Death Certificate-Based ICD-10 Diagnosis Codes for COVID-19 Mortality Surveillance - United States, January-December 2020

Mortality of older construction and craft workers employed at Department of Energy (DOE) nuclear sites: Follow-up through 2021

BACKGROUND

To determine if construction and trades workers formerly employed at US Department of Energy (DOE) nuclear weapons sites are at significant risk for occupational diseases, we studied the mortality experience of participants in the Building Trades National Medical Screening Program (BTMed).

METHODS

The cohort included 26,922 participants enrolled between 1998 and 2021 and 8367 deaths. Standardized mortality ratios were calculated based on US death rates. Cox models compared construction workers (n = 22,747; 7487 deaths) to two nonconstruction subpopulations: administrative, scientific and security workers (n = 1894; 330 deaths), and all other nonconstruction workers (n = 2218; 550 deaths).

RESULTS

Mortality was elevated for all causes, all cancers, cancers of the trachea, bronchus, lung, kidneys, and lymphatic and hematopoietic system, mesothelioma, chronic obstructive pulmonary disease (COPD), asbestosis, transportation injuries, and other injuries, particularly accidental poisonings. There were 167 deaths from coronavirus disease 2019 (COVID-19), which was lower than expected using US death rates. Overall cause-specific mortality was significantly higher among construction workers than for internal comparison groups.

CONCLUSIONS

Construction workers employed at DOE sites have a significantly increased risk for occupational illnesses. Apart from COVID-19 deaths, this update: (1) found that mortality among construction workers is significantly elevated compared to the US population and significantly higher than in the internal comparison populations, and (2) confirmed excess risk for these workers for first employment after 1990. Cancer mortality risks are similar to the cancers identified for DOE compensation from radiation exposures. The high lung cancer risk supports the value of early lung cancer detection. Continued medical surveillance is important.

Trends and disparities in deaths among young persons in the US during the COVID-19 pandemic

PURPOSE

To examine changes in death rates by demographic group and by the leading causes of death in U.S. persons 1 to 24 years of age during the COVID-19 pandemic.

METHODS

A retrospective cross-sectional study using mortality data from the National Vital Statistics System from April 2017 to March 2023. Pre-pandemic death rates were compared with death rates during the pandemic overall, by race/ethnicity, age, sex, and cause group.

RESULTS

Age-adjusted death rates in young persons 1-24 years of age increased by 14.3% during the pandemic. Injury-related causes accounted for 78.2% of the increase, driven mainly by increases in homicides and unintentional injuries related to drug overdose, firearms, and motor-vehicle traffic crashes. Non-Hispanic Black and Hispanic teens and young adults experienced the largest increases in deaths overall and across the leading causes of death.

CONCLUSIONS

During the COVID-19 pandemic, injury-related causes accounted for the majority of the increases in deaths in children and young adults, driven mainly by firearms, drug overdoses, and motor vehicle traffic crashes. Findings highlight the importance of understanding the drivers of these marked increases in injury-related mortality and the need for injury prevention efforts among children even in the context of an infectious disease pandemic.

Adverse delivery hospitalisation outcomes in 2020 during the COVID-19 pandemic

OBJECTIVE

To evaluate risk for adverse obstetric outcomes associated with the coronavirus disease 2019 (COVID-19) pandemic period and with COVID-19 diagnoses.

DESIGN

Serial cross-sectional study.

SETTING

A national sample of US delivery hospitalisations before (1/2016 to 2/2020) and during the first 10 months of (3/2020 to 12/2020) the COVID-19 pandemic.

POPULATION

All 2016-2020 US delivery hospitalisations in the National Inpatient Sample.

METHODS

Delivery hospitalisations were identified and stratified into pre-pandemic and pandemic periods and the likelihood of adverse obstetric outcomes was compared using logistic regression models with adjusted odds ratios (aOR) with 95% confidence intervals (CI) as measures of association. Risk for adverse outcomes was also analysed specifically for 2020 deliveries with a COVID-19 diagnosis.

MAIN OUTCOME MEASURE

Adverse maternal outcomes including respiratory complications and cardiac morbidity.

RESULTS

Of an estimated 18.2 million deliveries, 2.9 million occurred during the pandemic. The proportion of delivery hospitalisations with a COVID-19 diagnosis increased from 0.1% in March 2020 to 3.1% in December. Comparing the pandemic period to the pre-pandemic period, there were higher adjusted odds of transfusion (aOR 1.12, 95% CI 1.05-1.19), a respiratory complication composite (aOR 1.37, 95% CI 1.29-1.46), cardiac severe maternal morbidity (aOR 1.30, 95% 1.20-1.39), postpartum haemorrhage (aOR 1.19, 95% CI 1.15-1.24), placental abruption/antepartum haemorrhage (OR 1.04, 95% CI 1.00-1.08), and hypertensive disorders of pregnancy (OR 1.23, 95% CI 1.21-1.26). These associations were similar to unadjusted analysis. Risk for these outcomes during the pandemic period was significantly higher in the presence of a COVID-19 diagnosis.

CONCLUSIONS

In a national estimate of delivery hospitalisations, the odds of cardiac and respiratory outcomes were higher in 2020 compared with 2016-2019. COVID-19 diagnoses were specifically associated with a range of serious complications.

