758 research outputs found
Mass campaigns with antimalarial drugs: a modelling comparison of artemether-lumefantrine and DHA-piperaquine with and without primaquine as tools for malaria control and elimination
Antimalarial drugs are a powerful tool for malaria control and elimination.
Artemisinin-based combination therapies (ACTs) can reduce transmission when
widely distributed in a campaign setting. Modelling mass antimalarial campaigns
can elucidate how to most effectively deploy drug-based interventions and
quantitatively compare the effects of cure, prophylaxis, and
transmission-blocking in suppressing parasite prevalence. A previously
established agent-based model that includes innate and adaptive immunity was
used to simulate malaria infections and transmission. Pharmacokinetics of
artemether, lumefantrine, dihydroartemisinin, piperaquine, and primaquine were
modelled with a double-exponential distribution-elimination model including
weight-dependent parameters and age-dependent dosing. Drug killing of asexual
parasites and gametocytes was calibrated to clinical data. Mass distribution of
ACTs and primaquine was simulated with seasonal mosquito dynamics at a range of
transmission intensities. A single mass campaign with antimalarial drugs is
insufficient to permanently reduce malaria prevalence when transmission is
high. Current diagnostics are insufficiently sensitive to accurately identify
asymptomatic infections, and mass-screen-and-treat campaigns are much less
efficacious than mass drug administrations. Improving campaign coverage leads
to decreased prevalence one month after the end of the campaign, while
increasing compliance lengthens the duration of protection against reinfection.
Use of a long-lasting prophylactic as part of a mass drug administration
regimen confers the most benefit under conditions of high transmission and
moderately high coverage. Addition of primaquine can reduce prevalence but
exerts its largest effect when coupled with a long-lasting prophylactic.Comment: 14 pages, 5 figure
Metastability and low lying spectra in reversible Markov chains
We study a large class of reversible Markov chains with discrete state space
and transition matrix . We define the notion of a set of {\it metastable
points} as a subset of the state space \G_N such that (i) this set is reached
from any point x\in \G_N without return to x with probability at least ,
while (ii) for any two point x,y in the metastable set, the probability
to reach y from x without return to x is smaller than
. Under some additional non-degeneracy assumption, we show
that in such a situation: \item{(i)} To each metastable point corresponds a
metastable state, whose mean exit time can be computed precisely. \item{(ii)}
To each metastable point corresponds one simple eigenvalue of which is
essentially equal to the inverse mean exit time from this state. The
corresponding eigenfunctions are close to the indicator function of the support
of the metastable state. Moreover, these results imply very sharp uniform
control of the deviation of the probability distribution of metastable exit
times from the exponential distribution.Comment: 44pp, AMSTe
Metastability in stochastic dynamics of disordered mean-field models
We study a class of Markov chains that describe reversible stochastic
dynamics of a large class of disordered mean field models at low temperatures.
Our main purpose is to give a precise relation between the metastable time
scales in the problem to the properties of the rate functions of the
corresponding Gibbs measures. We derive the analog of the Wentzell-Freidlin
theory in this case, showing that any transition can be decomposed, with
probability exponentially close to one, into a deterministic sequence of
``admissible transitions''. For these admissible transitions we give upper and
lower bounds on the expected transition times that differ only by a constant.
