Topographic models for predicting malaria vector breeding habitats: Potential tools for vector control managers

Parasites and Vectors

Volumn 6, Issue 1, 2013, Pages

  Nmor, Jephtha C ^a,b   Sunahara, Toshihiko ^a   Goto, Kensuke ^a   Futami, Kyoko ^a   Sonye, George ^c   Akweywa, Peter ^d   Dida, Gabriel ^e   Minakawa, Noboru ^a  

^a NAGASAKI UNIVERSITY   (Japan)

^b DELTA STATE UNIVERSITY   (Nigeria)

^c Ability to Solve by Knowledge   (Kenya)

^d KENYA MEDICAL RESEARCH INSTITUTE   (Kenya)

^e MASENO UNIVERSITY   (Kenya)

Author keywords

Africa; Anopheles; Breeding habitats; Kenya; Malaria; Prediction; Topographic models

Indexed keywords

ANOPHELES; ARTICLE; BREEDING; HABITAT; KENYA; LARVA; MALARIA; NONHUMAN; PARASITE VECTOR; PREDICTIVE VALUE; RADIATION DETECTOR; SENSITIVITY AND SPECIFICITY; SWAMP; TOPOGRAPHY; VECTOR CONTROL;

AFRICA; ANIMALS; ANOPHELES; DATA COLLECTION; ECOSYSTEM; GEOGRAPHIC INFORMATION SYSTEMS; GEOGRAPHY; HUMANS; INSECT VECTORS; KENYA; LARVA; LOGISTIC MODELS; MALARIA; MODELS, THEORETICAL; MOSQUITO CONTROL; REMOTE SENSING TECHNOLOGY; REPRODUCIBILITY OF RESULTS; SEASONS;

EID: 84872200847     PISSN: None     EISSN: 17563305     Source Type: Journal    
DOI: 10.1186/1756-3305-6-14     Document Type: Article

References (56)

