Underestimation of COVID-19 mortality during the pandemic

COVID-19 vaccine hesitancy prevalence in Mexico: A systematic review and metanalysis

Background

Vaccine hesitancy (VH) is a recognized threat to public health that undermines efforts to mitigate disease burden. This study aims to gather available evidence regarding COVID-19 VH in Mexico, estimate the prevalence of VH, and its determinants to inform policymaking in this country.

Methods

Following PRISMA guidelines, a systematic review of the MEDLINE literature, articles that estimated the prevalence of COVID-19 VH in Mexico were included in the analysis to obtain a pooled estimate. We used a binomial-normal model for meta-analysis of proportions (i.e., generalized linear mixed model) to perform the metanalysis. We then performed a narrative review of COVID-19 VH in Mexican subpopulations.

Results

Seven studies met inclusion criteria. We estimated a pooled prevalence of COVID-19 VH of 16 % (95 % CI: 11-23 %) in Mexico. We found an association between VH and demographic characteristics, intrinsic vaccine factors, and beliefs. Subgroup analyses from specific studies suggested that patients with clinical conditions such as breast cancer or rheumatologic diseases had a higher prevalence of VH.

Conclusions

VH is a highly complex and dynamic phenomenon in Mexico. Characterizing and understanding COVID-19 vaccine hesitancy in the Mexican population helps target future policy interventions to mitigate the spread and impact of infectious diseases. The implications of VH differ among groups that may be at higher risk of severe disease, underscoring the importance of prompt research among these groups as well as targeted interventions to address VH.

Changing impact of COVID-19 on life expectancy 2019-2023 and its decomposition: Findings from 27 countries

Background

The World Health Organization declared COVID-19 no longer a global health emergency on 5th May 2023; however, the impact of COVID-19 on life expectancy throughout the pandemic period is not clear. This study aimed to quantify and decompose the changes in life expectancy during 2019-2023 and corresponding age and gender disparities in 27 countries.

Methods

Data were sourced from the Human Mortality Database, the World Population Prospects 2022 and the United Kingdom's Office for National Statistics. Life expectancy was estimated using the abridged life table method, while differentials of life expectancies were decomposed using the age-decomposition algorithm.

Results

There was an overall reduction in life expectancy at age 5 among the 27 countries in 2020. Life expectancy rebounded in Western, Northern and Southern Europe in 2021 but further decreased in the United States, Chile and Eastern Europe in the same year. In 2022 and after, lost life expectancy years in the United States, Chile and Eastern Europe were slowly regained; however, as of 7th May 2023, life expectancy in 22 of the 27 countries had not fully recovered to its pre-pandemic level. The reduced life expectancy in 2020 was mainly driven by reduced life expectancy at age 65+, while that in subsequent years was mainly driven by reduced life expectancy at age 45-74. Women experienced a lower reduction in life expectancy at most ages but a greater reduction at age 85+.

Conclusions

The pandemic has caused substantial short-term mortality variations during 2019-2023 in the 27 countries studied. Although most of the 27 countries experienced increased life expectancy after 2022, life expectancy in 22 countries still has not entirely regained its pre-pandemic level by May 2023. Threats of COVID-19 are more prominent for older adults and men, but special attention is needed for women aged 85+ years.

Excess Deaths During the COVID-19 Pandemic in Southern Iran: Estimating the Absolute Count and Relative Risk Using Ecological Data

OBJECTIVES

The coronavirus disease 2019 (COVID-19) pandemic led to increased mortality rates. To assess this impact, this ecological study aimed to estimate the excess death counts in southern Iran.

METHODS

The study obtained weekly death counts by linking the National Death Registry and Medical Care Monitoring Center repositories. The P-score was initially estimated using a simple method that involved calculating the difference between the observed and expected death counts. The interrupted time series analysis was then used to calculate the mean relative risk (RR) of death during the first year of the pandemic.

RESULTS

Our study found that there were 5571 excess deaths from all causes (P-score=33.29%) during the first year of the COVID-19 pandemic, with 48.03% of these deaths directly related to COVID-19. The pandemic was found to increase the risk of death from all causes (RR, 1.26; 95% confidence interval [CI], 1.19 to 1.33), as well as in specific age groups such as those aged 35-49 (RR, 1.21; 95% CI, 1.12 to 1.32), 50-64 (RR, 1.38; 95% CI, 1.28 to 1.49), and ≥65 (RR, 1.29; 95% CI, 1.12 to 1.32) years old. Furthermore, there was an increased risk of death from cardiovascular diseases (RR, 1.17; 95% CI, 1.11 to 1.22).

CONCLUSIONS

There was a 26% increase in the death count in southern Iran during the COVID-19 pandemic. More than half of these excess deaths were not directly related to COVID-19, but rather other causes, with cardiovascular diseases being a major contributor.

Assessing the heterogeneity of the impact of COVID-19 incidence on all-cause excess mortality among healthcare districts in Lombardy, Italy, to evaluate the local response to the pandemic: an ecological study

OBJECTIVES

The fragmentation of the response to the COVID-19 pandemic at national, regional and local levels is a possible source of variability in the impact of the pandemic on society. This study aims to assess how much of this variability affected the burden of COVID-19, measured in terms of all-cause 2020 excess mortality.

DESIGN

Ecological retrospective study.

SETTING

Lombardy region of Italy, 2015-2020.

OUTCOME MEASURES

We evaluated the relationship between the intensity of the epidemics and excess mortality, assessing the heterogeneity of this relationship across the 91 districts after adjusting for relevant confounders.

RESULTS

The epidemic intensity was quantified as the COVID-19 hospitalisations per 1000 inhabitants. Five confounders were identified through a directed acyclic graph: age distribution, population density, pro-capita gross domestic product, restriction policy and population mobility.Analyses were based on a negative binomial regression model with district-specific random effects. We found a strong, positive association between COVID-19 hospitalisations and 2020 excess mortality (p<0.001), estimating that an increase of one hospitalised COVID-19 patient per 1000 inhabitants resulted in a 15.5% increase in excess mortality. After adjusting for confounders, no district differed in terms of COVID-19-unrelated excess mortality from the average district. Minimal heterogeneity emerged in the district-specific relationships between COVID-19 hospitalisations and excess mortality (6 confidence intervals out of 91 did not cover the null value).

CONCLUSIONS

The homogeneous effect of the COVID-19 spread on the excess mortality in the Lombardy districts suggests that, despite the unprecedented conditions, the pandemic reactions did not result in health disparities in the region.

