Emergence of a Novel Coronavirus (COVID-19): Protocol for Extending Surveillance Used by the Royal College of General Practitioners Research and Surveillance Centre and Public Health England

Neuropathological findings in Down syndrome, Alzheimer's disease and control patients with and without SARS-COV-2: preliminary findings

The SARS-CoV-2 virus that led to COVID-19 is associated with significant and long-lasting neurologic symptoms in many patients, with an increased mortality risk for people with Alzheimer's disease (AD) and/or Down syndrome (DS). However, few studies have evaluated the neuropathological and inflammatory sequelae in postmortem brain tissue obtained from AD and people with DS with severe SARS-CoV-2 infections. We examined tau, beta-amyloid (Aβ), inflammatory markers and SARS-CoV-2 nucleoprotein in DS, AD, and healthy non-demented controls with COVID-19 and compared with non-infected brain tissue from each disease group (total n = 24). A nested ANOVA was used to determine regional effects of the COVID-19 infection on arborization of astrocytes (Sholl analysis) and percent-stained area of Iba-1 and TMEM 119. SARS-CoV-2 antibodies labeled neurons and glial cells in the frontal cortex of all subjects with COVID-19, and in the hippocampus of two of the three DS COVID-19 cases. SARS-CoV-2-related alterations were observed in peri-vascular astrocytes and microglial cells in the gray matter of the frontal cortex, hippocampus, and para-hippocampal gyrus. Bright field microscopy revealed scattered intracellular and diffuse extracellular Aβ deposits in the hippocampus of controls with confirmed SARS-CoV-2 infections. Overall, the present preliminary findings suggest that SARS-CoV-2 infections induce abnormal inflammatory responses in Down syndrome.

Rapid triage and transfer system for patients with proven Covid-19 at emergency department

BACKGROUND

COVID-19 is a viral disease notorious for frequent worldwide outbreaks. It is difficult to control, thereby resulting in overload of the healthcare system. A possible solution to prevent overcrowding is rapid triage of patients, which makes it possible to focus care on the high-risk patients and minimize the impact of crowding on patient prognosis.

METHODS

The triage algorithm assessed self-sufficiency, oximetry, systolic blood pressure, and the Glasgow coma scale. Compliance with the triage protocol was defined as fulfillment of all protocol steps, including assignment of the correct level of care. Triage was considered successful if there was no change in the scope of care (e.g., unscheduled hospital admission, transfer to different level of care) or if there was unexpected death within 48 hours.

RESULTS

A total of 929 patients were enrolled in the study. Triage criteria were fulfilled in 825 (88.8%) patients. Within 48 hours, unscheduled hospital admission, transfer to different level of care, or unexpected death occurred in 56 (6.0%), 6 (0.6%), and 5 (0.5%) patients, respectively. The risk of unscheduled hospital admission or transfer to different level of care was significantly increased if triage criteria were not fulfilled [13.1% vs. 76.1%, RR 5.8 (3.8-8.3), p < 0.001; 0.5% vs. 5.2%, RR 11.4 (2.3-57.7), p = 0.036, respectively].

CONCLUSION

The proposed algorithm for triage of patients with proven COVID-19 is a simple, fast, and reliable tool for rapid sorting for outpatient treatment, hospitalization on a standard ward, or assignment to an intensive care unit.

Long-Term Effects of SARS-CoV-2 in the Brain: Clinical Consequences and Molecular Mechanisms

Numerous investigations have demonstrated significant and long-lasting neurological manifestations of COVID-19. It has been suggested that as many as four out of five patients who sustained COVID-19 will show one or several neurological symptoms that can last months after the infection has run its course. Neurological symptoms are most common in people who are less than 60 years of age, while encephalopathy is more common in those over 60. Biological mechanisms for these neurological symptoms need to be investigated and may include both direct and indirect effects of the virus on the brain and spinal cord. Individuals with Alzheimer's disease (AD) and related dementia, as well as persons with Down syndrome (DS), are especially vulnerable to COVID-19, but the biological reasons for this are not clear. Investigating the neurological consequences of COVID-19 is an urgent emerging medical need, since close to 700 million people worldwide have now had COVID-19 at least once. It is likely that there will be a new burden on healthcare and the economy dealing with the long-term neurological consequences of severe SARS-CoV-2 infections and long COVID, even in younger generations. Interestingly, neurological symptoms after an acute infection are strikingly similar to the symptoms observed after a mild traumatic brain injury (mTBI) or concussion, including dizziness, balance issues, anosmia, and headaches. The possible convergence of biological pathways involved in both will be discussed. The current review is focused on the most commonly described neurological symptoms, as well as the possible molecular mechanisms involved.

Mining of EHR for interface terminology concepts for annotating EHRs of COVID patients

BACKGROUND

Two years into the COVID-19 pandemic and with more than five million deaths worldwide, the healthcare establishment continues to struggle with every new wave of the pandemic resulting from a new coronavirus variant. Research has demonstrated that there are variations in the symptoms, and even in the order of symptom presentations, in COVID-19 patients infected by different SARS-CoV-2 variants (e.g., Alpha and Omicron). Textual data in the form of admission notes and physician notes in the Electronic Health Records (EHRs) is rich in information regarding the symptoms and their orders of presentation. Unstructured EHR data is often underutilized in research due to the lack of annotations that enable automatic extraction of useful information from the available extensive volumes of textual data.

METHODS

We present the design of a COVID Interface Terminology (CIT), not just a generic COVID-19 terminology, but one serving a specific purpose of enabling automatic annotation of EHRs of COVID-19 patients. CIT was constructed by integrating existing COVID-related ontologies and mining additional fine granularity concepts from clinical notes. The iterative mining approach utilized the techniques of 'anchoring' and 'concatenation' to identify potential fine granularity concepts to be added to the CIT. We also tested the generalizability of our approach on a hold-out dataset and compared the annotation coverage to the coverage obtained for the dataset used to build the CIT.

RESULTS

Our experiments demonstrate that this approach results in higher annotation coverage compared to existing ontologies such as SNOMED CT and Coronavirus Infectious Disease Ontology (CIDO). The final version of CIT achieved about 20% more coverage than SNOMED CT and 50% more coverage than CIDO. In the future, the concepts mined and added into CIT could be used as training data for machine learning models for mining even more concepts into CIT and further increasing the annotation coverage.

CONCLUSION

In this paper, we demonstrated the construction of a COVID interface terminology that can be utilized for automatically annotating EHRs of COVID-19 patients. The techniques presented can identify frequently documented fine granularity concepts that are missing in other ontologies thereby increasing the annotation coverage.

Mortality in COVID-19 among women on hormone replacement therapy: a retrospective cohort study

BACKGROUND

Limited recent observational data have suggested that there may be a protective effect of oestrogen on the severity of COVID-19 disease. Our aim was to investigate the association between hormone replacement therapy (HRT) or combined oral contraceptive pill (COCP) use and the likelihood of death in women with COVID-19.

METHODS

We undertook a retrospective cohort study using routinely collected computerized medical records from the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) primary care database. We identified a cohort of 1,863,478 women over 18 years of age from 465 general practices in England. Mixed-effects logistic regression models were used to quantify the association between HRT or COCP use and all-cause mortality among women diagnosed with confirmed or suspected COVID-19 in unadjusted and adjusted models.

RESULTS

There were 5,451 COVID-19 cases within the cohort. HRT was associated with a reduction in all-cause mortality in COVID-19 (adjusted OR 0.22, 95% CI 0.05 to 0.94). There were no reported events for all-cause mortality in women prescribed COCPs. This prevented further examination of the impact of COCP.

CONCLUSIONS

We found that HRT prescription within 6 months of a recorded diagnosis of COVID-19 infection was associated with a reduction in all-cause mortality. Further work is needed in larger cohorts to examine the association of COCP in COVID-19, and to further investigate the hypothesis that oestrogens may contribute a protective effect against COVID-19 severity.

Long term follow up of direct oral anticoagulants and warfarin therapy on stroke, with all-cause mortality as a competing risk, in people with atrial fibrillation: Sentinel network database study

Background

We investigated differences in risk of stroke, with all-cause mortality as a competing risk, in people newly diagnosed with atrial fibrillation (AF) who were commenced on either direct oral anticoagulants (DOACs) or warfarin treatment.

Methods and results

We conducted a retrospective cohort study of the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) database (a network of 500 English general practices). We compared long term exposure to DOAC (n = 5,168) and warfarin (n = 7,451) in new cases of AF not previously treated with oral anticoagulants. Analyses included: survival analysis, estimating cause specific hazard ratios (CSHR), Fine-Gray analysis for factors affecting cumulative incidence of events occurring over time and a cumulative risk regression with time varying effects.We found no difference in CSHR between stroke 1.08 (0.72–1.63, p = 0.69) and all-cause mortality 0.93 (0.81–1.08, p = 0.37), or between the anticoagulant groups. Fine-Gray analysis produced similar results 1.07 (0.71–1.6 p = 0.75) for stroke and 0.93 (0.8–1.07, p = 0.3) mortality. The cumulative risk of mortality with DOAC was significantly elevated in early follow-up (67 days), with cumulative risk decreasing until 1,537 days and all-cause mortality risk significantly decreased coefficient estimate:: -0.23 (-0.38–0.01, p = 0.001); which persisted over seven years of follow-up.

Conclusions

In this large, contemporary, real world primary care study with longer follow-up, we found no overall difference in the hazard of stroke between warfarin and DOAC treatment for AF. However, there was a significant time-varying effect between anti-coagulant regimen on all-cause mortality, with DOACs showing better survival. This is a key methodological observation for future follow-up studies, and reassuring for patients and health care professionals for longer duration of therapy

Remote COVID-19 Assessment in Primary Care (RECAP) risk prediction tool: derivation and real-world validation studies

BACKGROUND

Accurate assessment of COVID-19 severity in the community is essential for patient care and requires COVID-19-specific risk prediction scores adequately validated in a community setting. Following a qualitative phase to identify signs, symptoms, and risk factors, we aimed to develop and validate two COVID-19-specific risk prediction scores. Remote COVID-19 Assessment in Primary Care-General Practice score (RECAP-GP; without peripheral oxygen saturation [SpO2]) and RECAP-oxygen saturation score (RECAP-O2; with SpO2).

