Publications by authors named "Arran Schlosberg"

Background: Social distancing have been widely used to mitigate community spread of SARS-CoV-2. We sought to quantify the impact of COVID-19 social distancing policies across 27 European counties in spring 2020 on population mobility and the subsequent trajectory of disease.

Methods: We obtained data on national social distancing policies from the Oxford COVID-19 Government Response Tracker and aggregated and anonymized mobility data from Google.

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Social distancing remains an important strategy to combat the COVID-19 pandemic in the United States. However, the impacts of specific state-level policies on mobility and subsequent COVID-19 case trajectories have not been completely quantified. Using anonymized and aggregated mobility data from opted-in Google users, we found that state-level emergency declarations resulted in a 9.

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Background: Until recently, determining penetrance required large observational cohort studies. Data from the Exome Aggregate Consortium (ExAC) allows a Bayesian approach to calculate penetrance, in that population frequencies of pathogenic germline variants should be inversely proportional to their penetrance for disease. We tested this hypothesis using data from two cohorts for succinate dehydrogenase subunits A, B and C () genetic variants associated with hereditary pheochromocytoma/paraganglioma (PC/PGL).

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The advent of next-generation sequencing (NGS) brings with it a need to manage large volumes of patient data in a manner that is compliant with both privacy laws and long-term archival needs. Outside of the realm of genomics there is a need in the broader medical community to store data, and although radiology aside the volume may be less than that of NGS, the concepts discussed herein are similarly relevant. The relation of so-called "privacy principles" to data protection and cryptographic techniques is explored with regards to the archival and backup storage of health data in Australia, and an example implementation of secure management of genomic archives is proposed with regards to this relation.

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Improvements in speed and cost of genome sequencing are resulting in increasing numbers of novel non-synonymous single nucleotide polymorphisms (nsSNPs) in genes known to be associated with disease. The large number of nsSNPs makes laboratory-based classification infeasible and familial co-segregation with disease is not always possible. In-silico methods for classification or triage are thus utilised.

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