ORCID Profile
0000-0002-4972-593X
Current Organisations
University of Western Australia
,
University of Basel
,
Telethon Kids Institute
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Publisher: Springer Science and Business Media LLC
Date: 04-10-2019
DOI: 10.1007/S40262-019-00822-9
Abstract: Medication use is highly prevalent with advanced age, but clinical studies are rarely conducted in the elderly, leading to limited knowledge regarding age-related pharmacokinetic changes. The objective of this study was to investigate which pharmacokinetic parameters determine drug exposure changes in the elderly by conducting virtual clinical trials for ten drugs (midazolam, metoprolol, lisinopril, amlodipine, rivaroxaban, repaglinide, atorvastatin, rosuvastatin, clarithromycin and rif icin) using our physiologically based pharmacokinetic (PBPK) framework. PBPK models for all ten drugs were developed in young adults (20-50 years) following the best practice approach, before predicting pharmacokinetics in the elderly (≥ 65 years) without any modification of drug parameters. A descriptive relationship between age and each investigated pharmacokinetic parameter (peak concentration [C The age-related changes in drug exposure were successfully simulated for all ten drugs. Pharmacokinetic parameters were predicted within 1.25-fold (70%), 1.5-fold (86%) and 2-fold (100%) of clinical data. AUC increased progressively by 0.9% per year throughout adulthood from the age of 20 years, which was explained by decreased clearance, while C The progressive decrease in hepatic and renal blood flow, as well as glomerular filtration, rate led to a reduced clearance driving exposure changes in the healthy elderly, independent of the drug.
Publisher: Springer Science and Business Media LLC
Date: 25-03-2023
DOI: 10.1038/S43856-023-00274-0
Abstract: Global progress against malaria has stagnated and novel medical interventions to prevent malaria are needed to fill gaps in existing tools and improve protection against infection and disease. Candidate selection for next-generation interventions should be supported by the best available evidence. Target product profiles and preferred product characteristics play a key role in setting selection criteria requirements and early endorsement by health authorities. While clinical evidence and expert opinion often inform product development decisions, integrating modelling evidence early and iteratively into this process provides an opportunity to link product characteristics with expected public health outcomes. Population models of malaria transmission can provide a better understanding of which, and at what magnitude, key intervention characteristics drive public health impact, and provide quantitative evidence to support selection of use-cases, transmission settings, and deployment strategies. We describe how modelling evidence can guide and accelerate development of new malaria vaccines, monoclonal antibodies, and chemoprevention.
Publisher: Cold Spring Harbor Laboratory
Date: 20-04-2021
DOI: 10.1101/2021.04.14.21255503
Abstract: As vaccination coverage against SARS-CoV-2 increases amidst the emergence and spread of more infectious and potentially more deadly viral variants, decisions on timing and extent of relaxing effective, but unsustainable, non-pharmaceutical interventions (NPIs) need to be made. An in idual- based transmission model of SARS-CoV-2 dynamics, OpenCOVID, was developed to compare the impact of various vaccination and NPI strategies on the COVID-19 epidemic in Switzerland. We estimate that any relaxation of NPIs in March 2021 will lead to increasing cases, hospitalisations, and deaths resulting in a ‘third wave’ in spring and into summer 2021. However, we find a cautious phased relaxation can substantially reduce population-level morbidity and mortality. We find that faster vaccination c aign can offset the size of such a wave, allowing more flexibility for NPI to be relaxed sooner. Our sensitivity analysis revealed that model results are particularly sensitive to the infectiousness of variant B.1.1.7.
Publisher: Elsevier BV
Date: 02-2019
DOI: 10.1016/J.JTBI.2018.10.050
Abstract: Development of resistance to malaria treatments remains a great threat to continued malaria burden reduction and elimination. Quantifying the impact of key factors which increase the emergence and spread of drug resistance can guide intervention strategies. Whilst modelling provides a framework to understand these factors, we show that a simple of model with a sensitive-resistant dichotomy leads to incorrectly focusing on reducing the treatment rate as a means to prevent resistance. Instead we present a model that considers the development of resistance within hosts as a scale, and we then quantify the number of resistant infections that would arise from a single sensitive infection. By including just one step before full resistance, the model highlights that disrupting this development is more effective than reducing treatment rate. This result is compounded when the model includes the more realistic scenario of several intermediary steps. An additional comparison to transmission probabilities, where resistant infections are less likely to be transmitted (cost of resistance), confirms that preventing the establishment of resistance is more effective than controlling the spread. Our work strongly advocates for further studies into within-host models of resistance, including the potential of combination therapies to disrupt emergence.
Publisher: Elsevier BV
Date: 03-2022
Publisher: Springer Science and Business Media LLC
Date: 18-11-2021
DOI: 10.1186/S12936-021-03973-Y
Abstract: Mathematical models are increasingly used to inform decisions throughout product development pathways from pre-clinical studies to country implementation of novel health interventions. This review illustrates the utility of simulation approaches by reviewing the literature on malaria vaccine modelling, with a focus on its link to the development of policy guidance for the first licensed product, RTS,S/AS01. The main contributions of modelling studies have been in inferring the mechanism of action and efficacy profile of RTS,S to predicting the public health impact and economic modelling mainly comprising cost-effectiveness analysis. The value of both product-specific and generic modelling of vaccines is highlighted.
Publisher: Cold Spring Harbor Laboratory
Date: 21-12-2016
Publisher: Elsevier BV
Date: 2008
Publisher: Springer Science and Business Media LLC
Date: 18-08-2010
Publisher: Elsevier BV
Date: 2008
Publisher: Springer Science and Business Media LLC
Date: 18-10-2017
Publisher: Springer Science and Business Media LLC
Date: 12-09-2022
Publisher: Springer Science and Business Media LLC
Date: 07-11-2013
Publisher: Proceedings of the National Academy of Sciences
Date: 09-2009
Abstract: Human rabies in developing countries can be prevented through interventions directed at dogs. Potential cost-savings for the public health sector of interventions aimed at animal-host reservoirs should be assessed. Available deterministic models of rabies transmission between dogs were extended to include dog-to-human rabies transmission. Model parameters were fitted to routine weekly rabid-dog and exposed-human cases reported in N′Djaména, the capital of Chad. The estimated transmission rates between dogs (β d ) were 0.0807 km 2 /(dogs·week) and between dogs and humans (β dh ) 0.0002 km 2 /(dogs·week). The effective reproductive ratio ( R e ) at the onset of our observations was estimated at 1.01, indicating low-level endemic stability of rabies transmission. Human rabies incidence depended critically on dog-related transmission parameters. We simulated the effects of mass dog vaccination and the culling of a percentage of the dog population on human rabies incidence. A single parenteral dog rabies-mass vaccination c aign achieving a coverage of least 70% appears to be sufficient to interrupt transmission of rabies to humans for at least 6 years. The cost-effectiveness of mass dog vaccination was compared to postexposure prophylaxis (PEP), which is the current practice in Chad. PEP does not reduce future human exposure. Its cost-effectiveness is estimated at US $46 per disability adjusted life-years averted. Cost-effectiveness for PEP, together with a dog-vaccination c aign, breaks even with cost-effectiveness of PEP alone after almost 5 years. Beyond a time-frame of 7 years, it appears to be more cost-effective to combine parenteral dog-vaccination c aigns with human PEP compared to human PEP alone.
