Comparison of approaches to control for intracranial volume in research on the association of brain volumes with cognitive outcomes

Most neuroimaging studies linking regional brain volumes with cognition correct for total intracranial volume (ICV), but methods used for this correction differ across studies. It is unknown whether different ICV correction methods yield consistent results. Using a brain-wide association approach in the MRI substudy of UK Biobank (N = 41,964; mean age = 64.5 years), we used regression models to estimate the associations of 58 regional brain volumetric measures with eight cognitive outcomes, comparing no correction and four ICV correction approaches. Approaches evaluated included: no correction; dividing regional volumes by ICV (proportional approach); including ICV as a covariate in the regression (adjustment approach); and regressing the regional volumes against ICV in different normative samples and using calculated residuals to determine associations (residual approach). We used Spearman-rank correlations and two consistency measures to quantify the extent to which associations were inconsistent across ICV correction approaches for each possible brain region and cognitive outcome pair across 2320 regression models. When the association between brain volume and cognitive performance was close to null, all approaches produced similar estimates close to the null. When associations between a regional volume and cognitive test were not null, the adjustment and residual approaches typically produced similar estimates, but these estimates were inconsistent with results from the crude and proportional approaches. For example, when using the crude approach, an increase of 0.114 (95% confidence interval [CI]: 0.103-0.125) in fluid intelligence was associated with each unit increase in hippocampal volume. However, when using the adjustment approach, the increase was 0.055 (95% CI: 0.043-0.068), while the proportional approach showed a decrease of -0.025 (95% CI: -0.035 to -0.014). Different commonly used methods to correct for ICV yielded inconsistent results. The proportional method diverges notably from other methods and results were sometimes biologically implausible. A simple regression adjustment for ICV produced biologically plausible associations.

Genetic risk score for Alzheimer's disease predicts brain volume differences in mid and late life in UK biobank participants

INTRODUCTION

We estimated the ages when associations between Alzheimer's disease (AD) genes and brain volumes begin among middle-aged and older adults.

METHODS

Among 45,616 dementia-free participants aged 45-80, linear regressions tested whether genetic risk score for AD (AD-GRS) had age-dependent associations with 38 regional brain magnetic resonance imaging volumes. Models were adjusted for sex, assessment center, genetic ancestry, and intracranial volume.

RESULTS

AD-GRS modified the estimated effect of age (per decade) on the amygdala (-0.41 mm3 [-0.42, -0.40]); hippocampus (-0.45 mm3 [-0.45, -0.44]), nucleus accumbens (-0.55 mm3 [-0.56, -0.54]), thalamus (-0.38 mm3 [-0.39, -0.37]), and medial orbitofrontal cortex (-0.23 mm3 [-0.24, -0.22]). Trends began by age 45 for the nucleus accumbens and thalamus, 48 for the hippocampus, 51 for the amygdala, and 53 for the medial orbitofrontal cortex. An AD-GRS excluding apolipoprotein E (APOE) was additionally associated with entorhinal and middle temporal cortices.

DISCUSSION

APOE and other genes that increase AD risk predict lower hippocampal and other brain volumes by middle age.

Considerations for Use of Blood-Based Biomarkers in Epidemiologic Dementia Research

Dementia represents a growing public health burden with large social, racial, and ethnic disparities. The etiology of dementia is poorly understood, and the lack of robust biomarkers in diverse, population-representative samples is a barrier to moving dementia research forward. Existing biomarkers and other measures of pathology-derived from neuropathology, neuroimaging, and cerebrospinal fluid samples-are commonly collected from predominantly White and highly educated samples drawn from academic medical centers in urban settings. Blood-based biomarkers are noninvasive and less expensive, offering promise to expand our understanding of the pathophysiology of dementia, including in participants from historically excluded groups. Although largely not yet approved by the Food and Drug Administration or used in clinical settings, blood-based biomarkers are increasingly included in epidemiologic studies on dementia. Blood-based biomarkers in epidemiologic research may allow the field to more accurately understand the multifactorial etiology and sequence of events that characterize dementia-related pathophysiological changes. As blood-based dementia biomarkers continue to be developed and incorporated into research and practice, we outline considerations for using them in dementia epidemiology, and illustrate key concepts with Alzheimer's Disease Neuroimaging Initiative (2003-present) data. We focus on measurement, including both validity and reliability, and on the use of dementia blood-based biomarkers to promote equity in dementia research and cognitive aging. This article is part of a Special Collection on Mental Health.

Estimated effects of amyloid reduction on cognitive change: A Bayesian update across a range of priors

INTRODUCTION

The results of the CLARITY-AD, GRADUATE I and II, and TRAILBLAZER-ALZ 2 trials have rekindled discussion on the impact of amyloid-targeting drugs. We use a Bayesian approach to quantify how rational observers would have updated their prior beliefs based on new trial results.

METHODS

We used publicly available data from the CLARITY-AD, GRADUATE I and II, and TRAILBLAZER-ALZ 2 trials to estimate the effect of reducing amyloid on the clinical dementia rating scale, sum of boxes (CDR-SB) score. A range of prior positions were then updated according to Bayes' theorem using these estimates.

RESULTS

After updating with new trial data, a wide range of starting positions resulted in credible intervals that did not include no effect of amyloid reduction on CDR-SB score.

DISCUSSION

For a range of starting beliefs and assuming the veracity of the underlying data, rational observers would conclude there is a small benefit of amyloid reductions on cognition. This benefit must be weighed against opportunity cost and side-effect risk.

HIGHLIGHTS

The results of recent trials of amyloid-targeting drugs have rekindled discussion on the impact of amyloid reductions achieved with amyloid-targeting drugs on cognition. Prior to the announcement of trial results, beliefs about the effects of altering amyloid levels varied. For a range of starting beliefs, one would conclude there is a small benefit of amyloid reductions due to amyloid-targeting drugs on cognition. The perceived value of individual drugs must balance the magnitude of this benefit against opportunity cost and risk of side effects.

Association of cancer history with structural brain aging markers of Alzheimer's disease and related dementias risk

INTRODUCTION

Cancer survivors are less likely than comparably aged individuals without a cancer history to develop Alzheimer's disease and related dementias (ADRD).

METHODS

In the UK Biobank, we investigated associations between cancer history and five structural magnetic resonance imaging (MRI) markers for ADRD risk, using linear mixed-effects models to assess differences in mean values and quantile regression to examine whether associations varied across the distribution of MRI markers.

RESULTS

Cancer history was associated with smaller mean hippocampal volume (b = -19 mm3 , 95% CI = -36, -1) and lower mean cortical thickness in the Alzheimer's disease signature region (b = -0.004 mm, 95% CI = -0.007, -0.000). Quantile regressions indicated individuals most vulnerable to ADRD were more affected by cancer history.

DISCUSSION

Some brain MRI markers associated with ADRD risk were elevated in adults with a history of cancer. The magnitude of the adverse associations varied across quantiles of neuroimaging markers, and the pattern suggests possible harmful associations for individuals already at high ADRD risk.

