Mapping hotspots of malaria transmission from pre-existing hydrology, geology and geomorphology data in the pre-elimination context of Zanzibar, United Republic of Tanzania

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• 作者：Andrew Hardy (1)
  Zawadi Mageni (2)
  Stefan Dongus (3)
  Gerry Killeen (2) (4)
  Mark G Macklin (1)
  Silas Majambare (2) (4)
  Abdullah Ali (5)
  Mwinyi Msellem (5)
  Abdul-Wahiyd Al-Mafazy (5)
  Mark Smith (6)
  Chris Thomas (7)
  
  1. Department of Geography and Earth Sciences ; Aberystwyth University ; Aberystwyth ; UK
  2. Environmental Health and Ecological Sciences ; Ifakara Health Institute ; Ifakara ; United Republic of Tanzania
  3. Department of Epidemiology and Public Health ; Swiss Tropical and Public Health Institute ; Basel ; Switzerland
  4. Vector Biology Department ; Liverpool School of Tropical Medicine ; Liverpool ; UK
  5. Zanzibar Malaria Elimination Program ; Zanzibar ; United Republic of Tanzania
  6. School of Geography ; University of Leeds ; Leeds ; UK
  7. Institute of Biological ; Environmental and Rural Sciences ; Aberystwyth University ; Aberystwyth ; UK
  
• 关键词：Mosquito breeding habitat ; Malaria ; Larval source management ; Hydrology ; Geomorphology ; Geology
• 刊名：Parasites & Vectors
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：8
• 期：1
• 全文大小：1,790 KB
• 参考文献：1. Ferguson H, Domhaus A, Beeche A, Borgemeister C, Gottlieb M, Mulla M, et al. Ecology: a prerequisite for malaria elimination and eradication. PLoS Med. 2010;7(8):1鈥?. CrossRef
  2. Ndenga BA, Simbauni JA, Mbugi JP, Githeko AK, Fillinger U. Productivity of malaria vectors from different habitat types in the Western Kenya highlands. PLoS One. 2011;6(4):e19473. CrossRef
  3. Gouagna LC, Rakotondranary M, Boyer S, Lemperiere G, Dehecq JS, Fontenille D. Abiotic and biotic factors associated with the presence of Anopheles arabiensis immatures and their abundance in naturally occurring and man-made aquatic habitats. Parasites Vectors. 2012;5(1):96. CrossRef
  4. Imbahale SS, Githeko A, Mukabana WR, Takken W. Integrated mosquito larval source management reduces larval numbers in two highland villages in western Kenya. BMC Public Health. 2012;12(1):362. CrossRef
  5. Zhou G, Munga S, Minakawa N, Githeko AK, Yan G. Spatial relationship between adult malaria vector abundance and environmental factors in western Kenya highlands. Am J Trop Med Hyg. 2007;77(1):29鈥?5.
  6. Killeen GF, Seyoum AK, Knols BGJ. Rationalizing Historical successes of malaria control in Africa in terms of mosquito resource availability management. Am J Trop Med Hyg. 2004;71(2 suppl):87鈥?3.
  7. Fillinger U, Lindsay SW. Suppression of exposure to malaria vectors by an order of magnitude using microbial larvicides in rural Kenya. Trop Med Int Health. 2006;11(11):1629鈥?2. CrossRef
  8. Mbare O, Lindsay S, Fillinger U. Aquatain(R) Mosquito Formulation (AMF) for the control of immature Anopheles gambiae sensu stricto and Anopheles arabiensis: dose-responses, persistence and sub-lethal effects. Parasites Vectors. 2014;7(1):438. CrossRef
  9. Haji KA, Khatib BO, Smith S, Ali AS, Devine GJ, Coetzee M, et al. Challenges for malaria elimination in Zanzibar: pyrethroid resistance in malaria vectors and poor performance of long-lasting insecticide nets. Parasites Vectors. 2013;6(1):82. CrossRef
  10. Zanzibar Malaria Control Programme. Zanzibar malaria epidemic early detection system biannual report. 2011.
  11. Smith DL, Perkins TA, Tusting LS, Scott TW, Lindsay SW. Mosquito population regulation and larval source management in heterogeneous environments. PLoS One. 2013;8(8):e71247. CrossRef
  12. Hardy AJ, Gamarra JGP, Cross DE, Macklin MG, Smith MW, Kihonda J, et al. Habitat hydrology and geomorphology control the distribution of malaria vector larvae in Rural Africa. PLoS One. 2013;8(12):1鈥?3. CrossRef
  13. Smith MW, Macklin MG, Thomas CJ. Hydrological and geomorphological controls of malaria transmission. Earth Sci Rev. 2013;116:109鈥?7. CrossRef
  14. Amerasinghe PH, Amerasinghe FP, Konradsen F, Fonseka KT, Wirtz RA. Malaria vectors in a traditional dry zone village in Sri Lanka. Am J Trop Med Hyg. 1999;60(3):421鈥?.
