Comparing the responses of the UK, Sweden and Denmark to COVID-19 using counterfactual modelling

Examining the influence of Covid-19 restrictions, a nurse strike, and SARS-CoV-2 coinfection on bacteremia mortality: A Danish population-based cohort study (2019-2022)

Objectives

Bacteremia is an acute severe infection with high mortality. Changes in healthcare services and coinfections with SARS-CoV-2 may have affected the mortality for bacteremia during the COVID-19 pandemic, which has been reported for other major diseases. In this study we examine the all-cause bacteremia mortality amidst the COVID-19 pandemic.

Methods

A population-based cohort study comprised of laboratory confirmed bacteremia episodes in the Capital Region, Denmark (March 2019-February 2022). Cox proportional hazards models were used to calculate hazard ratios (HR) and 95 % confidence intervals (CI) for all-cause bacteremia mortality associated with the Covid-19 restriction period, a strike period, and coinfection with SARS-CoV-2, adjusted for possible confounders.

Results

A total of 14,912 bacteremia episodes were identified in 12,693 patients during the study period. The 30- and 90-day all-cause mortality were 19 % and 27 %, respectively. The fully adjusted HR for 30- and 90-day all-cause mortality associated with the Covid-19 restriction period were 0.91 (95 % CI, 0.84 to 0.99) and 0.90 (95 % CI, 0.84 to 0.96), respectively, compared to the remaining time period. The corresponding HRs associated with SARS-CoV-2 coinfection were 1.29 (95 % CI, 1.11 to 1.50) and 1.36 (95 % CI, 1.20 to 1.55) compared to patients without coinfection. The association between the national nurse strike and all-cause bacteremia mortality was inconclusive.

Conclusions

In this large population-based cohort study, a significant reduction in all-cause mortality for bacteremia was observed during the Covid-19 restriction period in Denmark, while coinfection with SARS-CoV-2 seem to be a substantial risk factor for all-cause bacteremia mortality.

The influence of cross-border mobility on the COVID-19 epidemic in Nordic countries

Restrictions of cross-border mobility are typically used to prevent an emerging disease from entering a country in order to slow down its spread. However, such interventions can come with a significant societal cost and should thus be based on careful analysis and quantitative understanding on their effects. To this end, we model the influence of cross-border mobility on the spread of COVID-19 during 2020 in the neighbouring Nordic countries of Denmark, Finland, Norway and Sweden. We investigate the immediate impact of cross-border travel on disease spread and employ counterfactual scenarios to explore the cumulative effects of introducing additional infected individuals into a population during the ongoing epidemic. Our results indicate that the effect of inter-country mobility on epidemic growth is non-negligible essentially when there is sizeable mobility from a high prevalence country or countries to a low prevalence one. Our findings underscore the critical importance of accurate data and models on both epidemic progression and travel patterns in informing decisions related to inter-country mobility restrictions.

Building resilience: analysis of health care leaders' perspectives on the Covid-19 response in Region Stockholm

BACKGROUND

The Covid-19 pandemic has tested health care organizations worldwide. Responses have demonstrated great variation and Sweden has been an outlier in terms of both strategy and how it was enacted, making it an interesting case for further study. The aim of this study was to explore how health care leaders experienced the challenges and responses that emerged during the initial wave of the Covid-19 pandemic, and to analyze these experiences through an organizational resilience lens.

METHODS

A qualitative interview study with 12 senior staff members who worked directly with or supervised pandemic efforts. Transcripts were analyzed using traditional content analysis and the codes directed to the Integrated Resilience Attributes Framework to understand what contributed to or hindered organizational resilience, i.e. how organizations achieve their goals by utilizing existing resources during crises.

RESULTS/FINDINGS

Organizational resilience was found at the micro (situated) and meso (structural) system levels as individuals and organizations dealt with acute shortages and were forced to rapidly adapt through individual sacrifices, resource management, process management, and communications and relational capacity. Poor systemic resilience related to misaligned responses and a lack of learning from previous experiences, negatively impacted the anticipatory phase and placed greater pressure on individuals and organizations to respond. Conventional crisis leadership could hamper innovation, further cement chronic challenges, and generate a moral tension between centralized directives and clinical microsystem experiences.

CONCLUSIONS

The pandemic tested the resilience of the health care system, placing undue pressure on micro and meso systems responses. With improved learning capabilities, some of this pressure may be mitigated as it could raise the anticipatory resilience potential, i.e. with better health systems learning, we may need fewer heroes. How crisis leadership could better align decision-making with frontline needs and temper short-term acute needs with a longer-term infinite mindset is worth further study.

