Theoretical investigation of malaria prevalence in two Indian cities using the response surface method

Malaria Journal

Methodology

Ram Rup Sarkar¹  Somdatta Sinha¹  Sayantani Basu Roy¹ 

[1] Centre for Cellular and Molecular Biology (CSIR), Uppal Road, Hyderabad, India;

关键词: Malaria;    Response Surface Method;    Malaria Incidence;    Model Reduction Technique;    Slide Positivity Rate;   

DOI  :  10.1186/1475-2875-10-301

 received in 2011-06-13, accepted in 2011-10-14,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundElucidation of the relationships between malaria incidence and climatic and non-climatic factors in a region is of utmost importance in understanding the causative factors of disease spread and design of control strategies. Very often malaria prevalence data is restricted to short time scales (months to few years). This demands application of rigorous statistical modelling techniques for analysis and prediction. The monthly malaria prevalence data for three to five years from two cities in southern India, situated in two different climatic zones, are studied to capture their dependence on climatic factors.MethodsThe statistical technique of response surface method (RSM) is applied for the first time to study any epidemiological data. A new step-by-step model reduction technique is proposed to refine the initial model obtained from RSM. This provides a simpler structure and gives better fit. This combined approach is applied to two types of epidemiological data (Slide Positivity Rates values and Total Malaria cases), for two cities in India with varying strengths of disease prevalence and environmental conditions.ResultsThe study on these data sets reveals that RSM can be used successfully to elucidate the important environmental factors influencing the transmission of the disease by analysing short epidemiological time series. The proposed approach has high predictive ability over relatively long time horizons.ConclusionsThis method promises to provide reliable forecast of malaria incidence across varying environmental conditions, which may help in designing useful control programmes for malaria.

【 授权许可】

Unknown   
© Roy et al; licensee BioMed Central Ltd. 2011. 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 cited.