Segmentation and shielding of the most vulnerable members of the population as elements of an exit strategy from COVID-19 lockdown

Improving uptake of population health management through scalable analysis of linked electronic health data

Population Health Management - often abbreviated to PHM - is a relatively new approach for healthcare planning, requiring the application of analytical techniques to linked patient level data. Despite expectations for greater uptake of PHM, there is a deficit of available solutions to help health services embed it into routine use. This paper concerns the development, application and use of an interactive tool which can be linked to a healthcare system's data warehouse and employed to readily perform key PHM tasks such as population segmentation, risk stratification, and deriving various performance metrics and descriptive summaries. Developed through open-source code in a large healthcare system in South West England, and used by others around the country, this paper demonstrates the importance of a scalable, purpose-built solution for improving the uptake of PHM in health services.

The dangers of having only one pandemic exit strategy

BACKGROUND

When it comes to pandemic response, preparation can be the key. Between 2020 and 2024, the fast-paced development of COVID-19-often compounded by pubic policies' failures to reflect the latest reality and the public's divergent reactions to the pandemic and the policies-means that society should prepare for exit strategies that can reflect the reality of the pandemic and the interests of the people. Yet oftentimes societies only have one exit strategy with limited scope. This paper investigates the dangers of having only one pandemic exit strategy for pandemics like COVID-19.

METHODS

Analyses were based on a review of the literature on COVID-19 exit strategies and our own research. The PubMed literature search focused on two concepts-"COVID-19″ and "exit strategy"-and was limited to peer-reviewed papers published between 2020 and 2024 in English.

RESULTS

A total of 31 articles were included in the final review. Analyses showed that existing studies on COVID-19 exit strategies often focused on using the modelling method to gauge one exit strategy. Exit strategies were often discussed in the context of implementing, easing, or lifting specific pharmaceutical or non-pharmaceutical interventions. Staged and country-wide coordinated exit strategies were also discussed in the literature, both of which were often deemed as comparatively rigorous options compared to single or stand-alone exit strategies. Drawing on the overall development of COVID-19 and our own research, we presented and discussed the importance of having multiple exit strategies that are considerate of all possible pandemic trajectories, diverse interests of the public, and the communication challenges officials might face in introducing or implementing pandemic policies.

CONCLUSION

This paper underscored the importance of having multiple exit strategies for societies to prepare for pandemics. The insights of this study can help inform health policies so that they can more comprehensively and compassionately protect the needs and wants of the "public" in public health, particularly in grave times like COVID-19.

Non-pharmaceutical interventions to reduce COVID-19 transmission in the UK: a rapid mapping review and interactive evidence gap map

BACKGROUND

Non-pharmaceutical interventions (NPIs) were crucial in the response to the COVID-19 pandemic, although uncertainties about their effectiveness remain. This work aimed to better understand the evidence generated during the pandemic on the effectiveness of NPIs implemented in the UK.

METHODS

We conducted a rapid mapping review (search date: 1 March 2023) to identify primary studies reporting on the effectiveness of NPIs to reduce COVID-19 transmission. Included studies were displayed in an interactive evidence gap map.

RESULTS

After removal of duplicates, 11 752 records were screened. Of these, 151 were included, including 100 modelling studies but only 2 randomized controlled trials and 10 longitudinal observational studies.Most studies reported on NPIs to identify and isolate those who are or may become infectious, and on NPIs to reduce the number of contacts. There was an evidence gap for hand and respiratory hygiene, ventilation and cleaning.

CONCLUSIONS

Our findings show that despite the large number of studies published, there is still a lack of robust evaluations of the NPIs implemented in the UK. There is a need to build evaluation into the design and implementation of public health interventions and policies from the start of any future pandemic or other public health emergency.

