Can changes in malaria transmission intensity explain prolonged protection and contribute to high protective efficacy of intermittent preventive treatment for malaria in infants?
© Gosling et al; licensee BioMed Central Ltd. 2008
Received: 14 December 2007
Accepted: 03 April 2008
Published: 03 April 2008
Intermittent preventive (or presumptive) treatment of infants (IPTi), the administration of a curative anti-malarial dose to infants whether or not they are known to be infected, is being considered as a new strategy for malaria control. Five of the six trials using sulphadoxine-pyrimethamine (SP) for IPTi showed protective efficacies (PEs) against clinical malaria ranging from 20.1 – 33.3% whilst one, the Ifakara study, showed a protective efficacy of 58.6%.
Materials and methods
The possible mechanisms that could explain the differences in the reported PE of IPTi were examined by comparing output from a mathematical model to data from the six published IPTi trials.
Under stable transmission, the PE of IPTi predicted by the model was comparable with the observed PEs in all but the Ifakara study (ratio of the mean predicted PE to that observed was 1.02, range 0.39 – 1.59). When a reduction in the incidence of infection during the study was included in the model, the predicted PE of IPTi increased and extended into the second year of life, as observed in the Ifakara study.
A decrease in malaria transmission during the study period may explain part of the difference in observed PEs of IPTi between sites and the extended period of protection into the second year of life observed in the Ifakara study. This finding of continued benefit of interventions in settings of decreasing transmission may explain why rebound of clinical malaria was absent in the large scale trials of insecticide-treated bed nets.
Intermittent preventive treatment of infants (IPTi) is the administration of a curative anti-malarial dose to infants, whether or not they are known to be infected, at specified times to prevent malaria . IPTi delivered through the EPI programme was first shown to successfully prevent malaria in infants in 2001 . Three doses of sulphadoxine-pyrimethamine (SP) given to Tanzanian infants living in an area of perennial transmission at the time of vaccination with DPT2, DPT3 and measles vaccines reduced the incidence of clinical malaria and anaemia during the first year of life by 59% and 50% respectively. Furthermore, protection against clinical episodes of malaria persisted into the second year of life . In contrast, in northern Ghana, where malaria transmission is intense and highly seasonal, SP-IPTi gave only 25% protection against clinical malaria and 35% protection against hospital admissions with anaemia during the first year of life and no protection during the second year . A similar level of protection against clinical malaria during the first year of life was seen in Mozambique but no protection against anaemia was detected in this study . Further trials of SP-IPTi conducted in areas of Ghana [6, 7] and Gabon  with differing epidemiological patterns of malaria have given similar results to those observed in Ghana and Mozambique. The results from the first study in Tanzania therefore appear at odds with those from the later studies.
A number of explanations for the differences in protective efficacy (PE) of IPTi against clinical malaria between sites has been suggested including the intensity of transmission and consequent malaria incidence, the pattern of antimalarial resistance, the administration of iron and the use of additional control measures, specifically insecticide-treated nets (ITN) . This paper, using data from the six SP-IPTi randomized placebo-controlled trials reported so far, explored the association between resistance to SP, ITN coverage and malaria transmission intensity in each study site. The observed PE of IPTi against clinical malaria is examined using a mathematical model which mimics the acquisition and loss of parasites to predict the PE expected in the six trial settings.
Study characteristics of SP-IPTi efficacy trials
Schellenberg et al. [2, 3]
Chandramohan et al. 
Macete et al
Kobbe et al. 
Mockenhaupt et al. 
Grobusch et al
Highly seasonal high
Perennial with seasonal peaks moderate
Perennial with seasonal peaks high
Perennial with seasonal peaks low-moderate
In vivo SP resistance by day 14%
31 (1999–2000) 
22 (2004) 
21 (2001) 
14 (2002) 
21 (2004) 
Use of bed nets, % placebo/SP treated (untreated)
20/20 estimate (39/38)
Ages at dosing, months
2, 3, 9 (at time of DPT2, DPT3 & measles)
3, 4, 9, 12 (at time of DPT2, DPT3 & measles + extra at 12 months)
3, 4, 9 (at time of DPT2, DPT3 & measles)
3, 9, 15 (at time of DPT3 & measles + extra at 15 months)
3, 9, 15 (at time of DPT3 & measles + extra at 15 months)
3, 9, 15 (at time of DPT3 & measles + extra at 15 months)
No. of children enrolled, placebo/active
351/350 = 701
1,242/1,243 = 2,485
755/748 = 1,503
535/535 = 1,070
600/600 = 1,200
595/594 = 1,189
The relationship between the observed PE of IPTi and the following potential determinants of PE were explored: resistance to SP; estimated ITN coverage (% of the study population reporting use of ITN); and malaria transmission intensity (mean incidence of malaria per child per year in the placebo group). Day-14 parasitological and clinical failure rates were used to define resistance because five out of the six IPTi trials had published this information within two years of conducting the IPTi trial [10–14]. One site in Ghana, Kumasi, did not have data on day 14 parasitological and clinical failure of SP and therefore the estimate from Tamale, relatively close geographically, was used.
