Distributive effects of pytoplankton and sea surface temperature on cholera epidemics using satellite remote sensing and geographical information system / Abdul Rauf Abdul Rasam

Cholera is a diarrhoeal disease caused by Vibrio cholerae (Vc), which occurs
naturally in coastal phytoplankton (Chl-a) related with sea surface temperature
(SST), shellfish and man. However, there are contradictory of previous findings and
local perspective regarding the spatio-temporal effect of Chl-a and SST on cholera
epidemics. This study is to investigate the distributive effects of Chl-a and SST
variables on the epidemics in the district of Tawau using geographical information
system (GIS), satellite remote sensing and epidemiological techniques. The
techniques are integrated to analyze the effects qualitatively and quantitively. GIS
and Excel statistics were used to examine the spatio-temporal pattern of cholera
distribution in the district. ArcGIS spatial statistics, Pearson's correlation coefficient,
scatter diagram, MODIS remote sensing image, SST data, and cohort study were
used to determine the effect of these environmental variables on the epidemics.
Evaluation process was conducted using clinical analysis and public health practice
which involved selected health authorities from State Health Department (JKN)
Sabah, Institute for Medical Research (IMR) Malaysia, and Ministry of Health,
Malaysia (MOH). The key findings showed the effect of Chl-a (r=-0.33267) and SST
(r=0.09506) distribution on cholera epidemics in the district are only minimum
correlation from 2004 to 2008. The disease could outbreak at anywhere and anytime
particularly at high population, unhygienic environment, and close to contaminated
water supply especially during the hot and the wet season. The results of evaluation
process were also consistent founded in this study. The result not only answer the
previous contradict findings and local perspectives on the correlation, but also
provides an interesting dimension and new interpretation about constructing
appropriate spatial frameworks and predictive model of cholera in the district. This
study demonstrates that the environmental factors derived from public domain
remote sensing data and GIS technologies could be used as a cholera risk indicator,
and cholera control plan in Tawau. As this is the first study initiated in Malaysia
using the limited scope, several recommendations are made to enhance the analysis
used in order to achieve more significant result.