The current landscape of software tools for the climate-sensitive infectious disease modelling community

Climate-sensitive infectious disease modelling is crucial for public health planning and is underpinned by a complex network of software tools. We identified only 37 tools that incorporated both climate inputs and epidemiological information to produce an output of disease risk in one package, were transparently described and validated, were named (for future searching and versioning), and were accessible (ie, the code was published during the past 10 years or was available on a repository, web platform, or other user interface). We noted disproportionate representation of developers based at North American and European institutions. Most tools (n=30 [81%]) focused on vector-borne diseases, and more than half (n=16 [53%]) of these tools focused on malaria. Few tools (n=4 [11%]) focused on food-borne, respiratory, or water-borne diseases. The under-representation of tools for estimating outbreaks of directly transmitted diseases represents a major knowledge gap. Just over half (n=20 [54%]) of the tools assessed were described as operationalised, with many freely available online.Peer Reviewed"Article signat per 12 autors/es: Sadie J Ryan, PhD * Catherine A Lippi, Talia Caplan, Avriel Diaz, Willy Dunbar, Shruti Grover, Simon Johnson, Rebecca Knowles, Prof Rachel Lowe, Bilal A Mateen, Madeleine C Thomson, Anna M Stewart-Ibarra"Postprint (published version

High-sensitivity cardiac troponin concentrations at presentation in patients with ST-segment elevation myocardial infarction

No abstract available

Identifying Metocean Drivers of Turbidity Using 18 Years of MODIS Satellite Data: Implications for Marine Ecosystems under Climate Change

Turbidity impacts the growth and productivity of marine benthic habitats due to light limitation. Daily/monthly synoptic and tidal influences often drive turbidity fluctuations, however, our understanding of what drives turbidity across seasonal/interannual timescales is often limited, thus impeding our ability to forecast climate change impacts to ecologically significant habitats. Here, we analysed long term (18-year) MODIS-aqua data to derive turbidity and the associated meteorological and oceanographic (metocean) processes in an arid tropical embayment (Exmouth Gulf in Western Australia) within the eastern Indian Ocean. We found turbidity was associated with El Niño Southern Oscillation (ENSO) cycles as well as Indian Ocean Dipole (IOD) events. Winds from the adjacent terrestrial region were also associated with turbidity and an upward trend in turbidity was evident in the body of the gulf over the 18 years. Our results identify hydrological processes that could be affected by global climate cycles undergoing change and reveal opportunities for managers to reduce impacts to ecologically important ecosystems

Factorized Q-Learning for Large-Scale Multi-Agent Systems

Deep Q-learning has achieved significant success in single-agent decision making tasks. However, it is challenging to extend Q-learning to large-scale multi-agent scenarios, due to the explosion of action space resulting from the complex dynamics between the environment and the agents. In this paper, we propose to make the computation of multi-agent Q-learning tractable by treating the Q-function (w.r.t. state and joint-action) as a high-order high-dimensional tensor and then approximate it with factorized pairwise interactions. Furthermore, we utilize a composite deep neural network architecture for computing the factorized Q-function, share the model parameters among all the agents within the same group, and estimate the agents' optimal joint actions through a coordinate descent type algorithm. All these simplifications greatly reduce the model complexity and accelerate the learning process. Extensive experiments on two different multi-agent problems demonstrate the performance gain of our proposed approach in comparison with strong baselines, particularly when there are a large number of agents.Comment: 7 pages, 5 figures, DAI 201

Long-term spatial variations in turbidity and temperature provide new insights into coral-algal states on extreme/marginal reefs

Globally, coral reefs are under threat, with many exhibiting degradation or a shift towards algal-dominated regimes following marine heat waves, and other disturbance events. Marginal coral reefs existing under naturally extreme conditions, such as turbid water reefs, may be more resilient than their clear water counterparts as well as offer some insight into how reefs could look in the future under climate change. Here, we surveyed 27 benthic habitats across an environmental stress gradient in the Exmouth Gulf region of north Western Australia immediately following a marine heatwave event. We used multidecadal remotely sensed turbidity (from an in-situ validated dataset) and temperature, to assess how these environmental drivers influence variability in benthic communities and coral morphology. Long-term turbidity and temperature variability were associated with macroalgal colonisation when exceeding a combined threshold. Coral cover was strongly negatively associated with temperature variability, and positively associated with depth, and wave power, while coral morphology diversity was positively associated with turbidity. While moderate turbidity (long-term average ~ 2 mg/L suspended matter) appeared to raise the threshold for coral bleaching and macroalgal dominance, regions with higher temperature variability (> 3.5 °C) appeared to have already reached this threshold. The region with the least turbidity and temperature variability had the highest amount of coral bleaching from a recent heatwave event and moderate levels of both these variables may confer resilience to coral reefs

