Brushtail possum (Trichosurus vulpecula) social interactions and their implications for bovine tuberculosis epidemiology

The brushtail possum is the main reservoir of bovine tuberculosis in New Zealand. Disease prevalence is generally higher in males than in females. This has conventionally been assumed due to greater infection rates of males, but recent work has raised the hypothesis that it may instead be driven by survival differences. With bovine tuberculosis transmission among possums most likely occurring between individuals in close proximity, here we analyse social networks built on data from wild possums collared with contact loggers inhabiting a native New Zealand forest, to investigate whether there is mechanistic support for higher male infection rates. Our results revealed that adult female possums were generally just as connected with adult male possums as other adult males are, with male-female connection patterns not being significantly different. This result suggest that the new 'survivorship' hypothesis for the sex bias is more likely than the conventional 'infection rate' hypothesis. © 2018 Copyright 2018 by Koninklijke Brill NV, Leiden, The Netherlands

A CHecklist for statistical Assessment of Medical Papers (the CHAMP statement): explanation and elaboration

Misuse of statistics in medical and sports science research is common and may lead to detrimental consequences to healthcare. Many authors, editors and peer reviewers of medical papers will not have expert knowledge of statistics or may be unconvinced about the importance of applying correct statistics in medical research. Although there are guidelines on reporting statistics in medical papers, a checklist on the more general and commonly seen aspects of statistics to assess when peer-reviewing an article is needed. In this article, we propose a CHecklist for statistical Assessment of Medical Papers (CHAMP) comprising 30 items related to the design and conduct, data analysis, reporting and presentation, and interpretation of a research paper. While CHAMP is primarily aimed at editors and peer reviewers during the statistical assessment of a medical paper, we believe it will serve as a useful reference to improve authors’ and readers’ practice in their use of statistics in medical research. We strongly encourage editors and peer reviewers to consult CHAMP when assessing manuscripts for potential publication. Authors also may apply CHAMP to ensure the validity of their statistical approach and reporting of medical research, and readers may consider using CHAMP to enhance their statistical assessment of a paper

CHecklist for statistical Assessment of Medical Papers: the CHAMP statement

Misuse of statistics in medical and sports science research is common and may lead to detrimental consequences to healthcare. Many authors, editors and peer reviewers of medical papers will not have expert knowledge of statistics or may be unconvinced about the importance of applying correct statistics in medical research. Although there are guidelines on reporting statistics in medical papers, a checklist on the more general and commonly seen aspects of statistics to assess when peer-reviewing an article is needed. In this article, we propose a CHecklist for statistical Assessment of Medical Papers (CHAMP) comprising 30 items related to the design and conduct, data analysis, reporting and presentation, and interpretation of a research paper. While CHAMP is primarily aimed at editors and peer reviewers during the statistical assessment of a medical paper, we believe it will serve as a useful reference to improve authors’ and readers’ practice in their use of statistics in medical research. We strongly encourage editors and peer reviewers to consult CHAMP when assessing manuscripts for potential publication. Authors also may apply CHAMP to ensure the validity of their statistical approach and reporting of medical research, and readers may consider using CHAMP to enhance their statistical assessment of a paper

[Accepted Manuscript] Cash vs. food assistance to improve adherence to antiretroviral therapy among HIV-infected adults in Tanzania: a randomized trial.

We evaluated the effectiveness of short-term cash and food assistance to improve adherence to antiretroviral therapy (ART) and retention in care among people living with HIV in Tanzania. At three clinics, 805 participants were randomized to three groups in a 3 : 3 : 1 ratio, stratified by site : nutrition assessment and counseling (NAC) and cash transfers (∼$11/month, n = 347), NAC and food baskets (n = 345), and NAC-only (comparison group, n = 113, clinicaltrials.gov NCT01957917). Eligible people living with HIV were at least 18 years, initiated ART 90 days or less prior, and food insecure. Cash or food was provided for 6 or less consecutive months, conditional on visit attendance. The primary outcome was medication possession ratio (MPR) at least 95% at 6 months. Secondary outcomes were appointment attendance and loss to follow-up (LTFU) at 6 and 12 months. The primary intent-to-treat analysis included 800 participants. Achievement of MPR at least 95% at 6 months was higher in the NAC + cash group compared with NAC-only (85.0 vs. 63.4%), a 21.6 percentage point difference [95% confidence interval (CI): 9.8, 33.4, P < 0.01]. MPR at least 95% was also significantly higher in the NAC + food group vs. NAC-only (difference = 15.8, 95% CI: 3.8, 27.9, P < 0.01). When directly compared, MPR at least 95% was similar in the NAC + cash and NAC + food groups (difference = 5.7, 95% CI: -1.2, 12.7, P = 0.15). Compared with NAC-only, appointment attendance and LTFU were significantly higher in both the NAC + cash and NAC + food groups at 6 months. At 12 months, the effect of NAC + cash, but not NAC + food, on MPR at least 95% and retention was sustained. Short-term conditional cash and food assistance improves ART possession and appointment attendance and reduces LTFU among food-insecure ART initiates in Tanzania

A stochastic evolutionary model generating a mixture of exponential distributions

Recent interest in human dynamics has stimulated the investigation of the stochastic processes that explain human behaviour in various contexts, such as mobile phone networks and social media. In this paper, we extend the stochastic urn-based model proposed in \cite{FENN15} so that it can generate mixture models, in particular, a mixture of exponential distributions. The model is designed to capture the dynamics of survival analysis, traditionally employed in clinical trials, reliability analysis in engineering, and more recently in the analysis of large data sets recording human dynamics. The mixture modelling approach, which is relatively simple and well understood, is very effective in capturing heterogeneity in data. We provide empirical evidence for the validity of the model, using a data set of popular search engine queries collected over a period of 114 months. We show that the survival function of these queries is closely matched by the exponential mixture solution for our model