Analysis of Pedestrian Accident Injury-Severities at Road Junctions and Crossings using an Advanced Random Parameter Modelling Framework: The Case of Scotland

This paper investigates the determinants of injury severities in pedestrian-motor vehicle accidents at signalised and unsignalised junctions, and at physically-controlled and human-controlled crossings in Scotland. The accident data were drawn from the official police crash report database of the UK spanning a period between 2010 and 2018. Correlated random parameter ordered probit models with heterogeneity in the means were developed in order to account for the multi-layered impact of unobserved heterogeneity on statistical estimation. The model estimation results showed that the severities of accident injuries are affected by roadway, location, weather, vehicle, and driver characteristics as well as temporal attributes (including time and day of the accident). Factors such as the urban context, lighting and weather conditions and road surface conditions were found to result in correlated random parameters, thus capturing the intricate, yet interactive effects of unobserved heterogeneity, and particularly the unobserved behavioural response of road users to different traffic control types at junctions and crossings. Vehicle type, driver’s gender and day-of-the-week were observed to influence the random parameters' distributions. Empirically, the results showcase variations in the determinants of injury severities at signalised and unsignalised junctions, and at physically-controlled and human-controlled crossings. Even though most of these variations were related to the magnitude of impact of the determinants, differences in the directional effects on injury severities were also identified, mainly for factors related to weather conditions, hazard presence on the road, and temporal characteristics of the accidents

SARS-CoV-2 variants-associated outbreaks of COVID-19 in a tertiary institution, North-Central Nigeria: Implications for epidemic control.

The COVID-19 global pandemic is being driven by evolving SARS-CoV-2 variants with consequential implications on virus transmissibility, host immunity, and disease severity. Continuous molecular and genomic surveillance of the SARS-CoV-2 variants is therefore necessary for public health interventions toward the management of the pandemic. This study is a retrospective analysis of COVID-19 cases reported in a Nigerian tertiary institution from July to December 2021. In total, 705 suspected COVID-19 cases that comprised 547 students and 158 non-students were investigated by real time PCR (RT-PCR); of which 372 (~52.8%) tested positive for COVID-19. Using a set of selection criteria, 74 (~19.9%) COVID-19 positive samples were selected for next generation sequencing. Data showed that there were two outbreaks of COVID-19 within the university community over the study period, during which more females (56.8%) tested positive than males (47.8%) (p<0.05). Clinical data together with phylogenetic analysis suggested community transmission of SARS-CoV-2 through mostly asymptomatic and/or pre-symptomatic individuals. Confirmed COVID-19 cases were mostly mild, however, SARS-CoV-2 delta (77%) and omicron (4.1%) variants were implicated as major drivers of respective waves of infections during the study period. This study highlights the importance of integrated surveillance of communicable disease during outbreaks

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

Analysis of pedestrian accident injury-severities at road junctions and crossings using an advanced random parameter modelling framework: The case of Scotland

This paper investigates the determinants of injury severities in pedestrian-motor vehicle accidents at signalised and unsignalised junctions, and at physically-controlled and human-controlled crossings in Scotland. The accident data were drawn from the official police crash report database of the UK spanning a period between 2010 and 2018. Correlated random parameter ordered probit models with heterogeneity in the means were developed in order to account for the multi-layered impact of unobserved heterogeneity on statistical estimation. The model estimation results showed that the severities of accident injuries are affected by roadway, location, weather, vehicle, and driver characteristics as well as temporal attributes (including time and day of the accident). Factors such as the urban context, lighting and weather conditions and road surface conditions were found to result in correlated random parameters, thus capturing the intricate, yet interactive effects of unobserved heterogeneity, and particularly the unobserved behavioural response of road users to different traffic control types at junctions and crossings. Vehicle type, driver’s gender and day-of-the-week were observed to influence the random parameters' distributions. Empirically, the results showcase variations in the determinants of injury severities at signalised and unsignalised junctions, and at physically-controlled and human-controlled crossings. Even though most of these variations were related to the magnitude of impact of the determinants, differences in the directional effects on injury severities were also identified, mainly for factors related to weather conditions, hazard presence on the road, and temporal characteristics of the accidents

