Rabies Hotspot Detection Using Bipartite Network Modelling Approach
Abstract
Despite entering its fourth year, the rabies outbreak in the East Malaysian state of Sarawak has claimed another nine lives in 2020, culminating with a total of 31 laboratory-confirmed cases of human rabies as of 31st December 2020. One of the outbreak control challenges faced by the authorities within a previously rabies-free area, such as in the case of Sarawak, is the lack of information regarding possible starting sources, notably hotspot locations of the outbreak. Identification of potential high-risk areas for rabies infection is a sine qua non for effective disease interventions and control strategies. Motivated by this and in preparation for future similar incidents, this paper presented a preliminary study on rabies hotspot identification. The modelling approach adopted the bipartite network where the two disjoint sets of nodes are the Location node and Dog (Bite Cases) node. The formulation of the network followed closely the Bipartite Modeling Methodology Framework. Thorough model verification was done in an attempt to show that such problem domain can be modelled using the Bipartite Modeling approach.
References
Asamoah, J. K. K., Oduro, F. T., Bonyah, E., & Seidu, B. (2017). Modelling of rabies transmission dynamics using optimal control analysis. Journal of Applied Mathematics, 2017, 2451237
https://doi.org/10.1155/2017/2451237
Brookes, V. J., Dürr, S., & Ward, M. P. (2019). Rabies-induced behavioural changes are key to rabies persistence in dog populations: investigation using a network-based model. PLoS Neglected Tropical Diseases, 13(9), 1-19.
https://doi.org/10.1371/journal.pntd.0007739
Cao, Z., Feng, W., Wen, X., Zu, L., & Gao, J. (2020). Nontrivial periodic solution of a stochastic seasonal rabies epidemic model. Physica A: Statistical Mechanics and its Applications, 545, 123361.
https://doi.org/10.1016/j.physa.2019.123361
Chandler, C. M. (2017). Network modeling of infectious disease: transmission, control and prevention. University Honors Program Theses, 258
Craft, M. E., & Caillaud, D. (2011). Network models: an underutilized tool in wildlife epidemiology? Interdisciplinary Perspectives on Infectious Diseases, 2011, 676949
https://doi.org/10.1155/2011/676949
Dürr, S., & Ward, M. P. (2015). Development of a novel rabies simulation model for application in a non-endemic environment. PLoS Neglected Tropical Diseases, 9(6), e0003876.
https://doi.org/10.1371/journal.pntd.0003876
Huang, J., Ruan, S., Shu, Y., & Wu, X. (2019). Modeling the transmission dynamics of rabies for dog, Chinese Ferret Badger and human interactions in Zhejiang Province, China. Bulletin of Mathematical Biology, 81(4), 939-962.
https://doi.org/10.1007/s11538-018-00537-1
Hudson, E. G., Brookes, V. J., & Ward, M. P. (2017). Assessing the risk of a canine rabies incursion in Northern Australia. Frontiers in Veterinary Science, 4, 141.
https://doi.org/10.3389/fvets.2017.00141
Kok, W. C. (2018). A Computational Approach to Predict the Spread of Dengue (Master's thesis, Universiti Malaysia Sarawak, Samarahan, Malaysia). Retrieved from http://ir.unimas.my/id/eprint/24893
Kok, W. C., & Labadin, J. (2019). Validation of bipartite network model of dengue hotspot detection in Sarawak. Computational Science and Technology, 481, 335-345.
https://doi.org/10.1007/978-981-13-2622-6_33
Laager, M., Mbilo, C., Madaye, E. A., Naminou, A., Léchenne, M., Tschopp, A., Smieszek, T., Zinsstag, J., & Chitnis, N. (2018). The importance of dog population contact network structures in rabies transmission. PLoS Neglected Tropical Diseases, 12(8), e0006680.
https://doi.org/10.1371/journal.pntd.0006680
Liew, C. Y. (2016). Bipartite-network-based modeling of habitat suitability (Doctoral thesis, Universiti Malaysia Sarawak, Samarahan, Malaysia). Retrieved from http://ir.unimas.my/id/eprint/24874
Navanithakumar, B., Sohayati, A. R., Rohaiza, Y., Sarah, D. A., Mariani, H., Leonora, T. M., & Dorothy, K. S. (2019). An overview of rabies outbreaks in Malaysia, ordinances and laws. Malaysian Journal of Veterinary Research, 10(2), 148-158.
Pavlopoulos, G. A., Kontou, P. I., Pavlopoulou, A., Bouyioukos, C., Markou, E., & Bagos, P. G. (2018). Bipartite graphs in systems biology and medicine: a survey of methods and applications. GigaScience, 7(4), giy014.
https://doi.org/10.1093/gigascience/giy014
Pipatsart, N., Modchang, C., Triampo, W., & Amornsamankul, S. (2018). Network based model of infectious disease transmission in macroalgae. International Journal of Simulation-Systems, Science & Technology, 19(5).
Rayfield, B., Fortin, M. J., & Fall, A. (2011). Connectivity for conservation: a framework to classify network measures. Ecology, 92(4), 847-858.
https://doi.org/10.1890/09-2190.1
Siettos, C. I., & Russo, L. (2013). Mathematical modeling of infectious disease dynamics. Virulence, 4(4), 295-306.
https://doi.org/10.4161/viru.24041
Sparkes, J., McLeod, S., Ballard, G., Fleming, P. J., Körtner, G., & Brown, W. Y. (2016). Rabies disease dynamics in naive dog populations in Australia. Preventive Veterinary Medicine, 131, 127-136.
https://doi.org/10.1016/j.prevetmed.2016.07.015
State Disaster Management Committee (2020). "Rabies Info." Retrieved from https://infodisaster.sarawak.gov.my/
Taib, N. A. A., Labadin, J., & Piau, P. (2019). Model simulation for the spread of rabies in Sarawak, Malaysia. International Journal on Advanced Science, Engineering & Information Technology, 9(5), 1739-1745.
https://doi.org/10.18517/ijaseit.9.5.10230
Zhang, J., Jin, Z., Sun, G. Q., Sun, X. D., & Ruan, S. (2012). Modeling seasonal rabies epidemics in China. Bulletin of Mathematical Biology, 74(5), 1226-1251.
https://doi.org/10.1007/s11538-012-9720-6
Zhong, L., Zhang, Q., & Li, X. (2018). Modeling the intervention of HIV transmission across intertwined key populations. Scientific Reports, 8(1), 1-9.
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