Centre for Infectious Disease Control, National Institute for Public Health and the Environment, A van Leeuwenhoeklaan 9, PO Box 1, 3720 BA Bilthoven, the Netherlands.
BMC Infect Dis. 2010 Mar 16;10:69. doi: 10.1186/1471-2334-10-69.
A Q-fever outbreak occurred in an urban area in the south of the Netherlands in May 2008. The distribution and timing of cases suggested a common source. We studied the spatial relationship between the residence locations of human cases and nearby small ruminant farms, of which one dairy goat farm had experienced abortions due to Q-fever since mid April 2008. A generic geographic information system (GIS) was used to develop a method for source detection in the still evolving major epidemic of Q-fever in the Netherlands.
All notified Q-fever cases in the area were interviewed. Postal codes of cases and of small ruminant farms (size >40 animals) located within 5 kilometres of the cluster area were geo-referenced as point locations in a GIS-model. For each farm, attack rates and relative risks were calculated for 5 concentric zones adding 1 kilometre at a time, using the 5-10 kilometres zone as reference. These data were linked to the results of veterinary investigations.
Persons living within 2 kilometres of an affected dairy goat farm (>400 animals) had a much higher risk for Q-fever than those living more than 5 kilometres away (Relative risk 31.1 [95% CI 16.4-59.1]).
The study supported the hypothesis that a single dairy goat farm was the source of the human outbreak. GIS-based attack rate analysis is a promising tool for source detection in outbreaks of human Q-fever.
2008 年 5 月,荷兰南部一个城市地区发生了 Q 热疫情。病例的分布和时间表明存在共同来源。我们研究了人类病例的居住地点与附近小型反刍动物农场之间的空间关系,其中一个山羊奶农场自 2008 年 4 月中旬以来因 Q 热而经历了流产。使用通用地理信息系统(GIS)开发了一种方法,用于检测荷兰仍在发展的 Q 热大流行中的源头。
对该地区所有报告的 Q 热病例进行了访谈。病例和位于 5 公里以内的小型反刍动物农场(规模> 40 只动物)的邮政编码在 GIS 模型中被定位为点位置。对于每个农场,使用 5-10 公里区域作为参考,每次增加 1 公里,计算 5 个同心区域的攻击率和相对风险。将这些数据与兽医调查的结果联系起来。
居住在受影响的山羊奶农场(> 400 只动物)2 公里范围内的人比居住在 5 公里以外的人感染 Q 热的风险高得多(相对风险 31.1 [95%CI 16.4-59.1])。
该研究支持了一个假设,即单个山羊奶农场是人类疫情的源头。基于 GIS 的攻击率分析是检测人类 Q 热疫情源头的有前途的工具。