Publisher: Springer Science and Business Media LLC
Date: 04-11-2015
Publisher: Springer Science and Business Media LLC
Date: 08-09-2015
DOI: 10.1038/NCOMMS9170
Abstract: In many countries health system data remain too weak to accurately enumerate Plasmodium falciparum malaria cases. In response, cartographic approaches have been developed that link maps of infection prevalence with mathematical relationships to predict the incidence rate of clinical malaria. Microsimulation (or ‘agent-based’) models represent a powerful new paradigm for defining such relationships however, differences in model structure and calibration data mean that no consensus yet exists on the optimal form for use in disease-burden estimation. Here we develop a Bayesian statistical procedure combining functional regression-based model emulation with Markov Chain Monte Carlo s ling to calibrate three selected microsimulation models against a purpose-built data set of age-structured prevalence and incidence counts. This allows the generation of ensemble forecasts of the prevalence–incidence relationship stratified by age, transmission seasonality, treatment level and exposure history, from which we predict accelerating returns on investments in large-scale intervention c aigns as transmission and prevalence are progressively reduced.
Publisher: Springer Science and Business Media LLC
Date: 03-01-2017
Publisher: Cold Spring Harbor Laboratory
Date: 05-03-2021
DOI: 10.1101/2021.03.05.434041
Abstract: Malaria blood-stage infection length and intensity are important drivers of disease and transmission however, the underlying mechanisms of parasite growth and the host’s immune response during infection remain largely unknown. Over the last 30 years, several mechanistic mathematical models of malaria parasite within-host dynamics have been published and used in malaria transmission models. We identified mechanistic within-host models of parasite dynamics through a review of published literature. For a subset of these, we reproduced model code and compared descriptive statistics between the models using fitted data. Through simulation and model analysis, we compare and discuss key features of the models, including assumptions on growth, immune response components, variant switching mechanisms, and inter-in idual variability. The assessed within-host malaria models generally replicate infection dynamics in malaria-naïve in iduals. However, there are substantial differences between the model dynamics after disease onset, and models do not always reproduce late infection parasitemia data used for calibration of the within host infections. Models have attempted to capture the considerable variability in parasite dynamics between in iduals by including stochastic parasite multiplication rates variant switching dynamics leading to immune escape variable effects of the host immune responses or via probabilistic events. For models that capture realistic length of infections, model representations of innate immunity explain early peaks in infection density that cause clinical symptoms, and model representations of antibody immune responses control the length of infection. Models differed in their assumptions concerning variant switching dynamics, reflecting uncertainty in the underlying mechanisms of variant switching revealed by recent clinical data during early infection. Overall, given the scarce availability of the biological evidence there is limited support for complex models. Our study suggests that much of the inter-in idual variability observed in clinical malaria infections has traditionally been attributed in models to random variability, rather than mechanistic disease dynamics. Thus, we propose that newly developed models should assume simple immune dynamics that minimally capture mechanistic understandings and avoid over-parameterisation and large stochasticity which inaccurately represent unknown disease mechanisms.
Publisher: Springer Science and Business Media LLC
Date: 10-07-2021
DOI: 10.1186/S12936-021-03813-Z
Abstract: Malaria blood-stage infection length and intensity are important drivers of disease and transmission however, the underlying mechanisms of parasite growth and the host’s immune response during infection remain largely unknown. Over the last 30 years, several mechanistic mathematical models of malaria parasite within-host dynamics have been published and used in malaria transmission models. Mechanistic within-host models of parasite dynamics were identified through a review of published literature. For a subset of these, model code was reproduced and descriptive statistics compared between the models using fitted data. Through simulation and model analysis, key features of the models were compared, including assumptions on growth, immune response components, variant switching mechanisms, and inter-in idual variability. The assessed within-host malaria models generally replicate infection dynamics in malaria-naïve in iduals. However, there are substantial differences between the model dynamics after disease onset, and models do not always reproduce late infection parasitaemia data used for calibration of the within host infections. Models have attempted to capture the considerable variability in parasite dynamics between in iduals by including stochastic parasite multiplication rates variant switching dynamics leading to immune escape variable effects of the host immune responses or via probabilistic events. For models that capture realistic length of infections, model representations of innate immunity explain early peaks in infection density that cause clinical symptoms, and model representations of antibody immune responses control the length of infection. Models differed in their assumptions concerning variant switching dynamics, reflecting uncertainty in the underlying mechanisms of variant switching revealed by recent clinical data during early infection. Overall, given the scarce availability of the biological evidence there is limited support for complex models. This study suggests that much of the inter-in idual variability observed in clinical malaria infections has traditionally been attributed in models to random variability, rather than mechanistic disease dynamics. Thus, it is proposed that newly developed models should assume simple immune dynamics that minimally capture mechanistic understandings and avoid over-parameterization and large stochasticity which inaccurately represent unknown disease mechanisms.
Publisher: Public Library of Science (PLoS)
Date: 13-05-2014
Publisher: eLife Sciences Publications, Ltd
Date: 13-06-2020
Publisher: Wiley
Date: 18-09-2020
DOI: 10.1002/CPT.2017
Publisher: Elsevier BV
Date: 10-2017
Publisher: Elsevier BV
Date: 08-2020
Publisher: Elsevier BV
Date: 07-2016
Publisher: eLife Sciences Publications, Ltd
Date: 19-06-2022
Publisher: Springer Science and Business Media LLC
Date: 26-10-2022
DOI: 10.1186/S12936-022-04317-0
Abstract: Mathematical models provide an understanding of the dynamics of a Plasmodium falciparum blood-stage infection (within-host models), and can predict the impact of control strategies that affect the blood-stage of malaria. However, the dynamics of P. falciparum blood-stage infections are highly variable between in iduals. Within-host models use different techniques to capture this inter-in idual variation. This struggle may be unnecessary because patients can be clustered according to similar key within-host dynamics. This study aimed to identify clusters of patients with similar parasitaemia profiles so that future mathematical models can include an improved understanding of within-host variation. Patients’ parasitaemia data were analyzed to identify (i) clusters of patients (from 35 patients) that have a similar overall parasitaemia profile and (ii) clusters of patients (from 100 patients) that have a similar first wave of parasitaemia. For each cluster analysis, patients were clustered based on key features which previous models used to summarize parasitaemia dynamics. The clustering analyses were performed using a finite mixture model. The centroid values of the clusters were used to parameterize two established within-host models to generate parasitaemia profiles. These profiles (that used the novel centroid parameterization) were compared with profiles that used in idual-specific parameterization (as in the original models), as well as profiles that ignored in idual variation (using overall means for parameterization). To capture the variation of within-host dynamics, when studying the overall parasitaemia profile, two clusters efficiently grouped patients based on their infection length and the height of the first parasitaemia peak. When studying the first wave of parasitaemia, five clusters efficiently grouped patients based on the height of the peak and the speed of the clearance following the peak of parasitaemia. The clusters were based on features that summarize the strength of patient innate and adaptive immune responses. Parameterizing previous within host-models based on cluster centroid values accurately predict in idual patient parasitaemia profiles. This study confirms that patients have personalized immune responses, which explains the variation of parasitaemia dynamics. Clustering can guide the optimal inclusion of within-host variation in future studies, and inform the design and parameterization of population-based models.
Publisher: Springer Science and Business Media LLC
Date: 03-08-2010
Publisher: Springer Science and Business Media LLC
Date: 04-06-2022
DOI: 10.1186/S40249-022-00981-1
Abstract: Substantial research is underway to develop next-generation interventions that address current malaria control challenges. As there is limited testing in their early development, it is difficult to predefine intervention properties such as efficacy that achieve target health goals, and therefore challenging to prioritize selection of novel candidate interventions. Here, we present a quantitative approach to guide intervention development using mathematical models of malaria dynamics coupled with machine learning. Our analysis identifies requirements of efficacy, coverage, and duration of effect for five novel malaria interventions to achieve targeted reductions in malaria prevalence. A mathematical model of malaria transmission dynamics is used to simulate deployment and predict potential impact of new malaria interventions by considering operational, health-system, population, and disease characteristics. Our method relies on consultation with product development stakeholders to define the putative space of novel intervention specifications. We couple the disease model with machine learning to search this multi-dimensional space and efficiently identify optimal intervention properties that achieve specified health goals. We apply our approach to five malaria interventions under development. Aiming for malaria prevalence reduction, we identify and quantify key determinants of intervention impact along with their minimal properties required to achieve the desired health goals. While coverage is generally identified as the largest driver of impact, higher efficacy, longer protection duration or multiple deployments per year are needed to increase prevalence reduction. We show that interventions on multiple parasite or vector targets, as well as combinations the new interventions with drug treatment, lead to significant burden reductions and lower efficacy or duration requirements. Our approach uses disease dynamic models and machine learning to support decision-making and resource investment, facilitating development of new malaria interventions. By evaluating the intervention capabilities in relation to the targeted health goal, our analysis allows prioritization of interventions and of their specifications from an early stage in development, and subsequent investments to be channeled cost-effectively towards impact maximization. This study highlights the role of mathematical models to support intervention development. Although we focus on five malaria interventions, the analysis is generalizable to other new malaria interventions.
