Hostname: page-component-8448b6f56d-sxzjt Total loading time: 0 Render date: 2024-04-18T02:43:23.067Z Has data issue: false hasContentIssue false
  • English
  • Français

Application of GIS technology in public health: successes and challenges

Published online by Cambridge University Press:  02 February 2016

STEPHANIE M. FLETCHER-LARTEY Open the ORCID record for STEPHANIE M. FLETCHER-LARTEY [Opens in a new window]  and
GRAZIELLA CAPRARELLI
STEPHANIE M. FLETCHER-LARTEY*
Affiliation:
South Western Sydney Local Health District, Public Health Unit, PO Box 38, Liverpool, NSW 1871, Australia
GRAZIELLA CAPRARELLI
Affiliation:
Division of IT, Engineering and the Environment, University of South Australia, GPO Box 2471, Adelaide, SA 5001, Australia
*
*Corresponding author. South Western Sydney Local Health District, Public Health Unit, PO Box 38, Liverpool, NSW 1871, Australia. E-mail: stephanie.fletcher@sswahs.nsw.gov.au
Get access Rights & Permissions [Opens in a new window]

Summary

The uptake and acceptance of Geographic Information Systems (GIS) technology has increased since the early 1990s and public health applications are rapidly expanding. In this paper, we summarize the common uses of GIS technology in the public health sector, emphasizing applications related to mapping and understanding of parasitic diseases. We also present some of the success stories, and discuss the challenges that still prevent a full scope application of GIS technology in the public health context. Geographical analysis has allowed researchers to interlink health, population and environmental data, thus enabling them to evaluate and quantify relationships between health-related variables and environmental risk factors at different geographical scales. The ability to access, share and utilize satellite and remote-sensing data has made possible even wider understanding of disease processes and of their links to the environment, an important consideration in the study of parasitic diseases. For example, disease prevention and control strategies resulting from investigations conducted in a GIS environment have been applied in many areas, particularly in Africa. However, there remain several challenges to a more widespread use of GIS technology, such as: limited access to GIS infrastructure, inadequate technical and analytical skills, and uneven data availability. Opportunities exist for international collaboration to address these limitations through knowledge sharing and governance.

Keywords

Geographic information systemsinfectious diseasespublic healthparasitologyspatial analysis
Type
Review Article
Information
Parasitology , Volume 143 , Issue 4 , April 2016 , pp. 401 - 415
Check for updates
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Ali-Akbarpour, M., Mohammadbeigi, A., Tabatabaee, S. H. R. and Hatam, G. (2012). Spatial analysis of eco-environmental risk factors of cutaneous leishmaniasis in Southern Iran. Journal of Cutaneous and Aesthetic Surgery 5, 30.Google Scholar
Ault, S. K. (2007). Pan American Health Organization's Regional Strategic Framework for addressing neglected diseases in neglected populations in Latin America and the Caribbean. Memórias do Instituto Oswaldo Cruz 102, 99–107.Google Scholar
Bailey, T. C. (2001). Spatial statistical methods in health. Cadernos de Saúde Pública 17, 1083–1098.CrossRefGoogle ScholarPubMed
Baxter, P. and Jack, S. (2008). Qualitative case study methodology: study design and implementation for novice researchers. The Qualitative Report 13, 544–559.Google Scholar
Beale, L., Hodgson, S., Abellan, J. J., Lefevre, S. and Jarup, L. (2010). Evaluation of spatial relationships between health and the environment: the rapid inquiry facility. Environmental Health Perspectives 118, 1306.Google Scholar
