The development of stochastic SIR-SI Age-Structured model for leptospirosis mapping in Malaysia
This study aimed to develop the stochastic SIR-SI Age-Structured model to estimate therelative risk for leptospirosis mapping specifically for children and adults in Malaysia.This study used model development as it research design. The methodology of this study took intoaccount the transmission of l...
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RC Internal medicine Aznida Che Awang The development of stochastic SIR-SI Age-Structured model for leptospirosis mapping in Malaysia |
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This study aimed to develop the stochastic SIR-SI Age-Structured model to estimate therelative risk for leptospirosis mapping specifically for children and adults in Malaysia.This study used model development as it research design. The methodology of this study took intoaccount the transmission of leptospirosis in the stochastic SIR-SI model (S=susceptible, I=infected, R=recovered for human populations and S=susceptible, I=infected for vector populations). In this study, the existing SIR-SI model was improvised andadapted to the leptospirosis transmission. Then, the model was expended to form an alternativeSIR-SI Age-Structured model specifically for children and adults to estimate the relative risk ofleptospirosis for these populations in Malaysia. The data used in this study were weekly data fromepidemiology week 1 to epidemiology week 52 for the year 2015 for all sixteen states in Malaysia.The results of the analysis based on the age structured model were also compared with the existingmodels to identify the better model for estimating relative risk. For the children group, theresults showed that children in Kelantan have the highest risk of contracting leptospirosiswhile the children in Labuan have the lowest risk of contracting the disease. Similarly, adultsin Kelantan and Labuan also possessed the highest and lowest risk of contractingleptospirosis, respectively. As a conclusion, the new model was better as compared to otherexisting models in estimating relative risk for leptospirosis because it consideredimportant elements such as the number of population, age group and the transmission process of thedisease. This model also generates leptospirosis risk map for children and adults inMalaysia. In implication, the proposed model and generated risk maps can be practically appliedtowards the control of leptospirosis by government agencies, medical officers and authorities aswell as increasing the awareness of local communities towards the high-lowrisk areas of leptospirosis. |
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Aznida Che Awang |
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Aznida Che Awang |
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Aznida Che Awang |
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The development of stochastic SIR-SI Age-Structured model for leptospirosis mapping in Malaysia |
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The development of stochastic SIR-SI Age-Structured model for leptospirosis mapping in Malaysia |
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The development of stochastic SIR-SI Age-Structured model for leptospirosis mapping in Malaysia |
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The development of stochastic SIR-SI Age-Structured model for leptospirosis mapping in Malaysia |
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The development of stochastic SIR-SI Age-Structured model for leptospirosis mapping in Malaysia |
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development of stochastic sir-si age-structured model for leptospirosis mapping in malaysia |
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Fakulti Sains dan Matematik |
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oai:ir.upsi.edu.my:57502021-04-05 The development of stochastic SIR-SI Age-Structured model for leptospirosis mapping in Malaysia 2018 Aznida Che Awang RC Internal medicine This study aimed to develop the stochastic SIR-SI Age-Structured model to estimate therelative risk for leptospirosis mapping specifically for children and adults in Malaysia.This study used model development as it research design. The methodology of this study took intoaccount the transmission of leptospirosis in the stochastic SIR-SI model (S=susceptible, I=infected, R=recovered for human populations and S=susceptible, I=infected for vector populations). In this study, the existing SIR-SI model was improvised andadapted to the leptospirosis transmission. Then, the model was expended to form an alternativeSIR-SI Age-Structured model specifically for children and adults to estimate the relative risk ofleptospirosis for these populations in Malaysia. The