Journal of Urban Health

, Volume 81, Issue 3, pp 363–376 | Cite as

Measuring urbanization pattern and extent for malaria research: A review of remote sensing approaches

Abstract

Within the next 30 years, the proportion of urban dwellers will rise from under half to two thirds of the world's population. Such a shift will entail massive public health consequences, and most of this urban transition will occur in low-income regions of the world. Urban populations face very different health risks compared to those in rural areas, particularly in terms of malaria. To target effective and relevant public health interventions, the need for clear, consistent definitions of what determines urban areas and urban communities is paramount. Decision makers are increasingly seeing remote sensing as a cost-effective solution to monitoring urbanization at a range of spatial scales. This review focuses on the progress made within the field of remote sensing on mapping, monitoring, and modeling urban environments and examines existing challenges, drawbacks, and future prospects. We conclude by exploring' some of the particular relevance of these issues to malaria and note that they are of more general relevance to all those interested in urban public health.

Keywords

Satellite imagery Urban mapping Malaria risk 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    United Nations. World, Urbanisation Prospects, 2002 Revision. New York: United Nations; 2002.Google Scholar
  2. 2.
    Miller RB, Small C. Cities from space: potential applications of remote sensing in urban environmental research and policy. Environ Sci Policy. 2003;6:129–137CrossRefGoogle Scholar
  3. 3.
    Harpham T. Urbanisation and health in transition. Lancet. 1997;349(suppl 3):11–13.CrossRefGoogle Scholar
  4. 4.
    Harpham T, Tanner M, eds. Urbanisation Health in Developing Countries: Progress and Prospects. London: Earthscan; 1995.Google Scholar
  5. 5.
    McMichael AJ, Beaglehole R. The changing global context of public health. Lancet. 2000;356:495–499.CrossRefPubMedGoogle Scholar
  6. 6.
    McMichael AJ. The urban environment and health in a world of increasing globalization: issues for developing countries. Bull World Health Organ, 2000;78:1117–1126.PubMedGoogle Scholar
  7. 7.
    Knudsen AB, Slooff R. Vector-borne disease problems in rapid urbanization: new approaches to vector control. Bull World Health Organ. 1992;70:1–6.PubMedGoogle Scholar
  8. 8.
    Lines J, Harpham T, Leake C, Schofield C. Trends, priorities and policy directions in the control of vector-borne diseases in urban environments. Health Policy Plann. 1994; 9:113–129.Google Scholar
  9. 9.
    Mott KE, Desjeux P, Moncayo A, Ranque P, de Raadt P. Parasitic disease and urban development. Bull world Health Organ. 1990;68:691–698.PubMedGoogle Scholar
  10. 10.
    McCally M, Garg A, Oleskey C. the challenges of emerging illness in urban environments: an overview. J Urban Health 2001;78:350–358.PubMedGoogle Scholar
  11. 11.
    Rose AMC, Watson JM, Graham C, et al. Tuberculosis at the end of the 20th century in England and Wales: results of a national survey in 1998. Thorax. 2001;56:173–179.CrossRefPubMedGoogle Scholar
  12. 12.
    Rothenburg R, Baldwin J, Trotter R, Muth S. The risk environment for HIV transmission: results from the Atlanta and Flagstaff network studies. J Urban Health. 2001;78:419–432.Google Scholar
  13. 13.
    Bang YH, Shah NK. Human ecology related to urban mosquito-borne disease in countries of the South East Asia region. J Commun Dis. 1988;20:1–17.PubMedGoogle Scholar
  14. 14.
    Hay SI, Rogers DJ, Toomer JF, Snow RW. Annual Plasmodium falciparum entomological inoculation rates (EIR) across Africa: literature survey, internet access and review. Trans R Soc Trop Med Hyg. 2000;94:113–127.CrossRefPubMedGoogle Scholar
  15. 15.
    Robert V, MacIntyre K, Keating J, et al. Malaria transmission in urban sub-Saharan Africa. Am J Trop Med Hyg. 2003;68:169–176.PubMedGoogle Scholar
  16. 16.
