Avraam, D. | bioRxiv Science

bioRxiv2022

dsSurvival: Privacy preserving survival models for federated individual patient meta-analysis in DataSHIELD

ObjectiveAchieving sufficient statistical power in a survival analysis usually requires large amounts of data from different sites. Sensitivity of individual-level data, ethical and practical considerations regarding data sharing across institutions could be a potential challenge for achieving this added power. Hence we implemented a federated meta-analysis approach of survival models in DataSHIELD, where only anonymous aggregated data are shared across institutions, while simultaneously allowing for exploratory, interactive modelling. In this case, meta-analysis techniques to combine analysis results from each site are a solution, but an analytic workflow involving local analysis undertaken at individual studies hinders exploration. Thus, the aim is to provide a framework for performing meta-analysis of Cox regression models across institutions without manual analysis steps for the data providers. ResultsWe introduce a package (dsSurvival) which allows privacy preserving meta-analysis of survival models, including the calculation of hazard ratios. Our tool can be of great use in biomedical research where there is a need for building survival models and there are privacy concerns about sharing data.

bioinformatics↗

bioRxiv2019

Hand-hygiene mitigation strategies against globaldisease spreading through the air transportationnetwork

Hand hygiene is considered as an efficient and cost-effective way to limit the spread of diseases and, as such, it is recommended by both the World Health Organization (WHO) and the Centres for Disease Control and Prevention (CDC). While the effect of hand washing on individual transmissibility of a disease has been studied through medical and public-health research, its potential as a mitigation strategy against a global pandemic has not been fully explored yet. In this study, we investigate contagion dynamics through the world air transportation network and analyze the impact of hand-hygiene behavioural changes of airport population against the spread of infectious diseases worldwide. Using a granular dataset of the world air transportation traffic, we build a detailed individual mobility model that controls for the correlated and recurrent nature of human travel and the waiting-time distributions of individuals at different locations. We perform a Monte-Carlo simulation study to assess the impact of different hand-washing mitigation strategies at the early stages of a global epidemic. From the simulation results we find that increasing the hand cleanliness homogeneously at all airports in the world can inhibit the impact of a potential pandemic by 24 to 69%. By quantifying and ranking the contribution of the different airports to the mitigation of an epidemic outbreak, we identify ten key airports at the core of a cost-optimal deployment of the hand-washing strategy: increasing the engagement rate at those locations alone could potentially reduce a world pandemic by 8 to 37%. This research provides evidence of the effectiveness of hand hygiene in airports on the global spread of infectious diseases, and has important implications for the way public-health policymakers may design new effective strategies to enhance hand hygiene in airports through behavioral changes.

epidemiology↗