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Quantifying the value of surveillance data for improving model predictions of lymphatic filariasis elimination

Michael, E., Sharma, S., Smith, M.E., Touloupou, P., Giardina, F., Prada, Joaquin, Stolk, W.A., Hollingsworth, D. and de Vlas, S.J. (2018) Quantifying the value of surveillance data for improving model predictions of lymphatic filariasis elimination PLoS neglected tropical diseases, 12 (10).

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Abstract

Mathematical models are increasingly being used to evaluate strategies aiming to achieve the control or elimination of parasitic diseases. Recently, owing to growing realization that process-oriented models are useful for ecological forecasts only if the biological processes are well defined, attention has focused on data assimilation as a means to improve the predictive performance of these models.

Item Type: Article
Divisions : Faculty of Health and Medical Sciences
Authors :
NameEmailORCID
Michael, E.
Sharma, S.
Smith, M.E.
Touloupou, P.
Giardina, F.
Prada, Joaquinj.prada@surrey.ac.uk
Stolk, W.A.
Hollingsworth, D.
de Vlas, S.J.
Date : 2018
DOI : 10.1371/journal.pntd.0006674
Depositing User : Rebecca Cooper
Date Deposited : 03 Jan 2019 09:24
Last Modified : 03 Jan 2019 11:32
URI: http://epubs.surrey.ac.uk/id/eprint/850086

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