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University of Lethbridge

A time series analysis of trending dengue cases in Sri Lanka.

Abstract

The study aimed to predict dengue case numbers in Sri Lanka from January 2024 to December 2025. The prediction will assist the National Dengue Control Unit of Sri Lanka in assessing the potential dengue case numbers before a seasonal dengue crisis. This allows the Ministry of Health of Sri Lanka to plan effective healthcare mobilization and manage its resources during dengue seasons. Secondary data on all island dengue cases was obtained from the National Dengue Control Unit's national surveillance system from 2015 to 2023. A seasonal ARIMA(0,1,1)(0,0,2)[12] model was generated in R software by the forecast package’s time series function based on the Box-Jenkins method. The ARIMA model was validated as a good fit for prediction with the Ljung-Box (p-value >0.05), Shapiro-Wilk (p-value >0.05), and ADF (p-value <0.05) tests. The prediction’s MAPE was estimated as accurate for forecasting (4.46). The seasonal ARIMA model demonstrated the ability to make a short-term prediction in univariate analyses.

Author and committee

dc:creator, dc:contributor.*
Author
  • Kurukulasuriya Perera, Ruvani

Subjects

dc:subject × 4

Identifiers

dc:identifier.*
Identifier
hdl:10133/7026
OAI identifier oai:identifier
oai:opus.uleth.ca:10133/7026

Chain of custody

source
Harvested from
University of Lethbridge
Base URL
opus.uleth.ca/server/oai/request
Last updated
2026-07-27
Source record
OAI-PMH GetRecord
citation

Kurukulasuriya Perera, Ruvani. A time series analysis of trending dengue cases in Sri Lanka.. 2025.