Over- and under-estimation of COVID-19 deaths

SARS-CoV-2 Mpro inhibitor identification using a cellular gain-of-signal assay for high-throughput screening

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2, SARS2) is responsible for the COVID-19 pandemic and infections that continue to affect the lives of millions of people worldwide, especially those who are older and/or immunocompromised. The SARS2 main protease enzyme, Mpro (also called 3C-like protease, 3CLpro), is a bona fide drug target as evidenced by potent inhibition with nirmatrelvir and ensitrelvir, the active components of the drugs Paxlovid and Xocova, respectively. However, the existence of nirmatrelvir and ensitrelvir-resistant isolates underscores the need to develop next-generation drugs with different resistance profiles and/or distinct mechanisms of action. Here, we report the results of a high-throughput screen of 649,568 compounds using a cellular gain-of-signal assay. In this assay, Mpro inhibits expression of a luciferase reporter, and 8,777 small molecules were considered hits by causing a gain in luciferase activity 3x SD above the sample field activity (6.8% gain-of-signal relative to 100 µM GC376). Single concentration and dose-response gain-of-signal experiments confirmed 3,522/8,762 compounds as candidate inhibitors. In parallel, all initial high-throughput screening hits were tested in a peptide cleavage assay with purified Mpro and only 39/8,762 showed inhibition. Importantly, 19/39 compounds (49%) re-tested positive in both SARS2 assays, including two previously reported Mpro inhibitors, demonstrating the efficacy of the overall screening strategy. This approach led to the rediscovery of known Mpro inhibitors such as calpain inhibitor II, as well as to the discovery of novel compounds that provide chemical information for future drug development efforts.

Surveillance bias in the assessment of the size of COVID-19 epidemic waves: a case study

OBJECTIVES

To estimate the size of COVID-19 waves using four indicators across three pandemic periods and assess potential surveillance bias.

STUDY DESIGN

Case study using data from one region of Switzerland.

METHODS

We compared cases, hospitalizations, deaths, and seroprevalence during three periods including the first three pandemic waves (period 1: Feb-Oct 2020; period 2: Oct 2020-Feb 2021; period 3: Feb-Aug 2021). Data were retrieved from the Federal Office of Public Health or estimated from population-based studies. To assess potential surveillance bias, indicators were compared to a reference indicator, i.e. seroprevalence during periods 1 and 2 and hospitalizations during the period 3. Timeliness of indicators (the duration from data generation to the availability of the information to decision-makers) was also evaluated.

RESULTS

Using seroprevalence (our reference indicator for period 1 and 2), the 2nd wave size was slightly larger (by a ratio of 1.4) than the 1st wave. Compared to seroprevalence, cases largely overestimated the 2nd wave size (2nd vs 1st wave ratio: 6.5), while hospitalizations (ratio: 2.2) and deaths (ratio: 2.9) were more suitable to compare the size of these waves. Using hospitalizations as a reference, the 3rd wave size was slightly smaller (by a ratio of 0.7) than the 2nd wave. Cases or deaths slightly underestimated the 3rd wave size (3rd vs 2nd wave ratio for cases: 0.5; for deaths: 0.4). The seroprevalence was not useful to compare the size of these waves due to high vaccination rates. Across all waves, timeliness for cases and hospitalizations was better than for deaths or seroprevalence.

CONCLUSIONS

The usefulness of indicators for assessing the size of pandemic waves depends on the type of indicator and the period of the pandemic.

Power spectral density and similarity analysis of COVID-19 mortality waves across countries

Background

During the COVID-19 pandemic, the Johns Hopkins University Center for Systems Science and Engineering (CSSE) established a comprehensive database detailing daily mortality rates across countries. This dataset revealed fluctuating global mortality trends attributable to COVID-19; however, the specific differences and similarities in mortality patterns between countries remain insufficiently explored. Consequently, this study employs Fourier and similarity analyses to examine these patterns within the frequency domain, thereby offering novel insights into the dynamics of COVID-19 mortality waves across different nations.

Methods

We employed the Fast Fourier transform to calculate the power spectral density (PSD) of COVID-19 mortality waves in 199 countries from January 22, 2020, to March 9, 2023. Moreover, we performed a cosine similarity analysis of these PSD patterns among all the countries.

Results

We identified two dominant peaks in the grand averaged PSD: one at a frequency of 1.15 waves per year (i.e., one wave every 10.4 months) and another at 2.7 waves per year (i.e., one wave every 4.4 months). We also found a cosine similarity index distribution with a skewness of -0.54 and a global median of cosine similarity index of 0.84, thus revealing a remarkable similarity in the dominant peaks of the COVID-19 mortality waves.

Conclusion

These findings could be helpful for planetary health if a future pandemic of a similar scale occurs so that effective confinement measures or other actions could be planned during these two identified periods.

Mortality Rates of the Spanish Flu and Coronavirus Disease 2019 in the Netherlands: A Historical Comparison

The coronavirus disease 2019 (COVID-19) pandemic has been called the deadliest disease event in history. In this study, we compared the cause-specific mortality rate of the Spanish flu (1918-1920) with that of COVID-19 (2020-2022) in the Netherlands. During the periods of exposure, about 50 000 people died of COVID-19 and 32 000 people of the Spanish flu. In absolute numbers, COVID-19 seems to be deadlier than Spanish flu. However, the crude mortality rates for COVID-19 and Spanish flu were 287 and 486 per 100 000 inhabitants, respectively. Comparing age-standardized mortality rates, there would have been 28 COVID-19- and 194 Spanish flu-related deaths in 1918-1920, or 214 Spanish flu- and 98 COVID-19-related deaths in 2020-2022 per 100 000 inhabitants per year. Thus, taking the population differences into account, the Spanish flu would have been deadlier than COVID-19.

Gender-Based Socio-Economic Inequalities in the Pre-Vaccination Era of the COVID-19 Pandemic in Istanbul: A Neighborhood-Level Analysis of Excess Mortality

Worldwide excess mortality (EM) data have the potential to provide a better estimation of the impact of the pandemic. This study aims to investigate and map the inequalities in EM in Istanbul during the pre-vaccination era of the COVID-19 pandemic in 2020 and its association with selected demographic and socio-economic variables at the neighborhood level according to gender. This ecological study was conducted with the EM data of Istanbul. The EM data were obtained from the Istanbul Metropolitan Municipality (IMM) and analyzed according to socio-demographic indicators (gender, age), neighborhood-level indicators (population density, educational attainment) and neighborhood vulnerability (socio-economic and transportation) for the 808 neighborhoods, then presented separately according to gender to examine gender-specific factors. Socio-economic and transportation vulnerability indexes are provided the IMM. The excess mortality rate per 1000 (EMR) in 2020 has been calculated by using the number of deaths in the years 2018-2019. We have mapped EMRs of each neighborhood and used linear regression analysis in three datasets to examine gender specific factors. EMRs in Istanbul showed two peaks one in April and one in November. Male EMRs were higher compared to females in Istanbul during the pre-vaccination era of the pandemic. Higher EMRs were observed in neighborhoods with a higher share of 50+ year old age groups and higher neighborhood socio-economic vulnerability scores. Neighborhood socio-economic vulnerability was significantly associated with EMRs in males but not in females. Unequal distribution of EM between neighborhoods underlines the need for gender-specific pandemic measures to alleviate the burden of the COVID-19 pandemic, especially in socio-economically vulnerable settings. Increased use of area-based indicators with a gender perspective can enhance pandemic measures.

A Critical Analysis of All-Cause Deaths during COVID-19 Vaccination in an Italian Province

Immortal time bias (ITB) is common in cohort studies and distorts the association estimates between the treated and untreated. We used data from an Italian study on COVID-19 vaccine effectiveness, with a large cohort, long follow-up, and adjustment for confounding factors, affected by ITB, with the aim to verify the real impact of the vaccination campaign by comparing the risk of all-cause death between the vaccinated population and the unvaccinated population. We aligned all subjects on a single index date and considered the "all-cause deaths" outcome to compare the survival distributions of the unvaccinated group versus various vaccination statuses. The all-cause-death hazard ratios in univariate analysis for vaccinated people with 1, 2, and 3/4 doses versus unvaccinated people were 0.88, 1.23, and 1.21, respectively. The multivariate values were 2.40, 1.98, and 0.99. Possible explanations of this trend of the hazard ratios as vaccinations increase could be a harvesting effect; a calendar-time bias, accounting for seasonality and pandemic waves; a case-counting window bias; a healthy-vaccinee bias; or some combination of these factors. With 2 and even with 3/4 doses, the calculated Restricted Mean Survival Time and Restricted Mean Time Lost have shown a small but significant downside for the vaccinated populations.

