Environmental-mechanistic modelling of the impact of global change on human zoonotic disease emergence: a case study of Lassa fever

Methods in Ecology and Evolution

Volumn 7, Issue 6, 2016, Pages 646-655

  Redding, David W ^a   Moses, Lina M ^b   Cunningham, Andrew A ^c   Wood, James ^d   Jones, Kate E ^a,c  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b TULANE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c INSTITUTE OF ZOOLOGY   (United Kingdom)

^d UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

climate change; haemorrhagic disease; infectious disease; land use change; Mastomys natalensis; spillover events; West Africa

Indexed keywords

EID: 84974738103     PISSN: None     EISSN: 2041210X     Source Type: Journal    
DOI: 10.1111/2041-210X.12549     Document Type: Article

References (50)

1. Alexander, K.A., Lewis, B.L., Marathe, M., Eubank, S. & Blackburn, J.K. (2012) Modeling of wildlife-associated zoonoses: applications and caveats. Vector Borne and Zoonotic Diseases (Larchmont, NY), 12, 1005–1018.
2. Benson, D.A., Karsch-Mizrachi, I., Lipman, D.J., Ostell, J. & Wheeler, D.L. (2005) GenBank. Nucleic Acids Research, 33, D34–D38.
3. Carbone, C., Cowlishaw, G., Isaac, N.J. & Rowcliffe, J.M. (2005) How far do animals go? Determinants of day range in mammals. American Naturalist, 165, 290–297.
4. Carpenter, S.R., Mooney, H.A., Agard, J., Capistrano, D., DeFries, R.S., Díaz, S. et al. (2009) Science for managing ecosystem services: Beyond the Millennium Ecosystem Assessment. Proceedings of the National Academy of Sciences of the United States of America, 106, 1305–1312.
5. CDC (2012) Lassa Fever - Fact Sheet. http://wwwcdcgov/ncidod/dvrd/spb/mnpages/dispages/Fact_Sheets/Lassa_Fever_Fact_Sheet.pdf (ed. C.f.D.C.a. Prevention).
6. Chini, L.P., Hurtt, G.C. & Frolking, S. (2014) Harmonized Global Land Use for Years 1500–2100, V1. Data set. Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee.
7. CIESIN (2005) Gridded Population of the World Version 3 (GPWv3): Population Grids. SEDAC Columbia University, New York.
8. Civitello, D.J., Cohen, J., Fatima, H., Halstead, N.T., Liriano, J., McMahon, T.A. et al. (2015) Biodiversity inhibits parasites: Broad evidence for the dilution effect. Proceedings of the National Academy of Sciences, 112, 8667–8671.
9. Colangelo, P., Verheyen, E., Leirs, H., Tatard, C., Denys, C. & Dobigny, G. (2013) A mitochondrial phylogeographic scenario for the most widespread African rodent, Mastomys natalensis. Biological Journal of the Linnean Society, 108, 901–916.
10. Coulibaly-N'Golo, D., Allali, B., Kousassi, S.K., Fichet-Calvet, E. & Becker-Ziaja, B. (2011) Novel Arenavirus Sequences in Hylomyscus sp and Mus (Nannomys) setulosus from Côte d'Ivoire: Implications for Evolution of Arenaviruses in Africa. PLoS ONE, 6, e20893.
11. Elith, J., Graham, C.H., Anderson, R.P., Dudík, M., Ferrier, S., Guisan, A. et al. (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography, 29, 129–151.
12. Elvidge, C.D., Sutton, P.C., Ghosh, T., Tuttle, B.T., Baugh, K.E., Bhaduri, B. & Bright, E. (2009) A global poverty map derived from satellite data. Computers & Geosciences, 35, 1652–1660.
13. Emmerich, P., Gunther, S. & Schmitz, H. (2008) Strain-specific response to Lassa virus in the local population in West Africa. Journal of Clinical Virology, 42, 40–44.
14. Fichet-Calvet, E. & Rogers, D.J. (2009) Risk maps of lassa fever in West Africa. PLoS Neglected Tropical Diseases, 3, e388.
15. Fischer, G., Nachtergaele, F., Prieler, S., van Velthuizen, H.T., Verelst, L. & Wiberg, D. (2008) Global Agro-ecological Zones Assessment for Agriculture (GAEZ 2008). IIASA and FAO, Laxenburg, Austria and Rome, Italy.
16. Friedl, M.A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N., Sibley, A. & Huang, X. (2010) MODIS Collection 5 global land cover: Algorithm refinements and characterisation of new datasets. Remote Sensing of the Environment, 114, 168–182.
17. Global Biodiversity Information Facility (2013) Global Biodiversity Information Facility. http://www.gbif.org/.
18. Grace, D., Mutua, F., Ochungo, P., Kruska, R., Jones, K.E., Brierley, L. et al. (2012) Mapping of poverty and likely zoonoses hotspots. International Livestock Research Institute, Nairobi, Kenya.
19. Hall, T.A. (1999) BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symposium Series, 41, 95–98.
20. HarvestChoice (2014) Crop Production: SPAM. International Food Policy Research Institute, Washington, DC, and University of Minnesota, St. Paul, MN.
21. Hijmans, R.J. & van Etten, J. (2012) Raster: Geographic Analysis and Modeling with Raster Data R Package. R Foundation for Statistical Computing, Vienna, Austria.
22. Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. & Jarvis, A. (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965–1978.
23. Hutchinson, J. & Waser, P.M. (2007) Use, misuse and extensions of “ideal gas” models of animal encounter. Biological Reviews, 3, 335–359.
24. IPCC (2014) Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Cambridge University Press, Cambridge, UK and New York, NY USA.
25. Jarvis, A., Reuter, H.I., Nelson, A. & Guevara, E. (2008) Hole-filled SRTM for the globe. Version 4. CGIAR-CSI SRTM 90m Database.
26. Jones, K.E., Patel, N.G., Levy, M.A., Storeygard, A., Balk, D., Gittleman, J.L. & Daszak, P. (2008) Global trends in emerging infectious diseases. Nature, 451, 990–993.
27. Kaslow, R.A., Stanberry, L.R. & Le Duc, J.W. (2014) Viral Infections of Humans: Epidemiology and Control. Springer, New York, NY, USA.
28. Katoh, K., Kuma, K. & Hiroyuki, T. (2005) MAFFT version 5: improvement in accuracy of multiple sequence alignments. Nucleic Acids Research, 33, 511–518.
29. Keesing, F., Belden, L.K., Daszak, P., Dobson, A., Harvell, C.D., Holt, R.D. et al. (2010) Impacts of biodiversity on the emergence and transmission of infectious diseases. Nature, 468, 647–652.
30. Lehner, B. & Doll, P. (2004) Development and validation of a global database of lakes, reservoirs and wetlands. Journal of Hydrology, 296, 1–22.
31. Lo Iacono, G., Cunningham, A.A., Fichet-Calvet, E., Garry, R.F., Grant, D.S., Khan, S.H. et al. (2015) Using modelling to disentangle the relative contributions of zoonotic and anthroponotic transmission: the case of lassa fever. PLoS Neglected Tropical Diseases, 9, e3398.
32. Lutz, W., Sanderson, W. & Scherbov, S. (2001) The end of world population growth. Nature, 412, 543–545.
33. Makundi, R.H., Massawe, A.W. & Mulungu, L.S. (2007) Reproduction and population dynamics of Mastomys natalensis Smith, 1834 in an agricultural landscape in the Western Usambara Mountains, Tanzania. Integrative Zoology, 2, 233–238.
34. McCormick, J.B., Webb, P.A., Krebs, J.W., Johnson, K.M. & Smith, E.S. (1987) A prospective study of the epidemiology and ecology of Lassa fever. Journal of Infectious Diseases, 155, 437–444.
35. Millennium Ecosystem Assessment (2005) Ecosystems and Human Well-Being: Synthesis. Island Press, Washington, DC.
36. Mylne, A.Q., Pigott, D.M., Longbottom, J., Shearer, F., Duda, K.A., Messina, J.P. et al. (2015) Mapping the zoonotic niche of Lassa fever in Africa. Transactions of the Royal Society of Tropical Medicine and Hygiene, 109, 483–492.
37. Nabholz, B., Glemin, S. & Galtier, N. (2008) Strong Variations of Mitochondrial Mutation Rate across Mammals-the Longevity Hypothesis. Molecular Biology and Evolution, 25, 120–130.
38. Pearson, R.G., Phillips, S.J., Loranty, M.M., Beck, P.S.A., Damoulas, T., Knight, S.J. & Goetz, S.J. (2013) Shifts in Arctic vegetation and associated feedbacks under climate change. Nature Climate Change, 3, 673–677.
39. Phillips, S.J., Dudik, M. & Schapire, R.E. (2004) A maximum entropy approach to species distribution modeling. Proceedings of the 21st International Conference on Machine Learning. pp. 655–662. ACM Press, New York.
40. R Development Core Team (2009) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
41. Randolph, S.E. & Dobson, A.D. (2012) Pangloss revisited: a critique of the dilution effect and the biodiversity-buffers-disease paradigm. Parasitology, 139, 847–863.
42. Richmond, J.K. & Baglole, D.J. (2003) Lassa fever: epidemiology, clinical features, and social consequences. British Medical Journal, 327, 1271–1275.
43. Ronquist, F. & Huelsenbeck, J.P. (2005) MRBAYES 3: Bayesian phylogenetic inference under mixed models. Bioinformatics, 19, 1572–1574.
44. Safronetz, D., Lopez, J.E., Sogoba, N., Traore, S.F., Raffel, S.J., Fischer, E.R. et al. (2010) Detection of Lassa virus, Mali. Emerging Infectious Diseases, 16, 1123–1126.
45. Saluzzo, J.F., Adam, F., McCormick, J.B. & Digoutte, J.P. (1988) Lassa fever virus in Senegal. Journal of Infectious Diseases, 157, 605.
46. Taylor, L.H., Latham, S.M. & Woolhouse, M.E. (2001) Risk factors for human disease emergence. Philosophical Transactions of the Royal Society London, Series B: Biological Sciences, 29, 983–989.
47. United States Geological Survey (2010) Mineral operations outside the United States. (ed. G.S. (U.S.)). Reston, Virginia.
48. Weidmann, N.B., Rød, J.K. & Cederman, L.E. (2010) Representing ethnic groups in space: a new dataset. Journal of Peace Research, 47, 1–9.
49. World Bank (2014) World Development Indicators. World Bank, Washington, DC, USA.
50. Zwiefelhofer, D. (2013) Batch Geocoding.