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Estimating malaria transmission through mathematical models

Stuckey, Erin M., Smith, Thomas A., Chitnis, Nakul
Trends in parasitology 2013 v.29 no.10 pp. 477-482
malaria, mathematical models, parasitology, public health, seasonal variation
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.