Clinical Risk Factors Associated with Ambulatory Outcome in Acute Ischemic Stroke Patient Smokers Treated with Thrombolytic Therapy

Background: Patients who have suffered an acute ischemic stroke (AIS) and are smokers may have a better outcome following thrombolytic therapy when compared with non-smokers. While this finding is controversial, data on baseline clinical risk factors to predict treatment efficacy of thrombolytic therapy using ambulatory status in patients who suffered AIS and are smokers is not common. Methods: Between 2010 and 2016, retrospective data on patients who have suffered an AIS and received recombinant tissue plasminogen activator (rtPA) were obtained from Greenville health system registry. Assessment of clinical risk factors and the likelihood of an improvement in post-stroke ambulation among smokers and non-smokers was carried out using multivariate logistic regression. Results: Of 1001 patients, 70.8% were smokers and 29.2% non-smokers. Among the smokers and non-smokers, 74.6% and 84.6% improvement in ambulation respectively at discharge. The odds of improved ambulation decrease among smokers as age group increases compared to those below 50 [(60–69 years, aOR, 0.30, 95% C.I, 0.108–0.850, p \u3c 0.05), (70–79 years aOR, 0.27, 95% C.I, 0.096–0.734, p \u3c 0.05), (80+ years aOR, 0.16, 95% C.I, 0.057–0.430, P \u3c 0.01). Patients with National Institute of Health Stroke Scale Score (NIHSS) score \u3e 7 (reference \u3c7) were 91% less likely to have improved ambulation among smokers and non-smokers (aOR, 0.09, 95% C.I, 0.055–0.155, P = 0.01), and (aOR, 0.08, 95% C.I, 0.027–0.214, P = 0.01) respectively. Atrial fibrillation was an independent predictor of decreased improvement in ambulation only among smokers (aOR, 0.58, 95% C.I, 0.356–0.928 P \u3c 0.05). Conclusion: Our findings suggest that elderly smokers with atrial fibrillation would benefit more from aggressive management of atrial fibrillation than non-smokers

SARS-CoV-2 variants-associated outbreaks of COVID-19 in a tertiary institution, North-Central Nigeria: Implications for epidemic control. S1 Data

Data for the PLOS ONE paper, "SARS-CoV-2 variants-associated outbreaks of COVID-19 in a tertiary institution, North-Central Nigeria: Implications for epidemic control"

SARS-CoV-2 variants-associated outbreaks of COVID-19 in a tertiary institution, North-Central Nigeria: Implications for epidemic control.

The COVID-19 global pandemic is being driven by evolving SARS-CoV-2 variants with consequential implications on virus transmissibility, host immunity, and disease severity. Continuous molecular and genomic surveillance of the SARS-CoV-2 variants is therefore necessary for public health interventions toward the management of the pandemic. This study is a retrospective analysis of COVID-19 cases reported in a Nigerian tertiary institution from July to December 2021. In total, 705 suspected COVID-19 cases that comprised 547 students and 158 non-students were investigated by real time PCR (RT-PCR); of which 372 (~52.8%) tested positive for COVID-19. Using a set of selection criteria, 74 (~19.9%) COVID-19 positive samples were selected for next generation sequencing. Data showed that there were two outbreaks of COVID-19 within the university community over the study period, during which more females (56.8%) tested positive than males (47.8%) (p<0.05). Clinical data together with phylogenetic analysis suggested community transmission of SARS-CoV-2 through mostly asymptomatic and/or pre-symptomatic individuals. Confirmed COVID-19 cases were mostly mild, however, SARS-CoV-2 delta (77%) and omicron (4.1%) variants were implicated as major drivers of respective waves of infections during the study period. This study highlights the importance of integrated surveillance of communicable disease during outbreaks