HIGHLIGHTS

We found no evidence of an inverse association between cancer history and ADRD-related neurodegeneration. Cancer history was associated with smaller mean hippocampal volume and lower mean cortical thickness in the Alzheimer's disease signature region. Quantile regressions indicated individuals most vulnerable to ADRD were more affected by cancer history.

Metformin Cessation and Dementia Incidence

Importance

Prior studies suggested that metformin may be associated with reduced dementia incidence, but associations may be confounded by disease severity and prescribing trends. Cessation of metformin therapy in people with diabetes typically occurs due to signs of kidney dysfunction but sometimes is due to less serious adverse effects associated with metformin.

Objective

To investigate the association of terminating metformin treatment for reasons unrelated to kidney dysfunction with dementia incidence.

Design, Setting, and Participants

This cohort study was conducted at Kaiser Permanente Northern California, a large integrated health care delivery system, among a cohort of metformin users born prior to 1955 without history of diagnosed kidney disease at metformin initiation. Dementia follow-up began with the implementation of electronic health records in 1996 and continued to 2020. Data were analyzed from November 2021 through September 2023.

Exposures

A total of 12 220 early terminators, individuals who stopped metformin with normal estimated glomerular filtration rate (eGFR), were compared with routine metformin users, who had not yet terminated metformin treatment or had terminated (with or without restarting) after their first abnormal eGFR measurement. Early terminators were matched with routine users of the same age and gender who had diabetes for the same duration.

Main outcomes and measures

The outcome of interest was all-cause incident dementia. Follow-up for early terminators and their matched routine users was started at age of termination for the early terminator. Survival models adjusted for sociodemographic characteristics and comorbidities at the time of metformin termination (or matched age). Mediation models with HbA1c level and insulin usage 1 and 5 years after termination tested whether changes in blood glucose or insulin usage explained associations between early termination of metformin and dementia incidence.

Results

The final analytic sample consisted of 12 220 early terminators (5640 women [46.2%]; mean [SD] age at start of first metformin prescription, 59.4 [9.0] years) and 29 126 routine users (13 582 women [46.6%]; mean [SD] age at start of first metformin prescription, 61.1 [8.9] years). Early terminators had 1.21 times the hazard of dementia diagnosis compared with routine users (hazard ratio, 1.21; 95% CI, 1.12 to 1.30). In mediation analysis, contributions to this association by changes in HbA1c level or insulin use ranged from no contribution (0.00 years; 95% CI, -0.02 to 0.02 years) for insulin use at 5 years after termination to 0.07 years (95% CI, 0.02 to 0.13 years) for HbA1c level at 1 year after termination, suggesting that the association was largely independent of changes in HbA1c level and insulin usage.

Conclusions and Relevance

In this study, terminating metformin treatment was associated with increased dementia incidence. This finding may have important implications for clinical treatment of adults with diabetes and provides additional evidence that metformin is associated with reduced dementia risk.

Association between cancer and dementia risk in the UK Biobank: evidence of diagnostic bias

Epidemiological studies have identified an inverse association between cancer and dementia. Underlying methodological biases have been postulated, yet no studies have systematically investigated the potential for each source of bias within a single dataset. We used the UK Biobank to compare estimates for the cancer-dementia association using different analytical specifications designed to sequentially address multiple sources of bias, including competing risk of death, selective survival, confounding bias, and diagnostic bias. We included 140,959 UK Biobank participants aged ≥ 55 without dementia before enrollment and with linked primary care data. We used cancer registry data to identify cancer cases prevalent before UK Biobank enrollment and incident cancer diagnosed after enrollment. We used Cox models to evaluate associations of prevalent and incident cancer with all-cause dementia, Alzheimer's disease (AD), and vascular dementia. We used time-varying models to evaluate diagnostic bias. Over a median follow-up of 12.3 years, 3,310 dementia cases were diagnosed. All-site incident cancer was positively associated with all-cause dementia incidence (hazard ratio [HR] = 1.14, 95% CI: 1.02-1.29), but prevalent cancer was not (HR = 1.04, 95% CI: 0.92-1.17). Results were similar for vascular dementia. AD was not associated with prevalent or incident cancer. Dementia diagnosis was substantially elevated in the first year after cancer diagnosis (HR = 1.83, 95% CI: 1.42-2.36), after which the association attenuated to null, suggesting diagnostic bias. Following a cancer diagnosis, health care utilization or cognitive consequences of diagnosis or treatment may increase chance of receiving a dementia diagnosis, creating potential diagnostic bias in electronic health records-based studies.

Pragmatic approaches to handling practice effects in longitudinal cognitive aging research

INTRODUCTION

The challenge of accounting for practice effects (PEs) when modeling cognitive change was amplified by the COVID-19 pandemic, which introduced period and mode effects that may bias the estimation of cognitive trajectory.

METHODS

In three Kaiser Permanente Northern California prospective cohorts, we compared predicted cognitive trajectories and the association of grip strength with cognitive decline using three approaches: (1) no acknowledgment of PE, (2) inclusion of a wave indicator, and (3) constraining PE based on a preliminary model (APM) fit using a subset of the data.

RESULTS

APM-based correction for PEs based on balanced, pre-pandemic data, and with current age as the timescale produced the smallest discrepancy between within-person and between-person estimated age effects. Estimated associations between grip strength and cognitive decline were not sensitive to the approach used.

DISCUSSION

Constraining PEs based on a preliminary model is a flexible, pragmatic approach allowing for meaningful interpretation of cognitive change.

HIGHLIGHTS

The magnitude of practice effects (PEs) varied widely by study. When PEs were present, the three PE approaches resulted in divergent estimated age-related cognitive trajectories. Estimated age-related cognitive trajectories were sometimes implausible in models that did not account for PEs. The associations between grip strength and cognitive decline did not differ by the PE approach used. Constraining PEs based on estimates from a preliminary model allows for a meaningful interpretation of cognitive change.

Key questions for the evaluation of anti-amyloid immunotherapies for Alzheimer's disease

The clinical benefit associated with anti-amyloid immunotherapies, a new class of drugs for the treatment of Alzheimer's disease, is predicated on their ability to modify disease course by lowering brain amyloid levels. At the time of writing, two amyloid-lowering antibodies, aducanumab and lecanemab, have obtained United States Food and Drug Administration accelerated approval, with further agents of this class in the Alzheimer's disease treatment pipeline. Based on limited published clinical trial data to date, regulators, payors and physicians will need to assess their efficacy, clinical effectiveness and safety, as well as cost and accessibility. We propose that attention to three important questions related to treatment efficacy, clinical effectiveness and safety should guide evidence-based consideration of this important class of drugs. These are: (1) Were trial statistical analyses appropriate and did they convincingly support claims of efficacy? (2) Do reported treatment effects outweigh safety concerns and are they generalizable to a representative clinical population of people with Alzheimer's disease? and (3) Do the data convincingly demonstrate disease course modification, suggesting that increasing clinical benefits beyond the duration of the trials are likely? We suggest specific approaches to interpreting trial results for these drugs and highlight important areas of uncertainty where additional data and a cautious interpretation of existing results is warranted. Safe, effective and accessible treatments for Alzheimer's disease are eagerly awaited by millions of patients and their caregivers worldwide. While amyloid-targeting immunotherapies may be promising disease-modifying Alzheimer's disease treatments, rigorous and unbiased assessment of clinical trial data is critical to regulatory decision-making and subsequently determining their provision and utility in routine clinical practice. Our recommendations provide a framework for evidence-based appraisal of these drugs by regulators, payors, physicians and patients.

