Journal article

GEOFIL: A spatially-explicit agent-based modelling framework for predicting the long-term transmission dynamics of lymphatic filariasis in American Samoa

Zhijing Xu, Patricia M Graves, Colleen L Lau, Archie Clements, Nicholas Geard, Kathryn Glass

Epidemics | Elsevier | Published : 2019

Abstract

In this study, a spatially-explicit agent-based modelling framework GEOFIL was developed to predict lymphatic filariasis (LF) transmission dynamics in American Samoa. GEOFIL included individual-level information on age, gender, disease status, household location, household members, workplace/school location and colleagues/schoolmates at each time step during the simulation. In American Samoa, annual mass drug administration from 2000 to 2006 successfully reduced LF prevalence dramatically. However, GEOFIL predicted continual increase in microfilaraemia prevalence in the absence of further intervention. Evidence from seroprevalence and transmission assessment surveys conducted from 2010 to 20..

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University of Melbourne Researchers

Grants

Awarded by Australian National Health and Medical Research Council (NHMRC) Fellowship


Funding Acknowledgements

ZX is funded by a NHMRC Centre of Research Excellence. CLL was supported by an Australian National Health and Medical Research Council (NHMRC) Fellowship (1109035). We thank Wayne Melrose and Luke Becker, of the James Cook University WHO Collaborating Centre for Vector Borne and NTDs, for discussion about LF infection parameters and dynamics. We thank all those in American Samoa and elsewhere who conducted or participated in the human and entomological surveys that provided data for this study.