Infection fatality rate of SARS-CoV2 in a super-spreading event in Germany

Continuous population-level monitoring of SARS-CoV-2 seroprevalence in a large European metropolitan region

Effective public health measures against SARS-CoV-2 require granular knowledge of population-level immune responses. We developed a Tripartite Automated Blood Immunoassay (TRABI) to assess the IgG response against three SARS-CoV-2 proteins. We used TRABI for continuous seromonitoring of hospital patients and blood donors (n = 72'250) in the canton of Zurich from December 2019 to December 2020 (pre-vaccine period). We found that antibodies waned with a half-life of 75 days, whereas the cumulative incidence rose from 2.3% in June 2020 to 12.2% in mid-December 2020. A follow-up health survey indicated that about 10% of patients infected with wildtype SARS-CoV-2 sustained some symptoms at least twelve months post COVID-19. Crucially, we found no evidence of a difference in long-term complications between those whose infection was symptomatic and those with asymptomatic acute infection. The cohort of asymptomatic SARS-CoV-2-infected subjects represents a resource for the study of chronic and possibly unexpected sequelae.

Prevalence and determinants of SARS-CoV-2 neutralizing antibodies in Lebanon

According to the Lebanese Ministry of Public Health, more than 1,053,000 cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been confirmed in Lebanon so far. The actual number of cases is likely to be higher. We conducted a serological study from October 2020 to April 2021 to estimate the prevalence of SARS-CoV-2 neutralizing antibodies and identify associated factors. Serum samples as well as demographic, health, and behavioral data were collected from 2,783 subjects. Sera were tested by microneutralization assay. Neutralizing antibodies were detected in 58.9% of the study population. The positivity rate increased over the study period. It was highest among the group who remained at work during the COVID-19 pandemic and in peri-urban areas with limited adherence to preventive measures. Sex and age were associated with positivity. Reported previous COVID-19, exposure to a COVID-19 patient in the family, and attending gatherings were associated with increased prevalence. Not taking any precautionary measures against COVID-19 was a risk factor, whereas precautionary measures such as working from home and washing hands were protective. The high neutralizing antibody seroprevalence rates detected in this study emphasize the high transmission rate of SARS-CoV-2 infection in the community. Adherence to preventive measures and non-pharmaceutical interventions imposed by the government is recommended.

Spatial Risk Factors for Pillar 1 COVID-19 Excess Cases and Mortality in Rural Eastern England, UK

Understanding is still developing about spatial risk factors for COVID-19 infection or mortality. This is a secondary analysis of patient records in a confined area of eastern England, covering persons who tested positive for SARS-CoV-2 through end May 2020, including dates of death and residence area. We obtained residence area data on air quality, deprivation levels, care home bed capacity, age distribution, rurality, access to employment centers, and population density. We considered these covariates as risk factors for excess cases and excess deaths in the 28 days after confirmation of positive Covid status relative to the overall case load and death recorded for the study area as a whole. We used the conditional autoregressive Besag-York-Mollie model to investigate the spatial dependency of cases and deaths allowing for a Poisson error structure. Structural equation models were applied to clarify relationships between predictors and outcomes. Excess case counts or excess deaths were both predicted by the percentage of population age 65 years, care home bed capacity and less rurality: older population and more urban areas saw excess cases. Greater deprivation did not correlate with excess case counts but was significantly linked to higher mortality rates after infection. Neither excess cases nor excess deaths were predicted by population density, travel time to local employment centers, or air quality indicators. Only 66% of mortality was explained by locally high case counts. Higher deprivation clearly linked to higher COVID-19 mortality separate from wider community prevalence and other spatial risk factors.

SARS-CoV-2 in Environmental Samples of Quarantined Households

The role of environmental transmission of SARS-CoV-2 remains unclear. Thus, the aim of this study was to investigate whether viral contamination of air, wastewater, and surfaces in quarantined households result in a higher risk for exposed persons. For this study, a source population of 21 households under quarantine conditions with at least one person who tested positive for SARS-CoV-2 RNA were randomly selected from a community in North Rhine-Westphalia in March 2020. All individuals living in these households participated in this study and provided throat swabs for analysis. Air and wastewater samples and surface swabs were obtained from each household and analysed using qRT-PCR. Positive swabs were further cultured to analyse for viral infectivity. Out of all the 43 tested adults, 26 (60.47%) tested positive using qRT-PCR. All 15 air samples were qRT-PCR-negative. In total, 10 out of 66 wastewater samples were positive for SARS-CoV-2 (15.15%) and 4 out of 119 surface samples (3.36%). No statistically significant correlation between qRT-PCR-positive environmental samples and the extent of the spread of infection between household members was observed. No infectious virus could be propagated under cell culture conditions. Taken together, our study demonstrates a low likelihood of transmission via surfaces. However, to definitively assess the importance of hygienic behavioural measures in the reduction of SARS-CoV-2 transmission, larger studies should be designed to determine the proportionate contribution of smear vs. droplet transmission.

The clinical and economic value of a successful shutdown during the SARS-CoV-2 pandemic in Germany

BACKGROUND AND AIM

A shutdown of businesses enacted during the SARS-CoV-2 pandemic can serve different goals, e.g., preventing the intensive care unit (ICU) capacity from being overwhelmed ('flattening the curve') or keeping the reproduction number substantially below one ('squashing the curve'). The aim of this study was to determine the clinical and economic value of a shutdown that is successful in 'flattening' or 'squashing the curve' in Germany.

METHODS

In the base case, the study compared a successful shutdown to a worst-case scenario with no ICU capacity left to treat COVID-19 patients. To this end, a decision model was developed using, e.g., information on age-specific fatality rates, ICU outcomes, and the herd protection threshold. The value of an additional life year was borrowed from new, innovative oncological drugs, as cancer reflects a condition with a similar morbidity and mortality burden in the general population in the short term as COVID-19.

RESULTS

A shutdown that is successful in 'flattening the curve' is projected to yield an average health gain between 0.01 and 0.05 life years (0.1 to 0.6 months) per capita in the German population. The corresponding economic value ranges between €616 and €4797 per capita or, extrapolated to the total population, 1%-12% of the gross domestic product (GDP) in 2019. A shutdown that is successful in 'squashing the curve' is expected to yield a minimum health gain of 0.08 life years (1 month) per capita, corresponding to 19 % of the GDP in 2019. Results are particularly sensitive to mortality data and the prevalence of undetected cases.

CONCLUSION

A successful shutdown is forecasted to yield a considerable gain in life years in the German population. Nevertheless, questions around the affordability and underfunding of other parts of the healthcare system emerge.

Was Alpha deadlier than wild-type COVID? Analysis in rural England

Background

It is useful to document whether each newly dominant SARS-CoV-2 variant of concern was more or less dangerous than preceding dominant variant(s). We assessed if the emergence of the Alpha (B.1.1.7) variant in autumn 2020 could be linked to higher case fatality rates, compared to original wild-type COVID-19, subgrouping by age band, sex, deprivation or month of diagnosis as potential risk factors.

Methods

Observational study and secondary analysis were conducted of SARS-CoV-2 cases diagnosed due to medical need or occupational exposure in an administrative area of Eastern England, UK (base population 1 million), who first tested positive in the period 1 March 2020 to 28 February 2021. Multivariate logistic regression was performed to examine relationships of age group, sex, deprivation group and month of diagnosis with case fatality rates within 28 days of diagnosis. Marginal probabilities for risk of dying were calculated separately for the first two main ‘wave’ periods of the English pandemic.

Results

Older age and male sex consistently raised the risk of mortality in both wave periods. Higher deprivation was linked to mortality risk in the first wave period, but not in the second wave. Mortality decreased over time during the first wave period, but slightly increased over time during the second wave. Cases were younger in the second wave, and median age of the deceased varied little between waves.

Interpretation

The Alpha variant of SARS-CoV-2 did not lead to higher mortality rates for any age, deprivation or sex group, compared to case fatality rates in the early part of the pandemic period.

Supplementary Information

The online version contains supplementary material available at 10.1007/s15010-022-01787-x.

Spatiotemporal modeling of first and second wave outbreak dynamics of COVID-19 in Germany

The COVID-19 pandemic has kept the world in suspense for the past year. In most federal countries such as Germany, locally varying conditions demand for state- or county-level decisions to adapt to the disease dynamics. However, this requires a deep understanding of the mesoscale outbreak dynamics between microscale agent models and macroscale global models. Here, we use a reparameterized SIQRD network model that accounts for local political decisions to predict the spatiotemporal evolution of the pandemic in Germany at county resolution. Our optimized model reproduces state-wise cumulative infections and deaths as reported by the Robert Koch Institute and predicts the development for individual counties at convincing accuracy during both waves in spring and fall of 2020. We demonstrate the dominating effect of local infection seeds and identify effective measures to attenuate the rapid spread. Our model has great potential to support decision makers on a state and community politics level to individually strategize their best way forward during the months to come.