Bergquist, N. (2002). Schistosomiasis: from risk assessment to control. Trends in Parasitology 18, 309–314.Google Scholar
Bergquist, R. and Rinaldi, L. (2010). Health research based on geospatial tools: a timely approach in a changing environment. Journal of Helminthology 84, 1–11.CrossRefGoogle Scholar
Blanton, J., Manangan, A., Manangan, J., Hanlon, C., Slate, D. and Rupprecht, C. (2006). Development of a GIS-based, real-time Internet mapping tool for rabies surveillance. International Journal of Health Geographics 5, 47. doi:10.1186/1476-072X-5-47.Google Scholar
Boulos, M. (2004). Towards evidence-based, GIS-driven national spatial health information infrastructure and surveillance services in the United Kingdom. International Journal of Health Geographics 3, 1.Google Scholar
Brooker, S. (2007). Spatial epidemiology of human schistosomiasis in Africa: risk models, transmission dynamics and control. Transactions of the Royal Society of Tropical Medicine and Hygiene 101, 1–8.Google Scholar
Brooker, S. (2010). Estimating the global distribution and disease burden of intestinal nematode infections: adding up the numbers – a review. International Journal for Parasitology 40, 1137–1144.Google Scholar
Brooker, S. and Clements, A. C. A. (2009). Spatial heterogeneity of parasite co-infection: determinants and geostatistical prediction at regional scales. International Journal for Parasitology 39, 591–597.Google Scholar
Brooker, S. and Utzinger, J. (2007). Integrated disease mapping in a polyparasitic world. Geospatial Health 1, 141–146.Google Scholar
Brooker, S., Rowlands, M., Haller, L., Savioli, L. and Bundy, D. (2000). Towards an atlas of human helminth infection in sub-Saharan Africa: the use of geographical information systems (GIS). Parasitology Today 16, 303–307.Google Scholar
Brooker, S., Hay, S. I. and Bundy, D. a. P. (2002). Tools from ecology: useful for evaluating infection risk models? Trends in Parasitology 18, 70–74.Google Scholar
Brooker, S., Kabatereine, N., Gyapong, J., Stothard, J. R. and Utzinger, J. (2009 a). Rapid mapping of schistosomiasis and other neglected tropical diseases in the context of integrated control programmes in Africa. Parasitology 136, 1707–1718.Google Scholar
Brooker, S., Kabatereine, N., Smith, J., Mupfasoni, D., Mwanje, M., Ndayishimiye, O., Lwambo, N., Mbotha, D., Karanja, P. and Mwandawiro, C. (2009 b). An updated atlas of human helminth infections: the example of East Africa. International Journal of Health Geographics 8, 1–11.Google Scholar
Brooker, S., Hotez, P. J. and Bundy, D. A. (2010). The global atlas of helminth infection: mapping the way forward in neglected tropical disease control. PLoS Neglected Tropical Diseases 4, e779.CrossRefGoogle ScholarPubMed
Caprarelli, G. and Fletcher, S. (2014). A brief review of spatial analysis concepts and tools used for mapping, containment and risk modelling of infectious diseases and other illnesses. Parasitology 141, 581–601.Google Scholar
Cecchi, G., Paone, M., Franco, J., Fevre, E., Diarra, A., Ruiz, J., Mattioli, R. C. and Simarro, P. P. (2009). Towards the Atlas of human African trypanosomiasis. International Journal of Health Geographics 8, 15. doi:10.1186/1476-072X-8-15.Google Scholar
Chan, L., Kirsop, B. and Arunachalam, S. (2005). Open Access Archiving: The Fast Track to Building Research Capacity in Developing Countries. Science and Development Network. http://www.scidev.net/global/communication/feature/open-access-archiving-the-fast-track-to-building-r.html Google Scholar
Chang, A., Parrales, M., Jimenez, J., Sobieszczyk, M., Hammer, S., Copenhaver, D. and Kulkarni, R. (2009). Combining Google Earth and GIS mapping technologies in a dengue surveillance system for developing countries. International Journal of Health Geographics 8, 49.CrossRefGoogle Scholar
