Excess mortality from COVID-19: a commentary on the Italian experience

A simulation of undiagnosed population and excess mortality during the COVID-19 pandemic

Whereas the extent of outbreak of COVID-19 is usually accessed via the number of reported cases and the number of patients succumbed to the disease, the officially recorded overall excess mortality numbers during the pandemic waves, which are significant and often followed the rise and fall of the pandemic waves, put a question mark on the above methodology. Gradually it has been recognized that estimating the size of the undiagnosed population (which includes asymptomatic cases and symptomatic cases but not reported) is also crucial. Here we used the classical mathematical SEIR model having an additional compartment, that is the undiagnosed group in addition to the susceptible, exposed, diagnosed, recovered and deceased groups, to link the undiagnosed COVID-19 cases to the reported excess mortality numbers and thereby try to know the actual size of the disease outbreak. The developed model wase successfully applied to relevant COVID-19 waves in USA (initial months of 2020), South Africa (mid of 2021) and Russia (2020–21) when a large discrepancy between the reported COVID-19 mortality and the overall excess mortality had been noticed.

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].

Incidence and Impact of Ventilator Associated Multidrug Resistant Pneumonia in Patients with SARS-COV2

Introduction

Ventilator Associated Pneumonia (VAP) is associated with significant cost, morbidity, and mortality. There is limited data on the incidence of VAP, appropriate antibiotic timing, and the impact of multidrug resistant VAP in intubated Coronavirus disease-19 (COVID-19) patients.

Methods

A retrospective study was conducted at 2 tertiary urban academic centers involving 132 COVID-19 patients requiring invasive mechanical ventilation (IMV). The epidemiology of VAP, the impact of prior empiric antibiotic administration on the development of Multidrug Resistant Organism (MDRO) infections, and the impact of VAP on patient outcomes were studied.

Results

The average age of the patients was 60.58% were males, 70% were African-Americans and two-thirds of patients had diabetes, hypertension, or heart disease. The average Body Mass Index (BMI) was 32.9. Forty-one patients (27%) developed VAP. Patients with VAP had a significantly higher Sequential Organ Failure Assessment (SOFA) score prior to Intensive Care Unit (ICU) admission. Sixty percent received empiric antibiotics before initiation of IMV, mostly on hospital admission, and 81% received empiric antibiotics at the time of intubation. The administration of empiric antibiotics was not associated with a higher prevalence of VAP. The prevalence of VAP was 22 per 1000 days on ventilation. No difference in mortality was seen between VAP and non-VAP groups at 49% and 57% respectively (p = 0.4). VAP was associated with increased ICU length of stay (LOS), 30 vs. 16 days (p < 0.001), and longer hospital LOS 35 vs. 17 days (p < 0.001). 40% of VAPs were caused by MDROs. The most common organism was Staphylococcus aureus (28%), with almost half (48%) being methicillin resistant Staphylococcus aureus (MRSA).

Conclusion

VAP was a common complication of patients intubated for COVID-19 pneumonia. Most patients received empiric antibiotics upon the hospital and/or ICU admission. There was a 40% incidence of multidrug resistant pneumonia. Patients who developed VAP had almost twice as long hospital and ICU LOS.

First Wave of COVID-19 Pandemic in Italy: Data and Evidence

INTRODUCTION

Unexpectedly, Italy was the first Western country to face COVID-19 outbreak, but promptly it was the first one to adopt stringent procedures to stem the spread of infection. The objective of this study was to describe the epidemiological situation and comorbidities in Italy, in addition to containment measures and health system and social protection strengthening ones applied in this country.

METHODS

Available population data were collected, managed, and analysed from the daily reports on COVID-19 published every day, from 1 February to 8 June 2020.

