13 research outputs found
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
Author Correction:The temporal dynamics and infectiousness of subpatent Plasmodium falciparum infections in relation to parasite density
Correction to: Nature Communications https://doi.org/10.1038/s41467-019-09441-1; published online 29 March 201
Implementation and applications of EMOD, an individual-based multi-disease modeling platform
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach developed with formal software support. The epidemiological modeling software, EMOD, has undergone a decade of software development. It is structured so that a majority of code is shared across disease modeling including malaria, HIV, tuberculosis, dengue, polio and typhoid. In additional to implementation efficiency, the sharing increases code usage and testing. The freely available codebase also includes hundreds of regression tests, scientific feature tests and component tests to help verify functionality and avoid inadvertent changes to functionality during future development. Here we describe the levels of detail, flexible configurability and modularity enabled by EMOD and the role of software development principles and processes in its development
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Infectivity data and asexual parasite density. Used for figures 7,8
Data from: The temporal dynamics and infectiousness of subpatent Plasmodium falciparum infections in relation to parasite density
Malaria infections occurring below the limit of detection of standard diagnostics are common in all endemic settings. However, key questions remain surrounding their contribution to sustaining transmission and whether they need to be detected and targeted to achieve malaria elimination. In this study we analyse a range of malaria datasets to quantify the density, detectability, course of infection and infectiousness of subpatent infections. Asymptomatically infected individuals have lower parasite densities on average in low transmission settings compared to individuals in higher transmission settings. In cohort studies, subpatent infections are found to be predictive of future periods of patent infection and in membrane feeding studies, individuals infected with subpatent asexual parasite densities are found to be approximately a third as infectious to mosquitoes as individuals with patent (asexual parasite) infection. These results indicate that subpatent infections contribute to the infectious reservoir, may be long lasting, and require more sensitive diagnostics to detect them in lower transmission settings
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Parasite density data for each study and positivity by microscopy or RDT. Used for figures 1,2,
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Gametocyte and asexual parasite density data. Used for figure 6
shareable_data_master_fig5
Data on probability of being slide-positive in the future. Used for figure 5
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Longitudinal data with positivity by PCR and microscopy. Used for figure 4
Appui aux travaux conduits sur les systèmes avec semis direct et couvert végétal en Haute Guinée et en Guinée forestière : mission réalisée du 30 juin au 13 juillet 2002
Prostate tumours are highly variable in their response to therapies, but clinically available prognostic factors can explain only a fraction of this heterogeneity. Here we analysed 200 whole-genome sequences and 277 additional whole-exome sequences from localized, non-indolent prostate tumours with similar clinical risk profiles, and carried out RNA and methylation analyses in a subset. These tumours had a paucity of clinically actionable single nucleotide variants, unlike those seen in metastatic disease. Rather, a significant proportion of tumours harboured recurrent non-coding aberrations, large-scale genomic rearrangements, and alterations in which an inversion repressed transcription within its boundaries. Local hypermutation events were frequent, and correlated with specific genomic profiles. Numerous molecular aberrations were prognostic for disease recurrence, including several DNA methylation events, and a signature comprised of these aberrations outperformed well-described prognostic biomarkers. We suggest that intensified treatment of genomically aggressive localized prostate cancer may improve cure rates