A global model of malaria climate sensitivity: Comparing malaria response to historic climate data based on simulation and officially reported malaria incidence

Malaria Journal

Volumn 11, Issue , 2012, Pages

  Edlund, Stefan ^a   Davis, Matthew ^a   Douglas, Judith V ^a   Kershenbaum, Arik ^b   Waraporn, Narongrit ^c   Lessler, Justin ^d   Kaufman, James H ^a  

^a IBM ALMADEN RESEARCH CENTER   (United States)

^b UNIVERSITY OF HAIFA   (Israel)

^c KING MONGKUT'S UNIVERSITY OF TECHNOLOGY THONBURI   (Thailand)

^d JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

Anopheles; Climate data; High resolution data; Incidence; Macdonald Ross compartmental disease models; Malaria; Simulation

Indexed keywords

ANOPHELES; ARTICLE; CLIMATE CHANGE; DISEASE CARRIER; DISEASE MODEL; DISEASE TRANSMISSION; HUMAN; INCIDENCE; INTERMETHOD COMPARISON; LAND BIOME; MACDONALD ROSS COMPARTMENTAL DISEASE MODEL; MALARIA; NONHUMAN; PRECIPITATION; SEASONAL VARIATION; SIMULATION; SPATIOTEMPORAL EPIDEMIOLOGICAL MODELLER; TEMPERATURE; WORLD HEALTH ORGANIZATION;

ANIMALS; ANOPHELES; CLIMATE CHANGE; DISEASE VECTORS; HUMANS; INCIDENCE; MALARIA; MODELS, STATISTICAL; WORLD HEALTH;

EID: 84866296560     PISSN: None     EISSN: 14752875     Source Type: Journal    
DOI: 10.1186/1475-2875-11-331     Document Type: Article

References (57)

