School of Mathematics and Statistics - Research Publications
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ItemNo Preview AvailableA model for malaria treatment evaluation in the presence of multiple species(ELSEVIER, 2023-09)Plasmodium falciparum and P. vivax are the two most common causes of malaria. While the majority of deaths and severe morbidity are due to P. falciparum, P. vivax poses a greater challenge to eliminating malaria outside of Africa due to its ability to form latent liver stage parasites (hypnozoites), which can cause relapsing episodes within an individual patient. In areas where P. falciparum and P. vivax are co-endemic, individuals can carry parasites of both species simultaneously. These mixed infections complicate dynamics in several ways: treatment of mixed infections will simultaneously affect both species, P. falciparum can mask the detection of P. vivax, and it has been hypothesised that clearing P. falciparum may trigger a relapse of dormant P. vivax. When mixed infections are treated for only blood-stage parasites, patients are at risk of relapse infections due to P. vivax hypnozoites. We present a stochastic mathematical model that captures interactions between P. falciparum and P. vivax, and incorporates both standard schizonticidal treatment (which targets blood-stage parasites) and radical cure treatment (which additionally targets liver-stage parasites). We apply this model via a hypothetical simulation study to assess the implications of different treatment coverages of radical cure for mixed and P. vivax infections and a "unified radical cure" treatment strategy where P. falciparum, P. vivax, and mixed infections all receive radical cure after screening glucose-6-phosphate dehydrogenase (G6PD) normal. In addition, we investigated the impact of mass drug administration (MDA) of blood-stage treatment. We find that a unified radical cure strategy leads to a substantially lower incidence of malaria cases and deaths overall. MDA with schizonticidal treatment was found to decrease P. falciparum with little effect on P. vivax. We perform a univariate sensitivity analysis to highlight important model parameters.
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ItemNo Preview AvailableDevelopment and Validation of an In Silico Decision Tool To Guide Optimization of Intravenous Artesunate Dosing Regimens for Severe Falciparum Malaria Patients(AMER SOC MICROBIOLOGY, 2021-06)Most deaths from severe falciparum malaria occur within 24 h of presentation to a hospital. Intravenous (i.v.) artesunate is the first-line treatment for severe falciparum malaria, but its efficacy may be compromised by delayed parasitological responses. In patients with severe malaria, the life-saving benefit of the artemisinin derivatives is their ability to clear circulating parasites rapidly, before they can sequester and obstruct the microcirculation. To evaluate the dosing of i.v. artesunate for the treatment of artemisinin-sensitive and reduced ring stage sensitivity to artemisinin severe falciparum malaria infections, Bayesian pharmacokinetic-pharmacodynamic modeling of data from 94 patients with severe malaria (80 children from Africa and 14 adults from Southeast Asia) was performed. Assuming that delayed parasite clearance reflects a loss of ring stage sensitivity to artemisinin derivatives, the median (95% credible interval) percentage of patients clearing ≥99% of parasites within 24 h (PC24≥99%) for standard (2.4 mg/kg body weight i.v. artesunate at 0 and 12 h) and simplified (4 mg/kg i.v. artesunate at 0 h) regimens was 65% (52.5% to 74.5%) versus 44% (25% to 61.5%) for adults, 62% (51.5% to 74.5%) versus 39% (20.5% to 58.5%) for larger children (≥20 kg), and 60% (48.5% to 70%) versus 36% (20% to 53.5%) for smaller children (<20 kg). The upper limit of the credible intervals for all regimens was below a PC24≥99% of 80%, a threshold achieved on average in clinical studies of severe falciparum malaria infections. In severe falciparum malaria caused by parasites with reduced ring stage susceptibility to artemisinin, parasite clearance is predicted to be slower with both the currently recommended and proposed simplified i.v. artesunate dosing regimens.
