analytical sample of 9,281 adult current established smokers from the PATH survey wave 1 was used to develop classification models to predict smoking cessation by wave 2. Random forest and gradient boosting machines were applied for variable selection, and the SHapley Additive explanation method was used to show the effect direction of the top-ranked variables. The final model predicted wave 2 smoking cessation for current established smokers in wave 1 with an accuracy of 72% in the test dataset. The validation results showed that a similar model could predict wave 3 smoking cessation of wave 2 smokers with an accuracy of 70%. Our analysis indicated that more past 30 days e-cigarette use at the time of quitting, fewer past 30 days cigarette use before quitting, ages older than 18 at smoking initiation, fewer years of smoking, poly tobacco past 30-days use before quitting, and higher BMI resulted in higher chances of cigarette cessation for adult smokers in the US.

Use of Electronic Cigarettes Among Cannabis-Naive Adolescents and Its Association With Future Cannabis Use

IMPORTANCE

Electronic cigarette (e-cigarette) use has been reported to increase the likelihood of future cigarette smoking among adolescents. The prospective association between e-cigarette use and cannabis use has been less clear, especially in recent years.

OBJECTIVE

To examine the association between e-cigarette use among cannabis-naive adolescents and cannabis use 1 year later.

DESIGN, SETTING, AND PARTICIPANTS

The Population Assessment of Tobacco and Health (PATH) Study, a nationally representative cohort study, uses a 4-stage, stratified probability sample design to select participants aged 12 years or older from the US civilian, noninstitutionalized population. This study sample included 9828 cannabis-naive adolescents at the baseline survey who participated in both wave 4.5 (2017-2018) and wave 5 (2018-2019) of PATH.

EXPOSURES

e-Cigarette use, assessed by ever use, past 12-month use, and past 30-day use.

MAIN OUTCOMES AND MEASURES

Cannabis use in wave 5, assessed by past 12-month and past 30-day use. Multivariable logistic regressions assessed the association between e-cigarette use and cannabis use 1 year later. Results were weighted to produce nationally representative findings.

RESULTS

Of the 9828 adolescents included in the analysis, 5361 (57.3%) were aged 12 to 14 years, 5056 (50.7%) were male, and 4481 (53.0%) were non-Hispanic White. After adjustment for sociodemographic characteristics, environmental factors, other substance use, and sensation seeking, e-cigarette use among cannabis-naive adolescents was associated with increased likelihoods of both self-reported past 12-month and past 30-day cannabis use 1 year later. The adjusted relative risks (aRRs) of subsequent past 12-month cannabis use with ever use of e-cigarettes was 2.57 (95% CI, 2.04-3.09), with past 12-month use of e-cigarettes was 2.62 (95% CI, 2.10-3.15), and with past 30-day use of e-cigarettes was 2.18 (95% CI, 1.50-2.85). The aRRs of subsequent past 30-day cannabis use with ever use of e-cigarettes was 3.20 (95% CI, 2.10-4.31), with past 12-month use of e-cigarettes was 3.40 (95% CI, 2.17-4.63), and with past 30-day use of e-cigarettes was 2.96 (95% CI, 1.52-4.40).

CONCLUSIONS AND RELEVANCE

This cohort study's findings suggest a strong association between adolescent e-cigarette use and subsequent cannabis use. However, despite the strong association at the individual level, e-cigarette use seems to have had a minimal association with the prevalence of youth cannabis use at the population level.

Can PATH Study susceptibility measures predict e-cigarette and cigarette use among American youth 1 year later?

AIMS

To investigate whether e-cigarette and cigarette susceptibility predict e-cigarette and cigarette use among American youth 1 year later.

DESIGN AND SETTING

Longitudinal data from the Population Assessment of Tobacco and Health (PATH) Study-a four-stage, stratified probability cohort study of youth (12-17 years old) sampled from the United States civilian, non-institutionalized population. Multivariable logistic regression was used to estimate the association between initial product-specific susceptibility and subsequent cigarette smoking and e-cigarette use while controlling for sociodemographic characteristics, exposure to nicotine users, and behavioral risk factors.

PARTICIPANTS

The sample included 8841 adolescent never nicotine users at initial survey who participated in both wave 4 (2016-2017) and wave 4.5 (2017-2018) of PATH.

MEASUREMENTS

We measured cigarette and e-cigarette susceptibility (defined as a lack of a firm commitment to not use cigarettes or e-cigarettes) among never nicotine users at baseline (wave 4) as well as cigarette and e-cigarette use at 12-month follow-up (wave 4.5).

FINDINGS

Youth e-cigarette susceptibility was statistically significantly (P < 0.05) associated with e-cigarette use 1 year later, for both past 12-month (adjusted odds ratio [aOR], 2.99; 95% CI, 2.29-3.90) and past 30-day e-cigarette use (aOR, 2.73; 95% CI, 1.78-4.16), but not with cigarette smoking (aOR, 1.05; 95% CI, 0.64-1.73 for past 12-month smoking and aOR, 0.65; 95% CI, 0.29-1.45 for past 30-day smoking. Smoking susceptibility predicted subsequent smoking in the past 12 months (aOR, 1.82; 95% CI, 1.09-3.03) and past 30 days (aOR, 3.32; 95% CI (1.33-8.29), but not e-cigarette use in the past 12 months (aOR, 0.96; 95% CI, 0.77-1.19) or past 30 days (aOR, 1.11; 95% CI, 0.82-1.51).

