The effect of malaria transmission intensity on neonatal mortality in endemic areas

The influence of biological, epidemiological, and treatment factors on the establishment and spread of drug-resistant Plasmodium falciparum

The effectiveness of artemisinin-based combination therapies (ACTs) to treat Plasmodium falciparum malaria is threatened by resistance. The complex interplay between sources of selective pressure-treatment properties, biological factors, transmission intensity, and access to treatment-obscures understanding how, when, and why resistance establishes and spreads across different locations. We developed a disease modelling approach with emulator-based global sensitivity analysis to systematically quantify which of these factors drive establishment and spread of drug resistance. Drug resistance was more likely to evolve in low transmission settings due to the lower levels of (i) immunity and (ii) within-host competition between genotypes. Spread of parasites resistant to artemisinin partner drugs depended on the period of low drug concentration (known as the selection window). Spread of partial artemisinin resistance was slowed with prolonged parasite exposure to artemisinin derivatives and accelerated when the parasite was also resistant to the partner drug. Thus, to slow the spread of partial artemisinin resistance, molecular surveillance should be supported to detect resistance to partner drugs and to change ACTs accordingly. Furthermore, implementing more sustainable artemisinin-based therapies will require extending parasite exposure to artemisinin derivatives, and mitigating the selection windows of partner drugs, which could be achieved by including an additional long-acting drug.

Relationship between changing malaria burden and low birth weight in sub-Saharan Africa: A difference-in-differences study via a pair-of-pairs approach

Background

According to the World Health Organization (WHO), in 2018, an estimated 228 million malaria cases occurred worldwide with most cases occurring in sub-Saharan Africa. Scale-up of vector control tools coupled with increased access to diagnosis and effective treatment has resulted in a large decline in malaria prevalence in some areas, but other areas have seen little change. Although interventional studies demonstrate that preventing malaria during pregnancy can reduce the rate of low birth weight (i.e. child's birth weight <2500 g), it remains unknown whether natural changes in parasite transmission and malaria burden can improve birth outcomes.

Methods

We conducted an observational study of the effect of changing malaria burden on low birth weight using data from 18,112 births in 19 countries in sub-Saharan African countries during the years 2000-2015. Specifically, we conducted a difference-in-differences study via a pair-of-pairs matching approach using the fact that some sub-Saharan areas experienced sharp drops in malaria prevalence and some experienced little change.

Results

A malaria prevalence decline from a high rate (Plasmodium falciparum parasite rate in children aged 2-up-to-10 (i.e. PfPR2-10) > 0.4) to a low rate (PfPR2-10 < 0.2) is estimated to reduce the rate of low birth weight by 1.48 percentage points (95% confidence interval: 3.70 percentage points reduction, 0.74 percentage points increase), which is a 17% reduction in the low birth weight rate compared to the average (8.6%) in our study population with observed birth weight records (1.48/8.6 ≈ 17%). When focusing on first pregnancies, a decline in malaria prevalence from high to low is estimated to have a greater impact on the low birth weight rate than for all births: 3.73 percentage points (95% confidence interval: 9.11 percentage points reduction, 1.64 percentage points increase).

Conclusions

Although the confidence intervals cannot rule out the possibility of no effect at the 95% confidence level, the concurrence between our primary analysis, secondary analyses, and sensitivity analyses, and the magnitude of the effect size, contribute to the weight of the evidence suggesting that declining malaria burden can potentially substantially reduce the low birth weight rate at the community level in sub-Saharan Africa, particularly among firstborns. The novel statistical methodology developed in this article-a pair-of-pairs approach to a difference-in-differences study-could be useful for many settings in which different units are observed at different times.

Funding

Ryan A. Simmons is supported by National Center for Advancing Translational Sciences (UL1TR002553). The funder had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Modelling the relationship between malaria prevalence as a measure of transmission and mortality across age groups

Background

Parasite prevalence has been used widely as a measure of malaria transmission, especially in malaria endemic areas. However, its contribution and relationship to malaria mortality across different age groups has not been well investigated. Previous studies in a health and demographic surveillance systems (HDSS) platform in western Kenya quantified the contribution of incidence and entomological inoculation rates (EIR) to mortality. The study assessed the relationship between outcomes of malaria parasitaemia surveys and mortality across age groups.

