Costs and Benefits of Full Dual-Frame Telephone Survey Designs

Assesses the cost, sample composition, weighting, and substantive effect on survey results involved in interviewing respondents by cell phone, including those with landlines. Includes demographic profiles of cell phone-only, landline-only, and dual users

Issue Debates: Notecards in Extemporaneous Speaking

Editor\u27s Note: We are trying to bring debatable issues in the community to the forefront. Important contemporary issues are discussed at national tournaments, national conventions, and even at the average weekend tournament. But rarely are these issues written about in our journals. To foster those discussions, and in an effort to document some of the history of intercollegiate forensics, we will have an “Issue Debate” in each issue of Speaker & Gavel. For this issue, two well-known and successful coaches (and top-notch extempers in their day) debate the issue of note card use in extemporaneous speaking. We have seen this topic debated at length at multiple national events. But the interaction is limited to less than a minute per speaker and usually involves a dozen different speakers with two dozen different reasons as to why the event description language should or should not be changed. A journal’s format provides an opportunity for two scholars, well-versed in the activity, to express their reasoning on the issues related to this topic. It is an interesting read, and both sides make valid arguments

Predicting a diagnosis of ankylosing spondylitis using primary care health records–A machine learning approach

Ankylosing spondylitis is the second most common cause of inflammatory arthritis. However, a successful diagnosis can take a decade to confirm from symptom onset (via x-rays). The aim of this study was to use machine learning methods to develop a profile of the characteristics of people who are likely to be given a diagnosis of AS in future. The Secure Anonymised Information Linkage databank was used. Patients with ankylosing spondylitis were identified using their routine data and matched with controls who had no record of a diagnosis of ankylosing spondylitis or axial spondyloarthritis. Data was analysed separately for men and women. The model was developed using feature/variable selection and principal component analysis to develop decision trees. The decision tree with the highest average F value was selected and validated with a test dataset. The model for men indicated that lower back pain, uveitis, and NSAID use under age 20 is associated with AS development. The model for women showed an older age of symptom presentation compared to men with back pain and multiple pain relief medications. The models showed good prediction (positive predictive value 70%-80%) in test data but in the general population where prevalence is very low (0.09% of the population in this dataset) the positive predictive value would be very low (0.33%-0.25%). Machine learning can be used to help profile and understand the characteristics of people who will develop AS, and in test datasets with artificially high prevalence, will perform well. However, when applied to a general population with low prevalence rates, such as that in primary care, the positive predictive value for even the best model would be 1.4%. Multiple models may be needed to narrow down the population over time to improve the predictive value and therefore reduce the time to diagnosis of ankylosing spondylitis

The security of NTP's datagram protocol

For decades, the Network Time Protocol (NTP) has been used to synchronize computer clocks over untrusted network paths. This work takes a new look at the security of NTP’s datagram protocol. We argue that NTP’s datagram protocol in RFC5905 is both underspecified and flawed. The NTP specifications do not sufficiently respect (1) the conflicting security requirements of different NTP modes, and (2) the mechanism NTP uses to prevent off-path attacks. A further problem is that (3) NTP’s control-query interface reveals sensitive information that can be exploited in off-path attacks. We exploit these problems in several attacks that remote attackers can use to maliciously alter a target’s time. We use network scans to find millions of IPs that are vulnerable to our attacks. Finally, we move beyond identifying attacks by developing a cryptographic model and using it to prove the security of a new backwards-compatible client/server protocol for NTP.https://eprint.iacr.org/2016/1006.pdfhttps://eprint.iacr.org/2016/1006.pdfPublished versio

Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK

Background: To determine the extent and nature of changes associated with COVID-19 infection in terms of healthcare utilisation, this study observed healthcare contact 1 to 4 and 5 to 24 weeks following a COVID-19 diagnosis compared to propensity-matched controls.Methods: Two hundred forty nine thousand three hundred ninety Welsh individuals with a positive reverse transcription–polymerase chain reaction (RT-PCR) test were identified from data from national PCR test results. After elimination criteria, 98,600 positive individuals were matched to test negative and never tested controls using propensity matching. Cohorts were split on test location. Tests could be taken in either the hospital or community. Controls were those who had tested negative in their respective environments. Survival analysis was utilised for first clinicaloutcomes which are grouped into primary and secondary. Primary outcomes include post-viral-illness and fatigue as an indication of long-COVID. Secondary outcomes include clinical terminology concepts for embolism, respiratory conditions, mental health conditions, ft notes, or hospital attendance. Increased instantaneous risk for positive individuals was quantified using hazard ratios (HR) from Cox regression, while absolute risk (AR) and relative risk were quantified using life table analysis.Results: Analysis was conducted using all individuals and stratified by test location. Cases are compared to controls from the same test location. Fatigue (HR: 1.77, 95% CI: 1.34–2.25, p= <0.001) and embolism (HR: 1.50, 95% CI: 1.15–1.97, p=0.003) were more likely to occur in all positive individuals in the first 4 weeks; however, anxiety and depression (HR: 0.83, 95% CI: 0.73–0.95, p=0.007) were less likely. Positive individuals continued to be more at risk of fatigue(HR: 1.47, 95% CI: 1.24–1.75, p= <0.001) and embolism (HR: 1.51, 95% CI: 1.13–2.02, p=0.005) after 4 weeks. All positive individuals are also at greater risk of post-viral illness (HR: 4.57, 95% CI: 1.77–11.80, p=0.002). Despite statistical association between testing positive and several conditions, life table analysis shows that only a small minority of the studypopulation were affected

Islamist insurgency and the war against polio: a cross-national analysis of the political determinants of polio.

