ANALYSIS OF THE IMPACT OF TEMPERATURE AND RELATIVE HUMIDITY CHANGES ON DENGUE HEMORRHAGIC FEVER CASE NUMBERS ON 2016 (Case Study : Bandung) - Natascha Thiofanni, Aurelia
DHF (dengue hemorrhagic fever) is one of the diseases that is influenced by temperature and relative humidity changes. DHF case numbers in Bandung on 2016 increased and probably was caused by temperature and relative humidity changes on that year. To see the impact of temperature and relative humidity changes on DHF case numbers, regression and correlation analysis which also calculating the effect of fogging was done. Temperature and relative humidity data were processed to figure out the impact of time lag on the correlation with DHF case numbers. Then regression between the average values of temperature and relative humidity parameters in the time lag range was done. The optimal value from the result of the regression was used to determine optimal range for PDOR (Percentage of Days in Optimal Range) scenarios. PDOR scenario with the highest correlation to DHF case numbers were gone through another regression analysis along with fogging parameter. The result of the analysis showed that the temperature and relative humidity on two months before the DHF case detected have the highest correlation with DHF case numbers. The correlation between DHF case numbers and average values of temperature and relative humidity from two months until a week before DHF case detected is also positive. The optimal value of temperature parameter is 27oC. Relative humidity above 79% has positive impact. Optimal range for temperature is 24,86 – 29,15oC and for relative humidity is 70 – 88%. The result of the regression with PDOR 8-1 scenario and fogging has higher correlation (r = 0,964) and lower mean absolute percentage error (MAPE= 12,6%) than the one that used average value of temperature and relative humidity as parameters.