Impact of climate change on dengue incidence in Singapore: time-series seasonal analysis

ABSTRACT

This study aimed to identify the meteorological factors that contribute to dengue epidemics. The monthly incidence of dengue was used as the outcome variable, while maximum temperature, humidity, precipitation, and sunshine hours were used as independent variables. The results showed a consistent increase in monthly dengue cases from 2013 to 2021, with seasonal patterns observed in stationary time-series data. The ARIMA (2, 1, 3) × seasonal (0, 1, 2)₁₂ model was used based on its lowest Akaike Information Criterion (AIC) values. The analysis revealed that a 1-unit increase in rainfall was positively correlated with a small 0.062-unit increase in dengue cases, whereas a 1-unit increase in humidity was negatively associated, leading to a substantial reduction of approximately 16.34 cases. This study highlights the importance of incorporating weather data into national dengue prevention programs to enhance public awareness and to promote recommended safety measures.

KEYWORDS:

• Climate change
• dengue cases
• time series seasonal analysis
• Singapore

Disclosure statement

No potential conflict of interest was reported by the author(s).

Availability of data and materials

The dataset used in this study is available at Dengue data from 1990 to 2021 at https://www.moh.gov.sg/ and Meteorological data were collected from at https://data.gov.sg/.

Supplemental data

Supplemental data for this article can be accessed online at https://doi.org/10.1080/09603123.2024.2337827.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.