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ItemWithin-host modeling of blood-stage malaria(WILEY, 2018-09)Malaria infection continues to be a major health problem worldwide and drug resistance in the major human parasite species, Plasmodium falciparum, is increasing in South East Asia. Control measures including novel drugs and vaccines are in development, and contributions to the rational design and optimal usage of these interventions are urgently needed. Infection involves the complex interaction of parasite dynamics, host immunity, and drug effects. The long life cycle (48 hours in the common human species) and synchronized replication cycle of the parasite population present significant challenges to modeling the dynamics of Plasmodium infection. Coupled with these, variation in immune recognition and drug action at different life cycle stages leads to further complexity. We review the development and progress of "within-host" models of Plasmodium infection, and how these have been applied to understanding and interpreting human infection and animal models of infection.
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ItemAssessing the utility of an anti-malarial pharmacokinetic-pharmacodynamic model for aiding drug clinical development(BIOMED CENTRAL LTD, 2012-08-30)BACKGROUND: Mechanistic within-host models relating blood anti-malarial drug concentrations with the parasite-time profile help in assessing dosing schedules and partner drugs for new anti-malarial treatments. A comprehensive simulation study to assess the utility of a stage-specific pharmacokinetic-pharmacodynamic (PK-PD) model for predicting within-host parasite response was performed. METHODS: Three anti-malarial combination therapies were selected: artesunate-mefloquine, dihydroartemisinin-piperaquine, and artemether-lumefantrine. The PK-PD model included parameters to represent the concentration-time profiles of both drugs, the initial parasite burden and distribution across the parasite life cycle, and the parasite multiplication factor due to asexual reproduction. The model also included the maximal killing rate of each drug, and the blood drug concentration associated with half of that killing effect (in vivo EC50), derived from the in vitro IC50, the extent of binding to 0.5% Albumax present in the in vitro testing media, and the drugs plasma protein binding and whole blood to plasma partitioning ratio. All stochastic simulations were performed using a Latin-Hypercube-Sampling approach. RESULTS: The simulations demonstrated that the proportion of patients cured was highly sensitive to the in vivo EC50 and the maximal killing rate of the partner drug co-administered with the artemisinin derivative. The in vivo EC50 values that corresponded to on average 95% of patients cured were much higher than the adjusted values derived from the in vitro IC50. The proportion clinically cured was not strongly influenced by changes in the parameters defining the age distribution of the initial parasite burden (mean age of 4 to 16 hours) and the parasite multiplication factor every life cycle (ranging from 8 to 12 fold/cycle). The median parasite clearance times, however, lengthened as the standard deviation of the initial parasite burden increased (i.e. the infection became more asynchronous). CONCLUSIONS: This simulation study demonstrates that the PD effect predicted from in vitro growth inhibition assays does not accord well with the PD effect of the anti-malarials observed within the patient. This simulation-based PK-PD modelling approach should not be considered as a replacement to conducting clinical trials but instead as a decision tool to improve the design of a clinical trial during drug development.
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ItemSequential infection experiments for quantifying innate and adaptive immunity during influenza infection(PUBLIC LIBRARY SCIENCE, 2019-01)Laboratory models are often used to understand the interaction of related pathogens via host immunity. For example, recent experiments where ferrets were exposed to two influenza strains within a short period of time have shown how the effects of cross-immunity vary with the time between exposures and the specific strains used. On the other hand, studies of the workings of different arms of the immune response, and their relative importance, typically use experiments involving a single infection. However, inferring the relative importance of different immune components from this type of data is challenging. Using simulations and mathematical modelling, here we investigate whether the sequential infection experiment design can be used not only to determine immune components contributing to cross-protection, but also to gain insight into the immune response during a single infection. We show that virological data from sequential infection experiments can be used to accurately extract the timing and extent of cross-protection. Moreover, the broad immune components responsible for such cross-protection can be determined. Such data can also be used to infer the timing and strength of some immune components in controlling a primary infection, even in the absence of serological data. By contrast, single infection data cannot be used to reliably recover this information. Hence, sequential infection data enhances our understanding of the mechanisms underlying the control and resolution of infection, and generates new insight into how previous exposure influences the time course of a subsequent infection.
