摘要
利用空间大数据研究了环境要素对霍乱疫情发病影响机制,分析了沿海地区影响霍乱发病的主要气象和海洋环境要素,并以浙江省为实验区,基于浙江省近海海域海表面温度、海表面高度、海水叶绿素浓度以及气温和降水量等环境要素建立了霍乱预测模型,同时考虑霍乱的二次传播性,建立了基于宏观环境-SIR构架的霍乱预测改进模型,结果表明海洋环境参数对浙江省霍乱发病量有显著的影响,且具有一定的滞后性,考虑二次传播的基于宏观环境-SIR构架的改进模型预测效果要优于完全基于环境要素的预测模型。根据环境影响要素对霍乱疫情影响的时间滞后性效应,利用空间大数据构建沿海地区霍乱发病预测模型,可以使霍乱防控更加主动、及时和有效。
Supported by spatial big data,we studied the impact mechanism of environmental factors on the incidence of cholera,analyzed the main meteorological and marine environmental factors affecting the incidence of cholera in coastal areas.We established a cholera prediction model in Zhejiang Province based on environmental factors including sea surface temperature,sea surface height,sea chlorophyll concentration,temperature and precipitation in the sea area near Hangzhou Bay,and built an improved prediction model taking into account the secondary transmission of cholera.The prediction results show that the prediction model taking account the secondary transmission in Zhejiang Province are significantly better than the model that completely based on environmental factors.According to the time lag effect of environmental impact factors on the impact of cholera epidemic,using spatial big data to build the cholera incidence prediction model in coastal areas can make cholera prevention and control more active,timely and effective.
作者
徐敏
曹春香
钟少波
王丹萍
崔腾飞
康建荣
XU Min;CAO Chunxiang;ZHONG Shaobo;WANG Danping;CUI Tengfei;KANG Jianrong(State Key Laboratory of Remote Sensing Science,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing100101,China;School of Geography,Geomatics and Planning,Jiangsu Normal University,Xuzhou 221116,China;Beijng Research Center of Urban Systems Engineering,Beijing 100035,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《地理空间信息》
2022年第12期12-16,22,共6页
Geospatial Information
关键词
空间大数据
霍乱
遥感
环境要素
预测模型
spatial big data
cholera
remote sensing
environmental factor
prediction model
