Evaluating public health effects of risk-based travel policy for the COVID-19 epidemic in Scotland (preprint)

Background: Decisions to impose temporary travel measures are less common as the global epidemiology of COVID-19 evolves. Risk-based travel measures may avoid the need for a complete travel ban, however evaluations of their effects are lacking. Here we investigated the public health effects of a temporary traffic light system introduced in the United Kingdom (UK) in 2021, imposing red-amber-green (RAG) status based on risk assessment. Methods: We analysed data on international flight passengers arriving into Scotland, COVID-19 testing surveillance, and SARS-CoV-2 whole genome sequences to quantify effects of the traffic light system on (i) international travel frequency, (ii) travel-related SARS-CoV-2 case importations, (iii) national SARS-CoV-2 case incidence, and (iv) importation of novel SARS-CoV-2 variants. Results: International flight passengers arriving into Scotland had increased by 754% during the traffic light period. Amber list countries were the most frequently visited and ranked highly for SARS-CoV-2 importations and contribution to national case incidence. Rates of international travel and associated SARS-CoV-2 cases varied significantly across age, health board, and deprivation groups. Multivariable logistic regression revealed SARS-CoV-2 cases detections were less likely among travellers than non-travellers, although increasing from green-to-amber and amber-to-red lists. When examined according to travel destination, SARS-CoV-2 importation risks did not strictly follow RAG designations, and red lists did not prevent establishment of novel SARS-CoV-2 variants. Conclusions: Our findings suggest that country-specific post-arrival screening undertaken in Scotland did not prohibit the public health impact of COVID-19 in Scotland. Travel rates likely contributed to patterns of high SARS-CoV-2 case importation and population impact.

Influence of Socioeconomic Deprivation on Interventions and Outcomes for Patients Admitted with COVID-19 to Critical Care Units in Scotland: A National Cohort Study (preprint)

Background: Coronavirus disease 2019 (COVID-19) can lead to significant respiratory failure with between 14% and 18% of hospitalised patients requiring critical care admission. This study describes the impact of socioeconomic deprivation on 30-day survival following critical care admission for COVID-19, and the impact of the COVID-19 pandemic on critical care capacity in Scotland.Methods: This cohort study used linked national hospital records including ICU, virology testing and national death records to identify and describe patients with COVID-19 admitted to a critical care unit in Scotland. Multivariable logistic regression was used to assess the impact of deprivation on 30-day mortality. Critical care capacity was described by reporting the percentage of baseline ICU bed utilisation required.Results: There were 735 patients with COVID-19 admitted to critical care units across Scotland from 1/3/2020 to 20/6/2020. There was a higher proportion of patients from more deprived areas, with 183 admissions (24.9%) from the most deprived quintile and 100 (13.6%) from the least deprived quintile. 30-day mortality was 34.8%. After adjusting for age, sex and ethnicity, mortality was significantly higher in patients from the most deprived quintile (OR 1.97, 95%CI 1.13, 3.41, p=0.016). ICUs serving populations with higher levels of deprivation spent a greater amount of time over their baseline ICU bed capacity.Conclusion: Patients with COVID-19 living in areas with greater socioeconomic deprivation had a higher frequency of critical care admission and a higher adjusted 30-day mortality. ICUs in health boards with higher levels of socioeconomic deprivation had both higher peak occupancy and longer duration of occupancy over normal maximum capacity.Funding Statement: None.Declaration of Interests: All authors declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; NL is Director of Research, Intensive Care Society; JM is funded by a THIS.Institute (University of Cambridge) Research Fellowship (PD-2019-02-16). Ethics Approval Statement: The Scottish Intensive Care Society Audit Group in Public Health Scotland has a legislative remit to process personal data in relation to public health. Linkage to additional datasets was approved following scrutiny by the Public Benefit and Privacy Panel for Health and Social Care (ref 1920-0093). Access and use of the data for the purpose of this work were approved following a Public Health Scotland information governance review of linking additional internal datasets to identify patients with COVID-19. Only analysts working in Public Health Scotland had access to the linked patient data which could only be accessed via an NHS secure network.

