Data reduction and data mining framework for digital forensic evidence: storage, intelligence, review and archive

With the volume of digital forensic evidence rapidly increasing, this paper proposes a data reduction and data mining framework that incorporates a process of reducing data volume by focusing on a subset of information. Foreword The volume of digital forensic evidence is rapidly increasing, leading to large backlogs. In this paper, a Digital Forensic Data Reduction and Data Mining Framework is proposed. Initial research with sample data from South Australia Police Electronic Crime Section and Digital Corpora Forensic Images using the proposed framework resulted in significant reduction in the storage requirements—the reduced subset is only 0.196 percent and 0.75 percent respectively of the original data volume. The framework outlined is not suggested to replace full analysis, but serves to provide a rapid triage, collection, intelligence analysis, review and storage methodology to support the various stages of digital forensic examinations. Agencies that can undertake rapid assessment of seized data can more effectively target specific criminal matters. The framework may also provide a greater potential intelligence gain from analysis of current and historical data in a timely manner, and the ability to undertake research of trends over time

Grain Residuals and Time Requirements for Combine Cleaning

Emerging identity-preserved grain markets depend on avoidance of commingling grain at harvest. Knowledge of where grain resides in a combine, cleaning labor requirements, and resulting purity levels would assist producers. Measurements were made of grain and other material residing in different areas of rotary- and cylinder-type combines in replicated clean-outs during corn and soybean harvest and also in preliminary clean-outs during oat harvest. Concentration of the prior (i.e., commingled) grain was measured in the first grain harvested of the subsequent crop

Classification of animal dive tracks via automatic landmarking, principal components analysis and clustering

The BRS study was financially supported by the United States (U.S.) Office of Naval Research (www.onr.navy.mil) Grants N00014‐07‐10988, N00014‐07‐11023, N00014‐08‐10990; the U.S. Strategic Environmental Research and Development Program (www.serdp.org) Grant SI‐1539, the Environmental Readiness Division of the U.S. Navy (http://www.navy.mil/local/n45/), the U.S. Chief of Naval Operations Submarine Warfare Division (Undersea Surveillance), the U.S. National Oceanic and Atmospheric Administration (National Marine Fisheries Service, Office of Science and Technology) (http://www.st.nmfs.noaa.gov/), U.S. National Oceanic and Atmospheric Administration Ocean Acoustics Program (http://www.nmfs.noaa.gov/pr/acoustics/), and the Joint Industry Program on Sound and Marine Life of the International Association of Oil and Gas Producers (www.soundandmarinelife.org).The behaviour of animals and their interactions with the environment can be inferred by tracking their movement. For this reason, biologgers are an important source of ecological data, but analysing the shape of the tracks they record is difficult. In this paper we present a technique for automatically determining landmarks that can be used to analyse the shape of animal tracks. The approach uses a parametric version of the SALSA algorithm to fit regression splines to 1‐dimensional curves in N dimensions (in practice N = 2 or 3). The knots of these splines are used as landmarks in a subsequent Principal Components Analysis, and the dives classified via agglomerative clustering. We demonstrate the efficacy of this algorithm on simulated 2‐dimensional dive data, and apply our method to real 3‐dimensional whale dive data from the Behavioral Response Study (BRS) in the Bahamas. The BRS is a series of experiments to quantify shifts in behavior due to SONAR. Our analysis of 3‐dimensional track data supports an alteration in the dive behavior post‐ensonification.Publisher PDFPeer reviewe

Nosocomial or not? A combined epidemiological and genomic investigation to understand hospital-acquired COVID-19 infection on an elderly care ward

Background: COVID-19 has the potential to cause outbreaks in hospitals. Given the comorbid and elderly cohort of patients hospitalized, hospital-acquired COVID-19 infection is often fatal. Pathogen genome sequencing is becoming increasingly important in infection prevention and control (IPC). Aim: To inform the understanding of in-hospital SARS-CoV-2 transmission in order to improve IPC practices and to inform the future development of virological testing for IPC. Methods: Patients detected COVID-19 positive by polymerase chain reaction on Ward A in April and May 2020 were included with contact tracing to identify other potential cases. Genome sequencing was undertaken for a subgroup of cases. Epidemiological, genomic, and cluster analyses were performed to describe the epidemiology and to identify factors contributing to the outbreak. Findings: Fourteen cases were identified on Ward A. Contact tracing identified 16 further patient cases; in addition, eight healthcare workers (HCWs) were identified as being COVID-19 positive through a round of asymptomatic testing. Genome sequencing of 16 of these cases identified viral genomes differing by two single nucleotide polymorphisms or fewer, with further cluster analysis identifying two groups of infection (a five-person group and a six-person group). Conclusion: Despite the temporal relationship of cases, genome sequencing identified that not all cases shared transmission events. However, 11 samples were found to be closely related and these likely represented in-hospital transmission. This included three HCWs, thereby confirming transmission between patients and HCWs

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

Exponential growth, high prevalence of SARS-CoV-2, and vaccine effectiveness associated with the Delta variant

SARS-CoV-2 infections were rising during early summer 2021 in many countries associated with the Delta variant. We assessed RT-PCR swab-positivity in the REal-time Assessment of Community Transmission-1 (REACT-1) study in England. We observed sustained exponential growth with average doubling time (June-July 2021) of 25 days driven by complete replacement of Alpha variant by Delta, and by high prevalence at younger less-vaccinated ages. Unvaccinated people were three times more likely than double-vaccinated people to test positive. However, after adjusting for age and other variables, vaccine effectiveness for double-vaccinated people was estimated at between ~50% and ~60% during this period in England. Increased social mixing in the presence of Delta had the potential to generate sustained growth in infections, even at high levels of vaccination