CONCLUSION

E-cigarette and cigarette susceptibility measures appear to predict product-specific use among youth 1 year later.

The importance of peer imitation on smoking initiation over time: a dynamical systems approach

A recent Institute of Medicine Report calls for explicit modeling of smoking initiation, cessation and addiction processes. We introduce a model of smoking initiation that explicitly teases out the percentage of initiation due to social pressures, which we call "peer-imitation," and the percentage due to other factors, such as media ads, family smoking, and psychological factors, which we call "self-initiation." We propose a dynamic non-linear behavioral contagion model of smoking initiation and employ data from the National Survey on Drug Use and Health to estimate the relative contributions of imitation and self-initiation to the overall smoking initiation process. Although the percent of total smoking due to peer imitation has been trending downward over time, it remains higher than the percent due to self-initiation. We note unexpected changes for the 2007 cohort, and we discuss possible implications for intervention and for the spread of e-cigarettes.

Evaluation of Self-reported Cannabis Vaping Among US Youth and Young Adults Who Use e-Cigarettes

This cross-sectional study examines the prevalence and frequency of cannabis vaping, which is distinct from nicotine vaping, among young people aged 12 to 24 years.

Is Adolescent E-Cigarette Use Associated With Subsequent Smoking? A New Look

INTRODUCTION

Prospective studies have consistently reported a strong association between e-cigarette use and subsequent cigarette smoking, but many failed to adjust for important risk factors.

METHODS

Using longitudinal data from the Population Assessment of Tobacco and Health (PATH) Study, we employed multivariable logistic regressions to assess the adolescent vaping-to-smoking relationship, with four regressions (Models 1-4) sequentially adding more risk factors.Our sample included all waves (waves 1-5) of the PATH Study.

RESULTS

The association between ever e-cigarette use and subsequent cigarette smoking decreased substantially in magnitude when adding more control variables, including respondents' sociodemographic characteristics, exposure to tobacco users, cigarette susceptibility, and behavioral risk factors. Using the most recent data (waves 4-4.5 and waves 4.5-5), this association was not significant in the most complete model (Model 4). Using wave 4.5-5 data, the adjusted odds ratio (aOR) for ever e-cigarette use at initial wave and subsequent past 12-month smoking declined from 4.07 (95% confidence interval [CI, 2.86-5.81) in Model 1, adjusting only for sociodemographic characteristics, to 1.35 (95% CI, 0.84-2.16) in Model 4, adjusting for all potential risk factors. Similarly, the aOR of ever e-cigarette use and past 30-day smoking at wave 5 decreased from 3.26 (95% CI, 1.81-5.86) in Model 1 to 1.21 (95% CI, 0.59-2.48) with all covariates (Model 4).

CONCLUSIONS

Among adolescent never cigarette smokers, those who had ever used e-cigarettes at baseline, compared with never e-cigarette users, exhibited modest or non-significant increases in subsequent past 12-month or past 30-day smoking when adjusting for behavioral risk factors.

Evaluation of the impact of pre- and post-harvest maize handling practices on mycotoxin contamination on smallholder farms in Guatemala

Mycotoxins are secondary metabolites produced by fungi including Aspergillus and Fusarium that commonly contaminate crops, such as maize, resulting in economic losses and food insecurity. Mycotoxins can contaminate crops during pre- and post-harvest stages. Consumption of mycotoxin-contaminated foods has been linked to a variety of negative health outcomes including liver cancer, stunting, and neural tube defects. In countries such as Guatemala where maize constitutes a major portion of the diet, mycotoxins can be a significant contributor to disease burden. This review describes maize pre- and post-harvest practices in Guatemala that can lead to the development of mycotoxins and subsequent exposure to humans and animals, current information gaps, and opportunities for future research. There are specific challenges to minimising fungal growth and subsequent mycotoxin production during storage of maize in Guatemala, including reducing moisture content, minimising pest damage, and controlling temperature. Research on maize-handling practices that are associated with the greatest mycotoxin exposure in Guatemala is needed to prioritise allocation of resources and reduce exposure.

The Use of Expert Elicitation among Computational Modeling Studies in Health Research: A Systematic Review

BACKGROUND

Expert elicitation (EE) has been used across disciplines to estimate input parameters for computational modeling research when information is sparse or conflictual.

OBJECTIVES

We conducted a systematic review to compare EE methods used to generate model input parameters in health research.

DATA SOURCES

PubMed and Web of Science.

STUDY ELIGIBILITY

Modeling studies that reported the use of EE as the source for model input probabilities were included if they were published in English before June 2021 and reported health outcomes.

DATA ABSTRACTION AND SYNTHESIS

Studies were classified as "formal" EE methods if they explicitly reported details of their elicitation process. Those that stated use of expert opinion but provided limited information were classified as "indeterminate" methods. In both groups, we abstracted citation details, study design, modeling methodology, a description of elicited parameters, and elicitation methods. Comparisons were made between elicitation methods.

STUDY APPRAISAL

Studies that conducted a formal EE were appraised on the reporting quality of the EE. Quality appraisal was not conducted for studies of indeterminate methods.

RESULTS

The search identified 1520 articles, of which 152 were included. Of the included studies, 40 were classified as formal EE and 112 as indeterminate methods. Most studies were cost-effectiveness analyses (77.6%). Forty-seven indeterminate method studies provided no information on methods for generating estimates. Among formal EEs, the average reporting quality score was 9 out of 16.

