Regional transport and its association with tuberculosis in the Shandong province of China, 2009–2011
Introduction
There is compelling evidence that much of disease spread today is related to global movement of people, animals, and goods. It has also been observed that the most recent outbreak of Ebola and its intense transmission in West Africa are being monitored and tracked closely because there is real risk of new countries being affected (Gomes et al., 2014, Wesolowski et al., 2014). While migratory birds have contributed to the spread of avian influenza, it has been said that modern modes of transportation, especially air travel, are responsible for the unprecedented volume and speed of cross-border and cross-continental transmission of diseases in the 21st century.
Hagerstrand’s theory of diffusion (Ellegård and Svedin, 2012) is the basis for the formulation of many epidemic models. His time-geographic concepts link individuals in one or more places through movement in space and time. Diffusion of disease is examined by tracking where an infected individual has been and with whom the infected has been in contact. The outbreak of SARS in 2003 highlighted the importance of tracking a highly infectious index patient in Hong Kong that resulted in an acute outbreak almost went out of control. The 2009 Swine flu also painted a bleak picture of disease transmission and diffusion. But the tracking of individuals’ space–time movement is a daunting task (Kwan, 2000, Chen et al., 2011). Even with today’s technological advances in following people’s small-scale movements and activity space, scientists are baffled by the immense detail and volume of data and how to make sense of the placing and patterning of human activities.
Disease diffusion concerns the spread of a disease from its source to new locations and the pattern of diffusion is affected by barriers such as time, distance, physical, and cultural factors (Bossak and Welford, 2015). It is well documented that the farther away from the source of a disease, the more time it takes to feel the impact. This friction of distance is what geographers refer to as the distance decay effect. The likelihood of disease spread can be explained by the mechanisms of expansion and relocation (deBlij and Murphy, 2003). Expansion diffusion is said to occur when the number of infected individuals in an area grows continuously larger in space and time. Expansion can occur through an established structure, also known as hierarchical diffusion, or through a group of people or an area, also known as contagious diffusion (Cliff et al., 1981, Meade et al., 2000). Relocation is a sequential diffusion process whereby an infection is transmitted through movement of its carrier agents or a migrating population (Cliff and Haggett, 2004, Martens and Hall, 2000, Stoddard et al., 2009). The distance decay function in geographic profiling (the circle hypothesis and the distance decay theory) of disease investigation is highly influenced by human activities and environmental attributes. As the impact of human activities spread more widely through global transportation networks, disease can be transported via many different processes and pathways. However, the processes generally result in some degree of distance decay.
The fact that disease emergence decays with distance from population centers has been reported time and time again (Fotheringham and Rogerson, 1993, Xia et al., 2004). With new evidence highlighting that disease spread tended to occur faster along established transportation routes (such as major roads, waterways, and coastlines) (Kausrud et al., 2010, Wen et al., 2012), it is more certain that both environmental factors and population movements play important roles in disease transmission. Although the modeling of complex spatial interaction of disease phenomena is far from being perfect, understanding the role of disease spread along these networks and the travel patterns would allow for better identification of distance jumps or rate of disease infection. For example, Balcan et al. (2009) found that the effect of short-range commuting flows was larger than that of long-range airline flows and that the epidemic behavior would be different due to multiscale mobility processes in the disease dynamics. The ability to estimate how fast or broad an infection would spread under different conditions could help public health officials refine disease control or intervention measures.
Section snippets
Tuberculosis
Mycobacterium tuberculosis (TB) is a highly contagious bacterium that spreads from person to person via aerosols (Dye, 2006, Jones-López et al., 2013). The worldwide spread of TB has been a continuous threat to public health globally with almost one third of the world’s population infected (Dye, 2006). The World Health Organization (WHO, 2012) estimated that the world had over 8.7 million new TB infection and 1 million TB-related deaths in 2012.
The transmission of TB is highly complex and
Data and methods
This was a retrospective study to test the null hypothesis of no association between TB clusters and transport networks differentiated into two separate regions of low and high elevation. We postulated that TB cases are spatially related to transport networks whereby well-connected roads facilitate peoples’ movements. We also postulated that provincial roads in zones of low altitude had a higher association with people movement because of their greater accessibility to travelers.
Exploring spatial patterns of TB cases
The K-function analysis (Fig. 2a) showed that the overall patterns of TB cases varied from clustered to dispersed with changing distance scales from 0 to 16 km. This result indicated that TB cases were spatially heterogeneous with significant clustering (confidence intervals CI: 99.9%) at a scale of around 7 km but became increasingly dispersed thereafter. The highest level of TB clustering occurred at about 4–5 km.
Based upon results of the K-function analysis (Fig. 2a), we modified the local K
Discussion
Public transports have been observed to associate with TB transmission (CDC, 1995, Kenyon et al., 1996). Compared with air transports, passengers had nearly twice the risk of being infected when exposed to infectious passengers in mass public transports (Mohr et al., 2012). The current study is one of only few studies on the quantitative estimates of the risk of TB transmission by local and regional transport infrastructures. The results indicated that human mobility could have contributed to
Conclusion
It is crucial for public health administrators to develop an understanding of people movement, especially in areas infected with TB but with limited access to healthcare facilities, so that they can plan for appropriate measures to carry out adaptive prevention measures. This study highlights important associations between TB and human mobility in two regions of different altitudinal variation. In the low altitude region, national roads and provincial roads might have facilitated regional and
Ethical approval
Ethical approval (No: 2011LINSHEN8) for GIS-based study was obtained from the Institutional Review Board (IRB) of the Shandong Chest Hospital (NIH IRB00006010). The authors declare they have no actual or potential competing financial interests.
Acknowledgement
This study was supported by the earmarked grant CUHK 14411614 of the Hong Kong Research Grants Council. We would like to thank participating laboratories in the county/district tuberculosis dispensaries, which collected and provided samples to the Shandong Chest Hospital for further analysis.
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