  15. Mutuku FM, Alaii JA, Bayoh MN, Gimnig JE, Vulule JM, Walker ED, et al. Distribution, description, and local knowledge of larval habitats of / Anopheles Gambiae s.l. in a village in Western Kenya. Am J Trop Med Hyg. 2006;74(1):44鈥?3.
  16. Oesterholt M, Bousema J, Mwerinde O, Harris C, Lushino P, Masokoto A, et al. Spatial and temporal variation in malaria transmission in a low endemicity area in northern Tanzania. Malar J. 2006;5(1):98. CrossRef
  17. Van Der Hoek W, Konradsen F, Amerasinghe PH, Perera D, Piyaratne M, Amerasinghe FP. Towards a risk map of malaria for Sri Lanka: the importance of house location relative to vector breeding sites. Int J Epidemiol. 2003;32(2):280鈥?. CrossRef
  18. B酶gh C, Lindsay SW, Clarke SE, Dean A, Jawara M, Pinder M, et al. High spatial resolution mapping of malaria transmission risk in the Gambia, West Africa, using Landsat TM satellite imagery. Am J Trop Med Hyg. 2007;76(5):875鈥?1.
  19. Thomas CJ, Cross DE, B酶gh C. Landscape movements of anopheles gambiae malaria vector mosquitoes in Rural Gambia. PLoS One. 2013;8(7):e68679. CrossRef
  20. Bomblies A. Modeling the role of rainfall patterns in seasonal malaria transmission. Climatic Change. 2012;112(3鈥?):673鈥?5. CrossRef
  21. Dobson M. 鈥淢arsh fever鈥濃€攖he geography of malaria in England. J Hist Geogr. 1980;6(4):357鈥?9. CrossRef
  22. Staedke SG, Nottingham EW, Cox J, Kamya MR, Rosenthal PJ, Dorsey G. Short report: proximity to mosquito breeding sites as a risk factor for clinical malaria episodes in an urban cohort of Ugandan children. Am J Trop Med Hyg. 2003;69(3):244鈥?.
  23. Ernst KC, Lindblade KA, Koech D, Sumba PO, Kuwuor DO, John CC, et al. Environmental, socio鈥恉emographic and behavioural determinants of malaria risk in the western Kenyan highlands: a case鈥揷ontrol study. Trop Med Int Health. 2009;14(10):1258鈥?5. CrossRef
  24. Protopopoff N, Van Bortel W, Marcotty T, Van Herp M, Maes P, Baza D, et al. Spatial targeted vector control in the highlands of Burundi and its impact on malaria transmission. Malar J. 2007;6(1):158. CrossRef
  25. Balls MJ, B酶dker R, Thomas CJ, Kisinza W, Msangeni HA, Lindsay SW. Effect of topography on the risk of malaria infection in the Usambara Mountains, Tanzania. Trans R Soc Trop Med Hyg. 2004;98(7):400鈥?. CrossRef
  26. Cohen J, Ernst C, Lindblade K, Vulule J, John C, Wilson M. Local topographic wetness indices predict household malaria risk better than land-use and land-cover in the western Kenya highlands. Malar J. 2010;9(328):1鈥?0.
  27. Minakawa N, Seda P, Yan G. Influence of host and larval habitat distribution on the abundance of African malaria vectors in western Kenya. Am J Trop Med Hyg. 2002;67(1):32鈥?.
  28. Minakawa N, Munga S, Atieli F, Mushinzimana E, Zhou G, Githeko AK, et al. Spatial distribution of anopheline larval habitats in Western Kenyan highlands: effects of land cover types and topography. Am J Trop Med Hyg. 2005;73(1):157鈥?5.
  29. Hewlett JD, Hibbert AR. Factors affecting the response of small watersheds to precipitation in humid areas. In: Sopper WE, Lull HW, editors. International symposium on forest hydrology. Oxford: Pergammon; 1967. p. 275鈥?0.