Publisher: Wiley
Date: 14-06-2020
DOI: 10.1111/BCP.14402
Abstract: The impact of ageing on antiretroviral pharmacokinetics remains uncertain, leading to missing dosing recommendations for elderly people living with human immunodeficiency virus (HIV: PLWH). The objective of this study was to investigate whether ageing leads to clinically relevant pharmacokinetic changes of antiretrovirals that would support a dose adjustment based on the age of the treated PLWH. Plasma concentrations for 10 first‐line antiretrovirals were obtained in PLWH ≥55 years, participating in the Swiss HIV Cohort Study, and used to proof the predictive performance of our physiologically based pharmacokinetic (PBPK) model. The verified PBPK model predicted the continuous effect of ageing on HIV drug pharmacokinetics across adulthood (20–99 years). The impact of ethnicity on age‐related pharmacokinetic changes between whites and other races was statistically analysed. Clinically observed concentration–time profiles of all investigated antiretrovirals were generally within the 95% confidence interval of the PBPK simulations, demonstrating the predictive power of the modelling approach used. The predicted decline in drug clearance drove age‐related pharmacokinetic changes of antiretrovirals, resulting in a maximal 70% [95% confidence interval: 40%, 120%] increase in antiretrovirals exposure across adulthood. Peak concentration, time to peak concentration and apparent volume of distribution were predicted to be unaltered by ageing. There was no statistically significant difference of age‐related pharmacokinetic changes between studied ethnicities. Dose adjustment for antiretrovirals based on the age of male and female PLWH is a priori not necessary in the absence of severe comorbidities considering the large safety margin of the current first‐line HIV treatments.
Publisher: Springer New York
Date: 2017
Publisher: Springer Science and Business Media LLC
Date: 12-2019
DOI: 10.1186/S12936-019-3019-0
Abstract: Field studies are evaluating if mass drug administration (MDA) might shorten the time to elimination of Plasmodium falciparum malaria, when vector control measures and reactive surveillance strategies are scaled-up. A concern with this strategy is that there may be resurgence of transmission following MDA. A conceptual model was developed to classify possible outcomes of an initial period of MDA, followed by continuously implementing other interventions. The classification considered whether elimination or a new endemic stable state is achieved, and whether changes are rapid, transient, or gradual. These categories were informed by stability analyses of simple models of vector control, case management, and test-and-treat interventions. In idual-based stochastic models of malaria transmission ( OpenMalaria ) were then used to estimate the probability and likely rates of resurgence in realistic settings. Effects of concurrent interventions, including routine case management and test-and-treat strategies were investigated. Analysis of the conceptual models suggest resurgence will occur after MDA unless transmission potential is very low, or the post-MDA prevalence falls below a threshold, which depends on both transmission potential and on the induction of bistability. Importation rates are important only when this threshold is very low. In most OpenMalaria simulations the approximately stable state achieved at the end of the simulations was independent of inclusion of MDA and the final state was unaffected by importation of infections at plausible rates. Elimination occurred only with high effective coverage of case management, low initial prevalence, and high intensity test-and-treat. High coverage of case management but not by test-and-treat induced bistability. Where resurgence occurred, its rate depended mainly on transmission potential (not treatment rates). A short burst of high impact MDA is likely to be followed by resurgence. To avert resurgence, concomitant interventions need either to substantially reduce average transmission potential or to be differentially effective in averting or clearing infections at low prevalence. Case management at high effective coverage has this differential effect, and should suffice to avert resurgence caused by imported cases at plausible rates of importation. Once resurgence occurs, its rate depends mainly on transmission potential, not on treatment strategies.
Publisher: Springer Science and Business Media LLC
Date: 25-07-2015
Publisher: Springer Science and Business Media LLC
Date: 29-07-2015
Publisher: Wiley
Date: 02-04-2019
DOI: 10.1002/PSP4.12399
Publisher: American Society for Microbiology
Date: 10-2016
DOI: 10.1128/AAC.00992-16
Abstract: Praziquantel is the only drug available for the treatment of Opisthorchis viverrini infections. Tribendimidine has emerged as a potential treatment alternative however, its pharmacokinetic (PK) properties have not been sufficiently studied to date. Via two phase IIa dose-finding studies, 68 O. viverrini patients were treated with 25- to 600-mg doses of tribendimidine using 50- and 200-mg tablet formulations. Plasma, blood, and dried blood spots (DBS) were s led at selected time points. The two main metabolites of tribendimidine, active deacetylated amidantel (dADT) and acetylated dADT (adADT), were analyzed in plasma, blood, and DBS. PK parameters were estimated by noncompartmental analysis. An acceptable agreement among plasma and DBS concentrations was observed, with a mean bias of ≤10%, and 60% dADT and 74% adADT concentrations being within ±20% margins. We found that 200-mg tribendimidine tablets possess immediate floating characteristics, which led to variable time to maximal concentration of drug ( T max ) values (2 to 24 h) between in iduals. Dose proportionality was observed for dADT from 25 to 200 mg using 50-mg tablets, but at higher dosages (200 to 600 mg), saturation occurred. The median ratio of the area under the plasma concentration-time curve from 0 to 24 h (AUC 0–24 ) of dADT to the AUC 0– 24 of adADT ranged from 0.8 to 26.4, suggesting substantial differences in acetylation rates. Cure rates ranged from 11% (25-mg dose) to 100% (400-mg dose). Cured patients showed significantly higher dADT maximal serum concentrations ( C max ) and AUC 0–24 values than uncured patients. Tribendimidine is a promising drug for the treatment of opisthorchiasis. However, the tablet formulation should be optimized to achieve consistent absorption among patients. Further studies are warranted to assess the large differences between in iduals in the rate of metabolic turnover of dADT to adADT. (This study has been registered with the ISRCTN Registry under no. ISRCTN96948551.)
Publisher: American Society for Microbiology
Date: 10-2018
DOI: 10.1128/AAC.02193-17
Abstract: Amodiaquine plus artesunate is the recommended antimalarial treatment in many countries where malaria is endemic. However, pediatric doses are largely based on a linear extrapolation from adult doses.
Publisher: Elsevier BV
Date: 02-2013
DOI: 10.1016/J.MBS.2012.11.013
Abstract: Mosquito dispersal is a key behavioural factor that affects the persistence and resurgence of several vector-borne diseases. Spatial heterogeneity of mosquito resources, such as hosts and breeding sites, affects mosquito dispersal behaviour and consequently affects mosquito population structures, human exposure to vectors, and the ability to control disease transmission. In this paper, we develop and simulate a discrete-space continuous-time mathematical model to investigate the impact of dispersal and heterogeneous distribution of resources on the distribution and dynamics of mosquito populations. We build an ordinary differential equation model of the mosquito life cycle and replicate it across a hexagonal grid (multi-patch system) that represents two-dimensional space. We use the model to estimate mosquito dispersal distances and to evaluate the effect of spatial repellents as a vector control strategy. We find evidence of association between heterogeneity, dispersal, spatial distribution of resources, and mosquito population dynamics. Random distribution of repellents reduces the distance moved by mosquitoes, offering a promising strategy for disease control.