LIMITATIONS

Elicitations on nonhealth topics and those reported in the gray literature were not included.

CONCLUSIONS

We found poor reporting of EE methods used in modeling studies, making it difficult to discern meaningful differences in approaches. Improved quality standards for EEs would improve the validity and replicability of computational models.

HIGHLIGHTS

We find extensive use of expert elicitation for the development of model input parameters, but most studies do not provide adequate details of their elicitation methods.Lack of reporting hinders greater discussion of the merits and challenges of using expert elicitation for model input parameter development.There is a need to establish expert elicitation best practices and reporting guidelines.

Consequences of a match made in hell: the harm caused by menthol smoking to the African American population over 1980-2018

BACKGROUND

For many years, national surveys have shown a consistently disproportionately high prevalence of menthol smokers among African Americans compared with the general population. However, to our knowledge, no prior study has quantified the harm that menthol smoking has caused on that population. In this work, we estimate the public health harm that menthol cigarettes have caused to the African American community over the last four decades.

METHODS

Using National Health Interview Survey data, we employed a well-established simulation model to reproduce the observed smoking trajectory over 1980-2018 in the African American population. Then, we repeat the experiment, removing the effects of menthol on the smoking initiation and cessation rates over that period, obtaining a new hypothetical smoking trajectory. Finally, we compared both scenarios to calculate the public health harm attributable to menthol cigarettes over 1980-2018.

RESULTS

Our results show that menthol cigarettes were responsible for 1.5 million new smokers, 157 000 smoking-related premature deaths and 1.5 million life-years lost among African Americans over 1980-2018. While African Americans constitute 12% of the total US population, these figures represent, respectively, a staggering 15%, 41% and 50% of the total menthol-related harm.

DISCUSSION

Our results show that menthol cigarettes disproportionally harmed African Americans significantly over the last 38 years and are responsible for exacerbating health disparities among that population. Removing menthol cigarettes from the market would benefit the overall US population but, particularly, the African American community.

Trends in Nicotine Product Use Among US Adolescents, 1999-2020

IMPORTANCE

With increasing e-cigarette use among US adolescents and decreasing use of other tobacco products, it is unclear how total use of nicotine products, and its long-term health risks, have changed. The Centers for Disease Control and Prevention's standard measure-any tobacco product use in the past 30 days-considers neither frequency of use nor product risk implications.

OBJECTIVE

To investigate how nicotine product use, including frequency of use, and its associated risks have changed among middle school and high school students since 1999.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used data from the 1999-2020 National Youth Tobacco Survey, an in-school survey of a nationally representative sample of students in grades 6 through 12; each survey recruited between 15 000 and 36 000 participants.

EXPOSURES

Nicotine product use in the past 30 days.

MAIN OUTCOMES AND MEASURES

Use of nicotine products assessed by nicotine product days (NPDs), the number of days that the average student consumed these products in the past 30 days. Risk-adjusted NPDs account for differential long-term health risks of various products.

RESULTS

This study included 16 years of cross-sectional survey data. Each survey recruited between 15 000 and 36 000 participants in grades 6 through 12 (male students: mean, 50.4% [minimum, 48.5%; maximum, 58.4%]; mean age, 14.5 years [minimum, 14.0 years; maximum, 14.7 years]). Nationally representative cross-sectional data for high school students showed that NPDs decreased steadily from 5.6 days per month in 1999 (95% CI, 5.0-6.2 days per month) to 2.2 days per month in 2017 (95% CI, 1.9-2.6 days per month), increased to 4.6 days per month in 2019 (95% CI, 4.1-5.1 days per month), and then decreased to 3.6 days per month in 2020 (95% CI, 3.0-4.1 days per month). For a risk weight of 0.1 for e-cigarettes, compared with combustible products, risk-adjusted NPDs decreased from 2.5 days per month in 2013 (95% CI, 2.2-2.9 days per month) (prior to the popularity of e-cigarettes) to 2.0 days per month in 2019 (95% CI, 1.6-2.5 days per month) and 1.4 days per month in 2020 (95% CI, 1.0-1.8 days per month). However, with a risk weight of 1.0 for e-cigarettes (identical to that of combustible products), risk-adjusted NPDs increased to 5.3 days per month in 2019 (95% CI, 4.4-6.2 days per month) and 3.9 days per month in 2020 (95% CI, 3.1-4.7 days per month). Similar trends were found for middle school students.

CONCLUSIONS AND RELEVANCE

This study suggests that NPDs represent an improvement, albeit an imperfect one, compared with any 30-day tobacco product use by incorporating the frequency of use of various products. By distinguishing products, NPDs permit consideration of the health consequences associated with different mixes of products over time. Health risks of adolescent nicotine product use could have decreased during vaping's popularity if assessment of the long-term risks associated with vaping compared with those of smoking is low. There is a need to closely monitor youth nicotine and tobacco product use patterns.

Estimating the Population Health Impact of Recently Introduced Modified Risk Tobacco Products: A Comparison of Different Approaches

Introduction

Various approaches have been used to estimate the population health impact of introducing a Modified Risk Tobacco Product (MRTP).

Aims and Methods

We aimed to compare and contrast aspects of models considering effects on mortality that were known to experts attending a meeting on models in 2018.