  30. Kobayashi J, Nambanya S, Miyagi I, Vanachone B, Manivong K, Koubouchan T, et al. Collection of anopheline mosquitos in three villages endemic for malaria in Khammouane, Lao PDR. Southeast Asian J Trop Med Public Health. 1997;28:615鈥?0.
  31. Obsomer V, Defourny P, Coosemans M. The Anopheles dirus complex: spatial distribution and environmental drivers. Malar J. 2007;6(1):26. CrossRef
  32. Toma T, Miyagi I, Okazawa T, Kobayashi J, Saita S, Tuzuki A, et al. Entomological surveys on malaria in Khammouane Province, Lao PDR, in 1999 and 2000. Southeast Asian J Trop Med Public Health. 2002;33(3):532鈥?6.
  33. Manguin S, Garros C, Dusfour I, Harbach R, Coosemans M. Bionomics, taxonomy, and distribution of the major malaria vector taxa of Anopheles subgenus Cellia in Southeast Asia: an updated review. Infect Genet Evol. 2008;8(4):489鈥?03. CrossRef
  34. O'Loughlin S, Somboon P, Walton C. High levels of population structure caused by habitat islands in the malarial vector / Anopheles scanloni. Heredity. 2007;99(1):31鈥?0. CrossRef
  35. Bugoro H, Cooper RD, Butafa C, Iro'ofa C, Mackenzie DO, Chen C-C, et al. Bionomics of the malaria vector Anopheles farauti in Temotu Province, Solomon Islands: issues for malaria elimination. Malar J. 2011;10:133. CrossRef
  36. Mwangangi JM, Mbogo CM, Orindi BO, Muturi EJ, Midega JT, Nzovu J, et al. Shifts in malaria vector species composition and transmission dynamics along the Kenyan coast over the past 20聽years. Malar J. 2013;12:13. CrossRef
  37. Summerfield MA. Global geomorphology: an introduction to the study of landforms: Longman Scientific & Technical. Wiley; 1991.
  38. Sweeting M. Karst landforms. London: The Macmillan Press Ltd; 1972.
  39. Ford DC, Williams P. Karst hydrogeology and geomorphology. Chichester: John Wiley & Sons; 2007. CrossRef
  40. Pi帽ol J, Beven K, Freer J. Modelling the hydrological response of Mediterranean catchments, Prades. Catalonia. The use of distributed models as aids to hypothesis formulation. Hydrol Processes. 1997;11(9):1287鈥?06. CrossRef
  41. Johnson J. A review of the hydrogeology of Zanzibar (Tanzania). New York: United Nations; 1984.
  42. Siex KS, Struhsaker TT. Ecology of the Zanzibar red colobus monkey: demographic variability and habitat stability. Int J Primatol. 1999;20(2):163鈥?2. CrossRef
  43. Sikat L. Assessing the spatial and temporal characteristics of groundwater recharge in Zanzibar: towards the optimal management of grounwater resources. Twente, The Netherlands: University of Twente; 2011.
  44. Bousema T, Drakeley C, Gesase S, Hashim R, Magesa S, Mosha F, et al. Identification of hot spots of malaria transmission for targeted malaria control. J Infect Dis. 2010;201(11):1764鈥?4. CrossRef
  45. Colbert G, Wagner BH, Pinther M. Hydrogeological map of Zanzibar. New York, USA: United Nations; 1987.
  46. Hettige ML. Land evaluation and land suitability classification - Unguja and Pemba islands. Rome: UN Food and Agricultural Organisation; 1990.
  47. Earth Explorer [http://earthexplorer.usgs.gov]
  48. ESRI. ArcGIS desktop: release 10.2.1. Redlands, CA: Environmental Systems Research Institute; 2013.
  49. Costantini C, LI SG, Torre AD, Sagnon NF, Coluzzi M, Taylor CE. Density, survival and dispersal of Anopheles gambiae complex mosquitoes in a West African Sudan savanna village. Med Vet Entomol. 1996;10(3):203鈥?9. CrossRef
  50. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2012.