Does the healthy vaccinee bias rule them all? Association of COVID-19 vaccination status and all-cause mortality from an analysis of data from 2.2 million individual health records

OBJECTIVES

We investigated the validity of claims of the healthy vaccinee effect (HVE) in COVID-vaccine studies by analyzing associations between all-cause mortality (ACM) and COVID-19 vaccination status.

METHODS

Approximately 2.2 million individual records from two Czech health insurance companies were retrospectively analyzed. Each age group was stratified according to the vaccination status (unvaccinated vs. individuals less than 4 weeks vs. more than 4 weeks from Doses 1, 2, 3, and 4 or more doses of vaccine). ACMs in these groups were computed and compared.

RESULTS

Consistently over datasets and age categories, ACM was substantially lower in the vaccinated than unvaccinated groups regardless of the presence or absence of a wave of COVID-19 deaths. Moreover, the ACMs in groups more than 4 weeks from Doses 1, 2, or 3 were consistently several times higher than in those less than 4 weeks from the respective dose. HVE appears to be the only plausible explanation for this, which is further corroborated by a created mathematical model.

CONCLUSIONS

In view of the presence of HVE, the baseline difference in the frailty of vaccinated and unvaccinated populations in periods without COVID-19 must be taken into account when estimating COVID-19 vaccine effectiveness from observational data.

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.

Effectiveness of a fourth SARS-CoV-2 vaccine dose in previously infected individuals from Austria

INTRODUCTION

Evidence is limited on the effectiveness of a fourth vaccine dose against coronavirus disease 2019 (COVID-19) in populations with prior severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. We estimated the risk of COVID-19 deaths and SARS-CoV-2 infections according to vaccination status in previously infected individuals in Austria.

METHODS

This is a nationwide retrospective observational study. We calculated age and gender adjusted Cox proportional hazard ratios (HRs) of COVID-19 deaths (primary outcome) and SARS-CoV-2 infections (secondary outcome) from 1 November to 31 December 2022, primarily comparing individuals with four versus three vaccine doses. Relative vaccine effectiveness (rVE) was calculated as (1-HR) X 100.

RESULTS

Among 3,986,312 previously infected individuals, 281,291 (7,1%) had four and 1,545,242 (38.8%) had three vaccinations at baseline. We recorded 69 COVID-19 deaths and 89,056 SARS-CoV-2 infections. rVE for four versus three vaccine doses was -24% (95% CI: -120 to 30) against COVID-19 deaths, and 17% (95% CI: 14-19) against SARS-CoV-2 infections. This latter effect rapidly diminished over time and infection risk with four vaccinations was higher compared to less vaccinated individuals during extended follow-up until June 2023. Adjusted HR (95% CI) for all-cause mortality for four versus three vaccinations was 0.79 (0.74-0.85).

DISCUSSION

In previously infected individuals, a fourth vaccination was not associated with COVID-19 death risk, but with transiently reduced risk of SARS-CoV-2 infections and reversal of this effect in longer follow-up. All-cause mortality data suggest healthy vaccinee bias.

The Importance of Estimating Excess Deaths Regionally During the COVID-19 Pandemic

National or statewide estimates of excess deaths have limited value to understanding the impact of the COVID-19 pandemic regionally. We assessed excess deaths in a 9-county geographically defined population that had low rates of COVID-19 and widescale availability of testing early in the pandemic, well-annotated clinical data, and coverage by 2 medical examiner's offices. We compared mortality rates (MRs) per 100,000 person-years in 2020 and 2021 with those in the 2019 reference period and MR ratios (MRRs). In 2020 and 2021, 177 and 219 deaths, respectively, were attributed to COVID-19 (MR = 52 and 66 per 100,000 person-years, respectively). COVID-19 MRs were highest in males, older persons, those living in rural areas, and those with 7 or more chronic conditions. Compared with 2019, we observed a 10% excess death rate in 2020 (MRR = 1.10 [95% CI, 1.04 to 1.15]), with excess deaths in females, older adults, and those with 7 or more chronic conditions. In contrast, we did not observe excess deaths overall in 2021 compared with 2019 (MRR = 1.04 [95% CI, 0.99 to 1.10]). However, those aged 18 to 39 years (MRR = 1.36 [95% CI, 1.03 to 1.80) and those with 0 or 1 chronic condition (MRR = 1.28 [95% CI, 1.05 to 1.56]) or 7 or more chronic conditions (MRR = 1.09 [95% CI, 1.03 to 1.15]) had increased mortality compared with 2019. This work highlights the value of leveraging regional populations that experienced a similar pandemic wave timeline, mitigation strategies, testing availability, and data quality.

Patterns of protection, infection, and detection: Country-level effectiveness of COVID-19 vaccination in reducing mortality worldwide

Background

The relationship between COVID-19 vaccination and mortality has been established through clinical trials and other investigations at the individual level. In this study, we aimed to investigate the negative relationship between mortality and COVID-19 vaccination at country level.

Study design

We conducted an exploratory, correlational, country-level analysis of open data centralized by Our World in Data concerning the cumulative COVID-19 mortality for the winter wave (October 2021-March 2022) of the pandemic as function of the vaccination rate in October 2021.

Methods

We controlled variables that capture country-level social development and level of testing. We also deployed three segmentation tactics, distinguishing among countries based on their level of COVID-19 testing, age structure, and types of vaccines used.

Results

Controlling for confounding factors did not highlight a statistically significant relationship between vaccination and cumulative mortality in the total country sample. Still, a strong, significant, negative relationship between cumulative mortality (log scale) and vaccination was highlighted through segmentation analysis for countries positioned at the higher end of the social development spectrum. The strongest estimate for vaccine effectiveness at ecological level was obtained for the set of countries that used Western-only vaccines.

Conclusions

COVID-19 testing (log scale) has a significant and positive relationship with cumulative mortality for all subsamples, consistent with patterns of under- and overreporting of COVID-19 deaths at country level, partly driven by testing. This indicates that testing intensity should be controlled as a potential confounder in future ecological analyses of COVID-19 mortality.

Impact of COVID-19 on mortality in coastal Kenya: a longitudinal open cohort study

The mortality impact of COVID-19 in Africa remains controversial because most countries lack vital registration. We analysed excess mortality in Kilifi Health and Demographic Surveillance System, Kenya, using 9 years of baseline data. SARS-CoV-2 seroprevalence studies suggest most adults here were infected before May 2022. During 5 waves of COVID-19 (April 2020-May 2022) an overall excess mortality of 4.8% (95% PI 1.2%, 9.4%) concealed a significant excess (11.6%, 95% PI 5.9%, 18.9%) among older adults ( ≥ 65 years) and a deficit among children aged 1-14 years (-7.7%, 95% PI -20.9%, 6.9%). The excess mortality rate for January 2020-December 2021, age-standardised to the Kenyan population, was 27.4/100,000 person-years (95% CI 23.2-31.6). In Coastal Kenya, excess mortality during the pandemic was substantially lower than in most high-income countries but the significant excess mortality in older adults emphasizes the value of achieving high vaccine coverage in this risk group.

Effects of the COVID-19 pandemic on life expectancy at birth at the global, regional, and national levels: A joinpoint time-series analysis

Background

Current estimates indicate that coronavirus disease 2019 (COVID-19) caused 14.9 million excess deaths in 2020 and 2021. Thus, estimating the change in life expectancy at birth due to the COVID-19 pandemic could aid in understanding its impact and implementing public health initiatives.

Methods

We collected data on the life expectancy at birth of the combined population between 1990 and 2021 at the global, regional, and national levels from the 2022 Revision of World Population Prospects. In this time series study, we estimated the trend segments, the change of trend years (joinpoints), the annual percentage change (APC) in life expectancy at birth within each trend segment, and the average APC (AAPC) in life expectancy at birth during the full study period using joinpoint regression analysis.

