Prediction of disability-free survival in healthy older people

Prolonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6–77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people. Trial registration Clinicaltrials.gov (NCT01038583

Context: The Foundation of Close Reading of Primary Source Texts

The Common Core State Standards (CCSS) invite students to engage in close reading of primary source texts from American history, but an overly rigid definition of close reading that excludes providing background knowledge threatens to undermine these efforts. This approach flies in the face of decades of research on successful reading comprehension strategies. It also rejects the extensive literature on discipline-based learning in history, which has routinely affirmed the importance of context for understanding primary source texts. Primary sources are typically drawn from a world different from that of the students in time or place, or both. Teachers should provide historical context to their students by giving them information about the time, location, and purpose for the creation of the source. They should also situate the source in a specific location—whether local, national, or international—and examine the source in relation to other events of the time. Context is not the enemy of close reading of primary sources; context is the very thing that makes close reading possible and meaningful.</jats:p

Visitor management and revegetation efforts on a degraded Lake Superior cliff edge

Section: Management politics and method

Paradoxes and synergies: optimizing management of a deadly virus in an endangered carnivore

AbstractPathogen management strategies in wildlife are typically accompanied by an array of uncertainties such as the efficacy of vaccines or potential unintended consequences of interventions. In the context of such uncertainties, models of disease transmission can provide critical insight for optimizing pathogen management, especially for species of conservation concern. The endangered Florida panther experienced an outbreak of feline leukemia virus (FeLV) in 2002-04, and continues to be affected by this deadly virus. Ongoing management efforts aim to mitigate the effects of FeLV on panthers, but with limited information about which strategies may be most effective and efficient.We used a simulation-based approach to determine optimal FeLV management strategies in panthers. We simulated use of proactive FeLV management strategies (i.e., proactive vaccination) and several reactive strategies, including reactive vaccination and test-and-removal. Vaccination strategies accounted for imperfect vaccine-induced immunity, specifically partial immunity in which all vaccinates achieve partial pathogen protection. We compared the effectiveness of these different strategies in mitigating the number of FeLV mortalities and the duration of outbreaks.Results showed that inadequate proactive vaccination can paradoxically increase the number of disease-induced mortalities in FeLV outbreaks. These effects were most likely due to imperfect vaccine immunity causing vaccinates to serve as a semi-susceptible population, thereby allowing outbreaks to persist in circumstances otherwise conducive to fadeout. Combinations of proactive vaccination with reactive test-and-removal or vaccination, however, had a synergistic effect in reducing impacts of FeLV outbreaks, highlighting the importance of using mixed strategies in pathogen management.Synthesis and applications: Management-informed disease simulations are an important tool for identifying unexpected negative consequences and synergies among pathogen management strategies. In particular, we find that imperfect vaccine-induced immunity necessitates further consideration to avoid unintentionally worsening epidemics in some conditions. However, mixing proactive and reactive interventions can improve pathogen control while mitigating uncertainties associated with imperfect interventions.</jats:p

Agent Orange Exposure Does Not Predict for Shorter Overall Survival in Patients with Chronic Lymphocytic Leukemia: A National Veteran Affairs Tumor Registry Study

