The temporal lagged association between meteorological factors and malaria in 30 counties in south-west China: a multilevel distributed lag non-linear analysis

Malaria Journal

Research

Xiao-Hua Zhou¹  Zijian Feng²  Xiaosong Li³  Fei Chen³  Xing Zhao⁴ 

[1] Department of Biostatistics, School of Public Health, University of Washington, NE Pacific Street, 98195, Seattle, USA;HSR&D Center of Excellence, VA Puget Sound Health Care System, 1100 Olive Way Metro Park West Suite 1400, 98101, Seattle, USA;Office for Disease Control and Emergency Response, Chinese Centre for Disease Control and Prevention, NE Pacific Street, 102206, Beijing, China;West China School of Public Health, Sichuan University, No.17 Section 3, South Renmin Road, 610041, Chengdu, China;West China School of Public Health, Sichuan University, No.17 Section 3, South Renmin Road, 610041, Chengdu, China;Department of Biostatistics, School of Public Health, University of Washington, NE Pacific Street, 98195, Seattle, USA;

关键词: Malaria;    Malaria Case;    Meteorological Variable;    Meteorological Factor;    Malaria Incidence;   

DOI  :  10.1186/1475-2875-13-57

 received in 2013-11-23, accepted in 2014-02-13,  发布年份 2014

来源: Springer

【 摘 要 】

BackgroundThe association between malaria and meteorological factors is complex due to the lagged and non-linear pattern. Without fully considering these characteristics, existing studies usually concluded inconsistent findings. Investigating the lagged correlation pattern between malaria and climatic variables may improve the understanding of the association and generate possible better prediction models. This is especially beneficial to the south-west China, which is a high-incidence area in China.MethodsThirty counties in south-west China were selected, and corresponding weekly malaria cases and four weekly meteorological variables were collected from 2004 to 2009. The Multilevel Distributed Lag Non-linear Model (MDLNM) was used to study the temporal lagged correlation between weekly malaria and weekly meteorological factors. The counties were divided into two groups, hot and cold weathers, in order to compare the difference under different climatic conditions and improve reliability and generalizability within similar climatic conditions.ResultsRainfall was associated with malaria cases in both hot and cold weather counties with a lagged correlation, and the lag range was relatively longer than those of other meteorological factors. Besides, the lag range was longer in hot weather counties compared to cold weather counties. Relative humidity was correlated with malaria cases at early and late lags in hot weather counties.Minimum temperature had a longer lag range and larger correlation coefficients for hot weather counties compared to cold weather counties. Maximum temperature was only associated with malaria cases at early lags.ConclusionUsing weekly malaria cases and meteorological information, this work studied the temporal lagged association pattern between malaria cases and meteorological information in south-west China. The results suggest that different meteorological factors show distinct patterns and magnitudes for the lagged correlation, and the patterns will depend on the climatic condition. Existing inconsistent findings for climatic factors’ lags could be due to either the invalid assumption of a single fixed lag or the distinct temperature conditions from different study sites. The lag pattern for meteorological factors should be considered in the development of malaria early warning system.

【 授权许可】

Unknown   
© Zhao et al.; licensee BioMed Central Ltd. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.