Results

The global life expectancy at birth decreased from 72.8 years in 2019 to 71.0 years in 2021, with an annual decrease of 1.2% (95% confidence interval (CI) = 1.0, 1.5) during the 2019-2021 period, despite an overall increasing trend during the entire period from 1990 to 2021 (AAPC = 0.3%; 95% CI = 0.3, 0.4). We observed a significantly increasing trend in life expectancy at birth in all regions and nearly 87.7% (207/236) of the world's countries and areas during the entire period (1990-2021). All continental regions except Africa and Oceania experienced a significant decreasing trend in life expectancy at birth in 2019-2021, with an APC of -1.2% (95% CI = -1.5, -0.9) for Asia, -2.1% (95% CI = -2.7, -1.6) for Latin America and the Caribbean, -1.1% (95% CI = -1.6, -0.6) for Northern America, and -1.4% (95% CI = -1.9, -0.9) for Europe. Among all countries and areas, 107 countries and areas (45.3%) experienced a significant decreasing trend in life expectancy at birth in the most recent time segment, with 77 countries and areas (32.6%) experiencing a significant decreasing trend during the 2019-2021 period.

Conclusions

The world experienced a significant decreasing trend in life expectancy at birth in 2019-2021, with a decrease of 1.8 years; all continental regions except Africa and Oceania and 77 countries and areas experienced a significant decreasing trend in life expectancy at birth. These decreasing trends at global, regional, and national levels during the 2019-2021 period reflected the COVID-19 pandemic's direct and indirect adverse effects on life expectancy at birth.

The Burden of Disease due to COVID-19 (BoCO-19): A study protocol for a secondary analysis of surveillance data in Southern and Eastern Europe, and Central Asia

INTRODUCTION

The COVID-19 pandemic has had an extensive impact on public health worldwide. However, in many countries burden of disease indicators for COVID-19 have not yet been calculated or used for monitoring. The present study protocol describes an approach developed in the project "The Burden of Disease due to COVID-19. Towards a harmonization of population health metrics for the surveillance of dynamic outbreaks" (BoCO-19). The process of data collection and aggregation across 14 different countries and sub-national regions in Southern and Eastern Europe and Central Asia is described, as well as the methodological approaches used.

MATERIALS AND METHODS

The study implemented in BoCO-19 is a secondary data analysis, using information from national surveillance systems as part of mandatory reporting on notifiable diseases. A customized data collection template is used to gather aggregated data on population size as well as COVID-19 cases and deaths. Years of life lost (YLL), as one component of the number of Disability Adjusted Life Years (DALY), are calculated as described in a recently proposed COVID-19 disease model (the 'Burden-EU' model) for the calculation of DALY. All-cause mortality data are collected for excess mortality sensitivity analyses. For the calculation of Years lived with disability (YLD), the Burden-EU model is adapted based on recent evidence. Because Covid-19 cases vary in terms of disease severity, the possibility and suitability of applying a uniform severity distribution of cases across all countries and sub-national regions will be explored. An approach recently developed for the Global Burden of Disease Study, that considers post-acute consequences of COVID-19, is likely to be adopted. Findings will be compared to explore the quality and usability of the existing data, to identify trends across age-groups and sexes and to formulate recommendations concerning potential improvements in data availability and quality.

DISCUSSION

BoCO-19 serves as a collaborative platform in order to build international capacity for the calculation of burden of disease indicators, and to support national experts in the analysis and interpretation of country-specific data, including their strengths and weaknesses. Challenges include inherent differences in data collection and reporting systems between countries, as well as assumptions that have to be made during the calculation process.

Unmasking the COVID-19 pandemic prevention gains: excess mortality reversal in 2022

OBJECTIVES

The purpose of this study was to assess the long-term effectiveness of COVID-19 pandemic prevention measures in saving lives after European governments began to lift restrictions.

STUDY DESIGN

Excess mortality interrupted time series.

METHODS

Country-level weekly data on deaths were fitted to the Poisson mixed linear model to estimate excess deaths. Based on this estimate, the percentage of excess deaths above the baseline during the pandemic (week 11 in 2020 to week 15 in 2022) (when public health interventions were in place) and during the post-pandemic period (week 16 in 2022 to week 52 in 2022) were calculated. These results were fitted to the linear regression model to determine any potential relationship between mortality during these two periods.

RESULTS

The model used in this study had high predictive value (adjusted R2 = 59.4%). Mortality during the endemic (post-pandemic) period alone increased by 7.2% (95% confidence interval [CI]: 5.7, 8.6) above baseline, while each percentage increase in mortality during the pandemic corresponded to a 0.357% reduction (95% CI: 0.243, 0.471) in mortality during the post-pandemic period.

CONCLUSIONS

The most successful countries in terms of protective measures also experienced the highest mortality rates after restrictions were lifted. The model used in this study clearly shows a measure of bidirectional mortality displacement that is sufficiently clear to mask any impact of long COVID on overall mortality. Results from this study also seriously impact previous cost-benefit analyses of pandemic prevention measures, since, according to the current model, 12.2% (95% CI: 8.3, 16.1) of the gains achieved in pandemic containment were lost after restrictions were lifted.

Macro1 domain residue F156: A hallmark of SARS-CoV-2 de-MARylation specificity

SARS-CoV-2 is a large, enveloped and positive sense single stranded RNA virus. Its genome codes for 16 non-structural proteins. The largest protein of this complex is nsp3, that contains a well conserved Macro1 domain. Viral Macro domains were shown to bind to mono-ADP-ribose (MAR) and poly-ADP-ribose (PAR) in their free form or conjugated to protein substrates. They carry ADP-ribose hydrolase activities implicated in the regulation of innate immunity. SARS-CoV-2 and SARS-CoV show widely different induction and handling of the host interferon response. Herein, we have conducted a mutational study on the key amino-acid residue F156 in SARS-CoV-2, pinpointed by bioinformatic and structural studies, and its cognate residue N157 in SARS-CoV. Our data suggest that the exchange of these residues slightly modifies ADP-ribose binding, but drastically impacts de-MARylation activity. Alanine substitutions at this position hampers PAR binding, abolishes MAR hydrolysis of SARS-CoV-2, and reduces by 70% this activity in the case of SARS-CoV.

Public health factors help explain cross country heterogeneity in excess death during the COVID19 pandemic

The COVID-19 pandemic has taken a devastating toll around the world. Since January 2020, the World Health Organization estimates 14.9 million excess deaths have occurred globally. Despite this grim number quantifying the deadly impact, the underlying factors contributing to COVID-19 deaths at the population level remain unclear. Prior studies indicate that demographic factors like proportion of population older than 65 and population health explain the cross-country difference in COVID-19 deaths. However, there has not been a comprehensive analysis including variables describing government policies and COVID-19 vaccination rate. Furthermore, prior studies focus on COVID-19 death rather than excess death to assess the impact of the pandemic. Through a robust statistical modeling framework, we analyze 80 countries and show that actionable public health efforts beyond just the factors intrinsic to each country are important for explaining the cross-country heterogeneity in excess death.

Prepandemic cross-reactive humoral immunity to SARS-CoV-2 in Africa: Systematic review and meta-analysis

OBJECTIVES

To assess the evidence on the presence of antibodies cross-reactive with SARS-CoV-2 antigens in prepandemic samples from African populations.

METHODS

We performed a systematic review and meta-analysis of studies evaluating prepandemic African samples using pre-set assay-specific thresholds for SARS-CoV-2 seropositivity.

RESULTS

In total, 26 articles with 156 datasets were eligible, including 3437 positives among 29,923 measurements (11.5%) with large between-dataset heterogeneity. Positivity was similar for anti-nucleocapsid (14%) and anti-spike antibodies (11%), higher for anti-spike1 (23%), and lower for anti-receptor-binding domain antibodies (7%). Positivity was similar, on average, for immunoglobulin M and immunoglobulin G. Positivity was seen prominently in countries where malaria transmission occurs throughout and in datasets enriched in malaria cases (14%, 95% confidence interval, 12-15% vs 2%, 95% confidence interval 1-2% in other datasets). Substantial SARS-CoV-2 reactivity was seen in high malaria burden with or without high dengue burden (14% and 12%, respectively), and not without high malaria burden (2% and 0%, respectively). Lower SARS-CoV-2 cross-reactivity was seen in settings of high HIV seroprevalence. More sparse individual-level data showed associations of higher SARS-CoV-2 cross-reactivity with Plasmodium parasitemia and lower SARS-CoV-2 cross-reactivity with HIV seropositivity.

CONCLUSION

Prepandemic samples from Africa show high levels of anti-SARS-CoV-2 seropositivity. At the country level, cross-reactivity tracks especially with malaria prevalence.

