Early dengue outbreak detection modeling based on dengue incidences in Singapore during 2012 to 2017

Abstract

Dengue has been as an endemic with year‐round presence in Singapore. In the recent years 2013, 2014, and 2016, there were several severe dengue outbreaks, posing serious threat to the public health. To proactively control and mitigate the disease spread, early warnings of dengue outbreaks, at which there are rapid and large‐scale spread of dengue incidences, are extremely helpful. In this study, a two‐step framework is proposed to predict dengue outbreaks and it is evaluated based on the dengue incidences in Singapore during 2012 to 2017. First, a generalized additive model (GAM) is trained based on the weekly dengue incidence data during 2006 to 2011. The proposed GAM is a one‐week‐ahead forecasting model, and it inherently accounts for the possible correlation among the historical incidence data, making the residuals approximately normally distributed. Then, an exponentially weighted moving average (EWMA) control chart is proposed to sequentially monitor the weekly residuals during 2012 to 2017. Our investigation shows that the proposed two‐step framework is able to give persistent signals at the early stage of the outbreaks in 2013, 2014, and 2016, which provides early alerts of outbreaks and wins time for the early interventions and the preparation of necessary public health resources. In addition, extensive simulations show that the proposed method is comparable to other potential outbreak detection methods and it is robust to the underlying data‐generating mechanisms.

Dengue Early Warning System as Outbreak Prediction Tool: A Systematic Review

“…Malaysia was the country with the most eligible studies (n=4), 27–30 followed by Thailand (n=2) 31 , 32 and Singapore (n=2). 33 , 34 Other studies were carried out in the Philippines, 35 Vietnam, 36 Taiwan, 37 China, 38 India, 39 Sri Lanka 40 and Colombia. 41 Two studies were conducted in Brazil, Dominican Republic, Mexico, Malaysia and Vietnam 42 and Brazil, Malaysia and Mexico.…”

“…All included studies relied on indicator-based surveillance (IBS). Two studies were case informed EWS, 29 , 34 which is early outbreak detection that relies entirely on the past case trends for outbreaks. Another 15 studies were categorized as alarm informed EWS that used at least one alarm indicator as the independent variable to predict outbreaks.…”

“… 42 , 43 The coverage of EWS varies from city level, 37 District, 28 , 29 , 40 , 43 province, 31 , 35 , 36 , 38 state 27 , 30 , 39 and national level. 33 , 34 , 41 , 42 In terms of data source, all dengue cases were obtained directly from the national surveillance system from the Ministry of Health. However, one study used the reports published by the Ministry of Health as a source of data.…”

“…The details of the modelling approach, main findings, limitations, and conclusion of each included study were presented in Supplementary Material Table S2 . Out of 17 studies, four used statistical analysis approaches such as the general additive mixed (GAM) model, 34 time-series regression 40 and Poisson regression models. 31 , 37 On the other hand, the ML approach was the most frequent approach applied in the included studies.…”

Exponentially weighed moving average charts for monitoring zero-inflated proportions with applications in health care

“…Even though the CUSUM chart is more popular in health-related applications, the EWMA control charts have also been occasionally used in public health surveillance, especially in detecting disease outbreaks. 10,30 The outline of the paper is the following. In Section 2, we provide in brief the properties of the BEZI distribution.…”