Excess Deaths and Hospital Admissions for COVID-19 Due to a Late Implementation of the Lockdown in Italy

Description of the COVID-19 epidemiology in Malaysia

Introduction

Since the COVID-19 pandemic began, it has spread rapidly across the world and has resulted in recurrent outbreaks. This study aims to describe the COVID-19 epidemiology in terms of COVID-19 cases, deaths, ICU admissions, ventilator requirements, testing, incidence rate, death rate, case fatality rate (CFR) and test positivity rate for each outbreak from the beginning of the pandemic in 2020 till endemicity of COVID-19 in 2022 in Malaysia.

Methods

Data was sourced from the GitHub repository and the Ministry of Health's official COVID-19 website. The study period was from the beginning of the outbreak in Malaysia, which began during Epidemiological Week (Ep Wk) 4 in 2020, to the last Ep Wk 18 in 2022. Data were aggregated by Ep Wk and analyzed in terms of COVID-19 cases, deaths, ICU admissions, ventilator requirements, testing, incidence rate, death rate, case fatality rate (CFR) and test positivity rate by years (2020 and 2022) and for each outbreak of COVID-19.

Results

A total of 4,456,736 cases, 35,579 deaths and 58,906,954 COVID-19 tests were reported for the period from 2020 to 2022. The COVID-19 incidence rate, death rate, CFR and test positivity rate were reported at 1.085 and 0.009 per 1,000 populations, 0.80 and 7.57%, respectively, for the period from 2020 to 2022. Higher cases, deaths, testing, incidence/death rate, CFR and test positivity rates were reported in 2021 and during the Delta outbreak. This is evident by the highest number of COVID-19 cases, ICU admissions, ventilatory requirements and deaths observed during the Delta outbreak.

Conclusion

The Delta outbreak was the most severe compared to other outbreaks in Malaysia's study period. In addition, this study provides evidence that outbreaks of COVID-19, which are caused by highly virulent and transmissible variants, tend to be more severe and devastating if these outbreaks are not controlled early on. Therefore, close monitoring of key epidemiological indicators, as reported in this study, is essential in the control and management of future COVID-19 outbreaks in Malaysia.

Determinants of COVID-19 Infection Among Employees of an Italian Financial Institution

BACKGROUND

Understanding the trend of the severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) is becoming crucial. Previous studies focused on predicting COVID-19 trends, but few papers have considered models for disease estimation and progression based on large real-world data.

METHODS

We used de-identified data from 60,938 employees of a major financial institution in Italy with daily COVID-19 status information between 31 March 2020 and 31 August 2021. We consider six statuses: (i) concluded case, (ii) confirmed case, (iii) close contact, (iv) possible-probable contact, (v) possible contact, and (vi) no-COVID-19 or infection. We conducted a logistic regression to assess the odds ratio (OR) of transition to confirmed COVID-19 case at each time point. We also fitted a general model for disease progression via the multi-state transition probability model at each time point, with lags of 7 and 15 days.

RESULTS

Employment in a branch versus in a central office was the strongest predictor of case or contact status, while no association was detected with gender or age. The geographic prevalence of possible-probable contacts and close contacts was predictive of the subsequent risk of confirmed cases. The status with the highest probability of becoming a confirmed case was concluded case (12%) in April 2020, possible-probable contact (16%) in November 2020, and close contact (4%) in August 2021. The model based on transition probabilities predicted well the rate of confirmed cases observed 7 or 15 days later.

CONCLUSION

Data from industry-based surveillance systems may effectively predict the risk of subsequent infection.