Evaluation of concordance in estimation of excess mortality due to COVID-19 pandemic

BACKGROUND

The World Health Organization (WHO) kept track of COVID-19 data at country level daily during the pandemic that included the number of tests, infected cases and fatalities. This daily record was susceptible to change depending on the time and place and impacted by underreporting. In addition to reporting cases of excess COVID-19-related deaths, the WHO also provided estimates of excess mortality based on mathematical models.

OBJECTIVE

To evaluate the WHO reported and model-based estimate of excess deaths to determine the degree of agreement and universality.

METHODOLOGY

Epidemiological data gathered from nine different countries between April 2020 and December 2021 are used in this study. These countries are India, Indonesia, Italy, Russia, United Kingdom, Mexico, the United States, Brazil and Peru and each of them recorded more than 1.5 million deaths from COVID-19 during these months. Statistical tools including correlation, linear regression, intraclass correlation and Bland-Altman plots are used to assess the degree of agreement between reported and model-based estimates of excess deaths.

RESULTS

The WHO-derived mathematical model for estimating excess deaths due to COVID-19 was found to be appropriate for only four of the nine chosen countries, namely Italy, United Kingdom, the United States and Brazil. The other countries showed proportional biases and significantly high regression coefficients.

CONCLUSION

The study revealed that, for some of the chosen nations, the mathematical model proposed by the WHO is practical and capable of estimating the number of excess deaths brought on by COVID-19. However, the derived approach cannot be applied globally.

COVID-19 Vaccination Effectiveness in the General Population of an Italian Province: Two Years of Follow-Up

We carried out a cohort study on the overall population of the province of Pescara, Italy, to assess the real-world effectiveness of SARS-CoV-2 vaccination against infection, severe, or lethal COVID-19, two years after the start of the vaccination campaign. We included all the resident or domiciled subjects, and extracted the official demographic, vaccination, COVID-19, hospital and co-pay exemption datasets from 1 January 2021, up to 15 February 2023. Cox proportional hazards analyses were adjusted for gender, age, diabetes, hypertension, COPD, major cardio- and cerebrovascular events, cancer, and kidney diseases. Throughout the follow-up (466 days on average), 186,676 subjects received greater than or equal to three vaccine doses (of ChAdOx1 nCoV-19, BNT162b2, mRNA-1273, NVX-CoV2373, or JNJ-78436735), 47,610 two doses, 11,452 one dose, and 44,989 none. Overall, 40.4% of subjects were infected with SARS-CoV-2. Of them, 2.74% had severe or lethal (1.30%) COVID-19. As compared to the unvaccinated, the individuals who received greater than or equal to one booster dose showed a ≥85% lower risk of severe or lethal COVID-19. A massive impact of vaccination was found among the elderly: 22.0% of the unvaccinated, infected individuals died, as opposed to less than 3% of those who received greater than or equal to three vaccine doses. No protection against infection was observed, although this finding was certainly influenced by the Italian restriction policies to control the pandemic. Importantly, during the Omicron predominance period, only the group who received at least a booster dose showed a reduced risk of COVID-19-related death.

Flaws and uncertainties in pandemic global excess death calculations

Several teams have been publishing global estimates of excess deaths during the COVID-19 pandemic. Here, we examine potential flaws and underappreciated sources of uncertainty in global excess death calculations. Adjusting for changing population age structure is essential. Otherwise, excess deaths are markedly overestimated in countries with increasingly aging populations. Adjusting for changes in other high-risk indicators, such as residence in long-term facilities, may also make a difference. Death registration is highly incomplete in most countries; completeness corrections should allow for substantial uncertainty and consider that completeness may have changed during pandemic years. Excess death estimates have high sensitivity to modelling choice. Therefore different options should be considered and the full range of results should be shown for different choices of pre-pandemic reference periods and imposed models. Any post-modelling corrections in specific countries should be guided by pre-specified rules. Modelling of all-cause mortality (ACM) in countries that have ACM data and extrapolating these models to other countries is precarious; models may lack transportability. Existing global excess death estimates underestimate the overall uncertainty that is multiplicative across diverse sources of uncertainty. Informative excess death estimates require risk stratification, including age groups and ethnic/racial strata. Data to-date suggest a death deficit among children during the pandemic and marked socioeconomic differences in deaths, widening inequalities. Finally, causal explanations require great caution in disentangling SARS-CoV-2 deaths, indirect pandemic effects and effects from measures taken. We conclude that excess deaths have many uncertainties, but globally deaths from SARS-CoV-2 may be the minority of calculated excess deaths.

Unpacking the Complexity of COVID-19 Fatalities: Adverse Events as Contributing Factors-A Single-Center, Retrospective Analysis of the First Two Years of the Pandemic

In a retrospective analysis of 477 fatal COVID-19 cases hospitalised at a single medical centre during the period from 6 March 2020 to 30 June 2022, several factors defining those patients at admission were assessed, as well as the course of the hospitalisation and factors contributing to death. There was a predominance of men (59.3% (283)) burdened by comorbidities, with increased inflammation at admission. Patients aged ≥ 81 years were significantly more likely to be admitted to and die in infectious diseases units (IDU) due to respiratory failure, their hospital stays were shorter, and they were most likely not to receive specialist treatment. The most common COVID-19 complications included acute kidney injury in 31.2% (149) patients and thromboembolic complications in 23.5% (112). The course of hospitalisation was complicated by healthcare-associated infections (HAI) in 33.3% (159) of cases, more often in those treated with baricitinib (p < 0.001). The initial use of an antibiotic, although common (94.8% (452)), was unwarranted in almost half of the cases (47.6% (215)). Complications of hospitalisation (46.1% (220)) and adverse events involving staff (49.7% (237)) were found in almost half of the patients. In 88.7% (423) of the cases, death was due to respiratory failure in the course of SARS-CoV-2 infection. Adverse events during hospitalisation should be considered as an additional factor that, in addition to the infection itself, may have influenced the death of patients.

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.

A U-shaped protection of altitude against mortality and infection of COVID-19 in Peru: an ecological study

BACKGROUND

The COVID-19 pandemic has affected the world in multiple ways and has been a challenge for the health systems of each country. From the beginning, risk factors for the severity and mortality of the disease were considered, as the spread of the virus was related to the living conditions of each population.

METHODS

In this ecological study we have evaluated the role of geography, precisely the altitude above sea level in the incidence and mortality of COVID-19 in Peru. Incidence and mortality data were taken from the open-access database of the government of Peru until March 2021. COVID-19 cases and COVID-19 mortality were treated as cases/density population and 1000 x cases/inhabitants while altitude was treated as continuous and as a categorical variable divided in 7 categories. The relationship between COVID-19 cases or deaths for COVID-19 and altitude as continuous variable was determined using Spearman correlation test. Meanwhile when altitude was considered as a categorical variable, Poisson regression or negative binomial analyses were applied.

RESULTS

A significant inverse correlation was found between COVID-19 cases by population density and altitude (r=-0.37 p < 0.001). By altitude categories, the lowest risk for infection was observed between 3,000 and 3,500 m (IRR 0.08; 95% CI 0.05,0.12). Moreover, we found an inverse correlation between altitude and COVID-19 mortality (r=-0.39 p < 0.001). Also, the lowest risk for mortality was observed between 3,000 and 3,500 m (IRR 0.12; 95%CI 0.08; 0.18). Similar results were found when analyses were adjusted for inhabitants and stratified by sex.

CONCLUSION

This study reports an inverse relationship between COVID-19 incidence and mortality with respect to the altitude of residence, particularly, a u-shaped protection is shown, with a highest benefit between 3000 and 3500 m. The possibility of using hypoxia as an alternative treatment requires more complex studies that should allow knowing the physiological and environmental mechanisms of the protective role.

SARS-CoV-2 seroepidemiology in Mongolia, 2020-2021: a longitudinal national study

Background

The COVID-19 pandemic has global impacts but is relatively understudied in developing countries. Mongolia, a lower-middle-income country, instituted strict control measures in early 2020 and avoided widespread transmission until vaccines became available in February, 2021. Mongolia achieved its 60% vaccination coverage goal by July 2021. We investigated the distribution and determinants of SARS-CoV-2 seroprevalence in Mongolia over 2020 and 2021.