Methods

Parasitological data from annual cross-sectional surveys from the Kisumu HDSS between 2007 and 2015 were used to determine malaria parasite prevalence (PP) and clinical malaria (parasites plus reported fever within 24 h or temperature above 37.5 °C). Household surveys and verbal autopsy (VA) were used to obtain data on all-cause and malaria-specific mortality. Bayesian negative binomial geo-statistical regression models were used to investigate the association of PP/clinical malaria with mortality across different age groups. Estimates based on yearly data were compared with those from aggregated data over 4 to 5-year periods, which is the typical period that mortality data are available from national demographic and health surveys.

Results

Using 5-year aggregated data, associations were established between parasite prevalence and malaria-specific mortality in the whole population (RR_malaria = 1.66; 95% Bayesian Credible Intervals: 1.07–2.54) and children 1–4 years (RR_malaria = 2.29; 1.17–4.29). While clinical malaria was associated with both all-cause and malaria-specific mortality in combined ages (RR_all-cause = 1.32; 1.01–1.74); (RR_malaria = 2.50; 1.27–4.81), children 1–4 years (RR_all-cause = 1.89; 1.00–3.51); (RR_malaria = 3.37; 1.23–8.93) and in older children 5–14 years (RR_all-cause = 3.94; 1.34–11.10); (RR_malaria = 7.56; 1.20–39.54), no association was found among neonates, adults (15–59 years) and the elderly (60+ years). Distance to health facilities, socioeconomic status, elevation and survey year were important factors for all-cause and malaria-specific mortality.

Conclusion

Malaria parasitaemia from cross-sectional surveys was associated with mortality across age groups over 4 to 5 year periods with clinical malaria more strongly associated with mortality than parasite prevalence. This effect was stronger in children 5–14 years compared to other age-groups. Further analyses of data from other HDSS sites or similar platforms would be useful in investigating the relationship between malaria and mortality across different endemicity levels.

Electronic supplementary material

The online version of this article (10.1186/s12936-019-2869-9) contains supplementary material, which is available to authorized users.

Prevention of malaria in pregnancy

Malaria remains one of the most preventable causes of adverse birth outcomes. Intermittent preventive treatment in pregnancy (IPTp) with sulfadoxine-pyrimethamine is used to prevent malaria, but resistance to this drug combination has decreased its efficacy and new alternatives are needed. In Africa, a meta-analysis showed three-course or monthly IPTp with sulfadoxine-pyrimethamine to be safe and more effective than the original two-course sulfadoxine-pyrimethamine strategy, prompting WHO to update its policy in 2012. Although resistance to sulfadoxine-pyrimethamine reduces the parasitological efficacy of IPTp, this drug combination remains associated with reduced incidence of low birthweight in areas where prevalence of parasites with quintuple Plasmodium falciparum dihydrofolate reductase (Pfdhfr) and dihydropteroate synthetase (Pfdhps) mutations is greater than 90%. Nevertheless, its effectiveness is compromised in women infected with sextuple mutant parasites. Six trials of IPTp showed that neither amodiaquine, mefloquine, nor chloroquine-azithromycin are suitable replacements for sulfadoxine-pyrimethamine because of poor tolerability. Furthermore, four trials showed that intermittent screening and treatment with the current generation of malaria rapid diagnostic tests was not a suitable alternative strategy to IPTp with sulfadoxine-pyrimethamine, even in areas with high prevalence of quintuple mutations. Two trials showed that IPTp with dihydroartemisinin-piperaquine was well tolerated, effective, and acceptable for IPTp, with monthly regimens being the most effective. Coverage of IPTp and insecticide-treated nets continues to lag behind targets. The key barriers to uptake are well documented, and many are open to intervention. Outside of Africa, a single trial suggests a potential role for integrated approaches that combine sulfadoxine-pyrimethamine with azithromycin for IPTp in areas of Papua New Guinea where malaria transmission is high. Modelling analysis suggests the importance of the prevention of malaria early in pregnancy and the need to protect pregnant women declines more slowly than the rate at which transmission declines. Improved funding has led to an increase in the number of prevention trials in the past decade, showing the value of more sustained protection with monthly IPTp regimens. There is a need for confirmatory trials of the safety, efficacy, and feasibility of IPTp with dihydroartemisinin-piperaquine, for studies of intermittent screening and treatment with more sensitive rapid diagnostic tests, for studies of integrated strategies for malaria and other co-infections, and for studies of prevention strategies for malaria in pregnant women who are HIV-positive and living outside of Africa. Additional research is required on how to improve uptake of WHO's updated policy on IPTp with sulfadoxine-pyrimethamine and insecticide-treated nets.

