An efficient counting method for the colored triad census

The triad census is an important approach to understand local structure in network science, providing comprehensive assessments of the observed relational configurations between triples of actors in a network. However, researchers are often interested in combinations of relational and categorical nodal attributes. In this case, it is desirable to account for the label, or color, of the nodes in the triad census. In this paper, we describe an efficient algorithm for constructing the colored triad census, based, in part, on existing methods for the classic triad census. We evaluate the performance of the algorithm using empirical and simulated data for both undirected and directed graphs. The results of the simulation demonstrate that the proposed algorithm reduces computational time many-fold over the naive approach. We also apply the colored triad census to the Zachary karate club network dataset. We simultaneously show the efficiency of the algorithm, and a way to conduct a statistical test on the census by forming a null distribution from 1,000 realizations of a mixing-matrix conditioned graph and comparing the observed colored triad counts to the expected. From this, we demonstrate the method's utility in our discussion of results about homophily, heterophily, and bridging, simultaneously gained via the colored triad census. In sum, the proposed algorithm for the colored triad census brings novel utility to social network analysis in an efficient package

Rapid construction of insulated genetic circuits via synthetic sequence-guided isothermal assembly

In vitro recombination methods have enabled one-step construction of large DNA sequences from multiple parts. Although synthetic biological circuits can in principle be assembled in the same fashion, they typically contain repeated sequence elements such as standard promoters and terminators that interfere with homologous recombination. Here we use a computational approach to design synthetic, biologically inactive unique nucleotide sequences (UNSes) that facilitate accurate ordered assembly. Importantly, our designed UNSes make it possible to assemble parts with repeated terminator and insulator sequences, and thereby create insulated functional genetic circuits in bacteria and mammalian cells. Using UNS-guided assembly to construct repeating promoter-gene-terminator parts, we systematically varied gene expression to optimize production of a deoxychromoviridans biosynthetic pathway in Escherichia coli. We then used this system to construct complex eukaryotic AND-logic gates for genomic integration into embryonic stem cells. Construction was performed by using a standardized series of UNS-bearing BioBrick-compatible vectors, which enable modular assembly and facilitate reuse of individual parts. UNS-guided isothermal assembly is broadly applicable to the construction and optimization of genetic circuits and particularly those requiring tight insulation, such as complex biosynthetic pathways, sensors, counters and logic gates

Formaldehyde Exposure and Asthma in Children: A Systematic Review

Obj e c t i v e: Despite multiple published studies regarding the association between formaldehyde exposure and childhood asthma, a consistent association has not been identified. Here we report the results of a systematic review of published literature in order to provide a more comprehensive picture of this relationship. Data s o u r c e s: After a comprehensive literature search, we identified seven peer-reviewed studies providing quantitative results regarding the association between formaldehyde exposure and asthma in children. Studies were heterogeneous with respect to the definition of asthma (e.g., self-report, physician diagnosis). Most of the studies were cross-sectional

Agents of change: Comparing HIV-related risk behavior of people attending ART clinics in Dar es Salaam with members of their social networks.

The aim of the study is to compare sociodemographic characteristics, psychosocial factors, HIV knowledge and risk behaviors of people living with HIV (PLH) and their social network members (NMs) to inform HIV prevention programs that engage PLH as prevention educators in their communities. We compared baseline characteristics of PLH enrolled in an intervention to become HIV prevention Change Agents (CAs) (n = 458) and 602 NMs they recruited. CAs and NMs responded to questionnaires through a computer-driven interface with Audio Computer-Assisted Self Interview (ACASI) software. Although NMs scored higher on socio-economic status, self-esteem and general self-efficacy, they had lower HIV knowledge (AOR 1.5; 95% CI: 1.1-2.1), greater inconsistent condom use (AOR 3.2; 95% CI: 2.4-4.9), and recent experience as perpetrators of physical (AOR 2.5; 95% CI: 1.2-5.1) or sexual (AOR 4.1; 95% CI: 1.4-12.7) intimate partner violence; and as victims of physical (AOR 1.5; 95% CI: 1.0-2.3) or sexual (AOR 2.2; 95% CI: 1.3-3.8) forms of violence than CAs. Higher HIV knowledge and lower sexual risk behaviors among CAs suggest PLH's potential as communicators of HIV prevention information to NMs. CAs' training should also focus on improving self-esteem, general self-efficacy and social support to increase their potential effectiveness as HIV prevention educators and enhance their own overall health and well-being

Agents of change among people living with HIV and their social networks: stepped-wedge randomised controlled trial of the NAMWEZA intervention in Dar es Salaam, Tanzania.