Die Erforschung der Dynamik der Corona-Pandemie in Deutschland: Survey-Konzepte und eine exemplarische Umsetzung mit dem Sozio-oekonomischen Panel (SOEP)

Die Weltgesundheitsorganisation (WHO) hat im Frühjahr 2020 Richtlinien für Bevölkerungsstichproben veröffentlicht, die Basisdaten für gesundheitspolitische Entscheidungen im Pandemiefall liefern können. Diese Richtlinien umzusetzen ist keineswegs trivial. In diesem Beitrag schildern wir die Herausforderungen einer entsprechenden statistischen Erfassung der Corona Pandemie. Hierbei gehen wir im ersten Teil auf die Erfassung der Dunkelziffer bei der Meldung von Corona Infektionen, die Messung von Krankheitsverläufen im außerklinischen Bereich, die Messung von Risikomerkmalen sowie die Erfassung von zeitlichen und regionalen Veränderungen der Pandemie-Intensität ein. Wir diskutieren verschiedene Möglichkeiten, aber auch praktische Grenzen der Survey-Statistik, den vielfältigen Herausforderungen durch eine geeignete Anlage der Stichprobe und des Survey-Designs zu begegnen. Ein zentraler Punkt ist die schwierige Koppelung medizinischer Tests mit bevölkerungsrepräsentativen Umfragen, wobei bei einer personalisierten Rückmeldung der Testergebnisse das Statistik-Geheimnis eine besondere Herausforderung darstellt.

Im zweiten Teil berichten wir wie eine der großen Wiederholungsbefragungen in Deutschland, das Sozio-oekonomische Panel (SOEP), für eine WHO-konforme Covid-19-Erhebung genutzt wird, die im Rahmen einer Kooperation des Robert-Koch-Instituts (RKI) mit dem SOEP als „RKI-SOEP Stichprobe“ im September 2020 gestartet wurde. Erste Ergebnisse zum Rücklauf dieser Studie, die ab Oktober 2021 mit einer zweiten Erhebungswelle bei denselben Personen fortgesetzt werden wird, werden vorgestellt. Es zeigt sich, dass knapp fünf Prozent der bereits in der Vergangenheit erfolgreich Befragten aufgrund der Anfrage zwei Tests zu machen die weitere Teilnahme an der SOEP-Studie verweigern. Berücksichtigt man alle in der Studie erhobenen Informationen (IgG-Antikörper-Tests, PCR-Tests und Fragebögen) ergibt eine erste Schätzung, dass sich bis November 2020 nur etwa zwei Prozent der in Privathaushalten lebenden Erwachsenen in Deutschland mit SARS-CoV‑2 infiziert hatten. Damit war die Zahl der Infektionen etwa doppelt so hoch wie die offiziell gemeldeten Infektionszahlen.

Inferring the effect of interventions on COVID-19 transmission networks

Countries around the world implement nonpharmaceutical interventions (NPIs) to mitigate the spread of COVID-19. Design of efficient NPIs requires identification of the structure of the disease transmission network. We here identify the key parameters of the COVID-19 transmission network for time periods before, during, and after the application of strict NPIs for the first wave of COVID-19 infections in Germany combining Bayesian parameter inference with an agent-based epidemiological model. We assume a Watts–Strogatz small-world network which allows to distinguish contacts within clustered cliques and unclustered, random contacts in the population, which have been shown to be crucial in sustaining the epidemic. In contrast to other works, which use coarse-grained network structures from anonymized data, like cell phone data, we consider the contacts of individual agents explicitly. We show that NPIs drastically reduced random contacts in the transmission network, increased network clustering, and resulted in a previously unappreciated transition from an exponential to a constant regime of new cases. In this regime, the disease spreads like a wave with a finite wave speed that depends on the number of contacts in a nonlinear fashion, which we can predict by mean field theory.

Predicting the effects of COVID-19 related interventions in urban settings by combining activity-based modelling, agent-based simulation, and mobile phone data

Epidemiological simulations as a method are used to better understand and predict the spreading of infectious diseases, for example of COVID-19. This paper presents an approach that combines a well-established approach from transportation modelling that uses person-centric data-driven human mobility modelling with a mechanistic infection model and a person-centric disease progression model. The model includes the consequences of different room sizes, air exchange rates, disease import, changed activity participation rates over time (coming from mobility data), masks, indoors vs. outdoors leisure activities, and of contact tracing. It is validated against the infection dynamics in Berlin (Germany). The model can be used to understand the contributions of different activity types to the infection dynamics over time. It predicts the effects of contact reductions, school closures/vacations, masks, or the effect of moving leisure activities from outdoors to indoors in fall, and is thus able to quantitatively predict the consequences of interventions. It is shown that these effects are best given as additive changes of the reproduction number R. The model also explains why contact reductions have decreasing marginal returns, i.e. the first 50% of contact reductions have considerably more effect than the second 50%. Our work shows that is is possible to build detailed epidemiological simulations from microscopic mobility models relatively quickly. They can be used to investigate mechanical aspects of the dynamics, such as the transmission from political decisions via human behavior to infections, consequences of different lockdown measures, or consequences of wearing masks in certain situations. The results can be used to inform political decisions.

Resuming professional football (soccer) during the COVID-19 pandemic in a country with high infection rates: a prospective cohort study

OBJECTIVES

The risk of viral transmission associated with contact sports such as football (soccer) during the COVID-19 pandemic is unknown. The aim of this study was to describe the infective and immune status of professional football players, team staff and league officials over a truncated football season resumed at the height of the COVID-19 pandemic in a country with high infection rates and to investigate the clinical symptoms related to COVID-19 infection in professional football players.

METHODS

Prospective cohort study of 1337 football players, staff and officials during a truncated football season (9 weeks) with a tailored infection control programme based on preventive measures and regular SARS-CoV-2 PCR swab testing (every 3-5 days) combined with serology testing for immunity (every 4 weeks). Clinical symptoms in positive participants were recorded using a 26-item, Likert-Scale-based scoring system.

RESULTS

During the study period, 85 subjects returned positive (cycle threshold (cT) ≤30) or reactive (30

CONCLUSION

Football played outdoors involving close contact between athletes represents a limited risk for SARS-CoV-2 infection and severe illness when preventive measures are in place.

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Key Words

• football
• illness
• respiratory
• soccer
• virus

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MESH Headings

• Adult
• COVID-19/diagnosis
• COVID-19/immunology
• COVID-19/prevention & control
• COVID-19/transmission
• COVID-19 Testing
• Carrier State
• Communicable Disease Control
• Family Health
• Humans
• Pandemics
• Prospective Studies
• Qatar/epidemiology
• SARS-CoV-2/isolation & purification
• Soccer/statistics & numerical data
• Social Interaction

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Grants Collapse

Affiliation(s)

Yorck Olaf Schumacher Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar
Montassar Tabben Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar
Khalid Hassoun Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar
Asmaa Al Marwani Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar
Ibrahim Al Hussein Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar
Peter Coyle Hamad Medical Corporation, Doha, Qatar
Ahmed Khellil Abbassi Qatar Stars League, Doha, Qatar
Hani Taleb Ballan Qatar Stars League, Doha, Qatar
Abdulaziz Al-Kuwari Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar
Karim Chamari Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar
Roald Bahr Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar

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The Epistemology of a Positive SARS-CoV-2 Test

We investigate the epistemological consequences of a positive polymerase chain reaction SARS-CoV test for two relevant hypotheses: (i) V is the hypothesis that an individual has been infected with SARS-CoV-2; (ii) C is the hypothesis that SARS-CoV-2 is the cause of flu-like symptoms in a given patient. We ask two fundamental epistemological questions regarding each hypothesis: First, how much confirmation does a positive test lend to each hypothesis? Second, how much evidence does a positive test provide for each hypothesis against its negation? We respond to each question within a formal Bayesian framework. We construe degree of confirmation as the difference between the posterior probability of the hypothesis and its prior, and the strength of evidence for a hypothesis against its alternative in terms of their likelihood ratio. We find that test specificity-and coinfection probabilities when making inferences about C-were key determinants of confirmation and evidence. Tests with < 87% specificity could not provide strong evidence (likelihood ratio > 8) for V against ¬V regardless of sensitivity. Accordingly, low specificity tests could not provide strong evidence in favor of C in all plausible scenarios modeled. We also show how a positive influenza A test disconfirms C and provides weak evidence against C in dependence on the probability that the patient is influenza A infected given that his/her symptoms are not caused by SARS-CoV-2. Our analysis points out some caveats that should be considered when attributing symptoms or death of a positively tested patient to SARS-CoV-2.