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.

Analysis of the institutional landscape and proliferation of proposals for global vaccine equity for COVID-19: too many cooks or too many recipes?

This article outlines and compares current and proposed global institutional mechanisms to increase equitable access to COVID-19 vaccines, focusing on their institutional and operational complementarities and overlaps. It specifically considers the World Health Organization's (WHO's) COVAX (COVID-19 Vaccines Global Access) model as part of the Access to COVID-19 Tools Accelerator (ACT-A) initiative, the WHO's COVID-19 Technology Access Pool (C-TAP) initiative, the proposed TRIPS (Trade-Related Aspects of Intellectual Property Agreement) intellectual property waiver and other proposed WHO and World Trade Organization technology transfer proposals. We argue that while various individual mechanisms each have their specific individual merits-and in some cases weaknesses-overall, many of these current and proposed mechanisms could be highly complementary if used together to deliver equitable global access to vaccines. Nonetheless, we also argue that there are risks posed by the proliferation of proposals in this context, including the potential to disperse stakeholder attention or to delay decisive action. Therefore, we argue that there is now a clear need for concerted global multilateral action to recognise the complementarities of specific models and to provide a pathway for collaboration in attaining global equitable access to vaccines. The institutional infrastructure or proposals to achieve this amply exist at this point in time-but much greater cooperation from industry and clear, decisive and coordinated action from states and international organisations are urgently needed.

Total Excess Mortality Surveillance for Real-Time Decision-Making in Disasters and Crises

Crises such as Hurricane Maria and the coronavirus disease 2019 (COVID-19) pandemic have revealed that untimely reporting of the death toll results in inadequate interventions, impacts communication, and fuels distrust on response agencies. Delays in establishing mortality are due to the contested definition of deaths attributable to a disaster and lack of rapid collection of vital statistics data from inadequate health system infrastructure. Readily available death counts, combined with geographic, demographic, and socioeconomic data, can serve as a baseline to build a continuous mortality surveillance system. In an emergency setting, real-time Total, All-cause, Excess Mortality (TEM) can be a critical tool, granting authorities timely information ensuring a targeted response and reduce disaster impact. TEM measurement can identify spikes in mortality, including geographic disparities and disproportionate deaths in vulnerable populations. This study recommends that measuring total, all-cause, excess mortality as a first line of response should become the global standard for measuring disaster impact.

Comparing COVID-19 pandemic health responses in two high-income island nations: Iceland and New Zealand

AIMS

We aimed to compare COVID-19 control measures, epidemiological characteristics and economic performance measures in two high-income island nations with small populations, favorable border control options, and relatively good outcomes: Iceland and New Zealand (NZ).

METHODS

We examined peer-reviewed journal articles, official websites, reports, media releases and press articles for data on pandemic preparedness and COVID-19 public health responses from 1 January 2020 to 1 June 2022 in Iceland and NZ. We calculated epidemiological characteristics of the COVID-19 pandemic, as well as measures of economic performance.

RESULTS

Both nations had the lowest excess mortality in the OECD from the start of the pandemic up to June 2022. Iceland pursued a mitigation strategy, never used lockdowns or officially closed its border to foreign nationals, and instead relied on extensive testing and contact tracing early in the pandemic. Meanwhile, NZ pursued an elimination strategy, used a strict national lockdown to stop transmission, and closed its international border to everyone except citizens and permanent residents going through quarantine and testing. Iceland experienced a larger decrease in gross domestic product in 2020 (relative to 2019) than NZ (-8·27% vs. -1·22%, respectively). In late 2021, NZ announced a shift to a suppression strategy and in 2022 began to reopen its border in stages, while Iceland ended all public restrictions on 25 February 2022.

CONCLUSIONS

Many of Iceland's and NZ's pandemic control measures appeared successful and features of the responses in both countries could potentially be adopted by other jurisdictions to address future disease outbreaks and pandemic threats.

Estimating excess mortalities due to the COVID-19 pandemic in Malaysia between January 2020 and September 2021

Excess mortalities are a more accurate indicator of true COVID-19 disease burden. This study aims to investigate levels of excess all-cause mortality and their geographic, age and sex distributions between January 2020-September 2021. National mortality data between January 2016 and September 2021 from the Department of Statistics Malaysia was utilised. Baseline mortality was estimated using the Farrington algorithm and data between 1 January 2016 and 31 December 2019. The occurrence of excess all-cause mortality by geographic-, age- and sex-stratum was examined from 1 January 2020 to 30 September 2021. A sub-analysis was also conducted for road-traffic accidents, ethnicity and nationality. Malaysia had a 5.5-23.7% reduction in all-cause mortality across 2020. A reversal is observed in 2021, with an excess of 13.0-24.0%. Excess mortality density is highest between July and September 2021. All states and sexes reported excess trends consistent with the national trends. There were reductions in all all-cause mortalities in individuals under the age of 15 (0.4-8.1%) and road traffic accident-related mortalities (36.6-80.5%). These reductions were higher during the first Movement Control Order in 2020. Overall, there appears to be a reduction in all-cause mortality for Malaysia in 2020. This trend is reversed in 2021, with excess mortalities being observed. Surveillance of excess mortalities can allow expedient detection of aberrant events allowing timely health system and public health responses.

Serum procalcitonin level is independently associated with mechanical ventilation and case-fatality in hospitalized COVID-19-positive US veterans-A potential marker for disease severity

The Coronavirus-19 disease (COVID-19) has claimed over 6.8 million lives since first being reported in late 2019. The virus that causes COVID-19 disease is highly contagious and spreads rapidly. To date, there are no approved prognostic tools that could predict why some patients develop severe or fatal disease outcomes. Early COVID-19 studies found an association between procalcitonin (PCT) and hospitalization or duration of mechanical ventilation and death but were limited by the cohort sizes. Therefore, this study was designed to confirm the associations of PCT with COVID-19 disease severity outcomes in a large cohort. For this retrospective data analysis study, 27,154 COVID-19-positive US veterans with post-infection PCT laboratory test data and their disease severity outcomes were accessed using the VA electronic healthcare data. Cox regression models were used to test the association between serum PCT levels and disease outcomes while controlling for demographics and relevant confounding variables. The models demonstrated increasing disease severity (ventilation and death) with increasing PCT levels. For PCT serum levels above 0.20 ng/ml, the unadjusted risk increased nearly 2.3-fold for mechanical ventilation (hazard ratio, HR, 2.26, 95%CI: 2.11-2.42) and in-hospital death (HR, 2.28, 95%CI: 2.16-2.41). Even when adjusted for demographics, diabetes, pneumonia, antibiotic use, white blood cell count, and serum C-reactive protein levels, the risks remained relatively high for mechanical ventilation (HR, 1.80, 95%CI: 1.67-1.94) and death (HR, 1.76, 95%CI: 1.66-1.87). These data suggest that higher PCT levels have independent associations with ventilation and in-hospital death in veterans with COVID-19 disease, validating previous findings. The data suggested that serum PCT level may be a promising prognostic tool for COVID-19 severity assessment and should be further evaluated in a prospective clinical trial.