Bayesian spatio-temporal modeling of mortality in relation to malaria incidence in Western Kenya

INTRODUCTION

The effect of malaria exposure on mortality using health facility incidence data as a measure of transmission has not been well investigated. Health and demographic surveillance systems (HDSS) routinely capture data on mortality, interventions and other household related indicators, offering a unique platform for estimating and monitoring the incidence-mortality relationship in space and time.

METHODS

Mortality data from the HDSS located in Western Kenya collected from 2007 to 2012 and linked to health facility incidence data were analysed using Bayesian spatio-temporal survival models to investigate the relation between mortality (all-cause/malaria-specific) and malaria incidence across all age groups. The analysis adjusted for insecticide-treated net (ITN) ownership, socio-economic status (SES), distance to health facilities and altitude. The estimates obtained were used to quantify excess mortality due to malaria exposure.

RESULTS

Our models identified a strong positive relationship between slide positivity rate (SPR) and all-cause mortality in young children 1-4 years (HR = 4.29; 95% CI: 2.78-13.29) and all ages combined (HR = 1.55; 1.04-2.80). SPR had a strong positive association with malaria-specific mortality in young children (HR = 9.48; 5.11-37.94), however, in older children (5-14 years), it was associated with a reduction in malaria specific mortality (HR = 0.02; 0.003-0.33).

CONCLUSION

SPR as a measure of transmission captures well the association between malaria transmission intensity and all-cause/malaria mortality. This offers a quick and efficient way to monitor malaria burden. Excess mortality estimates indicate that small changes in malaria incidence substantially reduce overall and malaria specific mortality.

Spectrum-Malaria: a user-friendly projection tool for health impact assessment and strategic planning by malaria control programmes in sub-Saharan Africa

BACKGROUND

Scale-up of malaria prevention and treatment needs to continue but national strategies and budget allocations are not always evidence-based. This article presents a new modelling tool projecting malaria infection, cases and deaths to support impact evaluation, target setting and strategic planning.

METHODS

Nested in the Spectrum suite of programme planning tools, the model includes historic estimates of case incidence and deaths in groups aged up to 4, 5-14, and 15+ years, and prevalence of Plasmodium falciparum infection (PfPR) among children 2-9 years, for 43 sub-Saharan African countries and their 602 provinces, from the WHO and malaria atlas project. Impacts over 2016-2030 are projected for insecticide-treated nets (ITNs), indoor residual spraying (IRS), seasonal malaria chemoprevention (SMC), and effective management of uncomplicated cases (CMU) and severe cases (CMS), using statistical functions fitted to proportional burden reductions simulated in the P. falciparum dynamic transmission model OpenMalaria.

RESULTS

In projections for Nigeria, ITNs, IRS, CMU, and CMS scale-up reduced health burdens in all age groups, with largest proportional and especially absolute reductions in children up to 4 years old. Impacts increased from 8 to 10 years following scale-up, reflecting dynamic effects. For scale-up of each intervention to 80% effective coverage, CMU had the largest impacts across all health outcomes, followed by ITNs and IRS; CMS and SMC conferred additional small but rapid mortality impacts.

DISCUSSION

Spectrum-Malaria's user-friendly interface and intuitive display of baseline data and scenario projections holds promise to facilitate capacity building and policy dialogue in malaria programme prioritization. The module's linking to the OneHealth Tool for costing will support use of the software for strategic budget allocation. In settings with moderately low coverage levels, such as Nigeria, improving case management and achieving universal coverage with ITNs could achieve considerable burden reductions. Projections remain to be refined and validated with local expert input data and actual policy scenarios.

Applying a system dynamics modelling approach to explore policy options for improving neonatal health in Uganda

BACKGROUND

The most recent reports on global trends in neonatal mortality continue to show alarmingly slow progress on improvements in neonatal mortality rates, with sub-Saharan Africa still lagging behind. This emphasised the urgent need to innovatively employ alternative solutions that take into account the intricate complexities of neonatal health and the health systems in which the various strategies operate.

METHODS

In our first paper, we empirically explored the causes of the stagnating neonatal mortality in Uganda using a dynamic synthesis methodology (DSM) approach. In this paper, we completed the last three stages of DSM, which involved the development of a quantitative (simulation) model, using STELLA modelling software. We used statistical data to populate the model. Through brainstorming sessions with stakeholders, iterations to test and validate the model were undertaken. The different strategies and policy interventions that could possibly lower neonatal mortality rates were tested using what-if analysis. Sensitivity analysis was used to determine the strategies that could have a great impact on neonatal mortality.