where N is the fixed population size, r(a) is the age-dependent rate of natural clearance of parasitaemia and c(a) is the age-dependent rate of development of clinical disease which is then treated.
where ϕ is the rate of development of clinical disease in the absence of immunity and α1 and α2 are parameters which determine the number of infections after which full immunity to clinical disease occurs. The rate of natural clearance of parasites is assumed to be linear within the range of interest and hence is given by
r(a) = min(ω E [I(a)], 1)) (4)
where 1/ω is the mean number of infections after which full parasite immunity is obtained and it was assumed that at full immunity parasites are cleared after a mean of one day.
A generic maternal protective function which acts to reduce the force of infection following birth was incorporated. Maternal protection is complicated and multifaceted , incorporating both biological immunity as well as behavioural factors that limit exposure. Given the paucity of data with which to determine an appropriate function, the following factors were used, which act on the force of infection up to six months of age: 0.05, 0.15, 0.4 and 0.8 at age 2, 3, 4 and 5 months of age respectively, which represent a gradual loss of immunity.
The model was numerically evaluated as difference equations in 1-month time-steps using Excel.
Incorporation of IPT and ITN
The model only examines the personal protection gained from an ITN and does not examine any other effects, such as effects on transmission.
For the modelling exercise, the coverage of ITNs (reported ownership) in each trial site was used because the use of ITN at the individual level was not available for all trials. The expected incidence of clinical disease in each trial arm (placebo and IPT) is therefore calculated as a weighted combination of the model predictions with and without ITNs. The protective efficacy of IPT predicted by the model is calculated as 1-relative risk = 1-clinical incidence in IPTi group/clinical incidence in placebo group.
Summary of Model Parameters and Symbols
Definitions for equations
Susceptible population at age (a)
Asymptomatic population at age (a)
Age-dependent rate of natural clearance of parasitaemia at age (a)
Age-dependent rate of development of clinical disease which is then treated at age (a)
Rate of development of clinical disease in the absence of immunity
Mean number of infections after which full immunity to clinical disease occurs
Parameters which determine the number of infections after which full immunity to clinical disease occurs
α1 and α2
Mean number of infections after which full parasite immunity occurs
Protection offered by ITN use
Variable parameters between sites
Force of infection
See table 3
Drug action reducing the force of infection
See table 3
The proportion of infected children becoming symptomatic and treated in the absence of immunity was assumed to be 90% in one month. This was derived from a study of asymptomatic parasitaemia in 6–59 month old children in a moderate malaria setting in Kampala, Uganda ; in this population 50% of children with asymptomatic parasitaemia developed clinical malaria after 30 days. As the Ugandan study was undertaken in partially immune children we assumed a higher rate of development of disease. Clinical malaria cases are assumed to recover within a month post treatment, twice the average terminal half-life of the antimalarials used for treatment and rejoin the susceptible population. Deaths and migrations were not included in the model.
For those children receiving IPT, it is assumed that treatment, prophylaxis, and prevention of developing clinical disease effects of SP will be equally affected by the PCR uncorrected day 28 ACPR of SP. Day 28 PCR uncorrected ACPR is a measure of both the treatment and prophylactic effect combined (it includes both recrudescence's and re-infections) and is more likely to represent the effects of the drugs when used for prevention as opposed to treatment. The sensitivity analysis for how changes in ACPR affect PE is shown in the in the results section. Briefly, as drug resistance increases PE declines. The day 28 ACPR was only available for 2 sites, the sites with the highest and lowest resistances at day 14, namely Ifakara  and Tamale  respectively. The extrapolation from day 14 to 28 efficacy for the 3 studies [11–13] without day 28 ACPR is the mid point between these two studies.
A sensitivity analysis of how ACPR, ITN coverage and immunity functions affects predicted PE was carried out.