Results

Thirteen models are described, some focussing on e-cigarettes, others more general. Most models are cohort-based, comparing results with or without MRTP introduction. They typically start with a population with known smoking habits and then use transition probabilities either to update smoking habits in the “null scenario” or joint smoking and MRTP habits in an “alternative scenario”. The models vary in the tobacco groups and transition probabilities considered. Based on aspects of the tobacco history developed, the models compare mortality risks, and sometimes life-years lost and health costs, between scenarios. Estimating effects on population health depends on frequency of use of the MRTP and smoking, and the extent to which the products expose users to harmful constituents. Strengths and weaknesses of the approaches are summarized.

Conclusions

Despite methodological differences, most modellers have assumed the increase in risk of mortality from MRTP use, relative to that from cigarette smoking, to be very low and have concluded that MRTP introduction is likely to have a beneficial impact. Further model development, supplemented by preliminary results from well-designed epidemiological studies, should enable more precise prediction of the anticipated effects of MRTP introduction.

Implications

There is a need to estimate the population health impact of introducing modified risk nicotine-containing products for smokers unwilling or unable to quit. This paper reviews a variety of modeling methodologies proposed to do this, and discusses the implications of the different approaches. It should assist modelers in refining and improving their models, and help toward providing authorities with more reliable estimates.

A Magic Bullet? The Potential Impact of E-Cigarettes on the Toll of Cigarette Smoking

INTRODUCTION

We examine the proportion of US smoking-produced mortality that e-cigarettes might eliminate under assumptions regarding vaping's ability to increase smoking cessation, vaping's health risks, and the possibility that vaping will increase smoking among young people.

METHODS

We employ a dynamic population simulation model that tracks individuals from ages 0 to 110, differentiated by gender and smoking status. Using data from the US Census, the National Vital Statistics Reports, Cancer Prevention Study II, and the National Health Interview Survey, we estimate the number of smoking-related life-years lost (LYL) from 2018 to 2100 in a no-vaping scenario. We then compare results for model runs that assess the impact of vaping under a variety of assumptions.

RESULTS

The combination of assumptions produces 360 possible scenarios. 357 (99%) yield positive estimates of life-years saved (LYS) due to vaping by 2100, from 143 000 to 65 million. Most scenarios result in millions of individuals quitting smoking due to vaping. On average, vaping-induced quitters gain an extra 1.2-2.0 years of life compared to smokers who quit without vaping. The impact of vaping is greatest when it most helps smokers who otherwise have the greatest difficulty quitting smoking. While the numbers of LYS are generally large across all scenarios, they often represent a small fraction of the toll of smoking.

CONCLUSIONS

Vaping is highly likely to reduce smoking-produced mortality. Still, vaping is not "the" answer to the public health crisis created by smoking. Rather, it may well be a tool to add to the armamentarium of effective tobacco control measures.

IMPLICATIONS

E-cigarettes hold the potential to reduce cigarette smoking's enormous toll. By itself, however, tobacco harm reduction, as embodied in vaping, is no magic bullet. Going forward, tobacco control will require vigilant application of the evidence-based measures that have brought us so much success in combatting smoking. It will require, as well, the search for and adoption of novel means of attacking the remaining problem. Harm reduction can, and many would say should, be a part of the complex formula that will eventually bring about the demise of smoking.

An estimation of the harm of menthol cigarettes in the United States from 1980 to 2018

BACKGROUND

Menthol cigarettes are thought to encourage smoking initiation among youths and young adults and make it more difficult for smokers to quit, thus increasing cigarette harm. However, no study to date has quantified the damage that menthol cigarettes have caused the US population.

OBJECTIVE

To estimate the excess smoking prevalence, smoking initiation, and mortality in the US from 1980 through 2018 that can be attributed to menthol cigarettes.

METHODS

Using a well-established simulation model of smoking prevalence and health effects and data from the National Health Interview Survey (NHIS), we first reproduced the overall US adult smoking prevalence between 1980 and 2018 (pseudo-R2=0.98) and associated mortality. Then we re-ran the model, assuming that menthol cigarettes were not present in the market over the same period. Finally, we compared both scenarios to quantify the public health harm attributable to menthol over the 1980-2018 period.

RESULTS

From 1980 to 2018, we found that menthol cigarettes were responsible for slowing down the decline in smoking prevalence by 2.6 percentage points (13.7% vs 11.1% in 2018). Our results also show that menthol cigarettes were responsible for 10.1 million extra smokers, 3 million life years lost and 378 000 premature deaths during that period.

CONCLUSIONS

With millions of excess smoking initiators and thousands of smoking-related deaths due to mentholated cigarettes from 1980 through 2018, our results indicate that these products have had a significant detrimental impact on the public's health and could continue to pose a substantial health risk. Our findings can assist the Food and Drug Administration in evaluating potential regulatory actions for mentholated tobacco products.

MAIP: a web service for predicting blood-stage malaria inhibitors

Malaria is a disease affecting hundreds of millions of people across the world, mainly in developing countries and especially in sub-Saharan Africa. It is the cause of hundreds of thousands of deaths each year and there is an ever-present need to identify and develop effective new therapies to tackle the disease and overcome increasing drug resistance. Here, we extend a previous study in which a number of partners collaborated to develop a consensus in silico model that can be used to identify novel molecules that may have antimalarial properties. The performance of machine learning methods generally improves with the number of data points available for training. One practical challenge in building large training sets is that the data are often proprietary and cannot be straightforwardly integrated. Here, this was addressed by sharing QSAR models, each built on a private data set. We describe the development of an open-source software platform for creating such models, a comprehensive evaluation of methods to create a single consensus model and a web platform called MAIP available at https://www.ebi.ac.uk/chembl/maip/ . MAIP is freely available for the wider community to make large-scale predictions of potential malaria inhibiting compounds. This project also highlights some of the practical challenges in reproducing published computational methods and the opportunities that open-source software can offer to the community.

