The spread of antimalarial drug resistance: A mathematical model with practical implications for ACT drug policies

Most malaria-endemic countries are implementing a change in antimalarial drug policy to artemisinin combination therapy (ACT). The impact of different drug choices and implementation strategies is uncertain. A comprehensive model was constructed incorporating important epidemiological and biological factors and used to illustrate the spread of resistance in low and high transmission settings. The model predicts robustly that in low transmission settings drug resistance spreads faster than in high transmission settings, and that in low transmission areas ACTs slows the spread of drug resistance to a partner drug, especially at high coverage rates. This effect decreases exponentially with increasing delay in deploying the ACT and decreasing rates of coverage. A major obstacle to achieving the benefits of high coverage is the current cost of the drugs. This argues strongly for a global subsidy to make ACTs generally available and affordable in endemic areas

Spread of anti-malarial drug resistance: Mathematical model with implications for ACT drug policies

BACKGROUND: Most malaria-endemic countries are implementing a change in anti-malarial drug policy to artemisinin-based combination therapy (ACT). The impact of different drug choices and implementation strategies is uncertain. Data from many epidemiological studies in different levels of malaria endemicity and in areas with the highest prevalence of drug resistance like borders of Thailand are certainly valuable. Formulating an appropriate dynamic data-driven model is a powerful predictive tool for exploring the impact of these strategies quantitatively. METHODS: A comprehensive model was constructed incorporating important epidemiological and biological factors of human, mosquito, parasite and treatment. The iterative process of developing the model, identifying data needed, and parameterization has been taken to strongly link the model to the empirical evidence. The model provides quantitative measures of outcomes, such as malaria prevalence/incidence and treatment failure, and illustrates the spread of resistance in low and high transmission settings. The model was used to evaluate different anti-malarial policy options focusing on ACT deployment. RESULTS: The model predicts robustly that in low transmission settings drug resistance spreads faster than in high transmission settings, and treatment failure is the main force driving the spread of drug resistance. In low transmission settings, ACT slows the spread of drug resistance to a partner drug, especially at high coverage rates. This effect decreases exponentially with increasing delay in deploying the ACT and decreasing rates of coverage. In the high transmission settings, however, drug resistance is driven by the proportion of the human population with a residual drug level, which gives resistant parasites some survival advantage. The spread of drug resistance could be slowed down by controlling presumptive drug use and avoiding the use of combination therapies containing drugs with mismatched half-lives, together with reducing malaria transmission through vector control measures. CONCLUSION: This paper has demonstrated the use of a comprehensive mathematical model to describe malaria transmission and the spread of drug resistance. The model is strongly linked to the empirical evidence obtained from extensive data available from various sources. This model can be a useful tool to inform the design of treatment policies, particularly at a time when ACT has been endorsed by WHO as first-line treatment for falciparum malaria worldwide

Estimation of the Total Parasite Biomass in Acute Falciparum Malaria from Plasma PfHRP2

BACKGROUND: In falciparum malaria sequestration of erythrocytes containing mature forms of Plasmodium falciparum in the microvasculature of vital organs is central to pathology, but quantitation of this hidden sequestered parasite load in vivo has not previously been possible. The peripheral blood parasite count measures only the circulating, relatively non-pathogenic parasite numbers. P. falciparum releases a specific histidine-rich protein (PfHRP2) into plasma. Quantitative measurement of plasma PfHRP2 concentrations may reflect the total parasite biomass in falciparum malaria. METHODS AND FINDINGS: We measured plasma concentrations of PfHRP2, using a quantitative antigen-capture enzyme-linked immunosorbent assay, in 337 adult patients with falciparum malaria of varying severity hospitalised on the Thai–Burmese border. Based on in vitro production rates, we constructed a model to link this measure to the total parasite burden in the patient. The estimated geometric mean parasite burden was 7 × 10(11) (95% confidence interval [CI] 5.8 × 10(11) to 8.5 × 10(11)) parasites per body, and was over six times higher in severe malaria (geometric mean 1.7 × 10(12), 95% CI 1.3 × 10(12) to 2.3 × 10(12)) than in patients hospitalised without signs of severity (geometric mean 2.8 × 10(11), 95% CI 2.3 × 10(11) to 3.5 × 10(11); p < 0.001). Parasite burden was highest in patients who died (geometric mean 3.4 × 10(12), 95% CI 1.9 × 10(12) to 6.3 × 10(12); p = 0.03). The calculated number of sequestered parasites increased with disease severity and was higher in patients with late developmental stages of P. falciparum present on peripheral blood smears. Comparing model and laboratory estimates of the time of sequestration suggested that admission to hospital with uncomplicated malaria often follows schizogony—but in severe malaria is unrelated to stage of parasite development. CONCLUSION: Plasma PfHRP2 concentrations may be used to estimate the total body parasite biomass in acute falciparum malaria. Severe malaria results from extensive sequestration of parasitised erythrocytes