Intensity Capping: a simple method to improve cross-correlation PIV results

Abstract A common source of error in particle image velocimetry (PIV) is the presence of bright spots within the images. These bright spots are characterized by grayscale intensities much greater than the mean intensity of the image and are typically generated by intense scattering from seed particles. The displacement of bright spots can dominate the cross-correlation calculation within an interrogation window, and may thereby bias the resulting velocity vector. An efficient and easy-to-implement image-enhancement procedure is described to improve PIV results when bright spots are present. The procedure, called Intensity Capping, imposes a user-specified upper limit to the grayscale intensity of the images. The displacement calculation then better represents the displacement of all particles in an interrogation window and the bias due to bright spots is reduced. Four PIV codes and a large set of experimental and simulated images were used to evaluate the performance of Intensity Capping. The results indicate that Intensity Capping can significantly increase the number of valid vectors from experimental image pairs and reduce displacement error in the analysis of simulated images. A comparison with other PIV image-enhancement techniques shows that Intensity Capping offers competitive performance, low computational cost, ease of implementation, and minimal modification to the images

Nonlinear and delayed impacts of climate on dengue risk in Barbados: A modelling study

Background: Over the last 5 years (2013–2017), the Caribbean region has faced an unprecedented crisis of co-occurring epidemics of febrile illness due to arboviruses transmitted by the Aedes sp. mosquito (dengue, chikungunya, and Zika). Since 2013, the Caribbean island of Barbados has experienced 3 dengue outbreaks, 1 chikungunya outbreak, and 1 Zika fever outbreak. Prior studies have demonstrated that climate variability influences arbovirus transmission and vector population dynamics in the region, indicating the potential to develop public health interventions using climate information. The aim of this study is to quantify the nonlinear and delayed effects of climate indicators, such as drought and extreme rainfall, on dengue risk in Barbados from 1999 to 2016. Methods and findings: Distributed lag nonlinear models (DLNMs) coupled with a hierarchal mixed-model framework were used to understand the exposure–lag–response association between dengue relative risk and key climate indicators, including the standardised precipitation index (SPI) and minimum temperature (Tmin). The model parameters were estimated in a Bayesian framework to produce probabilistic predictions of exceeding an island-specific outbreak threshold. The ability of the model to successfully detect outbreaks was assessed and compared to a baseline model, representative of standard dengue surveillance practice. Drought conditions were found to positively influence dengue relative risk at long lead times of up to 5 months, while excess rainfall increased the risk at shorter lead times between 1 and 2 months. The SPI averaged over a 6-month period (SPI-6), designed to monitor drought and extreme rainfall, better explained variations in dengue risk than monthly precipitation data measured in millimetres. Tmin was found to be a better predictor than mean and maximum temperature. Furthermore, including bidimensional exposure–lag–response functions of these indicators—rather than linear effects for individual lags—more appropriately described the climate–disease associations than traditional modelling approaches. In prediction mode, the model was successfully able to distinguish outbreaks from nonoutbreaks for most years, with an overall proportion of correct predictions (hits and correct rejections) of 86% (81%:91%) compared with 64% (58%:71%) for the baseline model. The ability of the model to predict dengue outbreaks in recent years was complicated by the lack of data on the emergence of new arboviruses, including chikungunya and Zika. Conclusion: We present a modelling approach to infer the risk of dengue outbreaks given the cumulative effect of climate variations in the months leading up to an outbreak. By combining the dengue prediction model with climate indicators, which are routinely monitored and forecasted by the Regional Climate Centre (RCC) at the Caribbean Institute for Meteorology and Hydrology (CIMH), probabilistic dengue outlooks could be included in the Caribbean Health-Climatic Bulletin, issued on a quarterly basis to provide climate-smart decision-making guidance for Caribbean health practitioners. This flexible modelling approach could be extended to model the risk of dengue and other arboviruses in the Caribbean region

Duplication of amyloid precursor protein (APP), but not prion protein (PRNP) gene is a significant cause of early onset dementia in a large UK series.

