Classification and Anomaly Detection for Astronomical Datasets

This work develops two new statistical techniques for astronomical problems: a star / galaxy separator for the UKIRT Infrared Deep Sky Survey (UKIDSS) and a novel anomaly detection method for cross-matched astronomical datasets. The star / galaxy separator is a statistical classification method which outputs class membership probabilities rather than class labels and allows the use of prior knowledge about the source populations. Deep Sloan Digital Sky Survey (SDSS) data from the multiply imaged Stripe 82 region is used to check the results from our classifier, which compares favourably with the UKIDSS pipeline classification algorithm. The anomaly detection method addresses the problem posed by objects having different sets of recorded variables in cross-matched datasets. This prevents the use of methods unable to handle missing values and makes direct comparison between objects difficult. For each source, our method computes anomaly scores in subspaces of the observed feature space and combines them to an overall anomaly score. The proposed technique is very general and can easily be used in applications other than astronomy. The properties and performance of our method are investigated using both real and simulated datasets

Multiobjective Robust Control with HIFOO 2.0

Multiobjective control design is known to be a difficult problem both in theory and practice. Our approach is to search for locally optimal solutions of a nonsmooth optimization problem that is built to incorporate minimization objectives and constraints for multiple plants. We report on the success of this approach using our public-domain Matlab toolbox HIFOO 2.0, comparing our results with benchmarks in the literature

Credible Autocoding of Convex Optimization Algorithms

The efficiency of modern optimization methods, coupled with increasing computational resources, has led to the possibility of real-time optimization algorithms acting in safety critical roles. There is a considerable body of mathematical proofs on on-line optimization programs which can be leveraged to assist in the development and verification of their implementation. In this paper, we demonstrate how theoretical proofs of real-time optimization algorithms can be used to describe functional properties at the level of the code, thereby making it accessible for the formal methods community. The running example used in this paper is a generic semi-definite programming (SDP) solver. Semi-definite programs can encode a wide variety of optimization problems and can be solved in polynomial time at a given accuracy. We describe a top-to-down approach that transforms a high-level analysis of the algorithm into useful code annotations. We formulate some general remarks about how such a task can be incorporated into a convex programming autocoder. We then take a first step towards the automatic verification of the optimization program by identifying key issues to be adressed in future work

Relaxation of the parameter independence assumption in the bootComb R package

Background The bootComb R package allows researchers to derive confidence intervals with correct target coverage for arbitrary combinations of arbitrary numbers of independently estimated parameters. Previous versions (< 1.1.0) of bootComb used independent bootstrap sampling and required that the parameters themselves are independent - an unrealistic assumption in some real-world applications. Findings Using Gaussian copulas to define the dependence between parameters, the bootComb package has been extended to allow for dependent parameters. Implications The updated bootComb package can now handle cases of dependent parameters, with users specifying a correlation matrix defining the dependence structure. While in practice it may be difficult to know the exact dependence structure between parameters, bootComb allows running sensitivity analyses to assess the impact of parameter dependence on the resulting confidence interval for the combined parameter

bootComb—an R package to derive confidence intervals for combinations of independent parameter estimates

Motivation: To address the limits of facility- or study-based estimates, multiple independent parameter estimates may need to be combined. Specific examples include (i) adjusting an incidence rate for healthcare utilisation, (ii) deriving a disease prevalence from a conditional prevalence and the prevalence of the underlying condition, (iii) adjusting a seroprevalence for test sensitivity and specificity. Calculating combined parameter estimates is generally straightforward, but deriving corresponding confidence intervals often is not. bootComb is an R package using parametric bootstrap sampling to derive such intervals. Implementation: bootComb is a package for the statistical computation environment R. General features: Apart from a function returning confidence intervals for parameters combined from several independent estimates, bootComb provides auxiliary functions for 6 common distributions (beta, normal, exponential, gamma, Poisson and negative binomial) to derive best-fit distributions for parameters given their reported confidence intervals

Distinct climate influences on the risk of typhoid compared to invasive non-typhoid Salmonella disease in Blantyre, Malawi.

Invasive Salmonella diseases, both typhoid and invasive non-typhoidal Salmonella (iNTS), are seasonal bloodstream infections causing important morbidity and mortality globally in Africa. The reservoirs and transmission of both are not fully understood. We hypothesised that differences in the time-lagged relationships of rainfall or temperature with typhoid and iNTS incidence might infer differences in epidemiology. We assessed the dynamics of invasive Salmonella incidence over a 16-year period of surveillance, quantifying incidence peaks, seasonal variations, and nonlinear effects of rainfall and temperature exposures on the relative risks of typhoid and iNTS, using monthly lags. An increased relative risk of iNTS incidence was short-lasting but immediate after the onset of the rains, whereas that of typhoid was long-lasting but with a two months delayed start, implying a possible difference in transmission. The relative-risk function of temperature for typhoid was bimodal, with higher risk at both lower (with a 1 month lag) and higher (with a ≥4 months lag) temperatures, possibly reflecting the known patterns of short and long cycle typhoid transmission. In contrast, the relative-risk of iNTS was only increased at lower temperatures, suggesting distinct transmission mechanisms. Environmental and sanitation control strategies may be different for iNTS compared to typhoid disease

Performances d'algorithmes de focalisation en traitement SAR spatial très haute résolution