Meta-Analysis of COVID-19 BAL Single-Cell RNA Sequencing Reveals Alveolar Epithelial Transitions and Unique Alveolar Epithelial Cell Fates

Single-cell RNA sequencing (scRNA-seq) of BAL cells has provided insights into coronavirus disease (COVID-19). However, reports have been limited by small patient cohorts. We performed a meta-analysis of BAL scRNA-seq data from healthy control subjects (n = 13) and patients with COVID-19 (n = 20), sourced from six independent studies (167,280 high-quality cells in total). Consistent with the source reports, increases in infiltrating leukocyte subtypes were noted, several with type I IFN signatures and unique gene expression signatures associated with transcellular chemokine signaling. Noting dramatic reductions of inferred NKX2-1 and NR4A1 activity in alveolar epithelial type II (AT-II) cells, we modeled pseudotemporal AT-II-to-AT-I progression. This revealed changes in inferred AT-II cell metabolic activity, increased transitional cells, and a previously undescribed AT-I state. This cell state was conspicuously marked by the induction of genes of the epidermal differentiation complex, including the cornified envelope protein SPRR3 (small proline-rich protein 3), upregulation of multiple KRT (keratin) genes, inferred mitochondrial dysfunction, and cell death signatures including apoptosis and ferroptosis. Immunohistochemistry of lungs from patients with COVID-19 confirmed upregulation and colocalization of KRT13 and SPRR3 in the distal airspaces. Forced overexpression of SPRR3 in human alveolar epithelial cells ex vivo did not activate caspase-3 or upregulate KRT13, suggesting that SPRR3 marks an AT-I cornification program in COVID-19 but is not sufficient for phenotypic changes.

Maintaining the Utility of Coronavirus Disease 2019 Pandemic Severity Surveillance: Evaluation of Trends in Attributable Deaths and Development and Validation of a Measurement Tool

BACKGROUND

Death within a specified time window following a positive SARS-CoV-2 test is used by some agencies for attributing death to COVID-19. With Omicron variants, widespread immunity, and asymptomatic screening, there is cause to re-evaluate COVID-19 death attribution methods and develop tools to improve case ascertainment.

METHODS

All patients who died following microbiologically confirmed SARS-CoV-2 in the Veterans Health Administration (VA) and at Tufts Medical Center (TMC) were identified. Records of selected vaccinated VA patients with positive tests in 2022, and of all TMC patients with positive tests in 2021-2022, were manually reviewed to classify deaths as COVID-19-related (either directly caused by or contributed to), focused on deaths within 30 days. Logistic regression was used to develop and validate a surveillance model for identifying deaths in which COVID-19 was causal or contributory.

RESULTS

Among vaccinated VA patients who died ≤30 days after a positive test in January-February 2022, death was COVID-19-related in 103/150 cases (69%) (55% causal, 14% contributory). In June-August 2022, death was COVID-19-related in 70/150 cases (47%) (22% causal, 25% contributory). Similar results were seen among the 71 patients who died at TMC. A model including hypoxemia, remdesivir, and anti-inflammatory drugs had positive and negative predictive values of 0.82-0.95 and 0.64-0.83, respectively.

CONCLUSIONS

By mid-2022, "death within 30 days" did not provide an accurate estimate of COVID-19-related death in 2 US healthcare systems with routine admission screening. Hypoxemia and use of antiviral and anti-inflammatory drugs-variables feasible for reporting to public health agencies-would improve classification of death as COVID-19-related.

Estimate of COVID-19 Deaths, China, December 2022-February 2023

China announced a slight easing of its zero-COVID rules on November 11, 2022, and then a major relaxation on December 7, 2022. We estimate that the ensuing wave of SARS-CoV-2 infections caused 1.41 million deaths in China during December 2022-February 2023, substantially higher than that reported through official channels.

Immediate cause and the role of multimorbidity in deaths associated with COVID 19 among hospitalized patients in a low resource district in Kerala India: A record-based case-control analysis

Introduction

Multimorbidity is the coexistence of two or more chronic medical conditions in a person. The study aims to investigate the immediate cause of death and risk factors of mortality including multimorbidity among patients hospitalized with SARS CoV2 infection in Kasaragod district in Kerala, India.

Methods

A record-based case-control study was done using the hospital records and follow-up surveillance system of SARS-COV 2 patients admitted in the Kasaragod district. SARS-COV 2 patients who had expired during the study period from June to December 2020 and reported as COVID-19 deaths (N = 226) were the cases, and an equal number of hospital controls were the study participants.

Results

The mean (SD) age of the cases and controls were found to be 64.6 (14.2) years and 61.5 (13.4) years, respectively. Covid pneumonia alone was reported as the cause of death in more than half (52%) of the study participants. This was followed by cardiovascular events (8.5%) and acute kidney injury (6.5%). Among individual comorbidities among people who expired, diabetes mellitus (53%) was the most common, followed by hypertension (46%) and cardiovascular diseases (23%). More than 50% were found to have multimorbidity. Logistic regression showed chronic kidney disease (CKD) (Adjusted odds ratio (AOR) = 2.18 (1.24-3.83)) and malignancy (AOR = 3.05 (1.27-7.32)) to be significantly associated with mortality as individual determinants. Hypertension-diabetes mellitus [AOR = 1.68 (1.02-2.76), P = 0.043] and hypertension-CKD [AOR = 3.49 (1.01-12.01), P = 0.48] dyads were multimorbidities significantly associated with mortality.

Conclusion

Combinations of hypertension with diabetes mellitus and CKD were found to be significant determinants for mortality in hospitalized COVID-19 patients. Uniformity in death certification is required to understand the causes and contributors to death in COVID-19.

Cremation Permit Review and COVID-19 Death Certificates

ABSTRACT

Data derived from death certificates (DCs) is an important resource for mortality statistics, disease surveillance, and the creation of public health policies. This study involved the review of COVID-19 DCs occurring during the normal course of DC review for cremation approval purposes in a medical examiner office. During the review process since the occurrence of the pandemic, it was noticed that a significant percentage of COVID-19 DCs being reviewed did not include any comorbid conditions as contributing to death, despite reports, both within the medical literature and within the media, that suggested that most deaths occur in people with known risk factors. The study involved medical record review for COVID-19 DCs that did not list any comorbid conditions. The results indicated that a vast majority of such cases did, in fact, have significant comorbid conditions, such that they should have been listed on the DCs.

