Individual-based Modelling on Vector Heterogeneity of Leptospirosis Transmission in Sarawak

• Main Author: Jia Wen, Chong
• Format: Thesis
• Language: English; English
• Published: UNIMAS 2023
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://ir.unimas.my/id/eprint/41751/3/Master%20Thesis_Chong%20Jia%20Wen%20-%2024%20pages.pdf; http://ir.unimas.my/id/eprint/41751/4/Master%20Thesis_Chong%20Jia%20Wen_flltxt.pdf; http://ir.unimas.my/id/eprint/41751/

Leptospirosis is a zoonotic disease prevalent in various places, particularly the tropical and subtropical regions. The infectious disease is endemic across Malaysia, especially in Sarawak. In recent years, the threats of leptospirosis continue to grow as the number of confirmed cases in Sarawak has risen since 2010. Compartmental models are popular in disease modelling. However, the models are not suitable if heterogeneity in the population is taken into account. For zoonotic or vector-borne diseases, the heterogeneity of the hosts or vectors can significantly influence disease transmission. Hence, this research proposes an individual-based model or IBM to model the leptospirosis spread as it has the ability to capture the heterogeneity of the population, such as vectors’ active period and movement range. From the sensitivity analyses, the higher vector birth rate and higher transmission rate from susceptible to infected vectors generate more infected humans and vectors. The results also show that the active period durations of vectors do not influence leptospirosis transmission. However, a wider movement range of vectors causes more people and vectors to be infected. In the model validation with the actual prevalence data of leptospirosis in 2017, the coefficient of determination of more than 90% and normally distributed residuals for all three outbreaks indicate that IBM can model the leptospirosis spread in Sarawak. The actual prevalence data show three leptospirosis outbreaks occur within a year. By finding the correlation matrices, Pearson’s correlations deduce that temperature rise and precipitation influence disease transmission. Additionally, other factors such as misdiagnosis of leptospirosis as well as occupational and recreational exposures affect the infection.