BACKGROUND: There is widespread agreement that civil war obstructs efforts to eradicate polio. It is suggested that Islamist insurgents have a particularly negative effect on vaccination programmes, but this claim is controversial. METHODS: We analyse cross-national data for the period 2003-14 using negative binomial regressions to investigate the relationship between Islamist and non-Islamist insurgency and the global distribution of polio. The dependent variable is the annual number of polio cases in a country according to the WHO. Insurgency is operationalized as armed conflict between the state and an insurgent organization resulting in ≥25 battle deaths per year according to the Uppsala Conflict Data Programme. Insurgencies are divided into Islamist and non-Islamist insurgencies. We control for other possible explanatory variables. RESULTS: Islamist insurgency did not have a significant positive relationship with polio throughout the whole period. But in the past few years - since the assassination of Osama bin Laden in 2011- Islamist insurgency has had a strong effect on where polio cases occur. The evidence for a relationship between non-Islamist insurgency and polio is less compelling and where there is a relationship it is either spurious or driven by ecological fallacy. CONCLUSIONS: Only particular forms of internal armed conflict - those prosecuted by Islamist insurgents - explain the current global distribution of polio. The variation over time in the relationship between Islamist insurgency and polio suggests that Islamist insurgent's hostility to polio vaccinations programmes is not the result of their theology, as the core tenets of Islam have not changed over the period of the study. Rather, our analysis indicates that it is a plausibly a reaction to the counterinsurgency strategies used against Islamist insurgents. The assassination of Osama bin Laden and the use of drone strikes seemingly vindicated Islamist insurgents' suspicions that immunization drives are a cover for espionage activities

Insights from linking police domestic abuse data and health data in South Wales, UK: a linked routine data analysis using decision tree classification

Background: Exposure to domestic abuse can lead to long-term negative impacts on the victim's physical and psychological wellbeing. The 1998 Crime and Disorder Act requires agencies to collaborate on crime reduction strategies, including data sharing. Although data sharing is feasible for individuals, rarely are whole-agency data linked. This study aimed to examine the knowledge obtained by integrating information from police and health-care datasets through data linkage and analyse associated risk factor clusters. Methods: This retrospective cohort study analyses data from residents of South Wales who were victims of domestic abuse resulting in a Public Protection Notification (PPN) submission between Aug 12, 2015 and March 31, 2020. The study links these data with the victims’ health records, collated within the Secure Anonymised Information Linkage databank, to examine factors associated with the outcome of an Emergency Department attendance, emergency hospital admission, or death within 12 months of the PPN submission. To assess the time to outcome for domestic abuse victims after the index PPN submission, we used Kaplan-Meier survival analysis. We used multivariable Cox regression models to identify which factors contributed the highest risk of experiencing an outcome after the index PPN submission. Finally, we created decision trees to describe specific groups of individuals who are at risk of experiencing a domestic abuse incident and subsequent outcome. Findings: After excluding individuals with multiple PPN records, duplicates, and records with a poor matching score or missing fields, the resulting clean dataset consisted of 8709 domestic abuse victims, of whom 6257 (71·8%) were female. Within a year of a domestic abuse incident, 3650 (41·9%) individuals had an outcome. Factors associated with experiencing an outcome within 12 months of the PPN included younger victim age (hazard ratio 1·183 [95% CI 1·053–1·329], p=0·0048), further PPN submissions after the initial referral (1·383 [1·295–1·476]; p<0·0001), injury at the scene (1·484 [1·368–1·609]; p<0·0001), assessed high risk (1·600 [1·444–1·773]; p<0·0001), referral to other agencies (1·518 [1·358–1·697]; p<0·0001), history of violence (1·229 [1·134–1·333]; p<0·0001), attempted strangulation (1·311 [1·148–1·497]; p<0·0001), and pregnancy (1·372 [1·142–1·648]; p=0·0007). Health-care data before the index PPN established that previous Emergency Department and hospital admissions, smoking, smoking cessation advice, obstetric codes, and prescription of antidepressants and antibiotics were associated with having a future outcome following a domestic abuse incident. Interpretation: The results indicate that vulnerable individuals are detectable in multiple datasets before and after involvement of the police. Operationalising these findings could reduce police callouts and future Emergency Department or hospital admissions, and improve outcomes for those who are vulnerable. Strategies include querying previous Emergency Department and hospital admissions, giving a high-risk assessment for a pregnant victim, and facilitating data linkage to identify vulnerable individuals