Excess deaths from COVID-19 and other causes by region, neighbourhood deprivation level and place of death during the first 30 weeks of the pandemic in England and Wales: A retrospective registry study

Excess Mortality Calculations to Assess the Impact of the COVID-19 Pandemic: Concepts and Methodological Issues

We discuss some intriguing methodological aspects of excess mortality analyses, which have been widely used to describe the impact of the COVID-19 pandemic. We describe the main ways of presenting excess mortality: as a mortality rate (incidence rate) or as a percentage increase (relative risk or rate ratio). We discuss what should be regarded as the null value of excess mortality (i.e., when countries or regions can be judged as having fared equally well) and when age and sex standardization, adjustment for other determinants of the spread of a pandemic, or both is necessary. We discuss the level of detail by time and place and person that may be necessary. We note that an excess mortality comparison is essentially a difference-in-differences analysis. We conclude that, although one cannot rule out using excess mortality analyses for causal effect estimates, such analyses will remain most fruitful for generating hypotheses about both the efficiency of measures to curtail the pandemic and factors that cannot be influenced. Nevertheless, a judicious use of arguments and counterarguments can then lead to identifying best practices for various situations. (Am J Public Health. 2024;114(6):593-598. https://doi.org/10.2105/AJPH.2024.307572).

The Epidemiology of COVID-19 Vaccine-Induced Myocarditis

Background

In December 2019, the emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) led to the COVID-19 pandemic, with millions of deaths worldwide. Vaccine breakthroughs in late 2020 resulted in the authorization of COVID-19 vaccines. While these vaccines have demonstrated efficacy, evidence from vaccine safety monitoring systems around the globe supported a causal association between COVID-19 vaccines, in particular those using mRNA technology, i.e., Moderna's mRNA-1273 and Pfizer-BioNTech's BNT162b2, and myocarditis.

Objective

This paper aims to investigate the epidemiology of mRNA COVID-19 vaccine-induced myocarditis, including age, ethnicity, and gender associations with these vaccines. It also discusses the immunopathophysiological mechanisms of mRNA COVID-19 vaccine-associated myocarditis and outlines principles of diagnosis, clinical presentation, and management.

Methods

A literature review was conducted using PubMed, Embase, and Queen Mary University of London Library Services databases. Search terms included "myocarditis," "coronavirus disease 2019," "SARS-CoV-2," "mRNA Covid-19 vaccines," "Covid vaccine-associated myocarditis," "epidemiology," "potential mechanisms," "myocarditis diagnosis," and "myocarditis management."

Results

While the definite mechanism of mRNA COVID-19 vaccine-associated myocarditis remains ambiguous, potential mechanisms include molecular mimicry of spike proteins and activation of the adaptive immune response with dysregulated cytokine expression. Male predominance in COVID-19 vaccine-induced myocarditis may be attributed to sex hormones, variations in inflammatory reactions, coagulation states based on gender, and female-specific protective factors. Moreover, an analysis of diagnostic and management strategies reveals a lack of consensus on acute patient presentation management.

Conclusion

In contrast to viral infections that stand as the predominant etiological factor for myocarditis with more severe consequences, the mRNA COVID-19 vaccination elicits a mild and self-limiting manifestation of the condition. There is currently insufficient evidence to confirm the definite underlying mechanism of COVID-19 vaccine-associated myocarditis. Further research is needed to develop preventive and therapeutic solutions in this context.

A comparison of excess deaths by UK country and region during the first year of the COVID-19 pandemic

We compare the impact of the first two waves of the COVID-19 pandemic on risk of age-standardized mortality by sex, UK country, and English region. Each wave is defined as lasting 26 weeks and are consecutive beginning in 2020 week 11. The expected rate is estimated from 2015 to 2019 mean and the projected mortality trend from the same period are used to estimate excess mortality. By both measures, excess mortality was highest and lowest in regions of England, London and the South-West, respectively. Excess mortality was consistently higher for males than females.

Influence of COVID-19 pandemic in India on coronary artery disease clinical presentation, angiography, interventions and in-hospital outcomes: a single centre prospective registry-based observational study

OBJECTIVE

The study examined the influence of the COVID-19 pandemic in India on variation in clinical features, management and in-hospital outcomes in patients undergoing percutaneous coronary intervention (PCI).

DESIGN

Prospective registry-based observational study.

SETTING

A tertiary care hospital in India participant in the American College of Cardiology CathPCI Registry.

PARTICIPANTS

7089 successive patients who underwent PCI from April 2018 to March 2023 were enrolled (men 5627, women 1462). Details of risk factors, clinical presentation, coronary angiography, coronary interventions, clinical management and in-hospital outcomes were recorded. Annual data were classified into specific COVID-19 periods according to Government of India guidelines as pre-COVID-19 (April 2018 to March 2019, n=1563; April 2019 to March 2020, n=1594), COVID-19 (April 2020 to March 2020, n=1206; April 2021 to March 2022, n=1223) and post-COVID-19 (April 2022 to March 2023, n=1503).

