Pastoralism and delay in diagnosis of TB in Ethiopia

<p>Abstract</p> <p>Background</p> <p>Tuberculosis (TB) is a major public health problem in the Horn of Africa with Ethiopia being the most affected where TB cases increase at the rate of 2.6% each year. One of the main contributing factors for this rise is increasing transmission due to large number of untreated patients, serving as reservoirs of the infection within the communities. Reduction of the time between onset of TB symptoms to diagnosis is therefore a prerequisite to bring the TB epidemic under control. The aim of this study was to measure duration of delay among pastoralist TB patients at TB management units in Somali Regional State (SRS) of Ethiopia.</p> <p>Methods</p> <p>A cross sectional study of 226 TB patients with pastoralist identity was conducted in SRS of Ethiopia from June to September 2007. Patients were interviewed using questionnaire based interview. Time between onset of TB symptoms and first visit to a professional health care provider (patient delay), and the time between first visits to the professional health care provider to the date of diagnosis (medical provider's delay) were analyzed. Both pulmonary and extrapulmonary TB patients were included in the study.</p> <p>Result</p> <p>A total of 226 pastoralist TB patients were included in this study; 93 (41.2%) were nomadic pastoralists and 133 (58.8%) were agro-pastoralists. Median patient delay was found to be 60 days with range of 10–1800 days (83 days for nomadic pastoralists and 57 days for agro-pastoralists). Median health care provider's delay was 6 days and median total delay was 70 days in this study. Patient delay constituted 86% of the total delay. In multivariate logistic regression analysis, nomadic pastoralism (aOR. 2.69, CI 1.47–4.91) and having low biomedical knowledge on TB (aOR. 2.02, CI 1.02–3.98) were significantly associated with prolonged patient delay. However, the only observed risk factor for very long patient delay >120 days was distance to health facility (aOR.4.23, CI 1.32–13.54). Extra-pulmonary TB was the only observed predictor for health care providers' delay (aOR. 3.39, CI 1.68–6.83).</p> <p>Conclusion</p> <p>Patient delay observed among pastoralist TB patients in SRS is one of the highest reported so far from developing countries, exceeding two years in some patients. This long patient delay appears to be associated with patient's inadequate knowledge of the disease and distance to health care facility with nomadic pastoralists being the most affected. Regional TB control programmes need to consider the exceptional circumstances of pastoralists, to maximise their access to TB services.</p

Large optical nonlinearity of nanoantennas coupled to an epsilon-near-zero material

The size and operating energy of a nonlinear optical device are fundamentally constrained by the weakness of the nonlinear optical response of common materials1. Here, we report that a 50-nm-thick optical metasurface made of optical dipole antennas coupled to an epsilon-near-zero material exhibits a broadband (∼400 nm bandwidth) and ultrafast (recovery time less than 1 ps) intensity-dependent refractive index n2 as large as −3.73 ± 0.56 cm2 GW−1. Furthermore, the metasurface exhibits a maximum optically induced refractive index change of ±2.5 over a spectral range of ∼200 nm. The inclusion of low-Q nanoantennas on an epsilon-near-zero thin film not only allows the design of a metasurface with an unprecedentedly large nonlinear optical response, but also offers the flexibility to tailor the sign of the response. Our technique removes a longstanding obstacle in nonlinear optics: the lack of materials with an ultrafast nonlinear contribution to refractive index on the order of unity. It consequently offers the possibility to design low-power nonlinear nano-optical devices with orders-of-magnitude smaller footprints.PostprintPeer reviewe

The use of census migration data to approximate human movement patterns across temporal scales