RESULTS

We developed a neonatal health simulation model (NEOSIM) to explore potential interventions that could possibly improve neonatal health within a health system context. The model has four sectors, namely population, demand for services, health of the mothers and choices of clinical care. It tests the effects of various interventions validated by a number of Ugandan health practitioners, including health education campaigns, free delivery kits, motorcycle coupons, kangaroo mother care, improving neonatal resuscitation and labour management skills, and interventions to improve the mothers health, i.e. targeting malaria, anaemia and tetanus. Among the tested interventions, the package with the highest impact on reducing neonatal mortality rates was a combination of the free delivery kits in a setting where delivery services were free and motorcycle coupons to take women to hospital during emergencies.

CONCLUSIONS

This study presents a System Dynamics model with a broad and integrated view of the neonatal health system facilitating a deeper understanding of its current state and constraints and how these can be mitigated. A tool with a user friendly interface presents the dynamic nature of the model using 'what-if' scenarios, thus enabling health practitioners to discuss the consequences or effects of various decisions. Key findings of the research show that proposed interventions and their impact can be tested through simulation experiments thereby generating policies and interventions with the highest impact for improved healthcare service delivery.

Dynamics of the Human Infectious Reservoir for Malaria Determined by Mosquito Feeding Assays and Ultrasensitive Malaria Diagnosis in Burkina Faso

BACKGROUND

Plasmodium falciparum gametocytes are essential for malaria transmission. Malaria control measures that aim at reducing transmission require an accurate characterization of the human infectious reservoir.

METHODS

We longitudinally determined human infectiousness to mosquitoes and P. falciparum carriage by an ultrasensitive RNA-based diagnostics in 130 randomly selected inhabitants of an endemic area.

RESULTS

At least 1 mosquito was infected by 32.6% (100 of 307) of the blood samples; in total, 7.6% of mosquitoes (916 of 12 079) were infected. The proportion of infectious individuals and infected mosquitoes were negatively associated with age and positively with asexual parasites (P < .001). Human infectiousness was higher at the start of the wet season and subsequently declined at the peak of the wet season (adjusted odds ratio, 0.52; P = .06) and in the dry season (0.23; P < .001). Overall, microscopy-negative individuals were responsible for 28.7% of infectious individuals (25 of 87) and 17.0% of mosquito infections (145 of 855).

CONCLUSIONS

Our study reveals that the infectious reservoir peaks at the start of the wet season, with prominent roles for infections in children and submicroscopic infections. These findings have important consequences for strategies and the timing of interventions, which need to include submicroscopic infections and be implemented in the dry season.

Targeting Human Transmission Biology for Malaria Elimination

Malaria remains one of the leading causes of death worldwide, despite decades of public health efforts. The recent commitment by many endemic countries to eliminate malaria marks a shift away from programs aimed at controlling disease burden towards one that emphasizes reducing transmission of the most virulent human malaria parasite, Plasmodium falciparum. Gametocytes, the only developmental stage of malaria parasites able to infect mosquitoes, have remained understudied, as they occur in low numbers, do not cause disease, and are difficult to detect in vivo by conventional methods. Here, we review the transmission biology of P. falciparum gametocytes, featuring important recent discoveries of genes affecting parasite commitment to gametocyte formation, microvesicles enabling parasites to communicate with each other, and the anatomical site where immature gametocytes develop. We propose potential parasite targets for future intervention and highlight remaining knowledge gaps.

Determinants of the cost-effectiveness of intermittent preventive treatment for malaria in infants and children

BACKGROUND

Trials of intermittent preventive treatment in infants (IPTi) and children (IPTc) have shown promising results in reducing malaria episodes but with varying efficacy and cost-effectiveness. The effects of different intervention and setting characteristics are not well known. We simulate the effects of the different target age groups and delivery channels, seasonal or year-round delivery, transmission intensity, seasonality, proportions of malaria fevers treated and drug characteristics.

METHODS

We use a dynamic, individual-based simulation model of Plasmodium falciparum malaria epidemiology, antimalarial drug action and case management to simulate DALYs averted and the cost per DALY averted by IPTi and IPTc. IPT cost components were estimated from economic studies alongside trials.