RESULTS

Compared with the patients in pre-COVID-19 and post-COVID-19 periods, during the first COVID-19 year, patients had more hypertension, non-ST elevation myocardial infarction (NSTEMI), lower left ventricular ejection fraction (LVEF) and multivessel coronary artery disease (CAD). In the second COVID-19 year, patients had more STEMI, lower LVEF, multivessel CAD, primary PCI, multiple stents and more vasopressor and mechanical support. There were 99 (1.4%) in-hospital deaths which in the successive years were 1.2%, 1.4%, 0.8%, 2.4% and 1.3%, respectively (p=0.019). Compared with the baseline year, deaths were slightly lower in the first COVID-19-year (age-sex adjusted OR 0.68, 95% CI 0.31 to 1.47) but significantly more in the second COVID-19-year (OR 1.97, 95% CI 1.10 to 3.54). This variation attenuated following adjustment for clinical presentation, extent of CAD, in-hospital treatment and duration of hospitalisation.

CONCLUSIONS

In-hospital mortality among patients with CAD undergoing PCI was significantly higher in the second year of the COVID-19 pandemic in India and could be one of the reasons for excess deaths in the country. These patients had more severe CAD, lower LVEF, and more vasopressor and mechanical support and duration of hospitalisation.

A Year of Deaths Due to or With COVID-19 Under Universal Postmortem Testing in San Francisco

ABSTRACT

The Health Officer of the City and County of San Francisco, California, issued the order that all decedents were required to have a documented COVID-19 test effective from June 2020 to June 2021. The justification for the requirement was that complete data on COVID-19 status at the time of death were needed to help protect first responders and funeral home workers, identify missed cases, and characterize the places of death for otherwise unknown COVID-19 cases. To fill the gap in COVID-19 testing for all decedents, particularly among persons dying outside of hospitals, a specialized Decedent Testing Unit was created along with an increased capacity of the Office of the Chief Medical Examiner. From July 1, 2020, to June 30, 2021, the Decedent Testing Unit and Office of the Chief Medical Examiner provided postmortem testing results for 2776 decedents. Of these, 80 tested positive for COVID-19 for a positivity rate of 2.97%. The largest number of COVID-19-positive specimens were collected from persons who died at home (n = 37, 46.3%), followed by those who died in hospice (n = 20, 25.0%), other places outside of homes or facilities (n = 8, 10.0%), and in skilled nursing or long-term care facilities (n = 7, 8.8%). Follow-up of California death records found that 17 of these 80 cases (21.3%) had COVID-19 listed as one of the causes of death, 22 (27.5%) mentioned COVID-19 under "other conditions," and 41 (51.3%) made no mention of COVID-19. In the context of providing the COVID-19 status of decedents not otherwise known to have infection, our data help gauge the likelihood of missing deaths due to or with COVID-19 and inform future public health decisions on whether to require universal postmortem testing with COVID-19 resurgences or with new deadly epidemics.

COVID-19, deaths at home and end-of-life cancer care

During the COVID-19 pandemic there was a period of high excess deaths from cancer at home as opposed to in hospitals or in care homes. In this paper we aim to explore whether healthcare utilisation trajectories of cancer patients in the final months of life during the COVID-19 pandemic reveal any potential unmet healthcare need. We use English hospital records linked to data on all deaths in and out of hospital which identifies the cause and location of death. Our analysis shows that during the periods of peak COVID-19 caseload, patients dying of cancer experienced up to 42% less hospital treatment in their final month of life compared to historical controls. We find reductions in end-of-life hospital care for cancer patients dying in hospitals, care homes/hospices and at home, however the effect is amplified by the shift to more patients dying at home. Through the first year of the pandemic in England, we estimate the number of inpatient bed-days for end-of-life cancer patients in their final month reduced by approximately 282,282, or 25%. For outpatient appointments in the final month of life we find a reduction in face-to-face appointments and an increase in remote appointments which persists through the pandemic year and is not confined only to the periods of peak COVID-19 caseload. Our results suggest reductions in care provision during the COVID-19 pandemic may have led to unmet need, and future emergency reorganisations of health care systems must ensure consistent care provision for vulnerable groups such as cancer patients.

Evaluating Spatial, Cause-Specific and Seasonal Effects of Excess Mortality Associated with the COVID-19 Pandemic: The Case of Germany, 2020

BACKGROUND

Evaluating mortality effects of the COVID-19 pandemic using all-cause mortality data for national populations is inevitably associated with the risk of masking important subnational differentials and hampering targeted health policies. This study aims at assessing simultaneously cause-specific, spatial and seasonal mortality effects attributable to the pandemic in Germany in 2020.

METHODS

Our analyses rely on official cause-of-death statistics consisting of 5.65 million individual death records reported for the German population during 2015-2020. We conduct differential mortality analyses by age, sex, cause, month and district (N = 400), using decomposition and standardisation methods, comparing each strata of the mortality level observed in 2020 with its expected value, as well as spatial regression to explore the association of excess mortality with pre-pandemic indicators.

RESULTS

The spatial analyses of excess mortality reveal a very heterogenous pattern, even within federal states. The coastal areas in the north were least affected, while the south of eastern Germany experienced the highest levels. Excess mortality in the most affected districts, with standardised mortality ratios reaching up to 20%, is driven widely by older ages and deaths reported in December, particularly from COVID-19 but also from cardiovascular and mental/nervous diseases.