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ItemInvestigating the Efficacy of Triple Artemisinin-Based Combination Therapies for Treating Plasmodium falciparum Malaria Patients Using Mathematical Modeling(AMER SOC MICROBIOLOGY, 2018-11)The first line treatment for uncomplicated falciparum malaria is artemisinin-based combination therapy (ACT), which consists of an artemisinin derivative coadministered with a longer-acting partner drug. However, the spread of Plasmodium falciparum resistant to both artemisinin and its partner drugs poses a major global threat to malaria control activities. Novel strategies are needed to retard and reverse the spread of these resistant parasites. One such strategy is triple artemisinin-based combination therapy (TACT). We developed a mechanistic within-host mathematical model to investigate the efficacy of a TACT (dihydroartemisinin-piperaquine-mefloquine [DHA-PPQ-MQ]) for use in South-East Asia, where DHA and PPQ resistance are now increasingly prevalent. Comprehensive model simulations were used to explore the degree to which the underlying resistance influences the parasitological outcomes. The effect of MQ dosing on the efficacy of TACT was quantified at various degrees of DHA and PPQ resistance. To incorporate interactions between drugs, a novel model is presented for the combined effect of DHA-PPQ-MQ, which illustrates how the interactions can influence treatment efficacy. When combined with a standard regimen of DHA and PPQ, the administration of three 6.7-mg/kg doses of MQ was sufficient to achieve parasitological efficacy greater than that currently recommended by World Health Organization (WHO) guidelines. As a result, three 8.3-mg/kg doses of MQ, the current WHO-recommended dosing regimen for MQ, combined with DHA-PPQ, has the potential to produce high cure rates in regions where resistance to DHA-PPQ has emerged.
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ItemIdentifying and combating the impacts of COVID-19 on malaria(BMC, 2020-07-30)BACKGROUND: The COVID-19 pandemic has resulted in millions of infections, hundreds of thousands of deaths and major societal disruption due to lockdowns and other restrictions introduced to limit disease spread. Relatively little attention has been paid to understanding how the pandemic has affected treatment, prevention and control of malaria, which is a major cause of death and disease and predominantly affects people in less well-resourced settings. MAIN BODY: Recent successes in malaria control and elimination have reduced the global malaria burden, but these gains are fragile and progress has stalled in the past 5 years. Withdrawing successful interventions often results in rapid malaria resurgence, primarily threatening vulnerable young children and pregnant women. Malaria programmes are being affected in many ways by COVID-19. For prevention of malaria, insecticide-treated nets need regular renewal, but distribution campaigns have been delayed or cancelled. For detection and treatment of malaria, individuals may stop attending health facilities, out of fear of exposure to COVID-19, or because they cannot afford transport, and health care workers require additional resources to protect themselves from COVID-19. Supplies of diagnostics and drugs are being interrupted, which is compounded by production of substandard and falsified medicines and diagnostics. These disruptions are predicted to double the number of young African children dying of malaria in the coming year and may impact efforts to control the spread of drug resistance. Using examples from successful malaria control and elimination campaigns, we propose strategies to re-establish malaria control activities and maintain elimination efforts in the context of the COVID-19 pandemic, which is likely to be a long-term challenge. All sectors of society, including governments, donors, private sector and civil society organisations, have crucial roles to play to prevent malaria resurgence. Sparse resources must be allocated efficiently to ensure integrated health care systems that can sustain control activities against COVID-19 as well as malaria and other priority infectious diseases. CONCLUSION: As we deal with the COVID-19 pandemic, it is crucial that other major killers such as malaria are not ignored. History tells us that if we do, the consequences will be dire, particularly in vulnerable populations.
