A Multi-Host Agent-Based Model for a Zoonotic, Vector-Borne Disease. A Case Study on Trypanosomiasis in Eastern Province, Zambia
Authored by Simon Alderton, Kathrin Schaten, Susan C Welburn, Peter M Atkinson, Ewan T Macleod, Neil E Anderson, Joanna Kuleszo, Martin Simuunza
Date Published: 2016
DOI: 10.1371/journal.pntd.0005252
Sponsors:
United Kingdom Engineering and Physical Sciences Research Council (EPSRC)
Platforms:
No platforms listed
Model Documentation:
Other Narrative
Model Code URLs:
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Abstract
Background
This paper presents a new agent-based model (ABM) for investigating T.
b. rhodesiense human African trypanosomiasis (rHAT) disease dynamics, produced to aid a greater understanding of disease transmission, and
essential for development of appropriate mitigation strategies.
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 method offers
a complementary approach to traditional compartmentalised modelling
techniques, permitting incorporation of fine scale demographic data such
as ethnicity, age and gender into the simulation.
Results
Through identification of possible spatial, demographic and behavioural
characteristics which may have differing implications for rHAT risk in
the region, the ABM produced output that could not be readily generated
by other techniques. On average there were 1.99 (S.E. 0.245) human
infections and 1.83 (S.E. 0.183) cattle infections per 6 month period.
The model output identified that the approximate incidence rate (per
1000 person-years) was lower amongst cattle owning households (0.079, S.E. 0.017), than those without cattle (0.134, S.E. 0.017). Immigrant
tribes (e.g. Bemba I.R. = 0.353, S.E. 0.155) and school-age children
(e.g. 5-10 year old I.R. = 0.239, S.E. 0.041) were the most at-risk for
acquiring infection. These findings have the potential to aid the
targeting of future mitigation strategies.
Conclusion
ABMs provide an alternative way of thinking about HAT and NTDs more
generally, offering a solution to the investigation of local-scale
questions, and which generate results that can be easily disseminated to
those affected. The ABM can be used as a tool for scenario testing at an
appropriate spatial scale to allow the design of logistically feasible
mitigation strategies suggested by model output. This is of particular
importance where resources are limited and management strategies are
often pushed to the local scale.
Tags
human African trypanosomiasis
Diptera
Sleeping-sickness
General-model
Neglected tropical diseases
Tsetse-flies
Glossina-morsitans
Brucei-rhodesiense
Luangwa valley
T-rhodesiense