Standardized cumulative metrics of excess mortality to monitor health system resilience throughout COVID-19 and other respiratory virus resurgences.

Monitoring morbidity and mortality in resurgences of respiratory infections has been underpinned with the epidemic of COVID-19 and poses significant challenges. For example, case fatality rates and deaths attributed to specific respiratory pathogens are known to suffer from significant biases undermining their comparability through time and space. As a result, it is difficult to evaluate the protective effect of public health interventions or quantify the impact of a resurgence to the general population through direct recording of COVID-19 related deaths. To overcome these limitations, it has been proposed that more robust less biased metrics, such as the all-cause deaths, can be used to monitor the effect of an epidemic over a population and over time. More specifically, metrics of excess mortality over time, which have been used for influenza surveillance in the past, are increasingly considered important for COVID-19 surveillance. Here, we discuss excess mortality surveillance focusing on standardised single-point and standardised cumulative metrics that allow comparability of excess mortality through space and time. We explain why z-score allows for comparison of excess mortality between countries and different periods, while cumulative z-score allows assessment of excess mortality over long periods. Our commentary re-iterates the importance of standardised statistics of excess mortality for COVID-19 surveillance as we move towards co-existence with SARS-CoV-2 that will allow drawing conclusions from best practices in different health systems and different periods.

On the evolution of SARS-CoV-2 and the emergence of variants of concern.

The epidemiology of COVID-19 has dramatically changed since the beginning of the pandemic as we witnessed significant changes in transmissibility and pathogenicity with the emergence of SARS-CoV-2 variants of concern (VoCs). Here I present and comment on working hypotheses about the evolutionary dynamics of the emergence of VoCs.

Low circulation of respiratory syncytial and influenza viruses during autumn-winter 2021 in the industrial workplace and long-term healthcare facilities in Athens, Greece.

The emergence of SARS-CoV-2 has pinpointed the importance of non-pharmaceutical interventions (NPIs), which have been traditionally used for the prevention of the spread of respiratory viruses among individuals. The aim of our study was to capture the level of circulation of respiratory syncytial and influenza viruses during a period of medium severity NPIs due to SARS-CoV-2 pandemics in Greece. A total of 2,225 nasopharyngeal samples were received during the year 2021 as a part of the routine diagnostic service and were divided into two study groups: (a) January to September 2021 and (b) October to the end of December 2021. The latter is the time of the year when there is a peak of infections from most respiratory viruses, and thus, most of the samples were tested in that period. The samples were taken from three different sites, i.e., (a) industrial workers in a factory, (b) elderly homecare facilities, and c) people who actively asked to be tested for SARS-CoV-2. All the samples were tested simultaneously for SARS-CoV2, RSV, and influenza virus. A total of 2,110 samples were negative for either of the three viruses, 106 were SARS-CoV-2-positive, and 9 were RSV-positive from which 7 were found in the workers' group. None of the samples was found to be positive for the influenza virus, and no sample had co-infection. Our study shows the low-level circulation of RSV and influenza viruses during autumn-winter 2021 and will provide a reference for future studies of RSV and influenza in Greece.

Low circulation of respiratory syncytial and influenza viruses during autumn-winter 2021 in the industrial workplace and long-term healthcare facilities in Athens, Greece

The emergence of SARS-CoV-2 has pinpointed the importance of non-pharmaceutical interventions (NPIs), which have been traditionally used for the prevention of the spread of respiratory viruses among individuals. The aim of our study was to capture the level of circulation of respiratory syncytial and influenza viruses during a period of medium severity NPIs due to SARS-CoV-2 pandemics in Greece. A total of 2,225 nasopharyngeal samples were received during the year 2021 as a part of the routine diagnostic service and were divided into two study groups: (a) January to September 2021 and (b) October to the end of December 2021. The latter is the time of the year when there is a peak of infections from most respiratory viruses, and thus, most of the samples were tested in that period. The samples were taken from three different sites, i.e., (a) industrial workers in a factory, (b) elderly homecare facilities, and c) people who actively asked to be tested for SARS-CoV-2. All the samples were tested simultaneously for SARS-CoV2, RSV, and influenza virus. A total of 2,110 samples were negative for either of the three viruses, 106 were SARS-CoV-2-positive, and 9 were RSV-positive from which 7 were found in the workers' group. None of the samples was found to be positive for the influenza virus, and no sample had co-infection. Our study shows the low-level circulation of RSV and influenza viruses during autumn-winter 2021 and will provide a reference for future studies of RSV and influenza in Greece.