METHODS

RECAP was a prospective cohort study that used multivariable logistic regression. Data on signs and symptoms (predictors) of disease were collected from community-based patients with suspected COVID-19 via primary care electronic health records and linked with secondary data on hospital admission (outcome) within 28 days of symptom onset. Data sources for RECAP-GP were Oxford-Royal College of General Practitioners Research and Surveillance Centre (RCGP-RSC) primary care practices (development set), northwest London primary care practices (validation set), and the NHS COVID-19 Clinical Assessment Service (CCAS; validation set). The data source for RECAP-O2 was the Doctaly Assist platform (development set and validation set in subsequent sample). The two probabilistic risk prediction models were built by backwards elimination using the development sets and validated by application to the validation datasets. Estimated sample size per model, including the development and validation sets was 2880 people.

FINDINGS

Data were available from 8311 individuals. Observations, such as SpO2, were mostly missing in the northwest London, RCGP-RSC, and CCAS data; however, SpO2 was available for 1364 (70·0%) of 1948 patients who used Doctaly. In the final predictive models, RECAP-GP (n=1863) included sex (male and female), age (years), degree of breathlessness (three point scale), temperature symptoms (two point scale), and presence of hypertension (yes or no); the area under the curve was 0·80 (95% CI 0·76-0·85) and on validation the negative predictive value of a low risk designation was 99% (95% CI 98·1-99·2; 1435 of 1453). RECAP-O2 included age (years), degree of breathlessness (two point scale), fatigue (two point scale), and SpO2 at rest (as a percentage); the area under the curve was 0·84 (0·78-0·90) and on validation the negative predictive value of low risk designation was 99% (95% CI 98·9-99·7; 1176 of 1183).

INTERPRETATION

Both RECAP models are valid tools to assess COVID-19 patients in the community. RECAP-GP can be used initially, without need for observations, to identify patients who require monitoring. If the patient is monitored and SpO2 is available, RECAP-O2 is useful to assess the need for treatment escalation.

FUNDING

Community Jameel and the Imperial College President's Excellence Fund, the Economic and Social Research Council, UK Research and Innovation, and Health Data Research UK.

Mortality from angiotensin-converting enzyme-inhibitors and angiotensin receptor blockers in people infected with COVID-19: a cohort study of 3.7 million people

BACKGROUND

Concerns have been raised that angiotensin-converting enzyme-inhibitors (ACE-I) and angiotensin receptor blockers (ARBs) might facilitate transmission of severe acute respiratory syndrome coronavirus 2 leading to more severe coronavirus disease (COVID-19) disease and an increased risk of mortality. We aimed to investigate the association between ACE-I/ARB treatment and risk of death amongst people with COVID-19 in the first 6 months of the pandemic.

METHODS

We identified a cohort of adults diagnosed with either confirmed or probable COVID-19 (from 1 January to 21 June 2020) using computerized medical records from the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) primary care database. This comprised 465 general practices in England, United Kingdom with a nationally representative population of 3.7 million people. We constructed mixed-effects logistic regression models to quantify the association between ACE-I/ARBs and all-cause mortality among people with COVID-19, adjusted for sociodemographic factors, comorbidities, concurrent medication, smoking status, practice clustering, and household number.

RESULTS

There were 9,586 COVID-19 cases in the sample and 1,463 (15.3%) died during the study period between 1 January 2020 and 21 June 2020. In adjusted analysis ACE-I and ARBs were not associated with all-cause mortality (adjusted odds ratio [OR] 1.02, 95% confidence interval [CI] 0.85-1.21 and OR 0.84, 95% CI 0.67-1.07, respectively).

CONCLUSION

Use of ACE-I/ARB, which are commonly used drugs, did not alter the odds of all-cause mortality amongst people diagnosed with COVID-19. Our findings should inform patient and prescriber decisions concerning continued use of these medications during the pandemic.

National influenza surveillance systems in five European countries: a qualitative comparative framework based on WHO guidance

Background

Influenza surveillance systems vary widely between countries and there is no framework to evaluate national surveillance systems in terms of data generation and dissemination. This study aimed to develop and test a comparative framework for European influenza surveillance.

Methods

Surveillance systems were evaluated qualitatively in five European countries (France, Germany, Italy, Spain, and the United Kingdom) by a panel of influenza experts and researchers from each country. Seven surveillance sub-systems were defined: non-medically attended community surveillance, virological surveillance, community surveillance, outbreak surveillance, primary care surveillance, hospital surveillance, mortality surveillance). These covered a total of 19 comparable outcomes of increasing severity, ranging from non-medically attended cases to deaths, which were evaluated using 5 comparison criteria based on WHO guidance (granularity, timing, representativeness, sampling strategy, communication) to produce a framework to compare the five countries.

Results

France and the United Kingdom showed the widest range of surveillance sub-systems, particularly for hospital surveillance, followed by Germany, Spain, and Italy. In all countries, virological, primary care and hospital surveillance were well developed, but non-medically attended events, influenza cases in the community, outbreaks in closed settings and mortality estimates were not consistently reported or published. The framework also allowed the comparison of variations in data granularity, timing, representativeness, sampling strategy, and communication between countries. For data granularity, breakdown per risk condition were available in France and Spain, but not in the United Kingdom, Germany and Italy. For data communication, there were disparities in the timeliness and accessibility of surveillance data.

Conclusions

This new framework can be used to compare influenza surveillance systems qualitatively between countries to allow the identification of structural differences as well as to evaluate adherence to WHO guidance. The framework may be adapted for other infectious respiratory diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13433-0.

Sociodemographic disparities in COVID-19 seroprevalence across England in the Oxford RCGP primary care sentinel network

OBJECTIVES

To monitor changes in seroprevalence of SARS-CoV-2 antibodies in populations over time and between different demographic groups.

METHODS

A subset of practices in the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) sentinel network provided serum samples, collected when volunteer patients had routine blood tests. We tested these samples for SARS-CoV-2 antibodies using Abbott (Chicago, USA), Roche (Basel, Switzerland) and/or Euroimmun (Luebeck, Germany) assays, and linked the results to the patients' primary care computerised medical records. We report seropositivity by region and age group, and additionally examined the effects of gender, ethnicity, deprivation, rurality, shielding recommendation and smoking status.

RESULTS

We estimated seropositivity from patients aged 18-100 years old, which ranged from 4.1% (95% CI 3.1-5.3%) to 8.9% (95% CI 7.8-10.2%) across the different assays and time periods. We found higher Euroimmun seropositivity in younger age groups, people of Black and Asian ethnicity (compared to white), major conurbations, and non-smokers. We did not observe any significant effect by region, gender, deprivation, or shielding recommendation.

CONCLUSIONS

Our results suggest that prior to the vaccination programme, most of the population remained unexposed to SARS-CoV-2.

Rapidly adapting primary care sentinel surveillance across seven countries in Europe for COVID-19 in the first half of 2020: strengths, challenges, and lessons learned

As the COVID-19 pandemic began in early 2020, primary care influenza sentinel surveillance networks within the Influenza - Monitoring Vaccine Effectiveness in Europe (I-MOVE) consortium rapidly adapted to COVID-19 surveillance. This study maps system adaptations and lessons learned about aligning influenza and COVID-19 surveillance following ECDC / WHO/Europe recommendations and preparing for other diseases possibly emerging in the future. Using a qualitative approach, we describe the adaptations of seven sentinel sites in five European Union countries and the United Kingdom during the first pandemic phase (March–September 2020). Adaptations to sentinel systems were substantial (2/7 sites), moderate (2/7) or minor (3/7 sites). Most adaptations encompassed patient referral and sample collection pathways, laboratory testing and data collection. Strengths included established networks of primary care providers, highly qualified testing laboratories and stakeholder commitments. One challenge was the decreasing number of samples due to altered patient pathways. Lessons learned included flexibility establishing new routines and new laboratory testing. To enable simultaneous sentinel surveillance of influenza and COVID-19, experiences of the sentinel sites and testing infrastructure should be considered. The contradicting aims of rapid case finding and contact tracing, which are needed for control during a pandemic and regular surveillance, should be carefully balanced.

Primary care consultations for respiratory tract symptoms during the COVID-19 pandemic: a cohort study including 70,000 people in South West England

BACKGROUND

Primary care consultations for respiratory tract symptoms including identifying and managing COVID-19 during the pandemic have not been characterized.

METHODS

A retrospective cohort analysis using routinely collected records from 70,431 adults aged 18+ in South England within the Electronic Care and Health Information Analytics (CHIA) database. Total volume and type of consultations (face-to-face, home visits, telephone, email/video, or out of hours) for respiratory tract symptoms between 1 January and 31 July 2020 (during the first wave of the pandemic) were compared with the equivalent period in 2019 for the same cohort. Descriptive statistics were used to summarize consultations by sociodemographic and clinical characteristics, and by COVID-19 diagnosis and outcomes (death, hospitalization, and pneumonia).

RESULTS

Overall consultations for respiratory tract symptoms increased by 229% during the pandemic compared with the preceding year. This included significant increases in telephone consultations by 250%, a 1,574% increase in video/email consultations, 105% increase in home visits, and 92% increase in face-to-face consultations. Nearly 60% of people who presented with respiratory symptoms were tested for COVID-19 and 16% confirmed or clinically suspected to have the virus. Those with complications including pneumonia, requiring hospitalization, and who died were more likely to be seen in-person.

CONCLUSION

During the pandemic, primary care substantially increased consultations for respiratory tract symptoms to identify and manage people with COVID-19. These findings should be balanced against national reports of reduced GP workload for non-COVID care.