Education, incident cancer, and rate of memory decline in a national sample of US adults in mid-to-later-life

INTRODUCTION

Middle-aged and older adults who develop cancer experience memory loss following diagnosis, but memory decline in the years before and after cancer diagnosis is slower compared to their cancer-free counterparts. Educational attainment strongly predicts memory function during aging, but it is unclear whether education protects against memory loss related to cancer incidence or modifies long-term memory trajectories in middle-aged and older cancer survivors.

MATERIALS AND METHODS

Data were from 14,449 adults (3,248 with incident cancer, excluding non-melanoma skin cancer) aged 50+ in the population-based US Health and Retirement Study from 1998 to 2016. Memory was assessed every two years as a composite of immediate and delayed word recall tests and proxy assessments for impaired individuals. Memory scores all time points were standardized at to the baseline distribution. Using multivariate-adjusted linear mixed-effects models, we estimated rates of memory decline in the years before cancer diagnosis, shortly after diagnosis, and in the years after diagnosis. We compared rates of memory decline between incident cancer cases and age-matched cancer-free adults, overall and according to level of education (<12 years, "low"; 12 to <16 years, "intermediate"; ≥16 years, "high").

RESULTS

Incident cancer diagnoses were followed by short-term declines in memory averaging 0.06 standard deviation (SD) units (95% confidence interval [CI]: -0.084, -0.036). Those with low education experienced the strongest magnitude of short-term decline in memory after diagnosis (-0.10 SD units, 95% CI: -0.15, -0.05), but this estimate was not statistically significantly different from the short-term decline in memory experienced by those with high education (-0.04 SD units, 95% CI: -0.08, 0.01; p-value for education as an effect modifier = 0.15). In the years prior to and following an incident cancer diagnosis, higher educational attainment was associated with better memory, but it did not modify the difference in rate of long-term memory decline between cancer survivors and those who remained cancer-free.

DISCUSSION

Education was associated with better memory function over time among both cancer survivors and cancer-free adults aged 50 and over. Low education may be associated with a stronger short-term decline in memory after a cancer diagnosis.

Estimated Effects of Amyloid Reduction on Cognitive Change: A Bayesian Update across a Range of Priors

Introduction

Results of the CLARITY-AD and GRADUATE I and II trials rekindled discussion on the impact of amyloid-targeting drugs. We use a Bayesian approach to quantify how a rational observer would have updated their prior beliefs based on new trial results.

Methods

We used publicly available data from the CLARITY-AD and GRADUATE I & II trials to estimate the effect of reducing amyloid on CDR-SB score. A range of prior positions were then updated according to Bayes Theorem using these estimates.

Results

After updating with new trial data, a wide range of starting positions resulted in credible intervals that did not include no effect of amyloid reduction on CDR-SB.

Discussion

For a range of starting beliefs and assuming veracity of underlying data, rational observers would conclude there is a small benefit of amyloid-reductions on cognition. This benefit must be weighed against opportunity cost and side effect risk.

Discordance in chromosomal and self-reported sex in the UK Biobank: Implications for transgender- and intersex-inclusive data collection

There is growing need to distinguish between sex and gender. While sex is assigned at birth, gender is socially constructed and may not correspond to one's assigned sex. However, in most research studies, sex or gender is assessed in isolation or the terms are used interchangeably, which has implications for research accuracy and inclusivity. We used data from the UK Biobank to quantify the prevalence of disagreement between chromosomal and self-reported sex and identify potential reasons for discordance. Among approximately 200 individuals with sex discordance, 71% of discordances were potentially explained by the presence of intersex traits or transgender identity. The findings indicate that when describing sex- and/or gender-specific differences in health, researchers may be limited in their ability to draw conclusions regarding specific sex and/or gender health information.

Associations Between Handgrip Strength and Dementia Risk, Cognition, and Neuroimaging Outcomes in the UK Biobank Cohort Study

IMPORTANCE

The associations between muscle strength and cognitive outcomes have sparked interest in interventions that increase muscle strength for prevention of dementia, but the associations between muscle strength and cognitive aging are unclear, particularly among middle-aged adults.

OBJECTIVE

To evaluate the association between handgrip strength (HGS) and dementia, reduced cognition, and poorer neuroimaging outcomes in a UK population of middle-aged adults.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study evaluated UK Biobank participants aged 39 to 73 years enrolled from 2006 to 2010 with measured HGS and prospectively followed up for dementia diagnosis. Data were analyzed from October 2021 to April 2022.

EXPOSURES

HGS assessed in both hands via dynamometer.

MAIN OUTCOMES AND MEASURES

Outcomes included cognitive test scores (fluid intelligence and prospective memory), brain magnetic resonance imaging measures (total brain volume, white matter hyperintensity, and hippocampal volume), and incident dementia (all-cause, vascular, and Alzheimer disease [AD] from primary care, hospital, or death records) over a median (IQR) of 11.7 (11.0-12.4) years of follow-up. Mixed-effects linear and logistic regressions and Cox proportional-hazard models were used to estimate associations, stratified by gender and adjusted for covariates. Estimates are presented per 5-kg decrement in HGS. To evaluate reverse causation, we assessed whether a polygenic risk score for AD is associated with HGS.

RESULTS

A subsample of 190 406 adult participants in the UK Biobank (mean [SD] age, 56.5 [8.1] years; 102 735 women [54%]) were evaluated. A 5-kg decrement in HGS was associated with lower fluid intelligence scores in men (β, -0.007; 95% CI, -0.010 to -0.003) and women (β, -0.04; 95% CI, -0.05 to -0.04. A 5-kg decrement in HGS was associated with worse odds of correctly responding to a prospective memory task for men (odds ratio, 0.91; 95% CI, 0.90 to 0.92) and women (odds ratio, 0.88; 95% CI, 0.87 to 0.90). A 5-kg decrement in HGS was associated with greater white matter hyperintensity volume in men (β, 92.22; 95% CI, 31.09 to 153.35) and women (β, 83.56; 95% CI, 13.54 to 153.58). A 5-kg decrement in HGS was associated with incident dementia for men (hazard ratio, 1.20; 95% CI, 1.12 to 1.28) and women (hazard ratio, 1.12; 95% CI, 1.00 to 1.26). The AD genetic risk score was not significantly associated with HGS.

CONCLUSIONS AND RELEVANCE

These findings suggest that HGS is associated with measures of neurocognitive brain health among men and women and they add to a growing body of research indicating that interventions designed to increase muscle strength, particularly among middle-aged adults, may hold promise for the maintenance of neurocognitive brain health.

