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

<p>Abstract</p> <p>Background</p> <p>Elucidation 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 ofte...

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Main Authors: Sarkar Ram, Roy Sayantani, Sinha Somdatta
Format: Article
Language:English
Published: BMC 2011-10-01
Series:Malaria Journal
Online Access:http://www.malariajournal.com/content/10/1/301
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spelling doaj-e5800d9c24324d72979298ad4df352af2020-11-24T20:55:00ZengBMCMalaria Journal1475-28752011-10-0110130110.1186/1475-2875-10-301Theoretical investigation of malaria prevalence in two Indian cities using the response surface methodSarkar RamRoy SayantaniSinha Somdatta<p>Abstract</p> <p>Background</p> <p>Elucidation 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.</p> <p>Methods</p> <p>The 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.</p> <p>Results</p> <p>The 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.</p> <p>Conclusions</p> <p>This method promises to provide reliable forecast of malaria incidence across varying environmental conditions, which may help in designing useful control programmes for malaria.</p> http://www.malariajournal.com/content/10/1/301
collection DOAJ
language English
format Article
sources DOAJ
author Sarkar Ram
Roy Sayantani
Sinha Somdatta
spellingShingle Sarkar Ram
Roy Sayantani
Sinha Somdatta
Theoretical investigation of malaria prevalence in two Indian cities using the response surface method
Malaria Journal
author_facet Sarkar Ram
Roy Sayantani
Sinha Somdatta
author_sort Sarkar Ram
title Theoretical investigation of malaria prevalence in two Indian cities using the response surface method
title_short Theoretical investigation of malaria prevalence in two Indian cities using the response surface method
title_full Theoretical investigation of malaria prevalence in two Indian cities using the response surface method
title_fullStr Theoretical investigation of malaria prevalence in two Indian cities using the response surface method
title_full_unstemmed Theoretical investigation of malaria prevalence in two Indian cities using the response surface method
title_sort theoretical investigation of malaria prevalence in two indian cities using the response surface method
publisher BMC
series Malaria Journal
issn 1475-2875
publishDate 2011-10-01
description <p>Abstract</p> <p>Background</p> <p>Elucidation 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.</p> <p>Methods</p> <p>The 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.</p> <p>Results</p> <p>The 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.</p> <p>Conclusions</p> <p>This method promises to provide reliable forecast of malaria incidence across varying environmental conditions, which may help in designing useful control programmes for malaria.</p>
url http://www.malariajournal.com/content/10/1/301
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