Methods

We performed a longitudinal seroepidemiologic study aligned with WHO's Unity Studies protocols. We collected data from a panel of 5000 individuals in four rounds between October 2020 and December 2021. We selected participants through local health centres across Mongolia by age-stratified multi-stage cluster sampling. We tested serum for the presence of total antibodies against SARS-CoV-2 receptor-binding domain, and levels of anti-SARS-CoV-2 spike IgG and neutralising antibodies. We linked participant data with national mortality, COVID-19 case, and vaccination registries. We estimated population seroprevalence and vaccine uptake, as well as unvaccinated population prior-infection prevalence.

Findings

At the final round in late 2021, 82% (n = 4088) of participants completed follow-up. Estimated seroprevalence increased from 1.5% (95% CI: 1.2-2.0), to 82.3% (95% CI: 79.5-84.8) between late-2020 and late-2021. At the final round an estimated 62.4% (95% CI: 60.2-64.5) of the population were vaccinated, and of the unvaccinated population 64.5% (95% CI: 59.7-69.0) had been infected. Cumulative case ascertainment in the unvaccinated was 22.8% (95% CI: 19.1%-26.9%) and the overall infection-fatality ratio was 0.100% (95% CI: 0.088-0.124). Health workers had higher odds for being COVID-19 confirmed cases at all rounds. Males (1.72 (95% CI: 1.33-2.22)) and adults aged 20 and above (12.70 (95% CI: 8.14-20.26)) had higher odds for seroconverting by mid-2021. Among the seropositive, 87.1% (95% CI: 82.3%-90.8%) had SARS-CoV-2 neutralising antibodies by late 2021.

Interpretation

Our study enabled tracking of SARS-CoV-2 serological markers in the Mongolian population over one year. We found low SARS-CoV-2 seroprevalence in 2020 and early 2021, with seropositivity increasing over a 3-month interval in 2021 due to vaccine roll out and rapid infection of most of the unvaccinated population. Despite high seroprevalence in Mongolia amongst both vaccinated and unvaccinated individuals by end-2021, the SARS-CoV-2 Omicron immune escape variant caused a substantial epidemic.

Funding

World Health Organization, WHO UNITY Studies initiative, with funding by the COVID-19 Solidarity Response Fund and the German Federal Ministry of Health (BMG) COVID-19 Research and development. The Ministry of Health, Mongolia partially funded this study.

Analysis of fatality impact and seroprevalence surveys in a community sustaining a SARS-CoV-2 superspreading event

There is an ongoing debate on the COVID-19 infection fatality rate (IFR) and the impact of COVID-19 on overall population mortality. Here, we addressed these issues in a community in Germany with a major superspreader event analyzing deaths over time and auditing death certificates in the community.18 deaths that occurred within the first six months of the pandemic had a positive test for SARS-CoV-2. Six out of 18 deaths had non-COVID-19 related causes of death (COD). Individuals with COVID-19 COD typically died of respiratory failure (75%) and tended to have fewer reported comorbidities (p = 0.029). Duration between first confirmed infection and death was negatively associated with COVID-19 being COD (p = 0.04). Repeated seroprevalence essays in a cross-sectional epidemiological study showed modest increases in seroprevalence over time, and substantial seroreversion (30%). IFR estimates accordingly varied depending on COVID-19 death attribution. Careful ascertainment of COVID-19 deaths is important in understanding the impact of the pandemic.

SEIR models in the light of Critical Realism - A critique of exaggerated claims about the effectiveness of Covid 19 vaccinations

In a recent modeling study Watson et al. (Lancet Infect Dis 2022;3099:1-10) claim that Covid-19 vaccinations have helped to prevent roughly 14-20 million deaths in 2021. This conclusion is based on an epidemiological susceptible-exposed-infectious-recovered (SEIR) model trained on partially simulated data and yielding a reproduction number distribution which was then applied to a counterfactual scenario in which the efficacy of vaccinations was removed. Drawing on the meta-theory of Critical Realism, we point out several caveats of this model and caution against believing in its predictions. We argue that the absence of vaccinations would have significantly changed the causal tendencies of the system being modelled, yielding a different reproduction number than obtained from training the model on actually observed data. Furthermore, the model omits many important causal factors. Therefore this model, similar to many previous SEIR models, has oversimplified the complex interplay between biomedical, social and cultural dimensions of health and should not be used to guide public health policy. In order to predict the future in epidemic situations more accurately, continuously optimized dynamic causal models which can include the not directly tangible, yet real causal mechanisms affecting public health appear to be a promising alternative to SEIR-type models.

Estimates of COVID-19 deaths in Mainland China after abandoning zero COVID policy

BACKGROUND

China witnessed a surge of Omicron infections after abandoning 'zero COVID' strategies on 7 December 2022. The authorities report very sparse deaths based on very restricted criteria, but massive deaths are speculated.

METHODS

We aimed to estimate the COVID-19 fatalities in Mainland China until summer 2023 using the experiences of Hong Kong and of South Korea in 2022 as prototypes. Both these locations experienced massive Omicron waves after having had very few SARS-CoV-2 infections during 2020-2021. We estimated age-stratified infection fatality rates (IFRs) in Hong Kong and South Korea during 2022 and extrapolated to the population age structure of Mainland China. We also accounted separately for deaths of residents in long-term care facilities in both Hong Kong and South Korea.

RESULTS

Infection fatality rate estimates in non-elderly strata were modestly higher in Hong Kong than South Korea and projected 987,455 and 619,549 maximal COVID-19 deaths respectively, if the entire China population were infected. Expected COVID-19 deaths in Mainland China until summer 2023 ranged from 49,962 to 691,219 assuming 25-70% of the non-elderly population being infected and variable protection of elderly (from none to three-quarter reduction in fatalities). The main analysis (45% of non-elderly population infected and fatality impact among elderly reduced by half) estimated 152,886-249,094 COVID-19 deaths until summer 2023. Large uncertainties exist regarding potential changes in dominant variant, health system strain and impact on non-COVID-19 deaths.

CONCLUSIONS

The most critical factor that can affect total COVID-19 fatalities in China is the extent to which the elderly can be protected.

Lack of association between vaccination rates and excess mortality in Cyprus during the COVID-19 pandemic

BACKGROUND

It has been claimed that COVID-19 vaccination is associated with excess mortality during the COVID-19 pandemic, a claim that contributes to vaccine hesitancy. We examined whether all-cause mortality has actually increased in Cyprus during the first two pandemic years, and whether any increases are associated with vaccination rates.

METHODS

We calculated weekly excess mortality for Cyprus between January 2020 and June 2022, overall and by age group, using both a Distributed Lag Nonlinear Model (DLNM) adjusted for mean daily temperature, and the EuroMOMO algorithm. Excess deaths were regressed on the weekly number of confirmed COVID-19 deaths and on weekly first-dose vaccinations, also using a DLNM to explore the lag-response dimension.

RESULTS

552 excess deaths were observed in Cyprus during the study period (95% CI: 508-597) as opposed to 1306 confirmed COVID-19 deaths. No association between excess deaths and vaccination rates was found overall and for any age group except 18-49 years, among whom 1.09 excess deaths (95% CI: 0.27-1.91) per 10,000 vaccinations were estimated during the first 8 weeks post-vaccination. However, detailed cause-of-death examination identified just two such deaths potentially linked to vaccination, therefore this association is spurious and attributable to random error.

CONCLUSIONS

Excess mortality was moderately increased in Cyprus during the COVID-19 pandemic, primarily as a result of laboratory-confirmed COVID-19 deaths. No relationship was found between vaccination rates and all-cause mortality, demonstrating the excellent safety profile of COVID-19 vaccines.

Current tobacco use and COVID-19 diagnoses in a cohort of adult clients of public dental clinics in Sweden

Smoking has been linked with both increased and decreased risk of COVID-19, prompting the hypothesis of a protective role of nicotine in the pathogenesis of the disease. Studies of the association between use of smokeless tobacco and COVID-19 would help refining this hypothesis. We analysed data from 424,386 residents in the Stockholm Region, Sweden, with information on smoking and smokeless tobacco (snus) use prior to the pandemic obtained from dental records. Diagnoses of COVID-19 between February and October 2020 were obtained from health-care registers. We estimated the risk of receiving a diagnosis of COVID-19 for current smokers and for current snus users relative to non-users of tobacco, adjusting for potential confounders (aRR). The aRR of COVID -19 was elevated for current snus users (1.09 ;95%CI = 0.99-1.21 among men and 1.15; 95%CI = 1.00-1.33 among women). The risk for women consuming more than 1 can/day was twice as high as among non-users of tobacco. Current smoking was negatively associated with risk of COVID-19 (aRR = 0.68; 95% CI = 0.61-0.75); including hospital admission (aRR = 0.60; 95% CI = 0.47-0.76) and intensive care (aRR = 0.43; 95% CI = 0.21-0.89). The hypothesis of a protective effect of tobacco nicotine on COVID-19 was not supported by the findings. The negative association between smoking and COVID-19 remains unexplained.