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ItemModeling the dynamics of Plasmodium falciparum gametocytes in humans during malaria infection(eLIFE SCIENCES PUBL LTD, 2019-10-29)Renewed efforts to eliminate malaria have highlighted the potential to interrupt human-to-mosquito transmission - a process mediated by gametocyte kinetics in human hosts. Here we study the in vivo dynamics of Plasmodium falciparum gametocytes by establishing a framework which incorporates improved measurements of parasitemia, a novel gametocyte dynamics model and model fitting using Bayesian hierarchical inference. We found that the model provides an excellent fit to the clinical data from 17 volunteers infected with P. falciparum (3D7 strain) and reliably predicts observed gametocytemia. We estimated the sexual commitment rate and gametocyte sequestration time to be 0.54% (95% credible interval: 0.30-1.00%) per asexual replication cycle and 8.39 (6.54-10.59) days respectively. We used the data-calibrated model to investigate human-to-mosquito transmissibility, providing a method to link within-human host infection kinetics to epidemiological-scale infection and transmission patterns.
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ItemIdentifying and combating the impacts of COVID-19 on malaria(BMC, 2020-07-30)BACKGROUND: The COVID-19 pandemic has resulted in millions of infections, hundreds of thousands of deaths and major societal disruption due to lockdowns and other restrictions introduced to limit disease spread. Relatively little attention has been paid to understanding how the pandemic has affected treatment, prevention and control of malaria, which is a major cause of death and disease and predominantly affects people in less well-resourced settings. MAIN BODY: Recent successes in malaria control and elimination have reduced the global malaria burden, but these gains are fragile and progress has stalled in the past 5 years. Withdrawing successful interventions often results in rapid malaria resurgence, primarily threatening vulnerable young children and pregnant women. Malaria programmes are being affected in many ways by COVID-19. For prevention of malaria, insecticide-treated nets need regular renewal, but distribution campaigns have been delayed or cancelled. For detection and treatment of malaria, individuals may stop attending health facilities, out of fear of exposure to COVID-19, or because they cannot afford transport, and health care workers require additional resources to protect themselves from COVID-19. Supplies of diagnostics and drugs are being interrupted, which is compounded by production of substandard and falsified medicines and diagnostics. These disruptions are predicted to double the number of young African children dying of malaria in the coming year and may impact efforts to control the spread of drug resistance. Using examples from successful malaria control and elimination campaigns, we propose strategies to re-establish malaria control activities and maintain elimination efforts in the context of the COVID-19 pandemic, which is likely to be a long-term challenge. All sectors of society, including governments, donors, private sector and civil society organisations, have crucial roles to play to prevent malaria resurgence. Sparse resources must be allocated efficiently to ensure integrated health care systems that can sustain control activities against COVID-19 as well as malaria and other priority infectious diseases. CONCLUSION: As we deal with the COVID-19 pandemic, it is crucial that other major killers such as malaria are not ignored. History tells us that if we do, the consequences will be dire, particularly in vulnerable populations.
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ItemMaking the Most of Clinical Data: Reviewing the Role of Pharmacokinetic-Pharmacodynamic Models of Anti-malarial Drugs(SPRINGER, 2014-09)Mechanistic within-host models integrating blood anti-malarial drug concentrations with the parasite-time profile provide a valuable decision tool for determining dosing regimens for anti-malarial treatments, as well as a formative component of population-level drug resistance models. We reviewed published anti-malarial pharmacokinetic-pharmacodynamic models to identify the challenges for these complex models where parameter estimation from clinical field data is limited. The inclusion of key pharmacodynamic processes in the mechanistic structure adopted varies considerably. These include the life cycle of the parasite within the red blood cell, the action of the anti-malarial on a specific stage of the life cycle, and the reduction in parasite growth associated with immunity. With regard to estimation of the pharmacodynamic parameters, the majority of studies simply compared descriptive summaries of the simulated outputs to published observations of host and parasite responses from clinical studies. Few studies formally estimated the pharmacodynamic parameters within a rigorous statistical framework using observed individual patient data. We recommend three steps in the development and evaluation of these models. Firstly, exploration through simulation to assess how the different parameters influence the parasite dynamics. Secondly, application of a simulation-estimation approach to determine whether the model parameters can be estimated with reasonable precision based on sampling designs that mimic clinical efficacy studies. Thirdly, fitting the mechanistic model to the clinical data within a Bayesian framework. We propose that authors present the model both schematically and in equation form and give a detailed description of each parameter, including a biological interpretation of the parameter estimates.