Chapman, R. (2010). Government of PNG and United Nations Development Programme: Provincial Capacity Building Programme Phase II: Mid-Term Review. Australian Agency for International Development, Canberra, INH766.Google Scholar
Clarke, K. C., Mclafferty, S. L. and Tempalski, B. J. (1996). On epidemiology and geographic information systems: a review and discussion of future directions. Emerging Infectious Diseases 2, 85.CrossRefGoogle ScholarPubMed
Clements, A. C., Lwambo, N. J., Blair, L., Nyandindi, U., Kaatano, G., Kinung'hi, S., Webster, J. P., Fenwick, A. and Brooker, S. (2006 a). Bayesian spatial analysis and disease mapping: tools to enhance planning and implementation of a schistosomiasis control programme in Tanzania. Tropical Medicine and International Health 11, 490–503.Google Scholar
Clements, A. C., Moyeed, R. and Brooker, S. (2006 b). Bayesian geostatistical prediction of the intensity of infection with Schistosoma mansoni in East Africa. Parasitology 133, 711–719.CrossRefGoogle ScholarPubMed
Clements, A., Pfeiffe, R. D., Martin, V. and Otte, M. (2007). A Rift Valley fever atlas for Africa. Preventive Veterinary Medicine 82, 72–82.Google Scholar
Clements, A. C. A., Kur, L. W., Gatpan, G., Ngondi, J. M., Emerson, P. M., Lado, M., Sabasio, A. and Kolaczinski, J. H. (2010). Targeting Trachoma control through risk mapping: the example of Southern Sudan. PLoS Neglected Tropical Diseases 4, e799.CrossRefGoogle ScholarPubMed
Clements, A. C., Reid, H. L., Kelly, G. C. and Hay, S. I. (2013). Further shrinking the malaria map: how can geospatial science help to achieve malaria elimination? The Lancet Infectious Diseases 13, 709–718.Google Scholar
Conteh, L., Engels, T. and Molyneux, D. H. (2010). Socioeconomic aspects of neglected tropical diseases. The Lancet 375, 239–247.Google Scholar
Cross, E. R. and Bailey, R. C. (1984). Predicting areas endemic for schistosomiasis through use of discriminant analysis of environmental data. Military Medicine 149, 28–30.CrossRefGoogle ScholarPubMed
Cross, E. R., Perrine, R., Sheffield, C. and Pazzaglia, G. (1984). Predicting areas endemic for schistosomiasis using weather variables and a Landsat data base. Military Medicine 149, 542–543.CrossRefGoogle Scholar
Diggle, P., Thomson, M., Christensen, O., Rowlingson, B., Obsomer, V., Gardon, J., Wanji, S., Takougang, I., Enyong, P., Kamgno, J., Remme, J., Boussinesq, M. and Molyneux, D. (2007). Spatial modelling and the prediction of Loa loa risk: decision making under uncertainty. Annals of Tropical Medicine and Parasitology 101, 499–509.Google ScholarPubMed
Duncombe, J., Clements, A., Hu, W., Weinstein, P., Ritchie, S. and Espino, F. E. (2012). Geographical information systems for dengue surveillance. The American Journal of Tropical Medicine and Hygiene 86, 753–755.Google Scholar
Dunn, C. E., Atkins, P. J. and Townsend, J. G. (1997). GIS for development: a contradiction in terms? Area 29, 151–159.Google Scholar
Eade, D. (2007). Capacity building: who builds whose capacity? Development in Practice 17, 630–639.CrossRefGoogle Scholar
Eisen, L. and Lozano-Fuentes, S. (2009). Use of mapping and spatial and space-time modeling approaches in operational control of Aedes aegypti and dengue. PLoS Neglected Tropical Diseases 3, e411.CrossRefGoogle ScholarPubMed
Ekpo, U. F., Mafiana, C. F., Adeofun, C. O., Solarin, A. R. and Idowu, A. B. (2008). Geographical information system and predictive risk maps of urinary schistosomiasis in Ogun State, Nigeria. BMC Infectious Diseases 8, 74. doi:10.1186/1471-2334-8-74.Google Scholar
Estrada-Peña, A. (2007). A GIS framework for the assessment of tick impact on human health in a changing climate. Geospatial Health 1, 157–168.Google Scholar
