Second National Communications It will be noted that while NESSS data appears robust, the transition to the Philippine Integrated Disease Surveillance and Response (PIDSR) will move reported figures upwards due to having more reporting units (provincial level units). National data was utilized for historical correlation as baseline. This was done in parallel to the pilot areas in the study with the following results: Ø Malaria is positively associated with mean temperature (r = .364, p <.01). The number of malaria cases is high when the mean temperature is high. Ø Leptospirosis is positively associated with the volume of rainfall (r = .512, p <.01). The number of leptospirosis cases is high when the volume of rainfall is high. Ø No significant association exists between malaria and rainfall and so is leptospirosis and mean temperature. Climate Change Paramaters Malaria Leptospirosis r* p* r p Mean Temperature (°C) .364 .001 -.130 .156 Rainfall (mm/day) -.023 .837 .512 .000 Graph 16. Malaria Cases and Mean Temperature by Month Philippines, 2000-2006 477 Malaria Mean Tem perature 30 427 28 377 327 26 277 227 24 177 22 127 1Ja n 1- -00 Ap r-0 1- 0 Ju 1- l-00 Oc t 1- -00 Ja n1- 01 Ap r-0 1- 1 Ju 1- l-01 Oc t 1- -01 Ja n1- 02 Ap r-0 1- 2 Ju 1- l-02 Oc 1- t-02 Ja n 1- -03 Ap r-0 1- 3 Ju 1- l-03 Oc t 1- -03 Ja n1- 04 Ap r-0 1- 4 Ju 1- l-04 Oc 1- t-04 Ja n 1- -05 Ap r-0 1- 5 Ju 1- l-05 Oc t 1- -05 Ja n 1- -06 Ap r-0 1- 6 Ju 1- l-06 Oc t-0 6 77 20 42