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The Role of Place and Time in the Epidemiology of Tropical Diseases

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Geospatial Technology and the Role of Location in Science

Part of the book series: GeoJournal Library ((GEJL,volume 96))

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Abstract

The diseases found predominantly within or around the tropics of Cancer and Capricorn have been among the most virulent and destructive, arresting the economic development of the human populations affected and remaining a significant public health risk even in the 21st century. Chief among these tropical diseases is malaria, an insect vector-borne disease which causes great loss of life and which has outwitted many of the major advances in medical science. Such insect vector-borne diseases are closely synchronised to the annual seasonal rainfall patterns as well as the physical geography of the environment. Other diseases, such as bacterial meningitis, occur in those locations where water is absent from the environment and is closely related to the timing of moisture changes and cultural affectations of the human populations affected. This paper seeks to examine the specific roles of location and time in the epidemiology of tropical diseases and asks what technological advances (and methodological innovations) might help reduce the burden of such diseases in the future.

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Notes

  1. 1.

    1. Hausmann, B. Medecins sans Frontieres (Holland), personal communication, 1997.

References

  • Bouma MJ, Kovats RS, Goubet SA, Cox JSH and Haines A (1997). Global assessment of El Nino’s disaster burden. Lancet. 350: 1435–1438.

    Article  Google Scholar 

  • British Medical Journal – Student (BMJ). (2007). Poverty and health article. [Online]. Available at: http://archive.student.bmj.com/issues/01/06/education/180.php [Accessed 10 May 2007].

  • Cheesbrough JS, Morse AP and Green SDR (1995). Meningococcal meningitis and carriage in western Zaire: a hypoendemic zone related to climate? Epidemiological Infections. 114: 75–92.

    Article  Google Scholar 

  • Collier CG and Hardaker PJ (1995). Weather, air quality and health. Meteorological Applications. 2: 313–322.

    Article  Google Scholar 

  • Connor SJ, Flasse SP, Perryman AH and Thomson MC (1997). The contribution of satellite derived information to malaria stratification, monitoring and early warning. World Health Organization.: 1–31.

    Google Scholar 

  • Diaz HF and McCabe GJ (1999). A possible connection between the 1878 yellow fever epidemic in the southern United States and the 1877–78 El Nino episode. Bulletin of the American Meteorological Society. 80(1): 21–27.

    Article  Google Scholar 

  • Dugdale G, Hardy S and Milford JR (1991). Daily catchment rainfall estimated from METEOSAT. Hydrological Processes. 5: 261–270.

    Article  Google Scholar 

  • Ebrahim GJ (1997). Meningococcal Meningitis (Editorial). Journal of Tropical Pediatrics. 43: 126–127.

    Article  Google Scholar 

  • European health for all database (HFA-DB), viewed 26th June 2008, http://www.euro.who.int/HFADB

  • Flitcroft ID, Milford JR and Dugdale G (1989). Relating point to area average rainfall in semiarid West Africa and the implications for rainfall estimates derived from satellite data. Journal of Applied Meteorology. 28: 252–266.

    Article  Google Scholar 

  • Greenwood BM (1987). The epidemiology of acute bacterial meningitis in tropical Africa: Bacterial Meningitis. London, Academic Press.

    Google Scholar 

  • Greenwood BM, Bradley AK, Blakebrough IS, Wali S and Whittle HC (1984). Meningococcal disease and season in Sub-Saharan Africa. The Lancet.: 1339–1342.

    Google Scholar 

  • Greenwood BM, Greenwood AM, Bradley AK, Williams K, Hassan-King M, Shenton F, Wall RA and Hayes RJ (1987). Factors influencing susceptibility to meningococcal disease during an epidemic in the Gambia, West Africa. Journal of Infection. 14: 167–184.

    Article  Google Scholar 

  • Haines A, Smith R (1997). Working together to reduce poverty’s damage. BMJ 314: 529

    Google Scholar 

  • Hart CA and Cuevas LE (1997). Meningococcal disease in Africa. Annals of Tropical Medicine & Parasitology. 91(7): 777–785.

    Article  Google Scholar 

  • Hay SI and Lennon JJ (1999). Deriving meteorological variables across Africa for the study and control of vector-borne disease: a comparison of remote sensing and spatial interpolation of climate. Tropical Medicine and International Health. 4(1): 58–71.

    Article  Google Scholar 

  • Hay SI, Packer MJ and Rogers DJ (1997). The impact of remote sensing on the study and control of invertebrate intermediate hosts and vectors for disease. International Journal of Remote Sensing. 18(14): 2899–2930.

    Article  Google Scholar 

  • Hay SI, Snow RB and Rogers DJ (1998). Predicting malaria seasons in Kenya using multitemporal meteorological satellite sensor data. Transactions of the Royal Society of Tropical Medicine and Hygiene. 92: 12–20.

