Estimation of the HIV-1 backward mutation rate from transmitted drug-resistant strains.

One of the serious threats facing the administration of antiretroviral therapy to human immunodeficiency virus (HIV-1) infected patients is the reported increasing prevalence of transmitted drug resistance. However, given that HIV-1 drug-resistant strains are often less fit than the wild-type strains, it is expected that drug-resistant strains that are present during the primary phase of the HIV-1 infection are replaced by the fitter wild-type strains. This replacement of HIV-1 resistant mutations involves the emergence of wild-type strains by a process of backward mutation. How quickly the replacement happens is dependent on the class of HIV-1 mutation group. We estimate the backward mutation rates and relative fitness of various mutational groups known to confer HIV-1 drug resistance. We do this by fitting a stochastic model to data for individuals who were originally infected by an HIV-1 strain carrying any one of the known drug resistance-conferring mutations and observed over a period of time to see whether the resistant strain is replaced. To do this, we seek a distribution, generated from simulations of the stochastic model, that best describes the observed (clinical data) replacement times of a given mutation. We found that Lamivudine/Emtricitabine-associated mutations have a distinctly higher, backward mutation rate and low relative fitness compared to the other classes (as has been reported before) while protease inhibitors-associated mutations have a slower backward mutation rate and high relative fitness. For the other mutation classes, we found more uncertainty in their estimates.

Measuring social networks in British primary schools through scientific engagement.

Primary schools constitute a key risk group for the transmission of infectious diseases, concentrating great numbers of immunologically naive individuals at high densities. Despite this, very little is known about the social patterns of mixing within a school, which are likely to contribute to disease transmission. In this study, we present a novel approach where scientific engagement was used as a tool to access school populations and measure social networks between young (4-11 years) children. By embedding our research project within enrichment activities to older secondary school (13-15) children, we could exploit the existing links between schools to achieve a high response rate for our study population (around 90% in most schools). Social contacts of primary school children were measured through self-reporting based on a questionnaire design, and analysed using the techniques of social network analysis. We find evidence of marked social structure and gender assortativity within and between classrooms in the same school. These patterns have been previously reported in smaller studies, but to our knowledge no study has attempted to exhaustively sample entire school populations. Our innovative approach facilitates access to a vitally important (but difficult to sample) epidemiological sub-group. It provides a model whereby scientific communication can be used to enhance, rather than merely complement, the outcomes of research.