Although highly active antiretroviral therapy (HAART) in the form of triple combinations of drugs including protease inhibitors can reduce the plasma viral load of some HIV-1-infected individuals to undetectable levels, it is unclear what the effects of these regimens are on latently infected CD4⁺T cells and what role these cells play in the persistence of HIV-1 infection in individuals receiving such treatment. The present study demonstrates that highly purified CD4⁺T cells from 13 of 13 patients receiving HAART with an average treatment time of 10 months and with undetectable (<500 copies HIV RNA/ml) plasma viremia by a commonly used bDNA assay carried integrated proviral DNA and were capable of producing infectious virus upon cellular activationin vitro. Phenotypic analysis of HIV-1 produced by activation of latently infected CD4⁺T cells revealed the presence in some patients of syncytium-inducing virus. In addition, the presence of unintegrated HIV-1 DNA in infected resting CD4⁺T cells from patients receiving HAART, even those with undetectable plasma viremia, suggests persistent active virus replicationin vivo.

We discuss properties of infection processes on scale-free networks, relating them to the node-connectivity distribution that characterizes the network. Considering the epidemiologically important case of a disease that confers permanent immunity upon recovery, we derive analytic expressions for the final size of an epidemic in an infinite closed population and for the dependence of infection probability on an individual’s degree of connectivity within the population. As in an earlier study [R. Pastor-Satorras and A. Vesipignani, Phys. Rev. Lett. 86, 3200 (2001); Phys. Rev. E. 63, 006117 (2001)] for an infection that did not confer immunity upon recovery, the epidemic process—in contrast with many traditional epidemiological models—does not exhibit threshold behavior, and we demonstrate that this is a consequence of the extreme heterogeneity in the connectivity distribution of a scale-free network. Finally, we discuss effects that arise from finite population sizes, showing that networks of finite size do exhibit threshold effects: infections cannot spread for arbitrarily low transmission probabilities.

The spread of diseases in human and other populations can be described in terms of networks, where individuals are represented by nodes and modes of contact by edges. Similar models can be applied to the spread of viruses on the Internet. In their Perspective, [Lloyd and May][1] discuss the similarities and differences between the dynamics of computer viruses and infections of human and other populations. [1]: http://www.sciencemag.org/cgi/content/full/292/5520/1316

Mathematical models of mosquito-borne pathogen transmission originated in the early twentieth century to provide insights into how to most effectively combat malaria. The foundations of the Ross–Macdonald theory were established by 1970. Since then, there has been a growing interest in reducing the public health burden of mosquito-borne pathogens and an expanding use of models to guide their control. To assess how theory has changed to confront evolving public health challenges, we compiled a bibliography of 325 publications from 1970 through 2010 that included at least one mathematical model of mosquito-borne pathogen transmission and then used a 79-part questionnaire to classify each of 388 associated models according to its biological assumptions. As a composite measure to interpret the multidimensional results of our survey, we assigned a numerical value to each model that measured its similarity to 15 core assumptions of the Ross–Macdonald model. Although the analysis illustrated a growing acknowledgement of geographical, ecological and epidemiological complexities in modelling transmission, most models during the past 40 years closely resemble the Ross–Macdonald model. Modern theory would benefit from an expansion around the concepts of heterogeneous mosquito biting, poorly mixed mosquito-host encounters, spatial heterogeneity and temporal variation in the transmission process.