119 research outputs found

    A Malaria Ecology Index Predicted Spatial and Temporal Variation of Malaria Burden and Efficacy of Antimalarial Interventions Based on African Serological Data.

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    Reducing the global health burden of malaria is complicated by weak reporting systems for infectious diseases and a paucity of vital statistics registration. This limits our ability to predict changes in malaria health burden intensity, target antimalarial resources where needed, and identify malaria impacts in retrospective data. We refined and deployed a temporally and spatially varying Malaria Ecology Index (MEI) incorporating climatological and ecological data to estimate malaria transmission strength and validate it against cross-sectional serology data from 39,875 children from seven sub-Saharan African countries. The MEI is strongly associated with malaria burden; a 1 standard deviation higher MEI is associated with a 50-117% increase in malaria risk and a 3-5 g/dL lower level of Hg. Results show that the relationship between malaria ecology and disease burden is attenuated with sufficient coverage of insecticide treated nets (ITNs) or indoor residual spraying (IRS). Having both ITNs and IRS reduce the added risk from adverse malaria ecology conditions by half. Readily available climate and ecology data can be used to estimate the spatial and temporal variation in malaria disease burden, providing a feasible alternative to direct surveillance. This will help target resources for malaria programs in the absence of national coverage of active case detection systems, and facilitate malaria research using retrospective health data

    Scaling Up Malaria Control in Africa: An Economic and Epidemiological Assessment

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    This paper estimates the number of people at risk of contracting malaria in Africa using GIS methods and the disease's epidemiologic characteristics. It then estimates yearly costs of covering the population at risk with the package of interventions (differing by level of malaria endemicity and differing for rural and urban populations) for malaria as recommended by the UN Millennium Project. These projected costs are calculated assuming a ramp-up of coverage to full coverage by 2008, and then projected out through 2015 to give a year-by-year cost of meeting the Millennium Development Goal for reducing the burden of malaria by 75% We conclude that the cost of comprehensive malaria control for Africa is US3.0billionperyearonaverage,oraroundUS3.0 billion per year on average, or around US4.02 per African at risk.

    Africa's Lagging Demographic Transition: Evidence from Exogenous Impacts of Malaria Ecology and Agricultural Technology

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    Much of Africa has not yet gone through a "demographic transition" to reduced mortality and fertility rates. The fact that the continent's countries remain mired in a Malthusian crisis of high mortality, high fertility, and rapid population growth (with an accompanying state of chronic extreme poverty) has been attributed to many factors ranging from the status of women, pro-natalist policies, poverty itself, and social institutions. There remains, however, a large degree of uncertainty among demographers as to the relative importance of these factors on a comparative or historical basis. Moreover, econometric estimation is complicated by endogeneity among fertility and other variables of interest. We attempt to improve estimation (particularly of the effect of the child mortality variable) by deploying exogenous variation in the ecology of malaria transmission and in agricultural productivity through the staggered introduction of Green Revolution, high-yield seed varieties. Results show that child mortality (proxied by infant mortality) is by far the most important factor among those explaining aggregate total fertility rates, followed by farm productivity. Female literacy (or schooling) and aggregate income do not seem to matter as much, comparatively.

    What Can We Learn from Nighttime Lights for Small Geographies? Measurement Errors and Heterogeneous Elasticities

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    Nighttime lights are routinely used as a proxy for economic activity when official statistics are unavailable and are increasingly applied to study the effects of shocks or policy interventions at small geographic scales. The implicit assumption is that the ability of nighttime lights to pick up changes in GDP does not depend on local characteristics of the region under investigation or the scale of aggregation. This study uses panel data on regional GDP growth from six countries, and nighttime lights from the Defense Meteorological Satellite Program (DMSP) to investigate potential nonlinearities and measurement errors in the light production function. Our results for high statistical capacity countries (the United States and Germany) show that nightlights are significantly less responsive to changes in GDP at higher baseline level of GDP, higher population densities, and for agricultural GDP. We provide evidence that these nonlinearities are too large to be caused by differences in measurement errors across regions. We find similar but noisier relationships in other high-income countries (Italy and Spain) and emerging economies (Brazil and China). We also present results for different aggregation schemes and find that the overall relationship, including the nonlinearity, is stable across regions of different shapes and sizes but becomes noisier when regions become few and large. These findings have important implications for studies using nighttime lights to evaluate the economic effects of shocks or policy interventions. On average, nighttime lights pick up changes in GDP across many different levels of aggregation, down to relatively small geographies. However, the nonlinearity we document in this paper implies that some studies may fail to detect policy-relevant effects in places where lights react little to changes in economic activity or they may mistakenly attribute this heterogeneity to the treatment effect of their independent variable of interest

    If I Hear You Correctly: Building and Evaluating Interview Chatbots with Active Listening Skills

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    Interview chatbots engage users in a text-based conversation to draw out their views and opinions. It is, however, challenging to build effective interview chatbots that can handle user free-text responses to open-ended questions and deliver engaging user experience. As the first step, we are investigating the feasibility and effectiveness of using publicly available, practical AI technologies to build effective interview chatbots. To demonstrate feasibility, we built a prototype scoped to enable interview chatbots with a subset of active listening skills - the abilities to comprehend a user's input and respond properly. To evaluate the effectiveness of our prototype, we compared the performance of interview chatbots with or without active listening skills on four common interview topics in a live evaluation with 206 users. Our work presents practical design implications for building effective interview chatbots, hybrid chatbot platforms, and empathetic chatbots beyond interview tasks.Comment: Working draft. To appear in the ACM CHI Conference on Human Factors in Computing Systems (CHI 2020

    Rescue of Dystrophic Skeletal Muscle by PGC-1α Involves a Fast to Slow Fiber Type Shift in the mdx Mouse

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    Increased utrophin expression is known to reduce pathology in dystrophin-deficient skeletal muscles. Transgenic over-expression of PGC-1α has been shown to increase levels of utrophin mRNA and improve the histology of mdx muscles. Other reports have shown that PGC-1α signaling can lead to increased oxidative capacity and a fast to slow fiber type shift. Given that it has been shown that slow fibers produce and maintain more utrophin than fast skeletal muscle fibers, we hypothesized that over-expression of PGC-1α in post-natal mdx mice would increase utrophin levels via a fiber type shift, resulting in more slow, oxidative fibers that are also more resistant to contraction-induced damage. To test this hypothesis, neonatal mdx mice were injected with recombinant adeno-associated virus (AAV) driving expression of PGC-1α. PGC-1α over-expression resulted in increased utrophin and type I myosin heavy chain expression as well as elevated mitochondrial protein expression. Muscles were shown to be more resistant to contraction-induced damage and more fatigue resistant. Sirt-1 was increased while p38 activation and NRF-1 were reduced in PGC-1α over-expressing muscle when compared to control. We also evaluated if the use a pharmacological PGC-1α pathway activator, resveratrol, could drive the same physiological changes. Resveratrol administration (100 mg/kg/day) resulted in improved fatigue resistance, but did not achieve significant increases in utrophin expression. These data suggest that the PGC-1α pathway is a potential target for therapeutic intervention in dystrophic skeletal muscle
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