Acute respiratory infection rates in primary care anticipate ICU bed occupancy during COVID-19 waves

Background

Bed occupancy in the ICU is a major constraint to in-patient care during COVID-19 pandemic. Diagnoses of acute respiratory infection (ARI) by general practitioners have not previously been investigated as an early warning indicator of ICU occupancy.

Methods

A population-based central health care system registry in the autonomous community of Catalonia, Spain, was used to analyze all diagnoses of ARI related to COVID-19 established by general practitioners and the number of occupied ICU beds in all hospitals from Catalonia between March 26, 2020 and January 20, 2021. The primary outcome was the cross-correlation between the series of COVID-19-related ARI cases and ICU bed occupancy taking into account the effect of bank holidays and weekends. Recalculations were later implemented until March 27, 2022.

Findings

Weekly average incidence of ARI diagnoses increased from 252.7 per 100,000 in August, 2020 to 496.5 in October, 2020 (294.2 in November, 2020), while the average number of ICU beds occupied by COVID-19-infected patients rose from 1.7 per 100,000 to 3.5 in the same period (6.9 in November, 2020). The incidence of ARI detected in the primary care setting anticipated hospital occupancy of ICUs, with a maximum correlation of 17.3 days in advance (95% confidence interval 15.9 to 18.9).

Interpretation

COVID-19-related ARI cases may be a novel warning sign of ICU occupancy with a delay of over two weeks, a latency window period for establishing restrictions on social contacts and mobility to mitigate the propagation of COVID-19. Monitoring ARI cases would enable immediate adoption of measures to prevent ICU saturation in future waves.

Investigating the uptake, effectiveness and safety of COVID-19 vaccines: protocol for an observational study using linked UK national data

INTRODUCTION

The novel coronavirus SARS-CoV-2, which emerged in December 2019, has caused millions of deaths and severe illness worldwide. Numerous vaccines are currently under development of which a few have now been authorised for population-level administration by several countries. As of 20 September 2021, over 48 million people have received their first vaccine dose and over 44 million people have received their second vaccine dose across the UK. We aim to assess the uptake rates, effectiveness, and safety of all currently approved COVID-19 vaccines in the UK.

METHODS AND ANALYSIS

We will use prospective cohort study designs to assess vaccine uptake, effectiveness and safety against clinical outcomes and deaths. Test-negative case-control study design will be used to assess vaccine effectiveness (VE) against laboratory confirmed SARS-CoV-2 infection. Self-controlled case series and retrospective cohort study designs will be carried out to assess vaccine safety against mild-to-moderate and severe adverse events, respectively. Individual-level pseudonymised data from primary care, secondary care, laboratory test and death records will be linked and analysed in secure research environments in each UK nation. Univariate and multivariate logistic regression models will be carried out to estimate vaccine uptake levels in relation to various population characteristics. VE estimates against laboratory confirmed SARS-CoV-2 infection will be generated using a generalised additive logistic model. Time-dependent Cox models will be used to estimate the VE against clinical outcomes and deaths. The safety of the vaccines will be assessed using logistic regression models with an offset for the length of the risk period. Where possible, data will be meta-analysed across the UK nations.

ETHICS AND DISSEMINATION

We obtained approvals from the National Research Ethics Service Committee, Southeast Scotland 02 (12/SS/0201), the Secure Anonymised Information Linkage independent Information Governance Review Panel project number 0911. Concerning English data, University of Oxford is compliant with the General Data Protection Regulation and the National Health Service (NHS) Digital Data Security and Protection Policy. This is an approved study (Integrated Research Application ID 301740, Health Research Authority (HRA) Research Ethics Committee 21/HRA/2786). The Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub meets NHS Digital's Data Security and Protection Toolkit requirements. In Northern Ireland, the project was approved by the Honest Broker Governance Board, project number 0064. Findings will be made available to national policy-makers, presented at conferences and published in peer-reviewed journals.

Triage Strategies for COVID-19 Cases: A Scope Review

In the midst of the pandemic caused by the new coronavirus (SARS-CoV-2), researchers and governmental and non-governmental institutions are mobilizing to implement strategies to face cases of COVID-19. Aim: This study aimed to map the triage strategies for cases of COVID-19, with the purpose of identifying sources in the literature that make it possible to explore the understanding of the strategies in different contexts. A scope review was conducted with searches in the CINAHL Database, PubMed, LILACS and hand-search, considering studies carried out with users of health services and documents published by governmental and non-governmental institutions, between the years 2019 and 2020, resulting in 40 articles for full reading. To explore the key concept, thematic analysis was carried out at two levels: (1) triage strategies, (2) forms and experiences of triage. Five triage strategies were mapped: health services triage; digital triage by remote use of technologies; community triage; home visit triage and airport and port triage. The forms and experiences of mapped triages involved risk classification, diagnosis and definition of conducts or combined. The use of strategies with remote technological resources stands out, as well as the adaptation of existing scales with simple algorithms as a tendency.

COVID-19 Pandemic–Related Reductions in Pediatric Asthma Exacerbations Corresponded with an Overall Decrease in Respiratory Viral Infections

Background

Respiratory viruses, air pollutants, and aeroallergens are all implicated in worsening pediatric asthma symptoms, but their relative contributions to asthma exacerbations are poorly understood. A significant decrease in asthma exacerbations has been observed during the coronavirus disease 2019 pandemic, providing a unique opportunity to study how major asthma triggers correlate with asthma activity.

Objective

To determine whether changes in respiratory viruses, air pollutants, and/or aeroallergens during the coronavirus disease 2019 pandemic were concomitant with decreased asthma exacerbations.

Methods

Health care utilization and respiratory viral testing data between January 1, 2015, and December 31, 2020, were extracted from the Children’s Hospital of Philadelphia Care Network’s electronic health record. Air pollution and allergen data were extracted from US Environmental Protection Agency public databases and a National Allergy Bureau–certified station, respectively. Pandemic data (2020) were compared with historical data.

Results

Recovery of in-person asthma encounters during phased reopening (June 6 to November 15, 2020) was uneven: primary care well and specialty encounters reached 94% and 74% of prepandemic levels, respectively, whereas primary care sick and hospital encounters reached 21% and 40% of prepandemic levels, respectively. During the pandemic, influenza A and influenza B decreased to negligible frequency when compared with prepandemic cases, whereas respiratory syncytial virus and rhinovirus infections decreased to low (though nonnegligible) prepandemic levels, as well. No changes in air pollution or aeroallergen levels relative to historical observations were noted.

Conclusions

Our results suggest that viral respiratory infections are a primary driver of pediatric asthma exacerbations. These findings have broad relevance to both clinical practice and the development of health policies aimed at reducing asthma morbidity.

An Automated Dashboard to Improve Laboratory COVID-19 Diagnostics Management

Background: In response to the COVID-19 pandemic, our microbial diagnostic laboratory located in a university hospital has implemented several distinct SARS-CoV-2 RT-PCR systems in a very short time. More than 148,000 tests have been performed over 12 months, which represents about 405 tests per day, with peaks to more than 1,500 tests per days during the second wave. This was only possible thanks to automation and digitalization, to allow high throughput, acceptable time to results and to maintain test reliability. An automated dashboard was developed to give access to Key Performance Indicators (KPIs) to improve laboratory operational management.

Methods: RT-PCR data extraction of four respiratory viruses—SARS-CoV-2, influenza A and B and RSV—from our laboratory information system (LIS), was automated. This included age, gender, test result, RT-PCR instrument, sample type, reception time, requester, and hospitalization status etc. Important KPIs were identified and the visualization was achieved using an in-house dashboard based on the open-source language R (Shiny).

Results: The dashboard is organized into three main parts. The “Filter” page presents all the KPIs, divided into five sections: (i) general and gender-related indicators, (ii) number of tests and positivity rate, (iii) cycle threshold and viral load, (iv) test durations, and (v) not valid results. Filtering allows to select a given period, a dedicated instrument, a given specimen, an age range or a requester. The “Comparison” page allows a custom charting of all the available variables, which represents more than 182 combination. The “Data” page, gives the user an access to the raw data in tables format, with possibility of filtering, allowing for a deeper analysis and data download. Informations are updated every 4 h.

Conclusions: By giving a rapid access to a huge number of up-to-date information, represented using the most relevant visualization types, without the burden of timely data extraction and analysis, the dashboard represents a reliable and user-friendly tool for operational laboratory management. The dashboard represents a reliable and user-friendly tool improving the decision-making process, resource planning and quality management.

SGLT2i agonist and GLP-1 receptor COMBination therapy in type 2 diabetes: Protocol for a KIDney endpoints real world study-[COMBi-KID Study] (Preprint)

Background

Sodium-glucose cotransporter-2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP-1RAs) are both considered to be part of standard care in the management of glycemia in type 2 diabetes. Recent trial evidence has indicated benefits on primary kidney end points for individual drugs within each medication class. Despite the potential benefits of combining SGLT2is and GLP-1RAs for glycemia management, according to national and international guideline recommendations, there is currently limited data on kidney end points for this drug combination.

Objective

The aims of the study are to assess the real-world effects of combination SGLT2i and GLP-1RA therapies for diabetes management on kidney end points, glycemic control, and weight in people with type 2 diabetes who are being treated with renin-angiotensin system blockade medication.

Methods

This retrospective cohort study will use the electronic health records of people with type 2 diabetes that are registered with general practices covering over 15 million people in England and Wales and are included in the Oxford-Royal College of General Practitioners Research and Surveillance Centre network. A propensity score–matched cohort of prevalent new users of SGLT2is and GLP-1RAs and those who have been prescribed SGLT2is and GLP-1RAs in combination will be identified. They will be matched based on drug histories, comorbidities, and demographics. A repeated-measures, multilevel, linear regression analysis will be performed to compare the mean change (from baseline) in estimated glomerular filtration rate at 12 and 24 months between those who switched to combined therapy and those continuing monotherapy with an SGLT2i or GLP-1RA. The secondary end points will be albuminuria, serum creatinine level, glycated hemoglobin level, and BMI. These will also be assessed for change at the 12- and 24-month follow-ups.

