Malaria is one of the major mortality and morbidity incidences in the country. The main aim of the study is to
determine the malaria distribution along months of year 2003 to 2012 at Kucha district. The risks of morbidity and mortality
associated with malaria are characterized by its distribution in a period of time through month of year. The time series analysis
of malaria prevalence in the Kucha district was tested through test of randomness using turning point approach. A time series
analysis trend analysis and box-Jenkins models were employed to the data obtained from health centers of Kucha districts.
Autocorrelation Function and Partial Autocorrelation Function were adopted to identify the appropriate box-Jenkins models.
Autoregressive Integrated Moving Average models were adopted for final data analysis with differencing to attain stationary
data. The quadratic trend was found best fit for malaria data and it shows a decreasing trend along a period of month of year
2010 to 2012. Based on the results of model diagnostic checking ARIMA model was found to be significantly fit the data for
malaria prevalence forecast. As a result malaria distribution shows seasonal variation in the district especially in the month
September to January and July to August. The highest malaria prevalence was observed in December months of each year
while, low rate of malaria prevalence was observed in July months of each year.A study recommends that health professionals
should pay special attention on December months of each year by suggesting precaution action for those people living in the
district.