Remote sensing measurements of sea surface temperature as an indicator of Vibrio parahaemolyticus in oyster meat and human illnesses.
Remote sensing measurements of sea surface temperature as an indicator of Vibrio parahaemolyticus in oyster meat and human illnesses.
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DOI：
10.1186/s12940-017-0301-x
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发表时间：
2017-08-31
期刊：
影响因子：
--
通讯作者：
Galanis E
中科院分区：
文献类型：
--
作者：
Konrad S;Paduraru P;Romero-Barrios P;Henderson SB;Galanis E
副溶血性弧菌（Vp）是一种在全球海洋环境中自然存在的细菌。它可以引起人类胃肠道疾病，主要是通过食用生牡蛎。水温以及潜在的其他环境因素对Vp在环境中的生长和增殖起着重要作用。量化环境变量与Vp疾病发病率或指标之间的关系对公共卫生监测有价值，有助于提供信息并采取适当的预防措施。本研究旨在评估加拿大不列颠哥伦比亚省（BC）环境参数与Vp的关系。该研究使用了2002年至2015年牡蛎肉中的副Vp计数和2011年至2015年BC省实验室确认的副Vp疾病。这些数据与公开来源的环境参数相匹配，包括从空间分辨率为1公里的卫星读数中获得的夜间海面温度（SST）遥感测量值。利用三个独立的模型，本文评估了(1)牡蛎肉中每日海温与Vp计数之间的关系，(2)牡蛎中每周平均Vp计数与每周Vp疾病之间的关系，(3)每周平均海温与每周Vp疾病之间的关系。对盐度和叶绿素a的影响也进行了评价。采用线性回归量化海温与Vp之间的关系，采用分段回归确定关注的海温阈值。共收集牡蛎样本2327份，实验室确诊病例293例。在模型1中，海温和盐度都是牡蛎肉中log（Vp）计数的显著预测因子。在模型2中，牡蛎肉中的平均对数（Vp）计数是Vp疾病的显著预测因子。在模型3中，每周平均海温是每周Vp疾病的显著预测因子。分段回归模型确定了模型1和模型3的SST阈值约为14℃，表明在较高温度下牡蛎肉中Vp和Vp疾病的风险增加。监测海温，特别是通过容易获得的遥感数据，可以作为Vp的警告信号，并有助于告知采取和停止预防或控制措施。
Vibrio parahaemolyticus (Vp) is a naturally occurring bacterium found in marine environments worldwide. It can cause gastrointestinal illness in humans, primarily through raw oyster consumption. Water temperatures, and potentially other environmental factors, play an important role in the growth and proliferation of Vp in the environment. Quantifying the relationships between environmental variables and indicators or incidence of Vp illness is valuable for public health surveillance to inform and enable suitable preventative measures. This study aimed to assess the relationship between environmental parameters and Vp in British Columbia (BC), Canada. The study used Vp counts in oyster meat from 2002-2015 and laboratory confirmed Vp illnesses from 2011-2015 for the province of BC. The data were matched to environmental parameters from publicly available sources, including remote sensing measurements of nighttime sea surface temperature (SST) obtained from satellite readings at a spatial resolution of 1 km. Using three separate models, this paper assessed the relationship between (1) daily SST and Vp counts in oyster meat, (2) weekly mean Vp counts in oysters and weekly Vp illnesses, and (3) weekly mean SST and weekly Vp illnesses. The effects of salinity and chlorophyll a were also evaluated. Linear regression was used to quantify the relationship between SST and Vp, and piecewise regression was used to identify SST thresholds of concern. A total of 2327 oyster samples and 293 laboratory confirmed illnesses were included. In model 1, both SST and salinity were significant predictors of log(Vp) counts in oyster meat. In model 2, the mean log(Vp) count in oyster meat was a significant predictor of Vp illnesses. In model 3, weekly mean SST was a significant predictor of weekly Vp illnesses. The piecewise regression models identified a SST threshold of approximately 14oC for both model 1 and 3, indicating increased risk of Vp in oyster meat and Vp illnesses at higher temperatures. Monitoring of SST, particularly through readily accessible remote sensing data, could serve as a warning signal for Vp and help inform the introduction and cessation of preventative or control measures.
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影响因子：
4.4
作者：
Martinez-Urtaza, Jaime;Lozano-Leon, Antonio;Garcia-Martin, Oscar
通讯作者：
Garcia-Martin, Oscar
影响因子：
2
作者：
Nordstrom, JL;Kaysner, CA;DePaola, A
通讯作者：
DePaola, A
DOI：
10.3390/ijerph13020188
发表时间：
2016-02-03
影响因子：
--
作者：
Hsiao HI;Jan MS;Chi HJ
通讯作者：
Chi HJ
影响因子：
5.2
作者：
Haley BJ;Kokashvili T;Tskshvediani A;Janelidze N;Mitaishvili N;Grim CJ;Constantin de Magny G;Chen AJ;Taviani E;Eliashvili T;Tediashvili M;Whitehouse CA;Colwell RR;Huq A
通讯作者：
Huq A
影响因子：
30.7
作者：
Baker-Austin, Craig;Trinanes, Joaquin A.;Martinez-Urtaza, Jaime
通讯作者：
Martinez-Urtaza, Jaime