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Gene drives for schistosomiasis transmission control.

机译:基因驱动器用于血吸虫病传播控制。

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摘要

Schistosomiasis is one of the most important and widespread neglected tropical diseases (NTD), with over 200 million people infected in more than 70 countries; the disease has nearly 800 million people at risk in endemic areas. Although mass drug administration is a cost-effective approach to reduce occurrence, extent, and severity of the disease, it does not provide protection to subsequent reinfection. Interventions that target the parasites' intermediate snail hosts are a crucial part of the integrated strategy required to move toward disease elimination. The recent revolution in gene drive technology naturally leads to questions about whether gene drives could be used to efficiently spread schistosome resistance traits in a population of snails and whether gene drives have the potential to contribute to reduced disease transmission in the long run. Responsible implementation of gene drives will require solutions to complex challenges spanning multiple disciplines, from biology to policy. This Review Article presents collected perspectives from practitioners of global health, genome engineering, epidemiology, and snail/schistosome biology and outlines strategies for responsible gene drive technology development, impact measurements of gene drives for schistosomiasis control, and gene drive governance. Success in this arena is a function of many factors, including gene-editing specificity and efficiency, the level of resistance conferred by the gene drive, how fast gene drives may spread in a metapopulation over a complex landscape, ecological sustainability, social equity, and, ultimately, the reduction of infection prevalence in humans. With combined efforts from across the broad global health community, gene drives for schistosomiasis control could fortify our defenses against this devastating disease in the future.

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  • 作者单位
  • 年(卷),期 2020(),
  • 年度 2020
  • 页码
  • 总页数 21
  • 原文格式 PDF
  • 正文语种
  • 中图分类
  • 网站名称 剑桥大学机构知识库
  • 栏目名称 所有文件
  • 关键词

    Article;

  • 入库时间 2022-08-19 17:40:58
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