Association of Genetic Variants Linked to Late-Onset Alzheimer Disease With Cognitive Test Performance by Midlife

IMPORTANCE

Identifying the youngest age when Alzheimer disease (AD) influences cognition and the earliest affected cognitive domains will improve understanding of the natural history of AD and approaches to early diagnosis.

OBJECTIVE

To evaluate the age at which cognitive differences between individuals with higher compared with lower genetic risk of AD are first apparent and which cognitive assessments show the earliest difference.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used data from UK Biobank participants of European genetic ancestry, aged 40 years or older, who contributed genotypic and cognitive test data from January 1, 2006, to December 31, 2015. Data analysis was performed from March 10, 2020, to January 4, 2022.

EXPOSURE

The AD genetic risk score (GRS), which is a weighted sum of 23 single-nucleotide variations.

MAIN OUTCOMES AND MEASURES

Seven cognitive tests were administered via touchscreen at in-person visits or online. Cognitive domains assessed included fluid intelligence, episodic memory, processing speed, executive functioning, and prospective memory. Multiple cognitive measures were derived from some tests, yielding 32 separate measures. Interactions between age and AD-GRS for each of the 32 cognitive measures were tested with linear regression using a Bonferroni-corrected P value threshold. For cognitive measures with significant evidence of age by AD-GRS interaction, the youngest age of interaction was assessed with new regression models, with nonlinear specification of age terms. Models with youngest age of interaction from 40 to 70 years, in 1-year increments, were compared, and the best-fitting model for each cognitive measure was chosen. Results across cognitive measures were compared to determine which cognitive indicators showed earliest AD-related change.

RESULTS

A total of 405 050 participants (mean [SD] age, 57.1 [7.9] years; 54.1% female) were included. Sample sizes differed across cognitive tests (from 12 455 to 404 682 participants). The AD-GRS significantly modified the association with age on 13 measures derived from the pairs matching (range in difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 2.5%-11.5%), symbol digit substitution (range in difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 2.0%-5.8%), and numeric memory tests (difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 8.8%) (P = 1.56 × 10-3). Best-fitting models suggested that cognitive scores of individuals with a high vs low AD-GRS began to diverge by 56 years of age for all 13 measures and by 47 years of age for 9 measures.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study, by early midlife, subtle differences in memory and attention were detectable among individuals with higher genetic risk of AD.

Dynamical Modeling as a Tool for Inferring Causation

Dynamical models, commonly used in infectious disease epidemiology, are formal mathematical representations of time-changing systems or processes. For many chronic disease epidemiologists, the link between dynamical models and predominant causal inference paradigms is unclear. In this commentary, we explain the use of dynamical models for representing causal systems and the relevance of dynamical models for causal inference. In certain simple settings, dynamical modeling and conventional statistical methods (e.g., regression-based methods) are equivalent, but dynamical modeling has advantages over conventional statistical methods for many causal inference problems. Dynamical models can be used to transparently encode complex biological knowledge, interference and spillover, effect modification, and variables that influence each other in continuous time. As our knowledge of biological and social systems and access to computational resources increases, there will be growing utility for a variety of mathematical modeling tools in epidemiology.

The role of dementia diagnostic delay in the inverse cancer-dementia association

BACKGROUND

Cancer is inversely associated with dementia. Using simulations, we examined whether this inverse association may be explained by dementia diagnosis timing, including death before dementia diagnosis and differential diagnosis patterns by cancer history.

METHODS

We used multistate Markov simulation models to generate cohorts 65 years of age and free of cancer and dementia at baseline; follow-up for incident cancer (all cancers, breast, prostate, and lung cancer), dementia, dementia diagnosis among those with dementia, and death occurred monthly over 30 years. Models specified no true effect of cancer on dementia, and used age-specific transition rates calibrated to US population and cohort data. We varied the average lapse between dementia onset and diagnosis, including non-differential and differential delays by cancer history, and examined observed incidence rate ratios (IRRs) for the effect of cancer on dementia diagnosis.

RESULTS

Non-differential dementia diagnosis delay introduced minimal bias (IRRs=0.98-1.02) for all cancer, breast, and prostate models and substantial bias (IRR=0.78) in lung cancer models. For the differential dementia diagnosis delay model of all cancer types combined, simulation scenarios with ≥20% lower dementia diagnosis rate (additional 4.5-month delay) in those with cancer history versus without yielded results consistent with literature estimates. Longer dementia diagnosis delays in those with cancer and higher mortality in those with cancer and dementia yielded more bias.

CONCLUSIONS

Delays in dementia diagnosis may play a role in the inverse cancer-dementia relationship, especially for more fatal cancers, but moderate differential delays in those with cancer were needed to fully explain the literature-reported IRRs.

Proof of Concept Example for Use of Simulation to Allow Data Pooling Despite Privacy Restrictions

BACKGROUND

Integrating results from multiple samples is often desirable, but privacy restrictions may preclude full data pooling, and most datasets do not include fully harmonized variable sets. We propose a simulation-based method leveraging partial information across datasets to guide creation of synthetic data based on explicit assumptions about the underlying causal structure that permits pooled analyses that adjust for all desired confounders in the context of privacy restrictions.

METHODS

This proof-of-concept project uses data from the Health and Retirement Study (HRS) and Atherosclerosis Risk in Communities (ARIC) study. We specified an estimand of interest and a directed acyclic graph (DAG) summarizing the presumed causal structure for the effect of glycated hemoglobin (HbA1c) on cognitive change. We derived publicly reportable statistics to describe the joint distribution of each variable in our DAG. These summary estimates were used as data-generating rules to create synthetic datasets. After pooling, we imputed missing covariates in the synthetic datasets and used the synthetic data to estimate the pooled effect of HbA1c on cognitive change, adjusting for all desired covariates.

RESULTS

Distributions of covariates and model coefficients and associated standard errors for our model estimating the effect of HbA1c on cognitive change were similar across cohort-specific original and preimputation synthetic data. The estimate from the pooled synthetic incorporates control for confounders measured in either original dataset.

DISCUSSION

Our approach has advantages over meta-analysis or individual-level pooling/data harmonization when privacy concerns preclude data sharing and key confounders are not uniformly measured across datasets.

A Randomized Study to Assess the Effect of Including the Graduate Record Examinations Results on Reviewer Scores for Underrepresented Minorities

Whether requiring Graduate Record Examinations (GRE) results for doctoral applicants affects the diversity of admitted cohorts remains uncertain. This study randomized applications to 2 population-health doctoral programs at the University of California San Francisco to assess whether masking reviewers to applicant GRE results differentially affects reviewers’ scores for underrepresented minority (URM) applicants from 2018–2020. Applications with GRE results and those without were randomly assigned to reviewers to designate scores for each copy (1–10, 1 being best). URM was defined as self-identification as African American/Black, Filipino, Hmong, Vietnamese, Hispanic/Latinx, Native American/Alaska Native, or Native Hawaiian/Other Pacific Islander. We used linear mixed models with random effects for the applicant and fixed effects for each reviewer to evaluate the effect of masking the GRE results on the overall application score and whether this effect differed by URM status. Reviewer scores did not significantly differ for unmasked versus masked applications among non-URM applicants (β = 0.15; 95% CI: −0.03, 0.33) or URM applicants (β = 0.02, 95% CI: −0.49, 0.54). We did not find evidence that removing GREs differentially affected URM compared with non-URM students (β for interaction = −0.13, 95% CI: −0.55, 0.29). Within these doctoral programs, results indicate that GRE scores neither harm nor help URM applicants.