data used in this study were weekly data fromepidemiology week 1 to epidemiology week 52 for the year 2015 for all sixteen states in Malaysia.The results of the analysis based on the age structured model were also compared with the existingmodels to identify the better model for estimating relative risk. For the children group, theresults showed that children in Kelantan have the highest risk of contracting leptospirosiswhile the children in Labuan have the lowest risk of contracting the disease. Similarly, adultsin Kelantan and Labuan also possessed the highest and lowest risk of contractingleptospirosis, respectively. As a conclusion, the new model was better as compared to otherexisting models in estimating relative risk for leptospirosis because it consideredimportant elements such as the number of population, age group and the transmission process of thedisease. This model also generates leptospirosis risk map for children and adults inMalaysia. In implication, the proposed model and generated risk maps can be practically appliedtowards the control of leptospirosis by government agencies, medical officers and authorities aswell as increasing the awareness of local communities towards the high-lowrisk areas of leptospirosis. 2018 thesis https://ir.upsi.edu.my/detailsg.php?det=5750 https://ir.upsi.edu.my/detailsg.php?det=5750 text eng closedAccess Masters Universiti Pendidikan Sultan Idris Fakulti Sains dan Matematik Aznida Che Awang & Nor Azah Samat. (2017). Standardized Morbidity Ratio forLeptospirosis Mapping in Malaysia. In AIP Conference Proceedings (Vol. 2006, p. 20006).Assimina, Z. & Fotoula, B. (2008). Leptospirosis: Epidemiology and Preventive Measures.Health Science Journal. 2(2): 75-82Barreto, M. L. (2006). Infectious Diseases Epidemiology. Journal of Epidemiology & CommunityHealth, 60(3), 192195.Benacer, D., Kwai, L. T., Khebir Verasahib, Galloway, R. L., Hartskeerl, R. A., Lewis,J. W., & Siti Nursheena Mohd Zain. 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Evolution of the immune system in humansfrom infancy to old age. Proc Biol Sci, 282(1821), pii: 20143085.http://dx.doi.org/10.1098/rspb.2014.3085Siettos, C. I., & Russo, L. (2013). Mathematical modeling of infectious diseasedynamics. Virulence, 4(4), 295306.Triampo, W., Baowan, D., Tang, I. M., Nuttavut, N., & Doungchawee, G. (2006). A Simple Deterministic Model for the Spread of Leptospirosis in Thailand. InternationalJournal of Biological and Life Sciences, 2(1), 2226.Wahab, Z. A. (2015). Epidemiology and Current Situation of Leptospirosis in Malaysia.Persidangan Kesihatan Persekitaran Pihak Berkuasa Tempatan 2015. pp. 167.World Health Organization (2009). Informal Expert Consultation On Surveillance, Diagnosisand Risk Reduction of Leptospirosis, (September), 1718. Retrieved fromhttp://www.searo.who.int/entity/emerging_diseases/topics/Communicable_Diseases_Surveillance_and_response_SEA-CD-217.pdfWorld Health Organization. (2010). Report of the First Meeting of the Leptospirosis Burden Epidemiology Reference Group. Retrieved fromhttp://apps.who.int/iris/bitstream/10665/44382/1/9789241599894_eng.pdfWorld Health Organization. (2017). Infectious Disease. Retrieved fromhttp://www.who.int/topics/infectious_diseases/en/World Animal Health Information Database & Interface of the World Organization for Animal Health. (2014). Geographical Distribution. Retrieved fromhttp://www-old.caribvet.netZhao, J., Liao, J., Huang, X., Zhao, J., Wang, Y., Ren, J., Ding, F. (2016).Mapping risk of leptospirosis in China using environmental and socioeconomicdata. BMC Infectious Diseases, 16(1), 343. http://doi.org/10.1186/s12879-016-1653-5.APPENDIX A: KNOWLEDGE DISSEMINATIONA) Conference(1) Aznida Che Awang & Nor Azah Samat (2017), Standardized morbidity ratiofor leptospirosis mapping in Malaysia. 4?? International Postgraduate Conference onScience and Mathematics 2016, Universiti Pendidikan Sultan Idris, Oral Presentation Session.(2) Aznida Che Awang & Nor Azah Samat (2017), Leptospirosis Disease Mapping withStandardized Morbidity Ratio and Poisson-Gamma Model: An Analysis of Leptospirosis Disease inKelantan, Malaysia. 1?? International Conference on Applied & Industrial Mathematics 2017,Vistana Kuantan City Centre, Oral Presentation Session.B) Publication(1) Aznida Che Awang & Nor Azah Samat (2017). Standardized morbidity ratiofor leptospirosis mapping in Malaysia. In AIP Conference Proceedings (Vol. 2006, p. 20006).http://doi.org/10.1063/1.4983861(2) Aznida Che Awang & Nor Azah Samat (2017), Leptospirosis Disease Mapping withStandardized Morbidity Ratio and Poisson-Gamma Model: An Analysis of Leptospirosis Disease inKelantan, Malaysia. Journal if Physics:Conference Series, 2017(3) Nor Azah Samat & Aznida Che Awang (2018), The Discrete Time-SpaceSIR-SI Age-Structured Model for Leptospirosis. SCIEMATIC2018 |