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ORIGINAL ARTICLE
Year : 2017  |  Volume : 146  |  Issue : 5  |  Page : 612-621

Devising a method towards development of early warning tool for detection of malaria outbreak


Environmental Epidemiology Division, ICMR-National Institute of Malaria Research, New Delhi, India

Correspondence Address:
Dr. Ramesh C Dhiman
Environmental Epidemiology Division, ICMR-National Institute of Malaria Research, Dwarka, New Delhi 110 077
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijmr.IJMR_426_16

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Background & objectives: Uncertainty often arises in differentiating seasonal variation from outbreaks of malaria. The present study was aimed to generalize the theoretical structure of sine curve for detecting an outbreak so that a tool for early warning of malaria may be developed. Methods: A 'case/mean-ratio scale' system was devised for labelling the outbreak in respect of two diverse districts of Assam and Rajasthan. A curve-based method of analysis was developed for determining outbreak and using the properties of sine curve. It could be used as an early warning tool for Plasmodium falciparum malaria outbreaks. Result: In the present method of analysis, the critical Cmax(peak value of sine curve) value of seasonally adjusted curve for P. falciparum malaria outbreak was 2.3 for Karbi Anglong and 2.2 for Jaisalmer districts. On case/mean-ratio scale, the Cmax value of malaria curve between Cmaxand 3.5, the outbreak could be labelled as minor while >3.5 may be labelled as major. In epidemic years, with mean of case/mean ratio of ≥1.00 and root mean square (RMS) ≥1.504 of case/mean ratio, outbreaks can be predicted 1-2 months in advance. Interpretation & conclusions: The present study showed that in P. falciparum cases in Karbi Anglong (Assam) and Jaisalmer (Rajasthan) districts, the rise in Cmaxvalue of curve was always followed by rise in average/RMS or both and hence could be used as an early warning tool. The present method provides better detection of outbreaks than the conventional method of mean plus two standard deviation (mean+2 SD). The identified tools are simple and may be adopted for preparedness of malaria outbreaks.


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