Rumaisa Kruba
Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala, Darussalam, Banda Aceh and 23111, Indonesia

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Spatial Estimation of Relative Risk for Dengue Fever in Aceh Province using Conditional Autoregressive Method Latifah Rahayu; Novi Reandy Sasmita; Wulan Farisa Adila; Zurnila Marli Kesuma; Rumaisa Kruba
Journal of Applied Data Sciences Vol 4, No 4: DECEMBER 2023
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v4i4.141

Abstract

Dengue Fever (DHF) is a dangerous infectious disease that can cause death in an infected person. DHF is a disease transmitted by the Aedes Aegypti mosquito. Dengue cases have been reported in 449 districts/cities spread across 34 provinces with deaths spread across 162 districts/cities in 31 provinces, one of which is in Aceh Province. However, there are districts and cities in Aceh Province with a large number of cases and population at risk, and there are also districts and cities with fewer cases and population at risk. As a result, the number of cases and population at risk of DHF varies. Therefore, it is important to do planning to see which districts and cities have a high chance of DHF. In this study, the type of data used is secondary data sourced from the Aceh Provincial Health Profile from 2016 to 2022. The approach used is the Bayesian Conditional Autoregressive (CAR) prior model Besag-York-Mollie (BYM). The results of this study showed that mortality in dengue cases in Aceh Province from 2016 to 2022 had the highest mortality values in 2016 and 2022. The results of estimating the relative risk of DHF cases using the Bayesian Conditional Autoregressive (CAR) approach of the Besag-York-Mollie (BYM) Model in Aceh Province fulfill all categories with their relative risk values. Some districts/cities have relative risk values. Some districts/cities have high relative risk values of DHF cases and low relative risk values of DHF cases. Sabang city had the highest relative risk value of 3.54 and Bener Meriah district had the lowest relative risk of 0.2.