Discipline of Public Health, School of Population Health and Clinical Practice, The University of Adelaide, Adelaide, SA 5005, Australia.
Environ Int. 2010 Jul;36(5):439-45. doi: 10.1016/j.envint.2010.03.005. Epub 2010 Apr 20.
This study aimed to examine the impact of climate variation on malaria in a temperate region of China.
A 20-year historical time-series data analysis was conducted to examine the relationship between meteorological variables, including maximum and minimum temperatures, rainfall, humidity, and cases of malaria in Jinan, a temperate city in northern China. Data were retrieved from 1959 and 1979 and analyzed on a monthly basis. Spearman correlation and cross-correlation analyses were performed to identify time lag values between each meteorological variable and the number of malaria cases. The Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used to quantify the relationship between the meteorological variables and malaria cases.
The SARIMA models indicate that a 1 degrees C rise in maximum temperature may be related to a 7.7% to 12.7% increase and a 1 degrees C rise in minimum temperature may result in approximately 11.8% to 15.8% increase in the number of malaria cases. A clear association between malaria and other selected weather variables, including rainfall and humidity, has not been detected in this study.
Temperature could play an important role in the transmission of malaria in temperate regions of China.
本研究旨在探讨气候变异对中国温带地区疟疾的影响。
采用 20 年历史时间序列数据分析方法，考察了气象变量（包括最高温和最低温、降雨量、湿度和疟疾病例）与中国北方温带城市济南之间的关系。数据取自 1959 年至 1979 年，按月进行分析。采用 Spearman 相关和交叉相关分析确定每个气象变量与疟疾病例数之间的时间滞后值。采用季节性自回归综合移动平均（SARIMA）模型来量化气象变量与疟疾病例之间的关系。
SARIMA 模型表明，最高温度升高 1°C 可能与疟疾病例数增加 7.7%至 12.7%有关，最低温度升高 1°C 可能导致疟疾病例数增加约 11.8%至 15.8%。本研究未发现疟疾与其他选定天气变量（包括降雨量和湿度）之间存在明显关联。
温度可能在中国温带地区疟疾传播中发挥重要作用。