Interpretable Operations Research for High-Stakes Decisions: Designing the Greek COVID-19 Testing System

In the summer of 2020, in collaboration with the Greek government, we designed and deployed Eva-the first national-scale, reinforcement learning system for targeted COVID-19 testing. In this paper, we detail the rationale for three major design/algorithmic elements: Eva's testing supply chain, estimating COVID-19 prevalence, and test allocation. Specifically, we describe the design of Eva's supply chain to collect and process thousands of biological samples per day with special emphasis on capacity procurement. Then, we propose a novel, empirical Bayes estimation strategy to estimate COVID-19 prevalence among various passenger types with limited data and showcase how these estimates were instrumental in making a variety of downstream decisions. Finally, we propose a novel, multiarmed bandit algorithm that dynamically allocates tests to arriving passengers in a nonstationary environment with delayed feedback and batched decisions. All our design and algorithmic choices emphasize the need for transparent reasoning to enable human-in-the-loop analytics. Such transparency was crucial to building trust and acceptance among policymakers and public health experts in a period of global crisis.

Development and Analytical Validation of a One-Step Five-Plex RT-ddPCR Assay for the Quantification of SARS-CoV-2 Transcripts in Clinical Samples.

Highly sensitive methodologies for SARS-CoV-2 detection are essential for the control of COVID-19 pandemic. We developed and analytically validated a highly sensitive and specific five-plex one-step RT-ddPCR assay for SARS-CoV-2. We first designed in-silico novel primers and probes for the simultaneous absolute quantification of three different regions of the nucleoprotein (N) gene of SARS-CoV-2 (N1, N2, N3), a synthetic RNA as an external control (RNA-EC), and Beta-2-Microglobulin (B2M) as an endogenous RNA internal control (RNA-IC). The developed assay was analytically validated using synthetic DNA and RNA calibrator standards and then was applied to 100 clinical specimens previously analyzed with a commercially available CE-IVD RT-qPCR assay. The analytical validation of the developed assay resulted in very good performance characteristics in terms of analytical sensitivity, linearity, analytical specificity, and reproducibility and recovery rates even at very low viral concentrations. The simultaneous absolute quantification of the RNA-EC and RNA-IC provides the necessary metrics for quality control assessment. Direct comparison of the developed one-step five-plex RT-ddPCR assay with a CE-IVD RT-qPCR kit revealed a very high concordance and a higher sensitivity [concordance: 99/100 (99.0%, Spearman's correlation coefficient: -0.850, p < 0.001)]. The developed assay is highly sensitive, specific, and reproducible and has a broad linear dynamic range, providing absolute quantification of SARS-COV-2 transcripts. The inclusion of two RNA quality controls, an external and an internal, is highly important for standardization of SARS-COV-2 molecular testing in clinical and wastewater samples.

Immunogenicity and Safety of the BNT162b2 mRNA COVID-19 Vaccine in Patients with Melanoma Treated with Immunotherapy.

The BNT162b2 vaccine against SARS-CoV-2 has a proven efficacy and a favorable safety profile. In cancer patients under immunotherapy in the form of immune-checkpoint inhibitors (ICIs), the efficacy of the vaccine has not been thoroughly studied, while a theoretical concern has also been raised about triggering immune-related adverse events (irAEs) by the vaccine. We conducted a prospective, non-interventional study on the immunogenicity and safety of the BNT162b2 vaccine in patients with advanced or metastatic melanoma treated with ICIs. Blood samples were obtained 0-4 days before the first dose and 12-21 days after the second dose of the vaccine for the quantification of the SARS-CoV-2 anti-spike antibody using an ELISA and immunophenotyping of the T and myeloid cell subpopulations. The active recording of AEs for a two-month period was conducted. Forty patients were included in the study. All but one (97.3%) achieved seroconversion after two doses of the vaccine and no correlations of the antibody titers with any of the studied parameters (age, gender, stage and duration of the disease, type of ICI, previous treatment, etc.) were found. Moreover, no differences in the subpopulations of the T cells (including the T-regulatory cells) or the myeloid cells were found pre- and post-vaccination. All AEs were low-grade, while one case of arthritis exacerbation was noted. The seroconversion rate in the studied population was high and was comparable to that of healthy subjects, while no major safety issues were raised during the safety follow-up. Finally, no derangements in the subpopulations of T cells or myeloid cells were noted. This is the first study focusing on the immunogenicity, safety, and effect of anti-SARS-CoV-2 vaccines on the blood-cell immunophenotype status of patients with melanoma treated with ICIs.