Results

The study is due to commence in March 2022 and is expected to be complete by September 2022.

Conclusions

Our study will be the first to assess the impact of combination SGLT2i and GLP-1RA therapy in type 2 diabetes on primary kidney end points from a real-world perspective.

International Registered Report Identifier (IRRID)

PRR1-10.2196/34206

Transmission of SARS-CoV-2 in the household setting: A prospective cohort study in children and adults in England

OBJECTIVES

To measure secondary attack rates (SARs) in prospectively followed household contacts of paediatric and adult cases of SARS-CoV-2 infection in England.

METHODS

Self-taken nasal swabs from household contacts of PCR confirmed cases of COVID-19  and blood samples  on day 35 were tested for evidence of infection with SARS-CoV-2 virus.

RESULTS

The secondary attack rate (SAR) among 431 contacts of 172 symptomatic index cases  was 33% (95% confidence intervals [CI] 25-40) and was lower from primary cases without respiratory symptoms, 6% (CI 0-14) vs 37% (CI 29-45), p = 0.030. The SAR from index cases <11 years  was  25% (CI 12-38). SARs ranged from 16% (4-28) in contacts <11 years old to 36% (CI 28-45) in contacts aged 19-54 years (p = 0.119). The proportion infected who developed symptoms (78%) was similar by age (p = 0.44) though <19 year olds had fewer mean number of symptoms than adults (p = 0.001) and fewer reported loss of sense of taste or smell (p = 0.0001).

CONCLUSIONS

There are high risks of  transmission of SARS-CoV-2 virus in the home, including those where infection is introduced by a child. The risk of children acquiring infection was lower than that in adults and fewer developed typical symptoms of Covid-19 infection.

Implementation of targeted screening for poverty in a large primary care team in Toronto, Canada: a feasibility study

Background

Poverty has a significant influence on health. Efforts to optimize income and reduce poverty could make a difference to the lives of patients and their families. Routine screening for poverty in primary care is an important first step but rarely occurs in Canada. We aimed to implement a targeted screening and referral process in a large, distributed primary care team in Toronto, Ontario, Canada. The main outcome was the proportion of targeted patients screened.

Methods

This implementation evaluation was conducted with a large community-based primary care team in north Toronto. The primary care team serves relatively wealthy neighborhoods with pockets of poverty. Physicians were invited to participate. We implemented targeted screening by combining census information on neighborhood-level deprivation with postal codes in patient records. For physicians agreeing to participate, we added prompts to screen for poverty to the charts of adult patients living in the most deprived areas. Standardized electronic medical record templates recommended a referral to a team case worker for income optimization, for those patients screening positive. We recorded the number and percentages of participants at each stage, from screening to receiving advice on income optimization.

Results

128 targeted patients with at least one visit (25%) were screened. The primary care team included 86 physicians distributed across 19 clinical locations. Thirty-four physicians (39%) participated. Their practices provided care for 27,290 patients aged 18 or older; 852 patients (3%) were found to be living in the most deprived neighborhoods. 509 (60%) had at least one office visit over the 6 months of follow up. 25 patients (20%) screened positive for poverty, and 13 (52%) were referred. Eight patients (62% of those referred) were ultimately seen by a caseworker for income optimization.

Conclusions

We implemented a targeted poverty screening program combined with resources to optimize income for patients in a large, distributed community-based primary care team. Screening was feasible; however, only a small number of patients were linked to the intervention Further efforts to scale and spread screening and mitigation of poverty are warranted; these should include broadening the targeted population beyond those living in the most deprived areas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-021-01514-9.

Adverse events of interest following influenza vaccination, a comparison of cell culture-based with egg-based alternatives: English sentinel network annual report paper 2019/20

Background

The cell-based quadrivalent influenza vaccine (QIVc) is now offered as an alternative to egg-based quadrivalent (QIVe) and adjuvanted trivalent (aTIV) influenza vaccines in the UK. While post-licensure studies show non-inferiority of cell-based vaccines, it is not known how its safety profile compares to other types of vaccines in real-world use.

Methods

We conducted a retrospective cohort study using computerised medical records from the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) sentinel network database. We used a self-controlled case series design and calculated the relative incidence (RI) of adverse events of interest (AEIs) over different risk periods. We then compared the RIs of AEIs within seven days of vaccination overall and between QIVc and QIVe in the 18–64 years age group, and between QIVc and aTIV in the ≥65 years age group.

Findings

The majority of AEIs occurred within seven days of vaccination, and a seasonal effect was observed. Using QIVc as the reference group, QIVe showed similar incidence of AEIs whereas live attenuated influenza vaccine (LAIV) and aTIV had lower incidence of AEIs. In the stratified analyses, QIVe and aTIV were associated with a 16% lower incidence of AEIs in the seven days post-vaccination in both the 18–64 years and ≥65 years age groups.

Interpretation

Routine sentinel network data allow comparisons of safety profiles of equally suitable seasonal influenza vaccines. The higher incidence of AEIs associated with QIVc suggest monitoring of several seasons would allow robust comparisons to be made.

Funding

Public Health England.

Characterising long COVID: a living systematic review

BACKGROUND

While it is now apparent clinical sequelae (long COVID) may persist after acute COVID-19, their nature, frequency and aetiology are poorly characterised. This study aims to regularly synthesise evidence on long COVID characteristics, to help inform clinical management, rehabilitation strategies and interventional studies to improve long-term outcomes.

METHODS

A living systematic review. Medline, CINAHL (EBSCO), Global Health (Ovid), WHO Global Research on COVID-19 database, LitCovid and Google Scholar were searched till 17 March 2021. Studies including at least 100 people with confirmed or clinically suspected COVID-19 at 12 weeks or more post onset were included. Risk of bias was assessed using the tool produced by Hoy et al. Results were analysed using descriptive statistics and meta-analyses to estimate prevalence.

RESULTS

A total of 39 studies were included: 32 cohort, 6 cross-sectional and 1 case-control. Most showed high or moderate risk of bias. None were set in low-income countries and few included children. Studies reported on 10 951 people (48% female) in 12 countries. Most included previously hospitalised people (78%, 8520/10 951). The longest mean follow-up time was 221.7 (SD: 10.9) days post COVID-19 onset. Over 60 physical and psychological signs and symptoms with wide prevalence were reported, most commonly weakness (41%; 95% CI 25% to 59%), general malaise (33%; 95% CI 15% to 57%), fatigue (31%; 95% CI 24% to 39%), concentration impairment (26%; 95% CI 21% to 32%) and breathlessness (25%; 95% CI 18% to 34%). 37% (95% CI 18% to 60%) of patients reported reduced quality of life; 26% (10/39) of studies presented evidence of reduced pulmonary function.

CONCLUSION

Long COVID is a complex condition with prolonged heterogeneous symptoms. The nature of studies precludes a precise case definition or risk evaluation. There is an urgent need for prospective, robust, standardised, controlled studies into aetiology, risk factors and biomarkers to characterise long COVID in different at-risk populations and settings.

PROSPERO REGISTRATION NUMBER

CRD42020211131.

Primary Care Informatics Response to Covid-19 Pandemic: Adaptation, Progress, and Lessons from Four Countries with High ICT Development

OBJECTIVE

Internationally, primary care practice had to transform in response to the COVID pandemic. Informatics issues included access, privacy, and security, as well as patient concerns of equity, safety, quality, and trust. This paper describes progress and lessons learned.

METHODS

IMIA Primary Care Informatics Working Group members from Australia, Canada, United Kingdom and United States developed a standardised template for collection of information. The template guided a rapid literature review. We also included experiential learning from primary care and public health perspectives.

RESULTS

All countries responded rapidly. Common themes included rapid reductions then transformation to virtual visits, pausing of non-COVID related informatics projects, all against a background of non-standardized digital development and disparate territory or state regulations and guidance. Common barriers in these four and in less-resourced countries included disparities in internet access and availability including bandwidth limitations when internet access was available, initial lack of coding standards, and fears of primary care clinicians that patients were delaying care despite the availability of televisits.

CONCLUSIONS

Primary care clinicians were able to respond to the COVID crisis through telehealth and electronic record enabled change. However, the lack of coordinated national strategies and regulation, assurance of financial viability, and working in silos remained limitations. The potential for primary care informatics to transform current practice was highlighted. More research is needed to confirm preliminary observations and trends noted.

Protocol of the Cologne Corona Surveillance (CoCoS) Study- a prospective population-based cohort study

BACKGROUND

Surveillance strategies are critical to cope with the current SARS-CoV-2 pandemic and to evaluate, as well as adjust government-imposed countermeasures. Incidence estimates are widely based on laboratory confirmed cases reported by health authorities. Prevalence and incidence data of SARS-CoV-2 is still scarce, along with demographic and behavioural factors associated with infection risk.

METHODS

The Cologne Corona Surveillance Study will be conducted in the City of Cologne, which is the fourth-largest city in Germany with a population of approximately 1.1 million. Researchers will apply self-sampling surveillance to a rolling cohort of Cologne residents. Random samples of 6000 Cologne residents 18 years of age and older will be drawn from the registration office. Upon receiving the information and saliva sample kit, participants will be asked to fill out a questionnaire online or via phone, sign written informed consent, and send back written consent, as well as saliva sample. The saliva samples will be tested for SARS-CoV-2 by reverse PCR. The questionnaire will be administered to gather information about personal characteristics such as health status and risks. A second round of testing will take place 6 weeks after the first.

DISCUSSION

Self-administered saliva sampling proved to be a legitimate and feasible alternative to nasopharyngeal swabs taken by health professionals. However, it is unclear whether the targeted response rate of 40% can be achieved and whether the results are representative of the population.

