title: Intermittent preventive treatment for malaria in infants: a decision-support tool for sub-Saharan Africa.
abstract: 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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, England. ilona.carneiro@lshtm.ac.uk
authors.forename: Ilona
authors.initials: I
authors.lastname: Carneiro
authors.forename: Lucy
authors.initials: L
authors.lastname: Smith
authors.forename: Amanda
authors.initials: A
authors.lastname: Ross
authors.forename: Arantxa
authors.initials: A
authors.lastname: Roca-Feltrer
authors.forename: Brian
authors.initials: B
authors.lastname: Greenwood
authors.forename: Joanna Armstrong
authors.initials: JA
authors.lastname: Schellenberg
authors.forename: Thomas
authors.initials: T
authors.lastname: Smith
authors.forename: David
authors.initials: D
authors.lastname: Schellenberg
mesh_terms: D017954:Africa South of the Sahara / Q000453:epidemiology; D017677:Age Distribution; D000465:Algorithms; D000962:Antimalarials / Q000008:administration & dosage / Q000627:therapeutic use*; D002648:Child; D002675:Child, Preschool; D016001:Confidence Intervals; D003661:Decision Support Techniques; D004812:Epidemiologic Methods; D005260:Female; D006291:Health Policy; D006760:Hospitalization; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008288:Malaria / Q000453:epidemiology / Q000401:mortality / Q000517:prevention & control*; D008297:Male; D008962:Models, Theoretical; D010965:Plasmodium malariae / Q000302:isolation & purification*; D013269:Stochastic Processes; D013997:Time Factors
chemical_list: D000962:Antimalarials