Amyloid-PET imaging offers small improvements in predictions of future cognitive trajectories

BACKGROUND

Amyloid β (Aβ) is thought to initiate a cascade of pathology culminating in Alzheimer's disease-related cognitive decline. Aβ accumulation in brain tissues may begin one to two decades prior to clinical diagnosis of Alzheimer's disease. Prior studies have demonstrated that Aβ detected in vivo with positron emission tomography with amyloid ligands (amyloid-PET) predicts contemporaneously measured cognition and future cognitive trajectories. Prior studies have not evaluated the added value of Aβ measures in predicting future cognition when repeated past cognitive measures are available. We evaluated the extent to which amyloid-PET improves prediction of future cognitive changes over and above predictions based only on sociodemographics and past cognitive measures.

METHODS

We used data from participants in the University of California Davis Alzheimer's Disease Research cohort who were cognitively normal at baseline, participated in amyloid-PET imaging, and completed at least three cognitive assessments prior to amyloid-PET imaging (N = 132 for memory andN = 135 for executive function). We used sociodemographic and cognitive measures taken prior to amyloid-PET imaging to predict cognitive trajectory after amyloid-PET imaging and assessed whether measures of amyloid burden improved predictions of subsequent cognitive change. Improvements in prediction were characterized as percent reduction in the mean squared error (MSE) in predicted cognition post amyloid-PET and increase in percent variance explained.

RESULTS

The base model using only sociodemographics and past cognitive performance explained the majority of variance in both predicted memory measures (55.6%) and executive function measures (74.5%) following amyloid-PET. Adding amyloid positivity to the model reduced the MSE for memory by 0.2%, 95% CI: (0%, 2.6%), p = 0.48 and for executive function by 3.4%, 95% CI: (0.6%, 10.2%), p = 0.002. This corresponded to an increase in the percent variance explained of 0.1%, 95% CI: (0%, 1.2%) for memory and 0.9%, 95% CI: (0.1%, 2.8%) for executive function. Similar results were obtained using a continuous measure of amyloid burden.

CONCLUSION

In this cohort, the addition of amyloid burden slightly improved predictions of executive function compared to models based only on past cognitive assessments and sociodemographics. When repeated cognitive assessments are available, the additional utility of amyloid-PET in predicting future cognitive impairment may be limited.

Effect of reductions in amyloid levels on cognitive change in randomized trials: instrumental variable meta-analysis

OBJECTIVE

To evaluate trials of drugs that target amyloid to determine whether reductions in amyloid levels are likely to improve cognition.

DESIGN

Instrumental variable meta-analysis.

SETTING

14 randomized controlled trials of drugs for the prevention or treatment of Alzheimer's disease that targeted an amyloid mechanism, identified from ClinicalTrials.gov.

POPULATION

Adults enrolled in randomized controlled trials of amyloid targeting drugs. Inclusion criteria for trials vary, but typically include adults aged 50 years or older with a diagnosis of mild cognitive impairment or Alzheimer's disease, and amyloid positivity at baseline.

MAIN OUTCOME MEASURES

Analyses included trials for which information could be obtained on both change in brain amyloid levels measured with amyloid positron emission tomography and change in at least one cognitive test score reported for each randomization arm.

RESULTS

Pooled results from the 14 randomized controlled trials were more precise than estimates from any single trial. The pooled estimate for the effect of reducing amyloid levels by 0.1 standardized uptake value ratio units was an improvement in the mini-mental state examination score of 0.03 (95% confidence interval -0.06 to 0.1) points. This study provides a web application that allows for the re-estimation of the results when new data become available and illustrates the magnitude of the new evidence that would be necessary to achieve a pooled estimate supporting the benefit of reducing amyloid levels.

CONCLUSIONS

Pooled evidence from available trials reporting both reduction in amyloid levels and change in cognition suggests that amyloid reduction strategies do not substantially improve cognition.

Are adverse childhood experiences associated with late-life cognitive performance across racial/ethnic groups: results from the Kaiser Healthy Aging and Diverse Life Experiences study baseline

OBJECTIVES

Evidence on adverse childhood experiences (ACEs) and late-life cognitive outcomes is inconsistent, with little research among diverse racial/ethnic groups. We investigated whether ACE exposures were associated with worse late-life cognition for all racial/ethnic groups and at different ages of exposure.

DESIGN

Covariate-adjusted mixed-effects linear regression models estimated associations of: (1) total number of ACEs experienced, (2) earliest age when ACE occurred and (3) type of ACE with overall cognition.

SETTING

Kaiser Permanente Northern California members aged 65 years and older, living in Northern California.

PARTICIPANTS

Kaiser Healthy Aging and Diverse Life Experiences study baseline participants, aged 65 years and older (n=1661; including 403 Asian-American, 338 Latino, 427 Black and 493 white participants).

RESULTS

Most respondents (69%) reported one or more ACE, most frequently family illness (36%), domestic violence (23%) and parental divorce (22%). ACE count was not adversely associated with cognition overall (β=0.01; 95% CI -0.01 to 0.03), in any racial/ethnic group or for any age category of exposure. Pooling across all race/ethnicities, parent's remarriage (β=-0.11; 95% CI -0.20 to -0.03), mother's death (β=-0.18; 95% CI -0.30 to -0.07) and father's death (β=-0.11; 95% CI -0.20 to -0.01) were associated with worse cognition.

CONCLUSION

Adverse childhood exposures overall were not associated with worse cognition in older adults in a diverse sample, although three ACEs were associated with worse cognitive outcomes.

Cognitive Reserve, Incident Cancer, and Rate of Memory Decline in Later Life

Cognitive reserve (cognitive skills and abilities acquired before onset of brain pathology) helps maintain cognitive function during aging. Cognitive decline after cancer treatment, known as “chemobrain,” is a prevalent outcome among older cancer survivors. It is unknown whether cognitive reserve buffers against acute neuropathological events such as cancer-related cognitive decline. We examined acute and long-term rate of memory decline associated with incident cancer diagnosis by education levels as proxy for cognitive reserve (low: &lt;12 years; intermediate: 12 to &lt;16 years; high: ≥16 years) in 14,449 adults aged 50+ in the US Health and Retirement Study from 1998-2016. Memory (z-scored) was assessed biennially as immediate and delayed word recall combined with proxy assessments. We used adjusted linear mixed models to determine long-term rates of memory decline before and after cancer diagnosis, and acute memory decline immediately after diagnosis (3,248 incident cases), and compared them with corresponding memory trajectories in cancer-free participants. Acute memory decline immediately after diagnosis was larger in those with low (-0.098 SD units, 95% CI: -0.150, -0.045) versus high (-0.038 SD units, 95% CI: -0.084, -0.008) education. Long-term memory decline after cancer was faster in those with low (-1.16 SD units/decade, 95% CI: -1.25, -1.07) versus high (-0.89 SD units/decade, 95% CI: -0.96, -0.82) education. Consistent with previous research showing an inverse cancer-dementia relationship, individuals with cancer had more favorable memory trajectories than cancer-free individuals with similar age and education. Among those with cancer, lower cognitive reserve was associated with greater acute and long-term memory decline after diagnosis.