Fisher, R. P. and Myers, B. A. (2011). Free and simple GIS as appropriate for health mapping in a low resource setting: a case study in eastern Indonesia. International Journal of Health Geographics 10, 15.Google Scholar
Fletcher, S., Caprarelli, G., Merif, J., Andresen, D., Van Hal, S., Stark, D. and Ellis, J. (2014). Epidemiology and geographical distribution of enteric protozoan infections in Sydney, Australia. Journal of Public Health Research 3:298, 83–91.CrossRefGoogle ScholarPubMed
Frost, C. and Thompson, S. G. (2000). Correcting for regression dilution bias: comparison of methods for a single predictor variable. Journal of the Royal Statistical Society: Series A (Statistics in Society) 163, 173–189.CrossRefGoogle Scholar
García-Rangel, S. and Pettorelli, N. (2013). Thinking spatially: the importance of geospatial techniques for carnivore conservation. Ecological Informatics 14, 84–89.Google Scholar
Global Incident Map. (2012). Outbreaks Global Incident Maps [Online]. http://www.globalincidentmap.com/ Google Scholar
Godfrey, M., Sophal, C., Kato, T., Vou Piseth, L., Dorina, P., Saravy, T., Savora, T. and Sovannarith, S. (2002). Technical assistance and capacity development in an aid-dependent economy: the experience of Cambodia. World Development 30, 355–373.Google Scholar
Gosoniu, L., Vounatsou, P., Sogoba, N. and Smith, T. (2006). Bayesian modelling of geostatistical malaria risk data. Geospatial Health 1, 127–139.Google Scholar
Graham, A. J., Atkinson, P. M. and Danson, F. M. (2004). Spatial analysis for epidemiology. Acta Tropica 91, 219–225.Google Scholar
Grillet, M.-E., Barrera, R., Martínez, J.-E., Berti, J. and Fortin, M.-J. (2010). Disentangling the effect of local and global spatial variation on a mosquito-borne infection in a neotropical heterogeneous environment. The American Journal of Tropical Medicine and Hygiene 82, 194–201.Google Scholar
Guo, J.-G., Penelope, V., Cao, C.-L., Jürg, U., Zhu, H.-Q., Daniel, A., Zhu, R., He, Z.-Y., Li, D., Hu, F., Chen, M.-G. and Marcel, T. (2005). A geographic information and remote sensing based model for prediction of Oncomelania hupensis habitats in the Poyang Lake area, China. Acta Tropica 96, 213–222.Google Scholar
Hay, S. and Snow, R. (2006). The malaria atlas project: developing global maps of malaria risk. PLoS Medicine 3, e473. doi:10.1371/journal.pmed.0030473.Google Scholar
Hay, S., Guerra, C., Gething, P., Patil, A., Tatem, A., Noor, A., Kabaria, C., Manh, B., Elyazar, I., Brooker, S., Smith, D., Moyeed, R. and Snow, R. (2009). A world malaria map: Plasmodium falciparum endemicity in 2007. PLoS Medicine 6, e1000048. doi:10.1371/ journal.pmed.1000048.Google Scholar
Hay, S. I., Battle, K. E., Pigott, D. M., Smith, D. L., Moyes, C. L., Bhatt, S., Brownstein, J. S., Collier, N., Myers, M. F. and George, D. B. (2013). Global mapping of infectious disease. Philosophical Transactions of the Royal Society of London B: Biological Sciences 368, 20120250.Google Scholar
Higgs, G. (2004). A literature review of the use of GIS-based measures of access to health care services. Health Services and Outcomes Research Methodology 5, 119–139.Google Scholar
Hooper, P. J., Chu, B. K., Mikhailov, A., Ottesen, E. A. and Bradley, M. (2014). Assessing progress in reducing the at-risk population after 13 years of the Global Programme to eliminate lymphatic filariasis. PLoS Neglected Tropical Diseases 8, e3333.Google Scholar
Hotez, P. J. and Pecoul, B. (2010). “Manifesto” for advancing the control and elimination of neglected tropical diseases. PLoS Neglected Tropical Diseases 4, e718.Google Scholar
Hsu, C.-Y., Fuad, A., Lazuardi, L. and Sanjaya, G. Y. (2012). GIS for dengue surveillance: strengthening collaborations. The American Journal of Tropical Medicine and Hygiene 87, 1152–1152.Google Scholar
