Understanding bias when estimating life expectancy from age at death: a simulation approach applied to Morquio syndrome A

Objective Life expectancy can be estimated accurately from a cohort of individuals born in the same year and followed from birth to death. However, due to the resource-consuming nature of following a cohort prospectively, life expectancy is often assessed based upon retrospective death record reviews. This conventional approach may lead to potentially biased estimates, in particular when estimating life expectancy of rare diseases such as Morquio syndrome A. We investigated the accuracy of life expectancy estimation using death records by simulating the survival of individuals with Morquio syndrome A under four different scenarios. Results When life expectancy was constant during the entire period, using death data did not result in a biased estimate. However, when life expectancy increased over time, as is often expected to be the case in rare diseases, using only death data led to a substantial underestimation of life expectancy. We emphasize that it is therefore crucial to understand how estimates of life expectancy are obtained, to interpret them in an appropriate context, and to assess estimation methods within a sensitivity analysis framework, similar to the simulations performed herein.

Hidden Pain: Children Who Lost a Parent or Caregiver to COVID-19 and What the Nation Can Do to Help Them

The COVID-19 pandemic has been the single deadliest acute public health crisis in American history, and these deaths are a salient threat to the functioning of family and social networks. We assess counts and rates of parental and other in-home caregiver loss using death data published by the CDC and household composition data available through the American Community Survey's Public Use Microdata Sample. We find that, through mid-November 2021, more than 167,000 children under the age of 18 lost a parent or other in-home caregiver to COVID-19. Most of these children are under the age of 13 and, though this experience is universal across racial and ethnic groups, ages, and states, racial and ethnic disparities in caregiver loss exceed already high disparities in COVID-19 deaths. We summarize literature on the impacts of parental loss and, after reviewing potential interventions for these children, offer recommendations to policymakers and practitioners.

Bereavement among Adolescents with Intellectual Disability: A Qualitative Study

The current study was conducted to explore the bereavement (experienced loss of a loved one through death within time frame of 0–3 years span). Seven adolescents (10–19 years old) with intellectual disability were included in the study. Semi-structured interviews were conducted through interview guide which was prepared with the help of Piaget’s theory of cognitive development concept related to death. Data was analyzed with content analysis and six major themes were derived, that is, meaning of death, death rituals, religious concepts related to death, reasons of death, grieving perception, and coping with grief. Mostly, concepts were explained under the light of religious preaching and their introjection in the lives of adolescents with intellectual disability. Current study helped in exploration of experiential phenomenon of loss in adolescents with intellectual disability.

Deviation in the Age Structure of Mortality as an Indicator of COVID-19 Pandemic Severity

Objectives. To test whether distortions in the age distribution of deaths can track pandemic activity. Methods. We compared weekly distributions of all-cause deaths by age during the COVID-19 pandemic in the United States from March to December 2020 with corresponding prepandemic weekly baseline distributions derived from data for 2015 to 2019. We measured distortions via Kolmogorov–Smirnov (K-S) and χ2 goodness-of-fit statistics as well as deaths among individuals aged 65 years or older as a percentage of total deaths (PERC65+). We computed bivariate correlations between these measures and the number of recorded COVID-19 deaths for the corresponding weeks. Results. Elevated COVID-19-associated fatalities were accompanied by greater distortions in the age structure of mortality. Distortions in the age distribution of weekly US COVID-19 deaths in 2020 relative to earlier years were highly correlated with COVID fatalities (K-S: r = 0.71, P < .001; χ2: r = 0.90, P < .001; PERC65+: r = 0.85, P < .001). Conclusions. A population-representative sample of age-at-death data can serve as a useful means of pandemic activity surveillance when precise cause-of-death data are incomplete, inaccurate, or unavailable, as is often the case in low-resource environments. (Am J Public Health. 2022;112(1):165–168. https://doi.org/10.2105/AJPH.2021.306567 )

South African Population Immunity and Severe Covid-19 with Omicron Variant

Background We conducted a seroepidemiological survey from October 22 to December 9, 2021, in Gauteng Province, South Africa, to determine SARS-CoV-2 immunoglobulin G (IgG) seroprevalence primarily prior to the fourth wave of coronavirus disease 2019 (Covid-19), in which the B.1.1.529 (Omicron) variant is dominant. We evaluated epidemiological trends in case rates and rates of severe disease through to December 15, 2021, in Gauteng. Methods We contacted households from a previous seroepidemiological survey conducted from November 2020 to January 2021, plus an additional 10% of households using the same sampling framework. Dry blood spot samples were tested for anti-spike and anti-nucleocapsid protein IgG using quantitative assays on the Luminex platform. Daily case and death data, weekly excess deaths, and weekly hospital admissions were plotted over time. Results Samples were obtained from 7010 individuals, of whom 1319 (18.8%) had received a Covid-19 vaccine. Overall seroprevalence ranged from 56.2% (95% confidence interval [CI], 52.6 to 59.7) in children aged <12 years to 79.7% (95% CI, 77.6 to 81.5) in individuals aged >50 years. Seropositivity was 6.22-fold more likely in vaccinated (93.1%) vs unvaccinated (68.4%) individuals. Epidemiological data showed SARS-CoV-2 infection rates increased more rapidly than in previous waves but have now plateaued. Rates of hospitalizations and excess deaths did not increase proportionately, remaining relatively low. Conclusions We demonstrate widespread underlying SARS-CoV-2 seropositivity in Gauteng Province prior to the current Omicron-dominant wave, with epidemiological data showing an uncoupling of hospitalization and death rates from infection rate during Omicron circulation.