A Low-Cost Early Warning Method for Infectious Diseases with Asymptomatic Carriers

At the beginning of 2023, the Italian former prime minister, the former health minister and 17 others including the current president of the Lombardy region were placed under investigation on suspicion of aggravated culpable epidemic in connection with the government's response at the start of the COVID-19 pandemic. The charges revolve around the failure by authorities to take adequate measures to prevent the spread of the virus in the Bergamo area, which experienced a significant excess of deaths during the initial outbreak. The aim of this paper is to analyse the pandemic data of Italy and the Lombardy region in the first 10 days of the pandemic, spanning from the 24th of February 2020 to the 4th of March 2020. The objective is to determine whether the use of early warning indicators could have facilitated the identification of a critical increase in infections. This identification, in turn, would have enabled the timely formulation of strategies for pandemic containment, thereby reducing the number of deaths. In conclusion, to translate our findings into practical guidelines, we propose a low-cost early warning method for infectious respiratory diseases with asymptomatic carriers.

Effectiveness of social distancing measures and lockdowns for reducing transmission of COVID-19 in non-healthcare, community-based settings

Social distancing measures (SDMs) are community-level interventions that aim to reduce person-to-person contacts in the community. SDMs were a major part of the responses first to contain, then to mitigate, the spread of SARS-CoV-2 in the community. Common SDMs included limiting the size of gatherings, closing schools and/or workplaces, implementing work-from-home arrangements, or more stringent restrictions such as lockdowns. This systematic review summarized the evidence for the effectiveness of nine SDMs. Almost all of the studies included were observational in nature, which meant that there were intrinsic risks of bias that could have been avoided were conditions randomly assigned to study participants. There were no instances where only one form of SDM had been in place in a particular setting during the study period, making it challenging to estimate the separate effect of each intervention. The more stringent SDMs such as stay-at-home orders, restrictions on mass gatherings and closures were estimated to be most effective at reducing SARS-CoV-2 transmission. Most studies included in this review suggested that combinations of SDMs successfully slowed or even stopped SARS-CoV-2 transmission in the community. However, individual effects and optimal combinations of interventions, as well as the optimal timing for particular measures, require further investigation. This article is part of the theme issue 'The effectiveness of non-pharmaceutical interventions on the COVID-19 pandemic: the evidence'.

Impact of the COVID-19 pandemic on paediatric renal tumour presentation and management, a SIOP renal tumour study group study

BACKGROUND

The COVID-19 pandemic had global catastrophic effects on the management of non-communicable diseases including paediatric cancers. Restrictions during the start of 2020 complicated timely referrals of patients to specialized centres. We aimed to evaluate the pandemic's impact on the number of new diagnoses, disease characteristics and management delay for paediatric renal tumour patients included in the SIOP-RTSG-UMBRELLA study, as compared with data from a historical SIOP-RTSG trial (2005-2009).

METHODS

The number of intensive care admissions, population mobility rates and national lockdown periods/restrictions were used as proxies of the pandemic's severity and impact on societies. Clinical and tumour data were extracted from the SIOP-RTSG-UMBRELLA study and from historical SIOP-RTSG trials.

RESULTS

During the first lockdown in Europe, the number of newly diagnosed patients decreased following restrictions and population immobilisation. Additionally, there was a higher proportion of advanced disease (37% vs. 17% before and after COVID-9, p < 0.001) and larger median tumour volume (559 cm3 vs. 328 and 434 cm3 before and after, p < 0.0001). Also in Brazil, the proportion of advanced disease was higher during the national decrease in mobilisation and start of restrictions (50% and 24% vs. 11% and 18% before and after, p < 0.01). Tumour volume in Brazil was also higher during the first months of COVID-19 (599 cm3 vs. 459 and 514 cm3 ), although not significant (p = 0.17). We did not observe any delays in referral time nor in time to start treatment, even though COVID-19 restrictions may have caused children to reach care later.

CONCLUSION

The COVID-19 pandemic briefly changed the tumour characteristics of children presenting with renal tumours. The longer-term impact on clinical outcomes will be kept under review.

Risk management and communication plans from SARS to COVID-19 and beyond

OBJECTIVE

Nowadays, due to globalisation, the likelihood that infectious diseases spread rapidly is extraordinarily high. SARS and COVID-19 are two diseases of the Coronavirus family, which developed in China and then spread internationally, causing global public health emergencies. This study investigates the role that risk management and communication systems played in mitigating these emergencies, to establish how they should be improved in the future.