Association of greenness with COVID-19 deaths in India: An ecological study at district level

BACKGROUND

The world has witnessed a colossal death toll due to the novel coronavirus disease-2019 (COVID-19). A few environmental epidemiology studies have identified association of environmental factors (air pollution, greenness, temperature, etc.) with COVID-19 incidence and mortality, particularly in developed countries. India, being one of the most severely affected countries by the pandemic, still has a dearth of research exploring the linkages of environment and COVID-19 pandemic.

OBJECTIVES

We evaluate whether district-level greenness exposure is associated with a reduced risk of COVID-19 deaths in India.

METHODS

We used average normalized difference vegetation index (NDVI) from January to March 2019, derived by Oceansat-2 satellite, to represent district-level greenness exposure. COVID-19 death counts were obtained through May 1, 2021 (around the peak of the second wave) from an open portal: covid19india.org. We used hierarchical generalized negative binomial regressions to check the associations of greenness with COVID-19 death counts. Analyses were adjusted for air pollution (PM2.5), temperature, rainfall, population density, proportion of older adults (50 years and above), sex ratio over age 50, proportions of rural population, household overcrowding, materially deprived households, health facilities, and secondary school education.

RESULTS

Our analyses found a significant association between greenness and reduced risk of COVID-19 deaths. Compared to the districts with the lowest NDVI (quintile 1), districts within quintiles 3, 4, and 5 have respectively, around 32% [MRR = 0.68 (95% CI: 0.51, 0.88)], 39% [MRR = 0.61 (95% CI: 0.46, 0.80)], and 47% [MRR = 0.53 (95% CI: 0.40, 0.71)] reduced risk of COVID-19 deaths. The association remains consistent for analyses restricted to districts with a rather good overall death registration (>80%).

CONCLUSION

Though cause-of-death statistics are limited, we confirm that exposure to greenness was associated with reduced district-level COVID-19 deaths in India. However, material deprivation and air pollution modify this association.

Global law, policy, and governance for effective prevention and control of COVID-19: A comparative analysis of the law and policy of Pakistan, China, and Russia

Global health governance is a developing system in this complex institutional regime. The local and regional health policies sometimes challenge global health governance due to diverse discourse in various countries. In the wake of COVID-19, global health governance was reaffirmed as indifferent modules to control and eliminate the pandemic; however, the global agencies later dissected their own opinion and said that "countries must learn to live with a pandemic." Given the controversial statement, this research focuses on the strong and effective policies of the Russian Federation, Pakistan, and China. The research uses the law and governance results and newly developed policies of the three countries formed under the global health policies. The conclusion is based on the statement that in order to live with the pandemic, strong health measures are required at each level.

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.

Age-stratified infection fatality rate of COVID-19 in the non-elderly population

The largest burden of COVID-19 is carried by the elderly, and persons living in nursing homes are particularly vulnerable. However, 94% of the global population is younger than 70 years and 86% is younger than 60 years. The objective of this study was to accurately estimate the infection fatality rate (IFR) of COVID-19 among non-elderly people in the absence of vaccination or prior infection. In systematic searches in SeroTracker and PubMed (protocol: https://osf.io/xvupr), we identified 40 eligible national seroprevalence studies covering 38 countries with pre-vaccination seroprevalence data. For 29 countries (24 high-income, 5 others), publicly available age-stratified COVID-19 death data and age-stratified seroprevalence information were available and were included in the primary analysis. The IFRs had a median of 0.034% (interquartile range (IQR) 0.013-0.056%) for the 0-59 years old population, and 0.095% (IQR 0.036-0.119%) for the 0-69 years old. The median IFR was 0.0003% at 0-19 years, 0.002% at 20-29 years, 0.011% at 30-39 years, 0.035% at 40-49 years, 0.123% at 50-59 years, and 0.506% at 60-69 years. IFR increases approximately 4 times every 10 years. Including data from another 9 countries with imputed age distribution of COVID-19 deaths yielded median IFR of 0.025-0.032% for 0-59 years and 0.063-0.082% for 0-69 years. Meta-regression analyses also suggested global IFR of 0.03% and 0.07%, respectively in these age groups. The current analysis suggests a much lower pre-vaccination IFR in non-elderly populations than previously suggested. Large differences did exist between countries and may reflect differences in comorbidities and other factors. These estimates provide a baseline from which to fathom further IFR declines with the widespread use of vaccination, prior infections, and evolution of new variants.

COVID-19 Vaccination Did Not Increase the Risk of Potentially Related Serious Adverse Events: 18-Month Cohort Study in an Italian Province

This cohort study on the entire population of an Italian Province assessed the incidence of potentially vaccine-related serious adverse events (PVR-SAEs) by COVID-19 vaccination status. From January 2021 to July 2022, we extracted all deaths and hospitalizations due to several cardiovascular diseases, pulmonary embolism, and deep vein thrombosis from National Healthcare System official data. During the follow-up, 5743 individuals died, and 2097 were hospitalized for PVR-SAEs. Vaccinated subjects (n = 259,821) did not show an increased risk of all-cause death, non-COVID death, or any PVR-SAEs, as compared to the unvaccinated (n = 56,494). These results were consistent across genders, age-classes, vaccine types, and SARS-CoV-2 infection status and did not vary in Cox models adjusting for age, gender, SARS-CoV-2 infection, and selected comorbidities. In the infected population, any dose of vaccine was associated with a lower likelihood of death and PVR-SAE. In the uninfected population, subjects who received one or two doses showed a significantly higher incidence of most outcomes, likely due to a large selection bias introduced by the Italian restriction policies targeting uninfected subjects who received less than three doses. In conclusion, COVID-19 vaccination was not associated with an increase of mortality or selected PVR-SAEs incidence. Further research is warranted to evaluate the long-term safety of COVID-19 vaccines.

Factors influencing estimated effectiveness of COVID-19 vaccines in non-randomised studies

Non-randomised studies assessing COVID-19 vaccine effectiveness need to consider multiple factors that may generate spurious estimates due to bias or genuinely modify effectiveness. These include pre-existing immunity, vaccination misclassification, exposure differences, testing, disease risk factor confounding, hospital admission decision, treatment use differences, and death attribution. It is useful to separate whether the impact of each factor admission decision, treatment use differences, and death attribution. Steps and measures to consider for improving vaccine effectiveness estimation include registration of studies and of analysis plans; sharing of raw data and code; background collection of reliable information; blinded assessment of outcomes, e.g. death causes; using maximal/best information in properly-matched studies, multivariable analyses, propensity analyses, and other models; performing randomised trials, whenever possible, for suitable questions, e.g. booster doses or comparative effectiveness of different vaccination strategies; living meta-analyses of vaccine effectiveness; better communication with both relative and absolute metrics of risk reduction and presentation of uncertainty; and avoidance of exaggeration in communicating results to the general public.

Understanding the exceptional pre-vaccination Era East Asian COVID-19 outcomes

During the first year of the pandemic, East Asian countries have reported fewer infections, hospitalizations, and deaths from COVID-19 disease than most countries in Europe and the Americas. Our goal in this paper is to generate and evaluate hypothesis that may explain this striking fact. We consider five possible explanations: (1) population age structure (younger people tend to have less severe COVID-19 disease upon infection than older people); (2) the early adoption of lockdown strategies to control disease spread; (3) genetic differences between East Asian population and European and American populations that confer protection against COVID-19 disease; (4) seasonal and climactic contributors to COVID-19 spread; and (5) immunological differences between East Asian countries and the rest of the world. The evidence suggests that the first four hypotheses are unlikely to be important in explaining East Asian COVID-19 exceptionalism. Lockdowns, in particular, fail as an explanation because East Asian countries experienced similarly good infection outcomes despite vast differences in lockdown policies adopted by different countries to control the COVID-19 epidemic. The evidence to date is consistent with our fifth hypothesis - pre-existing immunity unique to East Asia - but there are still essential parts of this story left for scientists to check.

