Cross-sectional study of the burden of vector-borne and soil-transmitted polyparasitism in rural communities of Coast Province, Kenya.

BACKGROUND: In coastal Kenya, infection of human populations by a variety of parasites often results in co-infection or poly-parasitism. These parasitic infections, separately and in conjunction, are a major cause of chronic clinical and sub-clinical human disease and exert a long-term toll on economic welfare of affected populations. Risk factors for these infections are often shared and overlap in space, resulting in interrelated patterns of transmission that need to be considered at different spatial scales. Integration of novel quantitative tools and qualitative approaches is needed to analyze transmission dynamics and design effective interventions. METHODOLOGY: Our study was focused on detecting spatial and demographic patterns of single- and co-infection in six villages in coastal Kenya. Individual and household level data were acquired using cross-sectional, socio-economic, and entomological surveys. Generalized additive models (GAMs and GAMMs) were applied to determine risk factors for infection and co-infections. Spatial analysis techniques were used to detect local clusters of single and multiple infections. PRINCIPAL FINDINGS: Of the 5,713 tested individuals, more than 50% were infected with at least one parasite and nearly 20% showed co-infections. Infections with Schistosoma haematobium (26.0%) and hookworm (21.4%) were most common, as was co-infection by both (6.3%). Single and co-infections shared similar environmental and socio-demographic risk factors. The prevalence of single and multiple infections was heterogeneous among and within communities. Clusters of single and co-infections were detected in each village, often spatially overlapped, and were associated with lower SES and household crowding. CONCLUSION: Parasitic infections and co-infections are widespread in coastal Kenya, and their distributions are heterogeneous across landscapes, but inter-related. We highlighted how shared risk factors are associated with high prevalence of single infections and can result in spatial clustering of co-infections. Spatial heterogeneity and synergistic risk factors for polyparasitism need to be considered when designing surveillance and intervention strategies

Risk factors for mortality from imported falciparum malaria in the United Kingdom over 20 years: an observational study

Objectives To determine which travellers with malaria are at greatest risk of dying, highlighting factors which can be used to target health messages to travellers. Design Observational study based on 20 years of UK national data. Setting National register of malaria cases. Participants 25 054 patients notified with Plasmodium falciparum malaria, of whom 184 died, between 1987 and 2006. Main outcome measures Comparison between those with falciparum malaria who died and non-fatal cases, including age, reason for travel, country of birth, time of year diagnosed, malaria prophylaxis used. Results Mortality increased steadily with age, with a case fatality of 25/548 (4.6%) in people aged >65 years, adjusted odds ratio 10.68 (95% confidence interval 6.4 to 17.8), P<0.001 compared with 18–35 year olds. There were no deaths in the ≤5 year age group. Case fatality was 3.0% (81/2740 cases) in tourists compared with 0.32% (26/8077) in travellers visiting friends and relatives (adjusted odds ratio 8.2 (5.1 to 13.3), P<0.001). Those born in African countries with endemic malaria had a case fatality of 0.4% (36/8937) compared with 2.4% (142/5849) in others (adjusted odds ratio 4.6 (3.1 to 9.9), P<0.001). Case fatality was particularly high from the Gambia. There was an inverse correlation in mortality between region of presentation and number of cases seen in the region (R2=0.72, P<0.001). Most delay in fatal cases was in seeking care. Conclusions Most travellers acquiring malaria are of African heritage visiting friends and relatives. In contrast the risks of dying from malaria once acquired are highest in the elderly, tourists, and those presenting in areas in which malaria is seldom seen. Doctors often do not think of these as high risk groups for malaria; for this reason they are important groups to target in pre-travel advice

"Policy mandates for macro-prudential and monetary policies in a new Keynesian framework"

In the aftermath of the nancial crisis, the role of monetary policy and macro-prudential regulation in promoting nancial stability is under discussion. The old debate concerning whether monetary policy should respond to credit and asset price bubbles was revived, whereas macro-prudential regulation is being assessed as an alternative macroeconomic tool to deal with nancial imbalances. The paper explores both sides of the debate in a New Keynesian framework with nancial frictions by comparing the welfare and stabilisation impacts of distinct policy regimes. First, we investigate whether there is a welfare benet from monetary policy leaning against nancial instability. We show that monetary policy rules of this type perform better than conventional monetary rules. Second, by introducing macro-prudential regulation in the model, results from optimal policy analysis suggest also that there are welfare gains, even in the case in which monetary and macro-prudential authorities are independent and react to their own policy goal

Newly qualified physical education teachers’ experiences of developing subject knowledge prior to, during and after a Postgraduate Certificate in Education course

Office for Standards in Education (OFSTED) inspections of secondary Postgraduate Certificate in Education (PGCE) physical education courses in England between 1996 and 1998 (OFSTED, 1999) were critical of student teachers' subject knowledge. The purpose of this study was to investigate the development of subject knowledge and influences on the development of that subject knowledge in a sample of three newly qualified teachers (NQTs) who had completed a PGCE physical education course in England. The research comprised semi-structured interviews and analysis of documentation. Among these three NQTs there were some similarities, but more differences in terms of the development of subject knowledge as well as different influences on the development of subject knowledge. These results suggest that teacher educators may need to be flexible in how they approach and support the development of student teachers' subject knowledge. Results also suggest that teacher educators should work more closely with colleagues teaching sports-related undergraduate degree courses to support the development of subject knowledge for those students who wish to progress to a PGCE physical education course

On infinite-finite duality pairs of directed graphs

The (A,D) duality pairs play crucial role in the theory of general relational structures and in the Constraint Satisfaction Problem. The case where both classes are finite is fully characterized. The case when both side are infinite seems to be very complex. It is also known that no finite-infinite duality pair is possible if we make the additional restriction that both classes are antichains. In this paper (which is the first one of a series) we start the detailed study of the infinite-finite case. Here we concentrate on directed graphs. We prove some elementary properties of the infinite-finite duality pairs, including lower and upper bounds on the size of D, and show that the elements of A must be equivalent to forests if A is an antichain. Then we construct instructive examples, where the elements of A are paths or trees. Note that the existence of infinite-finite antichain dualities was not previously known

Generalization Error in Deep Learning

Deep learning models have lately shown great performance in various fields such as computer vision, speech recognition, speech translation, and natural language processing. However, alongside their state-of-the-art performance, it is still generally unclear what is the source of their generalization ability. Thus, an important question is what makes deep neural networks able to generalize well from the training set to new data. In this article, we provide an overview of the existing theory and bounds for the characterization of the generalization error of deep neural networks, combining both classical and more recent theoretical and empirical results