Publisher: Springer Science and Business Media LLC
Date: 21-01-2022
DOI: 10.1186/S12916-021-02214-Y
Abstract: With the recent certification by World Health Organization that the People’s Republic of China is malaria-free, it is timely to consider how elimination of malaria was completed in People’s Republic of China over the last 7 decades. Of the four widespread species of human malaria, Plasmodium vivax was the last to be eliminated by the national program of China. Understanding the incubation periods and relapses patterns of P. vivax through historical data from China is relevant for planning disease elimination in other malaria-endemic countries, with residual P. vivax malaria. We collated data from both published and unpublished malaria parasite inoculation experiments conducted between 1979 and 1988 with parasites from different regions of the People’s Republic of China. The studies had at least two years of follow-up. We categorized P. vivax incubation patterns via cluster analysis and investigated relapse studies by adapting a published within-host relapse model for P. vivax temperate phenotypes. Each model was fitted using the expectation-maximization (EM) algorithm initialized by hierarchical model-based agglomerative clustering. P. vivax parasites from the seven studies of five southern and central provinces in the People’s Republic of China covering geographies ranging from the south temperate to north tropical zones. The parasites belonged to two distinct phenotypes: short- (10–19 days) or long-incubation (228–371 days). The larger the sporozoite inoculation, the more likely short incubation periods were observed, and with more subsequent relapses (Spearman’s rank correlation between the number of inoculated sporozoites and the number of relapses of 0.51, p -value = 0.0043). The median of the posterior distribution for the duration of the first relapse interval after primary infection was 168.5 days (2.5% quantile: 89.7 97.5% quantile: 227.69 days). The predicted survival proportions from the within-host model fit well to the original relapse data. The within-host model also captures the hypnozoite activation rates and relapse frequencies, which consequently influences the transmission possibility of P. vivax . Through a within-host model, we demonstrate the importance of clearance of hypnozoites. A strategy of two rounds of radical hypnozoite clearance via mass drug administration (MDA) deployed during transmission (summer and autumn) and non-transmission (late spring) seasons had a pronounced effect on outbreaks during the malaria epidemics in China. This understanding can inform malaria control strategies in other endemic countries with similar settings.
Publisher: Springer Science and Business Media LLC
Date: 10-12-2021
DOI: 10.1038/S41467-021-27486-Z
Abstract: In idual-based models have become important tools in the global battle against infectious diseases, yet model complexity can make calibration to biological and epidemiological data challenging. We propose using a Bayesian optimization framework employing Gaussian process or machine learning emulator functions to calibrate a complex malaria transmission simulator. We demonstrate our approach by optimizing over a high-dimensional parameter space with respect to a portfolio of multiple fitting objectives built from datasets capturing the natural history of malaria transmission and disease progression. Our approach quickly outperforms previous calibrations, yielding an improved final goodness of fit. Per-objective parameter importance and sensitivity diagnostics provided by our approach offer epidemiological insights and enhance trust in predictions through greater interpretability.
Publisher: eLife Sciences Publications, Ltd
Date: 07-07-2022
DOI: 10.7554/ELIFE.77634
Abstract: The effectiveness of artemisinin-based combination therapies (ACTs) to treat Plasmodium falciparum malaria is threatened by resistance. The complex interplay between sources of selective pressure—treatment properties, biological factors, transmission intensity, and access to treatment—obscures understanding how, when, and why resistance establishes and spreads across different locations. We developed a disease modelling approach with emulator-based global sensitivity analysis to systematically quantify which of these factors drive establishment and spread of drug resistance. Drug resistance was more likely to evolve in low transmission settings due to the lower levels of (i) immunity and (ii) within-host competition between genotypes. Spread of parasites resistant to artemisinin partner drugs depended on the period of low drug concentration (known as the selection window). Spread of partial artemisinin resistance was slowed with prolonged parasite exposure to artemisinin derivatives and accelerated when the parasite was also resistant to the partner drug. Thus, to slow the spread of partial artemisinin resistance, molecular surveillance should be supported to detect resistance to partner drugs and to change ACTs accordingly. Furthermore, implementing more sustainable artemisinin-based therapies will require extending parasite exposure to artemisinin derivatives, and mitigating the selection windows of partner drugs, which could be achieved by including an additional long-acting drug.
Publisher: Springer Science and Business Media LLC
Date: 25-07-2022
DOI: 10.1038/S43856-022-00154-Z
Abstract: SARS-CoV-2 variants of concern, such as Omicron (B.1.1.529), continue to emerge. Assessing the impact of their potential viral properties on the probability of future transmission dominance and public health burden is fundamental in guiding ongoing COVID-19 control strategies. With an in idual-based transmission model, OpenCOVID, we simulated three viral properties infectivity, severity, and immune-evading ability, all relative to the Delta variant, to identify thresholds for Omicron’s or any emerging VOC’s potential future dominance, impact on public health, and risk to health systems. We further identify for which combinations of viral properties current interventions would be sufficient to control transmission. We show that, with first-generation SARS-CoV-2 vaccines and limited physical distancing in place, a VOC’s potential future dominance is primarily driven by its infectivity, which does not always lead to an increased public health burden. However, we also show that highly immune-evading variants that become dominant, even in the case of reduced variant severity, would likely require alternative measures to avoid strain on health systems, such as strengthened physical distancing measures, novel treatments, and second-generation vaccines. Expanded vaccination, that includes a booster dose for adults and child vaccination strategies, is projected to have the biggest public health benefit for a highly infective, highly severe VOC with low immune-evading capacity. These findings provide quantitative guidance to decision-makers at a critical time while Omicron’s properties are being assessed and preparedness for emerging VOCs is eminent. We emphasise the importance of both genomic and population epidemiological surveillance.
Publisher: Cold Spring Harbor Laboratory
Date: 06-01-2021
DOI: 10.1101/2021.01.05.21249283
Abstract: Substantial research is underway to develop next-generation interventions that address current malaria control challenges. As there is limited testing in their early development, it is difficult to predefine intervention properties such as efficacy that achieve target health goals, and therefore challenging to prioritize selection of novel candidate interventions. Here, we present a quantitative approach to guide intervention development using mathematical models of malaria dynamics coupled with machine learning. Our analysis identifies requirements of efficacy, coverage, and duration of effect for five novel malaria interventions to achieve targeted reductions in malaria prevalence. This study highlights the role of mathematical models to support intervention development. A mathematical model of malaria transmission dynamics is used to simulate deployment and predict potential impact of new malaria interventions by considering operational, health-system, population, and disease characteristics. Our method relies on consultation with product development stakeholders to define the putative space of novel intervention specifications. We couple the disease model with machine learning to search this multi-dimensional space and efficiently identify optimal intervention properties that achieve specified health goals. We demonstrate the power of our approach by application to five malaria interventions in development. Aiming for malaria prevalence reduction, we identify and quantify key determinants of intervention impact along with their minimal properties required to achieve the desired health goals. While coverage is generally identified as the largest driver of impact, higher efficacy, longer protection duration or multiple deployments per year are needed to increase prevalence reduction. We show that the efficacy and duration needs depend on the biological action of the interventions. Interventions on multiple parasite or vector targets, as well as combinations the new interventions with drug treatment, lead to significant burden reductions and lower efficacy or duration requirements. Our approach uses disease dynamic models and machine learning to support decision-making and resource investment, facilitating development of new malaria interventions. By evaluating the intervention capabilities in relation to the targeted health goal, our analysis allows prioritization of interventions and of their specifications from an early stage in development, and subsequent investments to be channeled cost-effectively towards impact maximization. Although we focus on five malaria interventions, the analysis is generalizable to other new malaria interventions.
