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An agent-based model of tsetse fly response to seasonal climatic drivers: Assessing the impact on sleeping sickness transmission rates
Alderton, Simon1,2,3; Macleod, Ewan T.4; Anderson, Neil E.5,6; Palmer, Gwen; Machila, Noreen4,7; Simuunza, Martin7; Welburn, Susan C.4; Atkinson, Peter M.1,2,3,8,9
2018-02-01
Source PublicationPLOS NEGLECTED TROPICAL DISEASES
ISSN1935-2735
Volume12Issue:2Pages:29
Corresponding AuthorAlderton, Simon(s.alderton@lancaster.ac.uk)
AbstractBackground This paper presents the development of an agent-based model (ABM) to incorporate climatic drivers which affect tsetse fly (G. m. morsitans) population dynamics, and ultimately disease transmission. The model was used to gain a greater understanding of how tsetse populations fluctuate seasonally, and investigate any response observed in Trypanosome brucei rhodesiense human African trypanosomiasis (rHAT) disease transmission, with a view to gaining a greater understanding of disease dynamics. Such an understanding is essential for the development of appropriate, well-targeted mitigation strategies in the future. Methods The ABM was developed to model rHAT incidence at a fine spatial scale along a 75 km transect in the Luangwa Valley, Zambia. The model incorporates climatic factors that affect pupal mortality, pupal development, birth rate, and death rate. In combination with fine scale demographic data such as ethnicity, age and gender for the human population in the region, as well as an animal census and a sample of daily routines, we create a detailed, plausible simulation model to explore tsetse population and disease transmission dynamics. Results The seasonally-driven model suggests that the number of infections reported annually in the simulation is likely to be a reasonable representation of reality, taking into account the high levels of under-detection observed. Similar infection rates were observed in human (0.355 per 1000 person-years (SE = 0.013)), and cattle (0.281 per 1000 cattle-years (SE = 0.025)) populations, likely due to the sparsity of cattle close to the tsetse interface. The model suggests that immigrant tribes and school children are at greatest risk of infection, a result that derives from the bottom-up nature of the ABM and conditioning on multiple constraints. This result could not be inferred using alternative population-level modelling approaches. Conclusions In producing a model which models the tsetse population at a very fine resolution, we were able to analyse and evaluate specific elements of the output, such as pupal development and the progression of the teneral population, allowing the development of our understanding of the tsetse population as a whole. This is an important step in the production of a more accurate transmission model for rHAT which can, in turn, help us to gain a greater understanding of the transmission system as a whole.
DOI10.1371/journal.pntd.0006188
WOS KeywordHUMAN AFRICAN TRYPANOSOMIASIS ; GLOSSINA-MORSITANS ORIENTALIS ; LUANGWA VALLEY ; EASTERN ZAMBIA ; RHODESIENSE ; EFFICACY ; HEALTH ; FLIES ; EPIDEMIOLOGY ; MANAGEMENT
Indexed BySCI
Language英语
Funding ProjectEPSRC[EP/G03690X/1] ; Dynamic Drivers of Disease in Africa Consortium, NERC project, Ecosystem Services for Poverty Alleviation (ESPA) programme[NE/J000701/1] ; Department for International Development (DFID) ; Economic and Social Research Council (ESRC) ; Natural Environment Research Council (NERC)
Funding OrganizationEPSRC ; Dynamic Drivers of Disease in Africa Consortium, NERC project, Ecosystem Services for Poverty Alleviation (ESPA) programme ; Department for International Development (DFID) ; Economic and Social Research Council (ESRC) ; Natural Environment Research Council (NERC)
WOS Research AreaInfectious Diseases ; Parasitology ; Tropical Medicine
WOS SubjectInfectious Diseases ; Parasitology ; Tropical Medicine
WOS IDWOS:000427279700008
PublisherPUBLIC LIBRARY SCIENCE
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/57205
Collection中国科学院地理科学与资源研究所
Corresponding AuthorAlderton, Simon
Affiliation1.Univ Southampton, Fac Social & Human Sci, Geog & Environm, Southampton, Hants, England
2.Univ Lancaster, Lancaster Environm Ctr, Lancaster, England
3.Univ Lancaster, Lancaster Med Sch, Ctr Hlth Informat Comp & Stat CHICAS, Lancaster, England
4.Univ Edinburgh, Coll Med & Vet Med, Edinburgh Med Sch, Div Infect & Pathway Med Biomed Sci, Edinburgh, Midlothian, Scotland
5.Univ Edinburgh, Royal Dick Sch Vet Studies, Roslin, Midlothian, Scotland
6.Univ Edinburgh, Roslin Inst, Roslin, Midlothian, Scotland
7.Univ Zambia, Sch Vet Med, Dept Dis Control, Lusaka, Zambia
8.Queens Univ Belfast, Sch Geog Archaeol & Palaeoecol, Belfast, Antrim, North Ireland
9.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Alderton, Simon,Macleod, Ewan T.,Anderson, Neil E.,et al. An agent-based model of tsetse fly response to seasonal climatic drivers: Assessing the impact on sleeping sickness transmission rates[J]. PLOS NEGLECTED TROPICAL DISEASES,2018,12(2):29.
APA Alderton, Simon.,Macleod, Ewan T..,Anderson, Neil E..,Palmer, Gwen.,Machila, Noreen.,...&Atkinson, Peter M..(2018).An agent-based model of tsetse fly response to seasonal climatic drivers: Assessing the impact on sleeping sickness transmission rates.PLOS NEGLECTED TROPICAL DISEASES,12(2),29.
MLA Alderton, Simon,et al."An agent-based model of tsetse fly response to seasonal climatic drivers: Assessing the impact on sleeping sickness transmission rates".PLOS NEGLECTED TROPICAL DISEASES 12.2(2018):29.
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