TRIAL REGISTRATION

DRKS.de, German Clinical Trials Register (DRKS), Identifier: DRKS00024046 , Registered on 25 February 2021.

Seroprevalence of SARS-CoV-2 among Blood Donors and Changes after Introduction of Public Health and Social Measures, London, UK

We describe results of testing blood donors in London, UK, for severe acute respiratory disease coronavirus 2 (SARS-CoV-2) IgG before and after lockdown measures. Anonymized samples from donors 17–69 years of age were tested using 3 assays: Euroimmun IgG, Abbott IgG, and an immunoglobulin receptor-binding domain assay developed by Public Health England. Seroprevalence increased from 3.0% prelockdown (week 13, beginning March 23, 2020) to 10.4% during lockdown (weeks 15–16) and 12.3% postlockdown (week 18) by the Abbott assay. Estimates were 2.9% prelockdown, 9.9% during lockdown, and 13.0% postlockdown by the Euroimmun assay and 3.5% prelockdown, 11.8% during lockdown, and 14.1% postlockdown by the receptor-binding domain assay. By early May 2020, nearly 1 in 7 donors had evidence of past SARS-CoV-2 infection. Combining results from the Abbott and Euroimmun assays increased seroprevalence by 1.6%, 2.3%, and 0.6% at the 3 timepoints compared with Euroimmun alone, demonstrating the value of using multiple assays.

Reorganisation of GP surgeries during the COVID-19 outbreak: analysis of guidelines from 15 countries

BACKGROUND

General practitioners (GPs) play a key role in managing the COVID-19 outbreak. However, they may encounter difficulties adapting their practices to the pandemic. We provide here an analysis of guidelines for the reorganisation of GP surgeries during the beginning of the pandemic from 15 countries.

METHODS

A network of GPs collaborated together in a three-step process: (i) identification of key recommendations of GP surgery reorganisation, according to WHO, CDC and health professional resources from health care facilities; (ii) collection of key recommendations included in the guidelines published in 15 countries; (iii) analysis, comparison and synthesis of the results.

RESULTS

Recommendations for the reorganisation of GP surgeries of four types were identified: (i) reorganisation of GP consultations (cancelation of non-urgent consultations, follow-up via e-consultations), (ii) reorganisation of GP surgeries (area partitioning, visual alerts and signs, strict hygiene measures), (iii) reorganisation of medical examinations by GPs (equipment, hygiene, partial clinical examinations, patient education), (iv) reorganisation of GP staff (equipment, management, meetings, collaboration with the local community).

CONCLUSIONS

We provide here an analysis of guidelines for the reorganisation of GP surgeries during the beginning of the COVID-19 outbreak from 15 countries. These guidelines focus principally on clinical care, with less attention paid to staff management, and the area of epidemiological surveillance and research is largely neglected. The differences of guidelines between countries and the difficulty to apply them in routine care, highlight the need of advanced research in primary care. Thereby, primary care would be able to provide recommendations adapted to the real-world settings and with stronger evidence, which is especially necessary during pandemics.

Using Point of Care Testing to estimate influenza vaccine effectiveness in the English primary care sentinel surveillance network

Introduction

Rapid Point of Care Testing (POCT) for influenza could be used to provide information on influenza vaccine effectiveness (IVE) as well as influencing clinical decision-making in primary care.

Methods

We undertook a test negative case control study to estimate the overall and age-specific (6 months-17 years, 18–64 years, ≥65 years old) IVE against medically attended POCT-confirmed influenza. The study took place over the winter of 2019–2020 and was nested within twelve general practices that are part of the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), the English sentinel surveillance network.

Results

648 POCT were conducted. 193 (29.7%) of those who were swabbed had received the seasonal influenza vaccine. The crude unadjusted overall IVE was 46.1% (95% CI: 13.9–66.3). After adjusting for confounders the overall IVE was 26.0% (95% CI: 0–65.5). In total 211 patients were prescribed an antimicrobial after swab testing. Given a positive influenza POCT result, the odds ratio (OR) of receiving an antiviral was 21.1 (95%CI: 2.4–182.2, p = <0.01) and the OR of being prescribed an antibiotic was 0.6 (95%CI: 0.4–0.9, p = <0.01).

Discussion

Using influenza POCT in a primary care sentinel surveillance network to estimate IVE is feasible and provides comparable results to published IVE estimates. A further advantage is that near patient testing of influenza is associated with improvements in appropriate antiviral and antibiotic use. Larger, randomised studies are needed in primary care to see if these trends are still present and to explore their impact on outcomes.

Comparison of Serologic Response of Hospitalized COVID-19 Patients Using 8 Immunoassays

BACKGROUND

In Korea, there were issues regarding the use of immunoassays for anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies to detect infection. So, we compared antibody results of eight kinds of commercial immunoassays using clinical remnant specimens.

METHODS

We compared the results of several immunoassay kits tested on 40 serum samples from 15 confirmed patients and 86 remnant serum samples from clinical laboratory. Eight kinds of IVD kits-four enzyme-linked immunosorbent assay, two lateral flow rapid immunochromatographic assays, and two chemiluminescent immunoassays with one RUO kit were tested.

RESULTS

Among 40 serum samples from 15 coronavirus disease 2019 (COVID-19) patients, 35 yielded at least one positive result for detecting antibodies in the combined assessment. There were inconsistent results in 12 (28%) samples by single immunoassay. Forty samples collected in 2019 before the first COVID-19 Korean case showed negative results except for one equivocal result.

CONCLUSION

The discrepant results obtained with different immunoassay kits in this study show that serological assessment of SARS-CoV-2 by a single immunoassay requires caution not only in detecting infection but also in assessing immunologic status.

The impact of social and physical distancing measures on COVID-19 activity in England: findings from a multi-tiered surveillance system

BackgroundA multi-tiered surveillance system based on influenza surveillance was adopted in the United Kingdom in the early stages of the coronavirus disease (COVID-19) epidemic to monitor different stages of the disease. Mandatory social and physical distancing measures (SPDM) were introduced on 23 March 2020 to attempt to limit transmission.AimTo describe the impact of SPDM on COVID-19 activity as detected through the different surveillance systems.MethodsData from national population surveys, web-based indicators, syndromic surveillance, sentinel swabbing, respiratory outbreaks, secondary care admissions and mortality indicators from the start of the epidemic to week 18 2020 were used to identify the timing of peaks in surveillance indicators relative to the introduction of SPDM. This timing was compared with median time from symptom onset to different stages of illness and levels of care or interactions with healthcare services.ResultsThe impact of SPDM was detected within 1 week through population surveys, web search indicators and sentinel swabbing reported by onset date. There were detectable impacts on syndromic surveillance indicators for difficulty breathing, influenza-like illness and COVID-19 coding at 2, 7 and 12 days respectively, hospitalisations and critical care admissions (both 12 days), laboratory positivity (14 days), deaths (17 days) and nursing home outbreaks (4 weeks).ConclusionThe impact of SPDM on COVID-19 activity was detectable within 1 week through community surveillance indicators, highlighting their importance in early detection of changes in activity. Community swabbing surveillance may be increasingly important as a specific indicator, should circulation of seasonal respiratory viruses increase.

Association between influenza vaccination and hospitalisation or all-cause mortality in people with COVID-19: a retrospective cohort study

INTRODUCTION

Recent evidence suggests that influenza vaccination may offer protection against COVID-19 severity. Our aim was to quantify the association between influenza vaccination status and risk of hospitalisation or all-cause mortality in people diagnosed with COVID-19.

METHODS

A retrospective cohort study using routinely collected health records from patients registered to a General Practitioner (GP) practice in South West England within the Electronic Care and Health Information Analytics database. The cohort included 6921 people with COVID-19 during the first wave of the pandemic (1 January-31 July 2020). Data on influenza vaccination, hospitalisation and all-cause mortality were ascertained through linked clinical and demographic records. We applied propensity score methods (stabilised inverse probability of treatment weight) to quantify the association between influenza vaccination status and COVID-19 outcomes (hospitalisation or all-cause mortality).

RESULTS

2613 (38%) participants received an influenza vaccination between 1 January 2019 and COVID-19 diagnosis. Receipt of influenza vaccination was associated with a significantly lower odds of hospitalisation or all-cause mortality (adjusted OR: 0.85, 95% CI 0.75 to 0.97, p=0.02), and 24% reduced odds of all-cause mortality (adjusted OR: 0.76, 95% CI 0.64 to 0.90).

DISCUSSION

Influenza vaccination was associated with a 15%-24% lower odds of severe COVID-19 outcomes. The current UK influenza vaccination programme needs urgent expansion as an integral component of the ongoing response plans to the COVID-19 pandemic.

Influenza and Respiratory Virus Surveillance, Vaccine Uptake, and Effectiveness at a Time of Cocirculating COVID-19: Protocol for the English Primary Care Sentinel System for 2020-2021

Background

The Oxford–Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) and Public Health England (PHE) are commencing their 54th season of collaboration at a time when SARS-CoV-2 infections are likely to be cocirculating with the usual winter infections.

Objective

The aim of this study is to conduct surveillance of influenza and other monitored respiratory conditions and to report on vaccine uptake and effectiveness using nationally representative surveillance data extracted from primary care computerized medical records systems. We also aim to have general practices collect virology and serology specimens and to participate in trials and other interventional research.

Methods

The RCGP RSC network comprises over 1700 general practices in England and Wales. We will extract pseudonymized data twice weekly and are migrating to a system of daily extracts. First, we will collect pseudonymized, routine, coded clinical data for the surveillance of monitored and unexpected conditions; data on vaccine exposure and adverse events of interest; and data on approved research study outcomes. Second, we will provide dashboards to give general practices feedback about levels of care and data quality, as compared to other network practices. We will focus on collecting data on influenza-like illness, upper and lower respiratory tract infections, and suspected COVID-19. Third, approximately 300 practices will participate in the 2020-2021 virology and serology surveillance; this will include responsive surveillance and long-term follow-up of previous SARS-CoV-2 infections. Fourth, member practices will be able to recruit volunteer patients to trials, including early interventions to improve COVID-19 outcomes and point-of-care testing. Lastly, the legal basis for our surveillance with PHE is Regulation 3 of the Health Service (Control of Patient Information) Regulations 2002; other studies require appropriate ethical approval.