CONCLUSIONS

Our results suggest that increased psychosocial stress influenced the outcome of excess mortality in the most affected areas during the second lockdown, thus hinting at possible adverse effects of strict policy measures. It is essential to accelerate the collection of detailed mortality data to provide policymakers earlier with relevant information in times of crisis.

Did the socioeconomic inequalities in avoidable and unavoidable mortality worsen during the first year of the COVID-19 pandemic in Korea?

OBJECTIVES

This study examined changes in socioeconomic inequalities in mortality in Korea before and after the outbreak of coronavirus disease 2019 (COVID-19).

METHODS

From 2017 to 2020, age-standardized mortality rates were calculated for all-cause deaths, avoidable deaths (preventable deaths, treatable deaths), and unavoidable deaths using National Health Insurance claims data and Statistics Korea's cause of death data. In addition, the slope index of inequality (SII) and the relative index of inequality (RII) by six income levels (Medical Aid beneficiary group and quintile of health insurance premiums) were computed to analyze the magnitude and change of mortality inequalities.

RESULTS

All-cause and avoidable mortality rates decreased steadily between 2017 and 2020, whereas unavoidable mortality remained relatively stable. In the case of mortality inequalities, the disparity in all-cause mortality between income classes was exacerbated in 2020 compared to 2019, with the SII increasing from 185.44 to 189.22 and the RII increasing from 3.99 to 4.29. In particular, the preventable and unavoidable mortality rates showed an apparent increase in inequality, as both the SII (preventable: 91.31 to 92.01, unavoidable: 69.99 to 75.38) and RII (preventable: 3.42 to 3.66, unavoidable: 5.02 to 5.89) increased.

CONCLUSIONS

In the first year of the COVID-19 pandemic, mortality inequality continued to increase, although there was no sign of exacerbation. It is necessary to continuously evaluate mortality inequalities, particularly for preventable and unavoidable deaths.

Healthcare utilisation in patients with long-term conditions during the COVID-19 pandemic: a population-based observational study of all patients across Greater Manchester, UK

OBJECTIVES

Data on population healthcare utilisation (HCU) across both primary and secondary care during the COVID-19 pandemic are lacking. We describe primary and secondary HCU stratified by long-term conditions (LTCs) and deprivation, during the first 19 months of COVID-19 pandemic across a large urban area in the UK.

DESIGN

A retrospective, observational study.

SETTING

All primary and secondary care organisations that contributed to the Greater Manchester Care Record throughout 30 December 2019 to 1 August 2021.

PARTICIPANTS

3 225 169 patients who were registered with or attended a National Health Service primary or secondary care service during the study period.

PRIMARY OUTCOMES

Primary care HCU (incident prescribing and recording of healthcare information) and secondary care HCU (planned and unplanned admissions) were assessed.

RESULTS

The first national lockdown was associated with reductions in all primary HCU measures, ranging from 24.7% (24.0% to 25.5%) for incident prescribing to 84.9% (84.2% to 85.5%) for cholesterol monitoring. Secondary HCU also dropped significantly for planned (47.4% (42.9% to 51.5%)) and unplanned admissions (35.3% (28.3% to 41.6%)). Only secondary care had significant reductions in HCU during the second national lockdown. Primary HCU measures had not recovered to prepandemic levels by the end of the study. The secondary admission rate ratio between multi-morbid patients and those without LTCs increased during the first lockdown by a factor of 2.40 (2.05 to 2.82; p<0.001) for planned admissions and 1.25 (1.07 to 1.47; p=0.006) for unplanned admissions. No significant changes in this ratio were observed in primary HCU.

CONCLUSION

Major changes in primary and secondary HCU were observed during the COVID-19 pandemic. Secondary HCU reduced more in those without LTCs and the ratio of utilisation between patients from the most and least deprived areas increased for the majority of HCU measures. Overall primary and secondary care HCU for some LTC groups had not returned to prepandemic levels by the end of the study.

Has COVID-19 increased inequality in mortality by income in the Netherlands?

BACKGROUND

In the Netherlands in 2020, COVID-19 deaths were more concentrated among individuals with a lower income. At the same time, COVID-19 was a new cause that also displaced some deaths from other causes, potentially reducing income-related inequality in non-COVID deaths. Our aim is to estimate the impact of the COVID-19 pandemic on the income-related inequality in total mortality and decompose this into the inequality in COVID-attributed deaths and changes in the inequality in non-COVID causes.

METHODS

We estimate excess deaths (observed minus trend-predicted deaths) by sex, age and income group for the Netherlands in 2020. Using a measure of income-related inequality (the concentration index), we decompose the inequality in total excess mortality into COVID-19 versus non-COVID causes.

RESULTS

Cause-attributed COVID-19 mortality exceeded total excess mortality by 12% for the 65-79 age group and by about 35% for 80+ in the Netherlands in 2020, implying a decrease in the number of non-COVID deaths compared with what was predicted. The income-related inequality in all-cause mortality was higher than predicted. This increase in inequality resulted from the combination of COVID-19 mortality, which was more unequally distributed than predicted total mortality, and the inequality in non-COVID causes, which was less unequal than predicted.

CONCLUSION

The COVID-19 pandemic has led to an increase in income-related inequality in all-cause mortality. Non-COVID mortality was less unequally distributed than expected due to displacement of other causes by COVID-19 and the potentially unequal broader societal impact of the pandemic.