    Noor AM, Zurovac D, Hay SI, Ochola SA, Snow RW. Defining equity in physical access to clinical services using geographical information systems as part of malaria planning and monitoring in Kenya. Trop Med Int Health. 2003;8:917–926.CrossRefPubMedGoogle Scholar
  17. 17.
    Vlahov D, Galea S. Urbanization, urbanicity and health. J Urban Health. 2002;79:1–12.Google Scholar
  18. 18.
    Rush M, Vernon S. Remote sensing and urban public health. Photogram Eng Remote Sens. 1975;41:1149–1155.Google Scholar
  19. 19.
    Jensen JR, Cowen DC. Remote sensing of urban suburban infrastructure and socioeconomic attributes. Photogram Eng Remote Sens. 1999;65:611–622.Google Scholar
  20. 20.
    Aplin P, Atkinson PM, Curran PJ. Fine spatial resolution satellite sensors for the next decade. Int J Remote Sens. 1997;18:3873–3881.CrossRefGoogle Scholar
  21. 21.
    Hay SI. An overview of remote sensing and geodesy for epidemiology and public health application. Adv Parasitol. 2000;47:1–35.PubMedGoogle Scholar
  22. 22.
    Hay SI, Omumbo JA, Craig MH, Snow RW. Earth observation, geographic information systems and Plasmodium falciparum malaria in sub-Saharan Africa. Adv. Parasitol. 2000;47:173–215.PubMedCrossRefGoogle Scholar
  23. 23.
    Rogers DJ, Randolph SE, Snow RW, Hay SI. Satellite imagery in the study and forecast of malaria. Nature. 2002;415:710–715.CrossRefPubMedGoogle Scholar
  24. 24.
    Coiner JC, Levine AL. Applications of remote sensing to urban problems. Urban Syst. 1979;4:205–219.CrossRefGoogle Scholar
  25. 25.
    New M, Lister D, Hulme M, Makin I. A high-resolution data set of surface climate over global land areas. Climate Res. 2002;21:1–25.Google Scholar
  26. 26.
    Henderson FM, Xia Z-G. SAR applications in human settlement detection, population estimation and urban land use pattern analysis: a status report. IEEE Trans Geosci Remote Sens. 1997;35:79–85.CrossRefGoogle Scholar
  27. 27.
    Dong Y, Forster B, Ticehurst C. Radar backscatter analysis for urban environments. Int J Remote Sens. 1997;18:1351–1364.CrossRefGoogle Scholar
  28. 28.
    Xia Z, Henderson FM. Understanding the relationships between radar response patterns and the bio- and geophysical parameters of urban areas. IEEE Trans Geosci Remote Sens. 1997;35:93–101.CrossRefGoogle Scholar
  29. 29.
    Quartulli M, Tupin F. Information extraction from high resolution SAR data for urban scene understanding. Paper presented at: Urban 2003; May 22–23, 2003; Berlin, Germany.Google Scholar
  30. 30.
    Roth A, Terra SAR-X: a new perspective for scientific use of high resolution spaceborne SAR data. Paper presented at: Urban 2003; 2003; Berlin, Germany.Google Scholar
  31. 31.
    Elvidge C, Hobson VR, Nelson IL, et al. Overview of DMSP OLS and scope of applications. In: Mesev V, ed. Remotely Sensed Cities. London: Taylor and Francis; 2003;281–299.Google Scholar
  32. 32.
    Dobson JE, Bright EA, Coleman PR, Bhaduri BL. Landscan: a global population database for estimating populations at risk. In: Mesev V, ed. Remotely Sensed Cities. London: Taylor and Francis; 2003:267–279.Google Scholar
  33. 33.
    Barnsley MJ, Moller-Jensen L, Barr SL. Inferring urban land use by spatial and structural pattern recognition. In: Donnay J-P, Barnsley MJ, Longley PA, eds. Remote Sensing and Urban Analysis. London: Taylor and Francis; 2001:115–144.Google Scholar
  34. 34.