Results

The RCGP RSC network has tripled in size; there were previously 100 virology practices and 500 practices overall in the network and we now have 322 and 1724, respectively. The Oxford–RCGP Clinical Informatics Digital Hub (ORCHID) secure networks enable the daily analysis of the extended network; currently, 1076 practices are uploaded. We are implementing a central swab distribution system for patients self-swabbing at home in addition to in-practice sampling. We have converted all our primary care coding to Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) coding. Throughout spring and summer 2020, the network has continued to collect specimens in preparation for the winter or for any second wave of COVID-19 cases. We have collected 5404 swabs and detected 623 cases of COVID-19 through extended virological sampling, and 19,341 samples have been collected for serology. This shows our preparedness for the winter season.

Conclusions

The COVID-19 pandemic has been associated with a groundswell of general practices joining our network. It has also created a permissive environment in which we have developed the capacity and capability of the national primary care surveillance systems and our unique public health institute, the RCGP and University of Oxford collaboration.

V. R, Jha RM, Kumari A, Gandotra S, Rao V, Faruq M, Kumar S, Reshma G. B, Varma G. N, Roy SS, Sengupta A, Chattopadhyay S, Singhal K, Pradhan S, Jha D, Naushin S, Wadhwa S, Tyagi N, Poojary M, Scaria V, Sivasubbu S. High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next-generation sequencing

The rapid emergence of coronavirus disease 2019 (COVID-19) as a global pandemic affecting millions of individuals globally has necessitated sensitive and high-throughput approaches for the diagnosis, surveillance, and determining the genetic epidemiology of SARS-CoV-2. In the present study, we used the COVIDSeq protocol, which involves multiplex-PCR, barcoding, and sequencing of samples for high-throughput detection and deciphering the genetic epidemiology of SARS-CoV-2. We used the approach on 752 clinical samples in duplicates, amounting to a total of 1536 samples which could be sequenced on a single S4 sequencing flow cell on NovaSeq 6000. Our analysis suggests a high concordance between technical duplicates and a high concordance of detection of SARS-CoV-2 between the COVIDSeq as well as RT-PCR approaches. An in-depth analysis revealed a total of six samples in which COVIDSeq detected SARS-CoV-2 in high confidence which were negative in RT-PCR. Additionally, the assay could detect SARS-CoV-2 in 21 samples and 16 samples which were classified inconclusive and pan-sarbeco positive respectively suggesting that COVIDSeq could be used as a confirmatory test. The sequencing approach also enabled insights into the evolution and genetic epidemiology of the SARS-CoV-2 samples. The samples were classified into a total of 3 clades. This study reports two lineages B.1.112 and B.1.99 for the first time in India. This study also revealed 1,143 unique single nucleotide variants and added a total of 73 novel variants identified for the first time. To the best of our knowledge, this is the first report of the COVIDSeq approach for detection and genetic epidemiology of SARS-CoV-2. Our analysis suggests that COVIDSeq could be a potential high sensitivity assay for the detection of SARS-CoV-2, with an additional advantage of enabling the genetic epidemiology of SARS-CoV-2.

Rapid community point-of-care testing for COVID-19 (RAPTOR-C19): protocol for a platform diagnostic study

BACKGROUND

The aim of RApid community Point-of-care Testing fOR COVID-19 (RAPTOR-C19) is to assess the diagnostic accuracy of multiple current and emerging point-of-care tests (POCTs) for active and past SARS-CoV2 infection in the community setting. RAPTOR-C19 will provide the community testbed to the COVID-19 National DiagnOstic Research and Evaluation Platform (CONDOR).

METHODS

RAPTOR-C19 incorporates a series of prospective observational parallel diagnostic accuracy studies of SARS-CoV2 POCTs against laboratory and composite reference standards in patients with suspected current or past SARS-CoV2 infection attending community settings. Adults and children with suspected current SARS-CoV2 infection who are having an oropharyngeal/nasopharyngeal (OP/NP) swab for laboratory SARS-CoV2 reverse transcriptase Digital/Real-Time Polymerase Chain Reaction (d/rRT-PCR) as part of clinical care or community-based testing will be invited to participate. Adults (≥ 16 years) with suspected past symptomatic infection will also be recruited. Asymptomatic individuals will not be eligible. At the baseline visit, all participants will be asked to submit samples for at least one candidate point-of-care test (POCT) being evaluated (index test/s) as well as an OP/NP swab for laboratory SARS-CoV2 RT-PCR performed by Public Health England (PHE) (reference standard for current infection). Adults will also be asked for a blood sample for laboratory SARS-CoV-2 antibody testing by PHE (reference standard for past infection), where feasible adults will be invited to attend a second visit at 28 days for repeat antibody testing. Additional study data (e.g. demographics, symptoms, observations, household contacts) will be captured electronically. Sensitivity, specificity, positive, and negative predictive values for each POCT will be calculated with exact 95% confidence intervals when compared to the reference standard. POCTs will also be compared to composite reference standards constructed using paired antibody test results, patient reported outcomes, linked electronic health records for outcomes related to COVID-19 such as hospitalisation or death, and other test results.

DISCUSSION

High-performing POCTs for community use could be transformational. Real-time results could lead to personal and public health impacts such as reducing onward household transmission of SARS-CoV2 infection, improving surveillance of health and social care staff, contributing to accurate prevalence estimates, and understanding of SARS-CoV2 transmission dynamics in the population. In contrast, poorly performing POCTs could have negative effects, so it is necessary to undertake community-based diagnostic accuracy evaluations before rolling these out.

TRIAL REGISTRATION

ISRCTN, ISRCTN14226970.

Tracking COVID-19 using online search

Previous research has demonstrated that various properties of infectious diseases can be inferred from online search behaviour. In this work we use time series of online search query frequencies to gain insights about the prevalence of COVID-19 in multiple countries. We first develop unsupervised modelling techniques based on associated symptom categories identified by the United Kingdom’s National Health Service and Public Health England. We then attempt to minimise an expected bias in these signals caused by public interest—as opposed to infections—using the proportion of news media coverage devoted to COVID-19 as a proxy indicator. Our analysis indicates that models based on online searches precede the reported confirmed cases and deaths by 16.7 (10.2–23.2) and 22.1 (17.4–26.9) days, respectively. We also investigate transfer learning techniques for mapping supervised models from countries where the spread of the disease has progressed extensively to countries that are in earlier phases of their respective epidemic curves. Furthermore, we compare time series of online search activity against confirmed COVID-19 cases or deaths jointly across multiple countries, uncovering interesting querying patterns, including the finding that rarer symptoms are better predictors than common ones. Finally, we show that web searches improve the short-term forecasting accuracy of autoregressive models for COVID-19 deaths. Our work provides evidence that online search data can be used to develop complementary public health surveillance methods to help inform the COVID-19 response in conjunction with more established approaches.

One Digital Health: A Unified Framework for Future Health Ecosystems

One Digital Health is a proposed unified structure. The conceptual framework of the One Digital Health Steering Wheel is built around two keys (ie, One Health and digital health), three perspectives (ie, individual health and well-being, population and society, and ecosystem), and five dimensions (ie, citizens’ engagement, education, environment, human and veterinary health care, and Healthcare Industry 4.0). One Digital Health aims to digitally transform future health ecosystems, by implementing a systemic health and life sciences approach that takes into account broad digital technology perspectives on human health, animal health, and the management of the surrounding environment. This approach allows for the examination of how future generations of health informaticians can address the intrinsic complexity of novel health and care scenarios in digitally transformed health ecosystems. In the emerging hybrid landscape, citizens and their health data have been called to play a central role in the management of individual-level and population-level perspective data. The main challenges of One Digital Health include facilitating and improving interactions between One Health and digital health communities, to allow for efficient interactions and the delivery of near–real-time, data-driven contributions in systems medicine and systems ecology. However, digital health literacy; the capacity to understand and engage in health prevention activities; self-management; and collaboration in the prevention, control, and alleviation of potential problems are necessary in systemic, ecosystem-driven public health and data science research. Therefore, people in a healthy One Digital Health ecosystem must use an active and forceful approach to prevent and manage health crises and disasters, such as the COVID-19 pandemic.

A multiplex chemiluminescent immunoassay for serological profiling of COVID-19-positive symptomatic and asymptomatic patients

The COVID-19 pandemic affects more than 81 million people worldwide with over 1.7 million deaths. As the population returns to work, it is critical to develop tests that reliably detect SARS-CoV-2-specific antibodies. Here we present results from a multiplex serology test for assessing the antibody responses to COVID-19. In an initial large cohort, this test shows greater than 99% agreement with COVID-19 PCR test. In a second outpatient cohort consisting of adults and children in Colorado, the IgG responses are more robust in positive/symptomatic participants than in positive/asymptomatic participants, the IgM responses in symptomatic participants are transient and largely fall below the detection limit 30 days after symptom onset, and the levels of IgA against SARS-CoV-2 receptor binding domain are significantly increased in participants with moderate-to-severe symptoms compared to those with mild-to-moderate symptoms or asymptomatic individuals. Our results thus provide insight into serology profiling and the immune response to COVID-19.

Antibody responses to SARS-CoV-2 may be important biomarkers for assessing the risk for viral transmission. Here the authors present serological antibody profiling results of COVID-19 patients using a new multiplex assay to show distinct kinetics and dynamics of IgG, IgM and IgA responses in patients with different disease severity.

Association Between Blood Pressure Control and Coronavirus Disease 2019 Outcomes in 45 418 Symptomatic Patients With Hypertension: An Observational Cohort Study

Supplemental Digital Content is available in the text.

