Geographic prediction of tuberculosis clusters in Fukuoka, Japan, using the space-time scan statistic.
BACKGROUND
Tuberculosis (TB) has reemerged as a global public health epidemic in recent years. Although evaluating local disease clusters leads to effective prevention and control of TB, there are few, if any, spatiotemporal comparisons for epidemic diseases.


METHODS
TB cases among residents in Fukuoka Prefecture between 1999 and 2004 (n = 9,119) were geocoded at the census tract level (n = 109) based on residence at the time of diagnosis. The spatial and space-time scan statistics were then used to identify clusters of census tracts with elevated proportions of TB cases.


RESULTS
In the purely spatial analyses, the most likely clusters were in the Chikuho coal mining area (in 1999, 2002, 2003, 2004), the Kita-Kyushu industrial area (in 2000), and the Fukuoka urban area (in 2001). In the space-time analysis, the most likely cluster was the Kita-Kyushu industrial area (in 2000). The north part of Fukuoka Prefecture was the most likely to have a cluster with a significantly high occurrence of TB.


CONCLUSIONS
The spatial and space-time scan statistics are effective ways of describing circular disease clusters. Since, in reality, infectious diseases might form other cluster types, the effectiveness of the method may be limited under actual practice. The sophistication of the analytical methodology, however, is a topic for future study.
Onozuka
Daisuke
D
Department of Information Science, Fukuoka Institute of Health and Environmental Sciences, 39 Mukaizano, Dazaifu, Fukuoka 818-0135, Japan. onozuka@fihes.pref.fukuoka.jp
Hagihara
Akihito
A
D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D016000:Cluster Analysis; D005260:Female; D040362:Geographic Information Systems; D006801:Humans; D007564:Japan / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011159:Population Surveillance; D011237:Predictive Value of Tests; D015995:Prevalence; D012680:Sensitivity and Specificity; D017678:Sex Distribution; D013029:Space-Time Clustering; D016019:Survival Analysis; D014397:Tuberculosis, Pulmonary / Q000175:diagnosis* / Q000453:epidemiology*