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

Spatio-temporal dynamics of gambiense human African trypanosomiasis infection

Gambiense human African trypanosomiasis (gHAT) is a disease targeted for elimination by the World Health Organization. In this thesis, I develop a stochastic mathematical model for gHAT infection dynamics that can explore the infection on the level of individual villages. This allows us to make predictions on the same scale at which the active screening interventions occur. Since regional elimination is dependent on the local elimination of transmission in villages, we then scale up the model to consider the interaction of villages in relation to the infection. The models show that infection is able to persist for long periods in relatively small isolated populations due to the long time scales of infection, and that not observing any cases is an indicator of local elimination, but not proof. Further analysis demonstrates that using a net monetary benefit framework, active screening has the most benefit when carried out at high coverage approximately annually. Modelling predictions also show that elimination is unlikely to be achieved in all areas with active screening at the current coverages alone. These results provide quantitative support for some current intervention strategies, while the insights given also highlight some potential difficulties for achieving and measuring a 2030 elimination goal

Village-scale persistence and elimination of gambiense human African trypanosomiasis

Gambiense human African trypanosomiasis (gHAT) is one of several neglected tropical diseases that is targeted for elimination by the World Health Organization. Recent years have seen a substantial decline in the number of globally reported cases, largely driven by an intensive process of screening and treatment. However, this infection is highly focal, continuing to persist at low prevalence even in small populations. Regional elimination, and ultimately global eradication, rests on understanding the dynamics and persistence of this infection at the local population scale. Here we develop a stochastic model of gHAT dynamics, which is underpinned by screening and reporting data from one of the highest gHAT incidence regions, Kwilu Province, in the Democratic Republic of Congo. We use this model to explore the persistence of gHAT in villages of different population sizes and subject to different patterns of screening. Our models demonstrate that infection is expected to persist for long periods even in relatively small isolated populations. We further use the model to assess the risk of recrudescence following local elimination and consider how failing to detect cases during active screening events informs the probability of elimination. These quantitative results provide insights for public health policy in the region, particularly highlighting the difficulties in achieving and measuring the 2030 elimination goal

Electromagnetic wave scattering experiments in Hall thruster plasma plumes

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76740/1/AIAA-1998-3642-699.pd

Development of an Annular Helicon Source for Electric Propulsion Applications

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76441/1/AIAA-2006-4841-172.pd

Magnetic light

In this paper we report on the observation of novel and highly unusual magnetic state of light. It appears that in small holes light quanta behave as small magnets so that light propagation through such holes may be affected by magnetic field. When arrays of such holes are made, magnetic light of the individual holes forms novel and highly unusual two-dimensional magnetic light material. Magnetic light may soon become a great new tool for quantum communication and computing.Comment: Submitted to Phys.Rev.Lett., 3 figure

The DEEP2 Galaxy Redshift Survey: Mean Ages and Metallicities of Red Field Galaxies at z ~ 0.9 from Stacked Keck/DEIMOS Spectra

As part of the DEEP2 galaxy redshift survey, we analyze absorption line strengths in stacked Keck/DEIMOS spectra of red field galaxies with weak to no emission lines, at redshifts 0.7 <= z <= 1. Comparison with models of stellar population synthesis shows that red galaxies at z ~ 0.9 have mean luminosity-weighted ages of the order of only 1 Gyr and at least solar metallicities. This result cannot be reconciled with a scenario where all stars evolved passively after forming at very high z. Rather, a significant fraction of stars can be no more than 1 Gyr old, which means that star formation continued to at least z ~ 1.2. Furthermore, a comparison of these distant galaxies with a local SDSS sample, using stellar populations synthesis models, shows that the drop in the equivalent width of Hdelta from z ~ 0.9 to 0.1 is less than predicted by passively evolving models. This admits of two interpretations: either each individual galaxy experiences continuing low-level star formation, or the red-sequence galaxy population from z ~ 0.9 to 0.1 is continually being added to by new galaxies with younger stars.Comment: A few typos were corrected and numbers in Table 1 were revise

Review of Major Crop and Animal Arthropod Pests of South Texas

The Lower Rio Grande Valley is an area in Texas that consists of the four southern-most counties. This area contains a diverse range of agriculture and land-use including vegetable, row-crop and livestock production. The year-around cool to hot subtropical climate means that green vegetation is continually present, including many crops. Geographically, it shares an international border, making it a region vulnerable to new invasive species and the re-introduction of pests that have been previously eliminated in the United States. These combined factors lead to an array of arthropod pests that may have serious impacts on the crops, animals, and people in the region. This review focuses on arthropod pests that have historically, currently, or have the potential to significantly impact vegetables, row-crops, livestock, and humans in the LRGV. This is not an all-inclusive re-view but aims to focus on many of the arthropods that have been significant in the last 20 years