RESULTS

Lombardia, a northern region of Italy, is considered the epicentre for the wave of the infection with the first diagnosed case, but in a few weeks other regions were involved (with Piemonte, Emilia-Romagna, and Veneto covering more than 70% of the Italian total cases). In the European context, after 3 months of containing measures of the sanitary emergency, Italy is the fourth country for the number of total positive cases (with 235,278 total case as at 8 June 2020), after Russia, the United Kingdom, and Spain, whereas it is the second for the number of deaths (with 33,964 deaths as at 8 June 2020), only after the United Kingdom. Regarding incidence, the curve of daily new cases shows an increasing trend up to 22 March 2020 with 6557 new daily cases and then a decreasing trend up to 280 as at 8 June. This turnaround can be explained by the application of national lockdown starting from 9 March and by the following 14 days of incubation of infection. Profiles of subjects at major risk of poor prognosis and death for COVID-19 are elderly (mean age of 80 years) and with three or more comorbidities. These characteristics can partially explain the high lethality rate for coronavirus observed in Italy, which is the European country with the highest share of elderly. In addition, other possible explanations of this high lethality are differences in testing policies among countries that influence the number of asymptomatic or pauci-symptomatic patients diagnosed as coronavirus positive, together with differences in definition and in the way of recording deaths for coronavirus. In the absence of a vaccine, severe nonpharmaceutical interventions (NPIs), including national lockdown, quarantine, social distancing, and use of facial masks, have been applied with success to reduce the virus spread and the burden on the National Health System. In addition to these stringent containment measures to fight the pandemic, other policies have been adopted searching to ensure economic sustainability, social safety, and stability.

CONCLUSION

Italy was the first Western country with a wide spread of COVID-19, but it was the first one to introduce containment restrictions, tightening them week by week and subjecting the 60 million people living in the country to unprecedented limitations. Many measurements have been adopted by the government, such as lockdown during the early stages of infection and subsequent social distancing and wearing face masks in public areas. Italians were compliant with all the measures ordered by the government and their discipline reflected in the COVID numbers: the curve of daily new cases after a peak at the end of March now shows a consistent decreasing trend up. In this phase of current reduction of virus diffusion, it is crucial to accommodate the need to continue protecting citizens from the risk of infection with the undeferrable, although gradual, restart of the economic and social system. This new scenario requires an active collaboration among all the actors: statutory bodies, employers, civil society, and the third sector.

Predicting the risk of severe COVID-19 outcomes in primary care: development and validation of a vulnerability index for equitable allocation of effective vaccines

BACKGROUND

General practitioners (GPs) need a valid, user-friendly tool to identify patients most vulnerable to COVID-19, especially in the hypothesis of a booster vaccine dose. The aim of this study was to develop and validate a GP-friendly prognostic index able to forecast severe COVID-19 outcomes in primary care. Indeed, no such prognostic score is as yet available in Italy.

RESEARCH DESIGN AND METHODS

In this retrospective cohort study, a representative sample of 47,868 Italian adults were followed up for 129,000 person-months. The study outcome was COVID-19-related hospitalization and/or death. Candidate predictors were chosen on the basis of systematic evidence and current recommendations. The model was calibrated by using Cox regression. Both internal and external validations were performed.

RESULTS

Age, sex and several clinical characteristics were significantly associated with severe outcomes. The final multivariable model explained 60% (95%CI 58-63%) of variance for COVID-19-related hospitalizations and/or deaths. The area under the receiver-operator curve (AUC) was 84% (95% CI: 83-85%). On applying the index to an external cohort, the AUC was 94% (95% CI: 93-95%).

CONCLUSIONS

This index is a reliable prognostic tool that can help GPs to prioritize their patients for preventive and therapeutic interventions.

Reduced turnaround times through multi-sectoral community collaboration during the first surge of SARS-CoV-2 and associated effect on patient care and hospital operations

BACKGROUND

In March 2020, an influx of admissions in COVID-19 positive patients threatened to overwhelm healthcare facilities in East Baton Rouge Parish, Louisiana. Exacerbating this problem was an overall shortage of diagnostic testing capability at that time, resulting in a delay in time-to-result return. An improvement in diagnostic testing availability and timeliness was necessary to improve the allocation of resources and ultimate throughput of patients. The management of a COVID-19 positive patient or patient under investigation requires infection control measures that can quickly consume personal protective equipment (PPE) stores and personnel available to treat these patients. Critical shortages of both PPE and personnel also negatively impact care in patients admitted with non-COVID-19 illnesses.

METHODS

A multisectoral partnership of healthcare providers, facilities and academicians created a molecular diagnostic lab within an academic research facility dedicated to testing inpatients and healthcare personnel for SARS-CoV-2. The purpose of the laboratory was to provide a temporary solution to the East Baton Rouge Parish healthcare community until individual facilities were self-sustaining in testing capabilities. We describe the partnership and the impacts of this endeavor by developing a model derived from a combination of data sources, including electronic health records, hospital operations, and state and local resources.

FINDINGS

Our model demonstrates two important principles: the impact of reduced turnaround times (TAT) on potential differences in inpatient population numbers for COVID-19 and savings in PPE attributed to the more rapid TAT.