Publisher: Springer Science and Business Media LLC
Date: 21-08-2018
DOI: 10.1007/S40262-018-0709-7
Abstract: Aging is characterized by anatomical, physiological, and biological changes that can impact drug kinetics. The elderly are often excluded from clinical trials and knowledge about drug kinetics and drug-drug interaction magnitudes is sparse. Physiologically based pharmacokinetic modeling can overcome this clinical limitation but detailed descriptions of the population characteristics are essential to adequately inform models. The objective of this study was to develop and verify a population database for aging Caucasians considering anatomical, physiological, and biological system parameters required to inform a physiologically based pharmacokinetic model that included population variability. A structured literature search was performed to analyze age-dependent changes of system parameters. All collated data were carefully analyzed, and descriptive mathematical equations were derived. A total of 362 studies were found of which 318 studies were included in the analysis as they reported rich data for anthropometric parameters and specific organs (e.g., liver). Continuous functions could be derived for most system parameters describing a Caucasian population from 20 to 99 years of age with variability. Areas with sparse data were identified such as tissue composition, but knowledge gaps were filled with plausible qualified assumptions. The developed population was implemented in Matlab The developed repository for aging subjects provides a singular specific source for key system parameters needed for physiologically based pharmacokinetic modeling and can in turn be used to investigate drug kinetics and drug-drug interaction magnitudes in the elderly.
Publisher: American Society for Microbiology
Date: 17-05-2022
DOI: 10.1128/AAC.01696-21
Abstract: The combination antimalarial therapy of artemisinin-naphthoquine (ART-NQ) was developed as a single-dose therapy, aiming to improve adherence relative to the multiday schedules of other artemisinin combination therapies. The pharmacokinetics of ART-NQ has not been well characterized, especially in children. A pharmacokinetic study was conducted in adults and children over 5 years of age (6 to 10, 11 to 17, and ≥18 years of age) with uncomplicated malaria in Tanzania.
Publisher: American Society for Microbiology
Date: 18-03-2021
DOI: 10.1128/AAC.01539-20
Abstract: Ensuring continued success against malaria depends on a pipeline of new antimalarials. Antimalarial drug development utilizes preclinical murine and experimental human malaria infection studies to evaluate drug efficacy.
Publisher: eLife Sciences Publications, Ltd
Date: 14-07-2020
DOI: 10.7554/ELIFE.53080
Abstract: Tanzanian adult male volunteers were immunized by direct venous inoculation with radiation-attenuated, aseptic, purified, cryopreserved Plasmodium falciparum (Pf) sporozoites (PfSPZ Vaccine) and protective efficacy assessed by homologous controlled human malaria infection (CHMI). Serum immunoglobulin G (IgG) responses were analyzed longitudinally using a Pf protein microarray covering 91% of the proteome, providing first insights into naturally acquired and PfSPZ Vaccine-induced whole parasite antibody profiles in malaria pre-exposed Africans. Immunoreactivity was identified against 2239 functionally erse Pf proteins, showing a wide breadth of humoral response. Antibody-based immune ‘fingerprints’ in these in iduals indicated a strong person-specific immune response at baseline, with little changes in the overall humoral immunoreactivity pattern measured after immunization. The moderate increase in immunogenicity following immunization and the extensive and variable breadth of humoral immune response observed in the volunteers at baseline suggest that pre-exposure reduces vaccine-induced antigen reactivity in unanticipated ways.
Publisher: Springer Science and Business Media LLC
Date: 16-09-2015
DOI: 10.1038/NATURE15535
Publisher: Public Library of Science (PLoS)
Date: 16-07-2008
Publisher: Springer Science and Business Media LLC
Date: 05-10-2015
Publisher: Springer Science and Business Media LLC
Date: 23-11-2020
DOI: 10.1186/S12936-020-03501-4
Abstract: Malaria was once a serious public health problem in China, with Plasmodium vivax the major species responsible for more than 90% of local transmission. Following significant integrated malaria control and elimination programmes, malaria burden declined, and since 2017 China has not recorded any indigenous case. To understand the historical malaria transmission patterns and epidemic characteristics in China and insights useful to guide P. vivax malaria control and elimination elsewhere, a retrospective study was carried out. Historical data from a pilot study conducted in Guantang, Luyi in central China from 1971–1995, were digitized. The data included monthly numbers of reported cases, febrile cases, parasite carriage rates, the neonatal infection rate, and entomological data regarding Anopheles sinensis . Following 25 years of continuous integrated malaria control activities, malaria incidence in Guantang decreased from 4,333 cases per 10,000 in 1970 before integrated implementation to 0.23 cases per 10,000 in 1991, and no cases in 1992–1995. Some fluctuations in incidence were observed between 1977 and 1981. During the period parasite rates, antibody levels and the neonatal infection rate also decreased. The pattern of seasonality confirmed that P. vivax in Henan Province was primarily of the long incubation type (temperate) during non-transmission period. The findings retrospectively provide a scientific basis for the implementation of mass c aigns of liver stage hypnozoite clearance. Entomological studies indicated that An. sinensis was the only vector, and it preferred bovine to human hosts, predominantly biting and resting outdoors . Mosquito densities declined between 1971 and 1984. The integrated malaria control approach in Guantang effectively controlled malaria and achieved elimination. Analysis of the effectiveness of the programme can provide guidance to other regions or countries with similar ecological settings aiming to move from malaria control to elimination. There is a potential challenge in the maintenance of non-transmission status owing to imported cases and the long dormancy of liver stage hypnozoites.
Publisher: Cold Spring Harbor Laboratory
Date: 10-04-2021
DOI: 10.1101/2021.04.08.437876
Abstract: Artemisinin-resistant genotypes have now emerged a minimum of five times on three continents despite recommendations that all artemisinins be deployed as artemisinin combination therapies (ACTs). Widespread resistance to the non-artemisinin partner drugs in ACTs has the potential to limit the clinical and resistance benefits provided by combination therapy. Using a consensus modelling approach with three in idual-based mathematical models of Plasmodium falciparum transmission, we evaluate the effects of pre-existing partner-drug resistance and ACT deployment on artemisinin resistance evolution. We evaluate settings where dihydroartemisinin-piperaquine (DHA-PPQ), artesunate-amodiaquine (ASAQ), or artemether-lumefantrine (AL) are deployed as first-line therapy. We use time until 0.25 artemisinin resistance allele frequency (the establishment time) as the primary outcome measure. Higher frequencies of pre-existing partner-drug resistant genotypes lead to earlier establishment of artemisinin resistance. Across all scenarios and pre-existing frequencies of partner-drug resistance explored, a 0.10 increase in partner-drug resistance frequency on average corresponded to 0.7 to 5.0 years loss of artemisinin efficacy. However, the majority of reductions in time to artemisinin establishment were observed after the first increment from 0.0 to 0.10 partner-drug resistance genotype frequency. Partner-drug resistance in ACTs facilitates the early emergence of artemisinin resistance and is a major public health concern. Higher grade partner-drug resistance has the largest effect, with piperaquine-resistance accelerating early emergence of artemisinin-resistant alleles the most. Continued investment in molecular surveillance of partner-drug resistant genotypes to guide choice of first-line ACT is paramount. Bill and Melinda Gates Foundation Wellcome Trust.
