DENGUE AND MALARIA CASES IN THE PHILIPPINES: ASSOCIATION WITH TEMPERATURE, HUMIDITY AND RAINFALL Maria Ruth B. Pineda-Cortel, Ph.D.
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1 DENGUE AND MALARIA CASES IN THE PHILIPPINES: ASSOCIATION WITH TEMPERATURE, HUMIDITY AND RAINFALL Maria Ruth B. Pineda-Cortel, Ph.D. University of Santo Tomas Philippines
2 Objectives of the Study Identify trends, distribution patterns, and relations among diseases, variability of climate and socio- economic conditions Present the number of cases of dengue and malaria from 2008 to 2015 in the Philippines: trends and patterns Determine if climate factors (temperature, rainfall and humidity) are significantly associated with dengue and malaria cases in the Philippines percent of the cases contributed by the climate factors climatic factor with greatest effect on the prediction of dengue and malarial Determine effect of socio-economic conditions on the cases
3 Conceptual Framework INDEPENDENT VARIABLE CLIMATE FACTORS MEAN TEMPERATURE RAINFALL RELATIVE HUMIDITY DEPENDENT VARIABLE DENGUE AND MALARIA CASES
4 Data Collection Data on climatic factors were obtained from PAGASA mean temperature, amount of rainfall, and relative humidity Data on dengue and malaria cases were obtained from DOH and from different regions in the Philippines 2008 to the third quarter of 2015
5 Statistical Analysis Time series and structural analysis using Eviews 9.5 SV Augmented Dickey Fuller (ADF) was used to test for stationarity Granger causality was used to investigate causality between two variables
6 Total Dengue Cases ( ) Morbidity Mortality
7 NCR Region IVA
8 Region III Region I
9 Suspected Dengue Cases in the Philippines per Region ( ) Low: 2008, 2009 and 2014 Spike: 2010, 2011, 2012, 2013 and 2015 Highest: July to September Lowest: April and May Region 6 has the highest count of suspected dengue case, on August OVERALL: NCR, Region 3 and 4a
10 Suspected Dengue Death Cases in the Philippines per Region ( ) exhibit similar pattern with that of morbidity cases 2010, 2011 and 2015 Highest: July to September Lowest: April and May OVERALL: NCR, Region 4a and Region 7
11 Total Suspected Malaria Cases in the Philippines ( ) Total Suspected Malaria Cases ( )
12 Suspected Malaria Cases in the Philippines ( ) Lower cases than dengue Region 4b has extreme suspected cases of Malaria Palawan (1,401; 5) Occidental Mindoro (490; 5) Oriental Mindoro (383; 1) Romblon (244; 0) Marinduque (204; 2)
13 Minimum and Maximum Temperatures Min. Temp. Rel. Hum. Rainfall Max. Temp. Ave. Temp. and Rh Ave. Rf
14 Association/Correlation with Climatic Factors Correlation Min Temp Max Temp Rainfall Humidity Dengue.135 ** **.173 ** Dengue Deaths.173 ** **.063 * Malaria.125 **.061 * **.042 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). Dengue, dengue deaths and malaria cases are associated with the minimum temperature of the area. As the Minimum temperature increases, the Dengue, dengue deaths and malaria cases also increases. Dengue is positively related to amount of rainfall, i.e. as rainfall increases, dengue and dengue deaths also increases. However malaria has a different direction. As the rainfall increases the malaria cases decreases. For the relative humidity, only dengue is related. As humidity increases, dengue and dengue deaths also increase.
15 Dengue Cases and Minimum Temperature, 2015 Positive association of dengue with minimum temperature p = ** p =.173 ** Dengue Cases Min Temp
16 Dengue Cases and Rainfall, 2015 Dengue Cases are positively associated with amount of rainfall p = ** p = ** Dengue Cases Rainfall
17 Dengue and Relative Humidity, 2015 Dengue Cases are positively associated with relative humidity p = ** p = * Dengue Cases Humidity
18 Malaria is positively associated with temperature and negatively associated with rainfall Malaria, Temperature and Rainfall, Malaria Cases Rainfall Min Temp
19 Stationarity time series Augmented Dickey Fuller Some series are detected to be non-stationary. Minimum Temperature in Regions 1, 2, 3, CAR and ARMM; Malaria cases in Region 13 and Humidity in Region 10. This means that these series are not constant over time and there is a presence of seasonality. Seasonality and trend means that there are common months that dengue cases are high and some months have the small number of cases.
20 Granger Causality A test to check if certain factors may be used to predict number of cases For dengue: Minimum temperature contains information that can predict the number of Dengue cases (in most regions, except 8 and ARMM) Rainfall (3, 4a, 4b, 7, 9, NCR) Humidity (11 only) For malaria: min. temp. and rainfall can predict cases of Malaria in Region 4b only
21 Acknowledgments Asia Pacific Network for Global Change Research (APN) Department of Health (DOH) Philippine Atmospheric, Geophysical, and Astronomical Services Administration (PAGASA) University of Santo Tomas (UST)
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