The impact of digital contact tracing on the SARS-CoV-2 pandemic-a comprehensive modelling study

Contact tracing is one of several strategies employed in many countries to curb the spread of SARS-CoV-2. Digital contact tracing (DCT) uses tools such as cell-phone applications to improve tracing speed and reach. We model the impact of DCT on the spread of the virus for a large epidemiological parameter space consistent with current literature on SARS-CoV-2. We also model DCT in combination with random testing (RT) and social distancing (SD). Modelling is done with two independently developed individual-based (stochastic) models that use the Monte Carlo technique, benchmarked against each other and against two types of deterministic models. For current best estimates of the number of asymptomatic SARS-CoV-2 carriers (approximately 40%), their contagiousness (similar to that of symptomatic carriers), the reproductive number before interventions ( R 0 at least 3) we find that DCT must be combined with other interventions such as SD and/or RT to push the reproductive number below one. At least 60% of the population would have to use the DCT system for its effect to become significant. On its own, DCT cannot bring the reproductive number below 1 unless nearly the entire population uses the DCT system and follows quarantining and testing protocols strictly. For lower uptake of the DCT system, DCT still reduces the number of people that become infected. When DCT is deployed in a population with an ongoing outbreak where O (0.1%) of the population have already been infected, the gains of the DCT intervention come at the cost of requiring up to 15% of the population to be quarantined (in response to being traced) on average each day for the duration of the epidemic, even when there is sufficient testing capability to test every traced person.

Assessment of SARS-CoV-2 Infection among Healthcare Workers of a German COVID-19 Treatment Center

To date, more than 160 million people have been infected with COVID-19 worldwide. In the present study, we investigated the history of SARS-CoV-2 infection among 3067 healthcare workers (HCW) in a German COVID-19 treatment center during the early phase of the pandemic (July 2020) based on the seroprevalence of SARS-CoV-2 antibodies and self-reported previous PCR results. The results demonstrate a low prevalence of SARS-CoV-2 infection (n = 107 [3.5%]) with no increased risk for employees with a high level of patient exposure in general or working in COVID-19-confined areas in particular. This suggests that the local hygiene standards implemented in our hospital during the first wave of COVID-19 pandemic were effective in preventing patient-to-HCW transmission. No evidence for highly mobile staff serving as a vector for SARS-CoV-2 transmission could be found. In addition, impairment of smell and/or taste was strongly associated with SARS-CoV-2 history.

SARS-CoV-2 transmission in schools: An updated living systematic review (version 2; November 2020)

BACKGROUND

Better understanding of SARS-CoV-2 transmission risks is needed to support decision-making around mitigation measures for COVID-19 in schools.

METHODS

We updated a living systematic review and meta-analysis to investigate the extent of SARS-CoV-2 transmission in schools. In this update we modified our inclusion criteria to include: 1) cohort studies; 2) cross-sectional studies that investigated and cross-assessed SARS-COV-2 positivity rates in schools and communities; and 3) pre-post studies. We performed risk of bias evaluation for all included studies using the Newcastle-Ottawa Scale (NOS).

RESULTS

6270 articles were retrieved and six new studies were added in this update. In total from the two updates and using the new inclusion criteria, we identified 11 cohort studies (1st update: n = 5; 2nd update: n = 6) and one cross-sectional study (1st update: n = 1; 2nd update: n = 0). We performed a meta-analysis on nine of the 11 cohort studies investigating IAR in schools. Nine cohort studies reported a total of 91 student and 52 staff index cases that exposed 5698 contacts with 101 secondary infections (overall infection attack rate (IAR) = 1.45%, 95% CI = 0.31%-3.26%). IARs for students and school staff were 1.66% (95% CI = 0.08%-4.78%) and 1.18% (95% CI = 0.00%-4.43%) respectively. The risk of bias was found to be high for most studies identified, limiting the confidence in results.

CONCLUSIONS

There is limited high-quality evidence available to quantify the extent of SARS-CoV-2 transmission in schools or to compare it to community transmission. Emerging evidence suggests the overall IAR and SARS-CoV-2 positivity rate in school settings are low. Higher IAR were found in students, compared to staff.

NOTE

This article is a living systematic review that will be updated to reflect emerging evidence. This is the second version of the original article published on 23 December 2020 (J Glob Health 2020;11:021104), and previous versions can be found as data supplements. When citing this paper please consider adding the version number and date of access for clarity.

AIDS and COVID: A tale of two pandemics and the role of statisticians

The world has experienced three global pandemics over the last half-century: HIV/AIDS, H1N1, and COVID-19. HIV/AIDS and COVID-19 are still with us and have wrought extensive havoc worldwide. There are many differences between these two infections and their global impacts, but one thing they have in common is the mobilization of scientific resources to both understand the infection and develop ways to combat it. As was the case with HIV, statisticians have been in the forefront of scientists working to understand transmission dynamics and the natural history of infection, determine prognostic factors for severe disease, and develop optimal study designs to assess therapeutics and vaccines.

Health Sufficiency Indicators for Pandemic Monitoring

The outbreak of the COVID-19 disease, spreading all around the world and causing a worldwide pandemic, has lead to the collapse of the health systems of the most affected countries. Due to the ease of transmission, early prevention measures are proved to be fundamental to control the pandemic and, hence, the saturation of the health systems. Given the difficulty of obtaining characteristics of these systems of different countries and regions, it is necessary to define indicators based on basic information that enable the assessment of the evolution of the impact of a disease in a health system along with fair comparisons among different ones. This present paper introduces the Health Sufficiency Indicator (HSI), in its accumulated and daily versions. This indicator measures the additional pressure that a health care system has to deal with due to a pandemic. Hence, it allows to evaluate the capacity of a health system to give response to the corresponding needs arising from a pandemic and to compare the evolution of the disease among different regions. In addition, the Potential Occupancy Ratio (POR) in both its hospital ward bed and ICU bed versions is here introduced to asses the impact of the pandemic in the capacity of hospitals. These indicators and other well-known ones are applied to track the evolution of the impact of the disease on the Spanish health system during the first wave of the pandemic, both on national and regional levels. An international comparison among the most affected countries is also performed.

Estimating COVID-19 mortality in Italy early in the COVID-19 pandemic

Estimating rates of COVID-19 infection and associated mortality is challenging due to uncertainties in case ascertainment. We perform a counterfactual time series analysis on overall mortality data from towns in Italy, comparing the population mortality in 2020 with previous years, to estimate mortality from COVID-19. We find that the number of COVID-19 deaths in Italy in 2020 until September 9 was 59,000–62,000, compared to the official number of 36,000. The proportion of the population that died was 0.29% in the most affected region, Lombardia, and 0.57% in the most affected province, Bergamo. Combining reported test positive rates from Italy with estimates of infection fatality rates from the Diamond Princess cruise ship, we estimate the infection rate as 29% (95% confidence interval 15–52%) in Lombardy, and 72% (95% confidence interval 36–100%) in Bergamo.

Estimates of COVID-19-related mortality are limited by incomplete testing. Here, the authors perform counterfactual analyses and estimate that there were 59,000–62,000 deaths from COVID-19 in Italy until 9^th September 2020, approximately 1.5 times higher than official statistics.

Surgical site infections: guidance for elective surgery during the SARS-CoV-2 pandemic - international recommendations and clinical experience

BACKGROUND

The COVID-19 pandemic not only had an impact on public life and healthcare facilities in general, but also affected established surgical workflows for elective procedures. The strategy to protect patients and healthcare workers from infection by SARS-CoV-2 in surgical departments has needed step-by-step development. Based on the evaluation of international recommendations and guidelines, as well as personal experiences in a clinical 'hot spot' and in a 450-bed surgical clinic, an adapted surgical site infection (SSI) prevention checklist was needed to develop concise instructions, which described roles and responsibilities of healthcare professionals that could be used for wider guidance in pandemic conditions.

METHOD

Publications of COVID-19-related recommendations and guidelines, produced by health authorities and organizations, such as WHO, US-CDC, ECDC, the American College of Surgery and the Robert Koch Institute, were retrieved, assessed and referenced up to 31st January 2020. Additionally, clinical personal experiences in Germany were evaluated and considered.

