Role of big data in the early detection of Ebola and other emerging infectious diseases

The lack of adequate disease surveillance systems in Ebola-affected areas has both reduced the ability to respond locally and has increased global risk. There is a need to improve disease surveillance in vulnerable regions, and digital surveillance could present a viable approach.

Investigation of movement and factors influencing post-release survival of line-caught coral reef fish using recreational tag-recapture data

Six species of line-caught coral reef fish (Plectropomus spp., Lethrinus miniatus, Lethrinus laticaudis, Lutjanus sebae, Lutjanus malabaricus and Lutjanus erythropterus) were tagged by members of the Australian National Sportsfishing Association (ANSA) in Queensland between 1986 and 2003. Of the 14,757 fish tagged, 1607 were recaptured and we analysed these data to describe movement and determine factors likely to impact release survival. All species were classified as residents since over 80% of recaptures for each species occurred within 1 km of the release site. Few individuals (range 0.8-5%) were recaptured more than 20 km from their release point. L. sebae had a higher recapture rate (19.9%) than the other species studied (range 2.1-11.7%). Venting swimbladder gases, regardless of whether or not fish appeared to be suffering from barotrauma, significantly enhanced (P < 0.05) the survival of L. sebae and L. malabaricus but had no significant effect (P > 0.05) on L. erythropterus. The condition of fish on release, subjectively assessed by anglers, was only a significant effect on recapture rate for L. sebae where fish in "fair" condition had less than half the recapture rate of those assessed as in "excellent" or "good" condition. The recapture rate of L. sebae and L. laticaudis was significantly (P < 0.05) affected by depth with recapture rate declining in depths exceeding 30 m. Overall, the results showed that depth of capture, release condition and treatment for barotrauma influenced recapture rate for some species but these effects were not consistent across all species studied. Recommendations were made to the ANSA tagging clubs to record additional information such as injury, hooking location and hook type to enable a more comprehensive future assessment of the factors influencing release survival.

A real coded genetic algorithm for data partitioning and scheduling in networks with arbitrary processor release time

The problem of scheduling divisible loads in distributed computing systems, in presence of processor release time is considered. The objective is to find the optimal sequence of load distribution and the optimal load fractions assigned to each processor in the system such that the processing time of the entire processing load is a minimum. This is a difficult combinatorial optimization problem and hence genetic algorithms approach is presented for its solution.

Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data

Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called `early warning signals', and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data.

Spatio-Temporal Scanning and Statistical Test of the Accelerating Moment Release (AMR) Model Using Australian Earthquake Data

The Accelerating Moment Release (AMR) preceding earthquakes with magnitude above 5 in Australia that occurred during the last 20 years was analyzed to test the Critical Point Hypothesis. Twelve earthquakes in the catalog were chosen based on a criterion for the number of nearby events. Results show that seven sequences with numerous events recorded leading up to the main earthquake exhibited accelerating moment release. Two occurred near in time and space to other earthquakes preceded by AM R. The remaining three sequences had very few events in the catalog so the lack of AMR detected in the analysis may be related to catalog incompleteness. Spatio-temporal scanning of AMR parameters shows that 80% of the areas in which AMR occurred experienced large events. In areas of similar background seismicity with no large events, 10 out of 12 cases exhibit no AMR, and two others are false alarms where AMR was observed but no large event followed. The relationship between AMR and Load-Unload Response Ratio (LURR) was studied. Both methods predict similar critical region sizes, however, the critical point time using AMR is slightly earlier than the time of the critical point LURR anomaly.

Coupling ecology and economy: modeling optimal release scenarios for summer flounder (Paralichthys dentatus) stock enhancement

Increasing interest in the use of stock enhancement as a management tool necessitates a better understanding of the relative costs and benefits of alternative release strategies. We present a relatively simple model coupling ecology and economic costs to make inferences about optimal release scenarios for summer flounder (Paralichthys dentatus), a subject of stock enhancement interest in North Carolina. The model, parameterized from mark-recapture experiments, predicts optimal release scenarios from both survival and economic standpoints for varyious dates-of-release, sizes-at-release, and numbers of fish released. Although most stock enhancement efforts involve the release of relatively small fish, the model suggests that optimal results (maximum survival and minimum costs) will be obtained when relatively large fish (75–80 mm total length) are released early in the nursery season (April). We investigated the sensitivity of model predictions to violations of the assumption of density-independent mortality by including density-mortality relationships based on weak and strong type-2 and type-3 predator functional responses (resulting in depensatory mortality at elevated densities). Depending on postrelease density, density-mortality relationships included in the model considerably affect predicted postrelease survival and economic costs associated with enhancement efforts, but do not alter the release scenario (i.e. combination of release variables) that produces optimal results. Predicted (from model output) declines in flounder over time most closely match declines observed in replicate field sites when mortality in the model is density-independent or governed by a weak type-3 functional response. The model provides an example of a relatively easy-to-develop predictive tool with which to make inferences about the ecological and economic potential of stock enhancement of summer flounder and provides a template for model creation for additional species that are subjects of stock enhancement interest, but for which limited empirical data exist.

Early clopidogrel versus prasugrel use among contemporary STEMI and NSTEMI patients in the US: insights from the National Cardiovascular Data Registry.

