52 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
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
Malaria elimination campaigns in the Lake Kariba region of Zambia: a spatial dynamical model
Background As more regions approach malaria elimination, understanding how
different interventions interact to reduce transmission becomes critical. The
Lake Kariba area of Southern Province, Zambia, is part of a multi-country
elimination effort and presents a particular challenge as it is an
interconnected region of variable transmission intensities.
Methods In 2012-13, six rounds of mass-screen-and-treat drug campaigns were
carried out in the Lake Kariba region. A spatial dynamical model of malaria
transmission in the Lake Kariba area, with transmission and climate modeled at
the village scale, was calibrated to the 2012-13 prevalence survey data, with
case management rates, insecticide-treated net usage, and drug campaign
coverage informed by surveillance. The model was used to simulate the effect of
various interventions implemented in 2014-22 on reducing regional transmission,
achieving elimination by 2022, and maintaining elimination through 2028.
Findings The model captured the spatio-temporal trends of decline and rebound
in malaria prevalence in 2012-13 at the village scale. Simulations predicted
that elimination required repeated mass drug administrations coupled with
simultaneous increase in net usage. Drug campaigns targeted only at high-burden
areas were as successful as campaigns covering the entire region.
Interpretation Elimination in the Lake Kariba region is possible through
coordinating mass drug campaigns with high-coverage vector control. Targeting
regional hotspots is a viable alternative to global campaigns when human
migration within an interconnected area is responsible for maintaining
transmission in low-burden areas
Characterization of the infectious reservoir of malaria with an agent-based model calibrated to age-stratified parasite densities and infectiousness
Background Elimination of malaria can only be achieved through removal of all
vectors or complete depletion of the infectious reservoir in humans.
Mechanistic models can be built to synthesize diverse observations from the
field collected under a variety of conditions and subsequently used to query
the infectious reservoir in great detail. Methods The EMOD model of malaria
transmission was calibrated to prevalence, incidence, asexual parasite density,
gametocyte density, infection duration, and infectiousness data from 9 study
sites. The infectious reservoir was characterized by diagnostic detection limit
and age group over a range of transmission intensities with and without case
management and vector control. Mass screen-and-treat drug campaigns were tested
for likelihood of achieving elimination. Results The composition of the
infectious reservoir by diagnostic threshold is similar over a range of
transmission intensities, and higher intensity settings are biased toward
infections in children. Recent ramp-ups in case management and use of
insecticide-treated bednets reduce the infectious reservoir and shift the
composition toward submicroscopic infections. Mass campaigns with antimalarial
drugs are highly effective at interrupting transmission if deployed shortly
after ITN campaigns. Conclusions Low density infections comprise a substantial
portion of the infectious reservoir. Proper timing of vector control, seasonal
variation in transmission intensity, and mass drug campaigns allows lingering
population immunity to help drive a region toward elimination.Comment: submitted to Malaria Journal on March 31, 201
An archetypes approach to malaria intervention impact mapping: a new framework and example application
Background: As both mechanistic and geospatial malaria modeling methods become more integrated into malaria policy decisions, there is increasing demand for strategies that combine these two methods. This paper introduces a novel archetypes-based methodology for generating high-resolution intervention impact maps based on mechanistic model simulations. An example configuration of the framework is described and explored.
Methods: First, dimensionality reduction and clustering techniques were applied to rasterized geospatial environmental and mosquito covariates to find archetypal malaria transmission patterns. Next, mechanistic models were run on a representative site from each archetype to assess intervention impact. Finally, these mechanistic results were reprojected onto each pixel to generate full maps of intervention impact. The example configuration used ERA5 and Malaria Atlas Project covariates, singular value decomposition, k-means clustering, and the Institute for Disease Modeling’s EMOD model to explore a range of three-year malaria interventions primarily focused on vector control and case management.
Results: Rainfall, temperature, and mosquito abundance layers were clustered into ten transmission archetypes with distinct properties. Example intervention impact curves and maps highlighted archetype-specific variation in efficacy of vector control interventions. A sensitivity analysis showed that the procedure for selecting representative sites to simulate worked well in all but one archetype.
Conclusion: This paper introduces a novel methodology which combines the richness of spatiotemporal mapping with the rigor of mechanistic modeling to create a multi-purpose infrastructure for answering a broad range of important questions in the malaria policy space. It is flexible and adaptable to a range of input covariates, mechanistic models, and mapping strategies and can be adapted to the modelers’ setting of choice
Role of mass drug administration in elimination of Plasmodium falciparum malaria: a consensus modelling study
Background Mass drug administration for elimination of Plasmodium falciparum malaria is recommended by WHO
in some settings. We used consensus modelling to understand how to optimise the effects of mass drug administration
in areas with low malaria transmission.
Methods We collaborated with researchers doing field trials to establish a standard intervention scenario and
standard transmission setting, and we input these parameters into four previously published models. We then
varied the number of rounds of mass drug administration, coverage, duration, timing, importation of infection, and
pre-administration transmission levels. The outcome of interest was the percentage reduction in annual mean
prevalence of P falciparum parasite rate as measured by PCR in the third year after the final round of mass drug
administration.
Findings The models predicted differing magnitude of the effects of mass drug administration, but consensus
answers were reached for several factors. Mass drug administration was predicted to reduce transmission over a
longer timescale than accounted for by the prophylactic effect alone. Percentage reduction in transmission was
predicted to be higher and last longer at lower baseline transmission levels. Reduction in transmission resulting from
mass drug administration was predicted to be temporary, and in the absence of scale-up of other interventions, such
as vector control, transmission would return to pre-administration levels. The proportion of the population treated in
a year was a key determinant of simulated effectiveness, irrespective of whether people are treated through high
coverage in a single round or new individuals are reached by implementation of several rounds. Mass drug
administration was predicted to be more effective if continued over 2 years rather than 1 year, and if done at the time
of year when transmission is lowest.
Interpretation Mass drug administration has the potential to reduce transmission for a limited time, but is not an
effective replacement for existing vector control. Unless elimination is achieved, mass drug administration has to be
repeated regularly for sustained effect
- …