Modelling recurrent malaria in Thailand
Malaria is a common infectious disease in many tropical countries. Thailand is located geographically in the tropical zone and the transmission of malaria is found widely, for instance, in the Tak province. The objective of this study is to find risk factors for the number of experiences with malari...
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th-mahidol.259492018-09-07T16:22:48Z Modelling recurrent malaria in Thailand M. Tiensuwan Mahidol University Health Professions Mathematics Medicine Malaria is a common infectious disease in many tropical countries. Thailand is located geographically in the tropical zone and the transmission of malaria is found widely, for instance, in the Tak province. The objective of this study is to find risk factors for the number of experiences with malaria of malaria patients, i.e. repeated recurrences of the disease within an infected individual in the Tak province in the rainy season by using Poisson regression models. Among the models fitted, the best are chosen based on the analysis of deviance. The results of this study show that the risk factors are race, spraying insecticides in houses in an infectious area, number of days staying overnight without protection against mosquitoes of malaria patients, and whether or not any members of the family of the malaria patient have had malaria. 2018-09-07T09:11:02Z 2018-09-07T09:11:02Z 2000-01-01 Review Statistical Methods in Medical Research. Vol.9, No.3 (2000), 249-258 10.1177/096228020000900305 09622802 2-s2.0-0033772382 https://repository.li.mahidol.ac.th/handle/123456789/25949 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=0033772382&origin=inward |
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Health Professions Mathematics Medicine M. Tiensuwan Modelling recurrent malaria in Thailand |
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Malaria is a common infectious disease in many tropical countries. Thailand is located geographically in the tropical zone and the transmission of malaria is found widely, for instance, in the Tak province. The objective of this study is to find risk factors for the number of experiences with malaria of malaria patients, i.e. repeated recurrences of the disease within an infected individual in the Tak province in the rainy season by using Poisson regression models. Among the models fitted, the best are chosen based on the analysis of deviance. The results of this study show that the risk factors are race, spraying insecticides in houses in an infectious area, number of days staying overnight without protection against mosquitoes of malaria patients, and whether or not any members of the family of the malaria patient have had malaria. |
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Mahidol University |
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Mahidol University M. Tiensuwan |
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Review |
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M. Tiensuwan |
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M. Tiensuwan |
title |
Modelling recurrent malaria in Thailand |
title_short |
Modelling recurrent malaria in Thailand |
title_full |
Modelling recurrent malaria in Thailand |
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Modelling recurrent malaria in Thailand |
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Modelling recurrent malaria in Thailand |
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modelling recurrent malaria in thailand |
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2018 |
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https://repository.li.mahidol.ac.th/handle/123456789/25949 |
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1763495845633720320 |