A research agenda for helminth diseases of humans: modelling for control and elimination

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.

Figure 1. A historical timeline of mathematical models for helminthiases.

Some of the pivotal papers that provided the foundation to the mathematical frameworks that are used for modelling helminth infections are highlighted (for a detailed explanation see main text; for a summary of current models see Table S1). Most of the work published until the 1980s (with the exception of papers by Hairston) largely consisted of theoretical frameworks that were motivated, but not fitted to epidemiological data. From that point onwards there has been an increased interest in parameterising models with data on the natural history of the infections, moving away from purely theoretical explorations. The deterministic and microsimulation models of the 1990s were strongly linked to the notion of providing decision support to control programmes (e.g., ONCHOSIM and the OCP in West Africa). Since the year 2000 there has been a steep increase in large-scale initiatives mostly reliant on anthelmintic drugs for the control and elimination of these parasitic infections, but this has not yet been accompanied by a comparable impetus towards using robust modelling to inform and guide such initiatives, though the GPELF has used LYMFASIM and EpiFil, and the SCI has used modified versions of EpiSchisto.