    Baudot Y. Geographical analysis of the population of fast-growing cities in the third world. In: Donnay J-P, Barnsley MJ, Longley PA, eds. Remote Sensing and Urban Analysis. London: Taylor and Francis; 2001:225–241.Google Scholar
  35. 35.
    Weber C. Urban agglomeration delimitation using remote sensing. In: Donnay J-P, Barnsley MJ, Longley PA, eds. Remote Sensing and Urban Analysis. London: Taylor and Francis; 2001:145–159.Google Scholar
  36. 36.
    Forster B. Some urban measurements from Landsat data. Photogram Eng Remote Sens. 1983;14:1693–1707.Google Scholar
  37. 37.
    Forster B. An examination of some problems and solutions in monitoring urban areas from satellite platforms. Int J Remote Sens. 1985;6:139–151.Google Scholar
  38. 38.
    Gao J, Skillcorn D. Capability of SPOT XS data in producing detailed land cover maps at the urban-rural periphery. Int J Remote Sens. 1998;19:2877–2891.CrossRefGoogle Scholar
  39. 39.
    Zha Y, Gao J, Ni S. Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. Int J Remote Sens. 2003;24:583–594.CrossRefGoogle Scholar
  40. 40.
    Vogelmann JE, Sohl T, Howard SM. Regional characterization of land cover using multiple sources of data. Photogram Eng Remote Sens. 1998;64:45–57.Google Scholar
  41. 41.
    Civco DL, Hurd JD, Wilson EH, Arnold CL, Prisloe MP. Quantifying and describing urbanizing landscapes in the Northeast United States. Photogram Eng Remote Sens. 2002;68:1083–1090.Google Scholar
  42. 42.
    Yu S, Berthod M, Giraudon G. Toward robust analysis of satelite images using map information—application to urban area detection. IEEE Trans Geosci Remote Sens. 1999;37:1925–1939.CrossRefGoogle Scholar
  43. 43.
    Mesev V, Longley PS, Batty M, Xie Y. Morphology from imagery: detecting and measuring the density of urban land use. Environ Plan A. 1995;27:759–780.Google Scholar
  44. 44.
    Webster CJ. Urban morphology fingerprints. Environ Plann B. 1996;23:279–297.Google Scholar
  45. 45.
    Longley PA, Mesev V. Measuring urban morphology using remotely-sensed imagery. In: Donnay J-P., Barnsley MJ, Longley PA, eds. Remote Sensing and Urban Analysis, London: Taylor and Francis; 2001:163–183.Google Scholar
  46. 46.
    Pesaresi M, Bianchin A. Recognizing settlement structure using mathematical morphology and image texture. In: Donnay J-P, Barnsley MJ, Longley PA, eds. Remote Sensing and Urban Analysis. London: Taylor and Francis; 2001:56–67.Google Scholar
  47. 47.
    Brivio PA, Zilioli E. Urban pattern characterization through geostatistical analysis of satellite images. In: Donnay J-P, Barnsley MJ, Longley PA, eds. Remote Sensing and Urban Analysis. London: Taylor and Francis; 2001:40–53.Google Scholar
  48. 48.
    Taket ND, Howarth SM, Burge RE. A model for the imaging of urban areas by synthetic aperture radar. IEEE Trans Geosci Remote Sens. 1991;29:432–443.CrossRefGoogle Scholar
  49. 49.
    Hepner GF, Houshmand B, Kulikov I, Bryant N. Investigation of the integration of AVIRIS and IFSAR for urban analysis. Photogram Eng. Remote Sens. 1998; 64:813–820.Google Scholar
  50. 50.
    Grey W, Luckman A. Mapping urban extent using satellite radar interferometry. Photogram Eng Remote Sens. 2003;69:957–962.Google Scholar
  51. 51.
    Imhoff ML, Lawrence WT, Stutzer DC, Elvidge CD. A technique for using composite DMSP.OLS “city lights” satellite data to map urban area. Remote Sens Environ. 1997;61:361–370.CrossRefGoogle Scholar
  52. 52.