1. Changes in the burden of malaria in sub-Saharan Africa. O'Meara WP, Mangeni JN, Steketee R, Greenwood B, Lancet Infect Dis 2010 10 8 545 555 10.1016/S1473-3099(10)70096-7 20637696
2. Larval source management for malaria control in Africa: myths and reality. Fillinger U, Lindsay SW, Malaria J 2011 10 353 10.1186/1475-2875-10-353
3. Integrated vector management for malaria control. Beier J, Keating J, Githure J, Macdonald M, Impoinvil D, Novak R, Malaria J 2008 7 1 4 10.1186/1475-2875-7-4
4. Surveillance of vector populations and malaria transmission during the 2009/10 El Niño event in the western Kenya highlands: opportunities for early detection of malaria hyper-transmission. Ototo EN, Githeko AK, Wanjala CL, Scott TW, Parasit Vectors 2011 4 144 10.1186/1756-3305-4-144 21781291
5. Integrated malaria vector control with microbial larvicides and insecticide treated nets in the western Kenyan highlands: a controlled trial. Fillinger U, Ndegwa B, Githeko A, Lindsay SW, Bull World Health Organ 2009 87 655 665 10.2471/BLT.08.055632 19784445
6. Temporal and spatial stability of Anopheles gambiae larval habitat distribution in Western Kenya highlands. Li L, Ling B, Laith Y, Guofa Z, Guiyun Y, Int J Health Geogr 2009 8 70 10.1186/1476-072X-8-70 20021640
7. Analysing the generality of spatially predictive mosquito habitat models. Li L, Bian L, Yakob L, Zhou G, Yan G, Acta Trop 2011 119 1 30 37 10.1016/j.actatropica.2011.04.003 21527240
8. Modelling the impact of vector control interventions on Anopheles gambiae population dynamics. Michael TW, Jamie TG, Thomas SC, Neil MF, Maria-Gloria B, Azra CG, Parasit Vectors 2011 4 153 10.1186/1756-3305-4-153 21798055
9. Spatial and temporal distribution patterns of Anopheles arabiensis breeding sites in La Reunion Island-multi-year trend analysis of historical records from 1996-2009. Gouagna LC, Dehecq JS, Girod R, Boyer S, Lempérière G, Fontenille D, Parasit Vectors 2011 4 121 10.1186/1756-3305-4-121 21708013
10. Malaria transmission after five years of vector control on Bioko Island, Equatorial Guinea. Overgaard HJ, Reddy VP, Abaga S, Matias A, Reddy MR, Kulkarni V, Schwabe C, Segura L, Kleinschmidt I, Slotman MA, Parasit Vectors 2012 5 253 10.1186/1756-3305-5-253 23146423
11. Abundance and dynamics of anopheline larvae in a highland malarious area of south-central Ethiopia. Animut A, Gebre-Michael T, Balkew M, Lindtjørn B, Parasit Vectors 2012 5 117 10.1186/1756-3305-5-117 22695178
12. Landscape determinants and remote sensing of anopheline mosquito larval habitats in the western Kenya highlands. Mushinzimana E, Munga S, Minakawa N, Li L, Feng CC, Bian L, Kitron U, Schmidt C, Beck L, Zhou G, Githeko AK, Yan G, Malaria J 2006 5 13 10.1186/1475-2875-5-13
13. Identifying malaria vector breeding habitats with remote sensing data and terrain-based landscape indices in Zambia. Clennon JA, Kamanga A, Musapa M, Shiff C, Glass GE, Int J Health Geogr 2010 9 58 10.1186/1476-072X-9-58 21050496
14. Local topographic wetness indices predict household malaria risk better than land-use and land-cover in the western Kenya highlands. Cohen JM, Ernst KC, Lindblade KA, Vulule JM, John CC, Wilson ML, Malaria J 2010 9 328 10.1186/1475-2875-9-328
15. Use of remote sensing to identify spatial risk factors for malaria in a region of declining transmission: a cross-sectional and longitudinal community survey. Moss WJ, Hamapumbu H, Kobayashi T, Shields T, Kamanga A, Clennon J, Mharakurwa S, Thuma PE, Gregory G, Malaria J 2011 10 163 10.1186/1475-2875-10- 163
16. Topography-derived wetness indices are associated with household-level malaria risk in two communities in the western Kenyan highlands. Cohen JM, Ernst KC, Lindblade KA, Vulule JM, John CC, Wilson ML, Malaria J 2008 7 40 10.1186/1475-2875-7-40
17. Topography as a modifier of breeding habitats and concurrent vulnerability to malaria risk in the western Kenya highlands. Atieli HE, Zhou G, Lee M, Kweka EJ, Afrane Y, Mwanzo I, Githeko AK, Yan G, Parasit Vectors 2011 4 241 10.1186/1756-3305-4-241 22196078
18. An exploratory study of community factors relevant for participatory malaria control on Rusinga Island, western Kenya. Opiyo P, Mukabana WR, Kiche I, Mathenge E, Killeen GF, Fillinger U, Malaria J 2007 6 48 10.1186/1475-2875-6-48
19. Spatial distribution and habitat characterization of anopheline mosquito larvae in Western Kenya. Minakawa N, Mutero CM, Githure JI, Beier JC, Yan G, AmJTrop Med Hyg 1999 61 1010 1016
20. Influence of host and larval habitat distribution on the abundance of African malaria vectors in western Kenya. Minakawa N, Seda P, Yan G, AmJTrop Med Hyg 2002 67 1 32 38
21. The practical importance of permanent and semipermanent habitats for controlling aquatic stages of Anopheles gambiae sensu lato mosquitoes: operational observation from a rural town in western Kenya. Fillinger U, Sonye G, Killeen GF, Knols BGJ, Becher N, Trop Med Int Health 2004 9 1274 1289 10.1111/j.1365-3156.2004.01335.x 15598259
22. Malaria Vectors in Lake Victoria and adjacent habitats in western Kenya. Minakawa N, Dida GO, Sonye GO, Futami K, Njenga SM, PLoS One 2012 7 3 32725 10.1371/journal.pone.0032725 22412913
23. Spatial and temporal dynamics of malaria transmission in rural Western Kenya. Amek N, Bayoh N, Hamel M, Lindblade KA, Gimnig JE, Odhiambo F, Laserson KF, Slutsker L, Smith T, Vounatsou P, Parasit Vectors 2012 5 86 10.1186/1756-3305-5-86 22541138
24. The Shuttle Radar Topography Mission (SRTM) http://www2.jpl.nasa.gov/ srtm/ (Accessed last on July, 2012)