METHODS

A narrative review was carried out to investigate different knowledge domains, such as risk management and communication, risk assessment and indicators, epidemiological and clinical data, diagnostic methods, vaccines, public health and social measures.

RESULTS

On one side, risk management systems assess the main data, knowledge, and indicators on epidemiology, diagnostics, and vaccines (science-based); on the other side, they apply public health and social measures (socially-based). Decision-makers, in fact, implement their actions by constantly balancing these two sides (policy-based).

CONCLUSIONS

A correct crisis management approach should support the governance of pandemics, by harmonising the actual risks assessed by experts with those perceived by the general population. It should incorporate not only the biological, but even the environmental, social and economic aspects of virus emergencies, towards establishing a suitable framework to deal with possible future pandemics.

Are preparedness indices reflective of pandemic preparedness? A COVID-19 reality check

The paper contributes to the body of knowledge working towards enhancing the understanding of crisis and disaster preparedness and effective response, via the lens of the ongoing global pandemic and responding to the questions: do the current measures for pandemic preparedness reflect preparedness adequately, and what does pandemic preparedness mean? We analysed how the reported cumulative mortality rates, during the spring of 2020 and in the 60 days after the date of a country's first COVID-19 related death, compared to the expected preparedness rank according to the existing global preparedness indices (IHR and GHSI) on a country level. We found, at country level, that the health-related outcomes from the first wave of the pandemic were primarily negatively correlated with the expected preparedness. We contend that our results indicate a need to investigate further development and enhancement of the preparedness indices.

Static Socio-Ecological COVID-19 Vulnerability Index and Vaccine Hesitancy Index for England

BACKGROUND

Population characteristics can be used to infer vulnerability of communities to COVID-19, or to the likelihood of high levels of vaccine hesitancy. Communities harder hit by the virus, or at risk of being so, stand to benefit from greater resource allocation than their population size alone would suggest. This study reports a simple but efficacious method of ranking small areas of England by relative characteristics that are linked with COVID-19 vulnerability and vaccine hesitancy.

METHODS

Publicly available data on a range of characteristics previously linked with either poor COVID-19 outcomes or vaccine hesitancy were collated for all Middle Super Output Areas of England (MSOA, n=6790, excluding Isles of Scilly), scaled and combined into two numeric indices. Multivariable linear regression was used to build a parsimonious model of vulnerability (static socio-ecological vulnerability index, SEVI) in 60% of MSOAs, and retained variables were used to construct two simple indices. Assuming a monotonic relationship between indices and outcomes, Spearman correlation coefficients were calculated between the SEVI and cumulative COVID-19 case rates at MSOA level in the remaining 40% of MSOAs over periods both during and out with national lockdowns. Similarly, a novel vaccine hesitancy index (VHI) was constructed using population characteristics aligned with factors identified by an Office for National Statistics (ONS) survey analysis. The relationship between the VHI and vaccine coverage in people aged 12+years (as of 2021-06-24) was determined using Spearman correlation. The indices were split into quintiles, and MSOAs within the highest vulnerability and vaccine hesitancy quintiles were mapped.

FINDINGS

The SEVI showed a moderate to strong relationship with case rates in the validation dataset across the whole study period, and for every intervening period studied except early in the pandemic when testing was highly selective. The SEVI was more strongly correlated with case rates than any of its domains (rs 0·59 95% CI 0.57-0.62) and outperformed an existing MSOA-level vulnerability index. The VHI was significantly negatively correlated with COVID-19 vaccine coverage in the validation data at the time of writing (rs -0·43 95% CI -0·46 to -0·41). London had the largest number and proportion of MSOAs in quintile 5 (most vulnerable/hesitant) of SEVI and VHI concurrently.