Investigation of hospital discharge cases and SARS-CoV-2 introduction into Lothian care homes

Background The first epidemic wave of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Scotland resulted in high case numbers and mortality in care homes. In Lothian, over one-third of care homes reported an outbreak, while there was limited testing of hospital patients discharged to care homes. Aim To investigate patients discharged from hospitals as a source of SARS-CoV-2 introduction into care homes during the first epidemic wave. Methods A clinical review was performed for all patients discharges from hospitals to care homes from 1st March 2020 to 31st May 2020. Episodes were ruled out based on coronavirus disease 2019 (COVID-19) test history, clinical assessment at discharge, whole-genome sequencing (WGS) data and an infectious period of 14 days. Clinical samples were processed for WGS, and consensus genomes generated were used for analysis using Cluster Investigation and Virus Epidemiological Tool software. Patient timelines were obtained using electronic hospital records. Findings In total, 787 patients discharged from hospitals to care homes were identified. Of these, 776 (99%) were ruled out for subsequent introduction of SARS-CoV-2 into care homes. However, for 10 episodes, the results were inconclusive as there was low genomic diversity in consensus genomes or no sequencing data were available. Only one discharge episode had a genomic, time and location link to positive cases during hospital admission, leading to 10 positive cases in their care home. Conclusion The majority of patients discharged from hospitals were ruled out for introduction of SARS-CoV-2 into care homes, highlighting the importance of screening all new admissions when faced with a novel emerging virus and no available vaccine

SARS-CoV-2 Omicron is an immune escape variant with an altered cell entry pathway

Vaccines based on the spike protein of SARS-CoV-2 are a cornerstone of the public health response to COVID-19. The emergence of hypermutated, increasingly transmissible variants of concern (VOCs) threaten this strategy. Omicron (B.1.1.529), the fifth VOC to be described, harbours multiple amino acid mutations in spike, half of which lie within the receptor-binding domain. Here we demonstrate substantial evasion of neutralization by Omicron BA.1 and BA.2 variants in vitro using sera from individuals vaccinated with ChAdOx1, BNT162b2 and mRNA-1273. These data were mirrored by a substantial reduction in real-world vaccine effectiveness that was partially restored by booster vaccination. The Omicron variants BA.1 and BA.2 did not induce cell syncytia in vitro and favoured a TMPRSS2-independent endosomal entry pathway, these phenotypes mapping to distinct regions of the spike protein. Impaired cell fusion was determined by the receptor-binding domain, while endosomal entry mapped to the S2 domain. Such marked changes in antigenicity and replicative biology may underlie the rapid global spread and altered pathogenicity of the Omicron variant

Hospital admission and emergency care attendance risk for SARS-CoV-2 delta (B.1.617.2) compared with alpha (B.1.1.7) variants of concern: a cohort study

Background: The SARS-CoV-2 delta (B.1.617.2) variant was first detected in England in March, 2021. It has since rapidly become the predominant lineage, owing to high transmissibility. It is suspected that the delta variant is associated with more severe disease than the previously dominant alpha (B.1.1.7) variant. We aimed to characterise the severity of the delta variant compared with the alpha variant by determining the relative risk of hospital attendance outcomes. Methods: This cohort study was done among all patients with COVID-19 in England between March 29 and May 23, 2021, who were identified as being infected with either the alpha or delta SARS-CoV-2 variant through whole-genome sequencing. Individual-level data on these patients were linked to routine health-care datasets on vaccination, emergency care attendance, hospital admission, and mortality (data from Public Health England's Second Generation Surveillance System and COVID-19-associated deaths dataset; the National Immunisation Management System; and NHS Digital Secondary Uses Services and Emergency Care Data Set). The risk for hospital admission and emergency care attendance were compared between patients with sequencing-confirmed delta and alpha variants for the whole cohort and by vaccination status subgroups. Stratified Cox regression was used to adjust for age, sex, ethnicity, deprivation, recent international travel, area of residence, calendar week, and vaccination status. Findings: Individual-level data on 43 338 COVID-19-positive patients (8682 with the delta variant, 34 656 with the alpha variant; median age 31 years [IQR 17–43]) were included in our analysis. 196 (2·3%) patients with the delta variant versus 764 (2·2%) patients with the alpha variant were admitted to hospital within 14 days after the specimen was taken (adjusted hazard ratio [HR] 2·26 [95% CI 1·32–3·89]). 498 (5·7%) patients with the delta variant versus 1448 (4·2%) patients with the alpha variant were admitted to hospital or attended emergency care within 14 days (adjusted HR 1·45 [1·08–1·95]). Most patients were unvaccinated (32 078 [74·0%] across both groups). The HRs for vaccinated patients with the delta variant versus the alpha variant (adjusted HR for hospital admission 1·94 [95% CI 0·47–8·05] and for hospital admission or emergency care attendance 1·58 [0·69–3·61]) were similar to the HRs for unvaccinated patients (2·32 [1·29–4·16] and 1·43 [1·04–1·97]; p=0·82 for both) but the precision for the vaccinated subgroup was low. Interpretation: This large national study found a higher hospital admission or emergency care attendance risk for patients with COVID-19 infected with the delta variant compared with the alpha variant. Results suggest that outbreaks of the delta variant in unvaccinated populations might lead to a greater burden on health-care services than the alpha variant. Funding: Medical Research Council; UK Research and Innovation; Department of Health and Social Care; and National Institute for Health Research