Coronavirus disease 2019 (COVID-19) excess mortality outcomes associated with pandemic effects study (COPES): A systematic review and meta-analysis

Background and aim

With the Coronavirus Disease 2019 (COVID-19) pandemic continuing to impact healthcare systems around the world, healthcare providers are attempting to balance resources devoted to COVID-19 patients while minimizing excess mortality overall (both COVID-19 and non-COVID-19 patients). To this end, we conducted a systematic review (SR) to describe the effect of the COVID-19 pandemic on all-cause excess mortality (COVID-19 and non-COVID-19) during the pandemic timeframe compared to non-pandemic times.

Methods

We searched EMBASE, Cochrane Database of SRs, MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Cochrane Controlled Trials Register (CENTRAL), from inception (1948) to December 31, 2020. We used a two-stage review process to screen/extract data. We assessed risk of bias using Newcastle-Ottawa Scale (NOS). We used Critical Appraisal and Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology.

Results

Of 11,581 citations, 194 studies met eligibility. Of these studies, 31 had mortality comparisons (n = 433,196,345 participants). Compared to pre-pandemic times, during the COVID-19 pandemic, our meta-analysis demonstrated that COVID-19 mortality had an increased risk difference (RD) of 0.06% (95% CI: 0.06-0.06% p < 0.00001). All-cause mortality also increased [relative risk (RR): 1.53, 95% confidence interval (CI): 1.38-1.70, p < 0.00001] alongside non-COVID-19 mortality (RR: 1.18, 1.07-1.30, p < 0.00001). There was "very low" certainty of evidence through GRADE assessment for all outcomes studied, demonstrating the evidence as uncertain.

Interpretation

The COVID-19 pandemic may have caused significant increases in all-cause excess mortality, greater than those accounted for by increases due to COVID-19 mortality alone, although the evidence is uncertain.

Systematic review registration

[https://www.crd.york.ac.uk/prospero/#recordDetails], identifier [CRD42020201256].

Analysis of risk factors for COVID-19-related fatal outcome in 337991 patients with type 1 and type 2 diabetes mellitus in 2020–2022 years: Russian nationwide retrospective study

BACKGROUND: The coronavirus pandemic has had an extremely negative impact on the patients with diabetes mellitus (DM both in terms of a more severe course of COVID -19 and an increased risk of death.

AIM: Analysis of risk factors for death due to COVID -19 in patients with DM type 1 and type 2 (DM1 and DM2).

MATERIALS AND METHODS: Retrospective analysis of the database of the national diabetes register (NDR), which included DM patients with COVID-19 and reported virus infection outcome (recovery/or death) in 15 712 DM1 and 322 279 DM2 patients during a 2-year follow-up period (01/02/2020 to 03/04/2022) (discharge date)).

RESULTS: Case fatality rate in patients with DM, who underwent COVID -19 was 17.1% (DM1–8.8%; DM2–17.5%). As a result of multivariate regression analysis of seven significant factors in DM1 and thirteen in DM2 (evaluated by univariate anlisys), a number of the most important predictors of risk for fatal outcome were identified: in DM1 these were age ≥65 years (OR =4.01, 95% CI: 1.42–11.36), presence of arterial hypertension (AH) (OR =2.72, 95% CI: 1.03 -7.16) and diabetic foot syndrome (DFS) (OR = 7.22, 95% CI: 1.98–26.29); for T2DM: age ≥ 65 years (OR =2.53, 95% CI: 1.96–3.27), male (OR =1.51, 95% CI: 1.23–1.84), duration DM ≥10 years (OR =2.01, 95% CI: 1.61–2.51), BMI ≥ 30 kg/m2 (OR =1.26, 95% CI: 1.02–1.55), ASCVD/CKD (OR =1.49, 95% CI: 1.01–2.04), history of diabetic coma (OR =12.97, 95% CI: 1.89–88.99) and presence of disability ( OR =1.40, 95% CI: 1.14–1.73). In T2DM, the type of antidiabetic therapy (ADT) prior to COVID -19 (last visit before the development of infection) had a significant impact: Insulin therapy (OR = 1.64, 95% CI: 1.30–2.07), sulfonylureas (SU) (OR =1.51, 95% CI: 1.23–1.84)); dipeptidyl peptidase-4 inhibitor (iDPP-4) therapy (OR =0.57, 95% CI: 0.39–0.83) and sodium-glucose cotransporter-2 inhibitor (iSGLT2) therapy (OR =0.64, 95% CI: 0.46–0.88). Vaccination was the most important protective factor in both types of DM: DM1 OR =0.19, 95% CI: 0.06–0.59; SD2 OR =0.20, 95% CI: 0.16–0.26.

CONCLUSION: The common risk factor for fatal outcome in both DM1 and DM2 was age ≥65 years; in DM1 — history of hypertension and DFS, in DM2 — male sex, diabetes duration ≥10 years, BMI ≥30 kg/m2, history of ASCVD/CKD and diabetic coma, disability. In T2DM, significant differences in risk were observed depending on the type of ADT: insulin and SU therapy were factors that increased the risk of death, whereas therapy with iDPP-4 and iSGLT2 reduced the risk of death. Vaccination reduced the risk of death in DM1 and DM2 by 5.2 and 5-fold, respectively.

Excess mortality in Poland during the first and second wave of the COVID-19 pandemic in 2020

Purpose

The aim of the study was to analyse excess deaths by major causes of death and associated changes in the mortality pattern of the Polish population in 2020 due to the impact of the COVID-19 pandemic.

Methods

The study used data on all deaths in Poland which occurred between 2010 and 2020 (N = 3,912,237). 10-year mortality trends for 2010-2019 were determined. An analysis of time trends has been carried out with joinpoint models and Joinpoint Regression Program. Based on the determined regression models, the number of deaths expected in 2020 and the number of excess deaths due to selected causes were calculated.

