Determining method for dengue epidemic threshold in Negeri Sembilan, Malaysia

Abstract

Introduction Dengue fever is an arthropod-borne viral disease that has become endemic in most tropical countries. In 2014, Malaysia reported 108 698 cases of dengue fever with 215 deaths which increased tremendously compared to 49 335 cases with 112 deaths in 2008 and 30 110 cases with 69 deaths in 2009. This study aimed to identify the best method in determining dengue outbreak threshold for Negeri Sembilan as it can help to send uniform messages to inform the general public and make the outbreak analysis comparable within and between countries. Methods Using retrospective Negeri Sembilan country dataset from 1st epid week of 2011 till the 52nd epid week of 2016. The data were split into two periods: 1) a 3-year historic period (2011–2013), used to calibrate and parameterise the model, and a 1-year evaluation period (2014); 2) a 2-year historic period (2014–2016), used to calibrate and parameterise the model, and a 1-year evaluation period (2016), used to test the model. E-dengue is a registration system for confirmed dengue cases dengue by Ministry of Health. Data included were details of cases, district locality, records on the outbreak and epidemiological week (Sunday to Saturday) captured using the Excel spreadsheet. Analysis method included endemic channel method, moving average or deviation bar chart and recent mean. Results Seremban as big district and facing with heavy dengue cases, all three methods (endemic curve, current mean and moving mean) showed promising results. Meanwhile comparing with small district of Port Dickson and Tampin with fewer dengue cases and outbreak recorded, the suitable method is by using endemic channel for epidemic threshold. Conclusions Simpler methods such as the endemic channel, recent mean and moving mean may be more appropriate in urban district. Whereas in rural or district with minimal dengue cases, Endemic Channel would be the most suitable method for epidemic threshold. However, both methods require a consistent updated graph threshold as time progress.