Author : Wahyu Ningsih, S.K.M.
Public Health Faculty, University of Indonesia
ABSTRACT
Malaria is still public health problem. Muaro Jambi District is one of district in Jambi Province which has endemic area of malaria. Malaria could be influence by other factors, including climate, population density, and altitude.
This study aims to find patterns of climate variations (temperature, humidity, and rainfall), population density and altitude in correlation and spatial relationship with positive malaria cases. This study is based on a mixture of ecology and which takes place in Muaro Jambi District, using secondary data of positive malaria cases and climate data in 2006-June 2010. Analysis by year, month, and sub-district the correlation and spatially which is supported with charts.
Based on correlation between temperature, humidity, rainfall and population density with positive malaria cases showed significant relationship on temperature and population density with r -0,136 and 0,393, respectively. Based on sub-district, significant relationship occurred in temperature and humidity: Maro Sebo Sub-District (r = -0,354) and Sungai Bahar Sub-District (r = -0,279) for temperature; and Sekernan Sub-District (r = 0,297), Kumpeh Ulu Sub-District (r = 0,381), Maro Sebo Sub-District (r = 0,531), and Mestong Sub-District (r = -0,273) for humidity. Significant relationship between population density with positive malaria cases by year was occurred in 2006 (r = 0,929).
Based on spatial analysis, variable of climate and altitude do not showed the appropriate relationship with the pattern of positive malaria meanwhile population density showed appropriate relationship with the pattern of positive malaria cases. Based on patterns of annual and monthly charts showed the same pattern of relationship between air humidity, rainfall and population density and temperature showed a different pattern of relations with the pattern of positive malaria cases.
Based on multivariate analysis showed temperature, humidity, and rainfall has influenced positive malaria cases about 2,4% and the most influential variable is temperature.
Key words :
Positive malaria, climate variations, population density, altitude, spatial analysis