Risk factors for deaths associated with COVID-19 according to the cause of death classification in Republic of Korea

OBJECTIVES

This study aimed to classify coronavirus disease 2019 (COVID-19)-related deaths according to whether COVID-19 was listed as the cause of death, and to investigate the differences in demographic characteristics and risk factors for COVID-19 death classifications.

METHODS

A total of 5,625 deaths in South Korea among patients with confirmed COVID-19 from January 20, 2020 to December 31, 2021 were selected. Excluding false reports and unnatural deaths, 5,597 deaths were analyzed. Based on death report data, deaths were classified according to whether the cause of death was listed as COVID-19 (CD) or not (NCD). The epidemiological characteristics and causes of deaths were investigated using descriptive, univariate, and multivariate statistical analyses. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to analyze the risk factors.

RESULTS

The case fatality ratio was 0.89% and increased with age. Additionally, 96.4% of the subjects had an underlying disease, and 53.4% died in winter. The proportion of NCDs was 9.3%, of whom 19.1% died at home and 39.0% were confirmed to have COVID-19 after death. Malignant neoplasms (102/416 vs. 637/4,442; OR, 1.71; 95% CI, 1.36-2.16; p<0.001) were significantly associated with NCD.

CONCLUSION

This is the first study to analyze risk factors by cause of death using COVID-19 death report data in South Korea. These results are expected to be used as evidence for establishing a death monitoring system that can collect timely information in a new infectious disease pandemic.

Factors Associated with COVID-19 Death in a High-Altitude Peruvian Setting during the First 14 Months of the Pandemic: A Retrospective Multicenter Cohort Study in Hospitalized Patients

Risk factors for COVID-19 death in high-altitude populations have been scarcely described. This study aimed to describe risk factors for COVID-19 death in three referral hospitals located at 3399 m in Cusco, Peru, during the first 14 months of the pandemic. A retrospective multicenter cohort study was conducted. A random sample of ~50% (1225/2674) of adult hospitalized patients who died between 1 March 2020 and 30 June 2021 was identified. Of those, 977 individuals met the definition of death by COVID-19. Demographic characteristics, intensive care unit (ICU) admission, invasive respiratory support (IRS), disease severity, comorbidities, and clinical manifestation at hospital admission were assessed as risk factors using Cox proportional-hazard models. In multivariable models adjusted by age, sex, and pandemic periods, critical disease (vs. moderate) was associated with a greater risk of death (aHR: 1.27; 95%CI: 1.14–1.142), whereas ICU admission (aHR: 0.39; 95%CI: 0.27–0.56), IRS (aHR: 0.37; 95%CI: 0.26–0.54), the ratio of oxygen saturation (ROX) index ≥ 5.3 (aHR: 0.87; 95%CI: 0.80–0.94), and the ratio of SatO2/FiO2 ≥ 122.6 (aHR: 0.96; 95%CI: 0.93–0.98) were associated with a lower risk of death. The risk factors described here may be useful in assisting decision making and resource allocation.

Mortality by Education Before and During the COVID-19 Pandemic, U.S., 2017-2020

INTRODUCTION

Mortality disparities by SES, including education, have steadily increased in the U.S. over the past decades. This study examined whether these disparities overall and for 7 major causes of death were exacerbated in 2020, coincident with the emergence of the COVID-19 pandemic.

METHODS

Using data on 7,123,254 U.S. deaths from 2017 to 2020, age-standardized death rates and mortality rate differences per 100,000 population and rate ratios comparing least with most educated were calculated by sex and race/ethnicity.

RESULTS

All-cause death rates were approximately 2 times higher among adults with least than among those with most education. Disparities in all-cause mortality by educational attainment slightly increased from 2017 (rate ratio=1.97; 95% CI=1.95, 1.98; rate difference=739.9) to 2019 (rate ratio=2.04; 95% CI=2.03, 2.06; rate difference=761.3) and then greatly increased in 2020 overall (rate ratio=2.32; 95% CI=2.30, 2.33; rate difference=1,042.9) and when excluding COVID-19 deaths (rate ratio=2.27; 95% CI=2.25, 2.28; rate difference=912.3). Similar patterns occurred across race/ethnicity and sex, although Hispanic individuals had the greatest relative increase in disparities for all-cause mortality from 2019 (rate ratio=1.47; 95% CI=1.43, 1.51; rate difference=282.4) to 2020 overall (rate ratio=2.00; 95% CI=1.94, 2.06; rate difference=652.3) and when excluding COVID-19 deaths (rate ratio=1.84; 95% CI=1.79, 1.90; rate difference=458.7). Disparities in cause-specific mortality by education were generally stable from 2017 to 2019, followed by a considerable increase from 2019 to 2020 for heart disease, cancer, cerebrovascular disease, and unintentional injury. Among these causes of death, the relative increase in rate ratio from 2019 to 2020 was greatest for unintentional injury (24.8%; from 3.41 [95% CI=3.23, 3.60] to 4.26 [95% CI=3.99, 4.53]).

CONCLUSIONS

Mortality disparities by education widened in the U.S. in 2020, during the COVID-19 pandemic. Further research is warranted to understand the reasons for these widened disparities.