BACKGROUND: P2Y12 antagonist therapy improves outcomes in acute myocardial infarction (MI) patients. Novel agents in this class are now available in the US. We studied the introduction of prasugrel into contemporary MI practice to understand the appropriateness of its use and assess for changes in antiplatelet management practices. METHODS AND RESULTS: Using ACTION Registry-GWTG (Get-with-the-Guidelines), we evaluated patterns of P2Y12 antagonist use within 24 hours of admission in 100 228 ST elevation myocardial infarction (STEMI) and 158 492 Non-ST elevation myocardial infarction (NSTEMI) patients at 548 hospitals between October 2009 and September 2012. Rates of early P2Y12 antagonist use were approximately 90% among STEMI and 57% among NSTEMI patients. From 2009 to 2012, prasugrel use increased significantly from 3% to 18% (5% to 30% in STEMI; 2% to 10% in NSTEMI; P for trend <0.001 for all). During the same period, we observed a decrease in use of early but not discharge P2Y12 antagonist among NSTEMI patients. Although contraindicated, 3.0% of patients with prior stroke received prasugrel. Prasugrel was used in 1.9% of patients ≥75 years and 4.5% of patients with weight <60 kg. In both STEMI and NSTEMI, prasugrel was most frequently used in patients at the lowest predicted risk for bleeding and mortality. Despite lack of supporting evidence, prasugrel was initiated before cardiac catheterization in 18% of NSTEMI patients. CONCLUSIONS: With prasugrel as an antiplatelet treatment option, contemporary practice shows low uptake of prasugrel and delays in P2Y12 antagonist initiation among NSTEMI patients. We also note concerning evidence of inappropriate use of prasugrel, and inadequate targeting of this more potent therapy to maximize the benefit/risk ratio.

Model selection for prognostic time-to-event gene signature discovery with applications in early breast cancer data

Model selection between competing models is a key consideration in the discovery of prognostic multigene signatures. The use of appropriate statistical performance measures as well as verification of biological significance of the signatures is imperative to maximise the chance of external validation of the generated signatures. Current approaches in time-to-event studies often use only a single measure of performance in model selection, such as logrank test p-values, or dichotomise the follow-up times at some phase of the study to facilitate signature discovery. In this study we improve the prognostic signature discovery process through the application of the multivariate partial Cox model combined with the concordance index, hazard ratio of predictions, independence from available clinical covariates and biological enrichment as measures of signature performance. The proposed framework was applied to discover prognostic multigene signatures from early breast cancer data. The partial Cox model combined with the multiple performance measures were used in both guiding the selection of the optimal panel of prognostic genes and prediction of risk within cross validation without dichotomising the follow-up times at any stage. The signatures were successfully externally cross validated in independent breast cancer datasets, yielding a hazard ratio of 2.55 [1.44, 4.51] for the top ranking signature.

Adjuvant bisphosphonate treatment in early breast cancer: meta-analyses of individual patient data from randomised trials

BACKGROUND: Bisphosphonates have profound effects on bone physiology, and could modify the process of metastasis. We undertook collaborative meta-analyses to clarify the risks and benefits of adjuvant bisphosphonate treatment in breast cancer.

METHODS: We sought individual patient data from all unconfounded trials in early breast cancer that randomised between bisphosphonate and control. Primary outcomes were recurrence, distant recurrence, and breast cancer mortality. Primary subgroup investigations were site of first distant recurrence (bone or other), menopausal status (postmenopausal [combining natural and artificial] or not), and bisphosphonate class (aminobisphosphonate [eg, zoledronic acid, ibandronate, pamidronate] or other [ie, clodronate]). Intention-to-treat log-rank methods yielded bisphosphonate versus control first-event rate ratios (RRs).

FINDINGS: We received data on 18 766 women (18 206 [97%] in trials of 2-5 years of bisphosphonate) with median follow-up 5·6 woman-years, 3453 first recurrences, and 2106 subsequent deaths. Overall, the reductions in recurrence (RR 0·94, 95% CI 0·87-1·01; 2p=0·08), distant recurrence (0·92, 0·85-0·99; 2p=0·03), and breast cancer mortality (0·91, 0·83-0·99; 2p=0·04) were of only borderline significance, but the reduction in bone recurrence was more definite (0·83, 0·73-0·94; 2p=0·004). Among premenopausal women, treatment had no apparent effect on any outcome, but among 11 767 postmenopausal women it produced highly significant reductions in recurrence (RR 0·86, 95% CI 0·78-0·94; 2p=0·002), distant recurrence (0·82, 0·74-0·92; 2p=0·0003), bone recurrence (0·72, 0·60-0·86; 2p=0·0002), and breast cancer mortality (0·82, 0·73-0·93; 2p=0·002). Even for bone recurrence, however, the heterogeneity of benefit was barely significant by menopausal status (2p=0·06 for trend with menopausal status) or age (2p=0·03), and it was non-significant by bisphosphonate class, treatment schedule, oestrogen receptor status, nodes, tumour grade, or concomitant chemotherapy. No differences were seen in non-breast cancer mortality. Bone fractures were reduced (RR 0·85, 95% CI 0·75-0·97; 2p=0·02).

INTERPRETATION: Adjuvant bisphosphonates reduce the rate of breast cancer recurrence in the bone and improve breast cancer survival, but there is definite benefit only in women who were postmenopausal when treatment began.

FUNDING: Cancer Research UK, Medical Research Council.