Science in China Series C: Life Sciences 2006 Vol.49 No.6 573—582 573 DOI: 10.1007/s11427-006-2015-0 Remote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases GONG Peng 1, XU Bing 2 & LIANG Song 1、3 1. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications, Chi- nese Academy of Sciences and Beijing Normal University, Box 9718, Beijing 100101, China; 2. Department of Geography, University of Utah, Salt Lake City, UT 84112, USA; 3. School of Public Health, University of California, Berkeley, CA 94720, USA Correspondence should be addressed to Gong Peng (email: [email protected]) Received March 14, 2006; accepted June 29, 2006 Abstract Similar to species immigration or exotic species invasion, infectious disease transmis- sion is strengthened due to the globalization of human activities. Using schistosomiasis as an exam- ple, we propose a conceptual model simulating the spatio-temporal dynamics of infectious diseases. We base the model on the knowledge of the interrelationship among the source, media, and the hosts of the disease. With the endemics data of schistosomiasis in Xichang, China, we demonstrate that the conceptual model is feasible; we introduce how remote sensing and geographic information systems techniques can be used in support of spatio-temporal modeling; we compare the different effects caused to the entire population when selecting different groups of people for schistosomiasis control. Our work illustrates the importance of such a modeling tool in supporting spatial decisions. Our mod- eling method can be directly applied to such infectious diseases as the plague, lyme disease, and hemorrhagic fever with renal syndrome. The application of remote sensing and geographic informa- tion systems can shed light on the modeling of other infectious disease and invasive species studies. Keywords: spatio-temporal modeling, spatial connectivity, prevention and control of infectious diseases, biological invasion. 1 Introduction from Uganda, was found in New York in 1999, and had spread to over 44 states by 2002; in 2003 and Infectious disease dispersion is becoming more 2004, the West Nile virus had infected over 12000 rapid and more extensive due to economic globaliza- people, killing 350(http://www.cdc.gov/ncidod/dvbid/ tion. The impact of infectious diseases is often related westnile/). After battling schistosomiasis for many to the population of the entire world. Severe Acute years along the Yangtze River Basin, many counties in Respirotory Syndrome (SARS) rapidly spread over 30 China had the disease under control for some time. countries and regions during a period of less than half However, there have been recent resurgences in many a year from the beginning of 2003, leading to over counties. In 2004, seven counties that used to have 8000 infected people and over 700 deaths(http://www. schistosomiasis under control had resurgences of the cdc.gov/ncidod/sars/). The West Nile virus, originating disease. www.scichina.com www.springerlink.com 574 Science in China Series C: Life Sciences The factors that dominate the spreading mechanism miological data. Such data provide a basis for statisti- of a particular infectious disease are still unknown. For cal analysis. For example, with GIS one can explore example, though the direct reason of SARS dispersal the statistical relationship between infectious disease is due to human air travel, we have little understanding data and environmental data, and then map the risk of its origin, transmission channel, and media. How- level in the area of interest. Infection risk mapping is ever, many other diseases are being carried around usually based on environmental suitability analysis. spatially by trade and tourism, but do not spread in This is done by searching for the environment whose their new environment. Therefore, we would like to conditions meet the requirement of a particular infec- ask which diseases will be spread around the globe tious disease. There are four cases that can result from successfully via globalization. What are their origins, the comparison between suitability for and actual dis- destinations, and spreading channels? What is the like- tribution of a particular disease: first, the actual dis- lihood of survival and endemics of a pathogen under tribution is located in the suitable area; second, the new environment? disease is found in unsuitable areas; third, the suitable In order to answer those questions, we need to de- area does not have the actual disease. Though the first velop models that can predict the transmission of in- and second cases are the most reasonable ones, the fectious diseases. We need to understand the history third should not be considered incorrect. Only when and current endemic region of an infectious disease. the distribution area is classified as an unsuitable area, There are three stages in predicting the transmission of is the third case incorrect. More can be done with GIS. infectious diseases: (1) identification of the pathogen, For example, when examining the infection risk dis- its animal host, and its pathway of transmission among tribution of schistosomiasis, one can evaluate the spa- the hosts; (2) determining the spatial transmission pat- tial autocorrelation among different residential groups; tern of each infectious disease, particularly the rela- such information is helpful in the spatial control of the tionship between the distribution of the disease and its disease transmission[2,3] environment; (3) understanding the dynamic process The third stage is based on the two previous stages. of the transmission of the disease, using models cali- The goal is to establish a quantitative process based brated with field survey data[1]. The epidemiological biological model. Such models can be calibrated with model thus established will have the capability to pre- field measurements and surveys. In general, these dict the dispersal of the virus, and its likelihood of models are limited to modeling the biological repro- transmission in new environment. However, each of duction cycle of a particular disease, and relevant these stages is difficult to complete. The work at stage hosts[4]. However, there are also studies that directly one is a diagnosis and initial exploration of the disease. model the dynamics between the environment and the For a new virus, there is the possibility of important transmission vector. For example, the relationship be- new discoveries. tween the climate and mosquito populations can be The second stage involves the survey and quantita- modeled. Rogers and Randolph[1] found that the sur- tive description of the spatial and temporal pattern of an infectious disease, followed by an analysis of the face temperature is nonlinearly related to the mortality relationship of the disease with its environment. Geo- of Gambia TseTse Fly with a one-month time lag. graphic information systems (GIS), remote sensing, We are certain that the increase of spatial connec- and statistical methods are most suitable to deal with tivity and environmental change resulting from glob- the problems at this stage. Remotely sensed data pro- alization are two dominant reasons for the intensifica- vide us with information about the land cover, surface tion of the spread of infectious diseases. Similar to temperature, soil moisture, and vegetation growth. invasive species, there exists a positive feedback be- Such information is very useful in indirectly predicting tween the intensification of infectious diseases and the abundance of virus transmission vectors, including environmental change (Fig. 1). GIS and remote sens- mosquitoes, ticks, mice and snails. GIS provides a ing are important tools for the study of spatial connec- spatial database containing environmental and epide- tivity and environmental change, respectively. Remote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases 575 Human activity Change of ecological Exotic species invasion properties Climate change (newly intro. disease) (health system) Increase bio. invasion (Increase chance Change of land use Land management (Environmental change) (Change living style) of new disease) Fig. 1. The relationship between the invasion of exotic species and environmental change. Human activities cause the migration of species, changes in ecological properties, and climate changes (mainly through modification of atmospheric constituents). Climate change and species migration may alter the ecological condition of a new area. Faced with changes in ecological conditions, humans may alter their land use and land management in order to protect themselves. Any of these behaviors would cause new invasions. This positive feedback model equally suits the introduction and dis- persion of infectious diseases. It is worth mentioning that the three stages of study no historically reported schistosomiasis infection, have are usually independently undertaken. It is particularly become endemic areas. How and where new snail true for the second and third stages. This has largely habitats will emerge according to recent environ- limited the understanding of the impact of the envi- mental changes have increasingly attracted research ronment on the transmission of infectious diseases. attention. Such a limitation further hampers disease control and Our model is obtained by adding a spatial connec- prevention. In this paper, we use