Association between IPTi protective efficacy and various factors
Protective efficacy of IPTi in stable transmission settings
Modelled and actual protective efficacy to 12 months of age in each IPTi trials
Age of SP IPTi administration (months)
Mean incidence in placebo group (episodes per person year) (λ (a)/2)
ITN coverage (%)
Estimated*** cross sectional prevalence parasitaemia at start of study (%)
Estimated Day 28 ACPR for SP ( σ × 100)
Model estimate of PE (%)
Actual PE of IPTi (% 95% CI)
2,3 and 9
2,4,9 and 12
3,4 and 9
3,9 and 15
3,9 and 15
3,9 and 15
Protective efficacy of IPTi in changing transmission settings
Change in Protective Efficacy and rebound effect with changes in transmission
Transmission effect per month (%)
Predicted protective efficacy over first 12 months (%)
No maternal immunity
> 24 months
Maternal immunity included
Sensitivity analysis of effects of ACPR on models predictions of PE
Observed PE (%, 95% CI)
Model PE (%)
ACPR increased to 100%
ACPR reduced to 40%
Sensitivity analysis of maternal immunity function on models predictions of PE with (a) no maternal immunity function, (b) with fixed non-parametric function used in the paper (Baseline) and (c) function based on maternal immunity to severe disease.
Observed PE (%, 95% CI)
Model PE (%)
(a) No immunity
(c) Alternative based on immunity to severe disease
The high PE of IPTi found in the Ifakara study and a similar preventive trial using amodiaquine in north-eastern Tanzania  triggered a series of IPT trials in other African study sites to investigate this potentially promising method of malaria control. Subsequent published trials showed a much lower efficacy of IPTi than was observed in Ifakara . To explain these differences in efficacy between sites some observers have focussed on the differences in drug resistance to SP between the sites. However, this explanation does not appear plausible because the site with the highest PE had the highest SP resistance (Figure 2). In response to this observation, it has been suggested that there may be an immunisation effect of SP, the "Leaky Drug" theory [3, 21]. The hypothesis is that a partially effective drug allows for low level and persisting parasitaemia and thus allowing prolonged stimulation of the immune system resulting in the extended period of protection as seen in the Ifakara site. This model-based analysis provides an alternative explanation, namely that the exceptionally high ITN coverage in Ifakara decreased transmission and boosted the observed PE of IPTi. High ITN coverage was recognised as a potential explanation of differences in PE between the Manhica and Ifakara studies . Ifakara District is known to have experienced a 10 fold reduction in transmission around the study period (for example, the EIR in 1995 was recorded as 300 and by 2001 had fallen to 29). Although the EIR estimates came from different places within the district there was a reported change in the epidemiology of clinical disease during this time period . In addition many other studies have shown the mass effect on transmission of high ITN coverage . The model suggests that changing the transmission intensity affects both the PE and the length of protection and thus gives a plausible explanation for the difference in results between study sites. Another modelling exercise focussing on the mechanism of IPTi (Ross A., manuscript in preparation) has confirmed this finding. No clear decrease was seen in the mean incidence of clinical malaria in the placebo arm of the Ifakara study from the published data from the first  to the second  year, going from 0.43 to 0.42 episodes per person year at risk. The model predicts that over the first year of the study transmission must fall by at least 22% per month to be within the 95% confidence limits of the PE observed. Whilst this seems unlikely, the pattern of transmission faced by the cohort may have changed within the observation period and affected the observed PE. To test the hypothesis derived from this model the data will need to be examined by looking at monthly incidence in each group by age in the Ifakara study.
The model shows that PE mainly depends on the level of malaria transmission during the few months which IPTi doses are administered and the length of follow up and transmission intensity when IPTi is not given. To maximise PE IPTi should be given during high malaria transmission and follow up should be short when malaria transmission is low. Supportive evidence for this is demonstrated in the extended analysis of the Navrongo study  and an IPT seasonal study where antimalarials were given in Senegal, West Africa during the malaria seasons with a short follow up of 13 weeks . In this study efficacy against clinical malaria was 86%.
This model also provides a coherent explanation as to why no rebound effect would be observed in situations of decreasing transmission, such as Ifakara or Kenya [24, 25]. The delay in acquisition of immunity caused by very successful interventions such as continuous chemoprophylaxis in infants are followed by increases in cases following cessation of the intervention, the rebound effect [26–28]. In this situation of chemoprophylaxis in a single age group there is no effect on transmission. However, in the large ITN trials where no rebound was seen, the mass effect of the ITNs in reducing vectorial capacity led to a decrease in transmission . The model predicts that in the presence of decreasing transmission rebound parasitaemia can disappear. Thus, although the population is immunologically more susceptible to infection with malaria, it is less exposed and so cases of malaria infection reduce. In contrast, when an intervention that reduces exposure and hence immunity to malaria takes place in a site with stable malaria transmission or one in which transmission is increasing a rebound effect would be evident. If IPT was spread across all age groups, ie as a form of mass drug administration or universal IPT (IPTu) reducing the asymptomatic pool (A(a) in the model) in the whole population and not a small age group, an effect on transmission may be seen.
