Predictive analysis across spatial scales links zoonotic malaria to deforestation

Proceedings of the Royal Society B: Biological Sciences

Volumn 286, Issue 1894, 2019, Pages

  Brock, Patrick M ^a   Fornace, Kimberly M ^b   Grigg, Matthew J ^c   Anstey, Nicholas M ^c   William, Timothy ^c,d   Cox, Jon ^b   Drakeley, Chris J ^b   Ferguson, Heather M ^a   Kao, Rowland R ^a,e  

^a UNIVERSITY OF GLASGOW   (United Kingdom)

^b LONDON SCHOOL OF HYGIENE AND TROPICAL MEDICINE   (United Kingdom)

^c MENZIES SCHOOL OF HEALTH RESEARCH   (Australia)

^d Gleneagles Hospital Kota Kinabalu   (Malaysia)

^e UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

Boosted regression trees; Disease ecology; Disease occurrence prediction; Malaria; Plasmodium knowlesi; Zoonoses

Indexed keywords

DEFORESTATION; DISEASE TRANSMISSION; DISEASE VECTOR; ENVIRONMENTAL CHANGE; LAND USE CHANGE; MACHINE LEARNING; MALARIA; PREDICTION; PROTOZOAN; REGRESSION ANALYSIS; SATELLITE IMAGERY; SPATIAL ANALYSIS; STATISTICAL ANALYSIS;

PLASMODIUM KNOWLESI;

ANIMAL; CASE CONTROL STUDY; CROSS-SECTIONAL STUDY; EPIDEMIOLOGICAL MONITORING; FOREST; FORESTRY; HUMAN; MACHINE LEARNING; MALARIA; MALAYSIA; PHYSIOLOGY; PLASMODIUM KNOWLESI; REMOTE SENSING; SPACE FLIGHT; SPATIAL ANALYSIS; STATISTICAL MODEL; THEORETICAL MODEL; ZOONOSIS;

ANIMALS; CASE-CONTROL STUDIES; CROSS-SECTIONAL STUDIES; EPIDEMIOLOGICAL MONITORING; FORESTRY; FORESTS; HUMANS; MACHINE LEARNING; MALARIA; MALAYSIA; MODELS, STATISTICAL; MODELS, THEORETICAL; PLASMODIUM KNOWLESI; REMOTE SENSING TECHNOLOGY; SPACECRAFT; SPATIAL ANALYSIS; ZOONOSES;

EID: 85061297890     PISSN: 09628452     EISSN: 14712954     Source Type: Journal    
DOI: 10.1098/rspb.2018.2351     Document Type: Article

References (46)