Human movement plays a key role in economies and development, the delivery of services, and the spread of infectious diseases. However, it remains poorly quantified partly because reliable data are often lacking, particularly for low-income countries. The most widely available are migration data from human population censuses, which provide valuable information on relatively long timescale relocations across countries, but do not capture the shorter-scale patterns, trips less than a year, that make up the bulk of human movement. Census-derived migration data may provide valuable proxies for shorter-term movements however, as substantial migration between regions can be indicative of well connected places exhibiting high levels of movement at finer time scales, but this has never been examined in detail. Here, an extensive mobile phone usage data set for Kenya was processed to extract movements between counties in 2009 on weekly, monthly, and annual time scales and compared to data on change in residence from the national census conducted during the same time period. We find that the relative ordering across Kenyan counties for incoming, outgoing and between-county movements shows strong correlations. Moreover, the distributions of trip durations from both sources of data are similar, and a spatial interaction model fit to the data reveals the relationships of different parameters over a range of movement time scales. Significant relationships between census migration data and fine temporal scale movement patterns exist, and results suggest that census data can be used to approximate certain features of movement patterns across multiple temporal scales, extending the utility of census-derived migration data

An overview of beach morphodynamic classification along the beaches between Ovari and Kanyakumari, Southern Tamilnadu Coast, India

Beach morphology relates the mutual adjustment between topography and fluid dynamics. The morphological makeup of beach systems is not accidental because the arrangement and association of forms occur in an organized contextual space and time. Since the classification derived by Wright and Short (1983) obtained from the analysis of the evolution in a number of Southern Tamilnadu beach sites, beach systems are comprehended in terms of three-dimensional morphodynamic models that include quantitative parameters (wave breaking height, sediment fall velocity, wave period and beach slope) and boundary conditions for definable form-processes association (e.g. presence or absence of bars as well as its type). This has lead to the classification of beaches into three main categories relating the beach state observations with the physical forcing (Short, 1999) dissipative, intermediate (from the intermediate-dissipative domain to the intermediate-reflective domain) and reflective modes. Morphodynamic classification of beach types was based on the equations of Wright & Short (1984) (Dimensionless fall velocity – Dean Parameter).Морфология берега отражает взаимное влияние топографии и динамики жидкости. При этом морфологическое строение береговых систем не является случайным, а определяется распределением и пространственно-временным взаимодействием береговых форм. Начиная с классификации, предложенной Райтом и Шортом (1983), основанной на анализе эволюции нескольких участков пляжа Южного берега Тамилнаду, пляжные системы рассматриваются в рамках трехмерных морфодинамических моделей, включающих количественные характеристики (высоту обрушения волн, скорость образования осадков, волновой период и уклон пляжа) и граничные условия для определенных взаимосвязей береговой динамики (т. е. наличие или отсутствие баров и их тип). Это привело к подразделению пляжей на три основные категории в соответствии с их поведением по отношению к внешним силам (Шорт, 1999) – рассеивающие, промежуточные (от промежуточно-рассеивающих до промежуточно-отражающих вариантов) и отражающие. Морфодинамическая классификация типов пляжей основана на уравнениях Райта и Шорта, 1984 (безразмерная скорость осадкообразования – параметр Дина).Морфологія берега відображає взаємний вплив топографії та динаміки рідини. При цьому морфологічна будова берегових систем не є випадковою, а визначається розподілом і просторово-часовою взаємодією берегових форм. Починаючи з класифікації, запропонованої Райтом та Шортом (1983), заснованої на аналізі еволюції декількох ділянок пляжу Південного берега Тамілнаду, пляжні системи розглядаються в рамках тривимірних морфодинамічних моделей, які включають кількісні характеристики (висоту обвалення хвиль, швидкість утворення опадів, хвильовий період та ухил пляжу) та граничні умови для певних взаємозв'язків берегової динаміки (тобто наявність або відсутність барів і їх тип). Це призвело до підрозділу пляжів на три основні категорії відповідно до їхньої поведінки відносно фізичних сил (Шорт, 1999) – розсіюючі, проміжні (від проміжно-розсіюючих до проміжно-відбиваючих варіантів) і відбиваючі. Морфодинамічна класифікація типів пляжів заснована на рівнянні Райта та Шорта, 1984 (безрозмірна швидкість осадоутворювання – параметр Діна)