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A multilevel study of dengue Epidemiology in Sri Lanka: modeling survival of dengue patients

International Journal of Mosquito Research · 2015 · Vol. 2(3) · pp. 114–121

Abstract

This paper focuses on exploring methods and analyzing the survival pattern of clustered dengue data reported from high risk areas in Sri Lanka during the period 2006 to 2009. Due to dengue cases being clustered within districts resulting in cluster correlation, the response of survival was modeled in a multilevel framework. As the data consists of several missing values this paper further investigates multilevel multiple imputation as a method to handle the partially observed dengue dataset appropriately. A Discrete Time Hazard Model via standard logistic model has been suggested to model the survival of dengue patients. Results indicate that there is an impact from the clustering variable, district and from different types of dengue infections, place treated initially, Packed Cell Volume and White Blood Cell count on the response of interest.

Statistical Methods and Bayesian InferenceHIV/AIDS Impact and ResponsesGlobal Maternal and Child HealthDengue feverSri lankaCluster (spacecraft)Logistic regressionProportional hazards modelCluster analysisEpidemiologyStatisticsHazard ratioSurvival analysis
Citations
3
FWCI
0.00
field-weighted impact
References
23
Percentile
20%
vs. same field & year
Citations per year
References
Statistical Analysis With Missing Data
Journal of the American Statistical Association · 1989 · 17,494 citations
Inference and missing data
Biometrika · 1976 · 9,558 citations
Working With Missing Values
Journal of Marriage and the Family · 2005 · 1,751 citations
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