The impact of Covid-19 vaccination in Aotearoa New Zealand: A modelling study

Aotearoa New Zealand implemented a Covid-19 elimination strategy in 2020 and 2021, which enabled a large majority of the population to be vaccinated before being exposed to the virus. This strategy delivered one of the lowest pandemic mortality rates in the world. However, quantitative estimates of the population-level health benefits of vaccination are lacking. Here, we use a validated mathematical model of Covid-19 in New Zealand to investigate counterfactual scenarios with differing levels of vaccine coverage in different age and ethnicity groups. The model builds on earlier research by adding age- and time-dependent case ascertainment, the effect of antiviral medications, improved hospitalisation rate estimates, and the impact of relaxing control measures. The model was used for scenario analysis and policy advice for the New Zealand Government in 2022 and 2023. We compare the number of Covid-19 hospitalisations, deaths, and years of life lost in each counterfactual scenario to a baseline scenario that is fitted to epidemiological data between January 2022 and June 2023. Our results estimate that vaccines saved 6650 (95% credible interval [4424, 10180]) lives, and prevented 74500 [51000, 115400] years of life lost and 45100 [34400, 55600] hospitalisations during this 18-month period. Making the same comparison before the benefit of antiviral medications is accounted for, the estimated number of lives saved by vaccines increases to 7604 [5080, 11942]. Due to inequities in the vaccine rollout, vaccination rates among Māori were lower than in people of European ethnicity. Our results show that, if vaccination rates had been equitable, an estimated 11%-26% of the 292 Māori Covid-19 deaths that were recorded in this time period could have been prevented. We conclude that Covid-19 vaccination greatly reduced health burden in New Zealand and that equity needs to be a key focus of future vaccination programmes.

Comparative impact assessment of COVID-19 policy interventions in five South Asian countries using reported and estimated unreported death counts during 2020-2021

There has been raging discussion and debate around the quality of COVID death data in South Asia. According to WHO, of the 5.5 million reported COVID-19 deaths from 2020-2021, 0.57 million (10%) were contributed by five low and middle income countries (LMIC) countries in the Global South: India, Pakistan, Bangladesh, Sri Lanka and Nepal. However, a number of excess death estimates show that the actual death toll from COVID-19 is significantly higher than the reported number of deaths. For example, the IHME and WHO both project around 14.9 million total deaths, of which 4.5-5.5 million were attributed to these five countries in 2020-2021. We focus our gaze on the COVID-19 performance of these five countries where 23.5% of the world population lives in 2020 and 2021, via a counterfactual lens and ask, to what extent the mortality of one LMIC would have been affected if it adopted the pandemic policies of another, similar country? We use a Bayesian semi-mechanistic model developed by Mishra et al. (2021) to compare both the reported and estimated total death tolls by permuting the time-varying reproduction number (Rt) across these countries over a similar time period. Our analysis shows that, in the first half of 2021, mortality in India in terms of reported deaths could have been reduced to 96 and 102 deaths per million compared to actual 170 reported deaths per million had it adopted the policies of Nepal and Pakistan respectively. In terms of total deaths, India could have averted 481 and 466 deaths per million had it adopted the policies of Bangladesh and Pakistan. On the other hand, India had a lower number of reported COVID-19 deaths per million (48 deaths per million) and a lower estimated total deaths per million (80 deaths per million) in the second half of 2021, and LMICs other than Pakistan would have lower reported mortality had they followed India's strategy. The gap between the reported and estimated total deaths highlights the varying level and extent of under-reporting of deaths across the subcontinent, and that model estimates are contingent on accuracy of the death data. Our analysis shows the importance of timely public health intervention and vaccines for lowering mortality and the need for better coverage infrastructure for the death registration system in LMICs.