Estimating Excess Mortality Due to Prostate, Breast, and Uterus Cancer during the COVID-19 Pandemic in Peru: A Time Series Analysis

During the COVID-19 pandemic, most of the deaths in Peru were related to COVID-19; however, cancer deaths have also been exacerbated in the first months of the pandemic. Despite this, excess mortalities of prostate, breast, and uterus cancer are not available by age group and region from January to December 2020. Therefore, we estimated the excess deaths and excess death rates (per 100,000 habitants) due to prostate, breast, and uterus cancer in 25 Peruvian regions. We did a time series analysis. Prostate, breast, and uterus cancer death data for 25 Peruvian regions were retrieved during the COVID-19 pandemic in 2020, as well as data for up to 3 years prior (2017-2019) from the Sistema Informatico Nacional de Defunciones at the Ministry of Health of Peru. Deaths in 2020 were defined as observed deaths. The expected deaths (in 2020) were estimated using the average deaths over 3 preceding years (2017, 2018 and 2019). Excess mortality was calculated as the difference between observed mortality and expected mortality in 2020. We estimated that the number of excess deaths and the excess death rates due to prostate, breast, and uterus cancer were 610 deaths (55%; 12.8 deaths per 100,000 men), 443 deaths (43%; 6 deaths per 100,000 women), and 154 deaths (25%; 2 deaths per 100,000 women), respectively. Excess numbers of deaths and excess death rates due to prostate and breast cancer increased with age. These excess deaths were higher in men aged ≥ 80 years (596 deaths (64%) and 150 deaths per 100,000 men) and women aged 70-79 years (229 deaths (58%) and 15 deaths per 100,000 women), respectively. In summary, during the COVID-19 pandemic, there were excess prostate and breast cancer mortalities in 2020 in Peru, while excess uterus cancer mortalities were low. Age-stratified excess death rates for prostate cancer and breast cancer were higher in men ≥ 80 years and in women ≥ 70 years, respectively.

Delay in Regular Visits of Chronic Disease Patients and Its Associated Factors during the COVID-19 Pandemic

Background

Chronic patients need regular follow-ups. During the COVID-19 pandemic, these regular visits can be affected. The delay of chronic patients and its contributing factors in their periodic visits during the COVID-19 pandemic are examined here.

Methods

This cross-sectional study was conducted between February and June 2021, in Fars, Iran. Two hundred and eighty-six households with at least one chronic patient were recruited. Then, several trained questioners called the studied households and asked about the studied variables. The dependent variable was the number of delays in regular visits during the COVID-19 pandemic. The results were analyzed through Poisson regression by SPSS Statistics version 22 and GraphPad Prism software version 9. A significance level of 0.05 was considered for this study.

Results

Out of 286 households 113 (73.4%) fathers, 138 (70.1%) mothers, and 17 (58.6%) children in the households reported delayed referral. In fathers, referring to the health center was significantly associated with a decrease in the number of delays (P=0.033). The higher age of the householder (P=0.005), the higher number of children (P=0.043), and having a family physician (P=0.007) in the mothers' group, also the number of children in households (P=0.001) in the children group were significantly associated with increasing the number of delays.

Conclusion

COVID-19 pandemic not only creates direct harmful effects but also adversely affects people in danger of chronic diseases. Delays in follow-ups are taken into account as a major challenge during the COVID-19 pandemic. This issue is not limited to rural or urban residency.

Demographic, behavioural and occupational risk factors associated with SARS-CoV-2 infection in UK healthcare workers: a retrospective observational study

OBJECTIVE

Healthcare workers (HCWs) are at higher risk of SARS-CoV-2 infection than the general population. This group is pivotal to healthcare system resilience during the COVID-19, and future, pandemics. We investigated demographic, social, behavioural and occupational risk factors for SARS-CoV-2 infection among HCWs.

DESIGN/SETTING/PARTICIPANTS

HCWs enrolled in a large-scale sero-epidemiological study at a UK university teaching hospital were sent questionnaires spanning a 5-month period from March to July 2020. In a retrospective observational cohort study, univariate logistic regression was used to assess factors associated with SARS-CoV-2 infection. A Least Absolute Shrinkage Selection Operator regression model was used to identify variables to include in a multivariate logistic regression model.

RESULTS

Among 2258 HCWs, highest ORs associated with SARS-CoV-2 antibody seropositivity on multivariate analysis were having a household member previously testing positive for SARS-CoV-2 antibodies (OR 6.94 (95% CI 4.15 to 11.6); p&lt;0.0001) and being of black ethnicity (6.21 (95% CI 2.69 to 14.3); p&lt;0.0001). Occupational factors associated with a higher risk of seropositivity included working as a physiotherapist (OR 2.78 (95% CI 1.21 to 6.36); p=0.015) and working predominantly in acute medicine (OR 2.72 (95% CI 1.57 to 4.69); p&lt;0.0001) or medical subspecialties (not including infectious diseases) (OR 2.33 (95% CI 1.4 to 3.88); p=0.001). Reporting that adequate personal protective equipment (PPE) was 'rarely' available had an OR of 2.83 (95% CI 1.29 to 6.25; p=0.01). Reporting attending a handover where social distancing was not possible had an OR of 1.39 (95% CI 1.02 to 1.9; p=0.038).

