Meteorological variables and malaria in a Chinese temperate city: A twenty-year time-series data analysis

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...

Full description

Saved in:
Bibliographic Details
Published inEnvironment international Vol. 36; no. 5; pp. 439 - 445
Main Authors Zhang, Ying, Bi, Peng, Hiller, Janet E.
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 01.07.2010
Elsevier
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary: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 °C rise in maximum temperature may be related to a 7.7% to 12.7% increase and a 1 °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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0160-4120
1873-6750
DOI:10.1016/j.envint.2010.03.005