PPChain: A Blockchain for Pandemic Prevention and Control Assisted by Federated Learning

Taking COVID-19 as an example, we know that a pandemic can have a huge impact on normal human life and the economy. Meanwhile, the population flow between countries and regions is the main factor affecting the changes in a pandemic, which is determined by the airline network. Therefore, realizing the overall control of airports is an effective way to control a pandemic. However, this is restricted by the differences in prevention and control policies in different areas and privacy issues, such as how a patient's personal data from a medical center cannot be effectively combined with their passenger personal data. This prevents more precise airport control decisions from being made. To address this, this paper designed a novel data-sharing framework (i.e., PPChain) based on blockchain and federated learning. The experiment uses a CPU i7-12800HX and uses Docker to simulate multiple virtual nodes. The model is deployed to run on an NVIDIA GeForce GTX 3090Ti GPU. The experiment shows that the relationship between a pandemic and aircraft transport can be effectively explored by PPChain without sharing raw data. This approach does not require centralized trust and improves the security of the sharing process. The scheme can help formulate more scientific and rational prevention and control policies for the control of airports. Additionally, it can use aerial data to predict pandemics more accurately.

Acceptability of restrictions in the COVID-19 pandemic: a population-based survey in Denmark and Sweden

Introduction

Denmark and Sweden initially adopted different responses to the COVID-19 pandemic although the two countries share many characteristics. Denmark responded swiftly with many mandatory restrictions. In contrast, Sweden relied on voluntary restrictions and a more "relaxed" response during the first wave of the pandemic. However, increased rates of COVID-19 cases led to a new approach that involved many more mandatory restrictions, thus making Sweden's response similar to Denmark's in the second wave of the pandemic.

Aim

The aim was to investigate and compare the extent to which the populations in Denmark and Sweden considered the COVID-19 restrictions to be acceptable during the first two waves of the pandemic. The study also aimed to identify the characteristics of those who were least accepting of the restrictions in the two countries.

Materials and methods

Cross-sectional surveys were conducted in Denmark and Sweden in 2021. The study population was sampled from nationally representative web panels in the two countries, consisting of 2,619 individuals from Denmark and 2,633 from Sweden. The questionnaire captured key socio-demographic characteristics. Acceptability was operationalized based on a theoretical framework consisting of seven constructs and one overarching construct.

Results

The respondents' age and gender patterns were similar in the two countries. The proportion of respondents in Denmark who agreed with the statements ("agree" alternative) that captured various acceptability constructs was generally higher for the first wave than the second wave of the pandemic. The opposite pattern was seen for Sweden. In Denmark, 66% in the first wave and 50% in the second wave were accepting of the restrictions. The corresponding figures for Sweden was 42% (first wave) and 47% (second wave). Low acceptance of the restrictions, defined as the 25% with the lowest total score on the seven acceptability statements, was associated with younger age, male gender and lower education levels.

Conclusion

Respondents in Sweden were more accepting of the restrictions in the second wave, when the country used many mandatory restrictions. In contrast, respondents in Denmark were more accepting of the restrictions in the first wave than in the second wave, implying an increased weariness to comply with the restrictions over time. There were considerable socio-demographic differences between those who expressed low acceptance of the restrictions and the others in both countries, suggesting the importance of tailoring communication about the pandemic to different segments of the population.

Community factors and excess mortality in the COVID-19 pandemic in England, Italy and Sweden

BACKGROUND

Analyses of coronavirus disease 19 suggest specific risk factors make communities more or less vulnerable to pandemic-related deaths within countries. What is unclear is whether the characteristics affecting vulnerability of small communities within countries produce similar patterns of excess mortality across countries with different demographics and public health responses to the pandemic. Our aim is to quantify community-level variations in excess mortality within England, Italy and Sweden and identify how such spatial variability was driven by community-level characteristics.

METHODS

We applied a two-stage Bayesian model to quantify inequalities in excess mortality in people aged 40 years and older at the community level in England, Italy and Sweden during the first year of the pandemic (March 2020-February 2021). We used community characteristics measuring deprivation, air pollution, living conditions, population density and movement of people as covariates to quantify their associations with excess mortality.

RESULTS

We found just under half of communities in England (48.1%) and Italy (45.8%) had an excess mortality of over 300 per 100 000 males over the age of 40, while for Sweden that covered 23.1% of communities. We showed that deprivation is a strong predictor of excess mortality across the three countries, and communities with high levels of overcrowding were associated with higher excess mortality in England and Sweden.

CONCLUSION

These results highlight some international similarities in factors affecting mortality that will help policy makers target public health measures to increase resilience to the mortality impacts of this and future pandemics.