RESULTS

Part 1 of this guidance summarizes the experience of a tertiary care, surgical centre which utilized redundant hospital buildings for immediate spatial separation in a 'hot spot' COVID-19 area. Part 2 outlines the successful screening and isolation strategy in a surgical clinic in a region of Germany with outbreaks in surrounding medical centres. Part 3 provides the synopsis of personal experiences and international recommendations suggested for implementation during the COVID-19 pandemic.

CONCLUSION

Understanding of COVID-19, and SARS-CoV-2-related epidemiology, is constantly and rapidly changing, requiring continuous adaptation and re-evaluation of recommendations. Established national and local guidelines for continuation of surgical services and prevention of SSI require ongoing scrutiny and focused implementation. This manuscript presents a core facility checklist to support medical institutions to continue their clinical and surgical work during the COVID-19 pandemic.

Sensitivity of anti-SARS-CoV-2 serological assays in a high-prevalence setting

Evaluation and power of seroprevalence studies depend on the performed serological assays. The aim of this study was to assess four commercial serological tests from EUROIMMUN, DiaSorin, Abbott, and Roche as well as an in-house immunofluorescence and neutralization test for their capability to identify SARS-CoV-2 seropositive individuals in a high-prevalence setting. Therefore, 42 social and working contacts of a German super-spreader were tested. Consistent with a high-prevalence setting, 26 of 42 were SARS-CoV-2 seropositive by neutralization test (NT), and immunofluorescence test (IFT) confirmed 23 of these 26 positive test results (NT 61.9% and IFT 54.8% seroprevalence). Four commercial assays detected anti-SARS-CoV-2 antibodies in 33.3-40.5% individuals. Besides an overall discrepancy between the NT and the commercial assays regarding their sensitivity, this study revealed that commercial SARS-CoV-2 spike-based assays are better to predict the neutralization titer than nucleoprotein-based assays are.

Is a Mask That Covers the Mouth and Nose Free from Undesirable Side Effects in Everyday Use and Free of Potential Hazards?

Many countries introduced the requirement to wear masks in public spaces for containing SARS-CoV-2 making it commonplace in 2020. Up until now, there has been no comprehensive investigation as to the adverse health effects masks can cause. The aim was to find, test, evaluate and compile scientifically proven related side effects of wearing masks. For a quantitative evaluation, 44 mostly experimental studies were referenced, and for a substantive evaluation, 65 publications were found. The literature revealed relevant adverse effects of masks in numerous disciplines. In this paper, we refer to the psychological and physical deterioration as well as multiple symptoms described because of their consistent, recurrent and uniform presentation from different disciplines as a Mask-Induced Exhaustion Syndrome (MIES). We objectified evaluation evidenced changes in respiratory physiology of mask wearers with significant correlation of O2 drop and fatigue (p < 0.05), a clustered co-occurrence of respiratory impairment and O2 drop (67%), N95 mask and CO2 rise (82%), N95 mask and O2 drop (72%), N95 mask and headache (60%), respiratory impairment and temperature rise (88%), but also temperature rise and moisture (100%) under the masks. Extended mask-wearing by the general population could lead to relevant effects and consequences in many medical fields.

SARS-CoV-2 Seroprevalence among Health Care Workers-A Voluntary Screening Study in a Regional Medical Center in Southern Germany

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is associated with a potentially severe clinical manifestation, coronavirus disease 2019 (COVID-19), and currently poses a worldwide challenge. Health care workers (HCWs) are at the forefront of any health care system and thus especially at risk for SARS-CoV-2 infection due to their potentially frequent and close contact with patients suffering from COVID-19. Serum samples from 198 HCWs with direct patient contact of a regional medical center and several outpatient facilities were collected during the early phase of the pandemic (April 2020) and tested for SARS-CoV-2-specific antibodies. Commercially available IgA- and IgG-specific ELISAs were used as screening technique, followed by an in-house neutralization assay for confirmation. Neutralizing SARS-CoV-2-specific antibodies were detected in seven of 198 (3.5%) tested HCWs. There was no significant difference in seroprevalence between the regional medical center (3.4%) and the outpatient institution (5%). The overall seroprevalence of neutralizing SARS-CoV-2-specific antibodies in HCWs in both a large regional medical center and a small outpatient institution was low (3.5%) at the beginning of April 2020. The findings may indicate that the timely implemented preventive measures (strict hygiene protocols, personal protective equipment) were effective to protect from transmission of an airborne virus when only limited information on the pathogen was available.

Epidemiology of SARS-CoV-2

PURPOSE

SARS-CoV-2 is a recently emerged ß-coronavirus. Here we present the current knowledge on its epidemiologic features.

METHODS

Non-systematic review.

RESULTS

SARS-CoV-2 replicates in the upper and lower respiratory tract. It is mainly transmitted by droplets and aerosols from asymptomatic and symptomatic infected subjects. The consensus estimate for the basis reproduction number (R0) is between 2 and 3, and the median incubation period is 5.7 (range 2-14) days. Similar to SARS and MERS, superspreading events have been reported, the dispersion parameter (kappa) is estimated at 0.1. Most infections are uncomplicated, and 5-10% of patients are hospitalized, mainly due to pneumonia with severe inflammation. Complications are respiratory and multiorgan failure; risk factors for complicated disease are higher age, hypertension, diabetes, chronic cardiovascular, chronic pulmonary disease and immunodeficiency. Nosocomial and infections in medical personnel have been reported. Drastic reductions of social contacts have been implemented in many countries with outbreaks of SARS-CoV-2, leading to rapid reductions. Most interventions have used bundles, but which of the measures have been more or less effective is still unknown. The current estimate for the infection's fatality rate is 0.5-1%. Using current models of age-dependent infection fatality rates, upper and lower limits for the attack rate in Germany can be estimated between 0.4 and 1.6%, lower than in most European countries.

CONCLUSIONS

Despite a rapid worldwide spread, attack rates have been low in most regions, demonstrating the efficacy of control measures.

Efficacy of face coverings in reducing transmission of COVID-19: Calculations based on models of droplet capture

In the COVID-19 pandemic, among the more controversial issues is the use of masks and face coverings. Much of the concern boils down to the question-just how effective are face coverings? One means to address this question is to review our understanding of the physical mechanisms by which masks and coverings operate-steric interception, inertial impaction, diffusion, and electrostatic capture. We enquire as to what extent these can be used to predict the efficacy of coverings. We combine the predictions of the models of these mechanisms which exist in the filtration literature and compare the predictions with recent experiments and lattice Boltzmann simulations, and find reasonable agreement with the former and good agreement with the latter. Building on these results, we explore the parameter space for woven cotton fabrics to show that three-layered cloth masks can be constructed with comparable filtration performance to surgical masks under ideal conditions. Reusable cloth masks thus present an environmentally friendly alternative to surgical masks so long as the face seal is adequate enough to minimize leakage.

Exploring COVID-19 Daily Records of Diagnosed Cases and Fatalities Based on Simple Nonparametric Methods

Containment strategies to combat epidemics such as SARS-CoV-2/COVID-19 require the availability of epidemiological parameters, e.g., the effective reproduction number. Parametric models such as the commonly used susceptible-infected-removed (SIR) compartment models fitted to observed incidence time series have limitations due to the time-dependency of the parameters. Furthermore, fatalities are delayed with respect to the counts of new cases, and the reproduction cycle leads to periodic patterns in incidence time series. Therefore, based on comprehensible nonparametric methods including time-delay correlation analyses, estimates of crucial parameters that characterise the COVID-19 pandemic with a focus on the German epidemic are presented using publicly available time-series data on prevalence and fatalities. The estimates for Germany are compared with the results for seven other countries (France, Italy, the United States of America, the United Kingdom, Spain, Switzerland, and Brazil). The duration from diagnosis to death resulting from delay-time correlations turns out to be 13 days with high accuracy for Germany and Switzerland. For the other countries, the time-to-death durations have wider confidence intervals. With respect to the German data, the two time series of new cases and fatalities exhibit a strong coherence. Based on the time lag between diagnoses and deaths, properly delayed asymptotic as well as instantaneous fatality-case ratios are calculated. The temporal median of the instantaneous fatality-case ratio with time lag of 13 days between cases and deaths for Germany turns out to be 0.02. Time courses of asymptotic fatality-case ratios are presented for other countries, which substantially differ during the first half of the pandemic but converge to a narrow range with standard deviation 0.0057 and mean 0.024. Similar results are obtained from comparing time courses of instantaneous fatality-case ratios with optimal delay for the 8 exemplarily chosen countries. The basic reproduction number, R0, for Germany is estimated to be between 2.4 and 3.4 depending on the generation time, which is estimated based on a delay autocorrelation analysis. Resonances at about 4 days and 7 days are observed, partially attributable to weekly periodicity of sampling. The instantaneous (time-dependent) reproduction number is estimated from the incident (counts of new) cases, thus allowing us to infer the temporal behaviour of the reproduction number during the epidemic course. The time course of the reproduction number turns out to be consistent with the time-dependent per capita growth.