COVID-19-related excess mortality - an overview of the current evidence

Analysis of excess deaths, defined as the difference in the total number of deaths in an emergency compared to the number of deaths expected under normal conditions, allows a more reliable assessment of the impact on health systems caused by the global threat of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2). So far, data for the two years of the pandemic (2020-2021) indicates the occurrence of 14.9 million excess deaths according to WHO (World Health Organization) estimates. The purpose of the analysis conducted was to define the concept and identify the causes of excess mortality during the COVID-19 pandemic. Inconsistent and unreliable death registration systems; overburdened health systems in low- and middle-income countries; reduced access to medical services for patients with health problems other than COVID-19; the introduction of social distancing and lockdown rules, which translated into increased deaths from psychiatric illnesses and addictions; political considerations and media messages that interfered with vaccination acceptance and adherence; and the additional impact of other natural disasters (hurricanes, floods, drought) were identified as the most important reasons for excess deaths occurrence. The correct identification of country-specific factors and the correct response and countermeasures taken appear crucial in terms of limiting the negative impact of the current pandemic, but also of future threats of a similar nature, in order to reduce excess deaths.

Biases in COVID-19 Case and Death Definitions: Potential Causes and Consequences

This paper investigates three controversies involving potential causes and consequences of information bias in case and death definitions during the coronavirus disease (COVID-19) pandemic. First, evidence suggests China's surveillance data were biased and misinterpreted by the World Health Organization (WHO), prompting the WHO to advise nations to copy China's lockdowns. China appeared to use narrow diagnostic definitions that undercounted cases and deaths. Second, novel genomic data disseminated during the pandemic without adequate guidance from rigorous epidemiologic studies biased infection control policies in many countries. A novel genomic sequence of a virus is insufficient to declare new cases of a novel disease. Third, media reports of COVID-19 surveillance data in many nations appeared to be biased. Broadened surveillance definitions captured additional information, but unadjusted surveillance data disseminated to the public are not true cases and deaths. Recommendations include clarification of the proper use of diagnostic and surveillance case and death definitions to avoid information bias.

Association between Short-Term Exposure to Air Pollution and COVID-19 Mortality: A Population-Based Case-Crossover Study Using Individual-Level Mortality Registry Confirmed by Medical Examiners

BACKGROUND

Studies have suggested links between ambient air pollution and coronavirus 2019 (COVID-19) mortality, yet confirmation by well-designed epidemiological studies with individual data is needed.

OBJECTIVES

We aimed to examine whether short-term exposure to air pollution is associated with risk of mortality from COVID-19 for those infected with COVID-19.

METHODS

The Cook County Medical Examiner's Office reports individual-level data for deaths from COVID-19 that occur in its jurisdiction, which includes all confirmed COVID-19 deaths in Cook County, Illinois. Case-crossover analysis was conducted to estimate the associations of estimated short-term exposures to particulate matter (PM) with aerodynamic diameter ≤2.5μm (PM2.5) and ozone (O3) on the day of death and up to 21 d before death at location of death with COVID-19. A total of 7,462 deaths from COVID-19 that occurred up to 28 February 2021 were included in the final analysis. We adjusted for potential confounders by time-stratified case-crossover design and by covariate adjustments (i.e., time-invariant factors, meteorological factors, viral transmission, seasonality, and time trend).

RESULTS

Of the 7,462 case and 25,457 self-control days, almost all were days with exposure levels below the PM2.5 24-h National Ambient Air Quality Standard (NAAQS) (35 μg/m3); 98.9% had O3 levels below the maximum 8-h NAAQS (35.7 μg/m3 or 70 parts per billion). An interquartile range (IQR) increase (5.2 μg/m3) in cumulative 3-wk PM2.5 exposure was associated with a 69.6% [95% confidence interval (CI): 34.6, 113.8] increase in risk of COVID-19 mortality. An IQR increase (8.2 μg/m3) in 3-d O3 exposure was associated with a 29.0% (95% CI: 9.9, 51.5) increase in risk of COVID-19 mortality. The associations differed by demographics or race/ethnicity. There was indication of modification of the associations by some comorbid conditions.

DISCUSSION

Short-term exposure to air pollution below the NAAQS may increase the mortality burden from COVID-19. https://doi.org/10.1289/EHP10836.

COVID-19 mortality burden and comorbidity patterns among decedents with and without intellectual and developmental disability in the US

BACKGROUND

While there is ample evidence of increased COVID-19 mortality risk among people with intellectual and developmental disability (IDD), research has not documented whether this higher risk resulted in increased COVID-19 mortality burden in the US or whether comorbidity patterns among COVID-19 deaths are similar or distinct for people with IDD.

OBJECTIVE

To determine the differences in COVID-19 mortality burden between decedents with and without IDD during the first year of the pandemic.

METHODS

This study uses 2020 US death certificate data to compare COVID-19 mortality burden and comorbidity patterns among decedents with and without IDD.

RESULTS

COVID-19 was the leading cause of death among decedents with IDD in 2020, compared with the 3rd leading cause among decedents without IDD. The proportion of deaths from COVID-19 was also higher for decedents with compared to without IDD. Comorbidities resulting from COVID-19 were similar among decedents with and without IDD, but there were some differences among reported pre-existing conditions, notably higher rates of hypothyroidism and seizures among decedents with IDD.

CONCLUSION

The COVID-19 mortality burden was greater for people with than without IDD during the first year of the pandemic. The continued practice of postmortem diagnostic overshadowing prevents analyzing whether this difference continues through today. Action is needed by the Centers for Disease Control and Prevention to mitigate this data inequity. Out of an abundance of caution, medical providers should carefully monitor symptoms among COVID-19 patients with IDD diagnosed with hypothyroidism and/or seizures.