Association Between Alzheimer Disease and Cancer With Evaluation of Study Biases: A Systematic Review and Meta-analysis

IMPORTANCE

Observational studies consistently report inverse associations between cancer and Alzheimer disease (AD). Shared inverse etiological mechanisms might explain this phenomenon, but a systematic evaluation of methodological biases in existing studies is needed.

OBJECTIVES

To systematically review and meta-analyze evidence on the association between cancer and subsequent AD, systematically identify potential methodological biases in studies, and estimate the influence of these biases on the estimated pooled association between cancer and AD.

DATA SOURCES

All-language publications were identified from PubMed, Embase, and PsycINFO databases through September 2, 2020.

STUDY SELECTION

Longitudinal cohort studies and case-control studies on the risk of AD in older adults with a history of any cancer type, prostate cancer, breast cancer, colorectal cancer, or nonmelanoma skin cancer, relative to those with no cancer history.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently abstracted the data and evaluated study biases related to confounding, diagnostic bias, competing risks, or survival bias. Random-effects meta-analysis was used to provide pooled estimates of the association between cancer and AD. Metaregressions were used to evaluate whether the observed pooled estimate could be attributable to each bias. The study was designed and conducted according to the Preferring Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline.

MAIN OUTCOMES AND MEASURES

Incidence, hazard, or odds ratios for AD comparing older adults with vs without a previous cancer diagnosis.

RESULTS

In total, 19 cohort studies and 3 case-control studies of the associations between any cancer type (n = 13), prostate cancer (n = 5), breast cancer (n = 1), and nonmelanoma skin cancer (n = 3) with AD were identified, representing 9 630 435 individuals. In all studies combined, cancer was associated with decreased AD incidence (cohort studies: random-effects hazard ratio, 0.89; 95% CI, 0.79-1.00; case-control studies: random-effects odds ratio, 0.75; 95% CI, 0.61-0.93). Studies with insufficient or inappropriate confounder control or greater likelihood of AD diagnostic bias had mean hazard ratios closer to the null value, indicating that these biases could not explain the observed inverse association. Competing risks bias was rare. Studies with greater likelihood of survival bias had mean hazard ratios farther from the null value.

CONCLUSIONS AND RELEVANCE

The weak inverse association between cancer and AD may reflect shared inverse etiological mechanisms or survival bias but is not likely attributable to diagnostic bias, competing risks bias, or insufficient or inappropriate control for potential confounding factors.

Association of genetic risk for Alzheimer disease and hearing impairment

OBJECTIVE

To test the hypothesis that incipient Alzheimer disease (AD) may adversely affect hearing and that hearing loss may adversely affect cognition, we evaluated whether genetic variants that increase AD risk also increase problem hearing and genetic variants that increase hearing impairment risk do not influence cognition.

METHODS

UK Biobank participants without dementia ≥56 years of age with Caucasian genetic ancestry completed a Digit Triplets Test of speech-in-noise hearing (n = 80,074), self-reported problem hearing and hearing with background noise (n = 244,915), and completed brief cognitive assessments. A genetic risk score for AD (AD-GRS) was calculated as a weighted sum of 23 previously identified AD-related polymorphisms. A genetic risk score for hearing (hearing-GRS) was calculated using 3 previously identified polymorphisms related to hearing impairment. Using age-, sex-, and genetic ancestry-adjusted logistic and linear regression models, we evaluated whether the AD-GRS predicted poor hearing and whether the hearing-GRS predicted worse cognition.

RESULTS

Poor speech-in-noise hearing (>-5.5-dB speech reception threshold; prevalence 14%) was associated with lower cognitive scores (ß = -1.28; 95% confidence interval [CI] -1.54 to -1.03). Higher AD-GRS was significantly associated with poor speech-in-noise hearing (odds ratio [OR] 1.06; 95% CI 1.01-1.11) and self-reported problems hearing with background noise (OR 1.03; 95% CI 1.00-1.05). Hearing-GRS was not significantly associated with cognitive scores (ß = -0.05; 95% CI -0.17 to 0.07).

CONCLUSIONS

Genetic risk for AD also influences speech-in-noise hearing. We failed to find evidence that genetic risk for hearing impairment affects cognition. AD disease processes or a that shared etiology may cause speech-in-noise difficulty before dementia onset.

Genetic Risk of Alzheimer's Disease and Sleep Duration in Non-Demented Elders

Growing evidence has suggested an association between sleep duration and Alzheimer's disease (AD), but it is unclear if sleep duration is a manifestation of the AD disease process. We studied whether genetic liability for AD predicts sleep duration using a genetic risk score (GRS) for AD (AD-GRS), in 406,536 UK Biobank participants with European ancestry and without dementia at enrollment. Higher AD-GRS score was associated with shorter sleep (b = -0.014, 95% confidence interval [CI] = -0.022 to -0.006), especially in those aged 55+. Using AD-GRS as an instrumental variable for AD diagnosis, incipient AD reduced sleep duration by 1.87 hours (95% CI = 0.96, 2.78). Short sleep duration might be an early marker of AD. ANN NEUROL 2021;89:177-181.

The competing risk of death and selective survival cannot fully explain the inverse cancer-dementia association

INTRODUCTION

We evaluated whether competing risk of death or selective survival could explain the reported inverse association between cancer history and dementia incidence (incidence rate ratio [IRR] ≈ 0.62-0.85).

METHODS

A multistate simulation model of a cancer- and dementia-free cohort of 65-year-olds was parameterized with real-world data (cancer and dementia incidence, mortality), assuming no effect of cancer on dementia (true IRR = 1.00). To introduce competing risk of death, cancer history increased mortality. To introduce selective survival, we included a factor (prevalence ranging from 10% to 50%) that reduced cancer mortality and dementia incidence (IRRs ranged from 0.30 to 0.90). We calculated IRRs for cancer history on dementia incidence in the simulated cohorts.

RESULTS

Competing risk of death yielded unbiased cancer-dementia IRRs. With selective survival, bias was small (IRRs = 0.89 to 0.99), even under extreme scenarios.

DISCUSSION

The bias induced by selective survival in simulations was too small to explain the observed inverse cancer-dementia link, suggesting other mechanisms drive this association.

