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Multiple linear regression model of visceral leishmaniasis in Bihar, India.

机译：印度比哈尔省内脏利什曼病的多元线性回归模型。

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摘要

Visceral Leishmaniasis (VL) is one of the world's worst parasitic killers, second only to Malaria, claiming nearly 500,000 lives each year. The disease attacks the spleen, liver, and bone marrow, and if left untreated is nearly always fatal. Whilst the disease is found all around the world, it is primarily prevalent in developing countries, in particular India. The most affected state in India is Bihar, where the disease is endemic. While other research has been conducted with emphasis on the effect of climate variables on the disease incidence rate, this analysis focuses on socio-economic variables such as literacy rate, housing structure, and working environment, to study their roles on the incidence rate. A Multiple linear regression model that includes these socio-economic factors as independent variables was initially developed and it explained 92% of the observed variance. The model was then reduced via stepwise regression and two models that explained 81% and 63% of the observed variance were used to help determine the most significant variables, such as housing and literacy rates. Modest comments are made on possible measures that could be taken to decrease the VL incidence rate, along with limitations of the model and suggestions for further research on this topic.
机译：内脏利什曼病（VL）是世界上最严重的寄生虫杀手之一，仅次于疟疾，每年夺去近50万人的生命。该病侵袭脾脏，肝脏和骨髓，如果不及时治疗几乎总是致命的。尽管该病在世界各地都有发现，但主要在发展中国家，特别是印度流行。印度受影响最严重的州是比哈尔邦，该病是地方病。尽管进行了其他研究，重点是气候变量对疾病发病率的影响，但该分析着重于社会经济变量，如识字率，住房结构和工作环境，以研究其在发病率中的作用。最初建立了包括这些社会经济因素作为独立变量的多元线性回归模型，该模型可以解释观察到的差异的92％。然后通过逐步回归简化模型，并使用两个解释了观察到的方差的81％和63％的模型来帮助确定最重要的变量，例如住房和识字率。对于可能采取的降低VL发生率的措施，以及该模型的局限性以及对该主题的进一步研究的建议，均发表了适当的评论。

著录项

  • 作者

    Sheets, Darren.;

  • 作者单位

    The University of Texas at Arlington.;

  • 授予单位 The University of Texas at Arlington.;
  • 学科 Biology Biostatistics.;Mathematics.;Biology Parasitology.
  • 学位 M.S.
  • 年度 2009
  • 页码 50 p.
  • 总页数 50
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 生物数学方法;数学;
  • 关键词

  • 入库时间 2022-08-17 11:38:31

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