Cold-Season Epidemic Dynamics of COVID-19 in Two Major Metropolitan Areas in Greece: Hypotheses and Implications for Public Health Interventions.

Many respiratory viruses, including coronaviruses, follow seasonal transmission dynamics. Analyzing the social and environmental mechanics of the emergence of SARS-CoV-2 over the first cold season provides insight into designing targeted interventions. We analyzed all fully anonymized SARS-CoV-2 case data in two metropolitan areas, Attika and Thessaloniki, diagnosed between September 1st and December 31st, 2020. The emergence of the second wave in Greece occurred in October-November. SARS-CoV-2 diagnoses in Thessaloniki increased quasi-exponentially in mid-October, coinciding with the increase in the proportion of diagnoses in young people aged 18-39. The same pattern was observed in Attika with an almost 2-week delay, even though Attika had a higher prevalence of cases throughout summer until the second wave. Crucially, the nighttime temperature in Thessaloniki dropped below 18°C 3 weeks earlier than that in Attika. Epidemic growth was independently associated with the proportion of cases attributed to the 18-39 age group as well as with the drop in nighttime temperature below 18°C in both metropolitan areas but with a time difference. This pattern can be explained by a shift of nighttime entertainment activities from open-air to closed spaces, which occurs as nighttime temperature drops. Vaccination of young individuals can be crucial in decelerating the cold-season dynamics of SARS-CoV-2.

Systematic review with meta-analysis: COVID-19 outcomes in patients receiving anti-TNF treatments.

BACKGROUND: Accumulating evidence suggests a beneficial effective of tumour necrosis factor-alpha (TNF-α) inhibitors on the outcomes of COVID-19 disease, which, however is not validated by all studies. AIMS: To perform a systematic review and meta-analysis of existing reports to investigate the impact of anti-TNF treatments on the clinical outcomes of COVID-19 patients. METHODS: A systematic search at PubMed and SCOPUS databases using specific keywords was performed. All reports of COVID-19 outcomes for patients receiving anti-TNF therapy by September 2021 were included. Pooled effect measures were calculated using a random-effects model. The Newcastle Ottawa Scale for observational studies was used to assess bias. Studies that were not eligible for meta-analysis were described qualitatively. RESULTS: In total, 84 studies were included in the systematic review, and 35 were included in the meta-analysis. Patients receiving anti-TNF treatment, compared to non-anti-TNF, among COVID-19 cases had a lower probability of hospitalisation (eight studies, 2555 patients, pooled OR = 0.53, 95% CI: 0.42-0.67, I2  = 0) and severe disease defined as intensive care unit admission or death (two studies, 1823 patients, pooled OR = 0.63, 95% CI: 0.41-0.96, I2  = 0), after adjustment for validated predictors of adverse disease outcomes. No difference was found for the risk for hospitalisation due to COVID-19 in populations without COVID-19 for patients receiving anti-TNF treatment compared to non-anti-TNF (three studies, 5 994 958 participants, pooled risk ratio = 0.97, 95% CI: 0.68-1.39, I2  = 20) adjusted for age, sex and comorbidities. CONCLUSIONS: TNF-α inhibitors are associated with a lower probability of hospitalisation and severe COVID-19 when compared to any other treatment for an underlying inflammatory disease.

Upregulation of Human Endogenous Retroviruses in Bronchoalveolar Lavage Fluid of COVID-19 Patients.

