Jia, Z., Jia, X., Liu, Y., Dye, C., Chen, F., Chen, C….Liu, H. (2008). Spatial Analysis of Tuberculosis Cases in Migrants and Permanent Residents, Beijing, 2000–2006. Emerging Infectious Diseases, 14(9), 1413-1419.
Tuberculosis (TB) is an infectious disease that most often affects the lungs, spreading through the air. The incidence of TB had been controlled to 7 cases per 100,000 population in Beijing during the last 90 years but remerged in the early 2000s. Previous studies had indicated that the reemergence of TB was correlated with the increasing migrants. Big data of the TB cases obtained from the Beijing Institute of Tuberculosis Control also showed that an increasing trend of the prevalence rate in TB in Beijing in the early 2000s is following the increasing migrant population. However, due to the limitation of the techniques, few previous studies displayed the spatial distribution of TB. Hence, based on previous studies and data, the authors made an argument that the migrant population contributed to the prevalence of TB in Beijing. The purpose of the study was to present the hotspots distribution of TB for both permanent and migrant residents at the district level and examined the impact of the migrant population on the reemergence and transmission of TB in Beijing.
The study site covers 18 districts of Beijing, around in total 16800 square kilometers surface area. Data for the study included all TB cases reported during 2000-2006 sourced from the Beijing Institute of Tuberculosis Control, and the demographic data of permanent residents and migrant population for each district in Beijing from 2000-2006 census, provided by Being Municipal Public Security Bureau.
A GIS-based spatial analysis was used to indicate the spatial distribution of TB and highlighted the hot spot areas. Global Morans’I statistics is to discern the spatial autocorrelation of TB cases, and Getis’s Gi statistics is to find out the TB hot spots. Both Morans’I and Getis’s Gi specified 10 km as the threshold of distance. Then, a couple of 2-level poison regression models were used to detect the difference of prevalence of TB among 18 districts and the origins of the population.
Results indicated that the hot spots among the prevalence rate of migrant population persisted in four central urban districts from 2000 through 2006. However, for permanent residents, there was only one hot spot detected in 2003. The results implied that the migrant population in Beijing dominated the prevalence of TB. Besides, the Poisson regression models showed there was a significant difference in TB prevalence at the district level, which was associated with the origin of the cases. Migrants from the western zones of China had the highest prevalence rate, compared to migrants from any other zones.
Overall, the study successfully exhibited the spatial distribution and hotspots of TB prevalence for both permanent residents and migrant population, which helps make TB control strategies. However, due to global Moran’s I statistics, the study failed to display the trend of TB prevalence in a smaller census unit. Though regression models show the origin of migrants contributed to the difference of TB prevalence rate at the district level, the models did not give details on how the migrants from different zones impacted on the prevalence rate for each district. Also, the study divided the population into permanents and migrants but ignored the impact of interactions between each other. The limitations above could be improved by using a local geographically weighted regression rather than the global Moran’s I. In general, I would like to give the study a 6.5 score.