Inaccurate recording of routinely collected data items influences identification of COVID-19 patients

Background

During the Coronavirus disease 2019 (COVID-19) pandemic it became apparent that it is difficult to extract standardized Electronic Health Record (EHR) data for secondary purposes like public health decision-making. Accurate recording of, for example, standardized diagnosis codes and test results is required to identify all COVID-19 patients. This study aimed to investigate if specific combinations of routinely collected data items for COVID-19 can be used to identify an accurate set of intensive care unit (ICU)-admitted COVID-19 patients.

Methods

The following routinely collected EHR data items to identify COVID-19 patients were evaluated: positive reverse transcription polymerase chain reaction (RT-PCR) test results; problem list codes for COVID-19 registered by healthcare professionals and COVID-19 infection labels. COVID-19 codes registered by clinical coders retrospectively after discharge were also evaluated. A gold standard dataset was created by evaluating two datasets of suspected and confirmed COVID-19-patients admitted to the ICU at a Dutch university hospital between February 2020 and December 2020, of which one set was manually maintained by intensivists and one set was extracted from the EHR by a research data management department. Patients were labeled ‘COVID-19′ if their EHR record showed diagnosing COVID-19 during or right before an ICU-admission. Patients were labeled ‘non-COVID-19′ if the record indicated no COVID-19, exclusion or only suspicion during or right before an ICU-admission or if COVID-19 was diagnosed and cured during non-ICU episodes of the hospitalization in which an ICU-admission took place. Performance was determined for 37 queries including real-time and retrospective data items. We used the F₁ score, which is the harmonic mean between precision and recall. The gold standard dataset was split into one subset including admissions between February and April and one subset including admissions between May and December to determine accuracy differences.

Results

The total dataset consisted of 402 patients: 196 ‘COVID-19′ and 206 ‘non-COVID-19′ patients. F₁ scores of search queries including EHR data items that can be extracted real-time ranged between 0.68 and 0.97 and for search queries including the data item that was retrospectively registered by clinical coders F₁ scores ranged between 0.73 and 0.99. F₁ scores showed no clear pattern in variability between the two time periods.

Conclusions

Our study showed that one cannot rely on individual routinely collected data items such as coded COVID-19 on problem lists to identify all COVID-19 patients. If information is not required real-time, medical coding from clinical coders is most reliable. Researchers should be transparent about their methods used to extract data. To maximize the ability to completely identify all COVID-19 cases alerts for inconsistent data and policies for standardized data capture could enable reliable data reuse.

Parkinson's disease related mortality: Long-term trends and impact of COVID-19 pandemic waves

Introduction

Parkinson's disease (PD) mortality burden is increasing worldwide, but accurate estimates on the magnitude of the impact of the COVID-19 pandemic are missing. Mortality rates vary largely when considering PD as underlying cause of death (UCOD), or as one among multiple causes reported in death certificates (MCOD). The aim of this study is to assess COVID-19 impact on PD-related mortality trends using the UCOD and MCOD approach.

Methods

Mortality records between 01/2008-12/2020 of residents aged ≥45 years in Veneto Region (Northeastern Italy) with any mention of PD were collected. Age-standardized sex-specific mortality rates were estimated for PD-related deaths as UCOD and MCOD to assess time trends. The average annual percentage change in age-standardized rates (AAPC) was estimated by linear regression models. Monthly mortality in 2020, the first year of the pandemic, was plotted against the 2018–2019 average.

Results

Overall, 13,746 PD-related deaths (2.3% of all deaths) were identified, 52% males, median age 84 years. Proportional mortality increased from 1.9% (2008) to 2.8% (2020). AAPC through 2008–2019 was +5.2% for males and +5.3% for females in analyses of the UCOD, and +1.4% in both genders based on MCOD. Excess in PD-related mortality during 2020 corresponded to 19% for UCOD and 28% for MCOD, with the latter showing two peaks corresponding to the first (28%) and second (59%) pandemic waves.

Conclusion

Age-standardized PD-related mortality rates have steeply increased during COVID-19 pandemic, amplifying a pre-existing long-term trend. Hence, surveillance of mortality associated to PD is warranted in the forthcoming pandemic and post-pandemic years.

Health Literacy, Equity, and Communication in the COVID-19 Era of Misinformation: Emergence of Health Information Professionals in Infodemic Management

The health information management (HIM) field’s contribution to health care delivery is invaluable in a pandemic context where the need for accurate diagnoses will hasten responsive, evidence-based decision-making. The COVID-19 pandemic offers a unique opportunity to transform the practice of HIM and bring more awareness to the role that frontline workers play behind the scenes in safeguarding reliable, comprehensive, accurate, and timely health information. This transformation will support future research, utilization management, public health surveillance, and forecasting and enable key stakeholders to plan and ensure equitable health care resource allocation, especially for the most vulnerable populations. In this paper, we juxtapose critical health literacy, public policy, and HIM perspectives to understand the COVID-19 infodemic and new opportunities for HIM in infodemic management.

Prediction of the need for intensive oxygen supplementation during hospitalisation among subjects with COVID-19 admitted to an academic health system in Texas: a retrospective cohort study and multivariable regression model

OBJECTIVE

SARS-CoV-2 has caused a pandemic claiming more than 4 million lives worldwide. Overwhelming COVID-19 respiratory failure placed tremendous demands on healthcare systems increasing the death toll. Cost-effective prognostic tools to characterise the likelihood of patients with COVID-19 to progress to severe hypoxemic respiratory failure are still needed.

DESIGN

We conducted a retrospective cohort study to develop a model using demographic and clinical data collected in the first 12 hours of admission to explore associations with severe hypoxemic respiratory failure in unvaccinated and hospitalised patients with COVID-19.

SETTING

University-based healthcare system including six hospitals located in the Galveston, Brazoria and Harris counties of Texas.

PARTICIPANTS

Adult patients diagnosed with COVID-19 and admitted to one of six hospitals between 19 March and 30 June 2020.

