Remote sensing measurements of sea surface temperature as an indicator of Vibrio parahaemolyticus in oyster meat and human illnesses

Environmental Health

Research

Pablo Romero-Barrios¹  Sarah B. Henderson²  Eleni Galanis²  Peggy Paduraru²  Stephanie Konrad³ 

[1] BC Centre for Disease Control, 655 West 12 Avenue, V5Z 4R4, Vancouver, British Columbia, Canada;BC Centre for Disease Control, 655 West 12 Avenue, V5Z 4R4, Vancouver, British Columbia, Canada;School of Population and Public Health, University of British Columbia, 2206 East Mall, V6T 1Z3, Vancouver, British Columbia, Canada;Canadian Field Epidemiology Program, Public Health Agency of Canada, 130 Colonnade Road, K1A 0K9, Ottawa, Ontario, Canada;BC Centre for Disease Control, 655 West 12 Avenue, V5Z 4R4, Vancouver, British Columbia, Canada;

关键词: Vibrio parahaemolyticus;    Oysters;    Illness;    Sea surface temperature;    Threshold model;    Environmental factors;    Remote sensing;   

DOI  :  10.1186/s12940-017-0301-x

 received in 2017-04-04, accepted in 2017-08-21,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundVibrio 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.MethodsThe 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.ResultsA 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.ConclusionMonitoring 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.

【 授权许可】

CC BY   
© The Author(s). 2017