Spatial epidemiological techniques in cholera mapping and analysis towards a local scale predictive modelling

• Published in: IOP Conference Series: Earth and Environmental Science
• Main Author: Rasam A.R.A.; Ghazali R.; Noor A.M.M.; Mohd W.M.N.W.; Hamid J.R.A.; Bazlan M.J.; Ahmad N.
• Format: Conference paper
• Language: English
• Published: Institute of Physics Publishing 2014
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84902313074&doi=10.1088%2f1755-1315%2f18%2f1%2f012095&partnerID=40&md5=de770752c27502ac677c2d3358fde8ae

Cholera spatial epidemiology is the study of the spread and control of the disease spatial pattern and epidemics. Previous studies have shown that multi-factorial causation such as human behaviour, ecology and other infectious risk factors influence the disease outbreaks. Thus, understanding spatial pattern and possible interrelationship factors of the outbreaks are crucial to be explored an in-depth study. This study focuses on the integration of geographical information system (GIS) and epidemiological techniques in exploratory analyzing the cholera spatial pattern and distribution in the selected district of Sabah. Spatial Statistic and Pattern tools in ArcGIS and Microsoft Excel software were utilized to map and analyze the reported cholera cases and other data used. Meanwhile, cohort study in epidemiological technique was applied to investigate multiple outcomes of the disease exposure. The general spatial pattern of cholera was highly clustered showed the disease spread easily at a place or person to others especially 1500 meters from the infected person and locations. Although the cholera outbreaks in the districts are not critical, it could be endemic at the crowded areas, unhygienic environment, and close to contaminated water. It was also strongly believed that the coastal water of the study areas has possible relationship with the cholera transmission and phytoplankton bloom since the areas recorded higher cases. GIS demonstrates a vital spatial epidemiological technique in determining the distribution pattern and elucidating the hypotheses generating of the disease. The next research would be applying some advanced geo-analysis methods and other disease risk factors for producing a significant a local scale predictive risk model of the disease in Malaysia. © Published under licence by IOP Publishing Ltd.