Severe COVID-19 pneumonia has been associated with the development of intense inflammatory responses during the course of infections with SARS-CoV-2. Given that human endogenous retroviruses (HERVs) are known to be activated during and participate in inflammatory processes, we examined whether HERV dysregulation signatures are present in COVID-19 patients. By comparing transcriptomes of bronchoalveolar lavage fluid (BALF) of COVID-19 patients and healthy controls, and peripheral blood monocytes (PBMCs) from patients and controls, we have shown that HERVs are intensely dysregulated in BALF of COVID-19 patients compared to those in BALF of healthy control patients but not in PBMCs. In particular, upregulation in the expression of specific HERV families was detected in BALF samples of COVID-19 patients, with HERV-FRD being the most highly upregulated family among the families analyzed. In addition, we compared the expression of HERVs in human bronchial epithelial cells (HBECs) without and after senescence induction in an oncogene-induced senescence model in order to quantitatively measure changes in the expression of HERVs in bronchial cells during the process of cellular senescence. This apparent difference of HERV dysregulation between PBMCs and BALF warrants further studies in the involvement of HERVs in inflammatory pathogenetic mechanisms as well as exploration of HERVs as potential biomarkers for disease progression. Furthermore, the increase in the expression of HERVs in senescent HBECs in comparison to that in noninduced HBECs provides a potential link for increased COVID-19 severity and mortality in aged populations. IMPORTANCE SARS-CoV-2 emerged in late 2019 in China, causing a global pandemic. Severe COVID-19 is characterized by intensive inflammatory responses, and older age is an important risk factor for unfavorable outcomes. HERVs are remnants of ancient infections whose expression is upregulated in multiple conditions, including cancer and inflammation, and their expression is increased with increasing age. The significance of this work is that we were able to recognize dysregulated expression of endogenous retroviral elements in BALF samples but not in PBMCs of COVID-19 patients. At the same time, we were able to identify upregulated expression of multiple HERV families in senescence-induced HBECs in comparison to that in noninduced HBECs, a fact that could possibly explain the differences in disease severity among age groups. These results indicate that HERV expression might play a pathophysiological role in local inflammatory pathways in lungs afflicted by SARS-CoV-2 and their expression could be a potential therapeutic target.

Comparative Immunogenicity of BNT162b2 mRNA Vaccine with Natural SARS-CoV-2 Infection.

BNT162b2 has proven to be highly effective, but there is a paucity of data regarding immunogenicity factors and comparison between response to vaccination and natural infection. This study included 871 vaccinated healthcare workers (HCW) and 181 patients with natural infection. Immunogenicity was assessed by measuring anti-SARS-CoV-2 against the RBD domain of the spike protein (anti-RBD). Samples were collected 1-2 weeks after vaccination or 15-59 days post-onset of symptoms. Post-vaccine anti-RBD concentrations were associated with age, gender, vaccination side-effects (VSE) and prior infection (Pr-CoV). Anti-RBD median levels (95%CI) were lower by 2466 (651-5583), 6228 (3254-9203) and 7651 (4479-10,823) AU/mL in 35-44, 45-54, 55-70 yrs, respectively, compared with the 18-34 yrs group. In females, the median levels were higher by 2823 (859-4787), 5024 (3122-6926) in individuals with VSE, and 9971 (5158-14,783) AU/mL in HCWs with Pr-CoV. The ratio of anti-RBD in vaccinated individuals versus those with natural infection varied from 1.0 to 19.4. The high immunogenicity of BNT162b2 is verified, although its sustainability has yet to be elucidated. The use of comparative data from natural infection serological panels, expressing the clinical heterogeneity of natural infection, may facilitate early decisions for candidate vaccines to be evaluated in clinical trials.

Efficient and targeted COVID-19 border testing via reinforcement learning.