Momentum lost or creating new constellations? Insights from an exercise-at-work project during the COVID-19 pandemic - a mixed methods approach

Exercise-at-work programmes have been identified as venues to decrease inequalities in physical activity and exercise between socioeconomic groups and to improve employees' health and wellbeing. Drawing on a multiple institutional logics perspective and adopting a mixed-methods approach, this paper investigates how employees, exercise-ambassadors and managers at five Danish workplaces experience Covid-19 induced changes to a 1-year exercise-at-work project, and how these changes impacted upon the workplace. Our results suggest that Covid-19 and the altered format of exercise and delivery polarized employees' opportunities for exercise at work. However, the generally positive experiences of exercise-at-work activities and their influence on social environment and collaboration (identified prior to Covid-19 lockdown) remained among those employees who continued with activities. Self-organized adaptions and models of employee exercise which emerged suggest that community logic endured despite the crisis. We show how Covid-19 induced organizational changes led to interplays between institutional logics, with family and state logics becoming more prominent. Specifically, the exercise-at-work programme changed from an aligned model, with complementary logics and minimal conflict, to a model where logics of profession and corporation became dominant at the expense of community logic (exercise-ambassadors activities), but constrained by a state and a family logic.

A Data-Political Spectacle: How COVID-19 Became A Source of Societal Division in Denmark

The COVID-19 pandemic has been a data-political spectacle. Data are omnipresent in prediction and surveillance, and even in resistance to governmental measures. How have citizens, whose lives were suddenly governed by pandemic data, understood and reacted to the pandemic as a data-political phenomenon? Based on a study carried out in Denmark, we show how society became divided into those viewing themselves as supporters of the governmental approach to the COVID-19 pandemic, and those who oppose it. These groups seem to subscribe to very different truths. We argue, however, that both sides share a positivist ideal and think that data and facts ought to rule. Both sides have also come to acknowledge that data are not unambiguous, and both cast increasing doubts on political uses of data. Though the people agreeing with, and the people opposing, the government strategy are in many ways surprisingly similar with respect to epistemic norms, they differ in what they perceive as dangerous or desirable, and in who they believe are telling the "truth" about the pandemic. These different perceptions result in different types of pandemic-related activism. Resistance against restrictions is often understood as inspired by conspiracy theories and in some countries anti-restrictions activism has turned violent. In our case, however, we suggest that when looking at similarities and differences across both groups, the gap between those opposing and those agreeing with the government approach is not as unbridgeable as might be suggested by their beliefs in differing truths and the emerging societal division.

COVID-19 Quarantine Measures Efficiency Evaluation by Best Tube Interval Data Envelopment Analysis

All countries have responded with a wide range of measures to stop the propagation of coronavirus. We apply best tube interval data envelopment analysis, in order to evaluate efficiency of quarantine measures using imprecise data. Using the Oxford COVID-19 Government Response Tracker’s (OxCGRT) data and given method, we construct time series of efficiency assessment of government responses to COVID-19. In addition, we separate all examined countries into several groups with similar patterns of quarantine measures efficiency. As a result, we highlight China and Vietnam as a benchmark for all other countries, because efficiency of these countries is high for almost whole period of research.

The Role of Economic Stress, Health Concerns, and Institutional Trust in Supporting Public Protests against COVID-19 Lockdown Measures in Denmark

During the current COVID-19 pandemic, most governments around the world have adopted strict COVID-19 lockdown measures. In Denmark, mainly from January to March 2021, an anonymous protest group called Men in Black organized demonstrations against the Danish COVID-19 lockdown measures in the three major cities in Denmark. Based on an online survey that we carried out in March 2021 in the Danish population aged 16 years and above (n = 2692), we analyze the individual-level factors behind supporting these demonstrations. Based on ordered logit regressions, the results show that being Muslim and being self-employed (business owner) was positively related to supporting the demonstrations, and that age and living in a city municipality was negatively related to supporting the demonstrations. Based on structural equation modeling (SEM), the results showed that the municipal COVID-19 incidence rate mediates the effect of living in a city municipality, that institutional trust mediates the effect of being Muslim, and that COVID-19 health concerns and institutional trust mediate the effect of age. Overall, economic stress among business owners, health concerns, and institutional trust were found to be the main predictors of supporting the demonstrations against the COVID-19 lockdown measures in Denmark.

