Defining and detecting malaria epidemics in south-east Iran

<p>Abstract</p> <p>Background</p> <p>A lack of consensus on how to define malaria epidemics has impeded the evaluation of early detection systems. This study aimed to develop local definitions of malaria epidemics in a known malarious area of Iran, and to use that defin...

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Main Authors: McKelvie William R, Haghdoost Ali, Raeisi Ahmad
Format: Article
Language:English
Published: BMC 2012-03-01
Series:Malaria Journal
Subjects:
Online Access:http://www.malariajournal.com/content/11/1/81
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spelling doaj-f447f28c0daf403fbd3e7aa3d152c1ee2020-11-25T00:03:44ZengBMCMalaria Journal1475-28752012-03-011118110.1186/1475-2875-11-81Defining and detecting malaria epidemics in south-east IranMcKelvie William RHaghdoost AliRaeisi Ahmad<p>Abstract</p> <p>Background</p> <p>A lack of consensus on how to define malaria epidemics has impeded the evaluation of early detection systems. This study aimed to develop local definitions of malaria epidemics in a known malarious area of Iran, and to use that definition to evaluate the validity of several epidemic alert thresholds.</p> <p>Methods</p> <p>Epidemic definition variables generated from surveillance data were plotted against weekly malaria counts to assess which most accurately labelled aberrations. Various alert thresholds were then generated from weekly counts or log counts. Finally, the best epidemic definition was used to calculate and compare sensitivities, specificities, detection delays, and areas under ROC curves of the alert thresholds.</p> <p>Results</p> <p>The best epidemic definition used a minimum duration of four weeks and week-specific and overall smoothed geometric means plus 1.0 standard deviation. It defined 13 epidemics. A modified C-SUM alert of untransformed weekly counts using a threshold of mean + 0.25 SD had the highest combined sensitivity and specificity. Untransformed C-SUM alerts also had the highest area under the ROC curve.</p> <p>Conclusions</p> <p>Defining local malaria epidemics using objective criteria facilitated the evaluation of alert thresholds. This approach needs further study to refine epidemic definitions and prospectively evaluate epidemic alerts.</p> http://www.malariajournal.com/content/11/1/81MalariaEpidemicsIranSensitivitySpecificitySurveillance
collection DOAJ
language English
format Article
sources DOAJ
author McKelvie William R
Haghdoost Ali
Raeisi Ahmad
spellingShingle McKelvie William R
Haghdoost Ali
Raeisi Ahmad
Defining and detecting malaria epidemics in south-east Iran
Malaria Journal
Malaria
Epidemics
Iran
Sensitivity
Specificity
Surveillance
author_facet McKelvie William R
Haghdoost Ali
Raeisi Ahmad
author_sort McKelvie William R
title Defining and detecting malaria epidemics in south-east Iran
title_short Defining and detecting malaria epidemics in south-east Iran
title_full Defining and detecting malaria epidemics in south-east Iran
title_fullStr Defining and detecting malaria epidemics in south-east Iran
title_full_unstemmed Defining and detecting malaria epidemics in south-east Iran
title_sort defining and detecting malaria epidemics in south-east iran
publisher BMC
series Malaria Journal
issn 1475-2875
publishDate 2012-03-01
description <p>Abstract</p> <p>Background</p> <p>A lack of consensus on how to define malaria epidemics has impeded the evaluation of early detection systems. This study aimed to develop local definitions of malaria epidemics in a known malarious area of Iran, and to use that definition to evaluate the validity of several epidemic alert thresholds.</p> <p>Methods</p> <p>Epidemic definition variables generated from surveillance data were plotted against weekly malaria counts to assess which most accurately labelled aberrations. Various alert thresholds were then generated from weekly counts or log counts. Finally, the best epidemic definition was used to calculate and compare sensitivities, specificities, detection delays, and areas under ROC curves of the alert thresholds.</p> <p>Results</p> <p>The best epidemic definition used a minimum duration of four weeks and week-specific and overall smoothed geometric means plus 1.0 standard deviation. It defined 13 epidemics. A modified C-SUM alert of untransformed weekly counts using a threshold of mean + 0.25 SD had the highest combined sensitivity and specificity. Untransformed C-SUM alerts also had the highest area under the ROC curve.</p> <p>Conclusions</p> <p>Defining local malaria epidemics using objective criteria facilitated the evaluation of alert thresholds. This approach needs further study to refine epidemic definitions and prospectively evaluate epidemic alerts.</p>
topic Malaria
Epidemics
Iran
Sensitivity
Specificity
Surveillance
url http://www.malariajournal.com/content/11/1/81
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