INTERPRETATION

The indices presented offer an efficacious way of identifying geographical disparities in COVID-19 risk, thus helping focus resources according to need.

FUNDING

Funder: Integrated Covid Hub North East.

AWARD NUMBER

n/a.

GRANT RECIPIENT

Fiona Matthews.

COVID-19 vaccination significantly reduces morbidity and absenteeism among healthcare personnel: A prospective multicenter study

AIM

Healthcare personnel (HCP) are prioritized for coronavirus disease 2019 (COVID-19) vaccination to protect them and non-disruptive provision of healthcare services. We assessed the impact of the Pfizer-BioNTech vaccine on morbidity and absenteeism among HCP.

METHODS

We studied 7445 HCP in five tertiary-care hospitals in Greece from November 15, 2020 through April 18, 2021.

RESULTS

A total of 910 episodes of absenteeism and 9695 days of absence were recorded during the entire study period. Starting from January 4, 2021, 4823/7445 HCP (64.8%) were fully or partially vaccinated. Overall, 535 episodes of absenteeism occurred from January 4, 2021 through April 18, 2021, including 309 (57.76%) episodes among 2622 unvaccinated HCP and 226 (42.24%) episodes among 4823 vaccinated HCP (11.8 versus 4.7 episodes of absenteeism per 100 HCP, respectively; p-value < 0.001). The mean duration of absenteeism was 11.9 days among unvaccinated HCP compared with 6.9 days among vaccinated HCP (p-value < 0.001). Unvaccinated HCP more frequently developed acute respiratory infection, influenza-like illness, and COVID-19 (p-values < 0.001 for all comparisons). Vaccine effectiveness for fully vaccinated HCP was estimated at 94.16% [confidence interval (CI): 88.50%-98.05%) against COVID-19, 83.62% (CI: 73.36%-90.38%) against SARS-CoV-2 infection (asymptomatic or COVID-19), and 66.42% (CI: 56.86%-74.15%) against absenteeism.

CONCLUSION

The COVID-19 pandemic had a considerable impact on healthcare workforce. The Pfizer-BioNTech vaccine significantly reduced morbidity, COVID-19, absenteeism and duration of absenteeism among HCP during a period of high SARS-CoV-2 circulation in the community. It is expected that HCP vaccination will protect them and healthcare services and contain healthcare costs.

Impact Evaluation of Coronavirus Disease 2019 Policy: A Guide to Common Design Issues

Policy responses to COVID-19, particularly those related to non-pharmaceutical interventions, are unprecedented in scale and scope. However, policy impact evaluations require a complex combination of circumstance, study design, data, statistics, and analysis. Beyond the issues that are faced for any policy, evaluation of COVID-19 policies is complicated by additional challenges related to infectious disease dynamics and a multiplicity of interventions. The methods needed for policy-level impact evaluation are not often used or taught in epidemiology, and differ in important ways that may not be obvious. Methodological complications of policy evaluations can make it difficult for decision-makers and researchers to synthesize and evaluate strength of evidence in COVID-19 health policy papers. We (1) introduce the basic suite of policy impact evaluation designs for observational data, including cross-sectional analyses, pre/post, interrupted time-series, and difference-in-differences analysis, (2) demonstrate key ways in which the requirements and assumptions underlying these designs are often violated in the context of COVID-19, and (3) provide decision-makers and reviewers a conceptual and graphical guide to identifying these key violations. The overall goal of this paper is to help epidemiologists, policy-makers, journal editors, journalists, researchers, and other research consumers understand and weigh the strengths and limitations of evidence.

Effectiveness of the movement control measures during the third wave of COVID-19 in Malaysia

OBJECTIVES

Starting in March 2020, movement control measures were instituted across several phases in Malaysia to break the chain of transmission of coronavirus disease 2019 (COVID-19). In this study, we developed a susceptible-exposed-infected-recovered (SEIR) model to examine the effects of the various phases of movement control measures on disease transmissibility and the trend of cases during the third wave of the COVID-19 pandemic in Malaysia.

