A Novel Cyber Resilience Framework – Strategies and Best Practices for Today's Organizations

Cyber resilience refers to an organization's ability to maintain its essential functions, services despite cyber-attacks and swiftly recover from any disruptions. It involves proactive measures like gathering threat intelligence and managing risks, as well as reactive measures such as incident response planning, data backup and recovery. To achieve cyber resilience, organizations must implement robust cyber security measures, regularly update their incident response plans, and educate employees on safe online practices. Furthermore, having a comprehensive backup and recovery strategy in place is crucial to swiftly restore critical systems and data in the event of an attack. Overall, the proposed framework emphasizes cyber resilience as a continuous and proactive approach for managing cyber security risks and safeguarding against the growing threat of cyber-attacks

An enterprise policy specification tool

As enterprises begin to increasingly conduct their businesses over multiple interconnected networks spanning many countries using large computer systems, there is a need to be able, to specify, represent and manipulate enterprise policies in these systems so as to be able to efficiently monitor and regulate enterprise processes and business transactions. A large enterprise typically comprises of hundreds of smaller units that to a large extent operate independently but within the overall goals of the enterprise. To reduce any bottlenecks or delays in everyday operations of enterprise units, it should be possible for various enterprise unit heads to create, delete or modify policies relevant to them with minimum reliance on a centralized policy administrator. However, when multiple users begin to manage enterprise policies, there is a need to identify "who can create policies on what resources" and "who should follow these policies". Also, when multiple units compete for common resources, policy conflicts may arise. It is important to detect and resolve conflicts between policies before accepting them for enforcement. An Enterprise Policy Specification Tool (PST) is introduced in this thesis that provides a solution to the above problems. The tool is unique since it provides a model-driven policy specification language that incorporates constructs to denote the enterprise model in the specified policies. We have defined policy conflicts that can arise and provide a mechanism to detect and resolve them at the time of specification. Although our proposed model is domain independent, the implementation and testing have been carried out in the context of a Message Notification System. A Java-based partial implementation of our proposed architecture has demonstrated the feasibility of the model-based approach to policy specificatio

Impact of prematurity on long-stay paediatric intensive care unit admissions in England 2008-2018

BACKGROUND: Survival following extreme preterm birth has improved, potentially increasing the number of children with ongoing morbidity requiring intensive care in childhood. Previous single-centre studies have suggested that long-stay admissions in paediatric intensive care units (PICUs) are increasing. We aimed to examine trends in long-stay admissions (≥28 days) to PICUs in England, outcomes for this group (including mortality and PICU readmission), and to determine the contribution of preterm-born children to the long-stay population, in children aged <2 years. METHODS: Data was obtained from the Paediatric Intensive Care Audit Network (PICANet) for all children <2 years admitted to National Health Service PICUs from 1/1/2008 to 31/12/2018 in England. We performed descriptive analysis of child characteristics and PICU outcomes. RESULTS: There were 99,057 admissions from 67,615 children. 2,693 children (4.0%) had 3,127 long-stays. Between 2008 and 2018 the annual number of long-stay admissions increased from 225 (2.7%) to 355 (4.0%), and the proportion of bed days in PICUs occupied by long-stay admissions increased from 24.2% to 33.2%. Of children with long-stays, 33.5% were born preterm, 53.5% were born at term, and 13.1% had missing data for gestational age. A considerable proportion of long-stay children required PICU readmission before two years of age (76.3% for preterm-born children). Observed mortality during any admission was also disproportionately greater for long-stay children (26.5% for term-born, 24.8% for preterm-born) than the overall rate (6.3%). CONCLUSIONS: Long-stays accounted for an increasing proportion of PICU activity in England between 2008 and 2018. Children born preterm were over-represented in the long-stay population compared to the national preterm birth rate (8%). These results have significant implications for future research into paediatric morbidity, and for planning future PICU service provision

Developing a Measure of Safety Data Culture

Safety is a critical concern for many organizations, especially those in construction and manufacturing. A newer approach to improving an organization’s decision making involves the use of data analytics. In regard to safety, the use of data analytics would allow for detecting and tracking risk factors such as behaviors, environmental contingencies, production, procedures, and hazards that are associated with workplace injuries. However, many organizations do not have a culture involving the use and measurement of relevant variables on an ongoing basis. Accordingly, the purpose of the study is to develop a measure of safety culture with a specific emphasis on the extent to which data is being utilized for management of safety in an organization. This measure of safety culture and analytics will assist in determining the extent to which an organization is ready to utilize data analytics into their safety program

Hospital admissions linked to SARS-CoV-2 infection in children and adolescents: cohort study of 3.2 million first ascertained infections in England

Objective To describe hospital admissions associated with SARS-CoV-2 infection in children and adolescents. Design Cohort study of 3.2 million first ascertained SARS-CoV-2 infections using electronic health care record data. Setting England, July 2020 to February 2022. Participants About 12 million children and adolescents (age &lt;18 years) who were resident in England. Main outcome measures Ascertainment of a first SARS-CoV-2 associated hospital admissions: due to SARS-CoV-2, with SARS-CoV-2 as a contributory factor, incidental to SARS-CoV-2 infection, and hospital acquired SARS-CoV-2. Results 3 226 535 children and adolescents had a recorded first SARS-CoV-2 infection during the observation period, and 29 230 (0.9%) infections involved a SARS-CoV-2 associated hospital admission. The median length of stay was 2 (interquartile range 1-4) days) and 1710 of 29 230 (5.9%) SARS-CoV-2 associated admissions involved paediatric critical care. 70 deaths occurred in which covid-19 or paediatric inflammatory multisystem syndrome was listed as a cause, of which 55 (78.6%) were in participants with a SARS-CoV-2 associated hospital admission. SARS-CoV-2 was the cause or a contributory factor in 21 000 of 29 230 (71.8%) participants who were admitted to hospital and only 380 (1.3%) participants acquired infection as an inpatient and 7855 (26.9%) participants were admitted with incidental SARS-CoV-2 infection. Boys, younger children (&lt;5 years), and those from ethnic minority groups or areas of high deprivation were more likely to be admitted to hospital (all P&lt;0.001). The covid-19 vaccination programme in England has identified certain conditions as representing a higher risk of admission to hospital with SARS-CoV-2: 11 085 (37.9%) of participants admitted to hospital had evidence of such a condition, and a further 4765 (16.3%) of participants admitted to hospital had a medical or developmental health condition not included in the vaccination programme’s list. Conclusions Most SARS-CoV-2 associated hospital admissions in children and adolescents in England were due to SARS-CoV-2 or SARS-CoV-2 was a contributory factor. These results should inform future public health initiatives and research