Kaiser, R., Spiegel, P. B., Henderson, A. K. and Gerber, M. L. (2003). The application of geographic information systems and global positioning systems in humanitarian emergencies: lessons learned, programme implications and future research. Disasters 27, 127–140.Google Scholar
Kasasa, S., Asoala, V., Gosoniu, L., Anto, F., Adjuik, M., Tindana, C., Smith, T., Owusu-Agyei, S. and Vounatsou, P. (2013). Spatio-temporal malaria transmission patterns in Navrongo demographic surveillance site, northern Ghana. Malaria Journal 12, 63.Google Scholar
Keating, J., Macintyre, K., Mbogo, C., Githeko, A., Regens, J., Swalm, C., Ndenga, B., Steinberg, L., Kibe, L., Githure, J. and Beier, J. (2003). A geographic sampling strategy for studying relationships between human activity and malaria vectors in urban Africa. The American Journal of Tropical Medicine and Hygiene 68, 357–365.Google Scholar
Kelly, G. C., Hale, E., Donald, W., Batarii, W., Bugoro, H., Nausien, J., Smale, J., Palmer, K., Bobogare, A., Taleo, G., Vallely, A., Tanner, M., Vestergaard, L. S. and Clements, A. C. (2013). A high-resolution geospatial surveillance-response system for malaria elimination in Solomon Islands and Vanuatu. Malaria Journal 12.Google Scholar
Kimaro, H. and Nhampossa, J. (2007). The challenges of sustainability of health information systems in developing countries: comparative case studies of Mozambique and Tanzania. Journal of Health Informatics in Developing Countries 1, 1–10.Google Scholar
Lau, C. L., Won, K. Y., Becker, L., Magalhaes, R. J. S., Fuimaono, S., Melrose, W., Lammie, P. J. and Graves, P. M. (2014). Seroprevalence and spatial epidemiology of Lymphatic Filariasis in American Samoa after successful mass drug administration. PLoS Neglected Tropical Diseases 8, e3297. doi:10.1371/journal.pntd.0003297.CrossRefGoogle ScholarPubMed
Luan, H. and Law, J. (2014). Web GIS-based public health surveillance systems: a systematic review. ISPRS International Journal of Geo-Information 3, 481–506.Google Scholar
Mabaso, M., Vounatsou, P., Midzi, S., Da Silva, J. and Smith, T. (2006). Spatio-temporal analysis of the role of climate in inter-annual variation of malaria incidence in Zimbabwe. International Journal of Health Geographics 5, 20.Google Scholar
Magalhães, R. J. S., Barnett, A. G. and Clements, A. C. (2011). Geographical analysis of the role of water supply and sanitation in the risk of helminth infections of children in West Africa. Proceedings of the National Academy of Sciences of the United States of America 108, 20084–20089.Google Scholar
Malone, J., Bergquist, N., Huh, O., Bavia, M., Bernardi, M., El Bahy, M., Fuentes, M., Kristensen, T., Mccarroll, J., Yilma, J. and Zhou, X. (2001). A global network for the control of snail-borne disease using satellite surveillance and geographic information systems. Acta Tropica 79, 7–12.Google Scholar
Marston, L., Kelly, G. C., Hale, E., Clements, A. C., Hodge, A. and Jimenez-Soto, E. (2014). Cost analysis of the development and implementation of a spatial decision support system for malaria elimination in Solomon Islands. Malaria Journal 13, 325·1–325·9.Google Scholar
Martinez, R., Vidaurre, M., Najera, P., Loyola, E., Castillo-Salgado, C. and Eisner, C. (2001). SIGEpi: geographic information system in epidemiology and public health. Epidemiological Bulletin 22, 4–5.Google Scholar
Mboera, L. E. G., Senkoro, K. P., Rumisha, S. F., Mayala, B. K., Shayo, E. H. and Mlozi, M. R. S. (2011). Plasmodium falciparum and helminth coinfections among schoolchildren in relation to agro-ecosystems in Mvomero District, Tanzania. Acta Tropica 120, 95–102.Google Scholar
Mcgeehin, M., Qualters, J. and Niskar, A. (2004). National Environmental Public Health Tracking Program: bridging the information gap. Environtal Health Perspectives 112, 1409–1413.Google Scholar