COVID-19: A Comparative Study of Contagions Peaks in Cities from Europe and the Americas

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by a group of viruses that provoke illnesses ranging from the common cold to more serious illnesses such as pneumonia. COVID-19 started in China and spread rapidly from a single city to an entire country in just 30 days and to the rest of the world in no more than 3 months. Several studies have tried to model the behavior of COVID-19 in diverse regions, based on differential equations of the SIR and stochastic SIR type, and their extensions. In this article, a statistical analysis of daily confirmed COVID-19 cases reported in eleven different cities in Europe and America is conducted. Log-linear models are proposed to model the rise or drop in the number of positive cases reported daily. A classification analysis of the estimated slopes is performed, allowing a comparison of the eleven cities at different epidemic peaks. By rescaling the curves, similar behaviors among rises and drops in different cities are found, independent of socioeconomic conditions, type of quarantine measures taken, whether more or less restrictive. The log-linear model appears to be suitable for modeling the incidence of COVID-19 both in rises and drops.

No time to waste; the impact of the COVID-19 pandemic on hip, knee, and shoulder arthroplasty surgeries in the Netherlands and Denmark

AIMS

This study aimed to investigate the estimated change in primary and revision arthroplasty rate in the Netherlands and Denmark for hips, knees, and shoulders during the COVID-19 pandemic in 2020 (COVID-period). Additional points of focus included the comparison of patient characteristics and hospital type (2019 vs COVID-period), and the estimated loss of quality-adjusted life years (QALYs) and impact on waiting lists.

METHODS

All hip, knee, and shoulder arthroplasties (2014 to 2020) from the Dutch Arthroplasty Register, and hip and knee arthroplasties from the Danish Hip and Knee Arthroplasty Registries, were included. The expected number of arthroplasties per month in 2020 was estimated using Poisson regression, taking into account changes in age and sex distribution of the general Dutch/Danish population over time, calculating observed/expected (O/E) ratios. Country-specific proportions of patient characteristics and hospital type were calculated per indication category (osteoarthritis/other elective/acute). Waiting list outcomes including QALYs were estimated by modelling virtual waiting lists including 0%, 5% and 10% extra capacity.

RESULTS

During COVID-period, fewer arthroplasties were performed than expected (Netherlands: 20%; Denmark: 5%), with the lowest O/E in April. In the Netherlands, more acute indications were prioritized, resulting in more American Society of Anesthesiologists grade III to IV patients receiving surgery. In both countries, no other patient prioritization was present. Relatively more arthroplasties were performed in private hospitals. There were no clinically relevant differences in revision arthroplasties between pre-COVID and COVID-period. Estimated total health loss depending on extra capacity ranged from: 19,800 to 29,400 QALYs (Netherlands): 1,700 to 2,400 QALYs (Denmark). With no extra capacity it will take > 30 years to deplete the waiting lists.

CONCLUSION

The COVID-19 pandemic had an enormous negative effect on arthroplasty rates, but more in the Netherlands than Denmark. In the Netherlands, hip and shoulder patients with acute indications were prioritized. Private hospitals filled in part of the capacity gap. QALY loss due to postponed arthroplasty surgeries is considerable.Cite this article: Bone Jt Open 2022;3(12):977-990.

A general framework for optimising cost-effectiveness of pandemic response under partial intervention measures

The COVID-19 pandemic created enormous public health and socioeconomic challenges. The health effects of vaccination and non-pharmaceutical interventions (NPIs) were often contrasted with significant social and economic costs. We describe a general framework aimed to derive adaptive cost-effective interventions, adequate for both recent and emerging pandemic threats. We also quantify the net health benefits and propose a reinforcement learning approach to optimise adaptive NPIs. The approach utilises an agent-based model simulating pandemic responses in Australia, and accounts for a heterogeneous population with variable levels of compliance fluctuating over time and across individuals. Our analysis shows that a significant net health benefit may be attained by adaptive NPIs formed by partial social distancing measures, coupled with moderate levels of the society's willingness to pay for health gains (health losses averted). We demonstrate that a socially acceptable balance between health effects and incurred economic costs is achievable over a long term, despite possible early setbacks.

Counterfactuals of effects of vaccination and public health measures on COVID-19 cases in Canada: What could have happened?

This study illustrates what may have happened, in terms of coronavirus disease 2019 (COVID-19) infections, hospitalizations and deaths in Canada, had public health measures not been used to control the COVID-19 epidemic, and had restrictions been lifted with low levels of vaccination, or no vaccination, of the Canadian population. The timeline of the epidemic in Canada, and the public health interventions used to control the epidemic, are reviewed. Comparisons against outcomes in other countries and counterfactual modelling illustrate the relative success of control of the epidemic in Canada. Together, these observations show that without the use of restrictive measures and without high levels of vaccination, Canada could have experienced substantially higher numbers of infections and hospitalizations and almost a million deaths.