METHODS

Three SEIR models were developed using the R programming software ODIN interface based on COVID-19 case data from September 1, 2020, to March 29, 2021. The models were validated and subsequently used to provide forecasts of daily cases from October 14, 2020, to March 29, 2021, based on 3 phases of movement control measures.

RESULTS

We found that the reproduction rate (R-value) of COVID-19 decreased by 59.1% from an initial high of 2.2 during the nationwide Recovery Movement Control Order (RMCO) to 0.9 during the Movement Control Order (MCO) and Conditional MCO (CMCO) phases. In addition, the observed cumulative and daily highest numbers of cases were much lower than the forecasted cumulative and daily highest numbers of cases (by 64.4-98.9% and 68.8-99.8%, respectively).

CONCLUSIONS

The movement control measures progressively reduced the R-value during the COVID-19 pandemic. In addition, more stringent movement control measures such as the MCO and CMCO were effective for further lowering the R-value and case numbers during the third wave of the COVID-19 pandemic in Malaysia due to their higher stringency than the nationwide RMCO.

The sooner the better: lives saved by the lockdown during the COVID-19 outbreak. The case of Italy

This paper estimates the effects of non-pharmaceutical interventions – mainly, the lockdown – on the COVID-19 mortality rate for the case of Italy, the first Western country to impose a national shelter-in-place order. We use a new estimator, the augmented synthetic control method (ASCM), that overcomes some limits of the standard synthetic control method (SCM). The results are twofold. From a methodological point of view, the ASCM outperforms the SCM in that the latter cannot select a valid donor set, assigning all the weights to only one country (Spain) while placing zero weights to all the remaining. From an empirical point of view, we find strong evidence of the effectiveness of non-pharmaceutical interventions in avoiding losses of human lives in Italy: conservative estimates indicate that the policy saved in total more than 21,000 human lives.

Early detection of COVID-19 outbreaks using human mobility data

BACKGROUND

Contact mixing plays a key role in the spread of COVID-19. Thus, mobility restrictions of varying degrees up to and including nationwide lockdowns have been implemented in over 200 countries. To appropriately target the timing, location, and severity of measures intended to encourage social distancing at a country level, it is essential to predict when and where outbreaks will occur, and how widespread they will be.

METHODS

We analyze aggregated, anonymized health data and cell phone mobility data from Israel. We develop predictive models for daily new cases and the test positivity rate over the next 7 days for different geographic regions in Israel. We evaluate model goodness of fit using root mean squared error (RMSE). We use these predictions in a five-tier categorization scheme to predict the severity of COVID-19 in each region over the next week. We measure magnitude accuracy (MA), the extent to which the correct severity tier is predicted.

RESULTS

Models using mobility data outperformed models that did not use mobility data, reducing RMSE by 17.3% when predicting new cases and by 10.2% when predicting the test positivity rate. The best set of predictors for new cases consisted of 1-day lag of past 7-day average new cases, along with a measure of internal movement within a region. The best set of predictors for the test positivity rate consisted of 3-days lag of past 7-day average test positivity rate, along with the same measure of internal movement. Using these predictors, RMSE was 4.812 cases per 100,000 people when predicting new cases and 0.79% when predicting the test positivity rate. MA in predicting new cases was 0.775, and accuracy of prediction to within one tier was 1.0. MA in predicting the test positivity rate was 0.820, and accuracy to within one tier was 0.998.

CONCLUSIONS

Using anonymized, macro-level data human mobility data along with health data aids predictions of when and where COVID-19 outbreaks are likely to occur. Our method provides a useful tool for government decision makers, particularly in the post-vaccination era, when focused interventions are needed to contain COVID-19 outbreaks while mitigating the collateral damage from more global restrictions.

