Geospatial analysis of household spread of Ebola virus in a quarantined village - Sierra Leone, 2014

被引:0
|
作者
Gleason, B. L. [1 ]
Foster, S. [2 ]
Wilt, G. E. [2 ]
Miles, B. [2 ]
Lewis, B. [2 ]
Cauthen, K. [3 ]
King, M. [4 ]
Bayor, F. [5 ]
Conteh, S. [5 ]
Sesay, T. [5 ]
Kamara, S. I. [5 ]
Lambert, G. [3 ]
Finley, P. [3 ]
Beyeler, W. [3 ]
Moore, T. [3 ]
Gaudioso, J. [3 ]
Kilmarx, P. H. [1 ]
Redd, J. T. [1 ]
机构
[1] Ctr Dis Control & Prevent CDC, Ctr Global Hlth, Atlanta, GA USA
[2] ATSDR, Atlanta, GA USA
[3] SNL, Albuquerque, NM USA
[4] CDC, Ctr Surveillance Epidemiol & Lab Serv, Atlanta, GA 30333 USA
[5] Minist Hlth & Sanitat Sierra Leone MoHS, Makeni, Sierra Leone
来源
EPIDEMIOLOGY AND INFECTION | 2017年 / 145卷 / 14期
关键词
Ebola; geospatial analysis; Generalized Estimating Equations (GEE); Geographic Information System (GIS); epidemiology; WEST-AFRICA; EPIDEMIC;
D O I
10.1017/S0950268817001856
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
We performed a spatial-temporal analysis to assess household risk factors for Ebola virus disease (Ebola) in a remote, severely-affected village. We defined a household as a family's shared living space and a case-household as a household with at least one resident who became a suspect, probable, or confirmed Ebola case from 1 August 2014 to 10 October 2014. We used Geographic Information System (GIS) software to calculate inter-household distances, performed space-time cluster analyses, and developed Generalized Estimating Equations (GEE). Village X consisted of 64 households; 42% of households became case-households over the observation period. Two significant space-time clusters occurred among households in the village; temporal effects outweighed spatial effects. GEE demonstrated that the odds of becoming a case-household increased by 4.0% for each additional person per household (P < 0.02) and 2.6% per day (P < 0.07). An increasing number of persons per household, and to a lesser extent, the passage of time after onset of the outbreak were risk factors for household Ebola acquisition, emphasizing the importance of prompt public health interventions that prioritize the most populated households. Using GIS with GEE can reveal complex spatial-temporal risk factors, which can inform prioritization of response activities in future outbreaks.
引用
收藏
页码:2921 / 2929
页数:9
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