Hot-spot and cluster analysis on legal and illegal dumping sites as the contributors of leptospirosis in a flood hazard area in Pahang, Malaysia

Background: Leptospirosis is one of the zoonotic diseases which pose major public health issues worldwide. The spread of leptospirosis depends on the climate conditions as well as environmental conditions. Methods: The cases of leptospirosis were determined by using database obtained from Ministry of Health, Malaysia. Case cluster and hot spot analysis within Geographical Information System (GIS) were done using ArcGIS version 9.3. Level of significance was set at alpha= 0.05. Results: Most of the cases were at the centre Pahang located along the flood hazard stream. Cluster analysis indicated that cases were mostly clustered near illegal and legal dumping sites. The outliers were Jerantut, Maran, Pekan, and Rompin in both maps (p<0.05). The hot spot analysis obtained an obvious trend in the legal dumping compared to the illegal dumping. The hot spot area was found in the middle of Pahang such as in Jerantut, Temerloh, Maran, Pekan, and Rompin. Conclusions Increasing flood risk, poor sanitation and abundance of rats are conditions that trigger leptospirosis outbreaks. Interventions are therefore needed, targeting at environmental sources of transmission namely open legal and illegal dumping sites as well as flooding in flood hazard areas. A refined waste management system is needed to control the spread of the disease

Comparative Study of Association Rules Mining

Association rule mining is a technique to finduseful patterns and associations in transactionaldatabases. The mining of association rules can bemapped into the problem of discovering large(frequent) itemsets where is a grouped of items whichappear in a sufficient number of transaction. Thediscovery of interesting association relationshipsamong huge amount of business transaction recordscan help in many business decision making process .There are many association rules mining algorithms.But this system is intended to make the comparativestudy of three association rules mining algorithmssuch as DHP algorithm, PHP algorithm and HybridApproach of Support-Ordered Tree and PHP basedon same dataset. Both DHP and PHP algorithm usehash base method and pruning method to reducedatabase size. DHP use direct hashing technique.PHP use perfect hashing technique. The two dataset,Kyar Nyo Pan Stationary Store and Orangeminimarket are used