A Quantitative Benefit-Risk Analysis of ChAdOx1 nCoV-19 Vaccine among People under 60 in Italy

The Oxford-AstraZeneca ChAdOx1 nCoV-19 is a vaccine against the COVID-19 infection that was granted a conditional marketing authorization by the European Commission in January 2021. However, following a report from the Pharmacovigilance Risk Assessment Committee (PRAC) of European Medicines Agency, which reported an association with thrombo-embolic events (TEE), in particular disseminated intravascular coagulation (DIC) and cerebral venous sinus thrombosis (CVST), many European countries either limited it to individuals older than 55–60 years or suspended its use. We used publicly available data to carry out a quantitative benefit–risk analysis of the vaccine among people under 60 in Italy. Specifically, we used data from PRAC, Eudravigilance and ECDC to estimate the excess number of deaths for TEE, DIC and CVST expected in vaccine users, stratified by age groups. We then used data from the National Institute of Health to calculate age-specific COVID-19 mortality rates in Italy. Preventable deaths were calculated assuming a 72% vaccine efficacy over an eight-month period. Finally, the benefit–risk ratio of ChAdOx1 nCoV-19 vaccination was calculated as the ratio of preventable COVID-19 deaths to vaccine-related deaths, using Monte-Carlo simulations. We found that among subjects aged 20–29 years the benefit–risk (B-R) ratio was not clearly favorable (0.70; 95% Uncertainty Interval (UI): 0.27–2.11). However, in the other age groups the benefits of vaccination largely exceeded the risks (for age 30–49, B-R ratio: 22.9: 95%UI: 10.1–186.4). For age 50–59, B-R ratio: 1577.1: 95%UI: 1176.9–2121.5). Although many countries have limited the use of the ChAdOx1 nCoV-19 vaccine, the benefits of using this vaccine clearly outweigh the risks in people older than 30 years. Study limitations included risk of underreporting and that we did not provide age-specific estimates. The use of this vaccine should be a strategic and fundamental part of the immunization campaign considering its safety and efficacy in preventing COVID-19 and its complications.

Professional Quality of Life, Engagement, and Self-Care in Healthcare Professionals in Ecuador during the COVID-19 Pandemic

The COVID-19 pandemic has highlighted the importance of healthcare workers and their professional quality of life. This quantitative cross-sectional study aims at exploring the professional quality of life, work engagement, and self-care of healthcare workers during the COVID-19 pandemic in Ecuador. A convenience sample of 117 participants completed an online voluntary and anonymous survey between April and July 2020. It contained a sociodemographic section, the Professional Quality of Life questionnaire V, the work engagement scale, and the scale of self-care behaviors for clinical psychologists. Results show that healthcare workers have an average quality of life with high levels of compassion satisfaction and average levels of compassion fatigue and burnout. Data also indicate that the sample frequently engaged in self-care practices and had high levels of work engagement. The regression analyses reveal that gender, the number of patients per week, the perceived fairness of the salary, among other variables are possible predictors of professional quality of life, frequency of self-care practices, and engagement. This study contributes to the understanding of these variables among healthcare professionals in Ecuador. These results should be considered when planning policies and prevention intervention efforts to promote professionals' wellbeing.

Medical students as the volunteer workforce during the COVID-19 pandemic: Polish experience

In response to the COVID-19 pandemic medical students in different countries were mobilized to support healthcare systems during the emergency. This study presents the experience of 580 students of a single medical university in Poland who served as volunteers at different healthcare units during the first six months of the first case being recorded in the country (March-September 2020). The mean ± SD hours and days spent on volunteering in the studied group were 52 ± 36 h and 144 ± 126 d, respectively, the collective number of worked hours amounted to 83,460 h. Compared to other fields of study students of medicine engaged in volunteering for more hours and for more days. The main tasks performed by the surveyed group included triage, servicing call-centers for patients and working at the admission ward, hospital clinics, emergency departments and diagnostic labs. The level of fear at the beginning of volunteering was relatively low in the studied group and did not increase over the course. The majority of students received positive feedback from families, friends, patients and healthcare workers, revealed a high level of satisfaction from volunteering (also when experiencing COVID-19-related prejudice), while gaining professional experience and a sense of giving real aid were among the most frequently indicated benefits. The results of the present study demonstrate that although medical students are not essential workers in response to the COVID-19 pandemic, they can be of real assistance to healthcare systems during times of emergency, and should be considered as such in the future in case such a need arises again.