RESULTS

IPTi and IPTc were predicted to be cost-effective in most of the scenarios modelled. The cost-effectiveness is driven by the impact on DALYs, particularly for IPTc, and the low costs, particularly for IPTi which uses the existing delivery strategy, EPI. Cost-effectiveness was predicted to decrease with low transmission, badly timed seasonal delivery in a seasonal setting, short-acting and more expensive drugs, high frequencies of drug resistance and high levels of treatment of malaria fevers. Seasonal delivery was more cost-effective in seasonal settings, and year-round in constant transmission settings. The difference was more pronounced for IPTc than IPTi due to the different proportions of fixed costs and also different assumed drug spacing during the transmission season. The number of DALYs averted was predicted to decrease as a target five-year age-band for IPTc was shifted from children under 5 years into older ages, except at low transmission intensities.

CONCLUSIONS

Modelling can extend the information available by predicting impact and cost-effectiveness for scenarios, for outcomes and for multiple strategies where, for practical reasons, trials cannot be carried out. Both IPTi and IPTc are generally cost-effective but could be rendered cost-ineffective by characteristics of the setting, drug or implementation.

Interpreting malaria age-prevalence and incidence curves: a simulation study of the effects of different types of heterogeneity

Background

Individuals in a malaria endemic community differ from one another. Many of these differences, such as heterogeneities in transmission or treatment-seeking behaviour, affect malaria epidemiology. The different kinds of heterogeneity are likely to be correlated. Little is known about their impact on the shape of age-prevalence and incidence curves. In this study, the effects of heterogeneity in transmission, treatment-seeking and risk of co-morbidity were simulated.

Methods

Simple patterns of heterogeneity were incorporated into a comprehensive individual-based model of Plasmodium falciparum malaria epidemiology. The different types of heterogeneity were systematically simulated individually, and in independent and co-varying pairs. The effects on age-curves for parasite prevalence, uncomplicated and severe episodes, direct and indirect mortality and first-line treatments and hospital admissions were examined.

Results

Different heterogeneities affected different outcomes with large effects reserved for outcomes which are directly affected by the action of the heterogeneity rather than via feedback on acquired immunity or fever thresholds. Transmission heterogeneity affected the age-curves for all outcomes. The peak parasite prevalence was reduced and all age-incidence curves crossed those of the reference scenario with a lower incidence in younger children and higher in older age-groups. Heterogeneity in the probability of seeking treatment reduced the peak incidence of first-line treatment and hospital admissions. Heterogeneity in co-morbidity risk showed little overall effect, but high and low values cancelled out for outcomes directly affected by its action. Independently varying pairs of heterogeneities produced additive effects. More variable results were produced for co-varying heterogeneities, with striking differences compared to independent pairs for some outcomes which were affected by both heterogeneities individually.

Conclusions

Different kinds of heterogeneity both have different effects and affect different outcomes. Patterns of co-variation are also important. Alongside the absolute levels of different factors affecting age-curves, patterns of heterogeneity should be considered when parameterizing or validating models, interpreting data and inferring from one outcome to another.

Towards a comprehensive simulation model of malaria epidemiology and control

Planning of the control of Plasmodium falciparum malaria leads to a need for models of malaria epidemiology that provide realistic quantitative prediction of likely epidemiological outcomes of a wide range of control strategies. Predictions of the effects of control often ignore medium- and long-term dynamics. The complexities of the Plasmodium life-cycle, and of within-host dynamics, limit the applicability of conventional deterministic malaria models. We use individual-based stochastic simulations of malaria epidemiology to predict the impacts of interventions on infection, morbidity, mortality, health services use and costs. Individual infections are simulated by stochastic series of parasite densities, and naturally acquired immunity acts by reducing densities. Morbidity and mortality risks, and infectiousness to vectors, depend on parasite densities. The simulated infections are nested within simulations of individuals in human populations, and linked to models of interventions and health systems. We use numerous field datasets to optimise parameter estimates. By using a volunteer computing system we obtain the enormous computational power required for model fitting, sensitivity analysis, and exploration of many different intervention strategies. The project thus provides a general platform for comparing, fitting, and evaluating different model structures, and for quantitative prediction of effects of different interventions and integrated control programmes.