INTRODUCTION: NAMWEZA is a novel intervention that focuses on preventing HIV and promoting sexual and reproductive health and rights by addressing underlying factors related to vulnerability of acquiring HIV, such as depression, intimate partner violence (IPV) and stigma. The goal of the study was to evaluate the effect of the NAMWEZA intervention on risk behaviour as well as factors potentially contributing to this vulnerability for people living with HIV and their network members. METHODS: A stepped-wedge randomised controlled trial was conducted from November 2010 to January 2014 among people living with HIV and their network members in Dar es Salaam, Tanzania. 458 people living with HIV were randomised within age/sex-specific strata to participate in the NAMWEZA intervention at three points in time. In addition, 602 members of their social networks completed the baseline interview. Intention-to-treat analysis was performed, including primary outcomes of uptake of HIV services, self-efficacy, self-esteem, HIV risk behaviour and IPV. RESULTS: For people living with HIV, a number of outcomes improved with the NAMWEZA intervention, including higher self-efficacy and related factors, as well as lower levels of depression and stigma. IPV reduced by 40% among women. Although reductions in HIV risk behaviour were not observed, an increase in access to HIV treatment was reported for network members (72% vs 94%, p=0.002). CONCLUSION: These results demonstrate the complexity of behavioural interventions in reducing the vulnerability of acquiring HIV, since it is possible to observe a broad range of different outcomes. This study indicates the importance of formally evaluating interventions so that policymakers can build on evidence-based approaches to advance the effectiveness of HIV prevention interventions. TRIAL REGISTRATION NUMBER: NCT01693458

High-Throughput High-Resolution Class I HLA Genotyping in East Africa

HLA, the most genetically diverse loci in the human genome, play a crucial role in host-pathogen interaction by mediating innate and adaptive cellular immune responses. A vast number of infectious diseases affect East Africa, including HIV/AIDS, malaria, and tuberculosis, but the HLA genetic diversity in this region remains incompletely described. This is a major obstacle for the design and evaluation of preventive vaccines. Available HLA typing techniques, that provide the 4-digit level resolution needed to interpret immune responses, lack sufficient throughput for large immunoepidemiological studies. Here we present a novel HLA typing assay bridging the gap between high resolution and high throughput. The assay is based on real-time PCR using sequence-specific primers (SSP) and can genotype carriers of the 49 most common East African class I HLA-A, -B, and -C alleles, at the 4-digit level. Using a validation panel of 175 samples from Kampala, Uganda, previously defined by sequence-based typing, the new assay performed with 100% sensitivity and specificity. The assay was also implemented to define the HLA genetic complexity of a previously uncharacterized Tanzanian population, demonstrating its inclusion in the major East African genetic cluster. The availability of genotyping tools with this capacity will be extremely useful in the identification of correlates of immune protection and the evaluation of candidate vaccine efficacy

The social and biological effects of patient-patient co-presence on health in hospitals using electronic medical records

Co-presence, defined as two people being physically proximate to one another, is a ubiquitous and important phenomenon that remains understudied. There is strong reason to believe that co-presence may affect health, but it is likely that these effects are relatively small. Because of this, relatively large sample sizes are needed to reliably detect these effects, and the data to test such hypotheses has only recently become widely-available. In this thesis, I use electronic medical records and hospital administrative data to assess how patient-patient co-presence in a health care system may affect patient health outcomes. In Chapter 3, I examine the social effects of co-presence on 5-year survival in a group of 4,791 chemotherapy patients. Because no metric for measuring co-presence precisely addressed all the nuances of hospital administrative data, I create a method to detect when patients are co-present more often than expected by chance, terming this consistent co-presence. Consistent co-presence thus allows me to subset co-presence to only that which is likely systematic enough to elicit social influence. Using this, I construct a consistent co-presence network. I then model 5-year survival on 1) whether a patient had any consistent co-presence in the network, 2) the number of patients who survived with whom one was consistently co-present, and 3) and likewise the number patients who did not survive with whom one was consistently co-present. I find that being consistently co-present with at least one other patient increased oneâs likelihood of 5-year survival compared to being consistently co-present with no one. Being consistently co-present with patients who survived increased oneâs likelihood of 5-year survival, and being consistently co-present with patients who did not survive decreased oneâs likelihood of 5-year survival. In Chapter 4, I assess the ability to predict subsequent infection based on the number of hours a patient spends co-present with another patient suspected of infection. Across five nosocomial infections, I find that this tool has a sensitivity from 0.95 to 1.00, and a specificity from 0.90 to 1.00. If this metric were put in place prospectively, I estimate that it would lead to detecting infections between 4 and 32 hours earlier than the current standard operating procedure. I then use this information, along with biomarker information to detect subclinical infections in Chapter 5. Subclinical infections are those where the bacterial or viral load is below a testâs threshold, meaning these infections go undiagnosed. I use a random forest model to perform the classification, and a variety of regression models to examine the validity of said model. I then show that subclinical infections have negative effects both on the affected patients and on the nosocomial disease dynamics, leading to increased infectious outbreak sizes. As a supplement to support my analyses in Chapter 5, I develop an efficient algorithm to be used in social networks analysis for the colored triad census in Appendix A. I apply this to the outbreak networks observed in Chapter 5 to understand the patterns of connections of subclinically-infected patients. In sum, I find that co-presence is a useful and informative construct which allows us to better understand patient health in hospitals. Additionally, the outcomes observed here are not exclusive to the health care setting; social influence and infectious disease spread both occur outside of hospitals. As a result, this research opens up a wide variety of future work, including studying these effects in more detail with hospitals and using similar data sources to examine these effects in other populations and settings.</p