    Schneider A, Friedl MA, Woodcock CE. Mapping urban areas by fusing multiple sources of coarse resolution remotely sensed data. Paper presented at: International Geoscience and Remote Sensing Symposium; July 21–25, 2003; Toulouse, France.Google Scholar
  53. 53.
    Dare PM, Fraser CS. Mapping informal settlements using high resolution imagery. Int J Remote Sens. 2001;22:1399–1401.CrossRefGoogle Scholar
  54. 54.
    Bjorgo E. Using very high spatial resolution multispectral satellite sensor imagery to monitor refugee camps. Int J Remote Sens. 2000;2:611–616.CrossRefGoogle Scholar
  55. 55.
    Rowland M, Nosten F. Malaria epidemiology and control in refugee camps and complex emergencies. Ann Trop Med Parasitol. 2001;95:741–754.CrossRefPubMedGoogle Scholar
  56. 56.
    Clapham WB. Continuum-based classification of remotely sensed imagery to describe urban sprawl on a watershed scale. Remote Sens Environ. 2003;86:322–340.CrossRefGoogle Scholar
  57. 57.
    Mesev V. Urban land use uncertainty. In: Mesev V, ed. Remotely Sensed Cities. London: Taylor and Francis; 2003:207–222.Google Scholar
  58. 58.
    Donnay J-P, Unwin D. Modelling geographical distributions in urban areas. In: Donnay J-P, Barnsley MJ, Longley PA, eds. Remote Sensing and Urban Analysis. London: Taylor and Francis; 2001:205–224.Google Scholar
  59. 59.
    Moller-Jensen L. Classification of urban land cover based on expert systems, object models and texture. Comput Environ Urban Syst. 1997;21:291–302.CrossRefGoogle Scholar
  60. 60.
    Baraldi A, Parmiggiani F. Urban area classification by multispectral SPOT images. IEEE Trans Geosci Remote Sens. 2000;28:674–680.CrossRefGoogle Scholar
  61. 61.
    Ben-Dor E, Saaroni H. A spectral based recognition of the urban environment using the visible and near infrared spectral region. A case study over Tel-Aviv, Israel. Int J Remote Sens. 2001;22:2193–2218.CrossRefGoogle Scholar
  62. 62.
    Mesev V, Gorte B, Longley PA. Modified maximum-likelihood classification algorithms and their application to urban remote sensing. In: Donnay J-P, Barnsley MJ, Longley PA, eds. Remote Sensing and Urban Analysis. London: Taylor and Francis; 2001:72–88.Google Scholar
  63. 63.
    Paola JD, Schowengerdt RA. A detailed comparison of backpropagation neural network and maximum-likelihood classifiers for urban land use classification. IEEE Trans Geosci Remote Sens. 1995;33:981–996.CrossRefGoogle Scholar
  64. 64.
    Gamba P, Houshmand B. An efficient neural classification of SAR and optical urban images. Int J Remote Sens. 2001;22:1535–1553.CrossRefGoogle Scholar
  65. 65.
    Brown M, Lewis HG, Gunn SR. Linear spectral mixture models and support vector machines for remote sensing. IEEE Trans Geosci Remote Sens. 2000;38:2346–2360.CrossRefGoogle Scholar
  66. 66.
    Phinn S, Stanford M, Scarth P, Murray AT, Shyy PT. Monitoring the composition of urban environments based on the vegetation-impervious surface-soil (VIS) model by subpixel analysis techniques. Int J Remote Sens. 2002;23:4131–4153.CrossRefGoogle Scholar
  67. 67.
    Zhang J, Foody GM. A fuzzy classification of sub-urban land cover from remotely sensed imagery. Int J Remote Sens. 1998;19:2721–2738.CrossRefGoogle Scholar
  68. 68.
    Gamba P, Dell'Acqua F. Increased accuracy multiband urban classification using a neuro-fuzzy classifier. Int J Remote Sens. 2003;24.Google Scholar
  69. 69.
