| Literature DB >> 19228438 |
Richard J Maude1, Wirichada Pontavornpinyo, Sompob Saralamba, Ricardo Aguas, Shunmay Yeung, Arjen M Dondorp, Nicholas P J Day, Nicholas J White, Lisa J White.
Abstract
BACKGROUND: Artemisinin combination therapy (ACT) is now the recommended first-line treatment for falciparum malaria throughout the world. Initiatives to eliminate malaria are critically dependent on its efficacy. There is recent worrying evidence that artemisinin resistance has arisen on the Thai-Cambodian border. Urgent containment interventions are planned and about to be executed. Mathematical modeling approaches to intervention design are now integrated into the field of malaria epidemiology and control. The use of such an approach to investigate the likely effectiveness of different containment measures with the ultimate aim of eliminating artemisinin-resistant malaria is described.Entities:
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Year: 2009 PMID: 19228438 PMCID: PMC2660356 DOI: 10.1186/1475-2875-8-31
Source DB: PubMed Journal: Malar J ISSN: 1475-2875 Impact factor: 2.979
Figure 1Schematic diagram of the structure of the mathematical modeling framework. The structure of the model is built up as follows: natural history and pharmacodynamics incorporated as a repeating unit (A) with four compartments – susceptible people, people with liver stage infection, people with noninfectious blood stage infection and people with infectious (blood) stage infection, rates of flow between these compartments (βI/N, δ, γ and σ) and rates of recovery due to each of artesunate and piperaquine treatment (c, c, cand c) (Additional file 1- Table S2) is shown. The times to recovery (1/rate) following treatment are then adjusted by a multiplying factor (erada or erbdb) (0 ≤ e ≤ 1) depending on the degree of resistance to each drug, giving three possible linked variants of unit A (resistant to no drug, artesunate only and piperaquine only) making up a repeating pattern (B). Finally the population dynamics of transmission is shown in (C). This consists of multiple repetitions of (B) with different rates of flow between them at different time points depending on which treatments and interventions are used. For example, for individuals with blood stage infections to begin treatment with ACT, they will move from the 'No drugs' box (1) to the equivalent parts of an 'ACT' box (2) at a rate determined by the time to begin treatment. The dynamics in the 'ACT' box are different from the 'No drugs' box as these individuals will be subjected to faster rates of recovery due to the ACT. Each box is also subject to pharmacokinetic dynamics independent of infection dynamics. This is in the form of waning pharmacodynamic drug effect over time ('loss of...') with sequential loss of DHA and then piperaquine. This results in a percentage of the entire unit moving to a new box 'Piperaquine' (3) which again has different dynamics representing the effect of piperaquine on recovery rates. Interventions shown here are elimation of artemisinin monotherapy and replacement with ACT ('Switch to ACT') and MSAT and MDA with ACT. Each circle represents a population exposed to a particular drug or combination. Key: ACT = dihydroartemisinin/piperaquine combination therapy, Rx = treatment, DHA = dihydroartemisinin. (For more details, please see the Full Model Code in Additional File 2.)
Figure 2Effect of continuing availability and use of artemisinin monotherapy on the total number of malaria infections (black line), the number of artemisinin-resistant infections (red line) and percentage of infections resistant to artemisinin (red dotted line) over time. Artesunate monotherapy is introduced as treatment in 1975 and a single artemisinin-resistant infection in 1980.
Figure 3Effect of eliminating artesunate monotherapy and replacement with ACT in 2009 for treatment of symptomatic cases on the total number of malaria infections (black line), the number of artemisinin-resistant infections (red line) and the percentage of infections resistant to artesunate (dotted lines, pink = artesunate red = ACT) (mean-field approximation).
Figure 4Example of a single stochastic output illustrating the effect of a switch of treatment to ACT in 2009.