  51. Hijmans RJ, Phillips S, Leathwick J, Elith J. Species distribution modeling. R package version 0.8-11. 2013.
  52. Buston PM, Elith J. Determinants of reproductive success in dominant pairs of clownfish: a boosted regression tree analysis. J Anim Ecol. 2011;80(3):528鈥?8. CrossRef
  53. Leathwick J, Elith J, Francis M, Hastie T, Taylor P. Variation in demersal fish species richness in the oceans surrounding New Zealand: an analysis using boosted regression trees. Mar Ecol Prog Ser. 2006;321:267鈥?1. CrossRef
  54. Sinka ME, Bangs MJ, Manguin S, Coetzee M, Mbogo CM, Hemingway J, et al. The dominant Anopheles vectors of human malaria in Africa, Europe and the Middle East: occurrence data, distribution maps and bionomic pr茅cis. Parasites Vectors. 2010;3:117. CrossRef
  55. Whittingham MJ, Stephens PA, Bradbury RB, Freckleton RP. Why do we still use stepwise modelling in ecology and behaviour? J Anim Ecol. 2006;75(5):1182鈥?. CrossRef
  56. Elith J, Leathwick JR, Hastie T. A working guide to boosted regression trees. J Anim Ecol. 2008;77(4):802鈥?3. CrossRef
  57. Burnham KP, Anderson DR. Model selection and multi-model inference: a practical information-theoretic approach. Verlag: Springer; 2002.
  58. Friedman JH, Meulman JJ. Multiple additive regression trees with application in epidemiology. Stat Med. 2003;22(9):1365鈥?1. CrossRef
  59. Clifford P, Richardson S, Hemon D. Corrected Pearson鈥檚 correlation for spatial autocorrelation. Biometrics. 1989;49:305鈥?4.
  60. Osorio F, Vallejos R. Package for analysis of spatial data. R package version 0.2. 2012.
  61. Vuai S. Geochemical characteristics of spaleotherm formation in caves from Zanzibar Island, Tanzania. vol. 1: OMICS; 2012: 1-5.
  62. Paaijmans KP, Wandago MO, Githeko AK, Takken W. Unexpected high losses of Anopheles gambiae larvae due to rainfall. PLoS One. 2007;2(11):e1146. CrossRef
  63. Gillies MT, De Meillon B. The Anophelinae of Africa South of the Sahara. Johannesburg: South African Institute for Medical Research; 1968.
  64. Thomas C, Lindsay S. Local-scale variation in malaria infection amongst rural Gambian children estimated by satellite remote sensing. Trans R Soc Trop Med Hyg. 2000;94(2):159鈥?3. CrossRef
  65. Moynihan MA, Baker DM, Mmochi AJ. Isotopic and microbial indicators of sewage pollution from Stone Town, Zanzibar, Tanzania. Mar Pollut Bull. 2012;64(7):1348鈥?5. CrossRef
  66. Sattler MA, Mtasiwa D, Kiama M, Premji Z, Tanner M, Killeen GF, et al. Habitat characterization and spatial distribution of Anopheles sp. mosquito larvae in Dar es Salaam (Tanzania) during an extended dry period. Malar J. 2005;4(1):4. CrossRef
  67. Bejon P, Williams T, Liljander A, Noor A, Wambua J, Ogada E, et al. Stable and unstable malaria hotspots in longitudinal cohort studies in Kenya. PLoS Med. 2010;7(7):1鈥?4. CrossRef
  68. Bousema T, Griffin JT, Sauerwein RW, Smith DL, Churcher TS, Takken W, et al. Hitting hotspots: spatial targeting of malaria for control and elimination. PLoS Med. 2012;9(1):e1001165. CrossRef
  69. Ijumba J, Shenton F, Clarke S, Mosha F, Lindsay S. Irrigated crop production is associated with less malaria than traditional agricultural practices in Tanzania. Trans R Soc Trop Med Hyg. 2002;96(5):476鈥?0. CrossRef
  70. Ijumba J, Lindsay S. Impact of irrigation on malaria in Africa: paddies paradox. Med Vet Entomol. 2001;15(1):1鈥?1. CrossRef
  71. Dunn CE, Le Mare A, Makungu C. Malaria risk behaviours, socio-cultural practices and rural livelihoods in southern Tanzania: implications for bednet usage. Soc Sci Med. 2011;72(3):408鈥?7. CrossRef
  72. Killeen GF. A second chance to tackle African malaria vector mosquitoes that avoid houses and don鈥檛 take drugs. Am J Trop Med Hyg. 2013;88(5):809鈥?6. CrossRef
  73. Alonso PL, Bassat Q, Binka F, Brewer T, Chandra R, Culpepper J, et al. A research agenda for malaria eradication: drugs. PLoS Med. 2010;8(1):1鈥?.