1. WHO, World Malaria Report 2010 Geneva: World Health Organization 2010
2. WHO, World Malaria Report 2008 Geneva: World Health Organization 2008
3. Ross R, The Prevention of Malaria London: Murray 2 1911
4. Macdonald G, The Epidemiology and Control of Malaria London: Oxford University Press 1957
5. The population dynamics of malaria. Aron JL, May RM, Population Dynamics of Infectious Diseases: Theory and Application London: Chapman and Hall, Anderson RM, 1982 139 179
6. The malaria atlas project: developing global maps of malaria risk. Hay SI, Snow RW, PLoS Med 2006 3 473 10.1371/journal.pmed.0030473 17147467
7. Malaria eradication back on the table? Tanner M, de Savigny D, Bull World Health Organ 2008 86 82 83 10.2471/BLT.07.050633 18297155
8. Sachs JD, A new global effort to control malaria. Department of Economics discussion paper #:0203-11 New York: Columbia University Department of Economics 2002
9. WHO, Malaria control in countries where time-limited eradication is impracticable at present. Report of a WHO interregional conference Geneva: World Health Organization 1974
10. A new global commitment to disease control in Africa. Sachs JD, Nat Med 2001 7 521 523 10.1038/87830 11329042
11. Artemisinin resistance: current status and scenarios for containment. Dondorp AM, Yeung S, White L, Nguon C, Day NPJ, Socheat D, von Seidlein L, Nat Rev Microbiol 2010 8 272 280 20208550
12. Climate change and vector-borne diseases: a global modelling perspective. Martens WJM, Jetten TH, Rotmans J, Niessen LW, Glob Environ Change 1995 5 195 209 10.1016/0959-3780(95)00051-O
13. Estimating the global clinical burden of Plasmodium falciparum malaria in 2007. Hay SI, Okiro EA, Gething PW, Patil AP, Tatem AJ, Guerra CA, Snow RW, PLoS Med 2010 7 1000290 10.1371/journal.pmed.1000290 20563310
14. A climate-based distribution model of malaria transmission in sub-Saharan Africa. Craig MH, Snow RW, le Sueur D, Parasitol Today 1999 15 105 111 10.1016/S0169-4758(99)01396-4 10322323
15. Web-based climate information resources for malaria control in Africa. Grover-Kopec EK, Blumenthal MB, Ceccato P, Dinku T, Omumbo JA, Connor SJ, Malar J 2006 5 38 10.1186/1475-2875-5-38 16689992
16. Predicting and mapping malaria under climate change scenarios: the potential redistribution of malaria vectors in Africa. Tonnang HEZ, Kangalawe RYM, Yanda PZ, Malar J 2010 9 111 10.1186/1475-2875-9-111 20416059
17. Monitoring vegetation systems in the Great Plains with ERTS. Rouse JW, Haas RH, Schell JA, Deering DW, Proceedings of the Third ERTS-1 Symposium NASA Goddard: NASA SP-351 1974 309 317
18. NASA, Moderate Resolution Imaging Spectroradiometer (Terra/MODIS) http://modis-land.gsfc.nasa.gov
19. MODIS vegetation index (MOD13. Huete A, Justice C, van Leeuwen W, Algorithm theoretical basis document http://modis.gsfc.nasa.gov/data/atbd/atbd- mod13.pdf
20. USGS, Famine Early Warning System (FEWS NET) Data Portal (Africa VCAP model) http://earlywarning.usgs.gov/fews/africa/index.php
21. Connor SJ, The Use of Environmental Information Systems (EIS) for Malaria Control in Africa United Kingdom: University of Liverpool 2002
22. The impact of regional climate change on malaria risk due to greenhouse forcing and land-use changes in tropical Africa. Ermert V, Fink AH, Morse AP, Paeth H, Environ Health Perspectives 2012 120 77 84
23. Hot topic or hot air? Climate change and malaria resurgence in East African highlands. Hay SI, Rogers DJ, Randolph SE, Stern DI, Cox J, Shanks GD, Snow RW, Trends Parasitol 2002 18 530 534 10.1016/S1471-4922(02)02374-7 12482536
24. Association between climate variability and malaria epidemics in the East African highlands. Zhou G, Minakawa N, Githeko AK, Yan G, Proc Natl Acad Sci USA 2004 101 2375 2380 Feb 24 10.1073/pnas.0308714100 14983017
25. Reif F, Fundamentals of Statistical and Thermal Physics New York, NY: McGraw-Hill 1967 261
26. Efron B, Tibshirani RJ, An Introduction to the Bootstrap. CRC Monographs on Statistics & Applied Probability Boca Raton, FL: Chapman & Hall/CRC Press 1993
27. NOAA, Global Land One-Kilometer Base Elevation (GLOBE) Project http://www.ngdc.noaa.gov/mgg/topo/globe.html
28. Comparing three basic models for seasonal influenza. Edlund S, Kaufman J, Lessler J, Douglas J, Bromberg M, Kaufman Z, Bassal R, Chodick G, Marom R, Shalev F, Mesika Y, Ram R, Leventhal A, J Epidemics 2011 3 135 142 10.1016/j.epidem.2011.04.002
29. Evaluation of MODIS land surface temperature data to estimate air temperature in different ecosystems over Africa. Vancutsem C, Ceccato P, Dinku T, Connor SJ, Remote Sensing Environ 2010 114 449 465 10.1016/j.rse.2009.10.002
30. NASA, Earth Observatory (NEO) http://earthobservatory.nasa.gov/
31. Spatio-Temporal Epidemiological Modeller http://www.eclipse.org/stem/
32. Spatio-Temporal Epidemiological Modeller http://wiki.eclipse.org/index. php/STEM
33. Infectious disease modeling: creating a community to respond to biological threats. Kaufman J, Edlund S, Douglas J, Stat Comm Infect Diseases 2009 Vol. 1 No. 1 pp. 1, ISSN 1948-4690. Berkeley Electronic Press
34. Charoenpanyanet A, Anopheles mosquito density predictive model based on remotely sensed data. Doctoral Dissertation Asian Institute of Technology, Bangkok, Thailand 2009
35. Eclipse Public License http://www.eclipse.org/legal/epl-v10.html
36. Mosquito Population Model http://wiki.eclipse.org/Available- Models#Mosquito-Population-Model
37. MacDonald Ross Disease Model http://wiki.eclipse.org/Available- Models#MacDonald-Ross-Disease-Model
38. Anderson RM, May RM, Anderson B, Infectious Diseases of Humans: Dynamics and Control New York: Oxford Science 1991
39. Cameron AC, Trivedi PK, Regression Analysis of Count Data New York: Cambridge University Press 1998
40. Christensen R, Log-Linear Models and Logistic Regression New York: Springer 2 1997
41. A malaria model tested in the African savannah. Dietz K, Molineaux L, Thomas A, Bull WHO 1974 50 347 357 4613512
42. Modelling the effect of control of mosquitoes and treatment on the transmission of Malaria. Tumwiine J, Luboobi LS, Mugisha JYT, Importance of Mathematical Modelling of Biological & Biomedical Process, Luboobi LS, Mugisha JYT, Kasozi, 2004 Series No. 1: 205-218 23082171
43. Modeling malaria as a complex adaptive system. Janssen MA, Martens WJM, Artif Life 1997 3 213 236 10.1162/artl.1997.3.3.213 9385735
44. Molineaux L, Gramiccia G, The Garki project: research on the epidemiology and control of malaria in the Sudan savanna of West Africa Geneva: World Health Organization 1980
45. Baker JR, Parasitic Protozoa London: Hutchinson 1973
46. The assessment of insecticidal impact on the malaria mosquitos vectorial capacity, from data on the proportion of parous females. Carrett-Jones C, Grab B, Bull WHO 1964 31 71 86 14230896
47. Models of spatio-temporal dynamics in malaria. Torres-Sorando L, Rodriguez DJ, Ecol Model 1997 104 231 240 10.1016/S0304-3800(97)00135-X
48. Error measures and the choice of a forecast method. Ahlburg DA, Int J Forecast 1992 8 99e100
49. A new metric for measuring metamodels quality-of-fit for deterministic simulations. Hamad H, Proceedings of the 38th Conference on Winter Simulation New York, NY: ACM Press 2006 882 888
50. Biting behavior and Plasmodium infection rates of Anopheles arabiensis from Sille, Ethiopia. Tayea A, Hadisa M, Adugnaa N, Tilahuna D, Wirtzb RA, Acta Trop 2006 96 50 54
51. Pan American Health Organization, Epidemiological map of malaria by risk levels http://www.paho.org/English/HCP/HCT/malaria-PPTindex.htm
52. Kakkilaya BS, Malaria risk in South America http://www.malariasite.com/ malaria/samerica.htm
53. Centers for Disease Control http://wwwnc.cdc.gov/travel/yellowbook/2012/ chapter-3-infectious-diseases-related-to-travel/yellow-fever-and-malaria- information-by-country.htm
54. World Health Organization, International Travel and Health 2010 http://www.who.int/ith/ITH2010.pdf
55. Inter-Tropical Convergence Zone (ITCZ) and seasonal precipitation http://www.srh.noaa.gov/jetstream/tropics/itcz.htm
56. Climate indices, rainfall onset and retreat, and malaria in Nigeria. Thomson AJ, J Vector Borne Dis 2010 47 193 203 21178211
57. Surface observed global land precipitation variations during 1900-1988. Dai A, Fung IY, Del Genio AD, J Climate 1997 10 2943 2962 10.1175/1520- 0442(1997)010<2943:SOGLPV>2.0.CO;2