Risk of hospitalisation with coronavirus disease 2019 in healthcare workers and their households:a nationwide linkage cohort study (preprint)

ObjectiveMany healthcare staff work in high-risk settings for contracting and transmitting Severe Acute Respiratory Syndrome Coronavirus 2. Their risk of hospitalisation for coronavirus disease 2019 (COVID-19), and that of their households, is poorly understood. Design and settings and participantsDuring the peak period for COVID-19 infection in Scotland (1st March 2020 to 6th June 2020) we conducted a national record linkage study to compare the risk of COVID-19 hospitalisation among healthcare workers (age: 18-65 years), their households and other members of the general population. Main outcomeHospitalisation with COVID-19 ResultsThe cohort comprised 158,445 healthcare workers, the majority being patient facing (90,733 / 158,445; 57.3%), and 229,905 household members. Of all COVID-19 hospitalisations in the working age population (18-65-year-old), 17.2% (360 / 2,097) were in healthcare workers or their households. Adjusting for age, sex, ethnicity, socio-economic deprivation and comorbidity, the risk of COVID-19 hospitalisation in non-patient facing healthcare workers and their households was similar to the risk in the general population (hazards ratio [HR] 0.81; 95%CI 0.52-1.26 and 0.86; 95%CI 0.49-1.51 respectively). In models adjusting for the same covariates however, patient facing healthcare workers, compared to non-patient facing healthcare workers, were at higher risk (HR 3.30; 95%CI 2.13-5.13); so too were household members of patient facing healthcare workers (HR 1.79; 95%CI 1.10-2.91). On sub-dividing patient-facing healthcare workers into those who worked in front-door, intensive care and non-intensive care aerosol generating settings and other, those in front door roles were at higher risk (HR 2.09; 95%CI 1.49-2.94). For most patient facing healthcare workers and their households, the estimated absolute risk of COVID-19 hospitalisation was less than 0.5% but was 1% and above in older men with comorbidity. ConclusionsHealthcare workers and their households contribute a sixth of hospitalised COVID-19 cases. Whilst the absolute risk of hospitalisation was low overall, patient facing healthcare workers and their households had 3- and 2-fold increased risks of COVID-19 hospitalisation.

Associations of severe COVID-19 with polypharmacy in the REACT-SCOT case-control study (preprint)

Objectives -- To investigate the relation of severe COVID-19 to prior drug prescribing. Design -- Matched case-control study (REACT-SCOT) based on record linkage to hospital discharges since June 2015 and dispensed prescriptions issued in primary care during the last 240 days. Setting -- Scottish population. Main outcome measure -- Severe COVID-19, defined by entry to critical care or fatal outcome. Participants -- All 4272 cases of severe COVID-19 in Scotland since the start of the epidemic, with 36948 controls matched for age, sex and primary care practice. Results -- Severe COVID-19 was strongly associated with the number of non-cardiovascular drug classes dispensed. This association was strongest in those not resident in care homes, in whom the rate ratio (95% CI) associated with dispensing of 12 or more drug classes versus none was 10.8 (8.7, 13.2), and was not accounted for by treatment of conditions designated as conferring increased risk. Of 17 drug classes postulated at the start of the epidemic to be "medications compromising COVID", all were associated with increased risk of severe COVID-19. The largest effect was for antipsychotic agents: rate ratio 4.14 (3.39, 5.07). Other drug classes with large effects included proton pump inhibitors (rate rato 2.19 (1.70, 2.80) for >= 2 defined daily doses/day), opioids (3.62 (2.65, 4.94) for >= 50 mg morphine equivalent/day) and gabapentinoids. These associations persisted after adjusting for covariates, and were stronger with recent than with non-recent exposure. Conclusions -- Severe COVID-19 is associated with polypharmacy and with drugs that cause sedation, respiratory depression or dyskinesia, have anticholinergic effects or affect the gastrointestinal system. These associations are not easily explained by co-morbidity. Although the evidence for causality is not conclusive, these results support existing guidance on reducing overprescribing of these drug classes and limiting inappropriate polypharmacy as a potential means of reducing COVID-19 risk. Registration -- ENCEPP number EUPAS35558

COVID-19 Disease in People with Diabetes in Scotland: Incidence, Severity and Risk Stratification Using Matched Case-Control and Prospective Cohort Studies (preprint)