Time-varying risk of death after SARS-CoV-2 infection in Swedish long-term care facility residents: a matched cohort study

OBJECTIVES

To evaluate whether SARS-CoV-2 infection in residents of long-term care (LTC) facilities is associated with higher mortality after the acute phase of infection, and to estimate survival in uninfected residents.

DESIGN

Extended follow-up of a previous, propensity score-matched, retrospective cohort study based on the Swedish Senior Alert register.

SETTING

LTC facilities in Sweden.

PARTICIPANTS

n=3604 LTC residents with documented SARS-CoV-2 until 15 September 2020 matched to 3604 uninfected controls using time-dependent propensity scores on age, sex, health status, comorbidities, prescription medications, geographical region and Senior Alert registration time. In a secondary analysis (n=3731 in each group), geographical region and Senior Alert registration time were not matched for in order to increase the follow-up time in controls and allow for an estimation of median survival.

PRIMARY OUTCOME MEASURES

All-cause mortality until 24 October 2020, tracked using the National Cause of Death Register.

RESULTS

Median age was 87 years and 65% were women. Excess mortality peaked at 5 days after documented SARS-CoV-2-infection (HR 21.5, 95% CI 15.9 to 29.2), after which excess mortality decreased. From the second month onwards, mortality rate became lower in infected residents than controls. The HR for death during days 61-210 of follow-up was 0.76 (95% CI 0.62 to 0.93). The median survival of uninfected controls was 1.6 years, which was much lower than the national life expectancy in Sweden at age 87 (5.05 years in men, 6.07 years in women).

CONCLUSIONS

The risk of death after SARS-CoV-2 infection in LTC residents peaked after 5 days and decreased after 2 months, probably because the frailest residents died during the acute phase, leaving healthier residents remaining. The limited life expectancy in this population suggests that LTC resident status should be accounted for when estimating years of life lost due to COVID-19.

Time-varying risk of death after SARS-CoV-2 infection in Swedish long-term care facility residents: a matched cohort study

OBJECTIVES

To evaluate whether SARS-CoV-2 infection in residents of long-term care (LTC) facilities is associated with higher mortality after the acute phase of infection, and to estimate survival in uninfected residents.

DESIGN

Extended follow-up of a previous, propensity score-matched, retrospective cohort study based on the Swedish Senior Alert register.

SETTING

LTC facilities in Sweden.

PARTICIPANTS

n=3604 LTC residents with documented SARS-CoV-2 until 15 September 2020 matched to 3604 uninfected controls using time-dependent propensity scores on age, sex, health status, comorbidities, prescription medications, geographical region and Senior Alert registration time. In a secondary analysis (n=3731 in each group), geographical region and Senior Alert registration time were not matched for in order to increase the follow-up time in controls and allow for an estimation of median survival.

PRIMARY OUTCOME MEASURES

All-cause mortality until 24 October 2020, tracked using the National Cause of Death Register.

RESULTS

Median age was 87 years and 65% were women. Excess mortality peaked at 5 days after documented SARS-CoV-2-infection (HR 21.5, 95% CI 15.9 to 29.2), after which excess mortality decreased. From the second month onwards, mortality rate became lower in infected residents than controls. The HR for death during days 61-210 of follow-up was 0.76 (95% CI 0.62 to 0.93). The median survival of uninfected controls was 1.6 years, which was much lower than the national life expectancy in Sweden at age 87 (5.05 years in men, 6.07 years in women).

CONCLUSIONS

The risk of death after SARS-CoV-2 infection in LTC residents peaked after 5 days and decreased after 2 months, probably because the frailest residents died during the acute phase, leaving healthier residents remaining. The limited life expectancy in this population suggests that LTC resident status should be accounted for when estimating years of life lost due to COVID-19.

Inequity after death: Exploring the equitable utilization of FEMA's COVID-19 funeral assistance funds

As of March 2021, the United States had nearly 1 million COVID-19 deaths. To aid families, the Federal Emergency Management Agency (FEMA) established the Funeral Assistance Program. Using publicly available data, we examine the equitable utilization of FEMA's COVID-19 Funeral Assistance Program funding. Results show a significant relationship between FEMA COVID-19 Funeral Assistance Program funding and some, but not all, social vulnerability components. Specifically, counties with higher percentages of the population with disabilities and higher percentages of minorities receive lower amounts of funding per 100,000 residents. These findings suggest that FEMA's equity efforts are not fully materializing regarding the utilization of the FEMA COVID-19 Funeral Assistance Program funding among socially vulnerable groups. FEMA should broaden its social equity outreach and priorities for those not traditionally considered in social equity discussions, such as people with disabilities while continuing efforts toward traditional social equity.

Global Excess Mortality during COVID-19 Pandemic: A Systematic Review and Meta-Analysis

BACKGROUND

Currently, reported COVID-19 deaths are inadequate to assess the impact of the pandemic on global excess mortality. All-cause excess mortality is a WHO-recommended index for assessing the death burden of COVID-19. However, the global excess mortality assessed by this index remains unclear. We aimed to assess the global excess mortality during the COVID-19 pandemic.

METHODS

We searched PubMed, EMBASE, and Web of Science for studies published in English between 1 January 2020, and 21 May 2022. Cross-sectional and cohort studies that reported data about excess mortality during the pandemic were included. Two researchers independently searched the published studies, extracted data, and assessed quality. The Mantel-Haenszel random-effects method was adopted to estimate pooled risk difference (RD) and their 95% confidence intervals (CIs).

RESULTS

A total of 79 countries from twenty studies were included. During the COVID-19 pandemic, of 2,228,109,318 individuals, 17,974,051 all-cause deaths were reported, and 15,498,145 deaths were expected. The pooled global excess mortality was 104.84 (95% CI 85.56-124.13) per 100,000. South America had the highest pooled excess mortality [134.02 (95% CI: 68.24-199.80) per 100,000], while Oceania had the lowest [-32.15 (95% CI: -60.53--3.77) per 100,000]. Developing countries had higher excess mortality [135.80 (95% CI: 107.83-163.76) per 100,000] than developed countries [68.08 (95% CI: 42.61-93.55) per 100,000]. Lower middle-income countries [133.45 (95% CI: 75.10-191.81) per 100,000] and upper-middle-income countries [149.88 (110.35-189.38) per 100,000] had higher excess mortality than high-income countries [75.54 (95% CI: 53.44-97.64) per 100,000]. Males had higher excess mortality [130.10 (95% CI: 94.15-166.05) per 100,000] than females [102.16 (95% CI: 85.76-118.56) per 100,000]. The population aged ≥ 60 years had the highest excess mortality [781.74 (95% CI: 626.24-937.24) per 100,000].

CONCLUSIONS

The pooled global excess mortality was 104.84 deaths per 100,000, and the number of reported all-cause deaths was higher than expected deaths during the global COVID-19 pandemic. In South America, developing and middle-income countries, male populations, and individuals aged ≥ 60 years had a heavier excess mortality burden.

Comparison of pandemic excess mortality in 2020-2021 across different empirical calculations

Different modeling approaches can be used to calculate excess deaths for the COVID-19 pandemic period. We compared 6 calculations of excess deaths (4 previously published [3 without age-adjustment] and two new ones that we performed with and without age-adjustment) for 2020-2021. With each approach, we calculated excess deaths metrics and the ratio R of excess deaths over recorded COVID-19 deaths. The main analysis focused on 33 high-income countries with weekly deaths in the Human Mortality Database (HMD at mortality.org) and reliable death registration. Secondary analyses compared calculations for other countries, whenever available. Across the 33 high-income countries, excess deaths were 2.0-2.8 million without age-adjustment, and 1.6-2.1 million with age-adjustment with large differences across countries. In our analyses after age-adjustment, 8 of 33 countries had no overall excess deaths; there was a death deficit in children; and 0.478 million (29.7%) of the excess deaths were in people <65 years old. In countries like France, Germany, Italy, and Spain excess death estimates differed 2 to 4-fold between highest and lowest figures. The R values' range exceeded 0.3 in all 33 countries. In 16 of 33 countries, the range of R exceeded 1. In 25 of 33 countries some calculations suggest R > 1 (excess deaths exceeding COVID-19 deaths) while others suggest R < 1 (excess deaths smaller than COVID-19 deaths). Inferred data from 4 evaluations for 42 countries and from 3 evaluations for another 98 countries are very tenuous. Estimates of excess deaths are analysis-dependent and age-adjustment is important to consider. Excess deaths may be lower than previously calculated.

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.