Publisher: Elsevier BV
Date: 2016
Publisher: Cold Spring Harbor Laboratory
Date: 19-10-2023
Publisher: Massachusetts Medical Society
Date: 22-06-2017
DOI: 10.1056/NEJMC1701144
Publisher: Public Library of Science (PLoS)
Date: 27-06-2014
Publisher: Cold Spring Harbor Laboratory
Date: 13-10-2023
Publisher: Elsevier BV
Date: 2017
DOI: 10.1016/J.VACCINE.2016.11.042
Abstract: RTS,S/AS01 is a safe and moderately efficacious vaccine considered for implementation in endemic Africa. Model predictions of impact and cost-effectiveness of this new intervention could aid in country adoption decisions. The impact of RTS,S was assessed in 43 countries using an ensemble of models of Plasmodium falciparum epidemiology. Informed by the 32months follow-up data from the phase 3 trial, vaccine effectiveness was evaluated at country levels of malaria parasite prevalence, coverage of control interventions and immunization. Benefits and costs of the program incremental to routine malaria control were evaluated for a four dose schedule: first dose administered at six months, second and third - before 9months, and fourth dose at 27months of age. Sensitivity analyses around vaccine properties, transmission, and economic inputs were conducted. If implemented in all 43 countries the vaccine has the potential to avert 123 (117 ) million malaria episodes over the first 10years. Burden averted averages 18,413 (range of country median estimates 156-40,054) DALYs per 100,000 fully vaccinated children with much variation across settings primarily driven by differences in transmission intensity. At a price of $5 per dose program costs average $39.8 per fully vaccinated child with a median cost-effectiveness ratio of $188 (range $78-$22,448) per DALY averted the ratio is lower by one third - $136 (range $116-$220) - in settings where parasite prevalence in children aged 2-10years is at or above 10%. RTS,S/AS01has the potential to substantially reduce malaria burden in children across Africa. Conditional on assumptions on price, coverage, and vaccine properties, adding RTS,S to routine malaria control interventions would be highly cost-effective. Implementation decisions will need to further consider feasibility of scaling up existing control programs, and operational constraints in reaching children at risk with the schedule.
Publisher: Cold Spring Harbor Laboratory
Date: 29-01-2021
DOI: 10.1101/2021.01.27.21250484
Abstract: In idual-based models have become important tools in the global battle against infectious diseases, yet model complexity can make calibration to biological and epidemiological data challenging. We propose a using a Bayesian optimization framework employing Gaussian process or machine learning emulator functions to calibrate a complex malaria transmission simulator. We demonstrate our approach by optimizing over a high-dimensional parameter space with respect to a portfolio of multiple fitting objectives built from datasets capturing the natural history of malaria transmission and disease progression. Our approach quickly outperforms previous calibrations, yielding an improved final goodness of fit. Per-objective parameter importance and sensitivity diagnostics provided by our approach offer epidemiological insights and enhance trust in predictions through greater interpretability.
Publisher: American Society for Microbiology
Date: 10-2016
DOI: 10.1128/AAC.00655-16
Abstract: There is a pressing need for alternative treatments against the liver fluke Opisthorchis viverrini . Oral tribendimidine is a promising candidate, but its population pharmacokinetic properties are unknown. Two phase IIa trials were conducted in Laos in O. viverrini -infected adults receiving single oral doses of 25 to 600 mg tribendimidine administered as different formulations in each study (study 1 used 200-mg tablets, and study 2 used 50-mg tablets). Venous whole blood, plasma, and capillary dried blood spots were s led frequently from 68 adults, and concentrations of the tribendimidine metabolites dADT (deacetylated amidantel) and adADT (acetylated dADT) were measured. Population pharmacokinetics were assessed by using nonlinear mixed-effects modeling. The relationship between drug exposure and cure (assessed at 21 days posttreatment) was evaluated by using univariable logistic regression. A six-transit compartment absorption model with a one-disposition compartment for each metabolite described the data well. Compared to the 50-mg formulation (study 2), the 200-mg formulation (study 1) had a 40.1% higher mean transit absorption time, a 113% higher dADT volume of distribution, and a 364% higher adADT volume of distribution. Each 10-year increase in age was associated with a 12.7% lower dADT clearance and a 21.2% lower adADT clearance. The highest cure rates (≥55%) were observed with doses of ≥100 mg. Higher dADT, but not adADT, peak concentrations and exposures were associated with cure ( P = 0.004 and 0.003, respectively). For the first time, population pharmacokinetics of tribendimidine have been described. Known differences in the 200-mg versus 50-mg formulations were captured by covariate modeling. Further studies are needed to validate the structural model and confirm covariate relationships. (This study has been registered with the ISRCTN Registry under no. ISRCTN96948551.)
Publisher: International Global Health Society
Date: 25-08-2019
Publisher: Springer Science and Business Media LLC
Date: 14-09-2020
DOI: 10.1186/S12936-020-03405-3
Abstract: Malaria programmes in countries with low transmission levels require evidence to optimize deployment of current and new tools to reach elimination with limited resources. Recent pilots of elimination strategies in Ethiopia, Senegal, and Zambia produced evidence of their epidemiological impacts and costs. There is a need to generalize these findings to different epidemiological and health systems contexts. Drawing on experience of implementing partners, operational documents and costing studies from these pilots, reference scenarios were defined for rapid reporting (RR), reactive case detection (RACD), mass drug administration (MDA), and in-door residual spraying (IRS). These generalized interventions from their trial implementation to one typical of programmatic delivery. In doing so, resource use due to interventions was isolated from research activities and was related to the pilot setting. Costing models developed around this reference implementation, standardized the scope of resources costed, the valuation of resource use, and the setting in which interventions were evaluated. Sensitivity analyses were used to inform generalizability of the estimates and model assumptions. Populated with local prices and resource use from the pilots, the models yielded an average annual economic cost per capita of $0.18 for RR, $0.75 for RACD, $4.28 for MDA (two rounds), and $1.79 for IRS (one round, 50% households). Intervention design and resource use at service delivery were key drivers of variation in costs of RR, MDA, and RACD. Scale was the most important parameter for IRS. Overall price level was a minor contributor, except for MDA where drugs accounted for 70% of the cost. The analyses showed that at implementation scales comparable to health facility catchment area, systematic correlations between model inputs characterizing implementation and setting produce large gradients in costs. Prospective costing models are powerful tools to explore resource and cost implications of policy alternatives. By formalizing translation of operational data into an estimate of intervention cost, these models provide the methodological infrastructure to strengthen capacity gap for economic evaluation in endemic countries. The value of this approach for decision-making is enhanced when primary cost data collection is designed to enable analysis of the efficiency of operational inputs in relation to features of the trial or the setting, thus facilitating transferability.
Publisher: Public Library of Science (PLoS)
Date: 11-09-2008
Publisher: Elsevier BV
Date: 06-2004
Publisher: Elsevier BV
Date: 10-2022
Publisher: Elsevier BV
Date: 07-2017
Publisher: Public Library of Science (PLoS)
Date: 14-03-2022
DOI: 10.1371/JOURNAL.PGPH.0000211
Abstract: Seasonal malaria chemoprevention (SMC) has proven highly efficacious in reducing malaria incidence. However, the continued success of SMC is threatened by the spread of resistance against one of its main preventive ingredients, Sulfadoxine-Pyrimethamine (SP), operational challenges in delivery, and incomplete adherence to the regimens. Via a simulation study with an in idual-based model of malaria dynamics, we provide quantitative evidence to assess long-acting injectables (LAIs) as potential alternatives to SMC. We explored the predicted impact of a range of novel preventive LAIs as a seasonal prevention tool in children aged three months to five years old during late-stage clinical trials and at implementation. LAIs were co-administered with a blood-stage clearing drug once at the beginning of the transmission season. We found the establishment of non-inferiority of LAIs to standard 3 or 4 rounds of SMC with SP-amodiaquine was challenging in clinical trial stages due to high intervention deployment coverage. However, our analysis of implementation settings where the achievable SMC coverage was much lower, show LAIs with fewer visits per season are potential suitable replacements to SMC. Suitability as a replacement with higher impact is possible if the duration of protection of LAIs covered the duration of the transmission season. Furthermore, optimising LAIs coverage and protective efficacy half-life via simulation analysis in settings with an SMC coverage of 60% revealed important trade-offs between protective efficacy decay and deployment coverage. Our analysis additionally highlights that for seasonal deployment for LAIs, it will be necessary to investigate the protective efficacy decay as early as possible during clinical development to ensure a well-informed candidate selection process.