Amyloid precursor protein gene (APP) duplications have been identified in screens of selected probands with early onset familial Alzheimer's disease (FAD). A causal role for copy number variation (CNV) in the prion protein gene (PRNP) in prion dementias is not known. We aimed to determine the prevalence of copy number variation in APP and PRNP in a large referral series, test a screening method for detection of the same, and expand knowledge of clinical phenotype. We used a 3-tiered screening assay for APP and PRNP duplication (exonic real-time quantitative polymerase chain reaction [exon-qPCR], fluorescent microsatellite quantitative PCR [fm-q-PCR], and Illumina array [Illumina Inc., San Diego, CA, USA]) for analysis of a heterogeneous referral series comprising 1531 probands. Five of 1531 probands screened showed APP duplication, a similar prevalence to APP missense mutation. Real-time quantitative PCR and fluorescent microsatellite quantitative PCR were similar individually but are theoretically complementary; we used Illumina arrays as our reference assay. Two of 5 probands were from an autosomal dominant early onset Alzheimer's disease (familial Alzheimer's disease) pedigree. One extensive, noncontiguous duplication on chromosome 21 was consistent with an unbalanced translocation not including the Down's syndrome critical region. Seizures were prominent in the other typical APP duplications. A range of imaging, neuropsychological, cerebrospinal fluid, and pathological findings are reported that extend the known phenotype. APP but not PRNP duplication is a significant cause of early onset dementia in the UK. The recognized phenotype may be expanded to include the possibility of early seizures and apparently sporadic disease which, in part, may be due to different mutational mechanisms. The pros and cons of our screening method are discussed

Aspiration therapy for the treatment of obesity: 4-year results of a multicenter randomized controlled trial.

BackgroundThe AspireAssist is the first Food and Drug Administration-approved endoluminal device indicated for treatment of class II and III obesity.ObjectivesWe earlier reported 1-year results of the PATHWAY study. Here, we report 4-year outcomes.SettingUnited States-based, 10-center, randomized controlled trial involving 171 participants with the treatment arm receiving Aspiration Therapy (AT) plus Lifestyle Therapy and the control arm receiving Lifestyle Therapy (2:1 randomization).MethodsAT participants were permitted to continue in the study for an additional year up to a maximum of 5 years providing they maintained at least 10% total weight loss (TWL) from baseline at each year end. For AT participants who continued the study, 5 medical monitoring visits were provided at weeks 60, 68, 76, 90, and 104 and thereafter once every 13 weeks up to week 260. Exclusion criteria were a history of eating disorder or evidence of eating disorder on a validated questionnaire. Follow-up weight, quality of life, and co-morbidities were compared with the baseline levels. In addition, rates of serious adverse event, persistent fistula, withdrawal, and A-tube replacement were reported. All analyses were performed using a per-protocol analysis.ResultsOf the 82 AT participants who completed 1 year, 58 continued to this phase of the trial. Mean baseline body mass index of these 58 patients was 41.6 ± 4.5 kg/m2. At the end of first year (at the beginning of the follow-up study), these 58 patients had a body mass index of 34.1 ± 5.4 kg/m2 and had achieved an 18.3 ± 8.0% TWL. On a per protocol basis, patients experienced 14.2%, 15.3%, 16.6%, and 18.7% TWL at 1, 2, 3, and 4 years, respectively (P < .01 for all). Forty of 58 patients (69%) achieved at least 10% TWL at 4 years or at time of study withdrawal. Improvements in quality of life scores and select cardiometabolic parameters were also maintained through 4 years. There were 2 serious adverse events reported in the second through fourth years, both of which resolved with removal or replacement of the A tube. Two persistent fistulas required surgical repair, representing approximately 2% of all tube removals. There were no clinically significant metabolic or electrolytes disorders observed, nor any evidence for development of any eating disorders.ConclusionsThe results of this midterm study have shown that AT is a safe, effective, and durable weight loss alternative for people with class II and III obesity and who are willing to commit to using the therapy and adhere to adjustments in eating behavior

The intertidal hydraulics of tide-dominated reef platforms

A 2 week field experiment investigated the hydrodynamics of a strongly tidally forced tropical intertidal reef platform in the Kimberley region of northwestern Australia, where the spring tidal range exceeds 8 m. At this site, the flat and wide (∼1.4 km) reef platform is located slightly above mean sea level, such that during low tide the offshore water level can fall 4 m below the platform. While the reef always remained submerged over each tidal cycle, there were dramatic asymmetries in both the water levels and velocities on the reef, i.e., the flood duration lasted only ∼2 h versus ∼10 h for the ebb. These dynamics were investigated using a one-dimensional numerical model (SWASH) to solve the nonlinear shallow water equations with rapid (sub to supercritical) flow transitions. The numerical model revealed that as water drains off the reef, a critical flow point was established near the reef edge prior to the water discharging down the steep forereef. Despite this hydraulic control, bottom friction on the reef was still found to make a far greater contribution to elevating water levels on the reef platform and keeping it submerged over each tidal cycle. Finally, a simple analytical model more broadly shows how water levels on intertidal reef platforms functionally depend on properties of reef morphology, bottom roughness, and tidal conditions, revealing a set of parameters (a reef draining time-scale and friction parameter) that can be used to quantify how the water depth will fall on a reef during ebb tide.This is the publisher’s final pdf. The article is copyrighted by American Geophysical Union and published by John Wiley & Sons, Inc.. It can be found at: http://agupubs.onlinelibrary.wiley.com/agu/jgr/journal/10.1002/%28ISSN%292169-9291