1. Bhatt S et al. 2015 The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015. Nature 526, 207-211. (doi:10.1038/ nature15535)
2. Gething PW, Battle KE, Bhatt S, Smith DL, Eisele TP, Cibulskis RE, Hay SI. 2014 Declining malaria in Africa: improving the measurement of progress. Malar. J. 13, 39. (doi:10.1186/1475-2875-13-39)
3. Hay SI et al. 2013 Global mapping of infectious disease. Phil. Trans. R. Soc. B 368, 20120250. (doi:10.1098/rstb.2012.0250)
4. Pigott DM et al. 2015 Prioritising infectious disease mapping. PLoS Negl. Trop. Dis. 9, e0003756. (doi:10. 1371/journal.pntd.0003756)
5. Sturrock HJW, Bennett AF, Midekisa A, Gosling RD, Gething PW, Greenhouse B. 2016 Mapping malaria risk in low transmission settings: challenges and opportunities. Trends Parasitol. 32, 635-645. (doi:10.1016/j.pt.2016.05.001)
6. Shearer FM et al. 2016 Estimating geographical variation in the risk of zoonotic Plasmodium knowlesi infection in countries eliminating malaria. PLoS Negl. Trop. Dis. 10, e0004915. (doi:10.1371/ journal.pntd.0004915)
7. Alegana VA et al. 2016 Advances in mapping malaria for elimination: fine resolution modelling of Plasmodium falciparum incidence. Sci. Rep. 6, 29628. (doi:10.1038/srep29628)
8. Bhatt S et al. 2013 The global distribution and burden of dengue. Nature 496, 504-507. (doi:10. 1038/nature12060)
9. Messina JP et al. 2015 The global distribution of Crimean-Congo hemorrhagic fever. Trans. R. Soc. Trop. Med. Hyg. 109, 503-513. (doi:10.1093/ trstmh/trv050)
10. Messina JP et al. 2016 Mapping global environmental suitability for Zika virus. Elife 5, e15272. (doi:10.7554/eLife.15272)
11. Pigott DM et al. 2016 Updates to the zoonotic niche map of Ebola virus disease in Africa. Elife 5, e16412. (doi:10.7554/eLife.16412)
12. Han BA, Schmidt JP, Bowden SE, Drake JM. 2015 Rodent reservoirs of future zoonotic diseases. Proc. Natl Acad. Sci. USA 112, 7039-7044. (doi:10.1073/ pnas.1501598112)
13. Evans MV, Dallas TA, Han BA, Murdock CC, Drake JM. 2017 Data-driven identification of potential Zika virus vectors. Elife 6, e22053. (doi:10.7554/eLife.22053)
14. Escobar LE, Craft ME. 2016 Advances and limitations of disease biogeography using ecological niche modeling. Front. Microbiol. 7, 1174.
15. Stephens PR et al. 2016 The macroecology of infectious diseases: a new perspective on global-scale drivers of pathogen distributions and impacts. Ecol. Lett. 19, 1159-1171. (doi:10.1111/ ele.12644)
16. Elith J, Leathwick JR, Hastie T. 2008 A working guide to boosted regression trees. J. Anim. Ecol. 77, 802-813. (doi:10.1111/j.1365-2656.2008. 01390.x)
17. Brady OJ et al. 2016 Vectorial capacity and vector control: reconsidering sensitivity to parameters for malaria elimination. Trans. R. Soc. Trop. Med. Hyg. 110, 107-117. (doi:10.1093/trstmh/trv113)
18. Parratt SA, Numminen E, Laine A. 2016 Infectious disease dynamics in heterogeneous landscapes. Annu. Rev. Ecol. Evol. Syst. 47, 283-306. (doi:10. 1146/annurev-ecolsys-121415-032321)
19. Stefani A, Roux E, Fotsing J-M, Carme B. 2011 Studying relationships between environment and malaria incidence in Camopi (French Guiana) through the objective selection of buffer-based landscape characterisations. Int. J. Health Geogr. 10, 65. (doi:10.1186/1476-072X-10-65)
20. Wardrop NA, Geary M, Osborne PE, Atkinson PM. 2014 Interpreting predictive maps of disease: highlighting the pitfalls of distribution models in epidemiology. Geospat. Health 9, 237-246. (doi:10. 4081/gh.2014.397)
21. Daneshvar C, Davis TM, Cox-Singh J, Rafa'ee MZ, Zakaria SK, Divis PC, Singh B. 2009 Clinical and laboratory features of human Plasmodium knowlesi infection. Clin. Infect. Dis. 49, 852-860. (doi:10. 1086/605439)
22. Wong ML et al. 2015 Seasonal and spatial dynamics of the primary vector of Plasmodium knowlesi within a major transmission focus in Sabah, Malaysia. PLoS Negl. Trop. Dis. 9, e0004135.
23. Singh B Sung LK, Matusop A, Radhakrishnan A, Shamsul SSG, Cox-Singh J, Thomas A, Conway DJ. 2004 A large focus of naturally acquired Plasmodium knowlesi infections in human beings. Lancet 363, 1017-1024. (doi:10.1016/S0140-6736(04)15836-4)
24. Lubis IN, Wijaya H, Lubis M, Lubis CP, Divis PC, Beshir KB, Sutherland CJ. 2017 Contribution of Plasmodium knowlesi to multi-species human malaria infections in North Sumatera, Indonesia. J. Infect. Dis. 215, 1148-1155. (doi:10.1093/ infdis/jix091)
25. Moyes CL et al. 2014 Defining the geographical range of the Plasmodium knowlesi reservoir. PLoS Negl. Trop. Dis. 8, e2780. (doi:10.1371/journal.pntd. 0002780)