    Article  Google Scholar 

  • Hay SI, Tucker CJ, Rogers DJ and Packer MJ (1996). Remotely sensed surrogates of meteorological data for the study of the distribution and abundance of arthropod vectors of disease. Annals of Tropical Medicine and Parasitology. 90(1): 1–19.

    Google Scholar 

  • Lethbridge M (1967). Precipitation probability and satellite radiation data. Monthly Weather Review. 95(7): 487–490.

    Article  Google Scholar 

  • Malone JB, Huh OK, Fehler DP, Wilson PA, Wilensky DE, Holmes RA and Elmagdoub AI (1994). Temperature data from satellite imagery and the distribution of schistosomiasis in Egypt. American Journal of Tropical Medicine and Hygiene. 50(6): 714–722.

    Google Scholar 

  • Mason SJ (1997). Review of recent developments in seasonal forecasting of rainfall. Water South Africa. 23(1): 57–62.

    Google Scholar 

  • McGuffie K and Henderson-Sellers A (1997). A climate modelling primer. Chichester, Wiley.

    Google Scholar 

  • Milford JR and Dugdale G (1989). Estimation of rainfall using geostationary satellite data. Applications of Remote Sensing in Agriculture, University of Nottingham, 48th Easter School of Agricultural Science.

    Google Scholar 

  • Moore P (1992). Meningococcal meningitis in Sub-Saharan Africa: a model for the epidemic process. Clinical Infectious Diseases. 14: 515–525.

    Google Scholar 

  • Palmer TN (2000). Predicting uncertainty in forecasts of weather and climate. Reports on Progress in Physics. 63: 71–116.

    Article  Google Scholar 

  • Palmer TN and Anderson DLT (1994). The prospects for seasonal forecasting – a review paper. Quarterly Journal of the Royal Meteorological Society. 120: 755–793.

    Google Scholar 

  • Riedo FX, Plikaytis BD and Broome CV (1995). Epidemiology and prevention of meningococcal disease. Pediatric Infectious Diseases Journal. 14: 643–657.

    Article  Google Scholar 

  • Robinson T, Rogers D and Williams B (1997). Mapping tsetse habitat suitability in the common fly belt of Southern Africa using multivariate analysis of climate and remotely sensed vegetation data. Medical and Veterinary Entomology. 11: 235–245.

    Article  Google Scholar 

  • Rogers DJ and Randolph SE (1991). Mortality rates and population density of tsetse flies correlated with satellite imagery. Nature. 351: 739–741.

    Article  Google Scholar 

  • Schwartz B, Moore PS and Broome CV (1989). Global epidemiology of meningococcal disease. Clinical Microbiology Reviews. 2: 118–124.

    Google Scholar 

  • Scott D (1965). Cerebrospinal Meningitis. Epidemic disease in Ghana 1901–1960. London, Oxford University Press, pp. 85–119.

    Google Scholar 

  • Smith WL (1966). Note on the relationship between total precipitable water and surface dew point. Journal of Applied Meteorology. 5: 726–727.

    Article  Google Scholar 

  • Stockdale TN (2000). An overview of techniques for seasonal forecasting. Stochastic Environmental Research and Risk Assessment. 14: 305–318.

    Article  Google Scholar 

  • Stockdale TN, Anderson DLT, Alves JOS and Balmaseda MA (1998). Global seasonal rainfall forecasts using a coupled ocean-atmosphere model. Nature. 392: 370–373.

    Article  Google Scholar 

  • Thomson MC, Connor SJ, Milligan PJM and Flasse SP (1996). The ecology of malaria – as seen from Earth observation satellites. Annals of Tropical Medicine and Parasitology. 90(3): 243–264.

    Google Scholar 

  • Thomson MC, Connor SJ, Milligan P, Flasse S and Service MW (1995). The potential in using environmental monitoring satellites to predict malaria epidemics in Africa. Meteorological Satellite Data User’s Conference, Winchester, UK.

    Google Scholar 

  • Waddy BB (1952). Climate and respiratory infections. The Lancet. 4: 674–677.

    Article  Google Scholar 

  • World Bank, Viewed 25th June 2008, http://web.worldbank.org

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Author information

Authors and Affiliations

  1. Department of Environmental & Geographical Sciences, Manchester Metropolitan University, Manchester, M1 5GD, UK

    Mark Cresswell

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  1. Mark Cresswell
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Correspondence to Mark Cresswell .

Editor information

Editors and Affiliations

  1. Dept. Spatial Economics, VU University Amsterdam Fac. Economics & Business Admin, De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands

    Henk J. Scholten

  2. Geonovum, Barchman Wuytierslaan 10, 3818 LH Amersfoort, The Netherlands

    Rob van de Velde

  3. Dept. History, University of York, Heslington, York, YO10 5DD, UK

    Niels van Manen

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Cresswell, M. (2009). The Role of Place and Time in the Epidemiology of Tropical Diseases. In: Scholten, H.J., van de Velde, R., van Manen, N. (eds) Geospatial Technology and the Role of Location in Science. GeoJournal Library, vol 96. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-2620-0_11

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