Population dynamics of a pathogen: the conundrum of vivax malaria

Building a mathematical model of population dynamics of pathogens within their host involves considerations of factors similar to those in ecology, as pathogens can prey on cells in the host. But within the multicellular host, attacked cell types are integrated with other cellular systems, which in turn intervene in the infection. For example, immune responses attempt to sense and then eliminate or contain pathogens, and homeostatic mechanisms try to compensate for cell loss. This review focuses on modeling applied to malarias, diseases caused by single-cell eukaryote parasites that infect red blood cells, with special concern given to vivax malaria, a disease often thought to be benign (if sometimes incapacitating) because the parasite only attacks a small proportion of red blood cells, the very youngest ones. However, I will use mathematical modeling to argue that depletion of this pool of red blood cells can be disastrous to the host if growth of the parasite is not vigorously check by host immune responses. Also, modeling can elucidate aspects of new field observations that indicate that vivax malaria is more dangerous than previously thought

Modeling denitrification in aquatic sediments

Author Posting. © The Author(s), 2008. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Biogeochemistry 93 (2009): 159-178, doi:10.1007/s10533-008-9270-z.Sediment denitrification is a major pathway of fixed nitrogen loss from aquatic systems. Due to technical difficulties in measuring this process and its spatial and temporal variability, estimates of local, regional and global denitrification have to rely on a combination of measurements and models. Here we review approaches to describing denitrification in aquatic sediments, ranging from mechanistic diagenetic models to empirical parameterizations of nitrogen fluxes across the sediment-water interface. We also present a compilation of denitrification measurements and ancillary data for different aquatic systems, ranging from freshwater to marine. Based on this data compilation we reevaluate published parameterizations of denitrification. We recommend that future models of denitrification use (1) a combination of mechanistic diagenetic models and measurements where bottom waters are temporally hypoxic or anoxic, and (2) the much simpler correlations between denitrification and sediment oxygen consumption for oxic bottom waters. For our data set, inclusion of bottom water oxygen and nitrate concentrations in a multivariate regression did not improve the statistical fit.Financial support for AEG to work on the manuscript came from NSF NSF-DEB-0423565. KF, DB and DDT acknowledge support from NOAA CHRP grant NA07NOS4780191