CONCLUSIONS

The emergence of SARS-CoV-2 variants and potential vaccine escape continue to threaten stability of healthcare systems worldwide, and sustained vigilance against HCW infection remains a priority. Enhanced risk assessments should be considered for HCWs of black ethnicity, physiotherapists and those working in acute medicine or medical subspecialties. Workplace risk reduction measures include ongoing access to high-quality PPE and effective social distancing measures.

Socio-demographic inequalities and excess non-COVID-19 mortality during the COVID-19 pandemic: a data-driven analysis of 1 069 174 death certificates in Mexico

BACKGROUND

In 2020, Mexico experienced one of the highest rates of excess mortality globally. However, the extent of non-COVID deaths on excess mortality, its regional distribution and the association between socio-demographic inequalities have not been characterized.

METHODS

We conducted a retrospective municipal and individual-level study using 1 069 174 death certificates to analyse COVID-19 and non-COVID-19 deaths classified by ICD-10 codes. Excess mortality was estimated as the increase in cause-specific mortality in 2020 compared with the average of 2015-2019, disaggregated by primary cause of death, death setting (in-hospital and out-of-hospital) and geographical location. Correlates of individual and municipal non-COVID-19 mortality were assessed using mixed effects logistic regression and negative binomial regression models, respectively.

RESULTS

We identified a 51% higher mortality rate (276.11 deaths per 100 000 inhabitants) compared with the 2015-2019 average period, largely attributable to COVID-19. Non-COVID-19 causes comprised one-fifth of excess deaths, with acute myocardial infarction and type 2 diabetes as the two leading non-COVID-19 causes of excess mortality. COVID-19 deaths occurred primarily in-hospital, whereas excess non-COVID-19 deaths occurred in out-of-hospital settings. Municipal-level predictors of non-COVID-19 excess mortality included levels of social security coverage, higher rates of COVID-19 hospitalization and social marginalization. At the individual level, lower educational attainment, blue-collar employment and lack of medical care assistance prior to death were associated with non-COVID-19 deaths.

CONCLUSION

Non-COVID-19 causes of death, largely chronic cardiometabolic conditions, comprised up to one-fifth of excess deaths in Mexico during 2020. Non-COVID-19 excess deaths occurred disproportionately out-of-hospital and were associated with both individual- and municipal-level socio-demographic inequalities.

The impact of the SARS-CoV-2 pandemic on cause-specific mortality patterns: a systematic literature review

Background

Understanding the effects of the COVID-19 pandemic on cause-specific mortality should be a priority, as this metric allows for a detailed analysis of the true burden of the pandemic. The aim of this systematic literature review is to estimate the impact of the pandemic on different causes of death, providing a quantitative and qualitative analysis of the phenomenon.

Methods

We searched MEDLINE, Scopus, and ProQuest for studies that reported cause-specific mortality during the COVID-19 pandemic, extracting relevant data.

Results

A total of 2413 articles were retrieved, and after screening 22 were selected for data extraction. Cause-specific mortality results were reported using different units of measurement. The most frequently analyzed cause of death was cardiovascular diseases (n = 16), followed by cancer (n = 14) and diabetes (n = 11). We reported heterogeneous patterns of cause-specific mortality, except for suicide and road accident.

Conclusions

Evidence on non-COVID-19 cause-specific deaths is not exhaustive. Reliable scientific evidence is needed by policymakers to make the best decisions in an unprecedented and extremely uncertain historical period. We advocate for the urgent need to find an international consensus to define reliable methodological approaches to establish the true burden of the COVID-19 pandemic on non-COVID-19 mortality.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10389-022-01755-7.

The collateral damage of COVID-19 to cardiovascular services: a meta-analysis

AIMS

The effect of the COVID-19 pandemic on care and outcomes across non-COVID-19 cardiovascular (CV) diseases is unknown. A systematic review and meta-analysis was performed to quantify the effect and investigate for variation by CV disease, geographic region, country income classification and the time course of the pandemic.

METHODS AND RESULTS

From January 2019 to December 2021, Medline and Embase databases were searched for observational studies comparing a pandemic and pre-pandemic period with relation to CV disease hospitalisations, diagnostic and interventional procedures, outpatient consultations, and mortality. Observational data were synthesised by incidence rate ratios (IRR) and risk ratios (RR) for binary outcomes and weighted mean differences for continuous outcomes with 95% confidence intervals. The study was registered with PROSPERO (CRD42021265930). A total of 158 studies, covering 49 countries and 6 continents, were used for quantitative synthesis. Most studies (80%) reported information for high-income countries (HICs). Across all CV disease and geographies there were fewer hospitalisations, diagnostic and interventional procedures, and outpatient consultations during the pandemic. By meta-regression, in low-middle income countries (LMICs) compared to HICs the decline in ST-segment elevation myocardial infarction (STEMI) hospitalisations (RR 0.79, 95% confidence interval [CI] 0.66-0.94) and revascularisation (RR 0.73, 95% CI 0.62-0.87) was more severe. In LMICs, but not HICs, in-hospital mortality increased for STEMI (RR 1.22, 95% CI 1.10-1.37) and heart failure (RR 1.08, 95% CI 1.04-1.12). The magnitude of decline in hospitalisations for CV diseases did not differ between the first and second wave.