Herd Immunity to Fight Against COVID-19: A Narrative Review

The advent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its consequent illness, coronavirus disease 2019 (COVID-19), has revealed the severe impact of new, contagious pathogens on the population throughout the globe. Here, we describe the fundamental notions of herd immunity and discuss their consequences from the perspective of COVID-19, along with the obstacles to acquiring herd immunity. SARS-CoV-2 causes COVID-19, a contagious respiratory infection. It is a major global health issue, with more than 179 million positive cases and 3.8 million deaths globally. It has impacted more than 159 countries; hence, the World Health Organization designated it a pandemic. Different vaccines have been developed against coronavirus to slow the spread of this deadly virus. Immunizing people against coronavirus is the key to getting through this infectious virus. The central concept of this review article is the effect of vaccinating a large population to achieve herd immunity and the reasons for the delay in developing herd immunity. Herd immunity can prove highly beneficial for dealing with reinfection. Moreover, it can reduce the severity of the reinfection in many people who are twice infected with COVID-19. Herd immunity can prevent people in the high-risk group such as immunocompromised individuals; those on immunosuppressants; organ transplant recipients; particular age groups such as neonates, infants, toddlers, and elderly; those with impaired immunity; those with anaphylaxis reactions; and people with chronic diseases. However, due to repeated mutations of the virus, it is evolving into new strains with more severity. Its consequences on the immune system and response to a vaccine are still a big challenge to overcome. How new variants of COVID-19 impacted herd immunity needs to be investigated. The duration required for the development of herd immunity and how long it would last is still under research, along with the number of doses needed, booster doses, and the proportion of the population to be vaccinated.

Antigenic evolution of SARS-CoV-2 in immunocompromised hosts

OBJECTIVES/AIMS

Prolonged infections of immunocompromised individuals have been proposed as a crucial source of new variants of SARS-CoV-2 during the COVID-19 pandemic. In principle, sustained within-host antigenic evolution in immunocompromised hosts could allow novel immune escape variants to emerge more rapidly, but little is known about how and when immunocompromised hosts play a critical role in pathogen evolution.

MATERIALS AND METHODS

Here, we use a simple mathematical model to understand the effects of immunocompromised hosts on the emergence of immune escape variants in the presence and absence of epistasis.

CONCLUSIONS

We show that when the pathogen does not have to cross a fitness valley for immune escape to occur (no epistasis), immunocompromised individuals have no qualitative effect on antigenic evolution (although they may accelerate immune escape if within-host evolutionary dynamics are faster in immunocompromised individuals). But if a fitness valley exists between immune escape variants at the between-host level (epistasis), then persistent infections of immunocompromised individuals allow mutations to accumulate, therefore, facilitating rather than simply speeding up antigenic evolution. Our results suggest that better genomic surveillance of infected immunocompromised individuals and better global health equality, including improving access to vaccines and treatments for individuals who are immunocompromised (especially in lower- and middle-income countries), may be crucial to preventing the emergence of future immune escape variants of SARS-CoV-2.

Cognitive factors influenced physical distancing adherence during the COVID-19 pandemic in a population-specific way

Even early in the COVID-19 pandemic, adherence to physical distancing measures was variable, exposing some communities to elevated risk. While cognitive factors from the Health Belief Model (HBM) and resilience correlate with compliance with physical distancing, external conditions may preclude full compliance with physical distancing guidelines. Our objective was to identify HBM and resilience constructs that could be used to improve adherence to physical distancing even when full compliance is not possible. We examined adherence as expressed through 7-day non-work, non-household contact rates in two cohorts: 1) adults in households with children from Minnesota and Iowa; and 2) adults ≥50 years-old from Minnesota, one-third of whom had Parkinson's disease. We identified multiple cognitive factors associated with physical distancing adherence, specifically perceived severity, benefits, self-efficacy, and barriers. However, the magnitude, and occasionally the direction, of these associations was population-dependent. In Cohort 1, perceived self-efficacy for remaining 6-feet from others was associated with a 29% lower contact rate (RR 0.71; 95% CI 0.65, 0.77). This finding was consistent across all race/ethnicity and income groups we examined. The barriers to adherence of having a child in childcare and having financial concerns had the largest effects among individuals from marginalized racial and ethnic groups and high-income households. In Cohort 2, self-efficacy to quarantine/isolate was associated with a 23% decrease in contacts (RR 0.77; 95% CI 0.66, 0.89), but upon stratification by education level, the association was only present for those with at least a Bachelor's degree. Education also modified the effect of the barrier to adherence leaving home for work, increasing contacts among those with a Bachelor's degree and reducing contacts among those without. Our findings suggest that public health messaging tailored to the identified cognitive factors has the potential to improve physical distancing adherence, but population-specific needs must be considered to maximize effectiveness.

