Abstract:
AUTHOR SUMMARY:Designing and implementing effective programs for infectious disease control requires complex decision-making, informed by an understanding of the diseases, the types of disease interventions and control measures available, and the disease-relevant characteristics of the local community. Though disease modeling frameworks have been developed to address these questions and support decision-making, the complexity of current models presents a significant barrier to on-the-ground end users. The picture is further complicated when considering approaches for integration of different disease control programs, where co-infection dynamics, treatment interactions, and other variables must also be taken into account. Here, we describe the development of an application available on the internet with a simple user interface, to support on-the-ground decision-making for integrating disease control, given local conditions and practical constraints. The model upon which the tool is built provides predictive analysis for the effectiveness of integration of schistosomiasis and malaria control, two diseases with extensive geographical and epidemiological overlap. This proof-of-concept method and tool demonstrate significant progress in effectively translating the best available scientific models to support pragmatic decision-making on the ground, with the potential to significantly increase the impact and cost-effectiveness of disease control.
journal_name
PLoS Negl Trop Disjournal_title
PLoS neglected tropical diseasesauthors
Standley CJ,Graeden E,Kerr J,Sorrell EM,Katz Rdoi
10.1371/journal.pntd.0006328subject
Has Abstractpub_date
2018-04-12 00:00:00pages
e0006328issue
4eissn
1935-2727issn
1935-2735pii
PNTD-D-17-00961journal_volume
12pub_type
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