Connectivity sustains disease transmission in environments with low potential for endemicity: modelling schistosomiasis with hydrologic and social connectivities.
Connectivity sustains disease transmission in environments with low potential for endemicity: modelling schistosomiasis with hydrologic and social connectivities.
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DOI：
10.1098/rsif.2008.0265
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发表时间：
2009-06-06
期刊：
影响因子：
--
通讯作者：
Seto EY
中科院分区：
文献类型：
--
作者：
Gurarie D;Seto EY
人群之间的社会互动和身体联系会影响寄生虫的传播。这些途径在维持寄生虫病传播中的作用尚不清楚，尽管越来越现实的集合种群模型被用于研究疾病如何在连通环境中持续存在。我们使用一个数学模型的血吸虫病传播的一组分布的异质性的村庄表明，通过社会（主机运动）和环境（寄生虫幼虫运动）途径的寄生虫的运输有后果的寄生虫控制，传播和持久性。我们发现，即使个别村庄的条件似乎不支持地方性，在一组相连的村庄，传输可以持续区域。最佳传播是由不同传播途径之间的相互作用决定的，而不一定是由那些最分散的传播途径决定的（例如，分散的社会接触可能不是传播的最佳途径）。我们发现，传统的针对高感染率的村庄，不考虑村庄之间的相互联系，可能不会导致最佳控制。这些发现对有效的疾病控制具有重大意义，这需要超越考虑疾病强度的地方差异，还要考虑人口相互关联的程度。
Social interaction and physical interconnections between populations can influence the spread of parasites. The role that these pathways play in sustaining the transmission of parasitic diseases is unclear, although increasingly realistic metapopulation models are being used to study how diseases persist in connected environments. We use a mathematical model of schistosomiasis transmission for a distributed set of heterogeneous villages to show that the transport of parasites via social (host movement) and environmental (parasite larvae movement) pathways has consequences for parasite control, spread and persistence. We find that transmission can be sustained regionally throughout a group of connected villages even when individual village conditions appear not to support endemicity. Optimum transmission is determined by an interplay between different transport pathways, and not necessarily by those that are the most dispersive (e.g. disperse social contacts may not be optimal for transmission). We show that the traditional targeting of villages with high infection, without regard to village interconnections, may not lead to optimum control. These findings have major implications for effective disease control, which needs to go beyond considering local variations in disease intensity, to also consider the degree to which populations are interconnected.
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影响因子：
120.7
作者：
Barbera, J;Macintyre, A;Layton, M
通讯作者：
Layton, M
DOI：
10.1016/s0035-9203(96)90501-5
发表时间：
1996-07-01
影响因子：
2.2
作者：
Picquet, M;Ernould, JC;Rollinson, D
通讯作者：
Rollinson, D
DOI：
10.1016/0035-9203(80)90008-5
发表时间：
1980-01-01
影响因子：
2.2
作者：
BELLA, H;MARSHALL, TFDC;VAUGHAN, JP
通讯作者：
VAUGHAN, JP
DOI：
10.1016/0035-9203(65)90152-5
发表时间：
1965-01-01
影响因子：
2.2
作者：
MACDONAL.G
通讯作者：
MACDONAL.G
影响因子：
2
作者：
Benziger, V
通讯作者：
Benziger, V