Publisher: Springer Science and Business Media LLC
Date: 29-10-2019
DOI: 10.1186/S12879-019-4467-4
Abstract: The only licensed malaria vaccine, RTS,S/AS01, has been developed for morbidity-control in young children. The potential impact on transmission of deploying such anti-infective vaccines to wider age ranges, possibly with co-administration of antimalarial treatment, is unknown. Combinations of existing malaria interventions is becoming increasingly important as evidence mounts that progress on reducing malaria incidence is stalling and threatened by resistance. Malaria transmission and intervention dynamics were simulated using OpenMalaria, an in idual-based simulation model of malaria transmission, by considering a seasonal transmission setting and by varying epidemiological and setting parameters such as transmission intensity, case management, intervention types and intervention coverages. Chemopreventive drugs and anti-infective vaccine efficacy profiles were based on previous studies in which model parameters were fitted to clinical trial data. These intervention properties were used to evaluate the potential of seasonal mass applications of preventative anti-infective malaria vaccines, alone or in combination with chemoprevention, to reduce malaria transmission, prevent resurgence, and/or reach transmission interruption. Deploying a vaccine to all ages on its own is a less effective intervention strategy compared to chemoprevention alone. However, vaccines combined with drugs are likely to achieve dramatic prevalence reductions and in few settings, transmission interruption. The combined mass intervention will result in lower prevalence following the intervention compared to chemoprevention alone and will increase chances of interruption of transmission resulting from a synergistic effect between both interventions. The combination of vaccine and drug increases the time before transmission resurges after mass interventions cease compared to mass treatment alone. Deploying vaccines and drugs together requires fewer rounds of mass intervention and fewer years of intervention to achieve the same public health impact as chemoprevention alone. Through simulations we identified a previously unidentified value of deploying vaccines with drugs, namely the greatest benefit will be in preventing and delaying transmission resurgence for longer periods than with other human targeted interventions. This is suggesting a potential role for deploying vaccines alongside drugs in transmission foci as part of surveillance-response strategies.
Publisher: Public Library of Science (PLoS)
Date: 17-01-2012
Publisher: Springer Science and Business Media LLC
Date: 08-06-2009
Abstract: A wide range of possible malaria vaccines is being considered and there is a need to identify which vaccines should be prioritized for clinical development. An important element of the information needed for this prioritization is a prediction of the cost-effectiveness of potential vaccines in the transmission settings in which they are likely to be deployed. This analysis needs to consider a range of delivery modalities to ensure that clinical development plans can be aligned with the most appropriate deployment strategies. The simulations are based on a previously published in idual-based stochastic model for the natural history and epidemiology of Plasmodium falciparum malaria. Three different vaccine types: pre-erythrocytic vaccines (PEV), blood stage vaccines (BSV), mosquito-stage transmission-blocking vaccines (MSTBV), and combinations of these, are considered each delivered via a range of delivery modalities (Expanded Programme of Immunization – EPI-, EPI with booster, and mass vaccination combined with EPI). The cost-effectiveness ratios presented are calculated for four health outcomes, for assumed vaccine prices of US$ 2 or US$ 10 per dose, projected over a 10-year period. The simulations suggest that PEV will be more cost-effective in low transmission settings, while BSV at higher transmission settings. Combinations of BSV and PEV are more efficient than PEV, especially in moderate to high transmission settings, while compared to BSV they are more cost-effective in moderate to low transmission settings. Combinations of MSTBV and PEV or PEV and BSV improve the effectiveness and the cost-effectiveness compared to PEV and BSV alone only when applied with EPI and mass vaccinations. Adding booster doses to the EPI is unlikely to be a cost-effective alternative to delivering vaccines via the EPI for any vaccine, while mass vaccination improves effectiveness, especially in low transmission settings, and is often a more efficient alternative to the EPI. However, the costs of increasing the coverage of mass vaccination over 50% often exceed the benefits. The simulations indicate malaria vaccines might be efficient malaria control interventions, and that both transmission setting and vaccine delivery modality are important to their cost-effectiveness. Alternative vaccine delivery modalities to the EPI may be more efficient than the EPI. Mass vaccination is predicted to provide substantial health benefits at low additional costs, although achieving high coverage rates can lead to substantial incremental costs.
Publisher: Cold Spring Harbor Laboratory
Date: 24-07-2023
DOI: 10.1101/2023.07.23.23293041
Abstract: Seasonal malaria chemoprevention (SMC) with sulfadoxine-pyrimethamine (SP) plus amodiaquine (AQ) prevents millions of clinical malaria cases in children under five in Africa’s Sahel region. However, parasites partially resistant to SP (with “quintuple” mutations) potentially threaten SMC protective effectiveness. We evaluated its spread and clinical consequences. An in idual-based malaria transmission model with explicit parasite dynamics and drug pharmacological models, was used to identify and quantify the influence of factors driving quintuple mutant spread and predict the time needed for the mutant to spread from 1% to 50% of inoculations for several SMC deployment strategies. We estimated the impact of this spread on SMC effectiveness against clinical malaria. Higher transmission intensity, SMC coverage, and expanded age range of chemoprevention promoted mutant spread. SMC implementation in a high transmission setting (40% parasite prevalence in children aged 2-10 years) with four monthly cycles to children aged three months to five years (with 95% initial coverage declining each cycle), the mutant requires 53·1 years (95% CI 50·5–56·0) to spread from 1% to 50% of inoculations. This time increased in lower transmission settings and reduced by half when SMC was extended to children under ten, or reduced by 10-13 years when an additional monthly cycle of SMC was deployed. For the same setting, the effective reduction in clinical cases in children receiving SMC was 79·0% (95% CI 77·8–80·8) and 60·4% (95% CI 58·6–62·3) during the months of SMC implementation when the mutant was absent or fixed in the population, respectively. SMC with SP+AQ leads to a relatively slow spread of SP-resistant quintuple mutants and remains effective at preventing clinical malaria despite the mutant spread. SMC with SP+AQ should be considered in seasonal settings where this mutant is already prevalent. Swiss National Science Foundation and Marie Curie In idual Fellowship.
Publisher: Cold Spring Harbor Laboratory
Date: 27-01-2021
DOI: 10.1101/2021.01.25.427822
Abstract: Antimicrobial resistance is a major health problem with complex dynamics. Resistance may occur in an area because treated infections mutated and developed resistance, and the proportion of infections in a population may then increase. We developed a novel and flexible model that captures several features of resistance dynamics and competition. The model is able to account for many antimicrobials and thus can generally explore competition dynamics and their impact on pathogens and bacteria. Unlike simpler models, our nested model allows the population of resistant pathogen to smoothly increase or decrease. Time dependent dynamics are incorporated into difference equations which examines the effects of 12 parameters. This enables us to explicitly include three key competition dynamics: the transmission cost of resistance that occurs between hosts, the fitness cost of resistance that occurs within untreated hosts, and the release of this competition (from the fitness cost) that occurs once a host is treated. For malaria, our results suggest that without competitive release, drug resistance does not emerge. However, once emerged, competitive release has little effect, and the best way to mitigate the spread is to ensure that treatment is very effective.