Assessing the utility of a smart thermometer and mobile application as a surveillance tool for influenza and influenza-like illness

Kinsa Inc. sells Food and Drug Administration-cleared smart thermometers, which synchronize with a mobile application, and may aid influenza forecasting efforts. We compare smart thermometer and mobile application data to regional influenza and influenza-like illness surveillance data from the California Department of Public Health. We evaluated the correlation between the regional California surveillance data and smart thermometer data, tested the hypothesis that smart thermometer readings and symptom reports provide regionally specific predictions, and determined whether smart thermometer and mobile application improved disease forecasts. Smart thermometer readings are highly correlated with regional surveillance data, are more predictive of surveillance data for their own region and season than for other times and places, and improve predictions of influenza, but not predictions of influenza-like illness. These results are consistent with the hypothesis that smart thermometer readings and symptom reports reflect underlying disease transmission in California. Data from such cloud-based devices could supplement syndromic influenza surveillance data.

Genotype-Specific Measles Transmissibility: A Branching Process Analysis

Background

Substantial heterogeneity in measles outbreak sizes may be due to genotype-specific transmissibility. Using a branching process analysis, we characterize differences in measles transmission by estimating the association between genotype and the reproduction number R among postelimination California measles cases during 2000-2015 (400 cases, 165 outbreaks).

Methods

Assuming a negative binomial secondary case distribution, we fit a branching process model to the distribution of outbreak sizes using maximum likelihood and estimated the reproduction number R for a multigenotype model.

Results

Genotype B3 is found to be significantly more transmissible than other genotypes (P = .01) with an R of 0.64 (95% confidence interval [CI], .48-.71), while the R for all other genotypes combined is 0.43 (95% CI, .28-.54). This result is robust to excluding the 2014-2015 outbreak linked to Disneyland theme parks (referred to as "outbreak A" for conciseness and clarity) (P = .04) and modeling genotype as a random effect (P = .004 including outbreak A and P = .02 excluding outbreak A). This result was not accounted for by season of introduction, age of index case, or vaccination of the index case. The R for outbreaks with a school-aged index case is 0.69 (95% CI, .52-.78), while the R for outbreaks with a non-school-aged index case is 0.28 (95% CI, .19-.35), but this cannot account for differences between genotypes.

Conclusions

Variability in measles transmissibility may have important implications for measles control; the vaccination threshold required for elimination may not be the same for all genotypes or age groups.

Multiple exposures, reinfection and risk of progression to active tuberculosis

A recent study reported on a tuberculosis (TB) outbreak in a largely Inuit village. Among newly infected individuals, exposure to additional active cases was associated with an increasing probability of developing active disease within a year. Using binomial risk models, we evaluated two potential mechanisms by which multiple infections during the first year following initial infection could account for increasing disease risk with increasing exposures. In the reinfection model, each infectious contact confers an independent risk of an infection, and infections contribute independently to active disease. In the threshold model, disease risk follows a sigmoidal function with small numbers of infectious contacts conferring a low risk of active disease and large numbers of contacts conferring a high risk. To determine the dynamic impact of reinfection during the early phase of infection, we performed simulations from a modified Reed-Frost model of TB dynamics following spread from an initial number of cases. We parametrized this model with the maximum-likelihood estimates from the reinfection and threshold models in addition to the observed distribution of exposures among new infections. We find that both models can plausibly account for the observed increase in disease risk with increasing infectious contacts, but the threshold model confers a better fit than a nested model without a threshold (p = 0.04). Our simulations indicate that multiple exposures to infectious individuals during this critical time period can lead to dramatic increases in outbreak size. In order to decrease TB burden in high-prevalence settings, it may be necessary to implement measures aimed at preventing repeated exposures, in addition to preventing primary infection.

Correction: Short-term leprosy forecasting from an expert opinion survey

[This corrects the article DOI: 10.1371/journal.pone.0182245.].

Compartmental Model Diagrams as Causal Representations in Relation to DAGs

Compartmental model diagrams have been used for nearly a century to depict causal relationships in infectious disease epidemiology. Causal directed acyclic graphs (DAGs) have been used more broadly in epidemiology since the 1990s to guide analyses of a variety of public health problems. Using an example from chronic disease epidemiology, the effect of type 2 diabetes on dementia incidence, we illustrate how compartmental model diagrams can represent the same concepts as causal DAGs, including causation, mediation, confounding, and collider bias. We show how to use compartmental model diagrams to explicitly depict interaction and feedback cycles. While DAGs imply a set of conditional independencies, they do not define conditional distributions parametrically. Compartmental model diagrams parametrically (or semiparametrically) describe state changes based on known biological processes or mechanisms. Compartmental model diagrams are part of a long-term tradition of causal thinking in epidemiology and can parametrically express the same concepts as DAGs, as well as explicitly depict feedback cycles and interactions. As causal inference efforts in epidemiology increasingly draw on simulations and quantitative sensitivity analyses, compartmental model diagrams may be of use to a wider audience. Recognizing simple links between these two common approaches to representing causal processes may facilitate communication between researchers from different traditions.

Facebook and Twitter vaccine sentiment in response to measles outbreaks

Social media posts regarding measles vaccination were classified as pro-vaccination, expressing vaccine hesitancy, uncertain, or irrelevant. Spearman correlations with Centers for Disease Control and Prevention-reported measles cases and differenced smoothed cumulative case counts over this period were reported (using time series bootstrap confidence intervals). A total of 58,078 Facebook posts and 82,993 tweets were identified from 4 January 2009 to 27 August 2016. Pro-vaccination posts were correlated with the US weekly reported cases (Facebook: Spearman correlation 0.22 (95% confidence interval: 0.09 to 0.34), Twitter: 0.21 (95% confidence interval: 0.06 to 0.34)). Vaccine-hesitant posts, however, were uncorrelated with measles cases in the United States (Facebook: 0.01 (95% confidence interval: -0.13 to 0.14), Twitter: 0.0011 (95% confidence interval: -0.12 to 0.12)). These findings may result from more consistent social media engagement by individuals expressing vaccine hesitancy, contrasted with media- or event-driven episodic interest on the part of individuals favoring current policy.

Short-term leprosy forecasting from an expert opinion survey

We conducted an expert survey of leprosy (Hansen’s Disease) and neglected tropical disease experts in February 2016. Experts were asked to forecast the next year of reported cases for the world, for the top three countries, and for selected states and territories of India. A total of 103 respondents answered at least one forecasting question. We elicited lower and upper confidence bounds. Comparing these results to regression and exponential smoothing, we found no evidence that any forecasting method outperformed the others. We found evidence that experts who believed it was more likely to achieve global interruption of transmission goals and disability reduction goals had higher error scores for India and Indonesia, but lower for Brazil. Even for a disease whose epidemiology changes on a slow time scale, forecasting exercises such as we conducted are simple and practical. We believe they can be used on a routine basis in public health.