Resources or trust: What matters more in the vaccination strategies of high-income liberal democracies?

Objectives

This paper presents an overview of the vaccination policy responses to the COVID-19 pandemic in Denmark, Canada, and the United States until September 1, 2021. The article seeks to understand the reasons for vaccination differences among high-income, liberal democracies.

Methods

The country cases were selected based on tiers of population-level vaccination uptake within six months after vaccines became broadly available (for high-income countries). We conducted a rapid review of primary data for each country case. Through a graphical and descriptive analysis, we evaluated common patterns as well as significant divergences in the vaccination rollout across countries and its relationship with COVID-19 health outcomes, government policy responses, resource constraints, and socio-political factors. This inductive analysis provides a sense of how resource constraints compare with current political contexts in each country case that may influence the public's response to a national vaccination strategy.

Results

Resources, socio-economic factors, and health outcomes related to COVID-19 do not ensure vaccination policy success as the case of the United States makes clear. Instead, trust in government and health systems appear to promise a higher vaccination uptake and maintained support for measures during a pandemic. Trust in government can be defined as the confidence citizens have that governmental actions will do what is right and perceived as fair.

Conclusion

Denmark, the United States, and Canada are high-income liberal democracies with very different vaccine strategies and subsequently different vaccination outcomes across their populations. What appears to be critical to successful vaccination outcomes is high trust in government or health officials, along with the depoliticization of the COVID-19 pandemic among the country's political parties.

Nonlinear frequency analysis of COVID-19 spread in Tokyo using empirical mode decomposition

Empirical mode decomposition (EMD) was adopted to decompose daily COVID-19 infections in Tokyo from February 28, 2020, to July 12, 2021. Daily COVID-19 infections were nonlinearly decomposed into several monochromatic waves, intrinsic mode functions (IMFs), corresponding to their periodic meanings from high frequency to low frequency. High-frequency IMFs represent variabilities of random factors and variations in the number of daily PCR and antigen inspections, which can be nonlinearly denoised using EMD. Compared with a moving average and Fourier transform, EMD provides better performance in denoising and analyzing COVID-19 spread. After variabilities of daily inspections were weekly denoised by EMD, one low-frequency IMF reveals that the average period of external influences (public health and social measures) to stop COVID-19 spread was 19 days, corresponding to the measures response duration based on the incubation period. By monitoring this nonlinear wave, public health and social measures for stopping COVID-19 spread can be evaluated and visualized quantitatively in the instantaneous frequency domain. Moreover, another low-frequency IMF revealed that the period of the COVID-19 outbreak and retreat was 57 days on average. This nonlinear wave can be used as a reference for setting the timeframe for state of emergency declarations. Thus, decomposing daily infections in the instantaneous frequency domain using EMD represents a useful tool to improve public health and social measures for stopping COVID-19 spread.

Patients' perspectives on the effect of the COVID-19 pandemic on access to cancer care and social contacts in Sweden and the UK: a cross-sectional study

PURPOSE

We aimed to determine whether there was a difference in access to cancer-related healthcare between people living in Sweden and the United Kingdom (UK) during the COVID-19 pandemic. We also describe how the pandemic affected social contact of patients undergoing treatment.

METHODS

This cross-sectional study used survey data collected through the War on Cancer mobile phone application between September 5, 2020, and January 6, 2021. We included individuals with cancer diagnoses living in Sweden or the UK. The association between difficulty accessing cancer-related healthcare and country was examined using logistic regression. Frequencies were used to describe the effect of the pandemic on social contact.

RESULTS

Of 491 individuals included in the study, 183 were living in the UK and 308 in Sweden. Living in the UK was associated with greater difficulty accessing cancer-related healthcare (n = 99/183, 54.1%) than living in Sweden (n = 100/308, 32.5%) (odds ratio 2.12, 95% CI 1.39-3.23, p < 0.001). The pandemic affected social contact for almost all patients (n = 218/238, 91.6%) undergoing treatment.

CONCLUSION

This study highlights the differential impact that the pandemic may have had on patients' access to cancer-related care in the UK and Sweden. In both countries, the pandemic overwhelmingly affected social contact of individuals undergoing cancer treatment. New ways must be found to improve access to cancer-related care and reduce social isolation for patients with cancer during a pandemic.