Results

The crude death rates of all-cause deaths increased from 2000 to 2019 at an average annual rate of 1% (p = 0.0007). The determined regression model revealed that the number of deaths in 2020 should have been 413,318 (95% CI: 411,252 to 415,385). In reality, 477,355 people died in Poland that year. The number of excess deaths was therefore 64,037 (15.5%). According to data from Statistics Poland the number of COVID-19-related deaths was 40,028, the number of non-COVID-19 deaths was 24,009. The largest percentage increase over the expected number of deaths was observed for suicide (12.5%), mental and behavioral disorders (7.2%) and diseases of circulatory system (5.9%). A lower than expected number of deaths was observed for malignant neoplasms (-3.2%) and transport accidents (-0.1%).

Conclusion

The difference between expected and observed non-COVID-19 deaths in 2020 indicates a need for further analysis of the causes of excess mortality.

COVID-19 mortality rate determinants in selected Eastern European countries

Background

The COVID-19 pandemic has caused increased mortality worldwide. We noticed a tendency for higher number of deaths in Eastern European countries. Therefore, we decided to investigate whether any common factor that might be responsible for the increased COVID-19 mortality exists.

Methods

In our cross-sectional study, we conducted the correlation and multiple regression analysis using R basing on the data gathered in publicly available databases. In the analysis, we included variables such as: number of deaths, number of new cases, number of hospitalizations, number of ICU (intensive care units) patients, number of vaccinations, number of boosters, number of fully vaccinated individuals, stringency index, number of reported COVID-19 variant cases, and number of flights. Additionally, we analyzed the influence of population density and median age in particular European countries on total number of COVID-19 deaths. Analyzed data represents periods from start of the COVID-19 pandemic in particular Eastern European Countries: Bulgaria, Croatia, Czech Republic, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia and Slovenia, while as the end of the study the day of January 31, 2022 is considered. Results were considered statistically significant at p < 0.05.

Results

Our study showed that mortality rate reflects the number of COVID-19 cases (e.g. for Poland was 0.0058, p < 0.001), number of hospitalized patients (e.g. for Poland 0.0116, p < 0.001), and patients in intensive care (e.g. for Slovakia 0.2326, p < 0.001). Stringency index corresponding to level of introduced restrictions and vaccination can affect the mortality rate of COVID-19 in a country-dependent manner: e.g. for Romania 0.0006, p < 0.001; whereas in Lithuania − 0.0002, p < 0.001. Moreover, occurrence of B.1.1.7 and B.1.617.2 variants increased COVID-19 mortality rates.

Conclusion

Our analysis showed that crucial factor for decreasing mortality is proper healthcare joined by accurate restriction policy. Additionally, our study shows that COVID-19 vaccination proven successful in COVID-19 mortality prevention.

Dynamics of Regional Mortality Rates From Cardiac Causes in Russia 2019–2020

Aim      To analyze the dynamics of standardized mortality ratios (SMR) (2019–2020) for the cardiological causes indicated as the primary (original) cause of death, in regions of the Russian Federation, based on the RF State Statistics Service Brief Nomenclature of Causes of Death (RFSSS BNCD). Reports have indicated substantial changes in the indexes and structure of mortality since the beginning of the COVID-19 pandemic in many countries.

Material and methods  RFSSS data on numbers of deaths were analyzed according to BNCD and mid-year population in single year of age groups in 2019 and 2020. SMRs were determined for 23 cardiological causes of death listed in the BNSD in a separate line; the average regional SMR value and the standard deviation were provided; and SMRs were compared both among 4 groups (with a previously described method) and by 23 RFSSS BNCD causes using the Wilcoxon test.

Results In 2020 vs. 2019, the mean regional SMR for cardiological causes increased by 12.07±9.86 % (from 301.02±77.67 to 336.15±84.5 %; р<0.0001). Decreases in SMR were found in 9 of 82 regions; however, only in two of them (the Republic of Ingushetia and the Sakhalin Region), SMR was decreased for all 4 groups of causes. In both 2019 and 2020 (60.9±13.8 and 62.5±12.8 %, respectively), the highest proportion of deaths was related with the 1st group of causes (chronic ischemic heart disease, IHD), with an increase in SMR of 18.66±33.28 % (р<0.0001). Increases in SMR were found in 75 regions while in the other regions, decreases in SMRs were observed. For the 2nd group of causes (myocardial infarction, other acute forms of IHD, sudden cardiac death), the mean regional SMR increased in 2020 by 3.2±18.1 % (р=0.3). Increased SMRs were noted in 54 regions. The proportion of the 2nd group in cardiological mortality was 17.3±9.7 % in 2019 and 16.1±9.6 % in 2020. The mean regional SNR for the 3rd group of causes (heart defects, myocardial diseases, etc.) increased in 2020 by 11.6±23.1 % (р=0.006). The mean regional proportion of causes for this group did not significantly changed compared to 2019 (17.5±8.2 and 17.1±7.3 %, respectively); however, the contribution of this group was greater than the contribution of the 2nd group. Increases in SMR were observed in 65 regions, while the contribution of causes related with arterial hypertension did not significantly change. Significant mid-regional differences in SMR values, dynamics of SMRs for different causes, and increases in the coefficient of variation were noted for almost all causes of death. Significant differences between 2019 and 2020 were found for 3 of 23 causes: other forms of chronic IHD (decreased SMRs in 15 regions and increased SMRs in the others), atherosclerotic heart disease (decreased SMRs in 38 regions), and alcoholic cardiomyopathy (decreased SMRs in 28 regions).

Conclusion      During the COVID-19 pandemic, the SMR for cardiological causes was increased. Considerable regional differences in values and dynamics of SMR for individual causes call for attention to the unification of the criteria for clinical diagnosis.

 

Length of hospital stay and survival of hospitalized COVID-19 patients during the second wave of the pandemic: A single centre retrospective study from Slovenia

Background

As of writing, there are no publications pertaining to the prediction of COVID-19-related outcomes and length of stay in patients from Slovene hospitals.

Objectives

To evaluate the length of regular ward and ICU stays and assess the survival of COVID-19 patients to develop better prediction models to forecast hospital capacity and staffing demands in possible further pandemic peaks.

Methods

In this retrospective, single-site study we analysed the length of stay and survival of all patients, hospitalized due to the novel coronavirus (COVID-19) at the peak of the second wave, between November 18th 2020 and January 27th 2021 at the University Clinic Golnik, Slovenia.

