Meteorological Variables and Malaria in a Chinese Temperate City: A Twenty-Year Time-Series Data Analysis

Abstract

ISEE-0022 Background and Objective: Re-emergence of malaria has been observed in China recently. Although the association between climate variation and malaria has been addressed in many countries, little is known about the impact of climate variation on malaria in temperate regions of China. Methods: A 20-year historical time-series data analysis was conducted to examine the relationship between meteorological variables, including maximum and minimum temperatures, rainfall, humidity, air pressure, and cases of malaria in Jinan, a temperate city in northern China. Data were retrieved for the period 1959 to 1979 and analyzed on a monthly basis. Spearman correlation and cross-correlation analyses were performed between each meteorological variable and the number of malaria cases, to identify time lag values. A Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used to quantify the relationship between the meteorological variables and malaria cases. Results: The SARIMA models indicate that a 1°C rise in maximum temperature may be related to a 4.2% to 13.9% increase, and a 1°C rise in minimum temperature, may result in an approximately 6.8% to 14.8% increase in the number of malaria cases. A clear association between malaria and other selected weather variables, including rainfall, humidity and air pressure, has not been detected in this study. Conclusion: Results suggest that temperature could play an important role in the transmission of malaria in temperate regions of China, and climate change may bring about more malaria cases in this region of China if no action is taken.