Associations of Underlying Health Conditions With Anxiety and Depression Among Outpatients: Modification Effects of Suspected COVID-19 Symptoms, Health-Related and Preventive Behaviors

Objectives: We explored the association of underlying health conditions (UHC) with depression and anxiety, and examined the modification effects of suspected COVID-19 symptoms (S-COVID-19-S), health-related behaviors (HB), and preventive behaviors (PB).

Methods: A cross-sectional study was conducted on 8,291 outpatients aged 18–85 years, in 18 hospitals and health centers across Vietnam from 14th February to May 31, 2020. We collected the data regarding participant's characteristics, UHC, HB, PB, depression, and anxiety.

Results: People with UHC had higher odds of depression (OR = 2.11; p < 0.001) and anxiety (OR = 2.86; p < 0.001) than those without UHC. The odds of depression and anxiety were significantly higher for those with UHC and S-COVID-19-S (p < 0.001); and were significantly lower for those had UHC and interacted with “unchanged/more” physical activity (p < 0.001), or “unchanged/more” drinking (p < 0.001 for only anxiety), or “unchanged/healthier” eating (p < 0.001), and high PB score (p < 0.001), as compared to those without UHC and without S-COVID-19-S, “never/stopped/less” physical activity, drinking, “less healthy” eating, and low PB score, respectively.

Conclusion: S-COVID-19-S worsen psychological health in patients with UHC. Physical activity, drinking, healthier eating, and high PB score were protective factors.

Burnout of health care providers during the COVID-19 pandemic: Focus on Medical Oncologists

The spread of the coronavirus disease 2019 (Covid-19) has challenged hard the national health system worldwide. At any level, the role of health care providers has been rapidly revisited and eventually modified to face the pandemic. The search of the balance between the provision of the most appropriate health-related services and safety of both patients and health care providers has become an indisputable necessity. The consequently increased work load, along with a widespread feeling of intellectual isolation, emotional overload, sense of inadequacy for involvement in tasks and disciplines which are not always familiar have all been proposed as factors related to the onset and/or worsening of the burnout phenomenon. This latter is sadly renown among care givers and is particularly common among medical oncologists. We herein share our perspectives on the burnout phenomenon over the course of the Covid-19 pandemic, with a specific focus on medical oncologists. Results from the most recent and inherent studies are presented and commented in light of hints provided by the experience matured by a quite restricted, still potentially representative, number of professionals figures from the medical oncologists' category. Reasons are proposed to explain the sense of inadequacy currently perceived in relation to the limits imposed by the current pandemic. In more detail, we illustrate the nature and extents of some of the most relevant difficulties in the optimal management of cancer patients and constant efforts towards the scientific upgrade which allows for the improvement of the professional performance. The need for a deeper understanding of the roots and consequences of the Covid-19 pandemic on the mental health of medical oncologists is finally stressed.

Underestimation of COVID-19 mortality during the pandemic

Background

There has been considerable international variation in mortality during the COVID-19 pandemic. The objective of this study was to investigate the differences between mortality registered as due to COVID-19 and the excess all-cause mortality reported in countries worldwide during the COVID-19 pandemic.

Methods

Ecological analysis of 22 countries compared 5-year historical all-cause mortality, reported all-cause mortality and expected all-cause mortality (calculated as historical mortality plus the reported deaths attributed to COVID-19). Data available from the first week of January 2020 to that most recently available were analysed.

Results

Compared to the preceding 5 years, there was an excess of 716 616 deaths, of which 64.3% were attributed to COVID-19. The proportion of deaths registered as COVID-19-related/excess deaths varied markedly between countries, ranging between 30% and 197% in those countries that had an excess of deaths during the period of observation. In most countries where a definite peak in COVID-19-related deaths occurred, the increase in reported all-cause mortality preceded the increase in COVID-19 reported mortality. During the latter period of observation, a few countries reported fewer all-cause deaths than the historical figures.

Conclusion

The increases in all-cause mortality preceded the increase in COVID-19 mortality in most countries that had definite spikes in COVID-19 mortality. The number of deaths attributed to COVID-19 was underestimated by at least 35%. Together these findings suggest that calculation of excess all-cause mortality is a better predictor of COVID-19 mortality than the reported rates, in those countries experiencing definite increases in mortality.