How much of the future mortality toll of smoking can be avoided?

OBJECTIVE

To determine how much future smoking-related mortality in the USA can be prevented, recognising that some of that future mortality results from past smoking.

METHODS

Employing a dynamic population simulation model, we estimate smoking's expected mortality burden in the USA, measured as life-years lost (LYL), in a status-quo scenario run from 2018 through 2100. We then estimate LYL attributable to past smoking assuming that all smoking ceases at the end of 2017. We calculate the potential avoidable LYL, which we call the maximum potential reduction in premature mortality (MPRPM), as the difference between the two. We use data from the US Census Bureau, National Vital Statistics Reports, the National Health Interview Survey and Cancer Prevention Study II.

RESULTS

Under status-quo assumptions, smoking will claim 305 million LYL in the US from 2018 to 2100. If all smoking ceased at the end of 2017, past smoking would be responsible for 191.8 million LYL. Thus, avoidable LYL by 2100-the MPRPM-would be 113.2 million, 37% of the expected toll of smoking. A sensitivity analysis finds that were the annual smoking initiation rate 3% instead of 7.8%, the MPRPM would be 13-14% lower. Were the annual permanent smoking cessation rate twice our status-quo estimate of 4.35%, the MPRPM would be 38-39% lower.

CONCLUSIONS

Public health can address only the future toll of future smoking. Smoking's MPRPM is the reduction in the mortality burden of smoking that tobacco control can strive to achieve.

ChEMBL: towards direct deposition of bioassay data

ChEMBL is a large, open-access bioactivity database (https://www.ebi.ac.uk/chembl), previously described in the 2012, 2014 and 2017 Nucleic Acids Research Database Issues. In the last two years, several important improvements have been made to the database and are described here. These include more robust capture and representation of assay details; a new data deposition system, allowing updating of data sets and deposition of supplementary data; and a completely redesigned web interface, with enhanced search and filtering capabilities.

E-cigarettes: Comparing the Possible Risks of Increasing Smoking Initiation with the Potential Benefits of Increasing Smoking Cessation

Introduction

The public health community is divided regarding electronic cigarettes. Skeptics emphasize potential vaping-induced increases in smoking among children and possible health hazards for adults. Enthusiasts consider e-cigarettes much less dangerous than smoking and believe they increase adult smoking cessation. We compare potential health benefits and costs to put these two perspectives in context.

Methods

Using a dynamic model that tracks the US adult population's smoking status and smoking-related deaths over time, we simulate the effects of vaping-induced smoking initiation and cessation on life-years saved or lost to the year 2070. The base case assumes that vaping annually increases smoking initiation by 2% and smoking cessation by 10%. Sensitivity analyses raise the initiation rate increase to 6% while decreasing the cessation rate increase to 5%. Sensitivity analyses also test vaping's reducing the health benefits of quitting smoking by 10%.

Results

With base-case assumptions, the population gains almost 3.3 million life-years by 2070. If all people who quit smoking by vaping lose 10% of the benefit of quitting smoking, the net life-year gain falls to 2.4 million. Under worst-case assumptions, in which vaping increases smoking initiation by 6% and cessation by 5%, and vaping-induced quitters lose 10% of the health benefits, the population gains over 580000 life-years.

Conclusion

Potential life-years gained as a result of vaping-induced smoking cessation are projected to exceed potential life-years lost due to vaping-induced smoking initiation. These results hold over a wide range of plausible parameters.

Implications

Our analysis strongly suggests that the upside health benefit associated with e-cigarettes, in terms of their potential to increase adult smoking cessation, exceeds their downside risk to health as a result of their possibly increasing the number of youthful smoking initiators. Public messaging and policy should continue to strive to reduce young people's exposure to all nicotine and tobacco products. But, they should not do so at the expense of limiting such products' potential to help adult smokers to quit.

Initiation versus Cessation Control Policies: Deriving Optimal Resource Allocation Strategies to Decrease Smoking Prevalence Under a Fixed Budget

Background. Over several decades the tobacco control community has recommended and implemented smoking initiation and cessation interventions to reduce the smoking toll. It is necessary to study the combined effect of these interventions to allocate resources optimally. However, there is a paucity of studies that address the right combination of initiation and cessation policies over time to reduce smoking prevalence. Objective. To derive optimal trajectories of initiation and cessation interventions that minimize overall smoking prevalence over a specified period while satisfying a budget constraint. Methods. Using an established dynamic model of smoking prevalence, we employ an optimal control formulation to minimize overall smoking prevalence within a specified time period. The budget constraint is handled through an iterative application of a penalty function on above-budget expenditures. We further derive the optimal cost ratio of initiation versus cessation programs over time. To parameterize our model, we use results from two empirical interventions. The demographic data are from the National Health Interview Survey in the United States. Results. For our example, our results show that the optimal cost ratio (initiation over cessation) starts around 2.02 and gradually increases to 5.28 in 30 years. Smoking prevalence decreases significantly compared with the status quo, 8.54% in 30 years with no interventions versus the estimated 6.43% with interventions. In addition, the optimal units of initiation and cessation interventions increase over time. Conclusions. Our model provides a general framework to incorporate policy details in determining the optimal mix of smoking interventions.