Hypertension has been identified as a risk factor for coronavirus disease 2019 (COVID-19) and associated adverse outcomes. This study examined the association between preinfection blood pressure (BP) control and COVID-19 outcomes using data from 460 general practices in England. Eligible patients were adults with hypertension who were tested or diagnosed with COVID-19. BP control was defined by the most recent BP reading within 24 months of the index date (January 1, 2020). BP was defined as controlled (<130/80 mm Hg), raised (130/80–139/89 mm Hg), stage 1 uncontrolled (140/90–159/99 mm Hg), or stage 2 uncontrolled (≥160/100 mm Hg). The primary outcome was death within 28 days of COVID-19 diagnosis. Secondary outcomes were COVID-19 diagnosis and COVID-19–related hospital admission. Multivariable logistic regression was used to examine the association between BP control and outcomes. Of the 45 418 patients (mean age, 67 years; 44.7% male) included, 11 950 (26.3%) had controlled BP. These patients were older, had more comorbidities, and had been diagnosed with hypertension for longer. A total of 4277 patients (9.4%) were diagnosed with COVID-19 and 877 died within 28 days. Individuals with stage 1 uncontrolled BP had lower odds of COVID-19 death (odds ratio, 0.76 [95% CI, 0.62–0.92]) compared with patients with well-controlled BP. There was no association between BP control and COVID-19 diagnosis or hospitalization. These findings suggest BP control may be associated with worse COVID-19 outcomes, possibly due to these patients having more advanced atherosclerosis and target organ damage. Such patients may need to consider adhering to stricter social distancing, to limit the impact of COVID-19 as future waves of the pandemic occur.

Excess mortality in the first COVID pandemic peak: cross-sectional analyses of the impact of age, sex, ethnicity, household size, and long-term conditions in people of known SARS-CoV-2 status in England

Background

The SARS-CoV-2 pandemic has passed its first peak in Europe.

Aim

To describe the mortality in England and its association with SARS-CoV-2 status and other demographic and risk factors.

Design and setting

Cross-sectional analyses of people with known SARS-CoV-2 status in the Oxford RCGP Research and Surveillance Centre (RSC) sentinel network.

Method

Pseudonymised, coded clinical data were uploaded from volunteer general practice members of this nationally representative network (n = 4 413 734). All-cause mortality was compared with national rates for 2019, using a relative survival model, reporting relative hazard ratios (RHR), and 95% confidence intervals (CI). A multivariable adjusted odds ratios (OR) analysis was conducted for those with known SARS-CoV-2 status (n = 56 628, 1.3%) including multiple imputation and inverse probability analysis, and a complete cases sensitivity analysis.

Results

Mortality peaked in week 16. People living in households of ≥9 had a fivefold increase in relative mortality (RHR = 5.1, 95% CI = 4.87 to 5.31, P<0.0001). The ORs of mortality were 8.9 (95% CI = 6.7 to 11.8, P<0.0001) and 9.7 (95% CI = 7.1 to 13.2, P<0.0001) for virologically and clinically diagnosed cases respectively, using people with negative tests as reference. The adjusted mortality for the virologically confirmed group was 18.1% (95% CI = 17.6 to 18.7). Male sex, population density, black ethnicity (compared to white), and people with long-term conditions, including learning disability (OR = 1.96, 95% CI = 1.22 to 3.18, P = 0.0056) had higher odds of mortality.

Conclusion

The first SARS-CoV-2 peak in England has been associated with excess mortality. Planning for subsequent peaks needs to better manage risk in males, those of black ethnicity, older people, people with learning disabilities, and people who live in multi-occupancy dwellings.

COVID-19 Surveillance in a Primary Care Sentinel Network: In-Pandemic Development of an Application Ontology

Background

Creating an ontology for COVID-19 surveillance should help ensure transparency and consistency. Ontologies formalize conceptualizations at either the domain or application level. Application ontologies cross domains and are specified through testable use cases. Our use case was an extension of the role of the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) to monitor the current pandemic and become an in-pandemic research platform.

Objective

This study aimed to develop an application ontology for COVID-19 that can be deployed across the various use-case domains of the RCGP RSC research and surveillance activities.

Methods

We described our domain-specific use case. The actor was the RCGP RSC sentinel network, the system was the course of the COVID-19 pandemic, and the outcomes were the spread and effect of mitigation measures. We used our established 3-step method to develop the ontology, separating ontological concept development from code mapping and data extract validation. We developed a coding system–independent COVID-19 case identification algorithm. As there were no gold-standard pandemic surveillance ontologies, we conducted a rapid Delphi consensus exercise through the International Medical Informatics Association Primary Health Care Informatics working group and extended networks.

Results

Our use-case domains included primary care, public health, virology, clinical research, and clinical informatics. Our ontology supported (1) case identification, microbiological sampling, and health outcomes at an individual practice and at the national level; (2) feedback through a dashboard; (3) a national observatory; (4) regular updates for Public Health England; and (5) transformation of a sentinel network into a trial platform. We have identified a total of 19,115 people with a definite COVID-19 status, 5226 probable cases, and 74,293 people with possible COVID-19, within the RCGP RSC network (N=5,370,225).

Conclusions

The underpinning structure of our ontological approach has coped with multiple clinical coding challenges. At a time when there is uncertainty about international comparisons, clarity about the basis on which case definitions and outcomes are made from routine data is essential.

Comparing the incidence of common adverse events of interest following influenza vaccination in the first season adjuvanted trivalent immunisation was introduced: English sentinel network annual report paper 2018/19 (Preprint)

Background

Vaccination is the most effective form of prevention of seasonal influenza; the United Kingdom has a national influenza vaccination program to cover targeted population groups. Influenza vaccines are known to be associated with some common minor adverse events of interest (AEIs), but it is not known if the adjuvanted trivalent influenza vaccine (aTIV), first offered in the 2018/2019 season, would be associated with more AEIs than other types of vaccines.

Objective

We aim to compare the incidence of AEIs associated with different types of seasonal influenza vaccines offered in the 2018/2019 season.

Methods

We carried out a retrospective cohort study using computerized medical record data from the Royal College of General Practitioners Research and Surveillance Centre sentinel network database. We extracted data on vaccine exposure and consultations for European Medicines Agency–specified AEIs for the 2018/2019 influenza season. We used a self-controlled case series design; computed relative incidence (RI) of AEIs following vaccination; and compared the incidence of AEIs associated with aTIV, the quadrivalent influenza vaccine, and the live attenuated influenza vaccine. We also compared the incidence of AEIs for vaccinations that took place in a practice with those that took place elsewhere.

Results

A total of 1,024,160 individuals received a seasonal influenza vaccine, of which 165,723 individuals reported a total of 283,355 compatible symptoms in the 2018/2019 season. Most AEIs occurred within 7 days following vaccination, with a seasonal effect observed. Using aTIV as the reference group, the quadrivalent influenza vaccine was associated with a higher incidence of AEIs (RI 1.46, 95% CI 1.41-1.52), whereas the live attenuated influenza vaccine was associated with a lower incidence of AEIs (RI 0.79, 95% CI 0.73-0.83). No effect of vaccination setting on the incidence of AEIs was observed.

Conclusions

Routine sentinel network data offer an opportunity to make comparisons between safety profiles of different vaccines. Evidence that supports the safety of newer types of vaccines may be reassuring for patients and could help improve uptake in the future.

Disparities in the excess risk of mortality in the first wave of COVID-19: Cross sectional study of the English sentinel network

OBJECTIVES

Few studies report contributors to the excess mortality in England during the first wave of coronavirus disease 2019 (COVID-19) infection. We report the absolute excess risk (AER) of mortality and excess mortality rate (EMR) from a nationally representative COVID-19 sentinel surveillance network including known COVID-19 risk factors in people aged 45 years and above.

METHODS

Pseudonymised, coded clinical data were uploaded from contributing primary care providers (N = 1,970,314, ≥45years). We calculated the AER in mortality by comparing mortality for weeks 2 to 20 this year with mortality data from the Office for National Statistics (ONS) from 2018 for the same weeks. We conducted univariate and multivariate analysis including preselected variables. We report AER and EMR, with 95% confidence intervals (95% CI).

RESULTS

The AER of mortality was 197.8/10,000 person years (95%CI:194.30-201.40). The EMR for male gender, compared with female, was 1.4 (95%CI:1.35-1.44, p<0.00); for our oldest age band (≥75 years) 10.09 (95%CI:9.46-10.75, p<0.00) compared to 45-64 year olds; Black ethnicity's EMR was 1.17 (95%CI: 1.03-1.33, p<0.02), reference white; and for dwellings with ≥9 occupants 8.01 (95%CI: 9.46-10.75, p<0.00). Presence of all included comorbidities significantly increased EMR. Ranked from lowest to highest these were: hypertension, chronic kidney disease, chronic respiratory and heart disease, and cancer or immunocompromised.

CONCLUSIONS

The absolute excess mortality was approximately 2 deaths per 100 person years in the first wave of COVID-19. More personalised shielding advice for any second wave should include ethnicity, comorbidity and household size as predictors of risk.

Epidemiologic surveillance for controlling Covid-19 pandemic: types, challenges and implications

The objectives of the study was to determine the types, challenges and implications of surveillance methods for controlling Covid-19 pandemic. An integrative article review was done. The source of data were documents from WHO, Euro-surveillance, CDC, Saudi CDC, MOH, and journals from PubMed, Medline, etc. The inclusion searching criteria were surveillance, Covid-19, types, benefits and challenges, during the period 2005-2020. Published studies, reviews and guidelines that determined these criteria were collected. Data extraction and analysis were completed for all included articles. A critical appraisal was done based on the University of Michigan Practice Guideline's levels of evidence. The final sample for the integrative review comprised 30 studies. Results revealed that types of Covid-9 surveillance includes routine surveillance (comprehensive, case-based, and aggregated weakly methods), active, wildlife, syndromic, sentinel and sentinel-syndromic methods. Laboratory and hospital-based surveillance are another important types. Help-lines, surveys, participatory electronic, digital and event-based surveillance are relatively new cost-effective methods. Many surveillance indicators can be calculated. Timely and accurate of surveillance data is an essential element for effective Covid-19 interventions. Regarding challenges, the quality of surveillance in developing countries is constrained by resources and training. The main limitations of surveillance are under-ascertainment/under-reporting, lack of timeliness and completeness of surveillance data. In conclusion, surveillance is a cornerstones for controlling Covid-19 pandemic. Enhancing Covid-19 surveillance is vital for rapid cases detection, containing spread & ending pandemic.