Mclafferty, S. (2003). GIS and health care. Annual Reviews in Public Health 24, 25–42.Google Scholar
Molyneux, D. (2003). Lymphatic Filariasis (Elephantiasis) elimination: a public health success and development opportunity. Filaria Journal 2, 13.Google Scholar
Moore, D. A. and Carpenter, T. E. (1999). Spatial analytical methods and geographic information systems: use in health research and epidemiology. Epidemiologic Reviews 21, 143–161.Google Scholar
Njau, J. D., Stephenson, R., Menon, M. P., Kachur, S. P. and Mcfarland, D. A. (2014). Investigating the important correlates of maternal education and childhood malaria infections. The American Journal of Tropical Medicine and Hygiene 91, 509–519.Google Scholar
Noma, M., Nwoke, B. E. B., Nutall, I., Tambala, P. A., Enyong, P., Namsenmo, A., Remme, J., Amazigo, U. V., Kale, O. O. and Seketely, A. (2002). Rapid epidemiology mapping of onchocerciasis (REMO): its application by the African Programme for Onchocerciasis Control (APOC). Annals of Tropical Medicine and Parasitology 96, S29–S39.Google Scholar
Noor, A. M., Elmardi, K. A., Abdelgader, T. M., Patil, A. P., Amine, A. A., Bakhiet, S., Mukhtar, M. M. and Snow, R. W. (2012). Malaria risk mapping for control in the Republic of Sudan. The American Journal of Tropical Medicine and Hygiene 87, 1012.Google Scholar
Norstrom, M. (2001). Geographical Information System (GIS) as a tool in surveillance and monitoring of animal diseases. Acta Veterinaria Scandinavica Suppl. 94, 79–85.Google Scholar
Ottesen, E. A. (2000). Editorial: The Global Programme to eliminate Lymphatic Filariasis. Tropical Medicine & International Health 5, 591–594.Google Scholar
Pan American Health Organization. (2008). Geographic information system in Epidemiology and Public Health. [Online]. online: PAHO/ WHO. http://ais.paho.org/sigepi/index.asp?xml=sigepi/index.htm Google Scholar
Ramasubramanian, L. (1999). GIS implementation in developing countries: learning from organisational theory and reflective practice. Transactions in GIS 3, 359–380.Google Scholar
Randolph, S. and Rogers, D. (2006). Tick-borne disease systems: mapping geographic and phylogenetic space. Advanced Parasitology 62, 263–291.Google Scholar
Raso, G., Matthys, B., N'goran, E. K., Tanner, M., Vounatsou, P. and Utzinger, J. (2005). Spatial risk prediction and mapping of Schistosoma mansoni infections among schoolchildren living in western Côte d'Ivoire. Parasitology 131, 97–108.Google Scholar
Raso, G., Vounatsou, P., Singer, B. H., Eliézer, K., Tanner, M. and Utzinger, J. (2006). An integrated approach for risk profiling and spatial prediction of Schistosoma mansoni–hookworm coinfection. Proceedings of the National Academy of Sciences of the United States of America 103, 6934–6939.Google Scholar
Roll Back Malaria Partnership (2008). The global malaria action plan for a malaria-free world 2008–2015. http://www.rollbackmalaria.org Google Scholar
Saikia, U. (2010). GIS applications for sustainable development and good governance in Eastern Indonesia and Timor Leste – edited by Rohan Fisher, Bronwyn Myers, Max Sanam and Vincent Tarus. Geographical Research 48, 449–451.Google Scholar
Schneider, M., Aguilera, X., Barbosa Da Silva Junior, J., Ault, S., Najera, P. and Brooker, S. (2011). Elimination of neglected diseases in Latin America and the Caribbean: a mapping of selected diseases. PLoS Neglected Tropical Diseases 5(2), e964.Google Scholar
Scholte, R. G. C., Freitas, C. C., Dutra, L. V., Guimaraes, R. J. P. S., Drummond, S. C., Oliveira, G. and Carvalho, O. S. (2012). Utilizing environmental, socioeconomic data and GIS techniques to estimate the risk for ascariasis and trichuriasis in Minas Gerais, Brazil. Acta Tropica 121, 112–117.Google Scholar
