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The impact of IPTi and IPTc interventions on malaria clinical burden - in silico perspectives.

Aguas R, Lourenço JM, Gomes MG, White LJ - PLoS ONE (2009)

Bottom Line: Here, we simulate several schemes of intervention under different transmission settings, while varying immunity build up assumptions.However, even when significant rebound effects are predicted to occur, the overall intervention impact is positive.On the contrary, IPTc has a significant potential to reduce transmission, specifically in areas where it is already low to moderate.

View Article: PubMed Central - PubMed

Affiliation: Instituto Gulbenkian de Ciência, Oeiras, Portugal. ricaguas@igc.gulbenkian.pt

ABSTRACT

Background: Clinical management of malaria is a major health issue in sub-Saharan Africa. New strategies based on intermittent preventive treatment (IPT) can tackle disease burden by simultaneously reducing frequency of infections and life-threatening illness in infants (IPTi) and children (IPTc), while allowing for immunity to build up. However, concerns as to whether immunity develops efficiently in treated individuals, and whether there is a rebound effect after treatment is halted, have made it imperative to define the effects that IPTi and IPTc exert on the clinical malaria scenario.

Methods and findings: Here, we simulate several schemes of intervention under different transmission settings, while varying immunity build up assumptions. Our model predicts that infection risk and effectiveness of acquisition of clinical immunity under prophylactic effect are associated to intervention impact during treatment and follow-up periods. These effects vary across regions of different endemicity and are highly correlated with the interplay between the timing of interventions in age and the age dependent risk of acquiring an infection. However, even when significant rebound effects are predicted to occur, the overall intervention impact is positive.

Conclusions: IPTi is predicted to have minimal impact on the acquisition of clinical immunity, since it does not interfere with the occurrence of mild infections, thus failing to reduce the underlying force of infection. On the contrary, IPTc has a significant potential to reduce transmission, specifically in areas where it is already low to moderate.

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IPTi impact on clinical malaria age profiles.Analysis of the outcome of applying prophylactics at 2, 3 and 9 months of age, for 10 years, in terms of age profile of clinical disease prevalence and intervention efficacy. Age profiles of populations under IPTi are compared with populations without intervention, in equilibrium conditions (black line). (A) Simulations assuming different combinations of values for c and σ, under intense malaria transmission. The values for these 2 parameters are equal for each curve, ranging from  (green line) to  (red line). The blue line represents the intermediate combination, . (B) The dashed line represents the age instantaneous intervention efficacy for the blue curve scenario in (A). The grey bars illustrate efficacy over a 3 months range. (C) Represents the same as in (A), but for a intermediate transmission setting. (D) The dashed line represents the age instantaneous intervention efficacy for the blue curve scenario in (C). The grey bars illustrate efficacy over a 3 months period.
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pone-0006627-g002: IPTi impact on clinical malaria age profiles.Analysis of the outcome of applying prophylactics at 2, 3 and 9 months of age, for 10 years, in terms of age profile of clinical disease prevalence and intervention efficacy. Age profiles of populations under IPTi are compared with populations without intervention, in equilibrium conditions (black line). (A) Simulations assuming different combinations of values for c and σ, under intense malaria transmission. The values for these 2 parameters are equal for each curve, ranging from (green line) to (red line). The blue line represents the intermediate combination, . (B) The dashed line represents the age instantaneous intervention efficacy for the blue curve scenario in (A). The grey bars illustrate efficacy over a 3 months range. (C) Represents the same as in (A), but for a intermediate transmission setting. (D) The dashed line represents the age instantaneous intervention efficacy for the blue curve scenario in (C). The grey bars illustrate efficacy over a 3 months period.

Mentions: Figures 2A and 2C investigate how the probability of acquiring clinical immunity when infected while in the ST class, c, and the reduced risk of acquiring an infection while treated, σ, modulate the age profiles of clinical malaria. We show the age profiles for the parameter combinations that result in the best (green line) and worst (red line) intervention impacts, as well as a parameter combination assuming an empirical estimate for σ [35]–[37] and a conservative guess for c (blue line). In Figure 2A, we use a value for the force of infection corresponding to a high transmission setting (in this case parasite prevalence if around 90%). We observe that, if immunity is efficiently acquired upon clinical infection,c = 1, and the drug does not reduce the risk of having a malaria infection, (green line), the predicted rebound effect is minimised. For intermediate levels, , of these parameters (blue line), the model suggests that rebound becomes significant after the first year of life. This effect is exacerbated when treatment prevents infection from occurring and clinical immunity is not built up due to prophylaxis, (red line). From the green, , to the red line, , the proportion of cases predicted to be prevented up to age 10 decreases from 12.8% to 0.9%, being 5.6% for the blue line, (Table 2). Generally, these results suggest that there is an evident beneficial effect at the ages targeted by treatment, regardless of parameter values. More importantly, there is a noticeable rebound effect, meaning that the treated group is at increased risk of having a clinical malaria episode, after the last dose of treatment.