Abstract BACKGROUND: Agent Orange (AO), a 1:1 mixture of herbicides + TCDD (2,3,7,8-tetrachlorodibenzo-p-dioxin), was used during the Vietnam War to destroy dense jungle and enemy crops. In 2002 the Department of Veteran Affairs (VA) determined that chronic lymphocytic leukemia (CLL) was associated with AO exposure. Case-control studies suggest an increased risk of death from CLL in areas where herbicide use was highest. There is also an increased incidence of other cancers (prostate, melanoma) in AO-exposed veterans. Limited data exists as to the specific impact of AO exposure on CLL disease presentation and outcome. METHODS: Patients (pts) diagnosed with CLL from 2009-2013 were identified in the National VAMC Tumor Registry. Baseline demographic and laboratory parameters were obtained, including Rai stage, marrow cytogenetics (when available), and lymphocyte doubling time (LDT). AO exposure was identified according to the medical record. The VA Benefits and Compensation officers determine AO exposure based on whether a person served on land and in the brown waters in Vietnam during the appropriate timeframe. Timing and types of CLL therapies were identified to determine if AO exposure influenced CLL treatment. RESULTS: 2052 CLL pts were identified, of which 418 had AO exposure. AO-exposed pts presented at a younger age (63.2 versus [vs] 70.5 years (yrs), p &lt;0.0001), had a higher hemoglobin (14.3 vs 13.8 g/dl, p&lt;0.001) and lower lactate dehydrogenase (LDH) (203 vs 227 IU/L, p = 0.01) compared to those without AO exposure. There were no differences in white cell, platelet, or absolute lymphocyte counts, Rai stage or LDT among the groups. Cytogenetic data was available for 1167 pts. There was no difference in the incidence of 17p-, 11q-, or 13q- between the two groups. Median overall survival (OS) was significantly better in patients with AO exposure, even when adjusted for age and Rai stage (median not reached vs 91.2 months, p &lt;0.0001. OS benefit was primarily seen in pts age 60-69 yrs (p = 0.002), and those with 11q- (p = 0.001). No OS differences were found in pts with 17p- or 13q-. Among all pts, regardless of AO exposure status, OS decreased with higher Rai stage. There was a trend towards AO-exposed pts to be more likely to receive CLL-directed therapies (37% vs 32%, p = 0.07). AO exposed pts were more likely, than unexposed pts, to receive therapies as follows: fludarabine, chlorambucil, rituximab (FCR) first-line (38% vs 21%) and second-line (11.6 vs 5%); bendamustine + rituximab (BR) first-line (25% vs 18%), second-line (35 vs 26%), and third-line (31 vs 23%). Pts with no AO exposure were more likely to receive single agent chlorambucil or cyclophosphamide as first-line therapy (17 vs 10%). CONCLUSION: Pts with AO exposure, compared to unexposed pts, had an OS benefit independent of age and Rai stage, with this benefit seen primarily in younger pts (age 60-69 yrs) and in those with 11q-. AO-exposed pts were also more likely to receive disease-specific therapy. This unexpected OS finding will require further analyses for confounding variables, but could potentially be related to earlier treatment with regimens as FCR or BR. Disclosures Morrison: Celgene: Speakers Bureau; Genentech: Speakers Bureau; Gilead: Speakers Bureau; Pharmacyclics: Speakers Bureau; Celgene: Other: Data Monitoring Committee; Merck: Other: Adjudication Committee. </jats:sec

Seasonal changes in network connectivity and consequences for pathogen transmission in a solitary carnivore

Abstract Seasonal variation in habitat use and animal behavior can alter host contact patterns with potential consequences for pathogen transmission dynamics. The endangered Florida panther (Puma concolor coryi) has experienced significant pathogen-induced mortality and continues to be at risk of future epidemics. Prior research has found increased panther movement in Florida’s dry versus wet seasons, which may affect panther population connectivity and seasonally increase potential pathogen transmission. Our objective was to determine if Florida panthers are more spatially connected in dry seasons relative to wet seasons, and test if identified connectivity differences resulted in divergent predicted epidemic dynamics. We leveraged extensive panther telemetry data to construct seasonal panther home range overlap networks over an 11 year period. We tested for differences in network connectivity, and used observed network characteristics to simulate transmission of a broad range of pathogens through dry and wet season networks. We found that panthers were more spatially connected in dry seasons than wet seasons. Further, these differences resulted in a trend toward larger and longer pathogen outbreaks when epidemics were initiated in the dry season. Our results demonstrate that seasonal variation in behavioral patterns—even among largely solitary species—can have substantial impacts on epidemic dynamics

Wildfire risk science facilitates adaptation of fire-prone social-ecological systems to the new fire reality