Desafios e propostas para ampliação da testagem e diagnóstico para COVID-19 no Brasil

Resumo O contexto brasileiro de desigualdades sociais e barreiras no acesso aos serviços de saúde pode agravar a situação da pandemia de COVID-19, que já afeta todos os estados da federação, com a curva crescente de aumento de casos confirmados e mortes. O governo dos países e os agentes do campo científico têm buscado evidências para as melhores práticas de prevenção e controle da transmissão, e cuidado da infecção e doença, incluindo medidas de diagnóstico, tratamento e de atenção à saúde. A estratégia de testagem em larga escala, visando o diagnóstico precoce, quarentena dos casos leves identificados, bem como dos contactantes, e cuidado adequado dos casos graves, tem sido revisada e indicada como uma das medidas eficientes para o controle da pandemia em vários países do mundo. O artigo tem como objetivo discutir os desafios da testagem e do diagnóstico de COVID-19 no Brasil.

Validation and performance comparison of three SARS-CoV-2 antibody assays

Serology testing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is increasingly being used during the current pandemic of coronavirus disease 2019 (COVID-19), although its clinical and epidemiologic utilities are still debatable. Characterizing these assays provides scientific basis to best use them. The current study assessed one chemiluminescent assay (Abbott COVID-2 IgG) and two lateral flow assays (STANDARD Q [SQ] IgM/IgG Duo and Wondfo total antibody test) using 113 blood samples from 71 PCR-confirmed COVID-19 hospitalized patients, 119 samples with potential cross-reactions, and 1068 negative controls including 942 pre-pandemic samples. SARS-CoV-2 IgM antibodies became detectable 3-4 days post-symptom onset using SQ IgM test and IgG antibodies were first detected 5-6 days post-onset using SQ IgG. Abbott IgG and Wondfo Total were able to detect antibodies 7 to 8 days post-onset. After 14 days post-symptom onset, the SQ IgG, Abbott IgG and Wondfo Total tests were able to detect antibodies from 100% of the PCR-confirmed patients in this series; 87.5% sensitivity for SQ IgM. Overall agreement was 88.5% between SQ IgM/IgG and Wondfo Total and 94.6% between SQ IgG and Abbott IgG. No cross-reaction due to recent sera with three of the endemic coronaviruses was observed. Viral hepatitis and autoimmune samples were the main source of limited cross-reactions. The specificities were 100% for SQ IgG and Wondfo Total, 99.62% for Abbott IgG, and 98.87% for SQ IgM. These findings demonstrated high sensitivity and specificity of appropriately validated SARS-CoV-2 serologic assays with implications for clinical use and epidemiological seroprevalence studies.

Predicting SARS-CoV-2 Infection Trend Using Technical Analysis Indicators

OBJECTIVES

Coronavirus disease 2019 (COVID-19) pandemic is a global health emergency caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study aimed to evaluate whether technical analysis (TA) indicators, commonly used in the financial market to spot security price trend reversals, might be proficiently used also to anticipate a possible increase of SARS-Cov-2 spread.

METHODS

Analysis was performed on datasets from Italy, Iran, and Brazil. TA indicators tested were: (1) the combined use of a faster (3-d) and a slower (20-d) simple moving averages (SMA), (2) the moving average converge/divergence (MACD), and (3) the divergence in the direction of the number of new daily cases trend and the corresponding MACD histogram.

RESULTS

We found that the use of both fast/slow SMAs and MACD provided a reliable signal of trend inversion of SARS-Cov-2 spread. Results were consistent for all the 3 countries considered. The trend reversals signaled by the indicators were always followed by a sustained trend persistence until a new signal of reversal appeared.

CONCLUSIONS

TA indicators tested here proved to be reliable tools to identify in the short mid-term a subsequent change of direction of viral spread trend either downward, upward, or sideward.

Managing COVID-19 within and across health systems: why we need performance intelligence to coordinate a global response

Background

The COVID-19 pandemic is a complex global public health crisis presenting clinical, organisational and system-wide challenges. Different research perspectives on health are needed in order to manage and monitor this crisis. Performance intelligence is an approach that emphasises the need for different research perspectives in supporting health systems’ decision-makers to determine policies based on well-informed choices. In this paper, we present the viewpoint of the Innovative Training Network for Healthcare Performance Intelligence Professionals (HealthPros) on how performance intelligence can be used during and after the COVID-19 pandemic.

Discussion

A lack of standardised information, paired with limited discussion and alignment between countries contribute to uncertainty in decision-making in all countries. Consequently, a plethora of different non-data-driven and uncoordinated approaches to address the outbreak are noted worldwide. Comparative health system research is needed to help countries shape their response models in social care, public health, primary care, hospital care and long-term care through the different phases of the pandemic. There is a need in each phase to compare context-specific bundles of measures where the impact on health outcomes can be modelled using targeted data and advanced statistical methods. Performance intelligence can be pursued to compare data, construct indicators and identify optimal strategies. Embracing a system perspective will allow countries to take coordinated strategic decisions while mitigating the risk of system collapse.A framework for the development and implementation of performance intelligence has been outlined by the HealthPros Network and is of pertinence. Health systems need better and more timely data to govern through a pandemic-induced transition period where tensions between care needs, demand and capacity are exceptionally high worldwide. Health systems are challenged to ensure essential levels of healthcare towards all patients, including those who need routine assistance.

Conclusion

Performance intelligence plays an essential role as part of a broader public health strategy in guiding the decisions of health system actors on the implementation of contextualised measures to tackle COVID-19 or any future epidemic as well as their effect on the health system at large. This should be based on commonly agreed-upon standardised data and fit-for-purpose indicators, making optimal use of existing health information infrastructures. The HealthPros Network can make a meaningful contribution.

Dynamics of Population Immunity Due to the Herd Effect in the COVID-19 Pandemic

The novel Coronavirus 2 Severe Acute Respiratory Syndrome (SARS-Cov-2) has led to the Coronavirus Disease 2019 (COVID-19) pandemic, which has surprised health authorities around the world, quickly producing a global health crisis. Different actions to cope with this situation are being developed, including confinement, different treatments to improve symptoms, and the creation of the first vaccines. In epidemiology, herd immunity is presented as an area that could also solve this new global threat. In this review, we present the basis of herd immunology, the dynamics of infection transmission that induces specific immunity, and how the application of immunoepidemiology and herd immunology could be used to control the actual COVID-19 pandemic, along with a discussion of its effectiveness, limitations, and applications.

Risk factors for SARS-CoV-2 among patients in the Oxford Royal College of General Practitioners Research and Surveillance Centre primary care network: a cross-sectional study

BACKGROUND

There are few primary care studies of the COVID-19 pandemic. We aimed to identify demographic and clinical risk factors for testing positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre primary care network.

METHODS

We analysed routinely collected, pseudonymised data for patients in the RCGP Research and Surveillance Centre primary care sentinel network who were tested for SARS-CoV-2 between Jan 28 and April 4, 2020. We used multivariable logistic regression models with multiple imputation to identify risk factors for positive SARS-CoV-2 tests within this surveillance network.

FINDINGS

We identified 3802 SARS-CoV-2 test results, of which 587 were positive. In multivariable analysis, male sex was independently associated with testing positive for SARS-CoV-2 (296 [18·4%] of 1612 men vs 291 [13·3%] of 2190 women; adjusted odds ratio [OR] 1·55, 95% CI 1·27-1·89). Adults were at increased risk of testing positive for SARS-CoV-2 compared with children, and people aged 40-64 years were at greatest risk in the multivariable model (243 [18·5%] of 1316 adults aged 40-64 years vs 23 [4·6%] of 499 children; adjusted OR 5·36, 95% CI 3·28-8·76). Compared with white people, the adjusted odds of a positive test were greater in black people (388 [15·5%] of 2497 white people vs 36 [62·1%] of 58 black people; adjusted OR 4·75, 95% CI 2·65-8·51). People living in urban areas versus rural areas (476 [26·2%] of 1816 in urban areas vs 111 [5·6%] of 1986 in rural areas; adjusted OR 4·59, 95% CI 3·57-5·90) and in more deprived areas (197 [29·5%] of 668 in most deprived vs 143 [7·7%] of 1855 in least deprived; adjusted OR 2·03, 95% CI 1·51-2·71) were more likely to test positive. People with chronic kidney disease were more likely to test positive in the adjusted analysis (68 [32·9%] of 207 with chronic kidney disease vs 519 [14·4%] of 3595 without; adjusted OR 1·91, 95% CI 1·31-2·78), but there was no significant association with other chronic conditions in that analysis. We found increased odds of a positive test among people who are obese (142 [20·9%] of 680 people with obesity vs 171 [13·2%] of 1296 normal-weight people; adjusted OR 1·41, 95% CI 1·04-1·91). Notably, active smoking was linked with decreased odds of a positive test result (47 [11·4%] of 413 active smokers vs 201 [17·9%] of 1125 non-smokers; adjusted OR 0·49, 95% CI 0·34-0·71).

INTERPRETATION

A positive SARS-CoV-2 test result in this primary care cohort was associated with similar risk factors as observed for severe outcomes of COVID-19 in hospital settings, except for smoking. We provide evidence of potential sociodemographic factors associated with a positive test, including deprivation, population density, ethnicity, and chronic kidney disease.

FUNDING

Wellcome Trust.