title: Identification of the prediction model for dengue incidence in Can Tho city, a Mekong Delta area in Vietnam.
abstract: The Mekong Delta is highly vulnerable to climate change and a dengue endemic area in Vietnam. This study aims to examine the association between climate factors and dengue incidence and to identify the best climate prediction model for dengue incidence in Can Tho city, the Mekong Delta area in Vietnam. We used three different regression models comprising: standard multiple regression model (SMR), seasonal autoregressive integrated moving average model (SARIMA), and Poisson distributed lag model (PDLM) to examine the association between climate factors and dengue incidence over the period 2003-2010. We validated the models by forecasting dengue cases for the period of January-December, 2011 using the mean absolute percentage error (MAPE). Receiver operating characteristics curves were used to analyze the sensitivity of the forecast of a dengue outbreak. The results indicate that temperature and relative humidity are significantly associated with changes in dengue incidence consistently across the model methods used, but not cumulative rainfall. The Poisson distributed lag model (PDLM) performs the best prediction of dengue incidence for a 6, 9, and 12-month period and diagnosis of an outbreak however the SARIMA model performs a better prediction of dengue incidence for a 3-month period. The simple or standard multiple regression performed highly imprecise prediction of dengue incidence. We recommend a follow-up study to validate the model on a larger scale in the Mekong Delta region and to analyze the possibility of incorporating a climate-based dengue early warning method into the national dengue surveillance system.
authors.affiliation: Centre for Environment and Population Health (CEPH), Griffith University, Brisbane, QLD, Australia; Health Environment Management Agency, Ministry of Health, Hà Nội, Vietnam. Electronic address: d.phung@griffith.edu.au.
authors.forename: Dung
authors.initials: D
authors.lastname: Phung
authors.affiliation: Centre for Environment and Population Health (CEPH), Griffith University, Brisbane, QLD, Australia.
authors.forename: Cunrui
authors.initials: C
authors.lastname: Huang
authors.affiliation: Centre for Environment and Population Health (CEPH), Griffith University, Brisbane, QLD, Australia.
authors.forename: Shannon
authors.initials: S
authors.lastname: Rutherford
authors.affiliation: Centre for Environment and Population Health (CEPH), Griffith University, Brisbane, QLD, Australia.
authors.forename: Cordia
authors.initials: C
authors.lastname: Chu
authors.affiliation: Commonwealth Scientific and Industrial Research Organisation (CSIRO), Clayton South, VIC, Australia.
authors.forename: Xiaoming
authors.initials: X
authors.lastname: Wang
authors.affiliation: Commonwealth Scientific and Industrial Research Organisation (CSIRO), Clayton South, VIC, Australia.
authors.forename: Minh
authors.initials: M
authors.lastname: Nguyen
authors.affiliation: Health Environment Management Agency, Ministry of Health, Hà Nội, Vietnam.
authors.forename: Nga Huy
authors.initials: NH
authors.lastname: Nguyen
authors.affiliation: Health Environment Management Agency, Ministry of Health, Hà Nội, Vietnam.
authors.forename: Cuong Do
authors.initials: CD
authors.lastname: Manh
mesh_terms: D002947:Cities; D002980:Climate; D057231:Climate Change; D003715:Dengue / Q000453:epidemiology*; D004196:Disease Outbreaks; D006801:Humans; D006813:Humidity; D015994:Incidence; D015233:Models, Statistical; D016012:Poisson Distribution; D012372:ROC Curve; D013696:Temperature; D014744:Vietnam / Q000453:epidemiology
keywords: Dengue incidence; Dengue outbreak; Mekong Delta; Prediction model; Vietnam