A dynamic model for estimating adult female mortality from ovarian dissection data for the tsetse fly Glossina pallidipes Austen sampled in Zimbabwe

Human and animal trypanosomiasis, spread by tsetse flies (Glossina spp), is a major public health concern in much of sub-Saharan Africa. The basic reproduction number of vector-borne diseases, such as trypanosomiasis, is a function of vector mortality rate. Robust methods for estimating tsetse mortality are thus of interest for understanding population and disease dynamics and for optimal control. Existing methods for estimating mortality in adult tsetse, from ovarian dissection data, often use invalid assumptions of the existence of a stable age distribution, and age-invariant mortality and capture probability. We develop a dynamic model to estimate tsetse mortality from ovarian dissection data in populations where the age distribution is not necessarily stable. The models correspond to several hypotheses about how temperature affects mortality: no temperature dependence (model 1), identical temperature dependence for mature adults and immature stages, i.e., pupae and newly emerged adults (model 2), and differential temperature dependence for mature adults and immature stages (model 3). We fit our models to ovarian dissection data for G. pallidipes collected at Rekomitjie Research Station in the Zambezi Valley in Zimbabwe. We compare model fits to determine the most probable model, given the data, by calculating the Akaike Information Criterion (AIC) for each model. The model that allows for a differential dependence of temperature on mortality for immature stages and mature adults (model 3) performs significantly better than models 1 and 2. All models produce mortality estimates, for mature adults, of approximately 3% per day for mean daily temperatures below 25°C, consistent with those of mark-recapture studies performed in other settings. For temperatures greater than 25°C, mortality among immature classes of tsetse increases substantially, whereas mortality remains roughly constant for mature adults. As a sensitivity analysis, model 3 was simultaneously fit to both the ovarian dissection and trap data; while this fit also produces comparable mortality at temperatures below 25°C, it is not possible to obtain good fits to both data sources simultaneously, highlighting the uncertain correspondence between trap catches and population levels and/or the need for further improvements to our model. The modelling approach employed here could be applied to any substantial time series of age distribution data.

Modeling historical tuberculosis epidemics among Canadian First Nations: effects of malnutrition and genetic variation

Late 19th century epidemics of tuberculosis (TB) in Western Canadian First Nations resulted in peak TB mortality rates more than six times the highest rates recorded in Europe. Using a mathematical modeling approach and historical TB mortality time series, we investigate potential causes of high TB mortality and rapid epidemic decline in First Nations from 1885 to 1940. We explore two potential causes of dramatic epidemic dynamics observed in this setting: first, we explore effects of famine prior to 1900 on both TB and population dynamics. Malnutrition is recognized as an individual-level risk factor for TB progression and mortality; its population-level effects on TB epidemics have not been explored previously. Second, we explore effects of heterogeneity in susceptibility to TB in two ways: modeling heterogeneity in susceptibility to infection, and heterogeneity in risk of developing disease once infected. Our results indicate that models lacking famine-related changes in TB parameters or heterogeneity result in an implausibly poor fit to both the TB mortality time series and census data; the inclusion of these features allows for the characteristic decline and rise in population observed in First Nations during this time period and confers improved fits to TB mortality data.

Mortality estimates from ovarian age distributions of the tsetse fly Glossina pallidipes Austen sampled in Zimbabwe suggest the need for new analytical approaches

Mortality estimates are central to understanding tsetse fly population dynamics, but are difficult to acquire from wild populations. They can be obtained from age distribution data but, with limited data, it is unclear whether the assumptions required to make the estimates are satisfied and, if not, how violations affect the estimates. We evaluate the assumptions required for existing mortality estimation techniques using long-term longitudinal ovarian dissection data from 144,106 female tsetse, Glossina pallidipes Austen, captured in Zimbabwe between 1988 and 1999. At the end of the hot-dry season each year, mean ovarian ages peaked, and maximum-likelihood mortality estimates declined to low levels, contrary to mark-recapture estimates, suggesting violations of the assumptions underlying the estimation technique. We demonstrate that age distributions are seldom stable for G. pallidipes at our study site, and hypothesize that this is a consequence of a disproportionate increase in the mortality of pupae and young adults at the hottest times of the year. Assumptions of age-independent mortality and capture probability are also violated, the latter bias varying with capture method and with pregnancy and nutritional status. As a consequence, mortality estimates obtained from ovarian dissection data are unreliable. To overcome these problems we suggest simulating female tsetse populations, using dynamical modelling techniques that make no assumptions about the stability of the age distribution.

The role of vaccination coverage, individual behaviors, and the public health response in the control of measles epidemics: an agent-based simulation for California

BACKGROUND

Measles cases continue to occur among susceptible individuals despite the elimination of endemic measles transmission in the United States. Clustering of disease susceptibility can threaten herd immunity and impact the likelihood of disease outbreaks in a highly vaccinated population. Previous studies have examined the role of contact tracing to control infectious diseases among clustered populations, but have not explicitly modeled the public health response using an agent-based model.

METHODS

We developed an agent-based simulation model of measles transmission using the Framework for Reconstructing Epidemiological Dynamics (FRED) and the Synthetic Population Database maintained by RTI International. The simulation of measles transmission was based on interactions among individuals in different places: households, schools, daycares, workplaces, and neighborhoods. The model simulated different levels of immunity clustering, vaccination coverage, and contact investigations with delays caused by individuals' behaviors and/or the delay in a health department's response. We examined the effects of these characteristics on the probability of uncontrolled measles outbreaks and the outbreak size in 365 days after the introduction of one index case into a synthetic population.

RESULTS

We found that large measles outbreaks can be prevented with contact investigations and moderate contact rates by having (1) a very high vaccination coverage (≥ 95%) with a moderate to low level of immunity clustering (≤ 0.5) for individuals aged less than or equal to 18 years, or (2) a moderate vaccination coverage (85% or 90%) with no immunity clustering for individuals (≤ 18 years of age), a short intervention delay, and a high probability that a contact can be traced. Without contact investigations, measles outbreaks may be prevented by the highest vaccination coverage with no immunity clustering for individuals (≤ 18 years of age) with moderate contact rates; but for the highest contact rates, even the highest coverage with no immunity clustering for individuals (≤ 18 years of age) cannot completely prevent measles outbreaks.

CONCLUSIONS

The simulation results demonstrated the importance of vaccination coverage, clustering of immunity, and contact investigations in preventing uncontrolled measles outbreaks.

Optimal seasonal timing of oral azithromycin for malaria

Mass administration of azithromycin for trachoma has been shown to reduce malarial parasitemia. However, the optimal seasonal timing of such distributions for antimalarial benefit has not been established. We performed numerical analyses on a seasonally forced epidemic model (of Ross-Macdonald type) with periodic impulsive annual mass treatment to address this question. We conclude that when azithromycin-based trachoma elimination programs occur in regions of seasonal malaria transmission, such as Niger, the optimal seasonal timing of mass drug administration (MDA) may not occur during the season of maximum transmission.

Autumn bloom of antarctic pack-ice algae

An autumn bloom of sea-ice algae was observed from February to June of 1992 within the upper 0.4 meter of multiyear ice in the Western Weddell Sea, Antarctica. The bloom was reliant on the freezing of porous areas within the ice that initiated a vertical exchange of nutrient-depleted brine with nutrient-rich seawater. This replenishment of nutrients to the algal community allowed the net production of 1760 milligrams of carbon and 200 milligrams of nitrogen per square meter of ice. The location of this autumn bloom is unlike that of spring blooms previously observed in both polar regions.