Bulletin of the World Health Organization

Intermittent preventive treatment for malaria in infants: a decision-support tool for sub-Saharan Africa

Ilona Carneiro, Lucy Smith, Amanda Ross, Arantxa Roca-Feltrer, Brian Greenwood, Joanna Armstrong Schellenberg, Thomas Smith & David Schellenberg

Objective

To develop a decision-support tool to help policy-makers in sub-Saharan Africa assess whether intermittent preventive treatment in infants (IPTi) would be effective for local malaria control.

Methods

An algorithm for predicting the effect of IPTi was developed using two approaches. First, study data on the age patterns of clinical cases of Plasmodium falciparum malaria, hospital admissions for infection with malaria parasites and malaria-associated death for different levels of malaria transmission intensity and seasonality were used to estimate the percentage of cases of these outcomes that would occur in children aged < 10 years targeted by IPTi. Second, a previously developed stochastic mathematical model of IPTi was used to predict the number of cases likely to be averted by implementing IPTi under different epidemiological conditions. The decision-support tool uses the data from these two approaches that are most relevant to the context specified by the user.

Findings

Findings from the two approaches indicated that the percentage of cases targeted by IPTi increases with the severity of the malaria outcome and with transmission intensity. The decision-support tool, available on the Internet, provides estimates of the percentage of malaria-associated deaths, hospitalizations and clinical cases that will be targeted by IPTi in a specified context and of the number of these outcomes that could be averted.

Conclusion

The effectiveness of IPTi varies with malaria transmission intensity and seasonality. Deciding where to implement IPTi must take into account the local epidemiology of malaria. The Internet-based decision-support tool described here predicts the likely effectiveness of IPTi under a wide range of epidemiological conditions.

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