The distribution rescaled transition times are shown to converge to the
exponential distribution. We exemplify our results in the context of the random
field Curie-Weiss model.Comment: 73pp, AMSTE
Fractional diffusion emulates a human mobility network during a simulated disease outbreak
From footpaths to flight routes, human mobility networks facilitate the
spread of communicable diseases. Control and elimination efforts depend on
characterizing these networks in terms of connections and flux rates of
individuals between contact nodes. In some cases, transport can be
parameterized with gravity-type models or approximated by a diffusive random
walk. As a alternative, we have isolated intranational commercial air traffic
as a case study for the utility of non-diffusive, heavy-tailed transport
models. We implemented new stochastic simulations of a prototypical
influenza-like infection, focusing on the dense, highly-connected United States
air travel network. We show that mobility on this network can be described
mainly by a power law, in agreement with previous studies. Remarkably, we find
that the global evolution of an outbreak on this network is accurately
reproduced by a two-parameter space-fractional diffusion equation, such that
those parameters are determined by the air travel network.Comment: 26 pages, 4 figure
Transplacental Passage of Drugs and other Exogenous Compounds: A Review - Part II
In addition to and in conjunction with its transport functions, the placenta possesses metabolic activity consisting of many enzyme systems which function int he biosynthesis, degradation, and biotransformation of numerous endogenous compounds
A malaria transmission-directed model of mosquito life cycle and ecology
<p>Abstract</p> <p>Background</p> <p>Malaria is a major public health issue in much of the world, and the mosquito vectors which drive transmission are key targets for interventions. Mathematical models for planning malaria eradication benefit from detailed representations of local mosquito populations, their natural dynamics and their response to campaign pressures.</p> <p>Methods</p> <p>A new model is presented for mosquito population dynamics, effects of weather, and impacts of multiple simultaneous interventions. This model is then embedded in a large-scale individual-based simulation and results for local elimination of malaria are discussed. Mosquito population behaviours, such as anthropophily and indoor feeding, are included to study their effect upon the efficacy of vector control-based elimination campaigns.</p> <p>Results</p> <p>Results for vector control tools, such as bed nets, indoor spraying, larval control and space spraying, both alone and in combination, are displayed for a single-location simulation with vector species and seasonality characteristic of central Tanzania, varying baseline transmission intensity and vector bionomics. The sensitivities to habitat type, anthropophily, indoor feeding, and baseline transmission intensity are explored.</p> <p>Conclusions</p> <p>The ability to model a spectrum of local vector species with different ecologies and behaviours allows local customization of packages of interventions and exploration of the effect of proposed new tools.</p
Prescription Writing for the Veterinarian
Veterinary prescription legend drugs are those which, by regulation, can only be used by or on the order of a licensed veterinarian since adequate directions for their use by a layman cannot be written. Generally, the prescription drugs are quite potent or otherwise hazardous, having a narrow range of tolerance in terms of safety for use
Optimal population-level infection detection strategies for malaria control and elimination in a spatial model of malaria transmission
Mass campaigns with antimalarial drugs are potentially a powerful tool for
local elimination of malaria, yet current diagnostic technologies are
insufficiently sensitive to identify all individuals who harbor infections. At
the same time, overtreatment of uninfected individuals increases the risk of
accelerating emergence of drug resistance and losing community acceptance.
Local heterogeneity in transmission intensity may allow campaign strategies
that respond to index cases to successfully target subpatent infections while
simultaneously limiting overtreatment. While selective targeting of hotspots of
transmission has been proposed as a strategy for malaria control, such
targeting has not been tested in the context of malaria elimination. Using
household locations, demographics, and prevalence data from a survey of four
health facility catchment areas in southern Zambia and an agent-based model of
malaria transmission and immunity acquisition, a transmission intensity was fit
to each household based on neighborhood age-dependent malaria prevalence. A set
of individual infection trajectories was constructed for every household in
each catchment area, accounting for heterogeneous exposure and immunity.
Various campaign strategies (mass drug administration, mass screen and treat,
focal mass drug administration, snowball reactive case detection, pooled
sampling, and a hypothetical serological diagnostic) were simulated and
evaluated for performance at finding infections, minimizing overtreatment,
reducing clinical case counts, and interrupting transmission. For malaria
control, presumptive treatment leads to substantial overtreatment without
additional morbidity reduction under all but the highest transmission
conditions. Selective targeting of hotspots with drug campaigns is an
ineffective tool for elimination due to limited sensitivity of available field
diagnostics
Helly-Type Theorems in Property Testing
Helly's theorem is a fundamental result in discrete geometry, describing the
ways in which convex sets intersect with each other. If is a set of
points in , we say that is -clusterable if it can be
partitioned into clusters (subsets) such that each cluster can be contained
in a translated copy of a geometric object . In this paper, as an
application of Helly's theorem, by taking a constant size sample from , we
present a testing algorithm for -clustering, i.e., to distinguish
between two cases: when is -clusterable, and when it is
-far from being -clusterable. A set is -far
from being -clusterable if at least
points need to be removed from to make it -clusterable. We solve
this problem for and when is a symmetric convex object. For , we
solve a weaker version of this problem. Finally, as an application of our
testing result, in clustering with outliers, we show that one can find the
approximate clusters by querying a constant size sample, with high probability
Metastability and small eigenvalues in Markov chains
In this letter we announce rigorous results that elucidate the relation
between metastable states and low-lying eigenvalues in Markov chains in a much
more general setting and with considerable greater precision as was so far
available. This includes a sharp uncertainty principle relating all low-lying
eigenvalues to mean times of metastable transitions, a relation between the
support of eigenfunctions and the attractor of a metastable state, and sharp
estimates on the convergence of probability distribution of the metastable
transition times to the exponential distribution.Comment: 5pp, AMSTe
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