The end of the COVID-19 pandemic

There are no widely accepted, quantitative definitions for the end of a pandemic such as COVID-19. The end of the pandemic due to a new virus and the transition to endemicity may be defined based on a high proportion of the global population having some immunity from natural infection or vaccination. Other considerations include diminished death toll, diminished pressure on health systems, reduced actual and perceived personal risk, removal of restrictive measures and diminished public attention. A threshold of 70% of the global population having being vaccinated or infected was probably already reached in the second half of 2021. Endemicity may still show major spikes of infections and seasonality, but typically less clinical burden, although some locations are still hit more than others. Death toll and ICU occupancy figures are also consistent with a transition to endemicity by end 2021/early 2022. Personal risk of the vast majority of the global population was already very small by end 2021, but perceived risk may still be grossly overestimated. Restrictive measures of high stringency have persisted in many countries by early 2022. The gargantuan attention in news media, social media and even scientific circles should be tempered. Public health officials need to declare the end of the pandemic. Mid- and long-term consequences of epidemic waves and of adopted measures on health, society, economy, civilization and democracy may perpetuate a pandemic legacy long after the pandemic itself has ended.

Change in age distribution of COVID-19 deaths with the introduction of COVID-19 vaccination

OBJECTIVES

Most countries initially deployed COVID-19 vaccines preferentially in elderly populations. We aimed to evaluate whether population-level vaccine effectiveness is heralded by an increase in the relative proportion of deaths among non-elderly populations that were less covered by vaccination programs.

ELIGIBLE DATA

We collected data from 40 countries on age-stratified COVID-19 deaths during the vaccination period (1/14/2021-5/31/2021) and two control periods (entire pre-vaccination period and excluding the first wave).

MAIN OUTCOME MEASURES

We meta-analyzed the proportion of deaths in different age groups in vaccination versus control periods in (1) countries with low vaccination rates; (2) countries with age-independent vaccination policies; and (3) countries with standard age-dependent vaccination policies.

RESULTS

Countries that prioritized vaccination among older people saw an increasing share of deaths among 0-69 year old people in the vaccination versus the two control periods (summary proportion ratio 1.32 [95 CI% 1.24-1.41] and 1.35 [95 CI% 1.26-1.44)]. No such change was seen on average in countries with age-independent vaccination policies (1.05 [95 CI% 0.78-1.41 and 0.97 [95 CI% 0.95-1.00], respectively) and limited vaccination (0.93 [95 CI% 0.85-1.01] and 0.95 [95 CI% 0.87-1.03], respectively). Proportion ratios were associated with the difference of vaccination rates in elderly versus non-elderly people. No significant changes occurred in the share of deaths in age 0-49 among all 0-69 deaths in the vaccination versus pre-vaccination periods.

CONCLUSIONS

The substantial shift in the age distribution of COVID-19 deaths in countries that rapidly implemented vaccination predominantly among elderly provides evidence for the population level-effectiveness of COVID-19 vaccination and a favorable evolution of the pandemic towards endemicity with fewer elderly deaths.

Towards an Accurate Estimation of COVID-19 Cases in Kazakhstan: Back-Casting and Capture–Recapture Approaches

Background and Objectives: Coronavirus disease 19 (COVID-19) has emerged as the most devastating syndemic of the 21st century, with worrisome and sustained consequences for the entire society. Despite the relative success of vaccination programs, the global threat of the novel coronavirus SARS-CoV-2 is still present and further efforts are needed for its containment and control. Essential for its control and containment is getting closer to understanding the actual extent of SARS-CoV-2 infections. Material and Methods: We present a model based on the mortality data of Kazakhstan for the estimation of the underlying epidemic dynamic—with both the lag time from infection to death and the infection fatality rate. For the estimation of the actual number of infected individuals in Kazakhstan, we used both back-casting and capture–recapture methods. Results: Our results suggest that despite the increased testing capabilities in Kazakhstan, official case reporting undercounts the number of infections by at least 60%. Even though our count of deaths may be either over or underestimated, our methodology could be a more accurate approach for the following: the estimation of the actual magnitude of the pandemic; aiding the identification of different epidemiological values; and reducing data bias. Conclusions: For optimal epidemiological surveillance and control efforts, our study may lead to an increased awareness of the effect of COVID-19 in this region and globally, and aid in the implementation of more effective screening and diagnostic measures.

Complexity of COVID-19 Dynamics

With population explosion and globalization, the spread of infectious diseases has been a major concern. In 2019, a newly identified type of Coronavirus caused an outbreak of respiratory illness, popularly known as COVID-19, and became a pandemic. Although enormous efforts have been made to understand the spread of COVID-19, our knowledge of the COVID-19 dynamics still remains limited. The present study employs the concepts of chaos theory to examine the temporal dynamic complexity of COVID-19 around the world. The false nearest neighbor (FNN) method is applied to determine the dimensionality and, hence, the complexity of the COVID-19 dynamics. The methodology involves: (1) reconstruction of a single-variable COVID-19 time series in a multi-dimensional phase space to represent the underlying dynamics; and (2) identification of “false” neighbors in the reconstructed phase space and estimation of the dimension of the COVID-19 series. For implementation, COVID-19 data from 40 countries/regions around the world are studied. Two types of COVID-19 data are analyzed: (1) daily COVID-19 cases; and (2) daily COVID-19 deaths. The results for the 40 countries/regions indicate that: (1) the dynamics of COVID-19 cases exhibit low- to medium-level complexity, with dimensionality in the range 3 to 7; and (2) the dynamics of COVID-19 deaths exhibit complexity anywhere from low to high, with dimensionality ranging from 3 to 13. The results also suggest that the complexity of the dynamics of COVID-19 deaths is greater than or at least equal to that of the dynamics of COVID-19 cases for most (three-fourths) of the countries/regions. These results have important implications for modeling and predicting the spread of COVID-19 (and other infectious diseases), especially in the identification of the appropriate complexity of models.

COVID-19 vaccination in children and university students

Strategies for the use of COVID-19 vaccines in children and young adults (in particular university students) are hotly debated and important to optimize. As of late August 2021, recommendations on the use of these vaccines in children vary across different countries. Recommendations are more uniform for vaccines in young adults, but vaccination uptake in this age group shows a large range across countries. Mandates for vaccination of university students are a particularly debated topic with many campuses endorsing mandates in the USA in contrast to European countries, at least as of August 2021. The commentary discusses the potential indirect impact of vaccination of youth on the COVID-19 burden of disease for other age groups and societal functioning at large, estimates of direct impact on reducing fatalities and nonlethal COVID-19-related events in youth, estimates of potential lethal and nonlethal adverse events from vaccines and differential considerations that may exist in the USA, European countries and nonhigh-income countries. Decision-making for deploying COVID-19 vaccines in young people is subject to residual uncertainty on the future course of the pandemic and potential evolution towards endemicity. Rational recommendations would also benefit from better understanding of the clinical and sociodemographic features of COVID-19 risk in young populations and from dissecting the role of re-infections and durability of natural vs. vaccine-induced immunity.

Inverse correlates of COVID-19 mortality across European countries during the first versus subsequent waves

The objectives of the study were to calculate the standardised mortality rates (SMRs) for COVID-19 in European Union/European Economic Area countries plus the UK and Switzerland and to evaluate the correlation between SMRs and selected indicators in the first versus the subsequent waves until 23 June 2021. We used indirect standardisation (using Italy as the reference) to compute SMRs and considered 16 indicators of health and social well-being, health system capacity and COVID-19 response. The highest SMRs were in Belgium, the UK and Spain in the first wave (1.20-1.84) and in Hungary, Czechia and Slovakia in the subsequent waves (2.50-2.69). Human Development Index (HDI), life expectancy, urbanisation and healthcare expenditure had positive correlations with SMR in the first wave (rho=0.30-0.46), but negative correlations (rho=-0.67 to -0.47) in the subsequent waves. Retail/recreation mobility and transit mobility were negatively correlated with SMR in the first wave, while transit mobility was inversely correlated with SMR in the subsequent waves. The first wave hit most hard countries with high HDI, high life expectancy, high urbanisation, high health expenditures and high tourism. This pattern may reflect higher early community seeding and circulation of the virus. Conversely, in the subsequent waves, this pattern was completely inversed: countries with more resources and better health status did better than eastern European countries. While major SMR differences existed across countries in the first wave, these differences largely dissipated by 23 June 2021, with few exceptions.