Comparing large-scale computational approaches to epidemic modeling: agent-based versus structured metapopulation models.
Comparing large-scale computational approaches to epidemic modeling: agent-based versus structured metapopulation models.
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DOI：
10.1186/1471-2334-10-190
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发表时间：
2010-06-29
影响因子：
3.7
通讯作者：
Vespignani A
中科院分区：
文献类型：
--
作者：
Ajelli M;Gonçalves B;Balcan D;Colizza V;Hu H;Ramasco JJ;Merler S;Vespignani A
近年来，用于真实模拟疫情暴发的大规模计算模型被越来越频繁地使用。方法适应于感兴趣的规模，范围从非常详细的基于代理的模型到空间结构的集合种群模型。因此，一个主要问题是不同建模方法发现的时空传播模式可能在多大程度上不同，并取决于所使用的不同近似和假设。我们首次对意大利的基线大流行事件的进展进行了基于随机代理的模型和结构化的集合人口随机模型所获得的结果的并列比较，意大利是一个地理上不同的大型国家。以代理人为基础的模型是基于通过关于社会人口结构的非常详细的数据明确地表示意大利人口。集合人口模拟使用全球流行病和流动性(GLEAM)模型，基于全球高分辨率人口普查数据，并将航空旅行流量数据与全球范围内的短期人类流动模式相结合。该模型还考虑了意大利的年龄结构数据。GLEAM和基于代理的模型通过使用相同的疾病参数，并通过定义来自国际旅行的相同输入感染病例，在其初始条件下同步。得到的结果表明，两个模型提供的流行病模式在两种方法所能达到的粒度水平上非常一致，高峰时间的差异在几天左右。流行病大小的相对差异取决于基本繁殖率R0，以及集合种群模型始终比基于代理人的模型产生更大发病率的事实，这是由于两种方法的种群内接触模式的结构不同所致。年龄细分分析表明，较年轻的年龄组也有类似的攻击率。这两种建模方法之间的良好一致性对于定义数据可用性和模型提供的信息之间的权衡非常重要。我们的结果根据现有的数据和计算资源定义了基于代理的方法和元种群方法相结合的混合模型的可能性。
In recent years large-scale computational models for the realistic simulation of epidemic outbreaks have been used with increased frequency. Methodologies adapt to the scale of interest and range from very detailed agent-based models to spatially-structured metapopulation models. One major issue thus concerns to what extent the geotemporal spreading pattern found by different modeling approaches may differ and depend on the different approximations and assumptions used. We provide for the first time a side-by-side comparison of the results obtained with a stochastic agent-based model and a structured metapopulation stochastic model for the progression of a baseline pandemic event in Italy, a large and geographically heterogeneous European country. The agent-based model is based on the explicit representation of the Italian population through highly detailed data on the socio-demographic structure. The metapopulation simulations use the GLobal Epidemic and Mobility (GLEaM) model, based on high-resolution census data worldwide, and integrating airline travel flow data with short-range human mobility patterns at the global scale. The model also considers age structure data for Italy. GLEaM and the agent-based models are synchronized in their initial conditions by using the same disease parameterization, and by defining the same importation of infected cases from international travels. The results obtained show that both models provide epidemic patterns that are in very good agreement at the granularity levels accessible by both approaches, with differences in peak timing on the order of a few days. The relative difference of the epidemic size depends on the basic reproductive ratio, R0, and on the fact that the metapopulation model consistently yields a larger incidence than the agent-based model, as expected due to the differences in the structure in the intra-population contact pattern of the approaches. The age breakdown analysis shows that similar attack rates are obtained for the younger age classes. The good agreement between the two modeling approaches is very important for defining the tradeoff between data availability and the information provided by the models. The results we present define the possibility of hybrid models combining the agent-based and the metapopulation approaches according to the available data and computational resources.
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DOI：
10.1073/pnas.0906910106
发表时间：
2009-12-22
影响因子：
11.1
作者：
Balcan, Duygu;Colizza, Vittoria;Vespignani, Alessandro
通讯作者：
Vespignani, Alessandro
DOI：
10.1073/pnas.0706849105
发表时间：
2008-03-25
影响因子：
11.1
作者：
Halloran, M. Elizabeth;Ferguson, Neil M.;Cooley, Philip
通讯作者：
Cooley, Philip
影响因子：
4.3
作者：
Chao DL;Halloran ME;Obenchain VJ;Longini IM Jr
通讯作者：
Longini IM Jr
DOI：
10.1073/pnas.0308344101
发表时间：
2004-10-19
影响因子：
11.1
作者：
Hufnagel, L;Brockmann, D;Geisel, T
通讯作者：
Geisel, T
影响因子：
2
作者：
Ajelli, Marco;Merler, Stefano
通讯作者：
Merler, Stefano