Abstract:
The study is particularly involved in the increasing effect of temperature and rainfall on the number of malaria outpatient and spatial variation in the sensitivity of malaria outpatient numbers to climate conditions. In this study, time analysis is ha been used to investigate the association between climatic variability and the n umber of monthly malaria outpatients from January 2009 to February 2014 in the Narok County where malaria epidemics have been reported. Higher order autoregressive model was used in order to test if the number of Outpatients is dependent on the past and the Durbin Wat on test was used to test existence of serial correlation in the outpatient number. Non -linear mixed regression was used to test effects of climate variables on malaria infections.These results shows that the variation in the number of outpatients due to autoregression 7.88%. On testing the serial correlation of the malaria outpatient we find that there is positive serial correlation by Durbin Watson test (D W). While the variation due to climatic factors combined is 94.92% thi is te ted by the coefficient of determination. Thus to a large extent weather is a contributing factor to spreading of malaria as compared to autoregression effect. From the data individual weather variables played no significant role except for minimum temperature which tends to affect the spread of malaria significantly by almost 25%. The study shows that during cool and wet season in Narok there is wide spread malaria infection to a large extent. High infection on children less than five years of age as been noticed of about 22% for the whole period under study according to the health records. This hence directs that young children should be immunized again t malaria and other malaria di ease preventive measures should be From the results conclude according to the results that indeed malaria outpatient is much related with climate variation and that malaria affects juveniles to a large extent. This knowledge is critical to the development of malaria early warning system for the Kenya government.