Semenza, J., Suk, J., Tsolova, S., Gillespie, I., Mook, P., Little, C., Grant, K., Mclauchlin, J., Kafatos, G. and Randolph, S. (2010). Social determinants of infectious diseases: a public health priority. EuroSurveill 15, 2–4.Google Scholar
Shaw, N. T. (2012). Geographical information systems and health: current state and future directions. Healthcare Informatics Research 18, 88–96.Google Scholar
Sieber, R. E. (2000). GIS implementation in the grassroots. URISA Journal 12, 15–29.Google Scholar
Simarro, P. P., Cecchi, G., Paone, M., Franco, J. R., Diarra, A., Ruiz, J. A., Fèvre, E. M., Courtin, F., Mattioli, R. C. and Jannin, J. G. (2010). The Atlas of human African trypanosomiasis: a contribution to global mapping of neglected tropical diseases. International Journal of Health Geographics 9, 57–75.Google Scholar
Simoonga, C., Utzinger, J., Brooker, S., Vounatsou, P., Appleton, C., Stensgaard, A., Olsen, A. and Kristensen, T. (2009). Remote sensing, geographical information system and spatial analysis for schistosomiasis epidemiology and ecology in Africa. Parasitology 136, 1683.Google Scholar
Smith, J., Solomon, A., Basanez, M.-G., Bockarie, M., Bundy, D., Clements, A., Emerson, P., Flueckiger, R., Foster, A., Haddad, D., Kelly-Hope, L., Mabey, D. and Soar, R. (2013). Response to Hay (2013) Global mapping of infectious disease. Philosophical Transactions of the Royal Society of London B: Biological Sciences 368, 0250. doi:10.1098/rstb.2012.0250.Google Scholar
Snow, R., Guerra, C., Noor, A., Myint, H. and Hay, S. (2005). The global distribution of clinical episodes of Plasmodium falciparum malaria. Nature 434, 214–217.Google Scholar
Wand, H., Lote, N., Semos, I. and Siba, P. (2012). Investigating the spatial variations of high prevalences of severe malnutrition among children in Papua New Guinea: results from geoadditive models. BMC Research Notes 5, 288.Google Scholar
Webster-Kerr, K., Figueroa, P. J., Weir, P. L., Lewis-Bell, K., Baker, E., Horner-Bryce, J., Lewis-Fuller, E., Bullock Ducasse, M., Carter, K. H. and Campbell-Forrester, S. (2011). Success in controlling a major outbreak of malaria because of Plasmodium falciparum in Jamaica. Tropical Medicine & International Health 16, 298–306.Google Scholar
World Health Assembly (1997). World Health Assembly Resolution 50·29 (WHA 50·29). World Health Assembly, Geneva, Switzerland.Google Scholar
World Health Organization (2005). Deworming for health and development: report of the Third Global Meeting of the Partners for Parasite Control.Google Scholar
World Health Organization (2014). DengueNet [Online]. World Health Organization. http://apps.who.int/globalatlas/default.asp Google Scholar
World Health Organization (2015). Public health surveillance [Online]. http://www.who.int/topics/public_health_surveillance/en/ Google Scholar
Yang, G.-J., Vounatsou, P., Zhou, X.-N., Tanner, M. and Utzinger, J. (2005). A Bayesian-based approach for spatio-temporal modeling of county level prevalence of Schistosoma japonicum infection in Jiangsu province, China. International Journal for Parasitology 35, 155–162.Google Scholar
Zeng, H., Yang, X., Meng, S., Wang, H., Tang, X., Tang, W., Zeng, S., Jeschke, S. and Wang, Y. (2011). Awareness and knowledge of schistosomiasis infection and prevention in the “Three Gorges Dam” reservoir area: a cross-sectional study on local residents and health personnel. Acta Tropica 120, 238–244.Google Scholar
Zhou, X.-N., Lv, S., Yang, G.-J., Kristensen, T. K., Bergquist, N. R., Utzinger, J. and Malone, J. B. (2009). Spatial epidemiology in zoonotic parasitic diseases: insights gained at the 1st International Symposium on Geospatial Health in Lijiang, China, 2007. Parasite and Vectors 2.Google Scholar