Abstract Large and severe wildfires are an observable consequence of an increasingly arid American West. There is increasing consensus that human communities, land managers, and fire managers need to adapt and learn to live with wildfires. However, a myriad of human and ecological factors constrain adaptation, and existing science-based management strategies are not sufficient to address fire as both a problem and solution. To that end, we present a novel risk-science approach that aligns wildfire response decisions, mitigation opportunities, and land management objectives by consciously integrating social, ecological and fire management system needs. We use fire-prone landscapes of the US Pacific Northwest as our study area, and report on and describe how three complementary risk-based analytic tools—quantitative wildfire risk assessment, mapping of suppression difficulty, and atlases of potential control locations—can form the foundation for adaptive governance in fire management. Together, these tools integrate wildfire risk with fire management difficulties and opportunities, providing a more complete picture of the wildfire risk management challenge. Leveraging recent and ongoing experience integrating local experiential knowledge with these tools, we provide examples and discuss how these geospatial datasets create a risk-based planning structure that spans multiple spatial scales and uses. These uses include pre-planning strategic wildfire response, implementing safe wildfire response balancing risk with likelihood of success, and alignment of non-wildfire mitigation opportunities to support wildfire risk management more directly. We explicitly focus on multi-jurisdictional landscapes to demonstrate how these tools highlight the shared responsibility of wildfire risk mitigation. By integrating quantitative risk science, expert judgement and adaptive co-management, this process provides a much-needed pathway to transform fire-prone social ecological systems to be more responsive and adaptable to change and live with fire in an increasingly arid American West.</jats:p

Transmission of one predicts another: Apathogenic proxies for transmission dynamics of a fatal virus

AbstractIdentifying drivers of transmission prior to an epidemic—especially of an emerging pathogen—is a formidable challenge for proactive disease management efforts. We tested a novel approach in the Florida panther, hypothesizing that apathogenic feline immunodeficiency virus (FIV) transmission could predict transmission dynamics for pathogenic feline leukemia virus (FeLV). We derived a transmission network using FIV whole genome sequences, and used exponential random graph models to determine drivers structuring this network. We used these drivers to predict FeLV transmission pathways among panthers and compared predicted outbreak dynamics against empirical FeLV outbreak data. FIV transmission was primarily driven by panther age class and distances between panther home range centroids. Prospective FIV-based modeling predicted FeLV dynamics at least as well as simpler, often retrospective approaches, with evidence that FIV-based predictions captured the spatial structuring of the observed FeLV outbreak. Our finding that an apathogenic agent can predict transmission of an analogously transmitted pathogen is an innovative approach that warrants testing in other host-pathogen systems to determine generalizability. Use of such apathogenic agents holds promise for improving predictions of pathogen transmission in novel host populations, and could thereby provide new strategies for proactive pathogen management in human and animal systems.</jats:p

Data_Sheet_1_Apathogenic proxies for transmission dynamics of a fatal virus.pdf

Identifying drivers of transmission—especially of emerging pathogens—is a formidable challenge for proactive disease management efforts. While close social interactions can be associated with microbial sharing between individuals, and thereby imply dynamics important for transmission, such associations can be obscured by the influences of factors such as shared diets or environments. Directly-transmitted viral agents, specifically those that are rapidly evolving such as many RNA viruses, can allow for high-resolution inference of transmission, and therefore hold promise for elucidating not only which individuals transmit to each other, but also drivers of those transmission events. Here, we tested a novel approach in the Florida panther, which is affected by several directly-transmitted feline retroviruses. We first inferred the transmission network for an apathogenic, directly-transmitted retrovirus, feline immunodeficiency virus (FIV), and then used exponential random graph models to determine drivers structuring this network. We then evaluated the utility of these drivers in predicting transmission of the analogously transmitted, pathogenic agent, feline leukemia virus (FeLV), and compared FIV-based predictions of outbreak dynamics against empirical FeLV outbreak data. FIV transmission was primarily driven by panther age class and distances between panther home range centroids. FIV-based modeling predicted FeLV dynamics similarly to common modeling approaches, but with evidence that FIV-based predictions captured the spatial structuring of the observed FeLV outbreak. While FIV-based predictions of FeLV transmission performed only marginally better than standard approaches, our results highlight the value of proactively identifying drivers of transmission—even based on analogously-transmitted, apathogenic agents—in order to predict transmission of emerging infectious agents. The identification of underlying drivers of transmission, such as through our workflow here, therefore holds promise for improving predictions of pathogen transmission in novel host populations, and could provide new strategies for proactive pathogen management in human and animal systems.</p