Results

Out of 407 included patients, 59% were male. The median length of stay on regular wards was 7.5 (IQR 5–13) days, and the median ICU length of stay was 6 (IQR 4–11) days. Age, male sex, and ICU stay were significantly associated with a higher risk of death. The probability of dying in 21 days at the regular ward was 14.4% (95% CI [10.9–18%]) and at the ICU it was 43.6% (95% CI [19.3-51.8%]).

Conclusion

The survival of COVID-19 is strongly affected by age, sex, and the fact that a patient had to be admitted to ICU, while the length of hospital bed occupancy is very similar across different demographic groups. Knowing the length of stay and admission rate to ICU is important for proper planning of resources during an epidemic.

Leading causes of excess mortality in Mexico during the COVID-19 pandemic 2020-2021: A death certificates study in a middle-income country

Background

The death toll after SARS-CoV-2 emergence includes deaths directly or indirectly associated with COVID-19. Mexico reported 325,415 excess deaths, 34.4% of them not directly related to COVID-19 in 2020. In this work, we aimed to analyse temporal changes in the distribution of the leading causes of mortality produced by COVID-19 pandemic in Mexico to understand excess mortality not directly related to the virus infection.

Methods

We did a longitudinal retrospective study of the leading causes of mortality and their variation with respect to cause-specific expected deaths in Mexico from January 2020 through December 2021 using death certificate information. We fitted a Poisson regression model to predict cause-specific mortality during the pandemic period, based on the 2015–2019 registered mortality. We estimated excess deaths as a weekly difference between expected and observed deaths and added up for the entire period. We expressed all-cause and cause-specific excess mortality as a percentage change with respect to predicted deaths by our model.

Findings

COVID-19 was the leading cause of death in 2020–2021 (439,582 deaths). All-cause total excess mortality was 600,590 deaths (38⋅2% [95% CI: 36·0 to 40·4] over expected). The largest increases in cause-specific mortality, occurred in diabetes (36·8% over expected), respiratory infections (33·3%), ischaemic heart diseases (32·5%) and hypertensive diseases (25·0%). The cause-groups that experienced significant decreases with respect to the expected pre-pandemic mortality were infectious and parasitic diseases (-20·8%), skin diseases (-17·5%), non-traffic related accidents (-16·7%) and malignant neoplasm (-5·3%).

Interpretation

Mortality from COVID-19 became the first cause of death in 2020–2021, the increase in other causes of death may be explained by changes in the health service utilization patterns caused by hospital conversion or fear of the population using them. Cause-misclassification cannot be ruled out.

Funding

This study was funded by Conacyt.

Modeling Global COVID-19 Dissemination Data After the Emergence of Omicron Variant Using Multipronged Approaches

The COVID-19 pandemic has followed a wave pattern, with an increase in new cases followed by a drop. Several factors influence this pattern, including vaccination efficacy over time, human behavior, infection management measures used, emergence of novel variants of SARS-CoV-2, and the size of the vulnerable population, among others. In this study, we used three statistical approaches to analyze COVID-19 dissemination data collected from 15 November 2021 to 09 January 2022 for the prediction of further spread and to determine the behavior of the pandemic in the top 12 countries by infection incidence at that time, namely Distribution Fitting, Time Series Modeling, and Epidemiological Modeling. We fitted various theoretical distributions to data sets from different countries, yielding the best-fit distribution for the most accurate interpretation and prediction of the disease spread. Several time series models were fitted to the data of the studied countries using the expert modeler to obtain the best fitting models. Finally, we estimated the infection rates (β), recovery rates (γ), and Basic Reproduction Numbers ([Formula: see text]) for the countries using the compartmental model SIR (Susceptible-Infectious-Recovered). Following more research on this, our findings may be validated and interpreted. Therefore, the most refined information may be used to develop the best policies for breaking the disease's chain of transmission by implementing suppressive measures such as vaccination, which will also aid in the prevention of future waves of infection.

Development and validation of a paper spray mass spectrometry method for the rapid quantitation of remdesivir and its active metabolite, GS-441524, in human plasma

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Rapid PS-MS/MS quantification of remdesivir and its active metabolite, GS-441524, directly from plasma.

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No sample preparation, short turn-around time, use of stable isotope-labeled internal standards.

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Robust stability data are presented.

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Suitable for adjusting remdesivir dosage for optimal efficacy and minimal toxicity.

Introduction

Remdesivir (GS-5734) is a nucleoside analog prodrug with antiviral activity against several single-stranded RNA viruses, including the novel severe respiratory distress syndrome virus 2 (SARS-CoV-2). It is currently the only FDA-approved antiviral agent for the treatment of individuals with COVID-19 caused by SARS-CoV-2. However, remdesivir pharmacokinetics/pharmacodynamics (PK/PD) and toxicity data in humans are extremely limited. It is imperative that precise analytical methods for the quantification of remdesivir and its active metabolite, GS-441524, are developed for use in further studies. We report, herein, the first validated anti-viral paper spray-mass spectrometry (PS-MS/MS) assay for the quantification of remdesivir and GS-441524 in human plasma. We seek to highlight the utility of PS-MS/MS technology and automation advancements for its potential future use in clinical research and the clinical laboratory setting.

Methods

Calibration curves for remdesivir and GS-441524 were created utilizing seven plasma-based calibrants of varying concentrations and two isotopic internal standards of set concentrations. Four plasma-based quality controls were prepared in a similar fashion to the calibrants and utilized for validation. No sample preparation was needed. Briefly, plasma samples were spotted on a paper substrate contained within pre-manufactured plastic cassette plates, and the spots were dried for 1 h. The samples were then analyzed directly for 1.2 min utilizing PS-MS/MS. All experiments were performed on a Thermo Scientific Altis triple quadrupole mass spectrometer utilizing automated technology.

Results

The calibration ranges were 20 – 5000 and 100 – 25000 ng/mL for remdesivir and GS-441524, respectively. The calibration curves for the two antiviral agents showed excellent linearity (average R² = 0.99–1.00). The inter- and intra-day precision (%CV) across validation runs at four QC levels for both analytes was less than 11.2% and accuracy (%bias) was within ± 15%. Plasma calibrant stability was assessed and degradation for the 4 °C and room temperature samples were seen beginning at Day 7. The plasma calibrants were stable at −20 °C. No interference, matrix effects, or carryover was discovered during the validation process.

Conclusions

PS-MS/MS represents a useful methodology for rapidly quantifying remdesivir and GS-441524, which may be useful for clinical PK/PD, therapeutic drug monitoring (TDM), and toxicity assessment, particularly during the current COVID-19 pandemic and future viral outbreaks.

