Abstract
Sin Nombre Virus (SNV) is a species of hantavirus that can cause hantavirus pulmonary syndrome in humans. To investigate the biodiversity effect on the SNV transmission in deer mouse, we formulated a stochastic agent-based model (ABM) to compare the impact between the presence of a dilution agent and an amplification agent in the deer mouse population. The ABM simulations were done in GAMA 1.8 and the results were then compared with the deterministic counterpart of the model. The deterministic results showed the dilution agent has better effectiveness in reducing the infected density compared to the amplification agent. However, this was not observed for the stochastic results with small populations. Instead, the infected densities were at a similar level for both dilution and amplification agent in the ABM results. This suggests that the investigation on the role of the community assemblage may not be relevant in reducing SNV transmission when the population density is small, and further research is needed to better understand the discrepancy between the stochastic and deterministic result and its implications. Our study highlights the importance of ABM in eco-epidemiological studies, and has established a methodological discussion regarding the usability of different simulation approaches e.g., deterministic and stochastic ABM in order to produce robust observations of eco-epidemiological phenomenon under consideration.
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Acknowledgements
The authors would like to thank the School of Mathematical Sciences and the Universiti Sains Malaysia (USM) for the support. Mohd Hafiz Mohd is supported by the USM Fundamental Research Grant Scheme (FRGS) No. 203/PMATHS/6711645.
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Lee, L.W.F., Mohd, M.H. (2021). Modelling the Dilution and Amplification Effects on Sin Nombre Virus (SNV) in Deer Mouse in GAMA 1.8. In: Mohd, M.H., Misro, M.Y., Ahmad, S., Nguyen Ngoc, D. (eds) Modelling, Simulation and Applications of Complex Systems. CoSMoS 2019. Springer Proceedings in Mathematics & Statistics, vol 359. Springer, Singapore. https://doi.org/10.1007/978-981-16-2629-6_3
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