SARS-CoV-2 population-based seroprevalence studies in Europe: a scoping review

OBJECTIVES

We aimed to review SARS-CoV-2 seroprevalence studies conducted in Europe to understand how they may be used to inform ongoing control strategies for COVID-19.

DESIGN

Scoping review of peer-reviewed publications and manuscripts on preprint servers from January 2020 to 15 September 2020.

PRIMARY MEASURE

Seroprevalence estimate (and lower and upper CIs). For studies conducted across a country or territory, we used the seroprevalence estimate and the upper and lower CIs and compared them to the total number of reported infections to calculate the ratio of reported to expected infections.

RESULTS

We identified 23 population-based seroprevalence studies conducted in Europe. Among 12 general population studies, seroprevalence ranged from 0.42% among residual clinical samples in Greece to 13.6% in an area of high transmission in Gangelt, Germany. Of the eight studies in blood donors, seroprevalence ranged from 0.91% in North-Western Germany to 23.3% in a high-transmission area in Lombardy region, Italy. In three studies which recruited individuals through employment, seroprevalence ranged from 0.5% among factory workers in Frankfurt, Germany, to 10.2% among university employees in Milan, Italy. In comparison to nationally reported cases, the extent of infection, as derived from these seroprevalence estimates, is manyfold higher and largely heterogeneous.

CONCLUSION

Exposure to the virus in Europe has not reached a level of infection that would prevent further circulation of the virus. Effective vaccine candidates are urgently required to deliver the level of immunity in the population.

The effectiveness of social bubbles as part of a Covid-19 lockdown exit strategy, a modelling study

Background: ​ During the coronavirus disease 2019 (COVID-19) lockdown, contact clustering in social bubbles may allow extending contacts beyond the household at minimal additional risk and hence has been considered as part of modified lockdown policy or a gradual lockdown exit strategy. We estimated the impact of such strategies on epidemic and mortality risk using the UK as a case study. Methods: ​ We used an individual based model for a synthetic population similar to the UK, stratified into transmission risks from the community, within the household and from other households in the same social bubble. The base case considers a situation where non-essential shops and schools are closed, the secondary household attack rate is 20% and the initial reproduction number is 0.8. We simulate social bubble strategies (where two households form an exclusive pair) for households including children, for single occupancy households, and for all households. We test the sensitivity of results to a range of alternative model assumptions and parameters. Results:  Clustering contacts outside the household into exclusive bubbles is an effective strategy of increasing contacts while limiting the associated increase in epidemic risk. In the base case, social bubbles reduced fatalities by 42% compared to an unclustered increase of contacts. We find that if all households were to form social bubbles the reproduction number would likely increase to above the epidemic threshold of R=1. Strategies allowing households with young children or single occupancy households to form social bubbles increased the reproduction number by less than 11%. The corresponding increase in mortality is proportional to the increase in the epidemic risk but is focussed in older adults irrespective of inclusion in social bubbles. Conclusions: ​ If managed appropriately, social bubbles can be an effective way of extending contacts beyond the household while limiting the increase in epidemic risk.

The effectiveness of social bubbles as part of a Covid-19 lockdown exit strategy, a modelling study

Background: ​ During the coronavirus disease 2019 (COVID-19) lockdown, contact clustering in social bubbles may allow extending contacts beyond the household at minimal additional risk and hence has been considered as part of modified lockdown policy or a gradual lockdown exit strategy. We estimated the impact of such strategies on epidemic and mortality risk using the UK as a case study. Methods: ​ We used an individual based model for a synthetic population similar to the UK, stratified into transmission risks from the community, within the household and from other households in the same social bubble. The base case considers a situation where non-essential shops and schools are closed, the secondary household attack rate is 20% and the initial reproduction number is 0.8. We simulate social bubble strategies (where two households form an exclusive pair) for households including children, for single occupancy households, and for all households. We test the sensitivity of results to a range of alternative model assumptions and parameters. Results:  Clustering contacts outside the household into exclusive bubbles is an effective strategy of increasing contacts while limiting the associated increase in epidemic risk. In the base case, social bubbles reduced fatalities by 42% compared to an unclustered increase of contacts. We find that if all households were to form social bubbles the reproduction number would likely increase to above the epidemic threshold of R=1. Strategies allowing households with young children or single occupancy households to form social bubbles increased the reproduction number by less than 11%. The corresponding increase in mortality is proportional to the increase in the epidemic risk but is focussed in older adults irrespective of inclusion in social bubbles. Conclusions: ​ If managed appropriately, social bubbles can be an effective way of extending contacts beyond the household while limiting the increase in epidemic risk.

[Importance of the COVID-19 pandemic for public health and group psychological aspects-Part 2 of a (preliminary) review]

Based upon the findings related to the impact of the coronavirus disease 2019 (COVID-19) pandemic on human living conditions and psychological health, in the first part of this review the authors discuss the consequences of the pandemic for public health. It is surprising to see that related to public health but also psychological factors and sequelae of the pandemic, a broad knowledge was already available based upon former pandemics and disasters long before the outbreak of COVID-19. This knowledge has been used very sparsely, if at all, for health political decisions. In view of the social significance of the pandemic and its social impact, findings from group psychology and group dynamics seem to be specifically important for a better understanding of behavior within the population as well as the conceptualization of public health interventions. An increase in psychological disorders was described related to the pandemic. For the treatment of these disorders, a range of psychotherapeutic approaches including evidence-based group psychotherapy are available. Whereas the use of telemedical and digital techniques is increasingly more common within individual psychotherapy, many questions are still open related to online group treatment.

The SARS-CoV-2 receptor and other key components of the Renin-Angiotensin-Aldosterone System related to COVID-19 are expressed in enterocytes in larval zebrafish

People with underlying conditions, including hypertension, obesity, and diabetes, are especially susceptible to negative outcomes after infection with coronavirus SARS-CoV-2, which causes COVID-19. Hypertension and respiratory inflammation are exacerbated by the Renin-Angiotensin-Aldosterone System (RAAS), which normally protects from rapidly dropping blood pressure via Angiotensin II (Ang II) produced by the enzyme Ace. The Ace paralog Ace2 degrades Ang II, counteracting its chronic effects, and serves as the SARS-CoV-2 receptor. Ace, the coronavirus, and COVID-19 comorbidities all regulate Ace2, but we do not yet understand how. To exploit zebrafish (Danio rerio) to help understand the relationship of the RAAS to COVID-19, we must identify zebrafish orthologs and co-orthologs of human RAAS genes and understand their expression patterns. To achieve these goals, we conducted genomic and phylogenetic analyses and investigated single cell transcriptomes. Results showed that most human RAAS genes have one or more zebrafish orthologs or co-orthologs. Results identified a specific type of enterocyte as the specific site of expression of zebrafish orthologs of key RAAS components, including Ace, Ace2, Slc6a19 (SARS-CoV-2 co-receptor), and the Angiotensin-related peptide cleaving enzymes Anpep (receptor for the common cold coronavirus HCoV-229E), and Dpp4 (receptor for the Middle East Respiratory Syndrome virus, MERS-CoV). Results identified specific vascular cell subtypes expressing Ang II receptors, apelin, and apelin receptor genes. These results identify genes and cell types to exploit zebrafish as a disease model for understanding mechanisms of COVID-19.

Epidemiology and transmission characteristics of early COVID-19 cases, 20 January-19 March 2020, in Bavaria, Germany

Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) led to a significant disease burden and disruptions in health systems. We describe the epidemiology and transmission characteristics of early coronavirus disease 2019 (COVID-19) cases in Bavaria, Germany. Cases were reverse transcription polymerase chain reaction (RT-PCR)-confirmed SARS-CoV-2 infections, reported from 20 January-19 March 2020. The incubation period was estimated using travel history and date of symptom onset. To estimate the serial interval, we identified pairs of index and secondary cases. By 19 March, 3546 cases were reported. A large proportion was exposed abroad (38%), causing further local transmission. Median incubation period of 256 cases with exposure abroad was 3.8 days (95%CI: 3.5-4.2). For 95% of infected individuals, symptom onset occurred within 10.3 days (95%CI: 9.1-11.8) after exposure. The median serial interval, using 53 pairs, was 3.5 days (95%CI: 3.0-4.2; mean: 3.9, s.d.: 2.2). Travellers returning to Germany had an important influence on the spread of SARS-CoV-2 infections in Bavaria in early 2020. Especially in times of low incidence, public health agencies should identify holiday destinations, and areas with ongoing local transmission, to monitor potential importation of SARS-CoV-2 infections. Travellers returning from areas with ongoing community transmission should be advised to quarantine to prevent re-introductions of COVID-19.

