Grants and Contracts Details
Description
Overview: Mathematical models for vector-borne diseases typically focus on population-level
between-host transmission dynamics, with increasingly more being developed on the within-host
pathogen dynamics. Fewer models have linked the between-host to the within-host dynamics.
A critical gap remains to be addressed: the e.ect of within-host drug pharmacokinetics and
pharmacodynamics (PK/PD) on population-level transmission, particularly their impact on the
spread of drug resistant vector-borne pathogens. The PK processes of drug absorption, distribution,
metabolism, and excretion determine the concentration levels of a drug in the body from time of
administration. These levels determine, in part, the efficacy of a dosage regimen in clearing invading
pathogens from the body (i.e. PD). Thus, the role of PK/PD in population-level disease dynamics
is important for understanding the spread of drug-resistant vector-borne pathogens. Specifically,
linking PK/PD in malaria transmission models allows for the study of anti-malarial drug resistance
among patients within di.erent age groups. This PK-epidemiological (PK-epi) framework will
incorporate di.erences that occur when an individual receives drug for preventative measures or for
treatment of a symptomatic infection. In the case of malaria, Intermittent Preventative Treatment
(IPT) is known to influence the selection of drug resistant parasites.
Intellectual Merit: A novel model framework linking a within-human PK/PD model, whose
output is drug concentration and parasite density . time units after drug administration, to a
between-host model of vector-borne disease with two competing parasite strains, is presented.
A two-age-structured model for malaria is constructed, in which each age group has a di.erent
immune status, with only those with naive immunity undergoing IPT. The model will be used
to study the impact of IPT and treatment drug PK/PD on the spread of drug-resistant malaria
parasites. The three specific aims of our proposal are to: (1) build a general framework that links
within-host PK/PD to between-host disease dynamics of competing pathogen strains, (2) quantify
the information lost by ignoring within-host PK/PD via (i) five key metrics: the basic reproduction
numbers, invasion reproduction numbers, number of deaths averted, and total morbidity; and via
(ii) di.erences in the emergent dynamics, (3) produce model-guided recommendations for optimal
treatment and IPT protocols, bolstered by uncertainty analyses and pharmacological data.
Broader Impacts: All six mathematicians have a track record of working with women and underrepresented
minority high school students, undergraduates, graduate and postdoctoral fellows. All
these groups will be involved in di.erent areas of the 8 stages of the project: development of the base
model framework, comparison between PK-Epi model and Epi model, parameter estimation using
PK/PD data, model validation using population-level statistics, uncertainty analysis, data-driven
model refinement, drug half-life and protocol optimization, and broadening the scope to other
systems including the study of antimicrobial resistance.
Transformative Potential: The proposed framework is based on nonlinear ordinary di.erential
equations. While this approach has great advantages over a partial di.erential equation model,
namely tractability and ease of simulation, the ODE model requires the approximations of piecewise
continuous within-host drug concentrations and continuous parasite densities by step functions,
introducing uncertainty which may propagate to the population-level disease dynamics. The group
will eventually link within-host PK/PD dynamics to between-host dynamics more naturally using a
system of PDEs, with the trade-o. of greater mathematical and numerical complexity, including the
challenge of developing a well-posed PK-Epi PDE model. Throughout the research grant timeframe,
the group will tackle the challenging problem of incorporating PK/PD data as distributions in a
PDE model framework, and building methods to analyze models of this type.
Status | Finished |
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Effective start/end date | 9/1/18 → 6/30/19 |
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