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时空错配数据的流行病学分析:尼日利亚高致病性禽流感病毒暴发案例。

Epidemiological analysis of spatially misaligned data: a case of highly pathogenic avian influenza virus outbreak in Nigeria.

机构信息

Department of Science and Mathematics, American University of Afghanistan, Kabul.

Department of Statistics and Population Studies, University of the Western Cape, South Africa.

出版信息

Epidemiol Infect. 2014 May;142(5):940-9. doi: 10.1017/S0950268813002136. Epub 2013 Sep 4.

Abstract

This research is focused on the epidemiological analysis of the transmission of the highly pathogenic avian influenza (HPAI) H5N1 virus outbreak in Nigeria. The data included 145 outbreaks together with the locations of the infected farms and the date of confirmation of infection. In order to investigate the environmental conditions that favoured the transmission and spread of the virus, weather stations were realigned with the locations of the infected farms. The spatial Kolmogorov-Smirnov test for complete spatial randomness rejects the null hypothesis of constant intensity (P < 0·0001). Preliminary exploratory analysis showed an increase in the incidence of H5N1 virus at farms located at high altitude. Results from the Poisson log-linear conditional intensity function identified temperature (-0·9601) and wind speed (0·6239) as the ecological factors that influence the intensity of transmission of the H5N1 virus. The model also includes distance from the first outbreak (-0·9175) with an Akaike's Information Criterion of -103·87. Our analysis using a point process model showed that geographical heterogeneity, seasonal effects, temperature, wind as well as proximity to the first outbreak are very important components of spread and transmission of HPAI H5N1.

摘要

这项研究专注于尼日利亚高致病性禽流感(HPAI)H5N1 病毒爆发的流行病学分析。数据包括 145 次疫情爆发,以及感染农场的位置和感染确认日期。为了调查有利于病毒传播和扩散的环境条件,对气象站与感染农场的位置进行了重新调整。完全空间随机性的空间柯尔莫哥洛夫-斯米尔诺夫检验拒绝了病毒强度恒定的零假设(P<0·0001)。初步探索性分析显示,高海拔地区农场的 H5N1 病毒发病率有所增加。泊松对数线性条件强度函数的结果确定了温度(-0·9601)和风速(0·6239)是影响 H5N1 病毒传播强度的生态因素。该模型还包括与第一次疫情爆发的距离(-0·9175),其 Akaike 信息准则为-103·87。我们使用点过程模型进行的分析表明,地理异质性、季节性影响、温度、风速以及与第一次疫情爆发的接近程度是 HPAI H5N1 传播和传播的重要组成部分。

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