A model for natural immunity to asexual blood stages of Plasmodium falciparum malaria in endemic areas

Most mathematical models for acquired immunity to Plasmodium falciparum consider effects of immunity on duration of infection and infectiousness, but do not consider the most evident effect of immunity, which is to reduce parasite densities. Few attempts have been made to fit such models to field data. We propose a stochastic simulation model to predict the distributions of P. falciparum parasite densities in endemic areas, in which acquired immunity acts by reducing parasite densities. We have fitted this model to age-specific prevalence and geometric mean densities from settings in Ghana, Nigeria, and Tanzania. The model appears to reproduce reasonably well the parasitologic patterns seen in malariologic surveys in endemic areas and is appropriate for predicting the impact of interventions such as vaccination in the context of continual exposure to P. falciparum.

Mathematical modeling of the impact of malaria vaccines on the clinical epidemiology and natural history of Plasmodium falciparum malaria: Overview

We report a major project to develop integrated mathematical models for predicting the epidemiologic and economic effects of malaria vaccines both at the individual and population level. The project has developed models of the within-host dynamics of Plasmodium falciparum that have been fitted to parasite density profiles from malaria therapy patients, and simulations of P. falciparum epidemiology fitted to field malariologic datasets from a large ensemble of settings across Africa. The models provide a unique platform for predicting both the short- and long-term effects of malaria vaccines on the burden of disease, allowing for the temporal dynamics of effects on immunity and transmission. We discuss how the models can be used to obtain robust cost-effectiveness estimates for a wide range of malaria vaccines and vaccination delivery strategies in different eco-epidemiologic settings. This paper outlines for a non-mathematical audience the approach we have taken and its underlying rationale.

An epidemiologic model of severe morbidity and mortality caused by Plasmodium falciparum

The intensity of Plasmodium falciparum transmission has multifarious and sometimes counter-intuitive effects on age-specific rates of severe morbidity and mortality in endemic areas. This has led to conflicting speculations about the likely impact of malaria control interventions. We propose a quantitative framework to reconcile the various apparently contradictory observations relating morbidity and mortality rates to malaria transmission. Our model considers two sub-categories of severe malaria episodes. These comprise episodes with extremely high parasite densities in hosts with little previous exposure, and acute malaria episodes accompanied by co-morbidity or other risk factors enhancing susceptibility. In addition to direct malaria mortality from severe malaria episodes, the model also considers the enhanced risk of indirect mortality following acute episodes accompanied by co-morbidity after the parasites have been cleared. We fit this model to summaries of field data from endemic areas of Africa, and show that it can account for the observed age- and exposure-specific patterns of pediatric severe malaria and malaria-associated mortality in children. This model will allow us to make predictions of the long-term impact of potential malaria interventions. Predictions for children will be more reliable than those for older people because there is a paucity of epidemiologic studies of adults and adolescents.

An approach to model the costs and effects of case management of Plasmodium falciparum malaria in sub-saharan Africa

An important shortcoming of existing methods for estimating the cost-effectiveness of malaria control interventions is that the incidence of illness and transmission dynamics are assumed to be independent of the case management system. We have developed a model for case management and integrated it into a stochastic simulation of Plasmodium falciparum malaria dynamics. This allows us to predict the incidence of clinical episodes and of mortality while incorporating effects of case management on persistence of parasites and transmission. We make predictions for a range of different transmission intensities in sub-Saharan Africa and simulate a range of case management scenarios with different coverage rates. The model predicts that high treatment rates have a proportionately greater epidemiologic impact at low transmission levels. Further development is needed for models for health-seeking behavior and referral patterns. The current model is a first step towards useful predictions of the epidemiologic and economic consequences of introducing and/or scaling-up of malaria control interventions.

Predictions of the epidemiologic impact of introducing a pre-erythrocytic vaccine into the expanded program on immunization in sub-Saharan Africa

We predict the effects of introduction of a pre-erythrocytic vaccine against Plasmodium falciparum into a malaria-endemic population in Africa. We use a stochastic simulation model that includes components of transmission, parasitology, and clinical epidemiology of malaria and was validated using the results of field trials of the RTS,S/AS02A vaccine. The results suggest that vaccines with efficacy similar to that of RTS,S/AS02A have a substantial impact on malaria morbidity and mortality during the first decade after their introduction, but have negligible effects on malaria transmission at levels of endemicity typical for sub-Saharan Africa. The main benefits result from prevention of morbidity and mortality in the first years of life. Vaccines with very short half-life or low efficacy may have little overall effect on incidence of severe malaria. A similar approach can be used to make predictions for other strategies for deployment of the vaccine and to other types of malaria vaccines and interventions.