ITNs exert a steady personal protection to the individual sleeping under the net of approximately 50%  as long as the insecticide remains active. IPTi offers intermittent protection which varies with the efficacy of the drug only at times when it is administered. Therefore it follows that protection with an ITN should be the primary intervention with IPTi as an additional strategy. The model found the largest difference in incidence of clinical malaria between placebo groups without ITN compared to ITN plus IPTi. This observation suggests that combining interventions must be a priority. ITN coverage has little influence on the predicted PE by the model. This is because the model defines the protection of an ITN to act to reduce the force of infection to the proportion of those using ITNs and then calculates the overall PE weighted by this coverage. The model assumes an additive effect of IPTi and ITNs and not synergy.
As with all theoretical studies, the model has some limitations. The model is dependent on some key assumptions regarding the effect of exposure on immunity. First, it is assumed that full clinical immunity was obtained after five infections. This figure was derived from past estimates for severe malaria  but clearly requires further data for verification. Increasing the number of infections required to become immune to developing clinical disease would result in a smaller rebound effect and a smaller decrease in transmission would eliminate the rebound effect. No clear evidence for rebound has been seen in the trials , thus the number of clinical attacks leading to immunity is likely to be more than five. Similarly, the threshold for achieving parasite immunity was arbitrarily set at 50 infections. However, as the model only considers malaria in the first 2 years of life, children are unlikely to reach the five attacks needed to become immune to clinical disease (mean number of expected attacks in Kumasi, the highest transmission setting, was 2.7 at 24 months of age) and even less likely to reach the 50 attacks to give full antiparasite immunity, the results are less sensitive to these choices of immune function. Whilst the choice of immunity functions determines the extent of the rebound effect predicted by the model, it does not impact greatly on the protective efficacies predicted by the model. In contrast, the assumptions made regarding maternal protection do impact on the predicted protective efficacy (Tables 4 and 6, Figure 4A and 4B). The effect of maternal protection is likely to vary by site and be influenced by levels of transmission experienced by the mother during the transplacental passage of humoral immunity and behavioural factors. Further data are required to refine this function. Differences in calculating time at risk following treatment also bias the model to detect a higher PE. In the analysis used to produce the PEs in the studies, a child was censored for 21 days after each case of malaria yet the model uses one month time steps and so cases of malaria are censored seven days longer, reducing the time at risk denominator. The model studies very few variables and only those directly affecting malaria. The differences of the PEs in the studies could be related to factors so far remaining unstudied such as HIV prevalence, socio-economic status, timing and dose of IPTi, heterogeneity of malaria transmission or placental infection.
What does this study mean for IPTi? This model demonstrates that during a decline in malaria transmission, which Africa is currently experiencing, IPTi can be highly effective and safe. Combining IPTi with ITNs results in greater protection for an individual, further more, if high levels of coverage of ITNs can be attained with a resultant decrease in transmission, then there appears to be synergy between the interventions. However, if transmission subsequently increases a reduction in the efficacy of IPTi (as currently measured by comparing incidence rates of malaria over a long period) can be expected. In stable conditions, PE does not seem to be greatly affected by levels of transmission, however the higher the level of transmission the more likely a rebound effect is to be seen. The rebound effect is equivalent to delaying of clinical cases of malaria to an older age which may be beneficial as older children appear to develop less severe illness than infants . Indeed, these observations will apply to all types of interventions during times of changing transmission intensity. Currently there is a reduction of transmission across sub-Saharan Africa , thus exposure and immunity will be reduced leaving the possibility for outbreaks of malaria disease should transmission increase again. Drug resistance does play a role in IPTi efficacy and this should continue to be monitored. However, changes in transmission are likely to have a greater effect on IPTi protective efficacy in the trials that have taken place with the levels of drug resistance studied.
The authors wish to thank the following people: The IPTi Consortium particularly David Schellenberg, Robert Newman, Andrea Egan, Clara Menendez, John Aponte, Martin Grobusch, Alexandra De Sousa, Mary Hamel, Ivo Meuller, Ilona Carneiro, Tom Smith and Amanda Ross for their helpful comments, access to the data and support; The editors of Tropical Medicine and International Health, Blackwell Publishing, for allowing us to reproduce Figure 3C; Chris Drakeley, Cally Roper, Tanya Marchant, Colin Sutherland, Matthew Cairns and Michala Van Rose for their comments and encouragement; and the Kilimanjaro IPTi study team and participants for their inspiration. RG, JD and LVS are funded through grants from the Bill and Melinda Gates Foundation. AG, BG and DC are funded by their respective institutions.
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