    Tatem AJ, Lewis HG, Atkinson PM, Nixon MS. Super-resolution mapping of urban scenes from IKONOS imagery using a Hopfield neural network. Paper presented at: International Geoscience and Remote Sensing Symposium: July 9–13, 2001; Sydney, Australia.Google Scholar
  70. 70.
    Tatem AJ, Lewis HG, Atkinson PM, Nixon MS. Super-resolution target identification from remotely sensed images using a Hopfield neural network. IEEE Trans Geosci Remote Sens. 2001;39:781–796.CrossRefGoogle Scholar
  71. 71.
    Tatem AJ, Lewis HG, Atkinson PM, Nixon MS. Increasing the spatial resolution of Landsat TM imagery for land cover mapping in agricultural areas. Int J Geogr Inform Sci. 2003;17:647–672.CrossRefGoogle Scholar
  72. 72.
    Jensen JR. Spectral and textural features to classify elusive land cover at the urban fringe. Prof Geographer. 1979;31:400–409.CrossRefGoogle Scholar
  73. 73.
    Herold M, Liu X, Clarke KC. Spatial metrics and image texture for mapping urban land use. Photogram Eng Remote Sens. 2003;69:991–1002.Google Scholar
  74. 74.
    Haralick RM, Shanmugam K, Dinstein I. Texture features for image classification. IEEE Trans Syst Man Cybernetics. 1973;3:610–621.Google Scholar
  75. 75.
    Shaban MA, Dikshit O. Improvement of classification in urban areas by the use of textural features: the case study of Lucknow city, Uttar Pradesh. Int J Remote Sens. 2001;22:565–593.CrossRefGoogle Scholar
  76. 76.
    Karathanassi V, Iossifidis C, Rokos D. A texture-based classification method for classifying built areas according to their density. Int J Remote Sens. 2000;21:1807–1823.CrossRefGoogle Scholar
  77. 77.
    Dell'Acqua F, Gamba P. Texture-based characterization of urban environments on satellite SAR images. IEEE Trans Geosci Remote Sens. 2003;41:153–159.CrossRefGoogle Scholar
  78. 78.
    Harris PM, Ventura SJ. The integration of geographic data with remotely sensed imagery to improve classification in an urban area. Photogram Eng Remote Sens. 1995;61:993–998.Google Scholar
  79. 79.
    Kam T. Integrating GIS and remote sensing techniques for urban land-cover and land-use analysis. Geocarto Int. 1995;10:39–48.Google Scholar
  80. 80.
    Stefanov WL, Ramsey MS, Christensen PR. Monitoring urban land cover change: an expert system approach to land cover classification of semiarid to arid urban centers. Remote Sens Environ. 2001;77:173–185.CrossRefGoogle Scholar
  81. 81.
    Weng QH. Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling. J Environ Manage. 2002;64:273–284.CrossRefPubMedGoogle Scholar
  82. 82.
    Gupta D, Munshi M. Urban change detection and land-use mapping of Delhi. Int J Remote Sens. 1985;6:529–534.Google Scholar
  83. 83.
    Kressler F, Steinnocher K. Change detection in urban areas using satellite images and spectral mixture analysis. Int Arch Photogram Remote Sens. 1996;31:379–383.Google Scholar
  84. 84.
    Batty M, Howes D. Predicting temporal patterns in urban development from remote imagery. In: Donnay J-P, Barnsley MJ, Longley PA, eds. Remote Sensing and Urban Analysis. London: Taylor and Francis; 2001:185–204.Google Scholar
  85. 85.
    Ji CY, Liu QH, Sun DF, Wang S, Lin P, Li XW. Monitoring urban expansion with remote sensing in China. Int J Remote Sens. 2001;22:1441–1455.CrossRefGoogle Scholar
  86. 86.
    Kwarteng AY, Chavez PS. Change detection study of Kuwait City and environs using multi-temporal Landsat Thematic Mapper data. Int J Remote Sens. 1998;19:1651–1662.CrossRefGoogle Scholar
  87. 87.
