Abstract: Objective To explore the fuzzy evaluation based on Matlab and its application in the quantitative risk evaluation of tick?borne diseases. Methods The coniferous forest, mixed coniferous?broadleaf forest, and meadow in the Weizigou forest farm, Dongjingcheng town, Heilongjiang province, China were selected as three habitats for investigation. All ticks were manually collected with white cloth flagging. A thermohygrometer was used to record the temperature and humidity. The fuzzy evaluation indicators of tick?borne diseases were collected, and the fuzzy inference system was created to assess the indicators. Results From May to July 2012, the analysis of survey data showed that the risk score exhibited an overall downward trend, with a maximum value of 60.0, which indicated a relatively high level of risk, and a minimum value of 10.3, which indicated a low level of risk. In May 2013, the analysis of survey data showed that the risk score was 85.5 for all the three habitats, which indicated a high level of risk. According to 13 times of investigation, 46.16% of the habitats had a low level of risk, 15.38% had a middle level of risk, 7.69% had a relatively high level of risk, and 30.77% had a high level of risk. The overall risk of Weizigou forest farm is at a low level. Conclusion Temperature and humidity are important influential factors for the activity of ticks. It is of certain significance to select temperature, humidity, and tick density as indicators in the fuzzy evaluation of tick?borne diseases. Based on the fuzzy mathematical theory, the fuzzy evaluation has a rigorous theoretical basis and is scientific and rational in the risk evaluation of tick?borne diseases.

Key words: Tick?borne disease, Fuzzy evaluation, Matlab

摘要： 目的 探索基于Matlab的模糊评价方法, 及其在蜱媒疾病定量风险评价中的应用。方法 在黑龙江省东京城镇苇子沟林场选择针叶林、针阔混交林、草地3种不同生境调查。用人工小时布旗法采蜱, 用温湿度计记录温度、湿度。收集蜱媒疾病模糊评价指标, 并且构建模糊推理系统对相应指标进行评价。结果 2012年5－7月调查数据经分析后显示:风险评分总体呈下降趋势, 最高值为60.0, 属于较高风险等级;最低值为10.3, 属于低风险水平。2013年5月调查数据经分析后显示:3种生境风险评分值均为85.5, 属于高风险水平。在13次调查中, 生境的风险评分有46.16%属于低风险水平, 15.38%属于中风险水平, 7.69%属于较高风险水平, 30.77%属于高风险水平。黑龙江省东京城镇苇子沟林场的总体风险等级处于低水平。结论 温度和湿度是影响蜱类活动的重要因素, 选择温度、湿度、蜱密度3个指标对蜱媒疾病进行模糊评价, 具有一定意义。基于模糊数学理论建立的模糊评价, 理论依据严密, 在蜱媒疾病风险评价的应用中具有科学性、合理性。

关键词: 蜱媒疾病, 模糊评价, Matlab