Serological antibody testing in the COVID-19 pandemic: their molecular basis and applications

The ongoing COVID-19 pandemic has placed an overwhelming burden on the healthcare system, and caused major disruption to the world economy. COVID-19 is caused by SARS-CoV-2, a novel coronavirus that leads to a variety of symptoms in humans, including cough, fever and respiratory failure. SARS-CoV-2 infection can trigger extensive immune responses, including the production of antibodies. The detection of antibody response by serological testing provides a supplementary diagnostic tool to molecular tests. We hereby present a succinct yet comprehensive review on the antibody response to SARS-CoV-2 infection, as well as molecular mechanisms behind the strengths and limitations of serological antibody tests. The presence of antibodies can be detected in patient sera within days post symptom onset. Serological tests demonstrate superior sensitivity to molecular tests in some periods of time during disease development. Compared with the molecular tests, serological tests can be used for point-of-care testing, providing faster results at a lower cost. Commercially available serological tests show variable sensitivity and specificity, and the molecular basis of these variabilities are analysed. We discuss assays of different complexities that are used to specifically quantitate neutralising antibodies against SARS-CoV-2, which has important implications for vaccine development and herd immunity. Furthermore, we discuss examples of successful applications of serological tests to contact tracing and community-level sero-surveying, which provide invaluable information for pandemic management and assessment.

Testing and tracking in the UK: A dynamic causal modelling study

By equipping a previously reported dynamic causal modelling of COVID-19 with an isolation state, we were able to model the effects of self-isolation consequent on testing and tracking. Specifically, we included a quarantine or isolation state occupied by people who believe they might be infected but are asymptomatic—and could only leave if they test negative. We recovered maximum posteriori estimates of the model parameters using time series of new cases, daily deaths, and tests for the UK. These parameters were used to simulate the trajectory of the outbreak in the UK over an 18-month period. Several clear-cut conclusions emerged from these simulations. For example, under plausible (graded) relaxations of social distancing, a rebound of infections is highly unlikely. The emergence of a second wave depends almost exclusively on the rate at which we lose immunity, inherited from the first wave. There exists no testing strategy that can attenuate mortality rates, other than by deferring or delaying a second wave. A testing and tracking policy—implemented at the present time—will defer any second wave beyond a time horizon of 18 months. Crucially, this deferment is within current testing capabilities (requiring an efficacy of tracing and tracking of about 20% of asymptomatic infected cases, with 50,000 tests per day). These conclusions are based upon a dynamic causal model for which we provide some construct and face validation—using a comparative analysis of the United Kingdom and Germany, supplemented with recent serological studies.

On the Effect of Age on the Transmission of SARS-CoV-2 in Households, Schools, and the Community

BACKGROUND

There is limited information on the effect of age on the transmission of SARS-CoV-2 infection in different settings.

METHODS

We reviewed published studies/data on detection of SARS-CoV-2 infection in contacts of COVID-19 cases, serological studies, and studies of infections in schools.

RESULTS

Compared to younger/middle-aged adults, susceptibility to infection for children younger than 10 years is estimated to be significantly lower, while estimated susceptibility to infection in adults older than 60 years is higher. Serological studies suggest that younger adults (particularly those younger than 35 years) often have high cumulative incidence of SARS-CoV-2 infection in the community. There is some evidence that given limited control measures, SARS-CoV-2 may spread robustly in secondary/high schools, and to a lesser degree in primary schools, with class size possibly affecting that spread. There is also evidence of more limited spread in schools when some mitigation measures are implemented. Several potential biases that may affect these studies are discussed.

CONCLUSIONS

Mitigation measures should be implemented when opening schools, particularly secondary/high schools. Efforts should be undertaken to diminish mixing in younger adults, particularly individuals aged 18-35 years, to mitigate the spread of the epidemic in the community.

SARS-CoV-2 antibody prevalence in England following the first peak of the pandemic

England has experienced a large outbreak of SARS-CoV-2, disproportionately affecting people from disadvantaged and ethnic minority communities. It is unclear how much of this excess is due to differences in exposure associated with structural inequalities. Here, we report from the REal-time Assessment of Community Transmission-2 (REACT-2) national study of over 100,000 people. After adjusting for test characteristics and re-weighting to the population, overall antibody prevalence is 6.0% (95% CI: 5.8-6.1). An estimated 3.4 million people had developed antibodies to SARS-CoV-2 by mid-July 2020. Prevalence is two- to three-fold higher among health and care workers compared with non-essential workers, and in people of Black or South Asian than white ethnicity, while age- and sex-specific infection fatality ratios are similar across ethnicities. Our results indicate that higher hospitalisation and mortality from COVID-19 in minority ethnic groups may reflect higher rates of infection rather than differential experience of disease or care.

[SARS-CoV-2, influenza and norovirus infection : A direct epidemiologic comparison]

Hintergrund

Hospitalisierungsraten, Notaufnahmeprävalenzen und Fallsterblichkeiten (CFP) stationärer SARS-CoV-2-Patienten und wie sich diese von anderen pandemischen oder saisonalen Viruserkrankungen, wie Influenza A/B oder Norovirusinfektionen unterscheiden, wurden bisher nicht untersucht. Diese Arbeit gibt einen Überblick aus einer Kommune darüber und vergleicht diesen auch mit den negativ getesteten stationären Verdachtsfällen.

Methoden

Im Rahmen retrospektiver Kohortenanalysen von 67.000 Krankenhausfällen eines Klinikums mit umfassender Notfallversorgung und Meldedaten des regionalen Gesundheitsamts wurden für die Virusinfektionen SARS-CoV‑2, Influenza A/B und Norovirus Genotyp 1/2 Hospitalisierungsraten, Notaufnahmeprävalenzen und CFP berechnet.

Ergebnisse

In Fürth (Stadt‑/Landkreis) wurden 0,34 % der Bevölkerung, 824 Personen, bis 07.05.2020 positiv auf SARS-CoV‑2 getestet, wovon 162 (19,7 %) stationär behandelt wurden. 91 der Infizierten verstarben (CFP 11,0 %), davon 48 stationär. In der aktuellen Grippe‑/Norovirussaison wurden 992 Einwohner als influenzapositiv und 135 als noroviruspositiv gemeldet, davon 202 (20,3 %) bzw. 125 (91,9 %) stationär behandelt. Die Notaufnahmeprävalenzen waren 4,1 %, 2,0 % und 0,6 %. Die CFP der SARS-CoV-2-, influenza- und noroviruspositiven Krankenhauspopulationen betrugen 29,1 %, 3,0 % und 1,6 %, die der testnegativen Verdachtsfälle 5,9 %, 4,8 % und 6,9 % bei einer Krankenhausmortalität von 2,1 % für 2020.

Schlussfolgerungen

Bei gleichen Hospitalisierungsraten von SARS-CoV-2- und Influenzapatienten unterschieden sich die CFP massiv, während die CFP der testnegativen Verdachtsfälle aller 3 Infektionserkrankungen sich nicht signifikant unterschieden.

Susceptibility to SARS-CoV-2 Infection Among Children and Adolescents Compared With Adults: A Systematic Review and Meta-analysis

IMPORTANCE

The degree to which children and adolescents are infected by and transmit severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unclear. The role of children and adolescents in transmission of SARS-CoV-2 is dependent on susceptibility, symptoms, viral load, social contact patterns, and behavior.

OBJECTIVE

To systematically review the susceptibility to and transmission of SARS-CoV-2 among children and adolescents compared with adults.

DATA SOURCES

PubMed and medRxiv were searched from database inception to July 28, 2020, and a total of 13 926 studies were identified, with additional studies identified through hand searching of cited references and professional contacts.

STUDY SELECTION

Studies that provided data on the prevalence of SARS-CoV-2 in children and adolescents (younger than 20 years) compared with adults (20 years and older) derived from contact tracing or population screening were included. Single-household studies were excluded.

DATA EXTRACTION AND SYNTHESIS

PRISMA guidelines for abstracting data were followed, which was performed independently by 2 reviewers. Quality was assessed using a critical appraisal checklist for prevalence studies. Random-effects meta-analysis was undertaken.

MAIN OUTCOMES AND MEASURES

Secondary infection rate (contact-tracing studies) or prevalence or seroprevalence (population screening studies) among children and adolescents compared with adults.

