Spatiotemporal disease mapping applied to infectious diseases

被引：9
|
作者：
Coly, Sylvain [1 ,2 ]
Charras-Garrido, Myriam [1 ]
Abrial, David [1 ]
Yao-Lafourcade, Anne-Francoise [2 ]
机构：
[1] Ctr INRA Clermont Ferrand, Theix Unite Epidemiol Anim, Route Theix, F-63122 St Genes Champanelle, France
[2] Univ Blaise Pascal, Lab Math, UMR 6620, F-63171 Aubiere, France
来源：
SPATIAL STATISTICS CONFERENCE 2015, PART 1 | 2015年 / 26卷
关键词：
Bayesian Inference; Disease Mapping; Epidemiology; Infectious Disease; Spatiotemporal; TIME; MODELS; AREA; RISK;
D O I：
10.1016/j.proenv.2015.05.019
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
Disease mapping aims to determine the underlying disease risk scattered from health data. This methodology enables to represent this disease risk by a gradation of colours on a map. Our aim is to apply disease mapping to infectious diseases, when a primary case can result in secondary cases, by direct or vector transmission. Contagion can lead to overdispersion and strengthen spatial and temporal structures. This study highlighted the relevance of using the negative binomial distribution to model such data. It also showed the need to take into account both spatial and temporal dimensions in this type of epidemiological study. (C) 2015 The Authors. Published by Elsevier B.V
引用
收藏
页码：32 / 37
页数：6
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