The use of mixture density networks in the emulation of complex epidemiological individual-based models

Complex, highly-computational, individual-based models are abundant in epidemiology. For epidemics such as macro-parasitic diseases, detailed modelling of human behaviour and pathogen life-cycle are required in order to produce accurate results. This can often lead to models that are computationally-expensive to analyse and perform model fitting, and often require many simulation runs in order to build up sufficient statistics. Emulation can provide a more computationally-efficient output of the individual-based model, by approximating it using a statistical model. Previous work has used Gaussian processes (GPs) in order to achieve this, but these can not deal with multi-modal, heavy-tailed, or discrete distributions. Here, we introduce the concept of a mixture density network (MDN) in its application in the emulation of epidemiological models. MDNs incorporate both a mixture model and a neural network to provide a flexible tool for emulating a variety of models and outputs. We develop an MDN emulation methodology and demonstrate its use on a number of simple models incorporating both normal, gamma and beta distribution outputs. We then explore its use on the stochastic SIR model to predict the final size distribution and infection dynamics. MDNs have the potential to faithfully reproduce multiple outputs of an individual-based model and allow for rapid analysis from a range of users. As such, an open-access library of the method has been released alongside this manuscript

Crustal seismic velocity responds to a magmatic intrusion and seasonal loading in Iceland's Northern Volcanic Zone.

Seismic noise interferometry is an exciting technique for studying volcanoes, providing a continuous measurement of seismic velocity changes (dv/v), which are sensitive to magmatic processes that affect the surrounding crust. However, understanding the exact mechanisms causing changes in dv/v is often difficult. We present dv/v measurements over 10 years in central Iceland, measured using single-station cross-component correlation functions from 51 instruments across a range of frequency bands. We observe a linear correlation between changes in dv/v and volumetric strain at stations in regions of both compression and dilatation associated with the 2014 Bárðarbunga-Holuhraun dike intrusion. Furthermore, a clear seasonal cycle in dv/v is modeled as resulting from elastic and poroelastic responses to changing snow thickness, atmospheric pressure, and groundwater level. This study comprehensively explains variations in dv/v arising from diverse crustal stresses and highlights the importance of deformation modeling when interpreting dv/v, with implications for volcano and environmental monitoring worldwide

Random Field and Random Anisotropy Effects in Defect-Free Three-Dimensional XY Models

Monte Carlo simulations have been used to study a vortex-free XY ferromagnet with a random field or a random anisotropy on simple cubic lattices. In the random field case, which can be related to a charge-density wave pinned by random point defects, it is found that long-range order is destroyed even for weak randomness. In the random anisotropy case, which can be related to a randomly pinned spin-density wave, the long-range order is not destroyed and the correlation length is finite. In both cases there are many local minima of the free energy separated by high entropy barriers. Our results for the random field case are consistent with the existence of a Bragg glass phase of the type discussed by Emig, Bogner and Nattermann.Comment: 10 pages, including 2 figures, extensively revise

Long-period seismicity reveals magma pathways above a laterally propagating dyke during the 2014–15 Bárðarbunga rifting event, Iceland

The 2014-15 Bárðarbunga-Holuhraun rifting event comprised the best-monitored dyke intrusion to date and the largest eruption in Iceland in 230 years. A huge variety of seismicity was produced, including over 30,000 volcano-tectonic earthquakes (VTs) associated with the dyke propagation at ∼ 6 km depth below sea level, and large-magnitude earthquakes accompanying the collapse of Bárðarbunga caldera. We here study the long-period seismicity associated with the rifting event. We systematically detect and locate both long-period events (LPs) and tremor during the dyke propagation phase and the first week of the eruption. We identify clusters of highly similar, repetitive LPs, which have a peak frequency of ∼ 1 Hz and clear P and S phases followed by a long-duration coda. The source mechanisms are remarkably consistent between clusters and also fundamentally different to those of the VTs. We accurately locate LP clusters near each of three ice cauldrons (depressions formed by basal melting) that were observed on the surface of Dyngjujökull glacier above the path of the dyke. Most events are in the vicinity of the northernmost cauldron, at shallower depth than the VTs associated with lateral dyke propagation. At the two northerly cauldrons, periods of shallow seismic tremor following the clusters of LPs are also observed. Given that the LPs occur at ∼ 4 km depth and in swarms during times of dyke-stalling, we infer that they result from excitation of magmatic fluid-filled cavities and indicate magma ascent. We suggest that the tremor is the climax of the vertical melt movement, arising from either rapid, repeated excitation of the same LP cavities, or sub-glacial eruption processes. This long-period seismicity therefore represents magma pathways between the depth of the dyke-VT earthquakes and the surface. Notably, we do not detect tremor associated with each cauldron, despite melt reaching the base of the overlying ice cap, a concern for hazard forecasting

