title: Estimating malaria transmission through mathematical models.
abstract: Evaluating the effectiveness of malaria control interventions on the basis of their impact on transmission is increasingly important as countries move from malaria control to pre-elimination programs. Mathematical modeling can examine relationships between malaria indicators, allowing translation of easily measured data into measures of transmission, and addressing key concerns with traditional methods for quantifying transmission. Simulations show these indicators are statistically correlated, allowing direct comparisons of malaria transmission using data collected using different methods across a range of transmission intensities and seasonal patterns. Results from such models can provide public health officials with accurate estimates of transmission, by seasonal pattern, that are necessary for assessing and tailoring malaria control and elimination programs to specific settings.
authors.affiliation: Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Socinstrasse 57, Postfach, 4002 Basel, Switzerland; University of Basel, Petersplatz 1, 4003 Basel, Switzerland. Electronic address: erin.stuckey@unibas.ch.
authors.forename: Erin M
authors.initials: EM
authors.lastname: Stuckey
authors.forename: Thomas A
authors.initials: TA
authors.lastname: Smith
authors.forename: Nakul
authors.initials: N
authors.lastname: Chitnis
mesh_terms: D000818:Animals; D003198:Computer Simulation; D009033:Culicidae / Q000469:parasitology; D006801:Humans; D007303:Insect Vectors / Q000469:parasitology; D016778:Malaria, Falciparum / Q000453:epidemiology / Q000517:prevention & control / Q000635:transmission*; D008962:Models, Theoretical; D010963:Plasmodium falciparum / Q000469:parasitology*; D012621:Seasons
keywords: OpenMalaria; malaria; mathematical modeling; seasonality; transmission