RESULTS

A total of 32 studies comprising 41 640 children and adolescents and 268 945 adults met inclusion criteria, including 18 contact-tracing studies and 14 population screening studies. The pooled odds ratio of being an infected contact in children compared with adults was 0.56 (95% CI, 0.37-0.85), with substantial heterogeneity (I2 = 94.6%). Three school-based contact-tracing studies found minimal transmission from child or teacher index cases. Findings from population screening studies were heterogenous and were not suitable for meta-analysis. Most studies were consistent with lower seroprevalence in children compared with adults, although seroprevalence in adolescents appeared similar to adults.

CONCLUSIONS AND RELEVANCE

In this meta-analysis, there is preliminary evidence that children and adolescents have lower susceptibility to SARS-CoV-2, with an odds ratio of 0.56 for being an infected contact compared with adults. There is weak evidence that children and adolescents play a lesser role than adults in transmission of SARS-CoV-2 at a population level. This study provides no information on the infectivity of children.

The Impact of SARS-CoV-2 Pandemic Lockdown on a Botulinum Toxin Outpatient Clinic in Germany

Botulinum neurotoxin type A (BoNT/A) injections have to be administered repeatedly to achieve a rather stable, high level of improvement. This study aimed to take a look at changes in the daily routine of a BoNT/A outpatient clinic due to the SARS-CoV-2 pandemic lockdown, analyze the impact of SARS-CoV-2-induced re-injection delay on outcomes in patients with cervical dystonia (CD) (n = 36) and four other disease entities (n = 58), and study the influence of covariables, including previous injections and doses. For the present observational study, the first 100 patients who were scheduled to have an appointment between April 20 and May 18 during the partial lockdown and also had been treated regularly before the lockdown were recruited. Clinical and demographical characteristics and treatment-related data from the previous visits were extracted from charts. Time delay, symptom severity assessment, and TSUI score (if applicable) were gathered at the first coronavirus pandemic lockdown emergency visit for each patient. Of the 94 patients who could come to the clinic, 48 reported a delay and 44 reported worsening during the delay. Delays ranged from 1 to 63 days, the mean delay was 23 days, and the mean worsening was 26% compared to the previous visit. A significant correlation was found between the duration of the delay and the patient's rating of worsening (PwP). In CD patients, the physician´s rating of CD worsening by the TSUI score (ATUSI-PTSUI) was significantly correlated with general worsening (DwP) and the TSUI at the last visit (PTSUI). A small delay of a few weeks led to a similar worsening of symptoms in CD and all other disease entities and to relapse on a higher level of severity. This relapse can only be compensated by continuous treatment up to at least 1 year until patients reach the same level of treatment efficacy as that before the SARS-CoV-2 pandemic.

Development of the reproduction number from coronavirus SARS-CoV-2 case data in Germany and implications for political measures

BACKGROUND

SARS-CoV-2 has induced a worldwide pandemic and subsequent non-pharmaceutical interventions (NPIs) to control the spread of the virus. As in many countries, the SARS-CoV-2 pandemic in Germany has led to a consecutive roll-out of different NPIs. As these NPIs have (largely unknown) adverse effects, targeting them precisely and monitoring their effectiveness are essential. We developed a compartmental infection dynamics model with specific features of SARS-CoV-2 that allows daily estimation of a time-varying reproduction number and published this information openly since the beginning of April 2020. Here, we present the transmission dynamics in Germany over time to understand the effect of NPIs and allow adaptive forecasts of the epidemic progression.

METHODS

We used a data-driven estimation of the evolution of the reproduction number for viral spreading in Germany as well as in all its federal states using our model. Using parameter estimates from literature and, alternatively, with parameters derived from a fit to the initial phase of COVID-19 spread in different regions of Italy, the model was optimized to fit data from the Robert Koch Institute.

RESULTS

The time-varying reproduction number (Rt) in Germany decreased to <1 in early April 2020, 2-3 weeks after the implementation of NPIs. Partial release of NPIs both nationally and on federal state level correlated with moderate increases in Rt until August 2020. Implications of state-specific Rt on other states and on national level are characterized. Retrospective evaluation of the model shows excellent agreement with the data and usage of inpatient facilities well within the healthcare limit. While short-term predictions may work for a few weeks, long-term projections are complicated by unpredictable structural changes.

CONCLUSIONS

The estimated fraction of immunized population by August 2020 warns of a renewed outbreak upon release of measures. A low detection rate prolongs the delay reaching a low case incidence number upon release, showing the importance of an effective testing-quarantine strategy. We show that real-time monitoring of transmission dynamics is important to evaluate the extent of the outbreak, short-term projections for the burden on the healthcare system, and their response to policy changes.

Model-based analysis on social acceptability and feasibility of a focused protection strategy against the COVID-19 pandemic

This paper studies the social acceptability and feasibility of a focused protection strategy against coronavirus disease 2019 (COVID-19). We propose a control scheme to develop herd immunity while satisfying the following two basic requirements for a viable policy option. The first requirement is social acceptability: the overall deaths should be minimized for social acceptance. The second is feasibility: the healthcare system should not be overwhelmed to avoid various adverse effects. To exploit the fact that the disease severity increases considerably with age and comorbidities, we assume that some focused protection measures for those high-risk individuals are implemented and the disease does not spread within the high-risk population. Because the protected population has higher severity ratios than the unprotected population by definition, the protective measure can substantially reduce mortality in the whole population and also avoid the collapse of the healthcare system. Based on a simple susceptible-infected-recovered model, social acceptability and feasibility of the proposed strategy are summarized into two easily computable conditions. The proposed framework can be applied to various populations for studying the viability of herd immunity strategies against COVID-19. For Japan, herd immunity may be developed by the proposed scheme if [Formula: see text] and the severity rates of the disease are 1/10 times smaller than the previously reported value, although as high mortality as seasonal influenza is expected.

Dynamics of COVID-19 under social distancing measures are driven by transmission network structure

In the absence of pharmaceutical interventions, social distancing is being used worldwide to curb the spread of COVID-19. The impact of these measures has been inconsistent, with some regions rapidly nearing disease elimination and others seeing delayed peaks or nearly flat epidemic curves. Here we build a stochastic epidemic model to examine the effects of COVID-19 clinical progression and transmission network structure on the outcomes of social distancing interventions. Our simulations show that long delays between the adoption of control measures and observed declines in cases, hospitalizations, and deaths occur in many scenarios. We find that the strength of within-household transmission is a critical determinant of success, governing the timing and size of the epidemic peak, the rate of decline, individual risks of infection, and the success of partial relaxation measures. The structure of residual external connections, driven by workforce participation and essential businesses, interacts to determine outcomes. We suggest limited conditions under which the formation of household "bubbles" can be safe. These findings can improve future predictions of the timescale and efficacy of interventions needed to control second waves of COVID-19 as well as other similar outbreaks, and highlight the need for better quantification and control of household transmission.

Global and local mobility as a barometer for COVID-19 dynamics

The spreading of infectious diseases including COVID-19 depends on human interactions. In an environment where behavioral patterns and physical contacts are constantly evolving according to new governmental regulations, measuring these interactions is a major challenge. Mobility has emerged as an indicator for human activity and, implicitly, for human interactions. Here, we study the coupling between mobility and COVID-19 dynamics and show that variations in global air traffic and local driving mobility can be used to stratify different disease phases. For ten European countries, our study shows a maximal correlation between driving mobility and disease dynamics with a time lag of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$14.6 \pm 5.6$$\end{document}14.6±5.6 days. Our findings suggest that trends in local mobility allow us to forecast the outbreak dynamics of COVID-19 for a window of two weeks and adjust local control strategies in real time.

Evaluation of undetected cases during the COVID-19 epidemic in Austria

BACKGROUND

Knowing the number of undetected cases of COVID-19 is important for a better understanding of the spread of the disease. This study analyses the temporal dynamic of detected vs. undetected cases to provide guidance for the interpretation of prevalence studies performed with PCR or antibody tests to estimate the detection rate.

METHODS

We used an agent-based model to evaluate assumptions on the detection probability ranging from 0.1 to 0.9. For each general detection probability, we derived age-dependent detection probabilities and calibrated the model to reproduce the epidemic wave of COVID-19 in Austria from March 2020 to June 2020. We categorized infected individuals into presymptomatic, symptomatic unconfirmed, confirmed and never detected to observe the simulated dynamic of the detected and undetected cases.