PRIMARY OUTCOME

The primary outcome was defined as reaching a WHO ordinal scale between 6 and 9 at any time during admission, which corresponded to severe hypoxemic respiratory failure requiring high-flow oxygen supplementation or mechanical ventilation.

RESULTS

We included 329 participants in the model cohort and 62 (18.8%) met the primary outcome. Our multivariable regression model found that lactate dehydrogenase (OR 2.36), Quick Sequential Organ Failure Assessment score (OR 2.26) and neutrophil to lymphocyte ratio (OR 1.15) were significant predictors of severe disease. The final model showed an area under the curve of 0.84. The sensitivity analysis and point of influence analysis did not reveal inconsistencies.

CONCLUSIONS

Our study suggests that a combination of accessible demographic and clinical information collected on admission may predict the progression to severe COVID-19 among adult patients with mild and moderate disease. This model requires external validation prior to its use.

Loneliness, Social Isolation, and All-Cause Mortality in a Large Sample of Older Adults

Objectives

Using data from a large random sample of U.S. older adults (N = 7982), the effect of loneliness and social isolation on all-cause mortality was examined considering their separate and combined effects.

Methods

The UCLA-3 Loneliness Scale and the Social Network Index (SNI) were used to define loneliness and social isolation. Cox proportional hazards regression models were performed.

Results

Among study participants, there were 548 deaths. In separate, adjusted models, loneliness (severe and moderate) and social isolation (limited and moderate social network) were both associated with all-cause mortality. When modeled together, social isolation (limited and moderate social network) along with severe loneliness remained significantly associated with mortality.

Discussion

Results demonstrate that both loneliness and social isolation contribute to greater risk of mortality within our population of older adults. As the COVID-19 pandemic continues, loneliness and social isolation should be targeted safely in efforts to reduce mortality risk among older adults.

A Typology of COVID-19 Data Gaps and Noise From Long-Term Care Facilities: Approximating the True Numbers

Although there is agreement that COVID-19 has had devastating impacts in long-term care facilities (LTCFs), estimates of cases and deaths have varied widely with little attention to the causes of this variation. We developed a typology of data vulnerabilities and a strategy for approximating the true total of COVID-19 cases and deaths in LTCFs. Based on iterative qualitative consensus, we categorized LTCF reporting vulnerabilities and their potential impacts on accuracy. Concurrently, we compiled one dataset based on LTCF self-reports and one based on confirmatory matching with California’s COVID-19 databases, including death certificates. Through March 2021, Alameda County LTCFs reported 6663 COVID-19 cases and 481 deaths. In contrast, our confirmatory matching file includes 5010 cases and 594 deaths, corresponding to 25% fewer cases but 23% more deaths. We argue that the higher (self-report) case total approximates the lower bound of true COVID-19 cases, and the higher (confirmed match) death total approximates the lower bound of true COVID-19 deaths, both of which are higher than state and federal counts. LTCFs other than nursing facilities accounted for 35% of cases and 29% of deaths. Improving the accuracy of COVID-19 figures, particularly across types of LTCFs, would better inform interventions for these vulnerable populations.

Efficacy of mRNA, adenoviral vector, and perfusion protein COVID-19 vaccines

Coronavirus disease 2019 (COVID-19) has a devastating impact on global populations triggered by a highly infectious viral sickness, produced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The third major cause of mortality in the United States, following heart disease and cancer in 2020, was undoubtedly COVID-19. The centers for disease control and prevention (CDC) and the world health organization (WHO) separately developed a categorization system for differentiating new strains of SARS-CoV-2 into variants of concern (VoCs) and variants of interest (VoIs) with the continuing development of various strains SARS-CoV-2. By December 2021, five of the SARS-CoV-2 VoCs were discovered from the onset of the pandemic depending on the latest epidemiologic report by the WHO: Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (B.1.1.529). Mutations in the receptor-binding domain (RBD) and n-terminal domain (NTD) have been found throughout all five identified VoCs. All strains other than the delta mutant are often found with the N501Y mutation situated on the RBD, resulting in higher binding between the spike protein and angiotensin-converting enzyme 2 (ACE2) receptors, enhanced viral adhesion, and following the entrance to host cells. The introduction of these new strains of SRAS-CoV-2 is likely to overcome the remarkable achievements gained in restricting this viral disease to the point where it is presented with remarkable vaccine developments against COVID-19 and strong worldwide mass immunization initiatives. Throughout this literature review, the effectiveness of current COVID-19 vaccines for managing and prohibiting SARS-CoV-2 strains is thoroughly described.

Characteristics of Reported Deaths Among Fully Vaccinated Persons with COVID-19 -United States, January-April 2021

Background

COVID-19 vaccines are highly efficacious, but SARS-CoV-2 infections post-vaccination occur. We characterized COVID-19 cases among fully vaccinated persons with an outcome of death.

Methods

We analyzed COVID-19 cases voluntarily reported to CDC by US health departments during January 1, 2021–April 30, 2021. We included cases among U.S. residents with a positive SARS-CoV-2 test ≥14 days after completion of an authorized primary vaccine series and who had a known outcome (alive or death) as of May 31, 2021. When available, specimens were sequenced for viral lineage and death certificates were reviewed for cause(s) of death.

Results

Of 8,084 reported COVID-19 cases among fully vaccinated persons during the surveillance period, 245 (3.0%) died. Compared with patients who remained alive, those who died were older (median age 82 years vs. 57 years, P <0.01), more likely to reside in a long-term care facility (51% vs. 18%, P <0.01), and more likely to have at least one underlying health condition associated with risk for severe disease (64% vs. 24%, P <0.01). Among 245 deaths, 191 (78%) were classified as COVID-19-related. Of 106 deaths with available death certificates, COVID-19 was listed on 81 (77%). There were no differences in the type of vaccine administered or the most common viral lineage (B.1.1.7).