COVID-19 Patient with Severe Comorbidity in Multimodal Acute Care Setting with Non-Invasive Medical Ventilation: A Clinical Outcome Report

The virus that causes COVID-19 is rapidly spreading across the globe. Elderly patients with multiple pre-existing conditions are at a higher risk. This case study describes acute inpatient treatment of a COVID-19 patient with uncontrolled diabetes mellitus, kidney complications, heart failure, chronic pain, depression, and other comorbidities in an isolation ward without mechanical ventilation.

Risk assessment and seroprevalence of SARS-CoV-2 infection in healthcare workers of COVID-19 and non-COVID-19 hospitals in Southern Switzerland

BACKGROUND

Hospital healthcare workers (HCW), in particular those involved in the clinical care of COVID-19 cases, are presumably exposed to a higher risk of acquiring the disease than the general population.

METHODS

Between April 16 and 30, 2020 we conducted a prospective, SARS-CoV-2 seroprevalence study in HCWs in Southern Switzerland. Participants were hospital personnel with varying COVID-19 exposure risk depending on job function and working site. They provided personal information (including age, sex, occupation, and medical history) and self-reported COVID-19 symptoms. Odds ratio (OR) of seropositivity to IgG antibodies was estimated by univariate and multivariate logistic regressions.

FINDINGS

Among 4726 participants, IgG antibodies to SARS-CoV-2 were detected in 9.6% of the HCWs. Seropositivity was higher among HCWs working on COVID-19 wards (14.1% (11.9-16.5)) compared to other hospital areas at medium (10.7% (7.6-14.6)) or low risk exposure (7.3% (6.4-8.3)). OR for high vs. medium wards risk exposure was 1.42 (0.91-2.22), P = 0.119, and 1.98 (1.55-2.53), P<0.001 for high vs. low wards risk exposure. The same was for true for doctors and nurses (10.1% (9.0-11.3)) compared to other employees at medium (7.1% (4.8-10.0)) or low risk exposure (6.6% (5.0-8.4)). OR for high vs. medium profession risk exposure was 1.37 (0.89-2.11), P = 0.149, and 1.75 (1.28-2.40), P = 0.001 for high vs. low profession risk exposure. Moreover, seropositivity was higher among HCWs who had household exposure to COVID-19 cases compared to those without (18.7% (15.3-22.5) vs. 7.7% (6.9-8.6), OR 2.80 (2.14-3.67), P<0.001).

INTERPRETATION

SARS-CoV-2 antibodies are detectable in up to 10% of HCWs from acute care hospitals in a region with high incidence of COVID-19 in the weeks preceding the study. HCWs with exposure to COVID-19 patients have only a slightly higher absolute risk of seropositivity compared to those without, suggesting that the use of PPE and other measures aiming at reducing nosocomial viral transmission are effective. Household contact with known COVID-19 cases represents the highest risk of seropositivity.

FUNDING

Henry Krenter Foundation, Ente Ospedaliero Cantonale and Vir Biotechnology.

Thyroid fine-needle aspiration trends before, during, and after the lockdown: what we have learned so far from the COVID-19 pandemic

PURPOSE

Nowadays, the clinical management of thyroid nodules needs to be multi-disciplinary. In particular, the crosstalk between endocrinologists and cytopathologists is key. When FNAs are properly requested by endocrinologists for nodules characterised by relevant clinical and ultrasound features, cytopathologists play a pivotal role in the diagnostic work-up. Conversely, improper FNA requests can lead to questionable diagnostic efficiency. Recently, recommendations to delay all non-urgent diagnostic procedures, such as thyroid FNAs, to contain the spread of COVID-19 infection, have made the interplay between endocrinologists and cytopathologists even more essential. The objective of this study was to assess the impact of COVID-19 pandemic on our practice by evaluating the total number of FNAs performed and the distribution of the Bethesda Categories before, during, and after the lockdown.

