title: Hydroclimatological variability and dengue transmission in Dhaka, Bangladesh: a time-series study.
abstract: BACKGROUND
  While floods can potentially increase the transmission of dengue, only few studies have reported the association of dengue epidemics with flooding. We estimated the effects of river levels and rainfall on the hospital admissions for dengue fever at 11 major hospitals in Dhaka, Bangladesh.
  
  
  METHODS
  We examined time-series of the number of hospital admissions of dengue fever in relation to river levels from 2005 to 2009 using generalized linear Poisson regression models adjusting for seasonal, between-year variation, public holidays and temperature.
  
  
  RESULTS
  There was strong evidence for an increase in dengue fever at high river levels. Hospitalisations increased by 6.9% (95% CI: 3.2, 10.7) for each 0.1 metre increase above a threshold (3.9 metres) for the average river level over lags of 0-5 weeks. Conversely, the number of hospitalisations increased by 29.6% (95% CI: 19.8, 40.2) for a 0.1 metre decrease below the same threshold of the average river level over lags of 0-19 weeks.
  
  
  CONCLUSIONS
  Our findings provide evidence that factors associated with both high and low river levels increase the hospitalisations of dengue fever cases in Dhaka.
authors.affiliation: Institute of Tropical Medicine (NEKKEN) and the Global Center of Excellence program, Nagasaki University, 1-12-4 Sakamoto, Nagasaki, Japan. hashizum@nagasaki-u.ac.jp
authors.forename: Masahiro
authors.initials: M
authors.lastname: Hashizume
authors.forename: Ashraf M
authors.initials: AM
authors.lastname: Dewan
authors.forename: Toshihiko
authors.initials: T
authors.lastname: Sunahara
authors.forename: M Ziaur
authors.initials: MZ
authors.lastname: Rahman
authors.forename: Taro
authors.initials: T
authors.lastname: Yamamoto
mesh_terms: D001459:Bangladesh / Q000453:epidemiology; D003715:Dengue / Q000453:epidemiology* / Q000635:transmission*; D055868:Floods; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D011891:Rain; D014887:Weather