Modeling Dengue Virus Infection Patients for Each Severity of Dengue Disease in Thailand

Montip Tiensuwan, Timothy O'Brien

Research output: Contribution to journalArticlepeer-review

Abstract

Dengue is an infectious mosquito-borne viral disease. Dengue or dengue-like epidemics ranks highly among new and newly emerging infectious diseases in public health significance and may affect persons of all ages in dengue endemic area. Dengue virus infections may lead to dengue fever (DF), dengue haemorrhagic fever (DHF) and may lead to hypovolaemic shock (dengue shock syndrome, DSS) then we separate dengue data by severity of dengue disease, i.e., DF, DHF and DSS. The objective of this study is to find factors which affect the dengue virus infection patients for each severity of dengue disease in Thailand by using multiple regression models. Amongst the models fitted, the best are chosen based on the analysis of variance, F-test and t-test. The results of this study show that the factors are time, seasonal factors, and monthly multivariate ENSO index for dengue fever (DF) and dengue haemorrhagic fever (DHF) while the factors for dengue shock syndrome (DSS) are population in each month, seasonal factors, and monthly multivariate ENSO index.

Original languageAmerican English
JournalMathematics and Statistics: Faculty Publications and Other Works
Volume2013
Issue number1
StatePublished - Jan 1 2013

Keywords

  • dengue fever (DF)
  • dengue haemorrhagic fever (DHF)
  • dengue shock syndrome (DSS)
  • mosquito
  • multiple regression models

Disciplines

  • Mathematics

Cite this