The Second Wave of COVID-19 in South and Southeast Asia and the Effects of Vaccination

Background: By February 2021, the overall impact of coronavirus disease 2019 (COVID-19) in South and Southeast Asia was relatively mild. Surprisingly, in early April 2021, the second wave significantly impacted the population and garnered widespread international attention.Methods: This study focused on the nine countries with the highest cumulative deaths from the disease as of August 17, 2021. We look at COVID-19 transmission dynamics in South and Southeast Asia using the reported death data, which fits a mathematical model with a time-varying transmission rate.Results: We estimated the transmission rate, infection fatality rate (IFR), infection attack rate (IAR), and the effects of vaccination in the nine countries in South and Southeast Asia. Our study suggested that the IAR is still low in most countries, and increased vaccination is required to prevent future waves.Conclusion: Implementing non-pharmacological interventions (NPIs) could have helped South and Southeast Asia keep COVID-19 under control in 2020, as demonstrated in our estimated low-transmission rate. We believe that the emergence of the new Delta variant, social unrest, and migrant workers could have triggered the second wave of COVID-19.

Inequalities in excess premature mortality in England during the COVID-19 pandemic: a cross-sectional analysis of cumulative excess mortality by area deprivation and ethnicity

ObjectivesTo examine magnitude of the impact of the COVID-19 pandemic on inequalities in premature mortality in England by deprivation and ethnicity.DesignA statistical model to estimate increased mortality in population subgroups during the COVID-19 pandemic by comparing observed with expected mortality in each group based on trends over the previous 5 years.SettingInformation on deaths registered in England since 2015 was used, including age, sex, area of residence and cause of death. Ethnicity was obtained from Hospital Episode Statistics records linked to death data.ParticipantsPopulation study of England, including all 569 824 deaths from all causes registered between 21 March 2020 and 26 February 2021.Main outcome measuresExcess mortality in each subgroup over and above the number expected based on trends in mortality in that group over the previous 5 years.ResultsThe gradient in excess mortality by area deprivation was greater in the under 75s (the most deprived areas had 1.25 times as many deaths as expected, least deprived 1.14) than in all ages (most deprived had 1.24 times as many deaths as expected, least deprived 1.20). Among the black and Asian groups, all area deprivation quintiles had significantly larger excesses than white groups in the most deprived quintiles and there were no clear gradients across quintiles. Among the white group, only those in the most deprived quintile had more excess deaths than deaths directly involving COVID-19.ConclusionThe COVID-19 pandemic has widened inequalities in premature mortality by area deprivation. Among those under 75, the direct and indirect effects of the pandemic on deaths have disproportionately impacted ethnic minority groups irrespective of area deprivation, and the white group the most deprived areas. Statistics limited to deaths directly involving COVID-19 understate the pandemic’s impact on inequalities by area deprivation and ethnic group at younger ages.

Improving methods to measure comparable mortality cause (IMMCMC) gold standard verbal autopsy dataset

Objectives Gold standard cause of death data is critically important to improve verbal autopsy (VA) methods in diagnosing cause of death where civil and vital registration systems are inadequate or poor. As part of a three-country research study—Improving Methods to Measure Comparable Mortality by Cause (IMMCMC) study—data were collected on clinicopathological criteria-based gold standard cause of death from hospital record reviews with matched VAs. The purpose of this data note is to make accessible a de-identified format of these gold standard VAs for interested researchers to improve the diagnostic accuracy of VA methods. Data description The study was conducted between 2011 and 2014 in the Philippines, Bangladesh, and Papua New Guinea. Gold standard diagnoses of underlying causes of death for deaths occurring in hospital were matched to VAs conducted using a standardized VA questionnaire developed by the Population Health Metrics Consortium. 3512 deaths were collected in total, comprised of 2491 adults (12 years and older), 320 children (28 days to 12 years), and 702 neonates (0–27 days).

The impact of errors in medical certification on the accuracy of the underlying cause of death

Background Correct certification of cause of death by physicians (i.e. completing the medical certificate of cause of death or MCCOD) and correct coding according to International Classification of Diseases (ICD) rules are essential to produce quality mortality statistics to inform health policy. Despite clear guidelines, errors in medical certification are common. This study objectively measures the impact of different medical certification errors upon the selection of the underlying cause of death. Methods A sample of 1592 error-free MCCODs were selected from the 2017 United States multiple cause of death data. The ten most common types of errors in completing the MCCOD (according to published studies) were individually simulated on the error-free MCCODs. After each simulation, the MCCODs were coded using Iris automated mortality coding software. Chance-corrected concordance (CCC) was used to measure the impact of certification errors on the underlying cause of death. Weights for each error type and Socio-demographic Index (SDI) group (representing different mortality conditions) were calculated from the CCC and categorised (very high, high, medium and low) to describe their effect on cause of death accuracy. Findings The only very high impact error type was reporting an ill-defined condition as the underlying cause of death. High impact errors were found to be reporting competing causes in Part 1 [of the death certificate] and illegibility, with medium impact errors being reporting underlying cause in Part 2 [of the death certificate], incorrect or absent time intervals and reporting contributory causes in Part 1, and low impact errors comprising multiple causes per line and incorrect sequence. There was only small difference in error importance between SDI groups. Conclusions Reporting an ill-defined condition as the underlying cause of death can seriously affect the coding outcome, while other certification errors were mitigated through the correct application of mortality coding rules. Training of physicians in not reporting ill-defined conditions on the MCCOD and mortality coders in correct coding practices and using Iris should be important components of national strategies to improve cause of death data quality.