In countries experiencing marked increases in all-cause mortality during the global pandemic, all-cause mortality more accurately estimates #COVID19 mortality and the onset of the pandemic than the reported COVID-19 mortality rateshttps://bit.ly/3fOtBJg

A comparison of COVID-19 epidemiological indicators in Sweden, Norway, Denmark, and Finland

Aims: To compare the early impact of COVID-19 infections and mortality from February to July 2020 across the Nordic nations of Sweden, Norway, Denmark, and Finland through available public data sources and conduct a descriptive analysis of the potential factors that drove different epidemiological outcomes, with a focus on Sweden's response. Methods: COVID-19 cases, deaths, tests, case age distribution, and the difference between 2020 all-cause mortality and the average mortality of the previous 5 years were compared across nations. Patterns in cell phone mobility data, testing strategies, and seniors' care home deaths were also compared. Data for each nation were based on publicly available sources as of July 31, 2020. Results: Compared with its Nordic peers, Sweden had a higher incidence rate across all ages, a higher COVID-19-related death rate only partially explained by population demographics, a higher death rate in seniors' care, and higher all-cause mortality. Sweden had approximately half as much mobility change as its Nordic neighbours until April and followed similar rates as its neighbours from April to July. Denmark led its Nordic peers in testing rates, while Sweden had the highest cumulative test-positivity rate continuously from mid-March. Conclusions: COVID-19 pushed Sweden's health system to its capacity, exposed systemic weaknesses in the seniors' care system, and revealed challenges with implementing effective contact tracing and testing strategies while experiencing a high case burden. Looser government restrictions at the beginning of the outbreak are likely to have played a role in the impact of COVID-19 in Sweden. In an effort to improve epidemic control, Sweden has increased testing rates, implemented more restrictive prevention measures, and increased their intensive care unit bed capacity.

A phase 2, open label, multicenter, single arm study of tocilizumab on the efficacy and tolerability of tocilizumab in the treatment of patients with COVID-19 pneumonia (TOCIVID-19 trial): Statistical analysis plan

BACKGROUND

Tocilizumab, an IL-6 receptor antagonist, was suggested as a possible treatment of severe or critical COVID-19 pneumonia in a small Chinese study. The TOCIVID-19 trial evaluates efficacy and tolerability of tocilizumab in the treatment of patients with severe or critical COVID-19 pneumonia.

METHODS

TOCIVID-19 is an academic multicenter, single-arm, open-label, phase 2 study. All the patients are being offered a single shot of 8 mg/kg of Tocilizumab (up to a maximum of 800 mg), with an eventual second administration at the discretion of the Investigator. A companion prospective cohort, added to corroborate internal validity, includes either patients not eligible for phase 2 or subjects eligible for phase 2 but exceeding the planned sample size. 14- and 30-days lethality rates are the two co-primary endpoints in the intention-to-treat (ITT) population. Secondary objectives are to evaluate mortality and clinical improvement in the modified-ITT population of subjects who received the drug. Details of the methodological and statistical approaches are reported here reflecting the amendments impelled by the continuously increasing knowledge on COVID-19 progression and challenges in data collection.

CONCLUSION

This paper provides details of planned statistical analyses for TOCIVID19 trial to reduce the risk of reporting bias and increase validity of the study findings.TOCIVID-19 trial is registered in the EudraCT database with number 2020-001110-38 and in clinicaltrials.gov with ID NCT04317092.

Cancer patients and coronavirus disease 2019: evidence in context

In the rapidly evolving coronavirus disease 2019 (COVID-19) outbreak, inherent literature has been increasing at an impressive rate. Such a dynamic scenario imposes the necessity to define a new framework for cancer care. The first emerging evidence has transmitted contrasting messages with regards to cancer care management. Some authors have hypothesized an increased infection risk for cancer patients, with a more severe disease, requiring a reorganization of health care system that could disrupt an established high quality cancer care routine in many developed countries. Other authors have attempted to interpret data related to cancer patients by better defining their “active status”. We herein present our point of view in the light of current evidence and based on the experience matured at our cancer institute in managing cancer patients during the COVID-19 pandemic. Our core idea is that “active cancer” may be considered a proxy of more recent exposure to diagnostic or therapeutic procedures, and the frequency of access to health care facilities can be predicted as a function of the severity of cancer symptoms. Hence, COVID-19 screening program and the adjustment of cancer care provision in a cancer institutions should be led by this risk model, while awaiting new evidence.