Estimation of heterogeneity in malaria transmission by stochastic modelling of apparent deviations from mass action kinetics

Malaria Journal
T Smith

Abstract

Quantifying heterogeneity in malaria transmission is a prerequisite for accurate predictive mathematical models, but the variance in field measurements of exposure overestimates true micro-heterogeneity because it is inflated to an uncertain extent by sampling variation. Descriptions of field data also suggest that the rate of Plasmodium falciparum infection is not proportional to the intensity of challenge by infectious vectors. This appears to violate the principle of mass action that is implied by malaria biology. Micro-heterogeneity may be the reason for this anomaly. It is proposed that the level of micro-heterogeneity can be estimated from statistical models that estimate the amount of variation in transmission most compatible with a mass-action model for the relationship of infection to exposure. The relationship between the entomological inoculation rate (EIR) for falciparum malaria and infection risk was reanalysed using published data for cohorts of children in Saradidi (western Kenya). Infection risk was treated as binomially distributed, and measurement-error (Poisson and negative binomial) models were considered for the EIR. Models were fitted using Bayesian Markov chain Monte Carlo algorithms and model fit compare...Continue Reading

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Citations

Jul 23, 2011·Malaria Journal·Sandip MandalSomdatta Sinha
Dec 22, 2011·Malaria Journal·Peter W GethingSimon I Hay
May 2, 2009·Malaria Journal·David L Smith, Simon I Hay
Dec 2, 2015·Malaria Journal·Milinda Lakkam, Lawrence M Wein
Nov 4, 2010·Nature Communications·David L SmithSimon I Hay
Sep 4, 2019·Nature Communications·Laura CooperDavid L Smith

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