Exit strategies from lockdowns due to COVID-19: a scoping review

INTRODUCTION

In response to the ongoing COVID-19 pandemic, countries have adopted various degrees of restrictive measures on people to reduce COVID-19 transmission. These measures have had significant social and economic costs. In the absence of therapeutics, and low vaccination coverage, strategies for a safe exit plan from a lockdown are required to mitigate the transmission and simultaneously re-open societies. Most countries have outlined or have implemented lockdown exit plans. The objective of this scoping review is to (a) identify and map the different strategies for exit from lockdowns, (b) document the effects of these exit strategies, and (c) discuss features of successful exit strategies based on the evidence.

METHODS

A five-step approach was used in this scoping review: (a) identifying the research question and inclusion/exclusion criteria; (b) searching the literature using keywords within PubMed and WHO databases; (c) study selection; (d) data extraction; (e) collating results and qualitative synthesis of findings.

RESULTS

Of the 406 unique studies found, 107 were kept for full-text review. Studies suggest the post-peak period as optimal timing for an exit, supplemented by other triggers such as sufficient health system capacity, and increased testing rate. A controlled and step-wise exit plan which is flexible and guided by information from surveillance systems is optimal. Studies recommend continued use of non-pharmaceutical interventions such as physical distancing, use of facemasks, and hygiene measures, in different combinations when exiting from a lockdown, even after optimal vaccination coverage has been attained.

CONCLUSION

Reviewed studies have suggested adopting a multi-pronged strategy consisting of different approaches depending on the context. Among the different exit strategies reviewed (phase-wise exit, hard exit, and constant cyclic patterns of lockdown), phase-wise exit appears to be the optimal exit strategy.

Risk of severe COVID-19 infection in persons with diabetes during the first and second waves in Denmark: A nationwide cohort study

OBJECTIVE

Coronavirus disease-2019 (COVID-19) increases risk of hospitalization and death in diabetes and diabetes-related conditions. We examined the temporal trends in COVID-19-related hospitalization and mortality in the total Danish population by diabetes and diabetes-related conditions in the two first waves of COVID-19 in Denmark.

MATERIALS AND METHODS

We identified all persons with diabetes in the whole Danish population using national registries. COVID-19-related risks of hospitalization and death were assessed using Cox regression analysis in wave 1 (1 March-31 August 2020) and wave 2 (1 September 2020-28 February 2021) of the pandemic for persons with (n=321,933) and without diabetes (n=5,479,755). Analyses were stratified according to status of hypertension, obesity, cardiovascular and microvascular disease.

RESULTS

The cumulative incidence of COVID-19 hospitalization increased from wave 1 to wave 2 in both persons without (from 4 to 10 in 10,000) and with diabetes (from 16 to 54 per 10,000). The relative risk of hospitalization, however, increased more in patients with diabetes compared to persons without (age-, sex- and co-morbidity-adjusted HR [aHR] 1.40 (95% CI 1.27, 1.55) versus 1.76 (1.65, 1.87), p<0.001 for interaction with wave). The mortality rate, according to the whole population, increased similarly in persons without and with diabetes from wave 1 to wave 2 (from 0.63 to 1.5 versus from 4.3 to 10 in 10,000; aHR 1.65; 1.34, 2.03 and 1.64; 1.43, 1.88). However, when mortality was restricted to the hospitalized population, the crude mortality fell from 26.8% to 19.6% in persons with diabetes, while only a minor decrease was seen in persons without diabetes (from 16.7% to 15.5%).

CONCLUSION

The risk of COVID-19-related hospitalization increased more in persons with than without diabetes from wave 1 to wave 2 of the COVID-19 pandemic in the Danish population. However, mortality according to the whole population did not change, due to reduced mortality among hospitalized persons with diabetes.

Risk of COVID-19 in shielded and nursing care home patients: a cohort study in general practice

Background

COVID-19 cases were first detected in the UK in January 2020 and vulnerable patients were asked to shield from March to reduce their risk of COVID-19 infection.

Aim

To determine the risk and determinants of COVID-19 diagnosis in shielded versus non-shielded groups, adjusted for key comorbidities not explained by shielding.

Design & setting

Retrospective cohort study of adults with COVID-19 infection between 1 February 2020 and 15 May 2020 in west London.