25. The Advanced Spaceborne Thermal Emission Reflection Radiometer Global DEM (ASTER GDEM) http://www.gdem.aster.ersdac.or.jp/ (Accessed last on July, 2012)
26. SAGA, System for Automated Geoscientific Analyses http://www.saga-gis. org/en/index.html (accessed last on Novermber, 2010)
27. Alternative methods for predicting species distribution: an illustration with Himalayan river birds. Manel S, Dias JM, Buckton ST, Ormerod SJ, J of Appl Eco 1999 36 734 747 10.1046/j.1365-2664.1999.00440.x
28. Predicting gray wolf landscape recolonization: logistic regression models vs. new field data. Mladenoff DJ, Sickley TA, Wydeven AP, Eco Appl 1999 9 37 44 10.1890/1051-0761(1999)009[0037:PGWLRL]2.0.CO;2
29. Selecting pseudo-absences for species distribution models: how, where and how many? Barbet-Massin M, Jiguet F, Albert CH, Thuiller W, Method Ecol Evol 2012 3 327 338 10.1111/j.2041-210X.2011.00172.x
30. Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data. Wisz MS, Guisan A, BMC Ecol 2009 9 8 10.1186/1472-6785-9-8 19393082
31. Maximum entropy modeling of species geographic distributions. Phillips SJ, Anderson RP, Schapire RE, Ecol Modell 2006 190 231 259 10.1016/j.ecolmodel. 2005.03.026
32. Selecting pseudo-absence data for presence-only distribution modeling: How far should you stray from what you know? VanDerWal J, Shoo LP, Graham C, Williams SE, Ecol modell 2009 220 589 594 10.1016/j.ecolmodel.2008.11.010
33. A fast, simple and versatile algorithm to fill the depressions of digital elevation models. Planchon O, Darboux F, Catena 2001 46 159 176
34. Soil attribute prediction using terrain analysis. Moore ID, Gessler PE, Nielsen GA, Peterson GA, Soil Sci Soc Am J 1993 57 443 452 10.2136/sssaj1993. 03615995005700020026x
35. Gorsevski PV, Gessler P, Foltz RB, Spatial Prediction of Landslide Hazard Using Logistic Regression and GIS Banff, Alberta, Canada: 4th International Conference on Integrating GIS and Environmental Modeling (GIS/EM4): Problems, Prospects and Research Needs 2000 http://www.colorado.edu/research/cires/banff/ pubpapers/110/ accessed online on September 17, 2011)
36. An evaluation of methods to determine slope using digital elevation data. Warren SD, Hohmann MG, Auerswald K, Mitasova H, Catena 2004 58 215 233 10.1016/j.catena.2004.05.001
37. Topographic partition of watersheds with digital elevation models. Band LE, Water Res Research 1986 22 5 l24 10.1029/WR022i001p00005
38. Plan curvature and landslide probability in regions dominated by earth flows and earth slides. Ohlmacher GC, Engr Geol 2007 91 117 134 10.1016/j.enggeo.2007.01.005
39. Buckley A, Understanding curvature rasters, in imagery, mapping, mapping centre lead http://blogs.esri.com/esri/arcgis. (Accessed last on May, 2012)
40. Olaf C, Convergence Index 2001 http://sourceforge.net/apps/trac/sagagis/ wiki/ta-morphometry-1 (Accessed last on June, 2012)
41. Comparison of DEM data capture and topographic wetness indices. Schmidt F, Persson A, Preci Agric 2003 4 179 192 10.1023/A:1024509322709
42. Weiss A, Topographic position and landforms analysis San Diego, CA: In ESRI User 2001
43. Comparing discriminant analysis, neural networks and logistic regression for predicting species distributions: a case study with a Himalayan river bird. Manel S, Dias JM, Ormerod SJ, Ecol Modell 1999 120 337 347 10.1016/S0304- 3800(99)00113-1
44. Modelling the distribution of Palsas in Finnish Lapland with logistic regression and GIS. Luoto M, Seppala M, Perma Periglac Pro 2002 13 17 28 10.1002/ppp.404
45. Hosmer DW, Lemeshow S, Applied logistic regression New York, USA: John Wiley and Sons 2000
46. R Development Core Team, R: a language and environment for statistical computing Vienna, Austria: R Foundation for Statistical Computing 2008 http://www.R-project.org. 010; 34(12)
47. Information Theory and an Extension of the Maximum Likelihood Principle. Akaike H, 2nd International Symposium on Information Theory Budapest: Akademiai Kiado, Petrov BN, Csaki F, 1973 267 281
48. Evaluating the predictive performance of habitat models developed using logistic regression. Pearce J, Ferrier S, Ecol Modell 2000 133 225 245 10.1016/S0304-3800(00)00322-7
49. Evaluating presence-absence models in ecology: the need to account for prevalence. Manel S, Williams HC, Ormerod SJ, J Appl Ecol 2001 38 921 931
50. A review of methods for the assessment of prediction errors in conservation presence/absence models. Fielding AH, Bell JF, Environ Conserv 1997 24 38 49 10.1017/S0376892997000088
51. Effects of species' ecology on the accuracy of distribution models. McPherson JM, Jetz W, Ecography 2007 30 135 151
52. Stevenson M, Nunes T, Sanchez J, Thornton R, Reiczigel J, Robison-Cox J, Sebastiani P, An R package for the analysis of epidemiological data version 0.9 2012 http://cran.r-project.org/web/packages/epiR/epiR.pdf
53. The falling lake Victoria water level: GRACE, TRIMM and CHAMP satellite analysis of the lake basin. Awange JL, Sharifi MA, Ogonda G, Wickert J, Grafarend EW, Omulo MA, Water Res Manage 2008 22 775 796 10.1007/s11269-007- 9191-y
54. The effects of oviposition-site deprivation on Anopheles gambiae reproduction. Dieter KL, Huestis DL, Lehmann T, Parasit Vectors 2012 5 235 10.1186/1756-3305-5-235 23072301
55. Spatial relationship between adult malaria vector abundance and environmental factors in Western Kenya highlands. Zhou G, Munga S, Minakawa N, Githeko AK, Yan G, Am J of Tropi Med and Hyg 2007 77 29 35
56. High resolution niche models of malaria vectors in northern Tanzania: a New capacity to predict malaria risk? Kulkarni MA, Desrochers RE, Kerr JT, PLoS One 2010 5 2 9396 10.1371/journal.pone.0009396 20195366