CONCLUSIONS

There was substantial global collateral CV damage during the COVID-19 pandemic with disparity in severity by country income classification.

Impact of the COVID-19 Pandemic on Cardiovascular Health in 2020: JACC State-of-the-Art Review

The impact of COVID-19 on the burden of cardiovascular diseases (CVD) during the early pandemic remains unclear. COVID-19 has become one of the leading causes of global mortality, with a disproportionate impact on persons with CVD. Studies of health facility admissions for CVD found significant decreases during the pandemic. Studies of hospital mortality for CVD were more variable. Studies of population-level CVD mortality differed across countries, with most showing decreases, although some revealed increases in deaths. In some countries where large increases in CVD deaths were reported in vital registration systems, misclassification of COVID-19 as CVD may have occurred. Taken together, studies suggest heterogeneous effects of the COVID-19 pandemic on CVD without large increases in CVD mortality in 2020 for a number of countries. Clinical and population science research is needed to examine the ways in which the pandemic has affected CVD burden.

Diabetes as a cause of death across different COVID-19 epidemic waves

AIMS

The aim of this study is to assess the role of diabetes as a cause of death through different epidemic waves of COVID-19.

METHODS

The annual percentage change in age-standardized rates (APC) was estimated for diabetes as the underlying (UCOD) and as multiple causes of death (MCOD) in 2008-2019. Diabetes-related deaths in 2020 were compared to the 2018-2019 average. SARIMA models were applied to monthly excess in mortality considering seasonality and long-term trends.

RESULTS

2018-2019-Age-standardized mortality rates decreased, especially among females (MCOD: APC -2.49, 95%CI -3.01/-1.97%). In 2020, deaths increased by 19% (95%CI 13-25%) for UCOD, and by 27% (95%CI 24-30%) for MCOD. Diabetes and COVID-19 accounted for 74% of such excess. During the first epidemic wave, the increase in observed rates vs predicted by the model was larger in males (March +39%, April +46%) than in females (+30% and +32%). In the second wave, a huge excess of similar magnitude was observed in the two sexes; rates in December exceeded those predicted by more than 100%.

CONCLUSIONS

The COVID-19 pandemic abruptly interrupted a long-term declining trend in mortality associated to diabetes. MCOD analyses are warranted to fully estimate the impact of epidemic waves on diabetes-related mortality.

COVID-19 Inpatient Deaths and Brought-in-Dead Cases in Malaysia

Coronavirus disease 2019 (COVID-19) deaths can occur in hospitals or otherwise. In Malaysia, COVID-19 deaths occurring outside of the hospital and subsequently brought to the hospital are known as brought-in-dead (BID) cases. To date, the characteristics of BID COVID-19 cases in Malaysia are not clear. The objectives of this study are 2-fold: to explore the characteristics of 29,155 mortality cases in Malaysia and determine the factors associated with the high probability of BID, using the multilevel logistic regression model. Data on COVID-19 mortality cases from the entire country between March 17, 2020 and November 3, 2021 were retrieved from a national open data source. Of the 29,155 COVID-19 mortality cases, 5,903 (20.2%) were BID. A higher probability of BID (p < 0.05) was seen among individuals aged between 18 and 59 years, non-Malaysians, had no comorbidities, did not receive COVID-19 vaccination, and the interval between the date of death and diagnosis. A high prevalence of BID is an alarming public health issue, as this may signal health system failure at one or several levels and, hence, need urgent attention from relevant stakeholders. Based on the findings of this study, increasing the intensity of the vaccination campaign, addressing any issues faced by noncitizens about to COVID-19 management in- and out-of-hospital, increasing the awareness of signs and symptoms of worsening COVID-19 and, hence, the significance of self-monitoring, and determining the potential gaps in the health system may contribute to their increased risk of deaths.

Excess mortality associated with the COVID-19 pandemic in Latvia: a population-level analysis of all-cause and noncommunicable disease deaths in 2020

Background

Age-standardised noncommunicable disease (NCD) mortality and the proportion of the elderly population in Latvia are high, while public health and health care systems are underresourced. The emerging COVID-19 pandemic raised concerns about its detrimental impact on all-cause and noncommunicable disease mortality in Latvia. We estimated the timing and number of excess all-cause and cause-specific deaths in 2020 in Latvia due to COVID-19 and selected noncommunicable diseases.

Methods

A time series analysis of all-cause and cause-specific weekly mortality from COVID-19, circulatory diseases, malignant neoplasms, diabetes mellitus, and chronic lower respiratory diseases from the National Causes of Death Database from 2015 to 2020 was used by applying generalised additive modelling (GAM) and joinpoint regression analysis.

Results

Between weeks 14 and 52 (from 1 April to 29 December) of 2020, a total of 3111 excess deaths (95% PI 1339 – 4832) were estimated in Latvia, resulting in 163.77 excess deaths per 100 000. Since September 30, with the outbreak of the second COVID-19 wave, 55% of all excess deaths have occurred. Altogether, COVID-19-related deaths accounted for only 28% of the estimated all-cause excess deaths. A significant increase in excess mortality was estimated for circulatory diseases (68.91 excess deaths per 100 000). Ischemic heart disease and cerebrovascular disease were listed as the underlying cause in almost 60% of COVID-19-contributing deaths.