The impact of IPTi and IPTc interventions on malaria clinical burden - in silico perspectives.

Aguas R, Lourenço JM, Gomes MG, White LJ - PLoS ONE (2009)

IPTi impact on clinical malaria age profiles.Analysis of the outcome of applying prophylactics at 2, 3 and 9 months of age, for 10 years, in terms of age profile of clinical disease prevalence and intervention efficacy. Age profiles of populations under IPTi are compared with populations without intervention, in equilibrium conditions (black line). (A) Simulations assuming different combinations of values for c and σ, under intense malaria transmission. The values for these 2 parameters are equal for each curve, ranging from  (green line) to  (red line). The blue line represents the intermediate combination, . (B) The dashed line represents the age instantaneous intervention efficacy for the blue curve scenario in (A). The grey bars illustrate efficacy over a 3 months range. (C) Represents the same as in (A), but for a intermediate transmission setting. (D) The dashed line represents the age instantaneous intervention efficacy for the blue curve scenario in (C). The grey bars illustrate efficacy over a 3 months period.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2722080&req=5

pone-0006627-g002: IPTi impact on clinical malaria age profiles.Analysis of the outcome of applying prophylactics at 2, 3 and 9 months of age, for 10 years, in terms of age profile of clinical disease prevalence and intervention efficacy. Age profiles of populations under IPTi are compared with populations without intervention, in equilibrium conditions (black line). (A) Simulations assuming different combinations of values for c and σ, under intense malaria transmission. The values for these 2 parameters are equal for each curve, ranging from (green line) to (red line). The blue line represents the intermediate combination, . (B) The dashed line represents the age instantaneous intervention efficacy for the blue curve scenario in (A). The grey bars illustrate efficacy over a 3 months range. (C) Represents the same as in (A), but for a intermediate transmission setting. (D) The dashed line represents the age instantaneous intervention efficacy for the blue curve scenario in (C). The grey bars illustrate efficacy over a 3 months period.
Mentions: Figures 2A and 2C investigate how the probability of acquiring clinical immunity when infected while in the ST class, c, and the reduced risk of acquiring an infection while treated, σ, modulate the age profiles of clinical malaria. We show the age profiles for the parameter combinations that result in the best (green line) and worst (red line) intervention impacts, as well as a parameter combination assuming an empirical estimate for σ [35]–[37] and a conservative guess for c (blue line). In Figure 2A, we use a value for the force of infection corresponding to a high transmission setting (in this case parasite prevalence if around 90%). We observe that, if immunity is efficiently acquired upon clinical infection,c = 1, and the drug does not reduce the risk of having a malaria infection, (green line), the predicted rebound effect is minimised. For intermediate levels, , of these parameters (blue line), the model suggests that rebound becomes significant after the first year of life. This effect is exacerbated when treatment prevents infection from occurring and clinical immunity is not built up due to prophylaxis, (red line). From the green, , to the red line, , the proportion of cases predicted to be prevented up to age 10 decreases from 12.8% to 0.9%, being 5.6% for the blue line, (Table 2). Generally, these results suggest that there is an evident beneficial effect at the ages targeted by treatment, regardless of parameter values. More importantly, there is a noticeable rebound effect, meaning that the treated group is at increased risk of having a clinical malaria episode, after the last dose of treatment.

Bottom Line: Here, we simulate several schemes of intervention under different transmission settings, while varying immunity build up assumptions.However, even when significant rebound effects are predicted to occur, the overall intervention impact is positive.On the contrary, IPTc has a significant potential to reduce transmission, specifically in areas where it is already low to moderate.

View Article: PubMed Central - PubMed

Affiliation: Instituto Gulbenkian de Ciência, Oeiras, Portugal. ricaguas@igc.gulbenkian.pt

ABSTRACT

Background: Clinical management of malaria is a major health issue in sub-Saharan Africa. New strategies based on intermittent preventive treatment (IPT) can tackle disease burden by simultaneously reducing frequency of infections and life-threatening illness in infants (IPTi) and children (IPTc), while allowing for immunity to build up. However, concerns as to whether immunity develops efficiently in treated individuals, and whether there is a rebound effect after treatment is halted, have made it imperative to define the effects that IPTi and IPTc exert on the clinical malaria scenario.

Methods and findings: Here, we simulate several schemes of intervention under different transmission settings, while varying immunity build up assumptions. Our model predicts that infection risk and effectiveness of acquisition of clinical immunity under prophylactic effect are associated to intervention impact during treatment and follow-up periods. These effects vary across regions of different endemicity and are highly correlated with the interplay between the timing of interventions in age and the age dependent risk of acquiring an infection. However, even when significant rebound effects are predicted to occur, the overall intervention impact is positive.

Conclusions: IPTi is predicted to have minimal impact on the acquisition of clinical immunity, since it does not interfere with the occurrence of mild infections, thus failing to reduce the underlying force of infection. On the contrary, IPTc has a significant potential to reduce transmission, specifically in areas where it is already low to moderate.

Show MeSH
Related in: MedlinePlus