Conclusions

COVID-19 deaths are rare in fully vaccinated persons, occurring most commonly in those with risk factors for severe disease, including older age and underlying health conditions. All eligible persons should be fully vaccinated against COVID-19 and follow other prevention measures to mitigate exposure risk.

Covid Adult Mortality in Brazil: An Analysis of Multiple Causes of Death

Objective

This study aimed to analyze the chain of events and contributing causes associated with COVID-19 adult mortality (30–69 years old), based on qualified data on CoD from three Brazilian capitals cities, Belo Horizonte, Salvador, and Natal, in 2020.

Methods

Data of all deaths among residents in the three capitals in 2020 were provided by these municipalities' routine Mortality Information System (SIM). Mentions B34.2 with the markers U07.1 and U07.2 in the death certificate identified COVID-19 deaths. We used a multiple-cause-of-death approach better to understand the complexity of the morbid process of COVID-19. Conditions that appeared more frequently in the same line or above the COVID-19 mentions in the death certificate were considered a chain-of-event. Conditions that occurred more often after the codes for COVID-19 were considered as contributing.

Results

In 2020, 7,029 records from COVID-19 as the underlying cause of death were registered in SIM in the three capitals. Among these, 2,921 (41.6%) were deceased between 30 and 69 years old, representing 17.0% of deaths in this age group. As chain-of-events, the most frequent conditions mentioned were sepsis (33.4%), SARS (32.0%), acute respiratory failure (31.9%), unspecified lower respiratory infections (unspecified pneumonia) (20.1%), and other specified respiratory disorders (14.1%). Hypertension (33.3%), diabetes unspecified type (21.7%), renal failure (12.7%), obesity (9.8%), other chronic kidney diseases (4.9%), and diabetes mellitus type 2 (4.7%) were the most frequent contributing conditions. On average, 3.04 conditions were mentioned in the death certificate besides COVID-19. This average varied according to age, place of death, and capital.

Conclusion

The multiple-cause analysis is a powerful tool to better understand the morbid process due to COVID-19 and highlight the importance of chronic non-communicable diseases as contributing conditions.

Measuring misclassification of Covid-19 as garbage codes: Results of investigating 1,365 deaths and implications for vital statistics in Brazil

The purpose of this article is to quantify the amount of misclassification of the Coronavirus Disease-2019 (COVID-19) mortality occurring in hospitals and other health facilities in selected cities in Brazil, discuss potential factors contributing to this misclassification, and consider the implications for vital statistics. Hospital deaths assigned to causes classified as garbage code (GC) COVID-related cases (severe acute respiratory syndrome, pneumonia unspecified, sepsis, respiratory failure and ill-defined causes) were selected in three Brazilian state capitals. Data from medical charts and forensic reports were extracted from standard forms and analyzed by study physicians who re-assigned the underlying cause based on standardized criteria. Descriptive statistical analysis was performed and the potential impact in vital statistics in the country was also evaluated. Among 1,365 investigated deaths due to GC-COVID-related causes, COVID-19 was detected in 17.3% in the age group 0-59 years and 25.5% deaths in 60 years and over. These GCs rose substantially in 2020 in the country and were responsible for 211,611 registered deaths. Applying observed proportions by age, location and specific GC-COVID-related cause to national data, there would be an increase of 37,163 cases in the total of COVID-19 deaths, higher in the elderly. In conclusion, important undercount of deaths from COVID-19 among GC-COVID-related causes was detected in three selected capitals of Brazil. After extrapolating the study results for national GC-COVID-related deaths we infer that the burden of COVID-19 disease in Brazil in official vital statistics was probably under estimated by at least 18% in the country in 2020.

COVID-19 pandemic and mental health problems of adults in United States: mediating roles of cognitive concerns and behavioral changes

OBJECTIVES

We examined the associations of statewide COVID-19 conditions (i.e., state-level case and death rates) with individual-level Generalized Anxiety Disorder (GAD) and Major Depression Disorder (MDD) focusing on the salient mediating roles of individual-level cognitive concerns and behavioral changes.

METHODS

Using a national representative sample of adults in the United States (n = 585,073), we fitted logistic regressions to examine the overall associations between the COVID-19 pandemic and GAD/MDD. We employed a causal mediation analysis with two mediators: cognitive concerns (i.e., concerns on going to the public, loss of income, food insufficiency, housing payment, and the economy) and behavioral changes (i.e., taking fewer trips, avoiding eating-out, more online-purchase, more curbside pick-up, and cancelling doctor's appointments).

RESULTS

We found relationships of statewide COVID-19 cases with GAD (odds ratio [OR] = 1.06; 95% confidence interval [CI] = 1.05, 1.07) and MDD (OR = 1.08; 95% CI = 1.07, 1.09). The ORs were mediated by cognitive concerns for GAD (OR = 1.02, proportion mediated: 29%) and MDD (OR = 1.01, 17%). Another salient mediator was behavioral changes for GAD (OR = 1.02, 31%) and MDD (OR = 1.01, 15%). Similar associations were found with statewide COVID-19 death.

CONCLUSIONS

Our mediation analyses suggest that cognitive concerns and behavioral changes are important mediators of the relationships between statewide COVID-19 case/death rates and GAD/MDD. COVID-19 pandemic may involve individual-level concerns and behavior changes, and such experiences are likely to affect mental health outcomes. Public health approaches to alleviate adverse mental health consequences should take into account the mediating factors.

