Space-time analysis of hospitalised dengue patients in rural Thailand reveals important temporal intervals in the pattern of dengue virus transmission.
OBJECTIVE
To determine the temporal intervals at which spatial clustering of dengue hospitalisations occurs.


METHODS
Space-time analysis of 262 people hospitalised and serologically confirmed with dengue virus infections in Kamphaeng Phet, Thailand was performed. The cases were observed between 1 January 2009 and 6 May 2011. Spatial coordinates of each patient's home were captured using the Global Positioning System. A novel method based on the Knox test was used to determine the temporal intervals between cases at which spatial clustering occurred. These intervals are indicative of the length of time between successive illnesses in the chain of dengue virus transmission.


RESULTS
The strongest spatial clustering occurred at the 15-17-day interval. There was also significant spatial clustering over short intervals (2-5 days). The highest excess risk was observed within 200 m of a previous hospitalised case and significantly elevated risk persisted within this distance for 32-34 days.


CONCLUSIONS
Fifteen to seventeen days are the most likely serial interval between successive dengue illnesses. This novel method relies only on passively detected, hospitalised case data with household locations and provides a useful tool for understanding region-specific and outbreak-specific dengue virus transmission dynamics.
Department of Geography, University at Buffalo, Buffalo, NY 14260, USA. geojared@buffalo.edu
Jared
J
Aldstadt
In-Kyu
IK
Yoon
Darunee
D
Tannitisupawong
Richard G
RG
Jarman
Stephen J
SJ
Thomas
Robert V
RV
Gibbons
Angkana
A
Uppapong
Sopon
S
Iamsirithaworn
Alan L
AL
Rothman
Thomas W
TW
Scott
Timothy
T
Endy
D000818:Animals; D009033:Culicidae / Q000821:virology; D003715:Dengue / Q000453:epidemiology* / Q000635:transmission*; D003716:Dengue Virus / Q000472:pathogenicity*; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D007303:Insect Vectors / Q000821:virology; D012424:Rural Population / Q000706:statistics & numerical data*; D013029:Space-Time Clustering; D013785:Thailand / Q000453:epidemiology