26. Hansen MC et al. 2013 High-resolution global maps of 21st-century forest cover change. Science 342, 850-853. (doi:10.1126/science.1244693)
27. World Health Organisation Regional Office for Western Pacific. 2017 Expert consultation on Plasmodium knowlesi malaria to guide malaria elimination strategies. Manila, Philippines: World Health Organization.
28. Fornace KM et al. 2016 Association between landscape factors and spatial patterns of Plasmodium knowlesi infections in Sabah, Malaysia. Emerg. Infect. Dis. 22, 201-208. (doi:10.3201/ eid2202.150656)
29. Grigg MJ et al. 2017 Individual-level factors associated with the risk of acquiring human Plasmodium knowlesi malaria in Malaysia: a case control study. Lancet Planet. Health 1, e97-e104. (doi:10.1016/S2542-5196(17)30031-1)
30. Fornace et al. Submitted. Environmental risk factors and exposure to the zoonotic malaria Plasmodium knowlesi across northern Sabah, Malaysia: a cross-sectional survey.
31. Weiss DJ, Mappin B, Dalrymple U, Bhatt S, Cameron E, Hay SI, Gething PW. 2015 Re-examining environmental correlates of Plasmodium falciparum malaria endemicity: a data-intensive variable selection approach. Malar. J. 14, 68. (doi:10.1186/ s12936-015-0574-x)
32. Land Processes Distributed Active Archive Center (LP DAAC). 2015 Advanced spaceborne thermal emission and reflection radiometer global digital elevation model (ASTER GDEM), version 2, 2015, NASA EOSDIS Land Processes DAAC, USGS Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota.
33. Barbet-Massin M, Jiguet F, Albert CH Thuiller W. 2012 Selecting pseudo-absences for species distribution models: how, where and how many? Methods Ecol. Evol. 3, 327-338. (doi:10.1111/ j.2041-210X.2011.00172.x)
34. Ward JH. 1963 Hierarchical grouping to optimize an objective function. J. Am. Stat. Assoc. 58, 236-244. (doi:10.1080/01621459.1963.10500845)
35. Hargis CD, Bissonette JA, David JL. 1998 The behaviour of landscape metrics commonly used in the study of habitat fragmentation. Landsc. Ecol. 13, 167-186. (doi:10.1023/ A:1007965018633)
36. Allan BF, Keesing F, Ostfeld RS. 2003 Effect of forest fragmentation on Lyme Disease risk. Conserv. Biol. 17, 267-272. (doi:10.1046/j.1523-1739.2003. 01260.x)
37. Rulli MC, Santini M, Hayman DTS, D'Odorico P, 2017 The nexus between forest fragmentation in Africa and Ebola virus disease outbreaks. Sci. Rep. 7, 41613. (doi:10.1038/srep41613)
38. Fooden J. 1995 Systematic review of Southeast Asian longtail macaques Macaca fascicularis. Fieldiana 81, 2-3.
39. Lima JM, Vittor A, Rifai S, Valle D. 2017 Does deforestation promote or inhibit malaria transmission in the Amazon? A systematic literature review and critical appraisal of current evidence. Phil. Trans. R. Soc. B 372, 20160125. (doi:10.1098/ rstb.2016.0125)
40. Barber BE William T, Grigg MJ, Menon J, Auburn S, Marfurt J, Anstey NM, Yeo TW. 2013 A prospective comparative study of knowlesi, falciparum, and vivax malaria in Sabah, Malaysia: high proportion with severe disease from Plasmodium knowlesi and Plasmodium vivax but no mortality with early referral and artesunate therapy. Clin. Infect. Dis. 56, 383-397. (doi:10. 1093/cid/cis902)
41. Weiss DJ, Bhatt S, Mappin B, Van Boeckel TP, Smith DL, Hay SI, Gething PW. 2014 Air temperature suitability for Plasmodium falciparum malaria transmission in Africa 2000-2012: a high-resolution spatiotemporal prediction. Malar. J. 13, 171. (doi:10.1186/1475-2875-13-171)
42. Mordecai EA et al. 2013 Optimal temperature for malaria transmission is dramatically lower than previously predicted. Ecol. Lett. 16, 22-30. (doi:10. 1111/ele.12015)
43. Manin BO, Ferguson HM, Vythilingam I, Fornace K, William T, Torr SJ, Drakeley C, Chua TH. 2016 Investigating the contribution of peri-domestic transmission to risk of zoonotic malaria infection in humans. PLoS Negl. Trop. Dis. 10, e0005064. (doi:10.1371/journal.pntd.0005064)
44. Brock PM, Fornace KM, Parmiter M, Cox J, Drakeley CJ, Ferguson HM, Kao RR. 2016 Plasmodium knowlesi transmission: integrating quantitative approaches from epidemiology and ecology to understand malaria as a zoonosis. Parasitology 143, 389-400. (doi:10.1017/S0031182015001821)
45. Han BA, Drake JM. 2016 Future directions in analytics for infectious disease intelligence: toward an integrated warning system for emerging pathogens. EMBO Rep. 17, 785-789. (doi:10. 15252/embr.201642534)
46. Fornace KM et al. 2018 Exposure and infection to Plasmodium knowlesi in case study communities in Northern Sabah, Malaysia and Palawan, The Philippines. PLoS Negl. Trop. Dis. 12, e0006432. (doi:10.1371/journal.pntd.0006432)