Estimation of Coronavirus Disease 2019 Hospitalization Costs From a Large Electronic Administrative Discharge Database, March 2020-July 2021

Background

Information on the costs of inpatient care for patients with coronavirus disease 2019 (COVID-19) is very limited. This study estimates the per-patient cost of inpatient care for adult COVID-19 patients seen at >800 US hospitals.

Methods

Patients aged ≥18 years with ≥1 hospitalization during March 2020–July 2021 with a COVID-19 diagnosis code in a large electronic administrative discharge database were included. We used validated costs when reported; otherwise, costs were calculated using charges multiplied by cost-to-charge ratios. We estimated costs of inpatient care per patient overall and by severity indicator, age, sex, underlying medical conditions, and acute complications of COVID-19 using a generalized linear model with log link function and gamma distribution.

Results

The overall cost among 654673 patients hospitalized with COVID-19 was $16.2 billion. Estimated per-patient hospitalization cost was $24 826. Among surviving patients, estimated per-patient cost was $13 090 without intensive care unit (ICU) admission or invasive mechanical ventilation (IMV), $21 222 with ICU admission alone, and $59 742 with IMV. Estimated per-patient cost among patients who died was $27 017. Adjusted cost differential was higher among patients with certain underlying conditions (eg, chronic kidney disease [$12 391], liver disease [$8878], cerebrovascular disease [$7267], and obesity [$5933]) and acute complications (eg, acute respiratory distress syndrome [$43 912], pneumothorax [$25 240], and intracranial hemorrhage [$22 280]).

Conclusions

The cost of inpatient care for COVID-19 patients was substantial through the first 17 months of the pandemic. These estimates can be used to inform policy makers and planners and cost-effectiveness analysis of public health interventions to alleviate the burden of COVID-19.

Deaths in Children and Adolescents Associated With COVID-19 and MIS-C in the United States

OBJECTIVES

To describe the demographics, clinical characteristics, and hospital course among persons <21 years of age with a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-associated death.

METHODS

We conducted a retrospective case series of suspected SARS-CoV-2-associated deaths in the United States in persons <21 years of age during February 12 to July 31, 2020. All states and territories were invited to participate. We abstracted demographic and clinical data, including laboratory and treatment details, from medical records.

RESULTS

We included 112 SARS-CoV-2-associated deaths from 25 participating jurisdictions. The median age was 17 years (IQR 8.5-19 years). Most decedents were male (71, 63%), 31 (28%) were Black (non-Hispanic) persons, and 52 (46%) were Hispanic persons. Ninety-six decedents (86%) had at least 1 underlying condition; obesity (42%), asthma (29%), and developmental disorders (22%) were most commonly documented. Among 69 hospitalized decedents, common complications included mechanical ventilation (75%) and acute respiratory failure (82%). The sixteen (14%) decedents who met multisystem inflammatory syndrome in children (MIS-C) criteria were similar in age, sex, and race and/or ethnicity to decedents without MIS-C; 11 of 16 (69%) had at least 1 underlying condition.

CONCLUSIONS

SARS-CoV-2-associated deaths among persons <21 years of age occurred predominantly among Black (non-Hispanic) and Hispanic persons, male patients, and older adolescents. The most commonly reported underlying conditions were obesity, asthma, and developmental disorders. Decedents with coronavirus disease 2019 were more likely than those with MIS-C to have underlying medical conditions.

Over- and under-estimation of COVID-19 deaths

The ratio of COVID-19-attributable deaths versus “true” COVID-19 deaths depends on the synchronicity of the epidemic wave with population mortality; duration of test positivity, diagnostic time window, and testing practices close to and at death; infection prevalence; the extent of diagnosing without testing documentation; and the ratio of overall (all-cause) population mortality rate and infection fatality rate. A nomogram is offered to assess the potential extent of over- and under-counting in different situations. COVID-19 deaths were apparently under-counted early in the pandemic and continue to be under-counted in several countries, especially in Africa, while over-counting probably currently exists for several other countries, especially those with intensive testing and high sensitization and/or incentives for COVID-19 diagnoses. Death attribution in a syndemic like COVID-19 needs great caution. Finally, excess death estimates are subject to substantial annual variability and include also indirect effects of the pandemic and the effects of measures taken.

A retrospective cohort study of 12,306 pediatric COVID-19 patients in the United States

Children and adolescents account for ~ 13% of total COVID-19 cases in the United States. However, little is known about the nature of the illness in children. The reopening of schools underlines the importance of understanding the epidemiology of pediatric COVID-19 infections. We sought to assess the clinical characteristics and outcomes in pediatric COVID-19 patients. We conducted a retrospective cross-sectional analysis of pediatric patients diagnosed with COVID-19 from healthcare organizations in the United States. The study outcomes (hospitalization, mechanical ventilation, critical care) were assessed using logistic regression. The subgroups of sex and race were compared after propensity score matching. Among 12,306 children with lab-confirmed COVID-19, 16.5% presented with respiratory symptoms (cough, dyspnea), 13.9% had gastrointestinal symptoms (nausea, vomiting, diarrhea, abdominal pain), 8.1% had dermatological symptoms (rash), 4.8% had neurological (headache), and 18.8% had other non-specific symptoms (fever, malaise, myalgia, arthralgia and disturbances of smell or taste). In the study cohort, the hospitalization frequency was 5.3%, with 17.6% needing critical care services and 4.1% requiring mechanical ventilation. Following propensity score matching, the risk of all outcomes was similar between males and females. Following propensity score matching, the risk of hospitalization was greater in non-Hispanic Black (RR 1.97 [95% CI 1.49–2.61]) and Hispanic children (RR 1.31 [95% CI 1.03–1.78]) compared with non-Hispanic Whites. In the pediatric population infected with COVID-19, a substantial proportion were hospitalized due to the illness and developed adverse clinical outcomes.