Efficacy and effectiveness of SARS-CoV-2 vaccines for death prevention: A protocol for a systematic review and meta-analysis

Background

There is consistent evidence that SARS-CoV-2 vaccines have statistical and clinical significant efficacy to prevent incident and severe cases of COVID-19, although different outcomes were analyzed and different risk reductions were observed. However, randomized control trials (RCT) were not designed or powered to assess whether the vaccines prevent deaths, even though this was a secondary or exploratory outcome across many studies. Early real-world observational data suggest that these vaccines are highly effective in reducing hospitalization and all-cause mortality. Our objective is to summarize and appraise—the existing evidence on the efficacy and real-world effectiveness of all SARS-CoV-2 vaccines currently approved for full or limited use to prevent all-cause and COVID-19-attributed mortality.

Methods

The population consists of persons with a record of vaccination status and the outcome of interest. Randomized controlled trials, comparative cohort and case-control studies reporting vaccination with any of the vaccines approved (intervention) will be eligible. The primary outcome will be all cause deaths. COVID-19-attributed deaths and deaths attributable to the vaccination (adverse event deaths) will be secondary outcomes. We will compare deaths occurring in vaccinated persons versus those non-vaccinated or having received placebo. Studies in any language will be eligible. Two independent reviewers will screen for inclusion and assess quality of studies using the Cochrane Risk of Bias 2 and the ROBINS-1 tool, as appropriate. Hazard ratios will be calculated. Assessment of statistical heterogeneity amongst the studies will be done using I² and prediction intervals, as well as visual inspection of the forest plots. Publication bias will be assessed using a funnel plot and Egger statistical test if we have more than 10 studies in a forest plot. We have followed the PRISMA-Protocol checklist for the current protocol, which is registered at Prospero (York University, CRD42021262211).

Estimation of Excess Deaths Associated With the COVID-19 Pandemic in Istanbul, Turkey

Background and Objectives

The official number of daily cases and deaths are the most prominent indicators used to plan actions against the COVID-19 pandemic but are insufficient to see the real impact. Official numbers vary due to testing policy, reporting methods, etc. Therefore, critical interventions are likely to lose their effectiveness and better-standardized indicators like excess deaths/mortality are needed. In this study, excess deaths in Istanbul were examined and a web-based monitor was developed.

Methods

Daily all-cause deaths data between January 1, 2015- November 11, 2021 in Istanbul is used to estimate the excess deaths. Compared to the pre-pandemic period, the % increase in the number of deaths was calculated as the ratio of excess deaths to expected deaths (P-Scores). The ratio of excess deaths to official figures (T) was also examined.

Results

The total number of official and excess deaths in Istanbul are 24.218 and 37.514, respectively. The ratio of excess deaths to official deaths is 1.55. During the first three death waves, maximum P-Scores were 71.8, 129.0, and 116.3% respectively.

Conclusion

Excess mortality in Istanbul is close to the peak scores in Europe. 38.47% of total excess deaths could be considered as underreported or indirect deaths. To re-optimize the non-pharmaceutical interventions there is a need to monitor the real impact beyond the official figures. In this study, such a monitoring tool was created for Istanbul. The excess deaths are more reliable than official figures and it can be used as a gold standard to estimate the impact more precisely.

In-hospital admissions and deaths in the context of the COVID-19 pandemic, in Romania

Introduction

The COVID-19 pandemic context led to a relevant burden on essential sectors of society; hospital sector capacity is tested in this period.

Methods

A cross-sectional study of admissions in hospitals reporting DRG data for 2018-2020. Trend analysis of admissions and deaths in hospitals was carried out for identifying annual patterns and deviations from the 2010-2020 trend. Data aggregated by year, month, diagnosis, death in hospital. Graph analysis for time and diagnosis comparisons and correlation identifying associations.

Results

There is an annual change in admission and death patterns recorded in Romanian hospitals. An important contraction in number of acute hospital admissions was recording during the COVID-19 pandemic; patients' hesitancy to seek healthcare and limited capacity to treat patients other than COVID-19 patients due to legal regulations limiting the admissions number could explain this pattern of admission only for serious condition or emergency surgery. In Romania excess deaths in second half 2020 was generally greater than COVID-19 deaths. Overall, excess mortality between March and December 2020 was more than double than reported COVID-19 deaths. The same mortality pattern persists, but with significant decreases for some diagnoses.

Conclusions

The Romanian healthcare system has been challenged due to COVID-19 pandemic, leading to temporary reorganization of hospitals with consequences on all acute care diagnostics and therapeutic pathways. It is a challenge to identify causes of reduced inpatient treatment rates and to provide evidence on hospital activity for understanding future optimal management of patients with COVID-19, but also with other acute and chronic conditions.

COVID-19 Autopsies Reveal Underreporting of SARS-CoV-2 Infection and Scarcity of Co-infections

Coronavirus disease 2019 (COVID-19) mortality can be estimated based on reliable mortality data. Variable testing procedures and heterogeneous disease course suggest that a substantial number of COVID-19 deaths is undetected. To address this question, we screened an unselected autopsy cohort for the presence of SARS-CoV-2 and a panel of common respiratory pathogens. Lung tissues from 62 consecutive autopsies, conducted during the first and second COVID-19 pandemic waves in Switzerland, were analyzed for bacterial, viral and fungal respiratory pathogens including SARS-CoV-2. SARS-CoV-2 was detected in 28 lungs of 62 deceased patients (45%), although only 18 patients (29%) were reported to have COVID-19 at the time of death. In 23 patients (37% of all), the clinical cause of death and/or autopsy findings together with the presence of SARS-CoV-2 suggested death due to COVID-19. Our autopsy results reveal a 16% higher SARS-CoV-2 infection rate and an 8% higher SARS-CoV-2 related mortality rate than reported by clinicians before death. The majority of SARS-CoV-2 infected patients (75%) did not suffer from respiratory co-infections, as long as they were treated with antibiotics. In the lungs of 5 patients (8% of all), SARS-CoV-2 was found, yet without typical clinical and/or autopsy findings. Our findings suggest that underreporting of COVID-19 contributes substantially to excess mortality. The small percentage of co-infections in SARS-CoV-2 positive patients who died with typical COVID-19 symptoms strongly suggests that the majority of SARS-CoV-2 infected patients died from and not with the virus.

