Risk Factor and Cluster Analysis to Identify Malaria Hot Spot for Control Strategy in Samigaluh Sub-District, Kulon Progo, Indonesia

Background: In 2015, Indonesia government targeted to eliminate malaria in Java Island. Nevertheless, until now malaria still occurs, including in Samigaluh, Kulon Progo District although many malaria programs has been run. Complexity and dynamic of the population also limited budget may become the...

Full description

Saved in:
Bibliographic Details
Main Authors: Sulistyawati SULISTYAWATI (Author), Isnah FITRIANI (Author)
Format: Book
Published: Tehran University of Medical Sciences, 2019-09-01T00:00:00Z.
Subjects:
Online Access:Connect to this object online.
Tags: Add Tag
No Tags, Be the first to tag this record!

MARC

LEADER 00000 am a22000003u 4500
001 doaj_8083ccd526ce429ea863b1c735d95b57
042 |a dc 
100 1 0 |a Sulistyawati SULISTYAWATI  |e author 
700 1 0 |a Isnah FITRIANI  |e author 
245 0 0 |a Risk Factor and Cluster Analysis to Identify Malaria Hot Spot for Control Strategy in Samigaluh Sub-District, Kulon Progo, Indonesia 
260 |b Tehran University of Medical Sciences,   |c 2019-09-01T00:00:00Z. 
500 |a 10.18502/ijph.v48i9.3024 
500 |a 2251-6085 
500 |a 2251-6093 
520 |a Background: In 2015, Indonesia government targeted to eliminate malaria in Java Island. Nevertheless, until now malaria still occurs, including in Samigaluh, Kulon Progo District although many malaria programs has been run. Complexity and dynamic of the population also limited budget may become the reason of malaria combat difficulties. Subsequently, a method to direct the policymaker on how to provide program effectively and efficiently was needed.  We examined malaria risk factor using statistical and cluster analysis. Methods: A quantitative study with case-control approach was conducted during Spring 2017 in Samigaluh II Public Health Centre, Indonesia. The structured questioner was used to collect the information from both of case and control which were people who had blood examination regarding malaria diagnosed during January-December 2016. Global Positioning System was used to record the geographical position of house participant which was used in cluster analysis. Results: Occupation was recognized as the significant risk factor to malaria. One most likely cluster was detected and translated as the source of transmission because of its fall in malaria hotspot. Conclusion: Satscan be able to detect a spatial cluster of malaria case and a promising method for supporting malaria control. 
546 |a EN 
690 |a Malaria 
690 |a Risk factor 
690 |a Cluster analysis 
690 |a Indonesia 
690 |a Public aspects of medicine 
690 |a RA1-1270 
655 7 |a article  |2 local 
786 0 |n Iranian Journal of Public Health, Vol 48, Iss 9 (2019) 
787 0 |n https://ijph.tums.ac.ir/index.php/ijph/article/view/18251 
787 0 |n https://doaj.org/toc/2251-6085 
787 0 |n https://doaj.org/toc/2251-6093 
856 4 1 |u https://doaj.org/article/8083ccd526ce429ea863b1c735d95b57  |z Connect to this object online.