Conclusions

All-cause mortality and mortality from circulatory diseases significantly increased in Latvia during the first pandemic year. All-cause excess mortality substantially exceeded reported COVID-19-related deaths, implying COVID-19-related mortality during was significantly underestimated. Increasing mortality from circulatory diseases suggests a negative cumulative effect of COVID-19 exposure and reduced access to healthcare services for NCD patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13491-4.

Impact of the COVID-19 pandemic on acute otolaryngology inpatient activity at a tertiary referral centre: a retrospective analysis

Objective

To determine the impact of the COVID‐19 pandemic on acute admissions and inpatient activity at a tertiary referral centre.

Design

Retrospective review of coding‐based inpatient electronic records.

Setting

An otolaryngology and head and neck surgery department at a major UK trauma and tertiary referral centre.

Participants

Otolaryngology patients admitted as an emergency over a period of 10 months pre‐COVID19 (01/04/2019‐23/01/2020) and 10 months post‐COVID19 (01/04/2020‐23/01/2021).

Main outcome measures

Baseline characteristics, admission rates, length of stay (LoS), overall mortality and 30‐day mortality.

Results

A total of 1620 records were reviewed; (1066 pre‐COVID19, 554 post‐COVID19). Admissions across all age groups were reduced, with an increase in mean age from 39.88 to 47.4 years (p = .018). LoS remained unchanged (3.85 vs 3.82 days, p = .160). Infection remained the most common presentation, followed secondly by epistaxis which entailed an increased LoS compared to the pre‐COVID19 cohort. GP referrals reduced from 18.3% to 4.2% (n = 195 vs n = 23, p < .001) and ED referrals proportionally increased from 71.9% to 85.9% (n = 766 vs n = 476, p < .001). Critical care admissions were higher in the post‐COVID19 cohort (OR 1.78 (1.07–2.98) [95% CI], p = .027).

There was no significant difference in overall mortality between groups (n = 60, 5.6% vs. n = 33, 6.0%; p = .844). Thirty‐day mortality increased from 0.9% (n = 12) pre‐COVID19 to 2.3% (n = 13) post‐COVID19 (p = .039).

Conclusions

This study demonstrates significant changes and a reduction in acute otolaryngology presentations. Our findings may suggest that sicker, frailer patients were admitted during the pandemic. This study reports the observational effect that the pandemic has had on acute otolaryngology admissions, which may be relevant in addressing unmet care needs in the post‐pandemic period.

Excess years of life lost to COVID-19 and other causes of death by sex, neighbourhood deprivation, and region in England and Wales during 2020: A registry-based study

BACKGROUND

Deaths in the first year of the Coronavirus Disease 2019 (COVID-19) pandemic in England and Wales were unevenly distributed socioeconomically and geographically. However, the full scale of inequalities may have been underestimated to date, as most measures of excess mortality do not adequately account for varying age profiles of deaths between social groups. We measured years of life lost (YLL) attributable to the pandemic, directly or indirectly, comparing mortality across geographic and socioeconomic groups.

METHODS AND FINDINGS

We used national mortality registers in England and Wales, from 27 December 2014 until 25 December 2020, covering 3,265,937 deaths. YLLs (main outcome) were calculated using 2019 single year sex-specific life tables for England and Wales. Interrupted time-series analyses, with panel time-series models, were used to estimate expected YLL by sex, geographical region, and deprivation quintile between 7 March 2020 and 25 December 2020 by cause: direct deaths (COVID-19 and other respiratory diseases), cardiovascular disease and diabetes, cancer, and other indirect deaths (all other causes). Excess YLL during the pandemic period were calculated by subtracting observed from expected values. Additional analyses focused on excess deaths for region and deprivation strata, by age-group. Between 7 March 2020 and 25 December 2020, there were an estimated 763,550 (95% CI: 696,826 to 830,273) excess YLL in England and Wales, equivalent to a 15% (95% CI: 14 to 16) increase in YLL compared to the equivalent time period in 2019. There was a strong deprivation gradient in all-cause excess YLL, with rates per 100,000 population ranging from 916 (95% CI: 820 to 1,012) for the least deprived quintile to 1,645 (95% CI: 1,472 to 1,819) for the most deprived. The differences in excess YLL between deprivation quintiles were greatest in younger age groups; for all-cause deaths, a mean of 9.1 years per death (95% CI: 8.2 to 10.0) were lost in the least deprived quintile, compared to 10.8 (95% CI: 10.0 to 11.6) in the most deprived; for COVID-19 and other respiratory deaths, a mean of 8.9 years per death (95% CI: 8.7 to 9.1) were lost in the least deprived quintile, compared to 11.2 (95% CI: 11.0 to 11.5) in the most deprived. For all-cause mortality, estimated deaths in the most deprived compared to the most affluent areas were much higher in younger age groups, but similar for those aged 85 or over. There was marked variability in both all-cause and direct excess YLL by region, with the highest rates in the North West. Limitations include the quasi-experimental nature of the research design and the requirement for accurate and timely recording.

CONCLUSIONS

In this study, we observed strong socioeconomic and geographical health inequalities in YLL, during the first calendar year of the COVID-19 pandemic. These were in line with long-standing existing inequalities in England and Wales, with the most deprived areas reporting the largest numbers in potential YLL.

