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手机与疟疾:人类与寄生虫的移动建模。

Mobile phones and malaria: modeling human and parasite travel.

机构信息

Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA 02115, USA.

出版信息

Travel Med Infect Dis. 2013 Jan-Feb;11(1):15-22. doi: 10.1016/j.tmaid.2012.12.003. Epub 2013 Mar 9.

DOI:10.1016/j.tmaid.2012.12.003
PMID:23478045
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3697114/
Abstract

Human mobility plays an important role in the dissemination of malaria parasites between regions of variable transmission intensity. Asymptomatic individuals can unknowingly carry parasites to regions where mosquito vectors are available, for example, undermining control programs and contributing to transmission when they travel. Understanding how parasites are imported between regions in this way is therefore an important goal for elimination planning and the control of transmission, and would enable control programs to target the principal sources of malaria. Measuring human mobility has traditionally been difficult to do on a population scale, but the widespread adoption of mobile phones in low-income settings presents a unique opportunity to directly measure human movements that are relevant to the spread of malaria. Here, we discuss the opportunities for measuring human mobility using data from mobile phones, as well as some of the issues associated with combining mobility estimates with malaria infection risk maps to meaningfully estimate routes of parasite importation.

摘要

人类流动在疟疾寄生虫在不同传播强度地区之间的传播中起着重要作用。无症状个体可能会不知不觉地将寄生虫携带到有蚊子媒介的地区,例如,当他们旅行时,会破坏控制计划并导致传播。因此,了解寄生虫以这种方式在地区之间输入是消除规划和传播控制的一个重要目标,这将使控制计划能够针对疟疾的主要来源。传统上,很难在人口规模上测量人类流动,但在低收入环境中广泛采用移动电话为直接测量与疟疾传播相关的人类活动提供了独特的机会。在这里,我们讨论了使用来自移动电话的数据测量人类流动的机会,以及将流动估计与疟疾感染风险图结合起来以有意义地估计寄生虫输入途径相关的一些问题。

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本文引用的文献

1
Quantifying the impact of human mobility on malaria.量化人类流动对疟疾的影响。
Science. 2012 Oct 12;338(6104):267-70. doi: 10.1126/science.1223467.
2
Digital epidemiology.数字流行病学。
PLoS Comput Biol. 2012;8(7):e1002616. doi: 10.1371/journal.pcbi.1002616. Epub 2012 Jul 26.
3
Human movement data for malaria control and elimination strategic planning.人类运动数据在疟疾控制和消除战略规划中的应用。
研究方案:通过识别厄瓜多尔、秘鲁和巴西边境地区社区间网络和人类流动情况,改善亚马逊地区对疟疾的应对。
BMJ Open. 2024 Apr 15;14(4):e078911. doi: 10.1136/bmjopen-2023-078911.
4
Characterizing mobility patterns and malaria risk factors in semi-nomadic populations of Northern Kenya.肯尼亚北部半游牧人群的移动模式及疟疾风险因素特征分析
PLOS Glob Public Health. 2024 Mar 13;4(3):e0002750. doi: 10.1371/journal.pgph.0002750. eCollection 2024.
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Network Profile: Improving Response to Malaria in the Amazon through Identification of Inter-Community Networks and Human Mobility in Border Regions of Ecuador, Peru, and Brazil.网络概况:通过识别厄瓜多尔、秘鲁和巴西边境地区的社区间网络和人口流动来改善亚马逊地区对疟疾的应对能力。
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The limits of human mobility traces to predict the spread of COVID-19: A transfer entropy approach.利用人类流动轨迹极限预测新冠病毒传播:一种转移熵方法
PNAS Nexus. 2023 Sep 14;2(10):pgad302. doi: 10.1093/pnasnexus/pgad302. eCollection 2023 Oct.
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The Implementation of a GPS-Based Location-Tracking Smartphone App in South Africa to Improve Engagement in HIV Care: Randomized Controlled Trial.基于 GPS 的位置追踪智能手机应用在南非改善 HIV 护理参与度的实施:随机对照试验。
JMIR Mhealth Uhealth. 2023 May 19;11:e44945. doi: 10.2196/44945.
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Med Sci (Basel). 2022 Dec 23;11(1):3. doi: 10.3390/medsci11010003.
10
Mobile phone handover data for measuring and analysing human population mobility in Western Ethiopia: implication for malaria disease epidemiology and elimination efforts.用于测量和分析埃塞俄比亚西部人口流动的手机切换数据:对疟疾疾病流行病学和消除工作的影响
Malar J. 2022 Nov 11;21(1):323. doi: 10.1186/s12936-022-04337-w.
Malar J. 2012 Jun 18;11:205. doi: 10.1186/1475-2875-11-205.
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Force of infection is key to understanding the epidemiology of Plasmodium falciparum malaria in Papua New Guinean children.感染力度是了解巴布亚新几内亚儿童中恶性疟原虫疟疾流行病学的关键。
Proc Natl Acad Sci U S A. 2012 Jun 19;109(25):10030-5. doi: 10.1073/pnas.1200841109. Epub 2012 Jun 4.
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Mapping populations at risk: improving spatial demographic data for infectious disease modeling and metric derivation.绘制风险人群图:改进空间人口数据,以进行传染病建模和指标推导。
Popul Health Metr. 2012 May 16;10(1):8. doi: 10.1186/1478-7954-10-8.
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Heterogeneous mobile phone ownership and usage patterns in Kenya.肯尼亚的手机拥有和使用模式呈现多样化。
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Travel risk, malaria importation and malaria transmission in Zanzibar.坦桑尼亚桑给巴尔的旅行风险、输入性疟疾和疟疾传播。
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