Finding the optimal mix of smoking initiation and cessation interventions to reduce smoking prevalence

There are more than one billion smokers globally according to the World Health Organization (WHO) report in 2017. Every year tobacco use causes nearly 6 million deaths worldwide. To deal with the smoking epidemic, society needs to invest resources efficiently. In this paper we introduce an optimal control model to determine the optimal mix of smoking initiation and cessation interventions to reduce smoking. We construct the model to reach a smoking prevalence target within a specific time horizon while minimizing cost. Our performance measure captures the cost of policy implementation over time, adjusting for inflation and social discounting. The analytical solutions to the model are presented in forms of ordinary differential equations (ODE). We then conduct several numerical simulations using data from the National Health Interview Survey (NHIS) and empirical studies. We first present analytical solutions for our model to solve for the optimal mix of smoking interventions. Then we simulate a public health policy to achieve 5% smoking prevalence in the US by 2030 using different combinations of real-life interventions. We examine the optimal trajectories, allocative efficiency and annual total cost of smoking cessation and initiation interventions. We find consistent results across all simulations. Our specific example reveals that the most efficient way to reach stated goal is by targeting cessation interventions first, and then gradually shifting resources to initiation interventions over time. While our numerical results are specific to the intervention we selected, our framework can be easily expanded to consider other potential interventions. We discuss the implications of our approach for the formulation of dynamic public health policies.

Survey of rabies vaccination status of Queensland veterinarians and veterinary students

BACKGROUND

To determine the rabies vaccination status of Queensland veterinarians and veterinary students and their perception of zoonotic risk from Australian bat lyssavirus (ABLV).

DESIGN

Cross-sectional questionnaire surveys.

METHODS

Questionnaires were sent by post in 2011 to veterinary surgeons registered in Queensland, to final-year veterinary students at James Cook University via SurveyMonkey® in 2013 and to final-year veterinary students at James Cook University and University of Queensland via SurveyMonkey® in 2014.

RESULTS

The response rate for registered veterinarians was 33.5% and for veterinary students 33.3% and 30% in 2013 and 2014, respectively. Of the 466 registered veterinary surgeons, 147 (31.5%) had been vaccinated, with 72 (15.5%) currently vaccinated. For veterinary students the rabies vaccination rate was 20.0% (4/20) and 13.0% (6/46) in the 2013 and 2014 surveys, respectively. More than 95% of veterinary students had received the mandatory Q fever vaccine. Both veterinarians and students regarded bats and horses as high-risk species for zoonoses.

CONCLUSIONS

Queensland veterinarians and veterinary students have low levels of protection against ABLV. Although incidents of ABLV spilling over from a bat to a domestic mammal are likely to remain rare, they pose a significant human health and occupational risk given the outcome of infection in humans is high consequence. Principals of veterinary practices and veterinary authorities in Australia should implement a policy of rabies vaccination for clinical staff and veterinary students.

Posttransplant oxygen inhalation improves the outcome of subcutaneous islet transplantation: A promising clinical alternative to the conventional intrahepatic site

Subcutaneous tissue is a promising site for islet transplantation, due to its large area and accessibility, which allows minimally invasive procedures for transplantation, graft monitoring, and removal of malignancies as needed. However, relative to the conventional intrahepatic transplantation site, the subcutaneous site requires a large number of islets to achieve engraftment success and diabetes reversal, due to hypoxia and low vascularity. We report that the efficiency of subcutaneous islet transplantation in a Lewis rat model is significantly improved by treating recipients with inhaled 50% oxygen, in conjunction with prevascularization of the graft bed by agarose-basic fibroblast growth factor. Administration of 50% oxygen increased oxygen tension in the subcutaneous site to 140 mm Hg, compared to 45 mm Hg under ambient air. In vitro, islets cultured under 140 mm Hg oxygen showed reduced central necrosis and increased insulin release, compared to those maintained in 45 mm Hg oxygen. Six hundred syngeneic islets subcutaneously transplanted into the prevascularized graft bed reversed diabetes when combined with postoperative 50% oxygen inhalation for 3 days, a number comparable to that required for intrahepatic transplantation; in the absence of oxygen treatment, diabetes was not reversed. Thus, we show oxygen inhalation to be a simple and promising approach to successfully establishing subcutaneous islet transplantation.

An application of the Continuous Opinions and Discrete Actions (CODA) model to adolescent smoking initiation

We investigated the impact of peers’ opinions on the smoking initiation process among adolescents. We applied the Continuous Opinions and Discrete Actions (CODA) model to study how social interactions change adolescents’ opinions and behaviors about smoking. Through agent-based modeling (ABM), we simulated a population of 2500 adolescents and compared smoking prevalence to data from 9 cohorts of adolescents in the National Survey on Drug Use and Health (NSDUH) from year 2001 till 2014. Our model adjusts well for NSDUH data according to pseudo R² values, which are at least 96%. Optimal parameter values indicate that adolescents exhibit imitator characteristics with regard to smoking opinions. The imitator characteristics suggests that teenagers tend to update their opinions consistently according to what others do, and these opinions later translate into smoking behaviors. As a result, peer influence from social networks plays a big role in the smoking initiation process and should be an important driver in policy formulation.