Method

Individuals diagnosed with COVID-19 were identified in SystmOne records using clinical codes. Infection risks were adjusted for sociodemographic factors, nursing home status, and comorbidities.

Results

Of 57 713 adults, 573 (1%) individuals were identified as shielded and 1074 adults had documented COVID-19 infections (1.9%). COVID-19 infection rate in the shielded group individuals compared with non-shielded adult individuals was 6.5% (n = 37/573) versus 1.8% (n = 1037/57 140), P<0.001. A multivariable fully adjusted Cox proportional hazards (CPH) regression identified that COVID-19 infection was increased with shielding status (adjusted hazard ratio [aHR] 1.52; 95% confidence interval [CI] = 1.00 to 2.30; P = 0.048). Other determinants of COVID-19 infection included nursing home residency (aHR 7.05; 95% CI = 4.22 to 11.77; P<0.001); Black African (aHR 2.52; 95% CI = 1.99 to 3.18; P<0.001), Other (aHR 1.74; 95% CI = 1.42 to 2.13; P<0.001), Non-stated (aHR 1.70; 95% CI = 1.02 to 2.84; P = 0.04), or South Asian ethnic group (aHR 1.46; 95% CI = 1.10 to 1.93; P = 0.01); history of respiratory disease (aHR 1.51; 95% CI = 1.06 to 2.16; P = 0.02); deprivation (third versus least deprived Index of Multiple Deprivation [IMD] quintile) (aHR 1.25 ; 95% CI = 1.01 to 1.56; P = 0.05); obesity (body mass index [BMI] >30 kg/m²) (aHR 1.39; 95% CI = 1.18 to 1.63; P<0.001); and age (aHR 1.02; 95% CI = 1.01 to 1.02; P<0.001. Male sex was associated with lower risk of COVID-19 infection (aHR 0.71; 95% CI = 0.62 to 0.82; P<0.001).

Conclusion

Shielded individuals had a higher COVID-19 infection rate compared with non-shielded individuals, after adjusting for sociodemographic factors, nursing home status, and comorbidities.

Comparison of COVID-19 outcomes among shielded and non-shielded populations

Many western countries used shielding (extended self-isolation) of people presumed to be at high-risk from COVID-19 to protect them and reduce healthcare demand. To investigate the effectiveness of this strategy, we linked family practitioner, prescribing, laboratory, hospital and death records and compared COVID-19 outcomes among shielded and non-shielded individuals in the West of Scotland. Of the 1.3 million population, 27,747 (2.03%) were advised to shield, and 353,085 (26.85%) were classified a priori as moderate risk. COVID-19 testing was more common in the shielded (7.01%) and moderate risk (2.03%) groups, than low risk (0.73%). Referent to low-risk, the shielded group had higher confirmed infections (RR 8.45, 95% 7.44-9.59), case-fatality (RR 5.62, 95% CI 4.47-7.07) and population mortality (RR 57.56, 95% 44.06-75.19). The moderate-risk had intermediate confirmed infections (RR 4.11, 95% CI 3.82-4.42) and population mortality (RR 25.41, 95% CI 20.36-31.71) but, due to their higher prevalence, made the largest contribution to deaths (PAF 75.30%). Age ≥ 70 years accounted for 49.55% of deaths. In conclusion, in spite of the shielding strategy, high risk individuals were at increased risk of death. Furthermore, to be effective as a population strategy, shielding criteria would have needed to be widely expanded to include other criteria, such as the elderly.

Modelling that shaped the early COVID-19 pandemic response in the UK

Infectious disease modelling has played an integral part of the scientific evidence used to guide the response to the COVID-19 pandemic. In the UK, modelling evidence used for policy is reported to the Scientific Advisory Group for Emergencies (SAGE) modelling subgroup, SPI-M-O (Scientific Pandemic Influenza Group on Modelling-Operational). This Special Issue contains 20 articles detailing evidence that underpinned advice to the UK government during the SARS-CoV-2 pandemic in the UK between January 2020 and July 2020. Here, we introduce the UK scientific advisory system and how it operates in practice, and discuss how infectious disease modelling can be useful in policy making. We examine the drawbacks of current publishing practices and academic credit and highlight the importance of transparency and reproducibility during an epidemic emergency. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.