Background: The risks of, and risk factors for, COVID-19 disease associated with diabetes are poorly quantified. Methods: We identified as cases all those in Scotland with a positive SARS-CoV-2 nucleic acid test in the national laboratory database and anyone else with a death certificate mentioning COVID-19. Seven controls matched for age, sex and general practice were selected per case. Data were linked to the national diabetes register, hospitalisation and critical care unit (CCU) databases. Analyses focused on those with COVID-19 requiring critical care or dying. Analyses were by conditional and unconditional logistic regression. Findings: 0.3% (n=845) of those with diabetes had developed severe or fatal COVID-19, representing rate ratios of 3.86 (2.74, 5.45) in type 1 and 1.69 (1.56, 1.84) in type 2 diabetes. Rates were almost threefold in the most versus least socioeconomically deprived quintiles of the population. Most (77%) cases had another recognised co-morbidity such as heart or lung disease (OR 2.6). Diabetes specific factors associated with increased risk included; HbA1c odds ratio (OR) >85 mmol/mol versus <53: 1.96(1.55,2.48);p-value <0.001, prior diabetic ketoacidosis: OR 2.44(1.41,4.20);p-value 0.001 and hypoglycaemia hospitalisations: OR 3.28(2.41,4.46);p-value <0.001. Chronic retinal and renal complications were also associated with increased risk. A cross-validated predictive model of severe or fatal disease had a C-statistic of 0.83. Interpretations: Relative risks of severe or fatal COVID-19 are substantially elevated in both types of diabetes. Risk scores based on prior clinical history should be useful for identifying those with diabetes needing tailored protective measures.Funding Statement: There was no specific funder for this study.Declaration of Interests: The authors declare no conflicts of interest.Ethics Approval Statement: This research was conducted with approval from the Public Benefit Privacy Protection Panel (PBPP ref. 1617- 0147), originally set up under PAC 33/11, with approval from the Scotland A Research Ethics Committee (ref. 11/AL/0225). All datasets were de-identified before analysis.

Rapid Epidemiological Analysis of Comorbidities andTreatments as risk factors for COVID-19 in Scotland(REACT-SCOT): a population-based case-control study (preprint)

BackgroundThe objectives of this study were to identify risk factors for severe COVID-19 and to lay the basis for risk stratification based on demographic data and health records. Methods and FindingsThe design was a matched case-control study. Severe COVID-19 was defined as either a positive nucleic acid test for SARS-CoV-2 in the national database followed by entry to a critical care unit or death within 28 days, or a death certificate with COVID-19 as underlying cause. Up to ten controls per case matched for sex, age and primary care practice were selected from the population register. All diagnostic codes from the past five years of hospitalisation records and all drug codes from prescriptions dispensed during the past nine months were extracted. Rate ratios for severe COVID-19 were estimated by conditional logistic regression. There were 4272 severe cases. In a logistic regression using the age-sex distribution of the national population, the odds ratios for severe disease were 2.87 for a 10-year increase in age and 1.63 for male sex. In the case-control analysis, the strongest risk factor was residence in a care home, with rate ratio (95% CI) 21.4 (19.1, 23.9). Univariate rate ratios (95% CIs) for conditions listed by public health agencies as conferring high risk were 2.75 (1.96, 3.88) for Type 1 diabetes, 1.60 (1.48, 1.74) for Type 2 diabetes, 1.49 (1.37, 1.61) for ischemic heart disease, 2.23 (2.08, 2.39) for other heart disease, 1.96 (1.83, 2.10) for chronic lower respiratory tract disease, 4.06 (3.15, 5.23) for chronic kidney disease, 5.4 (4.9, 5.8) for neurological disease, 3.61 (2.60, 5.00) for chronic liver disease and 2.66 (1.86, 3.79) for immune deficiency or suppression. 78% of cases and 52% of controls had at least one listed condition (NA of cases and NA of controls under age 40). Severe disease was associated with encashment of at least one prescription in the past nine months and with at least one hospital admission in the past five years [rate ratios 3.10 (2.59, 3.71)] and 2.75 (2.53, 2.99) respectively] even after adjusting for the listed conditions. In those without listed conditions significant associations with severe disease were seen across many hospital diagnoses and drug categories. Age and sex provided 2.58 bits of information for discrimination. A model based on demographic variables, listed conditions, hospital diagnoses and prescriptions provided an additional 1.25 bits (C-statistic 0.825). A limitation of this study is that records from primary care were not available. ConclusionsAlong with older age and male sex, severe COVID-19 is strongly associated with past medical history across all age groups. Many comorbidities beyond the risk conditions designated by public health agencies contribute to this. A risk classifier that uses all the information available in health records, rather than only a limited set of conditions, will more accurately discriminate between low-risk and high-risk individuals who may require shielding until the epidemic is over. Author summaryMost people infected with the SARS-CoV-2 coronavirus do not become seriously ill. It is The risk of severe or fatal illness is higher in older than in younger people, and is higher in people with conditions such as asthma and diabetes than in people without these conditions. Using Scotlands capability for linking electronic health records, we report the first systematic study of the relation of severe or fatal COVID-19 to pre-existing health conditions and other risk factors. We show that the strongest risk factor, apart from age, is residence in a care home. The conditions associated with increased risk include not only those already designated by public health agencies - asthma, diabetes, heart disease, disabling neurological disease, kidney disease - but many other diagnoses, associated with frailty and poor health. This lays a basis for constructing risk scores based on electronic health records that can be used to advise people at high risk of severe disease to shield themselves when there cases in their neighbourhood.