- Les futures applications de l'imagerie radar spatiale nécessitent des résolutions métriques voire sub-métriques que l'on qualifie dans cet article de Très Haute Résolution (THR). La THR implique un pré-traitement SAR spatial et un instrument différents de ceux développés à ce jour et certaines hypothèses simplificatrices, découlant souvent du domaine aéroporté, sont remises en question. Cet article a pour but de décrire un ensemble de traitements spécifiques à une chaîne de traitement SAR spatial très haute résolution et d'illustrer les performances et robustesse d'une telle chaîne

Study protocol for a single-centre observational study of household wellbeing and poverty status following a diagnosis of advanced cancer in Blantyre, Malawi - ‘Safeguarding the Family’ study

Background: Many households in low-and-middle income countries face the additional burden of crippling out-of-pocket expenditure when faced with a diagnosis of life-limiting illness. Available evidence suggests that receipt of palliative care supports cost-savings for cancer-affected households. This study will explore the relationship between receipt of palliative care, total household out-of-pocket expenditure on health and wellbeing following a first-time diagnosis of advanced cancer at Queen Elizabeth Central Hospital in Blantyre, Malawi. Protocol: Patients and their primary family caregivers will be recruited at the time of cancer diagnosis. Data on healthcare utilisation, related costs, coping strategies and wellbeing will be gathered using new and existing questionnaires (the Patient-and-Carer Cancer Cost Survey, EQ-5D-3L and the Integrated Palliative Care Outcome Score). Surveys will be repeated at one, three and six months after diagnosis. In the event of the patient’s death, a brief five-item questionnaire on funeral costs will be administered to caregivers not less than two weeks following the date of death. Descriptive and Poisson regression analyses will assess the relationship between exposure to palliative care and total household expenditure from baseline to six months. A sample size of 138 households has been calculated in order to detect a medium effect (as determined by Cohen’s f2=0.15) of receipt of palliative care in a regression model for change in total household out-of-pocket expenditure as a proportion of annual household income. Ethics and dissemination: The study has received ethical approval. Results will be reported using STROBE guidelines and disseminated through scientific meetings, open access publications and a national stakeholder meeting. Conclusions: This study will provide data on expenditure for healthcare by households affected by cancer in Malawi. We also explore whether receipt of palliative care is associated with a reduction in out-of-pocket expenditure at household level

Healthcare-associated infections and antimicrobial use in surgical wards of a large urban central hospital in Blantyre, Malawi: a point prevalence survey.

Background There are limited data on healthcare-associated infections (HAI) from African countries like Malawi. Aim We undertook a point prevalence survey of HAI and antimicrobial use in the surgery department of Queen Elizabeth Central Hospital (QECH) in Malawi and ascertained the associated risk factors for HAI. Methods A cross-sectional point prevalence survey (PPS) was carried out in the surgery department of QECH. The European Centre for Disease Prevention and Control PPS protocol version 5.3 was adapted to our setting and used as a data collection tool. Findings 105 patients were included in the analysis; median age was 34 (IQR: 24-47) years and 55.2% patients were male. Point prevalence of HAI was 11.4% (n=12/105) (95% CI: 6.0%-19.1%), including four surgical site infections, four urinary tract infections, three bloodstream infections and one bone/joint infection. We identified the following risk factors for HAI; length-of-stay between 8 and 14 days (OR=14.4, 95% CI: 1.65-124.7, p=0.0143), presence of indwelling urinary catheter (OR=8.3, 95% CI: 2.24-30.70, p=0.003) and history of surgery in the past 30 days (OR=5.11, 95% CI: 1.46-17.83, p=0.011). 29/105 patients (27.6%) were prescribed antimicrobials, most commonly the 3rd-generation cephalosporin, ceftriaxone (n=15). Conclusion The prevalence rates of HAI and antimicrobial use in surgery wards at QECH are relatively high. Hospital infection prevention and control measures need to be strengthened to reduce the burden of HAI at QECH

The global prevalence of hepatitis D virus infection:systematic review and metaanalysis

Background and Aims There are uncertainties about the epidemic patterns of hepatitis delta virus (HDV) infection and its contribution to the burden of liver disease. We estimated the global prevalence of HDV infection and explored its contribution to the development of cirrhosis and hepatocellular carcinoma (HCC) among hepatitis B surface antigen (HBsAg)-positive people. Methods We searched Pubmed, EMBASE and Scopus for studies reporting on total or IgG anti-HDV among HBsAg-positive people. Anti-HDV prevalence was estimated using a binomial mixed model, weighting for study quality and population size. The population attributable fraction (PAF) of HDV to cirrhosis and HCC among HBsAg-positive people was estimated using random-effects models. Results We included 282 studies, comprising 376 population samples from 95 countries, which together tested 120,293 HBsAg-positive people for anti-HDV. The estimated anti-HDV prevalence was 4.5% (95% CI 3.6, 5.7) among all HBsAg-positive people and 16.4% (14.6, 18.6) among those attending hepatology clinics. Worldwide, 0.16% (0.11, 0.25) of the general population, totalling 12.0 (8.7, 18.7) million people, were estimated to be anti-HDV positive. Prevalence among HBsAg-positive people was highest in Mongolia, the Republic of Moldova and countries in Western and Middle Africa, and was higher in injecting drug users, haemodialysis recipients, men who have sex with men, commercial sex workers, and those with hepatitis C virus or HIV. Among HBsAg-positive people, preliminary PAF estimates of HDV were 18% (10, 26) for cirrhosis and 20% (8, 33) for HCC. Conclusions An estimated 12 million people worldwide have experienced HDV infection, with higher prevalence in certain geographic areas and populations. HDV is a significant contributor to HBV-associated liver disease. More quality data are needed to improve the precisions of burden estimates