An Epidemiological Study to Investigate Links between Atmospheric Pollution from Farming and SARS-CoV-2 Mortality

Exposure to atmospheric particulate matter and nitrogen dioxide has been linked to SARS-CoV-2 infection and death. We hypothesized that long-term exposure to farming-related air pollutants might predispose to an increased risk of COVID-19-related death. To test this hypothesis, we performed an ecological study of five Italian Regions (Piedmont, Lombardy, Veneto, Emilia-Romagna and Sicily), linking all-cause mortality by province (administrative entities within regions) to data on atmospheric concentrations of particulate matter (PM_2.5 and PM₁₀) and ammonia (NH₃), which are mainly produced by agricultural activities. The study outcome was change in all-cause mortality during March-April 2020 compared with March-April 2015-2019 (period). We estimated all-cause mortality rate ratios (MRRs) by multivariate negative binomial regression models adjusting for air temperature, humidity, international import-export, gross domestic product and population density. We documented a 6.9% excess in MRR (proxy for COVID-19 mortality) for each tonne/km² increase in NH₃ emissions, explained by the interaction of the period variable with NH₃ exposure, considering all pollutants together. Despite the limitations of the ecological design of the study, following the precautionary principle, we recommend the implementation of public health measures to limit environmental NH₃ exposure, particularly while the COVID-19 pandemic continues. Future studies are needed to investigate any causal link between COVID-19 and farming-related pollution.

Analysis of the dynamics of mortality from respiratory diseases in the Russian Federation for 2019–2020

Aim. To study the dynamics and contribution of mortality from Diseases of the respiratory system (DRS) in 2019 and 2020 to mortality from all causes with and without deaths from COVID-19 in 82 regions of the Russian Federation. Materials and methods. The data provided by Rosstat for 2019 and 2020 on the average annual population and the number of deaths due to causes of DRS (class J00J99) were used the standardised death rate (SDR) were calculated, the regional average value, standard deviation and coefficient of variation. Results. The average increase in the SDR from DRS in 2020 was 22.1913.22 per 100 thousand population (66.4489.6% higher than in 2019). The average regional SDR from DRS + COVID-19 in 2020 was higher than the SDR from DRS in 2019 by 87.6530.1 per 100 thousand population. The average regional share of SDR in the structure of mortality excluding COVID-19 increased from 3.661.44 to 5.062.49%; taking into account COVID-19, it increased to 10.963.13%. In 16 regions, the SDR from DRS + COVID-19 exceeded the increase in mortality from all causes. No correlation was found between SDR (2020) from all causes and SDR from COVID-19 (r=0.09; p=0.39); an inverse correlation was found between SDR from DRS and SDR from COVID-19 in 2020 (r=-0.42; p0.0001). Conclusion. Against the background of high interregional variability of SDR from DRS in most regions, an increase in the mortality rate from DRS and the contribution of DRS to total mortality in 2020 was registered.

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.

Caveats on COVID-19 herd immunity threshold: the Spain case

After a year of living with the COVID-19 pandemic and its associated consequences, hope looms on the horizon thanks to vaccines. The question is what percentage of the population needs to be immune to reach herd immunity, that is to avoid future outbreaks. The answer depends on the basic reproductive number, R₀, a key epidemiological parameter measuring the transmission capacity of a disease. In addition to the virus itself, R₀ also depends on the characteristics of the population and their environment. Additionally, the estimate of R₀ depends on the methodology used, the accuracy of data and the generation time distribution. This study aims to reflect on the difficulties surrounding R₀ estimation, and provides Spain with a threshold for herd immunity, for which we considered the different combinations of all the factors that affect the R₀ of the Spanish population. Estimates of R₀ range from 1.39 to 3.10 for the ancestral SARS-CoV-2 variant, with the largest differences produced by the method chosen to estimate R₀. With these values, the herd immunity threshold (HIT) ranges from 28.1 to 67.7%, which would have made 70% a realistic upper bound for Spain. However, the imposition of the delta variant (B.1.617.2 lineage) in late summer 2021 may have expanded the range of R₀ to 4.02–8.96 and pushed the upper bound of the HIT to 90%.

Risk factors for COVID-19 case fatality rate in people with type 1 and type 2 diabetes mellitus: A nationwide retrospective cohort study of 235,248 patients in the Russian Federation

THE AIM

To study the association of demographic, clinical, and laboratory factors and the use of glucose-lowering drugs and anti-coronavirus disease (COVID-19) vaccination with the COVID-19-related case fatality rate (CFR) in diabetes mellitus (DM) patients.

METHODS

This study is a nationwide observational cohort study based on the data from the National Diabetes Register (NDR) that is the database containing online clinical information about the population with DM. The outcomes (death or recovery) for COVID-19 were registered in 235,248 patients with DM [type 1 diabetes mellitus (T1DM), n = 11,058; type 2 diabetes mellitus (T2DM), n = 224,190] from March 20, 2020, until November 25, 2021. The unadjusted odds ratio (OR) and 95% confidence interval (CI) were used to estimate the risk factors for CFR. Then the ranging of significant factors was performed and the most vulnerable groups of factors for the lethal outcome were chosen.

RESULTS

The CFR due to COVID-19 was 8.1% in T1DM and 15.3% in T2DM. Increased CFR was associated with the male population [OR = 1.25 (95% CI: 1.09-1.44) in T1DM and 1.18 (95% CI: 1.15-1.21) in T2DM], age ≥65 years [OR = 4.44 (95% CI: 3.75-5.24) in T1DM and 3.18 (95% CI: 3.09-3.26) in T2DM], DM duration ≥10 years [OR = 2.46 (95% CI: 2.06-2.95) in T1DM and 2.11 (95% CI: 2.06-2.16) in T2DM], body mass index (BMI) ≥30 kg/m² [OR = 1.95 (95% CI: 1.52-2.50)] in T1DM, HbA1c ≥7% [OR = 1.35 (95% CI: 1.29-1.43)] in T2DM. The atherosclerotic cardiovascular disease (ASCVD) and chronic kidney disease (CKD) were associated with higher CFR in T1DM but not in T2DM. The pre-COVID-19 glucose-lowering therapy in T2DM was differently associated with CFR (OR): 0.61 (95% CI: 0.59-0.62) for metformin, 0.59 (95% CI: 0.57-0.61) for dipeptidyl peptidase-4 inhibitors (DPP-4 inhibitors), 0.46 (95% CI: 0.44-0.49) for sodium-glucose co-transporter-2 (SGLT2) inhibitors, 0.38 (95% CI: 0.29-0.51) for glucagon-like peptide-1 receptor agonists (arGLP-1), 1.34 (95% CI: 1.31-1.37) for sulfonylurea (SU), and 1.47 (95% CI: 1.43-1.51) for insulin. Anti-COVID-19 vaccination was associated with a lower fatality risk in both DM types: OR = 0.07 (95% CI: 0.03-0.20) in T1DM and OR = 0.19 (95% CI: 0.17-0.22) in T2DM.