  74. Washino RK, Wood BL. Application of remote sensing to vector arthropod surveillance and control. Am J Trop Med Hyg. 1993;50:134鈥?4.
  75. Zanzibar Malaria Control Programme. Zanzibar malaria epidemic early detection system biannual report. 2009.
  76. Sidle RC, Ziegler AD, Negishi JN, Nik AR, Siew R, Turkelboom F. Erosion processes in steep terrain - truths, myths, and uncertainties related to forest management in Southeast Asia. Forest Ecol Manag. 2006;224(1鈥?):199鈥?25. CrossRef
  77. O'Sullivan L, Jardine A, Cook A, Weinstein P. Deforestation, mosquitoes, and ancient Rome: lessons for today. Bioscience. 2008;58(8):756鈥?0. CrossRef
  78. Angel JL. Ecology and population in the eastern Mediterranean. World Archaeol. 1972;4(1):88鈥?05. CrossRef
  79. Vittor AY, Gilman RH, Tielsch J, Glass G, Shields T, Lozano WS, et al. The effect of deforestation on the human-biting rate of Anopheles darlingi, the primary vector of falciparum malaria in the Peruvian Amazon. Am J Trop Med Hyg. 2006;74(1):3鈥?1.
  80. Yasuoka J, Levins R. Impact of deforestation and agricultural development on anopheline ecology and malaria epidemiology. Am J Trop Med Hyg. 2007;76(3):450鈥?0.
  81. Pattanayak S, Dickinson K, Corey C, Murray B, Sills E, Kramer R. Deforestation, malaria, and poverty: a call for transdisciplinary research to support the design of cross-sectoral policies. Sustainability. 2006;2(2):45鈥?6.
  82. Kipyab P, Khaemba B, Mwangangi J, Mbogo C. The bionomics of Anopheles merus (Diptera: Culicidae) along the Kenyan coast. Parasites Vectors. 2013;6(1):37. CrossRef
  83. Tatem AJ, Qiu Y, Smith DL, Sabot O, Ali AS, Moonen B. The use of mobile phone data for the estimation of the travel patterns and imported Plasmodium falciparum rates among Zanzibar residents. Malar J. 2009;8:287. CrossRef
  84. B酶gh C, Clarke S, Jawara M, Thomas C, Lindsay S. Localized breeding of the Anopheles gambiae complex (Diptera: Culicidae) along the River Gambia, West Africa. Bull Entomol Res. 2003;93(4):279鈥?7. CrossRef
  85. Steketee RW, Sipilanyambe N, Chimumbwa J, Banda JJ, Mohamed A, Miller J, et al. National malaria control and scaling up for impact: the Zambia experience through 2006. Am J Trop Med Hyg. 2008;79(1):45鈥?2.
  86. Kelly GC, Hii J, Batarii W, Donald W, Hale E, Nausien J, et al. Modern geographical reconnaissance of target populations in malaria elimination zones. Malar J. 2010;9:289. CrossRef
  
• 刊物主题：Parasitology; Infectious Diseases; Tropical Medicine; Entomology;
• 出版者：BioMed Central
• ISSN：1756-3305

文摘

Background Larval source management strategies can play an important role in malaria elimination programmes, especially for tackling outdoor biting species and for eliminating parasite and vector populations when they are most vulnerable during the dry season. Effective larval source management requires tools for identifying geographic foci of vector proliferation and malaria transmission where these efforts may be concentrated. Previous studies have relied on surface topographic wetness to indicate hydrological potential for vector breeding sites, but this is unsuitable for karst (limestone) landscapes such as Zanzibar where water flow, especially in the dry season, is subterranean and not controlled by surface topography. Methods We examine the relationship between dry and wet season spatial patterns of diagnostic positivity rates of malaria infection amongst patients reporting to health facilities on Unguja, Zanzibar, with the physical geography of the island, including land cover, elevation, slope angle, hydrology, geology and geomorphology in order to identify transmission hot spots using Boosted Regression Trees (BRT) analysis. Results The distribution of both wet and dry season malaria infection rates can be predicted using freely available static data, such as elevation and geology. Specifically, high infection rates in the central and southeast regions of the island coincide with outcrops of hard dense limestone which cause locally elevated water tables and the location of dolines (shallow depressions plugged with fine-grained material promoting the persistence of shallow water bodies). Conclusions This analysis provides a tractable tool for the identification of malaria hotspots which incorporates subterranean hydrology, which can be used to target larval source management strategies.