    Ridd MK, Liu J. A comparison of four algorithms for change detection in an urban environment. Remote Sens Environ. 1998;63:95–100.CrossRefGoogle Scholar
  88. 88.
    Zhang Y. Detection of urban housing development by fusing multisensor satellite data and performing spatial feature post-classification. Int J Remote Sens. 2001;22:3339–3355.CrossRefGoogle Scholar
  89. 89.
    Yang L, Xian G, Klaver JM, Deal B. Urban land-cover change detection through subpixel imperviousness mapping using remotely sensed data. Photogram Eng Remote Sens. 2003;69:1003–1010.Google Scholar
  90. 90.
    Herold M, Goldstein NC, Clarke KC. The spatiotemporal form of urban growth: measurement analysis and modeling. Remote Sens Environ. 2003;86:286–302.CrossRefGoogle Scholar
  91. 91.
    Theobold DM, Hobbs NT. Forecasting rural land use change: a comparison of regression and spatial transition-based models. Geogr Environ Model. 1998;2:65–82.Google Scholar
  92. 92.
    Liu X, Lathrop RG. Urban change detection based on an artificial neural network. Int J Remote Sens. 2002;23:2513–2518.CrossRefGoogle Scholar
  93. 93.
    Seto KC, Weiguo L. Comparing ARTMAP neural network with the maximum-likelihood classifier for detecting urban change. Photogram Eng Remote Sens. 2003;69:981–990.Google Scholar
  94. 94.
    Qiu F, Woller KL, Briggs R. Modeling urban population growth from remotely sensed imagery and TIGER GIS road data. Photogram Eng Remote Sens. 2003;69:1031–1042.Google Scholar
  95. 95.
    Clarke KC, Gaydos LJ. Loose-coupling a cellular automaton model and GIS: long-term urban growth prediction for San Francisco and Washington/Baltimore. Int J Geogr Inform Sci. 1998;12:699–714.CrossRefGoogle Scholar
  96. 96.
    Doll CNH. Estimating non-population activities from night-time satellite imagery. In: Mesev V, ed. Remotely Sensed Cities. London: Taylor and Francis; 2003:335–353.Google Scholar
  97. 97.
    Grey W, Luckman A, Holland D. Mapping urban change in the UK using satellite radar interferometry. Remote Sens Environ. 2003;87:16–22.CrossRefGoogle Scholar
  98. 98.
    Dousset B, Gourmelon F. Satellite multi-sensor data analysis of urban surface temperatures and landcover. ISPRS J Photogram Remote Sens. 2003;58:43–54.CrossRefGoogle Scholar
  99. 99.
    Streutker DR. A remote sensing study of the urban heat island of Houston, Texas. Int J Remote Sens. 2002;23:2595–2608.CrossRefGoogle Scholar
  100. 100.
    Kalnay E, Cai M. Impact of urbanization and land-use change on climate. Nature. 2003;423:528–531.CrossRefPubMedGoogle Scholar
  101. 101.
    Owen TW, Carlson TN, Gillies RR. An assessment of satellite remotely-sensed land cover parameters in quantitatively describing the climatic effect of urbanization. Int J Remote Sens. 1998;19:1663–1681.CrossRefGoogle Scholar
  102. 102.
    Dobson JE, Bright EA, Coleman PR, Durfee RC, Worley BA. Landscan: a global population database for estimating populations at risk. Photogram Eng Remote Sens. 2000;66:849–857.Google Scholar
  103. 103.
    Harvey JT. Population estimation at the pixel level. In: Mesev V, ed. Remotely Sensed Cities. London: Taylor and Francis; 2003:181–205.Google Scholar
  104. 104.
    Lo CP. Zone-based estimation of population and housing units from satellite-generated land use/land cover maps. In: Mesev V, ed. Remotely Sensed Cities. London: Taylor and Francis; 2003:157–180.Google Scholar
  105. 105.
    Sutton P, Roberts D, Elvidge C, Baugh K. Census from heaven: an estimate of the global human population using night-time satellite imagery. Int J Remote Sens. 2001;22:3061–3076.CrossRefGoogle Scholar
  106. 106.
