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International Journal of Scientific and Research Publications

IJSRP, Volume 4, Issue 2, February 2014 Edition [ISSN 2250-3153]


A Simple Score to Predict Malaria Occurrence in Keerom, Papua: A Prospective Cohort Study Analyzed by Multivariate Logistic Regression
      Bernardus Sandjaja, Nur Nasry Noor, A Arsunan Arsin and Armyn Nurdin
Abstract: Keerom regency is the most prevalent malaria in Papua (17.7%). Malaria prevention addressed to the people who lived in Keerom. Hence, it is necessary to start preventing people before entering Keerom. This study aimed to develop a kind of device called scoring system that could be used as a primordial prevention. Methods: A prospective cohort prognostic study followed 606 subjects for three months to find out the malaria dominant risk factors. Prior to constructing a scoring system, bivariate analysis using chi square and multivariate logistic regressions were applied in this study. Results: Among 15 identified risk factors (namely sex, age, ethnic group, education, duration of stay at Keerom, nutritional status, socio economic status, forest activity, drug prevention, using insecticide, using insecticide treated nets, night time activity, animals around the house, the distant of breeding places and health centers from house), respectively, only 6 risk factors considered as dominant risk factors. The dominant risk factors are socio economic status (RR 1,430 95% CI 1,025- 1,995), night time activity (RR 1,624 95% CI 1,030-2,561), sex (RR 1,543 95% CI 1,116-2,133), forest activity (RR 0,587 95% CI 0,369-0,943), nutritional status (RR 1,405 95% CI 1,017-1,941) and duration of stay at Keerom (RR 2,519 95% CI 1,462-4,340), respectively. The scoring system was constructed based on dominant risk factors and could be used to predict malaria occurrence according to someone’s characteristics and conditions. Calibration and discrimination test showed that scoring system was a reliable tool (Hosmer Lemeshow test p = 0,337 and AUC 0,633 (95% CI 0,580-0,687)). However there were only 57% risk factors could be included in the system. Therefore it is necessary to take into a consideration to enhance the system by including others risk factors such as genetic and climate risk factors. Conclusion: The scoring system usually used in clinical setting, but it could be used in public

Reference this Research Paper (copy & paste below code):

Bernardus Sandjaja, Nur Nasry Noor, A Arsunan Arsin and Armyn Nurdin (2018); A Simple Score to Predict Malaria Occurrence in Keerom, Papua: A Prospective Cohort Study Analyzed by Multivariate Logistic Regression; Int J Sci Res Publ 4(2) (ISSN: 2250-3153). http://www.ijsrp.org/research-paper-0214.php?rp=P262350
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