Malaria in India: A Predictive Study
- Author:
Surajit Das
1
;
Tapash Ranjan Saha
2
;
Sandeep Poddar
3
;
Sabyasachi Das
4
Author Information
- Publication Type:Journal Article
- Keywords: Malaria, India, ARIMA Model, Econometric forecasting model
- From:Malaysian Journal of Medicine and Health Sciences 2020;16(Supp 10, November):25-29
- CountryMalaysia
- Language:English
- Abstract: Introduction: Malaria is devastating infectious disease not only India but also throughout the globe due to its high morbidity and mortality factor for last few centuries. From 19th and early 20th centuries, almost a quarter of the Indian populations were severely suffering from malaria. The economic loss due to increased mortality in malaria was estimated 10 million rupees per year in 1935. According to the World Malaria Report of 2017, malaria incidence accounted for 58% of cases in India. The objective of this study is to prediction of “annual” malaria incidences in India, depending on the basis of last 22 years national malaria epidemiology data. Methods: This study uses data from the official website of the National Program for the Control of Vector borne Diseases (NVBDCP) (http://nvbdcp. gov.in/) from 1995 to 2016. For creating a forecasting tool on Malaria surveillance in India, Econometric forecasting model (ARIMA Model ((0,1,1) (1,0,0) 12)) was used. Results: ARIMA statistical model ((0,1,1) (1,0,0) 12) found to be highly effective and significant (P < 0.05) in prediction of future epidemiological surveillance of malaria in India. ARIMA statistical model could be successfully use in prediction of annual malaria incidences in India after adjusting different highly contributing environmental and geographical factors, such as climate change, temperature, rainfall, and relative humidity. Conclusion: The historical forecast of the occurrence of malaria in India will allow the government to improve planning, control and prevention through public health interventions. In addition, the pharmaceutical industry will assist medical members in pre-treatment and drug interventions to respond to the increased or decreased occurrence of malaria.
- Full text:11.2020my0902.pdf
