{"title":"Modelling Dengue Fever (DF) and Dengue Haemorrhagic Fever (DHF) Outbreak Using Poisson and Negative Binomial Model","authors":"W. Y. Wan Fairos, W. H. Wan Azaki, L. Mohamad Alias, Y. Bee Wah","volume":38,"journal":"International Journal of Biomedical and Biological Engineering","pagesStart":56,"pagesEnd":62,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/6765","abstract":"Dengue fever has become a major concern for health\r\nauthorities all over the world particularly in the tropical countries.\r\nThese countries, in particular are experiencing the most worrying\r\noutbreak of dengue fever (DF) and dengue haemorrhagic fever\r\n(DHF). The DF and DHF epidemics, thus, have become the main\r\ncauses of hospital admissions and deaths in Malaysia. This paper,\r\ntherefore, attempts to examine the environmental factors that may\r\ninfluence the recent dengue outbreak. The aim of this study is twofold,\r\nfirstly is to establish a statistical model to describe the\r\nrelationship between the number of dengue cases and a range of\r\nexplanatory variables and secondly, to identify the lag operator for\r\nexplanatory variables which affect the dengue incidence the most.\r\nThe explanatory variables involved include the level of cloud cover,\r\npercentage of relative humidity, amount of rainfall, maximum\r\ntemperature, minimum temperature and wind speed. The Poisson and\r\nNegative Binomial regression analyses were used in this study. The\r\nresults of the analyses on the 915 observations (daily data taken from\r\nJuly 2006 to Dec 2008), reveal that the climatic factors comprising of\r\ndaily temperature and wind speed were found to significantly\r\ninfluence the incidence of dengue fever after 2 and 3 weeks of their\r\noccurrences. 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