RESULTS

The calculation of the age-dependent detection probability ruled values lower than 0.4 as most likely. Furthermore, the proportion of undetected cases depends strongly on the dynamic of the epidemic wave: during the initial upswing, the undetected cases account for a major part of all infected individuals, whereas their share decreases around the peak of the confirmed cases.

CONCLUSIONS

The results of prevalence studies performed to determine the detection rate of COVID-19 patients should always be interpreted with regard to the current dynamic of the epidemic wave. Applying the method proposed in our analysis, the prevalence study performed in Austria in April 2020 could indicate a detection rate of 0.13, instead of the prevalent ratio of 0.29 between detected and estimated undetected cases at that time.

Tracking [Formula: see text] of COVID-19: A new real-time estimation using the Kalman filter

We develop a new method for estimating the effective reproduction number of an infectious disease ([Formula: see text]) and apply it to track the dynamics of COVID-19. The method is based on the fact that in the SIR model, [Formula: see text] is linearly related to the growth rate of the number of infected individuals. This time-varying growth rate is estimated using the Kalman filter from data on new cases. The method is easy to implement in standard statistical software, and it performs well even when the number of infected individuals is imperfectly measured, or the infection does not follow the SIR model. Our estimates of [Formula: see text] for COVID-19 for 124 countries across the world are provided in an interactive online dashboard, and they are used to assess the effectiveness of non-pharmaceutical interventions in a sample of 14 European countries.

HIV and SARS-CoV-2 co-infection: cross-sectional findings from a German 'hotspot'

Purpose

This study aimed to determine the proportion of people living with HIV with anti-SARS-CoV-2 IgG antibodies in a sample from a large single HIV center in Munich, Germany, after the first phase of the coronavirus pandemic and to infer the prevalence of SARS-CoV-2 co-infection in people living with HIV.

Methods

Prospective sub-study of the ongoing ArcHIV cohort between May and July 2020. Anti-SARS-CoV-2 IgG antibodies were measured using the recomWell SARS-CoV-2 IgG ELISA (Mikrogen, Neuried, Germany); positive and borderline results were re-tested using the recomLine SARS-CoV-2 IgG immunoassay (Mikrogen, Neuried, Germany). Demographic and medical data were extracted from the electronic patient files.

Results

Overall, 500 people living with HIV were included in the study (83% male, median age 51 years). Three participants had been diagnosed with COVID-19 prior to study inclusion. Of those, nine were confirmed positive for SARS-CoV-2 IgG antibodies, resulting in an estimated seroprevalence (accounting for sensitivity and specificity of the test) of 1.5% (CI 95%: 0.69; 3.13) for the entire study sample, and 2.2% (CI 95%: 1.1; 3.9) for the subset of the Munich citizens. There were no marked differences for people living with HIV with and without SARS-CoV-2 co-infection.

Conclusion

The seroprevalence of SARS-CoV-2 co-infection in people living with HIV as found in our study does not seem to exceed previous reports from general populations of ‘hot-sport’ areas; comparative data from the Munich population can be expected to be published soon. Our data also highlight, once more, the need to do confirmatory testing on positive samples to minimize the impact of false-positive results.

Infection fatality rate of COVID-19 inferred from seroprevalence data

OBJECTIVE

To estimate the infection fatality rate of coronavirus disease 2019 (COVID-19) from seroprevalence data.

METHODS

I searched PubMed and preprint servers for COVID-19 seroprevalence studies with a sample size ≥ 500 as of 9 September 2020. I also retrieved additional results of national studies from preliminary press releases and reports. I assessed the studies for design features and seroprevalence estimates. I estimated the infection fatality rate for each study by dividing the cumulative number of COVID-19 deaths by the number of people estimated to be infected in each region. I corrected for the number of immunoglobin (Ig) types tested (IgG, IgM, IgA).

FINDINGS

I included 61 studies (74 estimates) and eight preliminary national estimates. Seroprevalence estimates ranged from 0.02% to 53.40%. Infection fatality rates ranged from 0.00% to 1.63%, corrected values from 0.00% to 1.54%. Across 51 locations, the median COVID-19 infection fatality rate was 0.27% (corrected 0.23%): the rate was 0.09% in locations with COVID-19 population mortality rates less than the global average (< 118 deaths/million), 0.20% in locations with 118-500 COVID-19 deaths/million people and 0.57% in locations with > 500 COVID-19 deaths/million people. In people younger than 70 years, infection fatality rates ranged from 0.00% to 0.31% with crude and corrected medians of 0.05%.

CONCLUSION

The infection fatality rate of COVID-19 can vary substantially across different locations and this may reflect differences in population age structure and case-mix of infected and deceased patients and other factors. The inferred infection fatality rates tended to be much lower than estimates made earlier in the pandemic.

Molecular mechanism of inhibiting the SARS-CoV-2 cell entry facilitator TMPRSS2 with camostat and nafamostat

The entry of the coronavirus SARS-CoV-2 into human lung cells can be inhibited by the approved drugs camostat and nafamostat. Here we elucidate the molecular mechanism of these drugs by combining experiments and simulations. In vitro assays confirm that both drugs inhibit the human protein TMPRSS2, a SARS-Cov-2 spike protein activator. As no experimental structure is available, we provide a model of the TMPRSS2 equilibrium structure and its fluctuations by relaxing an initial homology structure with extensive 330 microseconds of all-atom molecular dynamics (MD) and Markov modeling. Through Markov modeling, we describe the binding process of both drugs and a metabolic product of camostat (GBPA) to TMPRSS2, reaching a Michaelis complex (MC) state, which precedes the formation of a long-lived covalent inhibitory state. We find that nafamostat has a higher MC population than camostat and GBPA, suggesting that nafamostat is more readily available to form the stable covalent enzyme–substrate intermediate, effectively explaining its high potency. This model is backed by our in vitro experiments and consistent with previous virus cell entry assays. Our TMPRSS2–drug structures are made public to guide the design of more potent and specific inhibitors.

The authors unravel the molecular action principle of nafamostat and camostat, two potential COVID-19 drugs targeting the human protein TMPRSS2.

Tracking [Formula: see text] of COVID-19: A new real-time estimation using the Kalman filter

We develop a new method for estimating the effective reproduction number of an infectious disease ([Formula: see text]) and apply it to track the dynamics of COVID-19. The method is based on the fact that in the SIR model, [Formula: see text] is linearly related to the growth rate of the number of infected individuals. This time-varying growth rate is estimated using the Kalman filter from data on new cases. The method is easy to implement in standard statistical software, and it performs well even when the number of infected individuals is imperfectly measured, or the infection does not follow the SIR model. Our estimates of [Formula: see text] for COVID-19 for 124 countries across the world are provided in an interactive online dashboard, and they are used to assess the effectiveness of non-pharmaceutical interventions in a sample of 14 European countries.

Tracking [Formula: see text] of COVID-19: A new real-time estimation using the Kalman filter

We develop a new method for estimating the effective reproduction number of an infectious disease ([Formula: see text]) and apply it to track the dynamics of COVID-19. The method is based on the fact that in the SIR model, [Formula: see text] is linearly related to the growth rate of the number of infected individuals. This time-varying growth rate is estimated using the Kalman filter from data on new cases. The method is easy to implement in standard statistical software, and it performs well even when the number of infected individuals is imperfectly measured, or the infection does not follow the SIR model. Our estimates of [Formula: see text] for COVID-19 for 124 countries across the world are provided in an interactive online dashboard, and they are used to assess the effectiveness of non-pharmaceutical interventions in a sample of 14 European countries.

[SARS-CoV-2/COVID-19-epidemiology and prevention]

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread globally since December 2019. A first wave is visible up to the end of June 2020 in many regions. This article presents a review of the current knowledge on the epidemiology and prevention. The SARS-CoV‑2 predominantly replicates in the upper and lower respiratory tracts and is particularly transmitted by droplets and aerosols. The estimate for the basic reproduction number (R₀) is between 2 and 3 and the median incubation period is 6 days (range 2-14 days). As with the related SARS-CoV and Middle East respiratory syndrome (MERS-CoV), superspreading events play an important role in the dissemination. A high proportion of infections are uncomplicated but moderate or severe courses develop in 5-10% of infected persons. Pneumonia, cardiac involvement and thromboembolisms are the most frequent manifestations leading to hospitalization. Risk factors for a complicated course are high age, hypertension, diabetes mellitus and chronic cardiovascular and pulmonary diseases as well as immunodeficiency. Currently, the estimation for the infection fatality rate (IFR) is between 0.5% and 1% across all age groups. Outbreaks were limited in many regions with bundles of various measures for reduction of social contacts. The incidence for the first wave in Germany can be estimated as 0.4-1.8% and excess mortality could not be observed.