Publisher: Cold Spring Harbor Laboratory
Date: 23-06-2022
DOI: 10.1101/2022.06.22.22276760
Abstract: Vaccinations have reduced severe burden of COVID-19 and allowed for lifting of non-pharmaceutical interventions. However, with immunity waning alongside emergence of more transmissible variants of concern, vaccination strategies must be examined. Here we apply a SARS-CoV-2 transmission model to identify preferred frequency, timing, and target groups for vaccine boosters to minimise public health burden and health systems risk. We estimated new infections and hospital admissions averted over two-years through annual or biannual boosting of those eligible (those who received doses one and two) who are 1) most vulnerable (60+ or persons with comorbidities) or 2) those 5+, at universal (98% of eligible) or lower coverage (85% of those 50+ or with comorbidities and 50% of 5−49-year-olds who are eligible) representing moderate vaccine fatigue and/or hesitancy. We simulated three emerging variant scenarios: 1) no new variants 2) 25% more infectious and immune-evading, Omicron-level severity, variants emerge annually and become dominant and 3) emerge biannually. We further explored the impact of varying seasonality, variant severity, timing, immune evasion, and infectivity, and vaccine infection blocking assumptions. To minimise COVID-19-related hospitalisations over the next two years, boosters should be provided for all those eligible annually three-four months ahead of peak winter whether or not new variants of concern emerge. Only boosting those most vulnerable is unlikely to ensure reduced stress on health systems. Moreover, boosting all eligible protects those most vulnerable more than only boosting the vulnerable group. Conversely, more hospitalisations could be averted per booster dose through annual boosting of those most vulnerable versus all eligible, an indication of cost-effectiveness. Whereas increasing to biannual boosting showed diminishing returns. Results were robust when key model parameters were varied. However, we found that the more frequently variants emerge, the less the effect boosters will have, regardless of whether administered annually or biannually. Well-timed and targeted vaccine boosters preferencing vulnerable, and if possible, all those eligible to receive boosters, can minimise infections and hospital admissions. Findings provide model-based evidence for decision-makers to plan for administering COVID-19 boosters ahead of winter 2022−2023 to help mitigate the health burden and health system stress.
Publisher: Springer Science and Business Media LLC
Date: 25-02-2013
Publisher: Elsevier BV
Date: 10-2018
Publisher: Elsevier BV
Date: 09-2022
Publisher: Springer Science and Business Media LLC
Date: 10-03-2020
DOI: 10.1038/S41598-020-61304-8
Abstract: Emerging drug resistance and high-attrition rates in early and late stage drug development necessitate accelerated development of antimalarial compounds. However, systematic and meaningful translation of drug efficacy and host-parasite dynamics between preclinical testing stages is missing. We developed an ensemble of mathematical within-host parasite growth and antimalarial action models, fitted to extensive data from four antimalarials with different modes of action, to assess host-parasite interactions in two preclinical drug testing systems of murine parasite P. berghei in mice, and human parasite P. falciparum in immune-deficient mice. We find properties of the host-parasite system, namely resource availability, parasite maturation and virulence, drive P. berghei dynamics and drug efficacy, whereas experimental constraints primarily influence P. falciparum infection and drug efficacy. Furthermore, uninvestigated parasite behavior such as dormancy influences parasite recrudescence following non-curative treatment and requires further investigation. Taken together, host-parasite interactions should be considered for meaningful translation of pharmacodynamic properties between murine systems and for predicting human efficacious treatment.
Publisher: American Society for Microbiology
Date: 04-2019
DOI: 10.1128/AAC.01391-18
Abstract: Opisthorchiasis, caused by the foodborne trematode Opisthorchis viverrini , affects more than 8 million people in Southeast Asia. In the framework of a phase 2b clinical trial conducted in Lao People’s Democratic Republic, pharmacokinetic s les were obtained from 125 adult and adolescent O. viverrini -infected patients treated with 400 mg tribendimidine following the design of a sparse s ling scheme at 20 min and 2, 7.75, 8, and 30 h after treatment using dried blood spot s ling.
Publisher: Cold Spring Harbor Laboratory
Date: 14-12-2021
DOI: 10.1101/2021.12.12.21267673
Abstract: SARS-CoV-2 variant Omicron (B.1.1.529) was classified as a variant of concern (VOC) on November 26, 2021. (1, 2) The infectivity, severity, and immune evasion properties of Omicron relative to the Delta variant would determine 1) the probability of dominant future transmission, and 2) the impact on disease burden. (3, 4) Here we apply in idual-based transmission model OpenCOVID to identify thresholds for Omicron’s or any VOC’s potential future dominance, impact on health, and risk to health systems and identify for which combinations of viral properties, current interventions would be sufficient to control transmission. We show that, with first-generation SARS-CoV-2 vaccines (5) and limited physical distancing in place, the threshold for Omicron’s future dominance was primarily be driven by its degree of infectivity. However, we identified that a VOC’s potential dominance will not necessarily lead to increased public health burden. Expanded vaccination, that includes a third-dose for adults and child vaccination strategies, was projected to have the biggest public health benefit for a highly infective, highly severe VOC with low immune evasion capacity. However, a highly immune evading variant that becomes dominant would likely require alternative measures for control, such as strengthened physical distancing measures, novel treatments, and second-generation vaccines. These findings provide quantitative guidance to decision-makers at a critical time while Omicron’s properties are being assessed and preparedness for new VOC’s is eminent. (6) We emphasize the importance of both genomic and population epidemiological surveillance.
Publisher: Cambridge University Press (CUP)
Date: 11-08-2008
DOI: 10.1017/S0031182008000371
Abstract: Planning of the control of Plasmodium falciparum malaria leads to a need for models of malaria epidemiology that provide realistic quantitative prediction of likely epidemiological outcomes of a wide range of control strategies. Predictions of the effects of control often ignore medium- and long-term dynamics. The complexities of the Plasmodium life-cycle, and of within-host dynamics, limit the applicability of conventional deterministic malaria models. We use in idual-based stochastic simulations of malaria epidemiology to predict the impacts of interventions on infection, morbidity, mortality, health services use and costs. In idual infections are simulated by stochastic series of parasite densities, and naturally acquired immunity acts by reducing densities. Morbidity and mortality risks, and infectiousness to vectors, depend on parasite densities. The simulated infections are nested within simulations of in iduals in human populations, and linked to models of interventions and health systems. We use numerous field datasets to optimise parameter estimates. By using a volunteer computing system we obtain the enormous computational power required for model fitting, sensitivity analysis, and exploration of many different intervention strategies. The project thus provides a general platform for comparing, fitting, and evaluating different model structures, and for quantitative prediction of effects of different interventions and integrated control programmes.
Publisher: Cold Spring Harbor Laboratory
Date: 07-02-2022
DOI: 10.1101/2022.02.05.22270500
Abstract: The effectiveness of artemisinin-based combination therapies (ACTs) to treat Plasmodium falciparum malaria is threatened by resistance. The complex interplay between sources of selective pressure – treatment properties, biological factors, transmission intensity, and access to treatment – obscures understanding how, when, and why resistance establishes and spreads across different locations. We developed a disease modelling approach with emulator-based global sensitivity analysis to systematically quantify which of these factors drive establishment and spread of drug resistance. Drug resistance was more likely to evolve in low transmission settings due to the lower levels of (i) immunity and (ii) within-host competition between genotypes. Spread of parasites resistant to artemisinin partner drugs depended on the period of low drug concentration (known as the selection window). Spread of partial artemisinin resistance was slowed with prolonged parasite exposure to artemisinin derivatives and accelerated when the parasite was also resistant to the partner drug. Thus, to slow the spread of partial artemisinin resistance, molecular surveillance should be supported to detect resistance to partner drugs and to change ACTs accordingly. Furthermore, implementing more sustainable artemisinin-based therapies will require extending parasite exposure to artemisinin derivatives, and mitigating the selection windows of partner drugs, which could be achieved by including an additional long-acting drug. Detailed models of malaria and treatment dynamics were combined with emulator-based global sensitivity analysis to elucidate how the interplay of drug properties, infection biology, and epidemiological dynamics drives evolution of resistance to artemisinin-based combination therapies. The results identify mitigation strategies.
Start Date: 2020
End Date: 2023
Funder: Swiss National Science Foundation
View Funded ActivityStart Date: 2021
End Date: 2023
Funder: Swiss National Science Foundation
View Funded ActivityStart Date: 2017
End Date: 2021
Funder: Swiss National Science Foundation
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