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建立模型以评估长期使用经杀虫剂处理过的蚊帐对疟蚊叮咬时间的影响。

Modelling the impact of the long-term use of insecticide-treated bed nets on Anopheles mosquito biting time.

机构信息

Departamento de Bioestatística, IBB, UNESP, Botucatu, SP, 18618-689, Brazil.

Faculdade de Computação e Engenharia Elétrica, UNIFESSPA, Marabá, PA, 68507-590, Brazil.

出版信息

Malar J. 2017 Sep 15;16(1):373. doi: 10.1186/s12936-017-2014-6.

DOI:10.1186/s12936-017-2014-6
PMID:28915892
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5602891/
Abstract

BACKGROUND

Evidence of changing in biting and resting behaviour of the main malaria vectors has been mounting up in recent years as a result of selective pressure by the widespread and long-term use of insecticide-treated bed nets (ITNs), and indoor residual spraying. The impact of resistance behaviour on malaria intervention efficacy has important implications for the epidemiology and malaria control programmes. In this context, a theoretical framework is presented to understand the mechanisms determining the evolution of feeding behaviour under the pressure of use of ITNs.

METHODS

An agent-based stochastic model simulates the impact of insecticide-treated bed nets on mosquito fitness by reducing the biting rates, as well as increasing mortality rates. The model also incorporates a heritability function that provides the necessary genetic plasticity upon which natural selection would act to maximize the fitness under the pressure of the control strategy.

RESULTS

The asymptotic equilibrium distribution of mosquito population versus biting time is shown for several daily uses of ITNs, and the expected disruptive selection on this mosquito trait is observed in the simulations. The relative fitness of strains that bite at much earlier time with respect to the wild strains, when a threshold of about 50% of ITNs coverage highlights the hypothesis of a behaviour selection. A sensitivity analysis has shown that the top three parameters that play a dominant role on the mosquito fitness are the proportion of individuals using bed nets and its effectiveness, the impact of bed nets on mosquito oviposition, and the mosquito genetic plasticity related to changing in biting time.

CONCLUSION

By taking the evolutionary aspect into account, the model was able to show that the long-term use of ITNs, although representing an undisputed success in reducing malaria incidence and mortality in many affected areas, is not free of undesirable side effects. From the evolutionary point of view of the parasite virulence, it should be expected that plasmodium parasites would be under pressure to reduce their virulence. This speculative hypothesis can eventually be demonstrated in the medium to long-term use of ITNs.

摘要

背景

由于广泛和长期使用经杀虫剂处理的蚊帐(ITN)和室内滞留喷洒,主要疟疾媒介的叮咬和休息行为发生变化的证据近年来不断增加。抗药性行为对疟疾干预效果的影响对流行病学和疟疾控制规划具有重要意义。在这种情况下,提出了一个理论框架来理解在使用 ITN 的压力下决定摄食行为演变的机制。

方法

基于主体的随机模型通过降低叮咬率以及增加死亡率来模拟杀虫剂处理的蚊帐对蚊子适应性的影响。该模型还包含一个遗传率函数,为自然选择提供了必要的遗传可塑性,以在控制策略的压力下最大限度地提高适应性。

结果

展示了几种 ITN 每日使用情况下蚊子种群与叮咬时间的渐近平衡分布,并在模拟中观察到了对这种蚊子特征的预期破坏性选择。当 ITN 覆盖率达到约 50%左右时,与野生株相比,叮咬时间更早的菌株的相对适应性更高,这突显了行为选择的假说。敏感性分析表明,对蚊子适应性起主要作用的前三个参数是使用蚊帐的个体比例及其有效性、蚊帐对蚊子产卵的影响以及与叮咬时间变化相关的蚊子遗传可塑性。

结论

通过考虑进化方面,该模型能够表明,尽管长期使用 ITN 代表了在减少许多受影响地区疟疾发病率和死亡率方面无可争议的成功,但它并非没有不良副作用。从寄生虫毒力的进化角度来看,疟原虫寄生虫应该会受到降低其毒力的压力。这种推测性假说最终可以在 ITN 的中长期使用中得到证明。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8b3/5602891/eedc9d9a3b98/12936_2017_2014_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8b3/5602891/e052b40538f4/12936_2017_2014_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8b3/5602891/e6c979d6bff2/12936_2017_2014_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8b3/5602891/83482d3a5035/12936_2017_2014_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8b3/5602891/6834fd045ec4/12936_2017_2014_Fig6_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8b3/5602891/c384a7be601b/12936_2017_2014_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8b3/5602891/eedc9d9a3b98/12936_2017_2014_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8b3/5602891/e052b40538f4/12936_2017_2014_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8b3/5602891/e6c979d6bff2/12936_2017_2014_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8b3/5602891/83482d3a5035/12936_2017_2014_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8b3/5602891/6834fd045ec4/12936_2017_2014_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8b3/5602891/3f7efe9a09cb/12936_2017_2014_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8b3/5602891/c384a7be601b/12936_2017_2014_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8b3/5602891/eedc9d9a3b98/12936_2017_2014_Fig9_HTML.jpg

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