Characteristics of Severe Acute Respiratory Syndrome Coronavirus-2 Infection and Comparison With Influenza in Children Admitted to U.K. PICUs

Objectives: Severe acute respiratory syndrome coronavirus-2 affects adults disproportionately more than children. A small proportion of children with severe acute respiratory syndrome coronavirus-2 required admission to a PICU. We describe the nationwide U.K. PICU experience of severe acute respiratory syndrome coronavirus-2 infection during the first wave of the pandemic and compare this with the critical care course of the 2019 influenza cohort. Design: Prospective nationwide cohort study of characteristics of severe acute respiratory syndrome coronavirus-2–positive children. Data collection utilized routine Pediatric Intensive Care Audit Network and severe acute respiratory syndrome coronavirus-2–specific data. Setting: All U.K. PICUs. Patients: Children less than 18 years old, admitted to U.K. PICUs between March 14, 2020, and June 13, 2020, and a positive severe acute respiratory syndrome coronavirus-2 polymerase chain reaction. Children admitted to U.K. PICUs in 2019 with influenza provided comparison. Interventions: None. Measurements and Main Results: We identified 76 PICU admissions among 73 children with a positive severe acute respiratory syndrome coronavirus-2 polymerase chain reaction test. Prevalence of PICU admissions per million was 5.2 for children versus 260 for adults. Ten children (14%) were identified on routine screening. Seventeen children (23%) had pediatric inflammatory multisystem syndrome temporally associated with severe acute respiratory syndrome coronavirus-2. Seventeen (23%) had coinfections. Invasive ventilation was required in seven of 17 children (41%) with pediatric inflammatory multisystem syndrome temporally associated with severe acute respiratory syndrome coronavirus-2 versus 38 of 56 other severe acute respiratory syndrome coronavirus-2 positive children (68%), with 77% requiring vasoactive support versus 43%, respectively. Seven children (10%) died. In comparison with influenza children, severe acute respiratory syndrome coronavirus-2 children were older (median [interquartile range]: 10 [1–13] vs 3 yr [1–8 yr]), more often Black or Asian (52% v 18%), higher weight z score (0.29 [–0.80 to 1.62] vs –0.41 [–1.37 to 0.63]), and higher deprivation index (3.3 [–1 to 6.3] vs 1.2 [–1.8 to 4.4]). Comorbidities, frequency of organ supports, and length of stay were similar. Conclusions: This nationwide study confirms that PICU admissions with severe acute respiratory syndrome coronavirus-2 infections were infrequent. We have reported similarities and differences in sociodemographic characteristics, organ support interventions, and outcomes of children affected by severe acute respiratory syndrome coronavirus-2 compared with influenza

In the eye of the storm: impact of COVID-19 pandemic on admission patterns to paediatric intensive care units in the UK and Eire

Background The coronavirus disease-19 (COVID-19) pandemic had a relatively minimal direct impact on critical illness in children compared to adults. However, children and paediatric intensive care units (PICUs) were affected indirectly. We analysed the impact of the pandemic on PICU admission patterns and patient characteristics in the UK and Ireland. Methods We performed a retrospective cohort study of all admissions to PICUs in children < 18 years during Jan–Dec 2020, using data collected from 32 PICUs via a central database (PICANet). Admission patterns, case-mix, resource use, and outcomes were compared with the four preceding years (2016–2019) based on the date of admission. Results There were 16,941 admissions in 2020 compared to an annual average of 20,643 (range 20,340–20,868) from 2016 to 2019. During 2020, there was a reduction in all PICU admissions (18%), unplanned admissions (20%), planned admissions (15%), and bed days (25%). There was a 41% reduction in respiratory admissions, and a 60% reduction in children admitted with bronchiolitis but an 84% increase in admissions for diabetic ketoacidosis during 2020 compared to the previous years. There were 420 admissions (2.4%) with either PIMS-TS or COVID-19 during 2020. Age and sex adjusted prevalence of unplanned PICU admission reduced from 79.7 (2016–2019) to 63.1 per 100,000 in 2020. Median probability of death [1.2 (0.5–3.4) vs. 1.2 (0.5–3.4) %], length of stay [2.3 (1.0–5.5) vs. 2.4 (1.0–5.7) days] and mortality rates [3.4 vs. 3.6%, (risk-adjusted OR 1.00 [0.91–1.11, p = 0.93])] were similar between 2016–2019 and 2020. There were 106 fewer in-PICU deaths in 2020 (n = 605) compared with 2016–2019 (n = 711). Conclusions The use of a high-quality international database allowed robust comparisons between admission data prior to and during the COVID-19 pandemic. A significant reduction in prevalence of unplanned admissions, respiratory diseases, and fewer child deaths in PICU observed may be related to the targeted COVID-19 public health interventions during the pandemic. However, analysis of wider and longer-term societal impact of the pandemic and public health interventions on physical and mental health of children is required