Using ChEMBL web services for building applications and data processing workflows relevant to drug discovery

INTRODUCTION

ChEMBL is a manually curated database of bioactivity data on small drug-like molecules, used by drug discovery scientists. Among many access methods, a REST API provides programmatic access, allowing the remote retrieval of ChEMBL data and its integration into other applications. This approach allows scientists to move from a world where they go to the ChEMBL web site to search for relevant data, to one where ChEMBL data can be simply integrated into their everyday tools and work environment. Areas covered: This review highlights some of the audiences who may benefit from using the ChEMBL API, and the goals they can address, through the description of several use cases. The examples cover a team communication tool (Slack), a data analytics platform (KNIME), batch job management software (Luigi) and Rich Internet Applications. Expert opinion: The advent of web technologies, cloud computing and micro services oriented architectures have made REST APIs an essential ingredient of modern software development models. The widespread availability of tools consuming RESTful resources have made them useful for many groups of users. The ChEMBL API is a valuable resource of drug discovery bioactivity data for professional chemists, chemistry students, data scientists, scientific and web developers.

The ChEMBL database in 2017

ChEMBL is an open large-scale bioactivity database (https://www.ebi.ac.uk/chembl), previously described in the 2012 and 2014 Nucleic Acids Research Database Issues. Since then, alongside the continued extraction of data from the medicinal chemistry literature, new sources of bioactivity data have also been added to the database. These include: deposited data sets from neglected disease screening; crop protection data; drug metabolism and disposition data and bioactivity data from patents. A number of improvements and new features have also been incorporated. These include the annotation of assays and targets using ontologies, the inclusion of targets and indications for clinical candidates, addition of metabolic pathways for drugs and calculation of structural alerts. The ChEMBL data can be accessed via a web-interface, RDF distribution, data downloads and RESTful web-services.

Impact of Health Insurance Expansions on Nonelderly Adults With Hypertension

INTRODUCTION

Hypertension is a risk factor for cardiovascular disease (CVD), the leading cause of death in the United States. The treatment and control of hypertension is inadequate, especially among patients without health insurance coverage. The Affordable Care Act offered an opportunity to improve hypertension management by increasing the number of people covered by insurance. This study predicts the long-term effects of improved hypertension treatment rates due to insurance expansions on the prevalence and mortality rates of CVD of nonelderly Americans with hypertension.

METHODS

We developed a state-transition model to simulate the lifetime health events of the population aged 25 to 64 years. We modeled the effects of insurance coverage expansions on the basis of published findings on the relationship between insurance coverage, use of antihypertensive medications, and CVD-related events and deaths.

RESULTS

The model projected that currently anticipated health insurance expansions would lead to a 5.1% increase in treatment rate among hypertensive patients. Such an increase in treatment rate is estimated to lead to 111,000 fewer new coronary heart disease events, 63,000 fewer stroke events, and 95,000 fewer CVD-related deaths by 2050. The estimated benefits were slightly greater for men than for women and were greater among nonwhite populations.

CONCLUSION

Federal and state efforts to expand insurance coverage among nonelderly adults could yield significant health benefits in terms of CVD prevalence and mortality rates and narrow the racial/ethnic disparities in health outcomes for patients with hypertension.

Biochemical profiles and physicochemical parameters of beef from cattle raised under contrasting feeding systems and pre-slaughter management

Diet and pre-slaughter stress are key factors that may affect the biochemical processes during conversion of muscle into meat. The aim of the present study was to evaluate the effect of two different pre-slaughter stress managements (PSM) at a slaughterhouse in Angus steers raised and finished in two contrasting feeding systems (FS grain and pasture systems), on the peri mortem muscle metabolism, and its relation to of meat quality. Results obtained showed that a higher level of pre-slaughter stress increased (P < 0.05) glucose, lactate and proteins blood levels and decreased (P < 0.05) the redness (a* parameter) of adipose tissue. Regarding feeding strategy, pasture-fed animals displayed increased (P < 0.05) levels of haematocrit and insulin concentrations, and higher (P < 0.05) muscle pH decrease during the first 3 h post mortem. Despite final pH (pH 24 h) of M. longissimus dorsi (LD) was not significantly modified, LD hardness was significantly affected by an interaction effect of FS and PSM. Lower pre-slaughter stress level led to a decrease (P < 0.05) of LD hardness in grain-fed animals. In general terms, results showed an impact of PSM and FS on meat quality through pH-independent mechanisms.

Response of Australian veterinarians to the announcement of a Hendra virus vaccine becoming available

DESIGN

A cross-sectional study of private veterinarians providing equine services in Queensland.

RESULTS

The study revealed that a majority of veterinarians would support the introduction of a Hendra virus (HeV) vaccine. Moreover, almost half of the respondents intended to make vaccination a prerequisite to horse patient presentation. However, participants also responded that a vaccine would not reduce the risk sufficiently to cease or downgrade their HeV management plan and infection control measures.

CONCLUSION

When devising promoting and marketing campaigns, government agencies and manufacturers should consider private veterinarians' intentions as a significant driver for the uptake of the HeV vaccine.