Throughout the coronavirus disease 2019 (COVID-19) pandemic, countries have relied on a variety of ad hoc border control protocols to allow for non-essential travel while safeguarding public health, from quarantining all travellers to restricting entry from select nations on the basis of population-level epidemiological metrics such as cases, deaths or testing positivity rates1,2. Here we report the design and performance of a reinforcement learning system, nicknamed Eva. In the summer of 2020, Eva was deployed across all Greek borders to limit the influx of asymptomatic travellers infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and to inform border policies through real-time estimates of COVID-19 prevalence. In contrast to country-wide protocols, Eva allocated Greece's limited testing resources on the basis of incoming travellers' demographic information and testing results from previous travellers. By comparing Eva's performance against modelled counterfactual scenarios, we show that Eva identified 1.85 times as many asymptomatic, infected travellers as random surveillance testing, with up to 2-4 times as many during peak travel, and 1.25-1.45 times as many asymptomatic, infected travellers as testing policies that utilize only epidemiological metrics. We demonstrate that this latter benefit arises, at least partially, because population-level epidemiological metrics had limited predictive value for the actual prevalence of SARS-CoV-2 among asymptomatic travellers and exhibited strong country-specific idiosyncrasies in the summer of 2020. Our results raise serious concerns on the effectiveness of country-agnostic internationally proposed border control policies3 that are based on population-level epidemiological metrics. Instead, our work represents a successful example of the potential of reinforcement learning and real-time data for safeguarding public health.

Molecular Epidemiology of SARS-CoV-2 in Greece Reveals Low Rates of Onward Virus Transmission after Lifting of Travel Restrictions Based on Risk Assessment during Summer 2020.

The novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread rapidly during the first months of 2020 and continues to expand in multiple areas across the globe. Molecular epidemiology has provided an added value to traditional public health tools by identifying SARS-CoV-2 clusters or providing evidence that clusters based on virus sequences and contact tracing are highly concordant. Our aim was to infer the levels of virus importation and to estimate the impact of public health measures related to travel restrictions to local transmission in Greece. Our phylogenetic and phylogeographic analyses included 389 full-genome SARS-CoV-2 sequences collected during the first 7 months of the pandemic in Greece and a random collection in five replicates of 3,000 sequences sampled globally, as well as the best hits to our data set identified by BLAST. Phylogenetic trees were reconstructed by the maximum likelihood method, and the putative source of SARS-CoV-2 infections was inferred by phylogeographic analysis. Phylogenetic analyses revealed the presence of 89 genetically distinct viruses identified as independent introductions into Greece. The proportion of imported strains was 41%, 11.5%, and 8.8% during the three periods of sampling, namely, March (no travel restrictions), April to June (strict travel restrictions), and July to September (lifting of travel restrictions based on thorough risk assessment), respectively. The results of phylogeographic analysis were confirmed by a Bayesian approach. Our findings reveal low levels of onward transmission from imported cases during summer and underscore the importance of targeted public health measures that can increase the safety of international travel during a pandemic. IMPORTANCE Our study based on current state-of-the-art molecular epidemiology methods suggests that virus screening and public health measures after the lifting of travel restrictions prevented SARS-CoV-2 onward transmission from imported cases during summer 2020 in Greece. These findings provide important data on the efficacy of targeted public health measures and have important implications regarding the safety of international travel during a pandemic. Our results can provide a roadmap about prevention policy in the future regarding the reopening of borders in the presence of differences in vaccination coverage, the circulation of the virus, and the presence of newly emergent variants across the globe.

SARS-CoV-2 Molecular Transmission Clusters and Containment Measures in Ten European Regions during the First Pandemic Wave.

BACKGROUND: The spatiotemporal profiling of molecular transmission clusters (MTCs) using viral genomic data can effectively identify transmission networks in order to inform public health actions targeting SARS-CoV-2 spread. METHODS: We used whole genome SARS-CoV-2 sequences derived from ten European regions belonging to eight countries to perform phylogenetic and phylodynamic analysis. We developed dedicated bioinformatics pipelines to identify regional MTCs and to assess demographic factors potentially associated with their formation. RESULTS: The total number and the scale of MTCs varied from small household clusters identified in all regions, to a super-spreading event found in Uusimaa-FI. Specific age groups were more likely to belong to MTCs in different regions. The clustered sequences referring to the age groups 50-100 years old (y.o.) were increased in all regions two weeks after the establishment of the lockdown, while those referring to the age group 0-19 y.o. decreased only in those regions where schools' closure was combined with a lockdown. CONCLUSIONS: The spatiotemporal profiling of the SARS-CoV-2 MTCs can be a useful tool to monitor the effectiveness of the interventions and to reveal cryptic transmissions that have not been identified through contact tracing.