A research agenda for Helminth diseases of humans: Modelling for control and elimination

Basanez, María-Gloria, McCarthy, James S., French, Michael D., Yang, Guo-Jing, Walker, Martin, Gambhir, Manoj, Prichard, Roger K. and Churcher, Thomas S. (2012) A research agenda for Helminth diseases of humans: Modelling for control and elimination. Plos Neglected Tropical Diseases, 6 4: e1548-1-e1548-11. doi:10.1371/journal.pntd.0001548


Author Basanez, María-Gloria
McCarthy, James S.
French, Michael D.
Yang, Guo-Jing
Walker, Martin
Gambhir, Manoj
Prichard, Roger K.
Churcher, Thomas S.
Title A research agenda for Helminth diseases of humans: Modelling for control and elimination
Journal name Plos Neglected Tropical Diseases   Check publisher's open access policy
ISSN 1935-2735
1935-2735
Publication date 2012-04
Sub-type Critical review of research, literature review, critical commentary
DOI 10.1371/journal.pntd.0001548
Open Access Status DOI
Volume 6
Issue 4
Start page e1548-1
End page e1548-11
Total pages 11
Place of publication San Francisco, CA, United States
Publisher Public Library of Science
Collection year 2013
Language eng
Abstract Mathematical modelling of helminth infections has the potential to inform policy and guide research for the control and elimination of human helminthiases. However, this potential, unlike in other parasitic and infectious diseases, has yet to be realised. To place contemporary efforts in a historical context, a summary of the development of mathematical models for helminthiases is presented. These efforts are discussed according to the role that models can play in furthering our understanding of parasite population biology and transmission dynamics, and the effect on such dynamics of control interventions, as well as in enabling estimation of directly unobservable parameters, exploration of transmission breakpoints, and investigation of evolutionary outcomes of control. The Disease Reference Group on Helminth Infections (DRG4), established in 2009 by the Special Programme for Research and Training in Tropical Diseases (TDR), was given the mandate to review helminthiases research and identify research priorities and gaps. A research and development agenda for helminthiasis modelling is proposed based on identified gaps that need to be addressed for models to become useful decision tools that can support research and control operations effectively. This agenda includes the use of models to estimate the impact of large-scale interventions on infection incidence; the design of sampling protocols for the monitoring and evaluation of integrated control programmes; the modelling of co-infections; the investigation of the dynamical relationship between infection and morbidity indicators; the improvement of analytical methods for the quantification of anthelmintic efficacy and resistance; the determination of programme endpoints; the linking of dynamical helminth models with helminth geostatistical mapping; and the investigation of the impact of climate change on human helminthiases. It is concluded that modelling should be embedded in helminth research, and in the planning, evaluation, and surveillance of interventions from the outset. Modellers should be essential members of interdisciplinary teams, propitiating a continuous dialogue with end users and stakeholders to reflect public health needs in the terrain, discuss the scope and limitations of models, and update biological assumptions and model outputs regularly. It is highlighted that to reach these goals, a collaborative framework must be developed for the collation, annotation, and sharing of databases from large-scale anthelmintic control programmes, and that helminth modellers should join efforts to tackle key questions in helminth epidemiology and control through the sharing of such databases, and by using diverse, yet complementary, modelling approaches.
Keyword Schistosome Transmission Dynamics
Lymphatic Filariasis
Mathematical-Models
Onchocerca-Volvulus
Anthelmintic Resistance
Population-Dynamics
Density-Dependence
Cost-Effectiveness
Geostatistical Prediction
Spatial Heterogeneity
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Article number e1548

Document type: Journal Article
Sub-type: Critical review of research, literature review, critical commentary
Collections: Official 2013 Collection
School of Medicine Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 42 times in Thomson Reuters Web of Science Article | Citations
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Created: Tue, 05 Jun 2012, 03:03:32 EST by System User