Variation in Cause-Specific Mortality Rates in Italy during the First Wave of the COVID-19 Pandemic: A Study Based on Nationwide Data

Italy was a country severely hit by the first coronavirus disease 2019 (COVID-19) pandemic wave in early 2020. Mortality studies have focused on the overall excess mortality observed during the pandemic. This paper investigates the cause-specific mortality in Italy from March 2020 to April 2020 and the variation in mortality rates compared with those in 2015-2019 regarding sex, age, and epidemic area. Causes of death were derived from the national cause-of-death register. COVID-19 was the leading cause of death among males and the second leading cause among females. Chronic diseases, such as diabetes and hypertensive, ischemic heart, and cerebrovascular diseases, with decreasing or stable mortality rates in 2015-2019, showed a reversal in the mortality trend. Moreover, mortality due to pneumonia and influenza increased. No increase in neoplasm mortality was observed. Among external causes of death, mortality increased for accidental falls but reduced for transport accidents and suicide. Mortality from causes other than COVID-19 increased similarly in both genders and more at ages 65 years or above. Compared with other areas in Italy, the Lombardy region showed the largest excess in mortality for all leading causes. Underdiagnosis of COVID-19 at the beginning of the pandemic may, to some extent, explain the mortality increase for some causes of death, especially pneumonia and other respiratory diseases.

Factors associated with excess all-cause mortality in the first wave of the COVID-19 pandemic in the UK: A time series analysis using the Clinical Practice Research Datalink

BACKGROUND

Excess mortality captures the total effect of the Coronavirus Disease 2019 (COVID-19) pandemic on mortality and is not affected by misspecification of cause of death. We aimed to describe how health and demographic factors were associated with excess mortality during, compared to before, the pandemic.

METHODS AND FINDINGS

We analysed a time series dataset including 9,635,613 adults (≥40 years old) registered at United Kingdom general practices contributing to the Clinical Practice Research Datalink. We extracted weekly numbers of deaths and numbers at risk between March 2015 and July 2020, stratified by individual-level factors. Excess mortality during Wave 1 of the UK pandemic (5 March to 27 May 2020) compared to the prepandemic period was estimated using seasonally adjusted negative binomial regression models. Relative rates (RRs) of death for a range of factors were estimated before and during Wave 1 by including interaction terms. We found that all-cause mortality increased by 43% (95% CI 40% to 47%) during Wave 1 compared with prepandemic. Changes to the RR of death associated with most sociodemographic and clinical characteristics were small during Wave 1 compared with prepandemic. However, the mortality RR associated with dementia markedly increased (RR for dementia versus no dementia prepandemic: 3.5, 95% CI 3.4 to 3.5; RR during Wave 1: 5.1, 4.9 to 5.3); a similar pattern was seen for learning disabilities (RR prepandemic: 3.6, 3.4 to 3.5; during Wave 1: 4.8, 4.4 to 5.3), for black or South Asian ethnicity compared to white, and for London compared to other regions. Relative risks for morbidities were stable in multiple sensitivity analyses. However, a limitation of the study is that we cannot assume that the risks observed during Wave 1 would apply to other waves due to changes in population behaviour, virus transmission, and risk perception.

CONCLUSIONS

The first wave of the UK COVID-19 pandemic appeared to amplify baseline mortality risk to approximately the same relative degree for most population subgroups. However, disproportionate increases in mortality were seen for those with dementia, learning disabilities, non-white ethnicity, or living in London.

Changing Patterns of Bloodstream Infections in the Community and Acute Care Across 2 Coronavirus Disease 2019 Epidemic Waves: A Retrospective Analysis Using Data Linkage

BACKGROUND

We examined community- and hospital-acquired bloodstream infections (BSIs) in coronavirus disease 2019 (COVID-19) and non-COVID-19 patients across 2 epidemic waves.

METHODS

We analyzed blood cultures of patients presenting to a London hospital group between January 2020 and February 2021. We reported BSI incidence, changes in sampling, case mix, healthcare capacity, and COVID-19 variants.

RESULTS

We identified 1047 BSIs from 34 044 blood cultures, including 653 (62.4%) community-acquired and 394 (37.6%) hospital-acquired. Important pattern changes were seen. Community-acquired Escherichia coli BSIs remained below prepandemic level during COVID-19 waves, but peaked following lockdown easing in May 2020, deviating from the historical trend of peaking in August. The hospital-acquired BSI rate was 100.4 per 100 000 patient-days across the pandemic, increasing to 132.3 during the first wave and 190.9 during the second, with significant increase in elective inpatients. Patients with a hospital-acquired BSI, including those without COVID-19, experienced 20.2 excess days of hospital stay and 26.7% higher mortality, higher than reported in prepandemic literature. In intensive care, the BSI rate was 421.0 per 100 000 intensive care unit patient-days during the second wave, compared to 101.3 pre-COVID-19. The BSI incidence in those infected with the severe acute respiratory syndrome coronavirus 2 Alpha variant was similar to that seen with earlier variants.

CONCLUSIONS

The pandemic have impacted the patterns of community- and hospital-acquired BSIs, in COVID-19 and non-COVID-19 patients. Factors driving the patterns are complex. Infection surveillance needs to consider key aspects of pandemic response and changes in healthcare practice.