    Lo CP, Faber BJ. Integration of Landsat Thematic Mapper and census data for quality of life assessment. Remote Sens Environ. 1997;62:143–157.CrossRefGoogle Scholar
  107. 107.
    Harris R. Population mapping by geodemographics and digital imagery. In: Mesev V, ed. Remotely Sensed Cities. London: Taylor and Francis; 2003;223–241.Google Scholar
  108. 108.
    Lo CP, Quattrochi DA. Land-use and land-cover change, urban heat island phenomenon, and health implications: a remote sensing approach. Photogram Eng Remote Sens. 2003;69:1053–1063.Google Scholar
  109. 109.
    Goetz SJ, Wright RK, Smith AJ, Zinecker E, Schaub E. IKONOS imagery for resource management: tree cover, impervious surfaces and riparian buffer analyses in the Mid-Atlantic region. Remote Sens Environ. 2003; in press.Google Scholar
  110. 110.
    Weeks JR. Does night-time lighting deter crime?: An analysis of remotely sensed imagery and crime data. In: Mesev V, ed. Remotely Sensed Cities. London: Taylor and Francis; 2003:355–372.Google Scholar
  111. 111.
    Snow RW, Craig M, Deichmann U, Marsh K. Estimating mortality, morbidity and disability due to malaria among Africa's non-pregnant population. Bull World Health Organ. 1999;77:624–640.PubMedGoogle Scholar
  112. 112.
    Hay SI, Rogers DJ, Randolph SE, et al. Hot topic or hot air? Climate change and malaria resurgence in East African highlands. Trends Parasitol. 2002;18:530–534.CrossRefPubMedGoogle Scholar
  113. 113.
    Hay SI, Cox J, Rogers DJ, et al. Climate change and the resurgence of malaria in the East African highlands. Nature. 2002;415:905–909.CrossRefPubMedGoogle Scholar
  114. 114.
    Greenwood B, Mutabingwa T. Malaria in 2002. Nature. 2002;415:670–672.CrossRefPubMedGoogle Scholar
  115. 115.
    Hay SI, Tucker CJ, Rogers DJ, Packer MJ. Remotely sensed surrogates of meteorological data for the study of the distribution and abundance of arthropod vectors of disease. Ann Trop Med Parasitol. 1996;90:1–19.PubMedGoogle Scholar
  116. 116.
    Tatem AJ, Baylis M, Mellor PS, et al. Prediction of bluetongue vector distribution in Europe and north Africa using satellite imagery. Vet Microbiol. 2003;97:13–29.CrossRefPubMedGoogle Scholar
  117. 117.
    Hay SI, Packer MJ, Rogers DJ. The impact of remote sensing on the study and control of invertebrate intermediate host and vectors for disease. Int J Remote Sens. 1997;18:2899–2930.CrossRefGoogle Scholar
  118. 118.
    Craig MH, Snow RW, le Sueur D. A climate-based distribution model of malaria transmission in sub-Saharan Africa. Parasitol Today. 1999;15:105–111.CrossRefPubMedGoogle Scholar
  119. 119.
    Brohult J, Jorfeldt L, Rombo L, et al. The working capacity of Liberian males: a comparison between rural and urban populations in relation to malaria. Ann Trop Med Parasitol. 1981;75:487–494.PubMedGoogle Scholar
  120. 120.
    Lindsay SW, Campbell H, Adiamah JH, Greenwood AM, Bangali JE, Greenwood BM. Malaria in a peri-urban area of the Gambia. Ann Trop Med Parasitol.. 1990;84:553–562.PubMedGoogle Scholar
  121. 121.
    Vercruysse J. Estimation of the survival rate of Anopheles arabiensis in an urban area (Pikine-Senegal). J Animal Ecol. 1985;54:343–350.Google Scholar
  122. 122.
    Vercruysse J, Jancloes M. Étude entomologique sur la transmission du paludisme humain dans la zone urbaine de Pikine (Sénégal). Cahiers ORSTOM. Sér Entomol Méd Parasitol. 1981;19:165–178.Google Scholar
  123. 123.