Radon, smoking, and lung cancer: the need to refocus radon control policy

Exposure to radon is the second leading cause of lung cancer, and the risk is significantly higher for smokers than for nonsmokers. More than 85% of radon-induced lung cancer deaths are among smokers. The most powerful approach for reducing the public health burden of radon is shaped by 2 overarching principles: public communication efforts that promote residential radon testing and remediation will be the most cost effective if they are primarily directed at current and former smokers; and focusing on smoking prevention and cessation is the optimal strategy for reducing radon-induced lung cancer in terms of both public health gains and economic efficiency. Tobacco control policy is the most promising route to the public health goals of radon control policy.

Propagation of electromagnetic waves in stochastic helical media

We have developed a model for studying the axial propagation of elliptically polarized electromagnetic waves in a spatially random helical media. We start by writing Maxwell equations for a structurally chiral medium whose dielectric permittivities, polar, and helical angles contain both a stochastic contribution and a deterministic one. We write the electromagnetic equations into a Marcuvitz-Schwigner representation to transform them afterward in a simpler expression by using the Oseen transformation. We exhibit that in the Oseen frame the Marcuvitz-Schwigner equations turns out to be a linear vector stochastic system of differential equations with multiplicative noise. Applying to the resulting equation a formalism for treating stochastic differential equations, we find the governing equations for the first moments of the electromagnetic field amplitudes for a general autocorrelation function for the system diffractive indexes, and calculate their corresponding band structure for a particular spectral noise density. We have shown that the average resulting electromagnetic fields exhibit a decaying exponential dependence which stems from by dissipation and the presence of qualitative modifications in the band structure including a considerable widening of the band gap and the existence of new local maxima for the modes without a band gap.

Efecto del manejo y del temperamento animal sobre indicadores de calidad de la carne bovina

El objetivo del presente trabajo fue estudiar el efecto de diferentes condiciones de manejo sobre indicadores fisiológicos de estrés y de calidad de carne en bovinos con temperamentos contras-tantes. Se utilizaron cuarenta animales clasificados como calmos y excitables. Los mismos fueron alimentados inicialmente a base de pasturas y terminados con una dieta mixta de grano de maíz y pasturas. Se dosaron indicadores bioquímicos de estrés (hematocrito, proteínas plasmáticas, glucosa, creatinina, actividad fosfatasa alcalina, cortisol, insulina, contenido muscular de glucó-geno). Como indicadores de calidad de carne se midieron el pH de 24 h y color instrumental. El temperamento animal demostró un incremento significativo (p

Minimising exposure of amphibians to pathogens during field studies

Many of the recent global amphibian mass mortalities, declines and extinctions have been attributed to the emerging infectious disease chytridiomycosis. There have been mass mortalities due to ranaviral disease but no major declines or extinctions. Controlling the transmission and spread of disease is of utmost importance, especially where there is the potential for human involvement. We have reviewed current hygiene guidelines for working with wild frogs, identified potential flaws and recommended those most suitable and effective for the field environment. Our within-site hygiene measures aim to reduce the risk of transmission among individuals. These measures encompass the capture, handling and holding of amphibians, skin disinfection before and after invasive procedures, marking frogs, sealing open wounds and treatment of accessory equipment. Our between-site hygiene measures aim to mitigate the risk of pathogen spread among populations. We have designed a risk calculator to help simplify and standardise the decision-making process for determining the level of risk and appropriate risk mitigation strategies to reduce the risk of increasing pathogen spread above background levels. Calculation of an overall risk score for pathogen spread takes into account the prior activity of field workers, the proposed activity, remoteness of the site, presence of known pathogens and the consequences of increased pathogen spread for amphibians in a given area.

Examining future adolescent human papillomavirus vaccine uptake, with and without a school mandate

PURPOSE

To develop a model of adolescent (HPV) human papillomavirus vaccine utilization that explored future HPV vaccination rates, with and without a school mandate, for the vaccine at middle school entry.

METHODS

A dynamic, population-based, compartmental model was developed that estimated over a 50-year time horizon HPV vaccine uptake among female adolescents living in the United States. The model incorporated data on parental attitudes about this vaccine and adolescent health care utilization levels.

RESULTS

Without a mandate, our model predicted that 70% coverage, a lower threshold value used in many previous modeling studies of HPV vaccination, would not be achieved until a mean of 23 years after vaccine availability. Maximal coverage of 79% was achieved after 50 years. With a school mandate in place, utilization increased substantially, with 70% vaccination coverage achieved by year 8 and maximal vaccination coverage, 90%, achieved by year 43.

CONCLUSIONS

Our results suggest that vaccine utilization is likely to be low for several years, though strong school mandates might improve HPV vaccine uptake. These results affect the interpretation of previous modeling studies that estimated the potential clinical effects of HPV vaccination under assumptions of very high vaccine utilization rates.

Pathology of cutaneous trombidiosis caused by larval trombiculid mites in a wild Lesueur's tree frog (Litoria wilcoxii)

Cutaneous trombidiosis caused by larvae of trombiculid mites (Vercammenia gloriosa and V. zweifelorum) in the skin of a wild tree frog, Litoria wilcoxii, in northern Queensland, Australia manifested as small, domed vesicular lesions on the dorsal and lateral surfaces posterior to the eyes. The lesions contained small, orange trombiculid mites, with a surrounding minimal inflammatory reaction. The general health and behaviour of the frog appeared unaffected. Provisional diagnosis of cutaneous trombidiosis can be made from its distinctive clinical appearance and confirmed by biopsy with direct microscopic examination of mites. This case report represents a new host record.