Predictability in a highly stochastic system: final size of measles epidemics in small populations.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files. This article is open access.A standard assumption in the modelling of epidemic dynamics is that the population of interest is well mixed, and that no clusters of metapopulations exist. The well-known and oft-used SIR model, arguably the most important compartmental model in theoretical epidemiology, assumes that the disease being modelled is strongly immunizing, directly transmitted and has a well-defined period of infection, in addition to these population mixing assumptions. Childhood infections, such as measles, are prime examples of diseases that fit the SIR-like mechanism. These infections have been well studied for many systems with large, well-mixed populations with endemic infection. Here, we consider a setting where populations are small and isolated. The dynamics of infection are driven by stochastic extinction-recolonization events, producing large, sudden and short-lived epidemics before rapidly dying out from a lack of susceptible hosts. Using a TSIR model, we fit prevaccination measles incidence and demographic data in Bornholm, the Faroe Islands and four districts of Iceland, between 1901 and 1965. The datasets for each of these countries suffer from different levels of data heterogeneity and sparsity. We explore the potential for prediction of this model: given historical incidence data and up-to-date demographic information, and knowing that a new epidemic has just begun, can we predict how large it will be? We show that, despite a lack of significant seasonality in the incidence of measles cases, and potentially severe heterogeneity at the population level, we are able to estimate the size of upcoming epidemics, conditioned on the first time step, to within reasonable confidence. Our results have potential implications for possible control measures for the early stages of new epidemics in small populations.US Department of Homeland Security HSHQDC-12-C-00058 Eunice Kennedy Shriver National Institute of Child Health and Human Development 5R24HD047879 National Institutes of Health 5T32HD007163 Bill and Melinda Gates Foundation RAPIDD program of the Science and Technology Directorate, Department of Homeland Security Fogarty International Center, National Institutes of Healt

Fermi Surface as the Driving Mechanism for Helical Antiferromagnetic Ordering in Gd-Y Alloys

The first direct experimental evidence for the Fermi surface (FS) driving the helical antiferromagnetic ordering in a gadolinium-yttrium alloy is reported. The presence of a FS sheet capable of nesting is revealed, and the nesting vector associated with the sheet is found to be in excellent agreement with the periodicity of the helical ordering.Comment: 4 pages, 4 figure

Promotion of access to essential medicines for Non-Communicable Diseases: Practical implications of the UN Political Declaration

Access to medicines and vaccines to prevent and treat non-communicable diseases (NCDs) is unacceptably low worldwide. In the 2011 UN political declaration on the prevention and control of NCDs, heads of government made several commitments related to access to essential medicines, technologies, and vaccines for such diseases. 30 years of experience with policies for essential medicines and 10 years of scaling up of HIV treatment have provided the knowledge needed to address barriers to long-term effective treatment and prevention of NCDs. More medicines can be acquired within existing budgets with efficient selection, procurement, and use of generic medicines. Furthermore, low-income and middle-income countries need to increase mobilisation of domestic resources to cater for the many patients with NCDs who do not have access to treatment. Existing initiatives for HIV treatment offer useful lessons that can enhance access to pharmaceutical management of NCDs and improve adherence to long-term treatment of chronic illness; policy makers should also address unacceptable inequities in access to controlled opioid analgesics. In addition to off-patent medicines, governments can promote access to new and future on-patent medicinal products through coherent and equitable health and trade policies, particularly those for intellectual property. Frequent conflicts of interest need to be identified and managed, and indicators and targets for access to NCD medicines should be used to monitor progress. Only with these approaches can a difference be made to the lives of hundreds of millions of current and future patients with NCDs

Modeling oscillatory Microtubule--Polymerization

Polymerization of microtubules is ubiquitous in biological cells and under certain conditions it becomes oscillatory in time. Here simple reaction models are analyzed that capture such oscillations as well as the length distribution of microtubules. We assume reaction conditions that are stationary over many oscillation periods, and it is a Hopf bifurcation that leads to a persistent oscillatory microtubule polymerization in these models. Analytical expressions are derived for the threshold of the bifurcation and the oscillation frequency in terms of reaction rates as well as typical trends of their parameter dependence are presented. Both, a catastrophe rate that depends on the density of {\it guanosine triphosphate} (GTP) liganded tubulin dimers and a delay reaction, such as the depolymerization of shrinking microtubules or the decay of oligomers, support oscillations. For a tubulin dimer concentration below the threshold oscillatory microtubule polymerization occurs transiently on the route to a stationary state, as shown by numerical solutions of the model equations. Close to threshold a so--called amplitude equation is derived and it is shown that the bifurcation to microtubule oscillations is supercritical.Comment: 21 pages and 12 figure

Measurement of double-differential cross sections for top quark pair production in pp collisions at [Formula: see text][Formula: see text] and impact on parton distribution functions.

Normalized double-differential cross sections for top quark pair ([Formula: see text]) production are measured in pp collisions at a centre-of-mass energy of 8[Formula: see text] with the CMS experiment at the LHC. The analyzed data correspond to an integrated luminosity of 19.7[Formula: see text]. The measurement is performed in the dilepton [Formula: see text] final state. The [Formula: see text] cross section is determined as a function of various pairs of observables characterizing the kinematics of the top quark and [Formula: see text] system. The data are compared to calculations using perturbative quantum chromodynamics at next-to-leading and approximate next-to-next-to-leading orders. They are also compared to predictions of Monte Carlo event generators that complement fixed-order computations with parton showers, hadronization, and multiple-parton interactions. Overall agreement is observed with the predictions, which is improved when the latest global sets of proton parton distribution functions are used. The inclusion of the measured [Formula: see text] cross sections in a fit of parametrized parton distribution functions is shown to have significant impact on the gluon distribution