    Vercruysse J, Jancloes M, Van de Velden L. Epidemiology of seasonal falciparum malaria in an urban area of Senegal. Bull World Health Organ. 1983;61:821–831.PubMedGoogle Scholar
  124. 124.
    Gardiner C, Biggar RJ, Collins WE, Nkrumah FK. Malaria in urban and rural areas of southern Ghana: a survey of parasitemia, antibodies, and antimalarial practices. Bull World Health Organ. 1984;62:607–613.PubMedGoogle Scholar
  125. 125.
    Robert V, Gazin P, Ouédraogo V, Carnevale P. Le paludisme urbain à Bobo-Dioulasso (Burkina Faso). 1. Étude entomologique de la transmission. Cahiers ORSTOM. Sér Entomol Méd Parasitol. 1986;24:121–128.Google Scholar
  126. 126.
    Modiano D, Sirima BS, Sawadogo A, et al. Severe malaria in Burkina Faso: urban and rural environment. Parasitologia. 1999;41:251–254.Google Scholar
  127. 127.
    Rossi P, Belli A, Mancini L, Sabatinelli G. Enquete entomologique longitudinale sur la transmission du paludisme à Ouagadougou (Burkina Faso). Parassitologia. 1986; 28:1–15.PubMedGoogle Scholar
  128. 128.
    Benasseni R, Gazin P, Carnevale P, Baudon D. Le paludisme urbain à Bobo-Dioulasso. 1. Étude de la morbidité palustre. Cahiers ORSTOM. Sér Entomol Méd Parasitol. 1987; 25:165–170.Google Scholar
  129. 129.
    Fondjo E, Robert V, Le Goff G, Toto JC, Carnevale P. Le paludisme urbain à Yaoundé (Cameroun). 2. Étude entomologique dans deux quartiers peu urbanisés. Bull Soc Pathol Exotique. 1992;85:57–63.Google Scholar
  130. 130.
    Trape JF, Zoulani A. Malaria and urbanisation in Central Africa: the example of Brazzaville. Part II. Results of entomological surveys and epidemiological analysis. Trans R Soc Trop Med Hyg. 1987;81 (suppl 2):34–42.PubMedGoogle Scholar
  131. 131.
    Ngimbi NP, Beckers A, Wery M. Aperçu de la situation épidémiologique du paludisme à Kinshasa (Republique du Zaire) en 1980. Ann Soc Belge Méd Trop. 1982;62:121–137.Google Scholar
  132. 132.
    Coene J. Malaria in urban and rural Kinshasa: the entomological input. Med Vet Entomol. 1993;7:127–137.PubMedGoogle Scholar
  133. 133.
    Yohannes M, Petros B. Urban malaria in Nazareth Ethiopia: parasitological studies. Ethiop Med J. 1996;34:83–90.PubMedGoogle Scholar
  134. 134.
    El Sayed BB, Arnot DE, Mukhtar MM, et al. A study of the urban malaria transmission problem in Khartoum. Acta Trop. 2000;75:163–171.CrossRefPubMedGoogle Scholar
  135. 135.
    Watts TE, Wray JR, Ng'andu H, Draper CC. Malaria in and urban and rural area of Zambia. Trans R Soc Trop Med Hyg. 1990;84:196–200.CrossRefPubMedGoogle Scholar
  136. 136.
    World Health Organization/United Nations International Children's Fund. The African Malaria Report 2003. Geneva/New York: World Health Organization/United Nations Children's Fund; 2003. WHO/CDC/MAL/2003.1093.Google Scholar

Copyright information

© The New York Academy of Medicine 2004

Authors and Affiliations

  1. 1.Trypanosomiases and Land-use in Africa (TALA) Research Group, Department of ZoologyUniversity of OxfordOxfordUK
  2. 2.Kenya medical Research Institute/Wellcome Trust Collaborative ProgrammeNairobiKenya

Personalised recommendations