METHODS

We analysed the FNA trends before (1st January 2019 to March 13th 2020), during (March 14th to May 15th), and after (May 16th to July 7th) the lockdown.

RESULTS

Although the total number of weekly FNAs dropped from 62.1 to 23.1, our referring endocrinologists managed to prioritise patients with high-risk nodules. In fact, in the post-lockdown, the weekly proportion of benign diagnoses dropped on average by 12% and that of high-risk diagnoses increased by 6%.

CONCLUSIONS

The lesson we have learned so far from this pandemic is that by applying safety protocols to avoid contagion and by increasing the threshold for FNA requests for thyroid nodules, we can continue to guarantee our services to high-risk patients even in times of a health crisis.

Europe's War against COVID-19: A Map of Countries' Disease Vulnerability Using Mortality Indicators

Specific and older age-associated comorbidities increase mortality risk in severe forms of coronavirus disease (COVID-19). We matched COVID-19 comorbidities with causes of death in 28 EU countries for the total population and for the population above 65 years and applied a machine-learning-based tree clustering algorithm on shares of death for COVID-19 comorbidities and for influenza and on their growth rates between 2011 and 2016. We distributed EU countries in clusters and drew a map of the EU populations’ vulnerabilities to COVID-19 comorbidities and to influenza. Noncommunicable diseases had impressive shares of death in the EU but with substantial differences between eastern and western countries. The tree clustering algorithm accurately indicated the presence of western and eastern country clusters, with significantly different patterns of disease shares of death and growth rates. Western populations displayed higher vulnerability to malignancy, blood-related diseases, and diabetes mellitus and lower respiratory diseases, while eastern countries’ populations suffered more from ischaemic heart, cerebrovascular, and circulatory diseases. Dissimilarities between EU countries were also present when influenza was considered. The heat maps of EU populations’ vulnerability to diseases based on mortality indicators constitute the basis for more targeted health policy strategies in a collaborative effort at the EU level.

Mental Health in Frontline Medical Workers during the 2019 Novel Coronavirus Disease Epidemic in China: A Comparison with the General Population

BACKGROUND

Since December 2019, China has been affected by a severe outbreak of coronavirus disease 2019 (COVID-19). Frontline medical workers experienced difficulty due to the high risk of being infected and long and distressing work shifts. The current study aims to evaluate psychological symptoms in frontline medical workers during the COVID-19 epidemic in China and to perform a comparison with the general population.

METHODS

An online survey was conducted from 14 February 2020 to 29 March 2020. A total of 899 frontline medical workers and 1104 respondents in the general population participated. Depression, anxiety, insomnia, and resilience were assessed via the Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder Scale (GAD-7), Insomnia Severity Index (ISI), and abbreviated Connor-Davidson Resilience Scale (CD-RISC-10), respectively.

RESULTS

Overall, 30.43%, 20.29%, and 14.49% of frontline medical workers in Hubei Province and 23.13%, 13.14%, and 10.64% of frontline medical workers in other regions reported symptoms of depression, anxiety, and insomnia, respectively. In addition, 23.33%, 16.67%, and 6.67% of the general population in Hubei Province and 18.25%, 9.22%, and 7.17% of the general population in other regions reported symptoms of depression, anxiety, and insomnia, respectively. The resilience of frontline medical staff outside Hubei Province was higher than that of the general population outside Hubei Province.

CONCLUSION

A large proportion of frontline medical workers and the general public experienced psychological symptoms during the COVID-19 outbreak. Psychological services for frontline medical workers and the general public are needed.