Hyperparasitaemia and low dosing are an important source of anti-malarial drug resistance

BACKGROUND: Preventing the emergence of anti-malarial drug resistance is critical for the success of current malaria elimination efforts. Prevention strategies have focused predominantly on qualitative factors, such as choice of drugs, use of combinations and deployment of multiple first-line treatments. The importance of anti-malarial treatment dosing has been underappreciated. Treatment recommendations are often for the lowest doses that produce "satisfactory" results. METHODS: The probability of de-novo resistant malaria parasites surviving and transmitting depends on the relationship between their degree of resistance and the blood concentration profiles of the anti-malarial drug to which they are exposed. The conditions required for the in-vivo selection of de-novo emergent resistant malaria parasites were examined and relative probabilities assessed. RESULTS: Recrudescence is essential for the transmission of de-novo resistance. For rapidly eliminated anti-malarials high-grade resistance can arise from a single drug exposure, but low-grade resistance can arise only from repeated inadequate treatments. Resistance to artemisinins is, therefore, unlikely to emerge with single drug exposures. Hyperparasitaemic patients are an important source of de-novo anti-malarial drug resistance. Their parasite populations are larger, their control of the infection insufficient, and their rates of recrudescence following anti-malarial treatment are high. As use of substandard drugs, poor adherence, unusual pharmacokinetics, and inadequate immune responses are host characteristics, likely to pertain to each recurrence of infection, a small subgroup of patients provides the particular circumstances conducive to de-novo resistance selection and transmission. CONCLUSION: Current dosing recommendations provide a resistance selection opportunity in those patients with low drug levels and high parasite burdens (often children or pregnant women). Patients with hyperparasitaemia who receive outpatient treatments provide the greatest risk of selecting de-novo resistant parasites. This emphasizes the importance of ensuring that only quality-assured anti-malarial combinations are used, that treatment doses are optimized on the basis of pharmacodynamic and pharmacokinetic assessments in the target populations, and that patients with heavy parasite burdens are identified and receive sufficient treatment to prevent recrudescence

Strategies for Diagnosis and Treatment of Suspected Leptospirosis: A Cost-Benefit Analysis

Symptoms and signs of leptospirosis are non-specific. A number of diagnostic tests for leptospirosis are available. We compared the cost-benefit of 5 management strategies: 1) no patients tested or given antibiotic treatment; 2) all patients given empirical doxycycline treatment; patients given doxycycline when a patient is tested positive for leptospirosis using: 3) lateral flow; 4) MCAT; 5) latex test. Outcomes were measured in duration of fever which is then converted to productivity losses to capture the full economic costs. Empirical doxycycline treatment was found to be the most efficient strategy, being both the least costly alternative and the one that resulted in the lowest average duration of fever. The significantly higher relative cost of using a diagnostic test as compared with presumptive treatment, and the limited sensitivity of all the diagnostic tests implied that only the latex test could be considered cost-effective when compared with the no-antibiotic-treatment option, and that all three tests were still inferior to empirical treatment

Mathematical modelling of antimalarial drug resistance

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Antimalarial drug resistance, artemisinin-based combination therapy, and the contribution of modeling to elucidating policy choices.

Increasing resistance of Plasmodium falciparum malaria to antimalarial drugs is posing a major threat to the global effort to "Roll Back Malaria". Chloroquine and sulfadoxine-pyrimethamine (SP) are being rendered increasingly ineffective, resulting in increasing morbidity, mortality, and economic and social costs. One strategy advocated for delaying the development of resistance to the remaining armory of effective drugs is the wide-scale deployment of artemisinin-based combination therapy. However, the cost of these combinations are higher than most of the currently used monotherapies and alternative non-artemisinin-based combinations. In addition, uncertainty about the actual impact in real-life settings has made them a controversial choice for first-line treatment. The difficulties in measuring the burden of drug resistance and predicting the impact of strategies aimed at its reduction are outlined, and a mathematical model is introduced that is being designed to address these issues and to clarify policy options