Vol. 7, Issue 1, Part A (2020)
Malaria incidences prognosis using climatic factors in Mysore, India: A time series approach
Author(s): Stavelin Abhinandithe K, Madhu B, S Balasubramanian and Sahana KS
Abstract: Changing condition along with climatic components represent the greatest test in battling against the wellspring of intestinal sickness Malaria despite everything stays a general medical issue in creating nations. Utilizing climatic factors in Mysore as indicators this investigation was intended to estimate Malaria cases in Mysore, India. Strategies: the number of month to month malaria occurrences from January 2013 to December 2017 have been gathered from District health office, Mysore. Climatic information of month to month mean rainfall, least and most extreme temperature were from territorial meteorological focus, Mysore. Expert modeler of IBM SPSS version 22 was utilized to serve the purpose of splitting down the time arrangement information. Result: Autoregressive moving average, winter's additive model, which is comparable to ARIMA (0, 1, 0) (0, 1, 0)12, was considered to be the best fit. Seasonal Adjusted Factor (SAF) for malaria incidences appears high during the long stretches of August and November. ARIMA models is a straightforward and solid instrument in creating dependable estimates for malaria in Mysore, India.
How to cite this article:
Stavelin Abhinandithe K, Madhu B, S Balasubramanian, Sahana KS. Malaria incidences prognosis using climatic factors in Mysore, India: A time series approach. Int J Mosq Res 2020;7(1):45-50.