CONCLUSIONS

The results of our study suggest that increased COVID-19-related fatality risk in both T1DM and T2DM patients associated with the male population, older age, longer DM duration, and absence of anti-COVID-19 vaccination. In T2DM, pre-COVID-19 glucose-lowering therapy with metformin, DPP-4 inhibitors, SGLT2 inhibitors, and arGLP-1 had a positive effect on the risk of death. The most vulnerable combination of risk factors for lethal outcome in both DM types was vaccine absence + age ≥65 years + DM duration ≥10 years.

A poorly understood disease? The impact of COVID-19 on the income gradient in mortality over the course of the pandemic

Mortality inequalities remain substantial in many countries, and large shocks such as pandemics could amplify them further. The unequal distribution of COVID-19 confirmed cases suggests that this is the case. Yet, evidence on the causal effect of the epidemic on mortality inequalities remains scarce. In this paper, we exploit exhaustive municipality-level data in France, one of the most severely hit country in the world, to identify a negative relationship between income and excess mortality within urban areas, that persists over COVID-19 waves. Over the year 2020, the poorest municipalities experienced a 30% higher increase in excess mortality. Our analyses can rule out an independent contribution of lockdown policies to this heterogeneous impact. Finally, we find evidence that both labor-market exposure and housing conditions are major determinants of the epidemic-induced effects of COVID-19 on mortality inequalities, but that their respective role depends on the state of the epidemic.

Estimation of all-cause excess mortality by age-specific mortality patterns for countries with incomplete vital statistics: a population-based study of the case of Peru during the first wave of the COVID-19 pandemic

BACKGROUND

All-cause excess mortality is a comprehensive measure of the combined direct and indirect effects of COVID-19 on mortality. Estimates are usually derived from Civil Registration and Vital Statistics (CRVS) systems, but these do not include non-registered deaths, which may be affected by changes in vital registration coverage over time.

METHODS

Our analytical framework and empirical strategy account for registered mortality and under-registration. This provides a better estimate of the actual mortality impact of the first wave of the COVID-19 pandemic in Peru. We use population and crude mortality rate projections from Peru's National Institute of Statistics and Information (INEI, in Spanish), individual-level registered COVID-19 deaths from the Ministry of Health (MoH), and individual-level registered deaths by region and age since 2017 from the National Electronic Deaths Register (SINADEF, in Spanish).We develop a novel framework combining different estimates and using quasi-Poisson models to estimate total excess mortality across regions and age groups. Also, we use logistic mixed-effects models to estimate the coverage of the new SINADEF system.

FINDINGS

We estimate that registered mortality underestimates national mortality by 37•1% (95% CI 23% - 48•5%) across 26 regions and nine age groups. We estimate total all-cause excess mortality during the period of analysis at 173,099 (95% CI 153,669 - 187,488) of which 108,943 (95% CI 96,507 - 118,261) were captured by the vital registration system. Deaths at age 60 and over accounted for 74•1% (95% CI 73•9% - 74•7%) of total excess deaths, and there were fewer deaths than expected in younger age groups. Lima region, on the Pacific coast and including the national capital, accounts for the highest share of excess deaths, 87,781 (95% CI 82,294 - 92,504), while in the opposite side regions of Apurimac and Huancavelica account for less than 300 excess deaths.

INTERPRETATION

Estimating excess mortality in low- and middle-income countries (LMICs) such as Peru must take under-registration of mortality into account. Combining demographic trends with data from administrative registries reduces uncertainty and measurement errors. In countries like Peru, this is likely to produce significantly higher estimates of excess mortality than studies that do not take these effects into account.

FUNDING

None.

Impact of COVID-19 Pandemic on Total Mortality in Poland

Background: According to published data the number of deaths attributed to COVID-19 is underestimated between 30 and 80%. Aim: The aim of this study is to assess the impact of COVID-19 on total mortality of Poland and the Silesian voivodship. Methods: Secondary epidemiological data on COVID-19 deaths were obtained from the Ministry of Health registry and data on total mortality were gathered from the National Statistical Office and Registry Office in Poland. Three scenarios were used to estimated COVID-19 deaths: real number + an extra 30%, 60%, and 70% excess total deaths. Results: In 2020, there were 73,254, 64,584, and 67,677 excess deaths in comparison to 2017–2019, respectively. For the Silesian voivodship, it was 8339, 7946, and 8701, respectively. The total mean increase in deaths was 16% for the whole country and the Silesian voivodship. The simulation for 30% extra COVID-19 deaths gave COVID-19 mortality equal to 12.5%; n = 50,708 deaths, for extra 60%; 17.9% n = 72,866 and for extra 70%; 19.7% n = 80,251 for Poland; and 11.9% (n = 6072), 17.2% (n = 8740), 24.2% (n = 12,297), respectively, for the Silesian voivodship. Conclusions: The participation of COVID-19 in total deaths should not exceed 20% for Poland and 24% for the Silesian voivodship in 2020.

Impact of Meteorological Conditions on the Dynamics of the COVID-19 Pandemic in Poland

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the novel coronavirus. The role of environmental factors in COVID-19 transmission is unclear. This study aimed to analyze the correlation between meteorological conditions (temperature, relative humidity, sunshine duration, wind speed) and dynamics of the COVID-19 pandemic in Poland. Data on a daily number of laboratory-confirmed COVID-19 cases and the number of COVID-19-related deaths were gatheredfrom the official governmental website. Meteorological observations from 55 synoptic stations in Poland were used. Moreover, reports on the movement of people across different categories of places were collected. A cross-correlation function, principal component analysis and random forest were applied. Maximum temperature, sunshine duration, relative humidity and variability of mean daily temperature affected the dynamics of the COVID-19 pandemic. An increase intemperature and sunshine hours decreased the number of confirmed COVID-19 cases. The occurrence of high humidity caused an increase in the number of COVID-19 cases 14 days later. Decreased sunshine duration and increased air humidity had a negative impact on the number of COVID-19-related deaths. Our study provides information that may be used by policymakers to support the decision-making process in nonpharmaceutical interventions against COVID-19.