Spatial and Temporal Clustering of Kawasaki Syndrome Cases

Division of Epidemiology, Graduate School of Public Health, San Diego State University, San Diego, CA, USA.
The Pediatric Infectious Disease Journal (Impact Factor: 3.14). 10/2008; 27(11):981-5. DOI: 10.1097/INF.0b013e31817acf4f
Source: PubMed

ABSTRACT The etiology of Kawasaki syndrome (KS) remains unknown despite 30 years of intensive search for an agent. Epidemiologic clues to a possible infectious etiology include the seasonal distribution of cases, the previous occurrence of epidemics, the clinical features of the syndrome that mimic other infectious rash/fever illnesses in children, the self-limited nature of the illness, and the peak age incidence in the toddler years.
We examined the epidemiology and spatial and temporal distribution of KS cases in San Diego County, California during the 6-year period from 1998 to 2003. Clustering in space and time was analyzed using geo-referenced data with the K-function, the local G-statistic, and Knox statistic.
A total of 318 patients were identified through active surveillance. The overall annual incidence was 21.7/100,000 in children <5 years, with rates in whites, white Hispanics, and Asian/Pacific Islanders of 15.3, 20.2, and 45.9/100,000, respectively. The Knox test showed significant clustering of cases within the space-time interval of 3 km and 3-5 days.
This is the first study of KS cases to use geo-referenced point pattern analysis to detect spatial and temporal clustering of KS cases. These data suggest that an infectious agent triggers the immunologic cascade of KS.

  • [Show abstract] [Hide abstract]
    ABSTRACT: This research presents both theoretical results regarding the nature of spatiotemporal clustering on a network, and applied outcomes from examining such clustering with regard to traffic incidents. The analysis considers fatal traffic incidents in eastern Fairfax County, Virginia and injury incidents in Franklin County, Ohio. The spatiotemporal analytical methods of Knox and subsequent researchers are reviewed. Specific methods for performing spatiotemporal analysis are outlined, with special attention given to the interpretation of the results for traffic incidents. An argument is made for conducting spatial and temporal cluster analyses independently, in addition to spatiotemporal cluster analysis, a comparative analysis of methods for testing for the significance of spatiotemporal clusters is presented, and suggestions for delineating critical parameters for the Knox statistic are provided.
    Computers Environment and Urban Systems 01/2013; 37:70–81. DOI:10.1016/j.compenvurbsys.2012.06.004 · 1.79 Impact Factor
  • Source
    The Open Pediatric Medicine Journal 06/2009; 3(1):38-44. DOI:10.2174/1874309900903010038
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Understanding global seasonal patterns of Kawasaki disease (KD) may provide insight into the etiology of this vasculitis that is now the most common cause of acquired heart disease in children in developed countries worldwide. Data from 1970-2012 from 25 countries distributed over the globe were analyzed for seasonality. The number of KD cases from each location was normalized to minimize the influence of greater numbers from certain locations. The presence of seasonal variation of KD at the individual locations was evaluated using three different tests: time series modeling, spectral analysis, and a Monte Carlo technique. A defined seasonal structure emerged demonstrating broad coherence in fluctuations in KD cases across the Northern Hemisphere extra-tropical latitudes. In the extra-tropical latitudes of the Northern Hemisphere, KD case numbers were highest in January through March and approximately 40% higher than in the months of lowest case numbers from August through October. Datasets were much sparser in the tropics and the Southern Hemisphere extra-tropics and statistical significance of the seasonality tests was weak, but suggested a maximum in May through June, with approximately 30% higher number of cases than in the least active months of February, March and October. The seasonal pattern in the Northern Hemisphere extra-tropics was consistent across the first and second halves of the sample period. Using the first global KD time series, analysis of sites located in the Northern Hemisphere extra-tropics revealed statistically significant and consistent seasonal fluctuations in KD case numbers with high numbers in winter and low numbers in late summer and fall. Neither the tropics nor the Southern Hemisphere extra-tropics registered a statistically significant aggregate seasonal cycle. These data suggest a seasonal exposure to a KD agent that operates over large geographic regions and is concentrated during winter months in the Northern Hemisphere extra-tropics.
    PLoS ONE 09/2013; 8(9):e74529. DOI:10.1371/journal.pone.0074529 · 3.53 Impact Factor


Available from