Withdrawn: COVID-19: A global and continental overview of the second wave and its (relatively) attenuated case fatality ratio

Analysis of patient outcomes after urological surgery during the second and third waves of SARS-CoV-2 pandemic in a high incidence area

OBJECTIVE

To analyze surgical safety through postoperative COVID-19 incidence and mortality at the urology department of a tertiary hospital located in Madrid (Spain).

METHODS

Observational, prospective study including all patients undergoing urological surgery from 1st March 2020 to 28th February 2021. According to the hospital organization and local epidemiological situation we delimitate three epidemic waves. A set of screening and protective measures was applied from 4th May onwards. Demographic, baseline, surgical and perioperative variables, as well as postoperative outcomes, were collected. Telephone follow-up was performed at least 3 weeks after hospital discharge.

RESULTS

940 urological surgeries were performed, 12 of them had to be rescheduled due to active or recent SARS-CoV-2 infection identified by the screening protocol. Thirty-one patients developed COVID-19 (3.3% incidence) and 7 died (22.6% mortality). The average time to onset of symptoms was 62.6 days after discharge, being 25 cases attributable to community transmission. The remaining 6 cases, due to in-hospital transmission, had worse outcomes. Five of them were identified during the first wave, especially when no preoperative PCR was obtained. In contrast, during the second and third waves, fewer and milder cases were diagnosed, with just 1 in-hospital transmission among 857 urological patients.

CONCLUSIONS

After implementing complete protective measures, postoperative in-hospital COVID-19 cases almost disappeared, even during the second and third waves. Most of the cases were due to community transmission and thus driven by the general epidemiological situation. While hospitals follow recommendations to avoid COVID-19 infection, urological surgery remains safe and can be maintained.

Individuals With SARS-CoV-2 Infection During the First and Second Waves in Catalonia, Spain: Retrospective Observational Study Using Daily Updated Data

BACKGROUND

A description of individuals with SARS-CoV-2 infection comparing the first and second waves could help adapt health services to manage this highly transmissible infection.

OBJECTIVE

We aimed to describe the epidemiology of individuals with suspected SARS-CoV-2 infection, and the characteristics of patients with a positive test comparing the first and second waves in Catalonia, Spain.

METHODS

This study had 2 stages. First, we analyzed daily updated data on SARS-CoV-2 infection in individuals from Girona (Catalonia). Second, we compared 2 retrospective cohorts of patients with a positive reverse-transcription polymerase chain reaction or rapid antigen test for SARS-CoV-2. The severity of patients with a positive test was defined by their admission to hospital, admission to intermediate respiratory care, admission to the intensive care unit, or death. The first wave was from March 1, 2020, to June 24, 2020, and the second wave was from June 25, 2020, to December 8, 2020.

RESULTS

The numbers of tests and cases were lower in the first wave than in the second wave (26,096 tests and 3140 cases in the first wave versus 140,332 tests and 11,800 cases in the second wave), but the percentage of positive results was higher in the first wave than in the second wave (12.0% versus 8.4%). Among individuals with a positive diagnostic test, 818 needed hospitalization in the first wave and 680 in the second; however, the percentage of hospitalized individuals was higher in the first wave than in the second wave (26.1% versus 5.8%). The group that was not admitted to hospital included older people and those with a higher percentage of comorbidities in the first wave, whereas the characteristics of the groups admitted to hospital were more alike.

CONCLUSIONS

Screening systems for SARS-CoV-2 infection were scarce during the first wave, but were more adequate during the second wave, reflecting the usefulness of surveillance systems to detect a high number of asymptomatic infected individuals and their contacts, to help control this pandemic. The characteristics of individuals with SARS-CoV-2 infection in the first and second waves differed substantially; individuals in the first wave were older and had a worse health condition.

COVID-19 pandemic in the Arctic and Subarctic

The pandemic caused by the deadly Coronavirus has spread across the entire world, impacting the lives and livelihood of billions of people living in different regions. Even the Arctic and Subarctic regions are also not exempted from the spread and effect of this pandemic. In this study, we emphasize the COVID-19 pandemic situation of the Arctic and Subarctic regions. Even though the population density of these regions is significantly less, the eminent impact due to COVID-19 remains the same, perhaps more, considering the harsh weather, less communication, and health facilities. We have analyzed seasonal pandemic scenarios, risks, governance responses, and resilience of the locals as well as governments in and around the Arctic and Subarctic regions of Canada, Finland, Greenland, Iceland, Norway, Russia, Sweden, and the United States (Alaska). Despite these regions being extreme, the results reveal that the devastating effect of the pandemic remains almost the same at par with the context of the significantly lower population density. However, the governance shows a silver lining during this period, proving that humankind can win any battle for its sustenance with proper governance and management actions.

COVID-19 second wave: District level study of concentration of confirmed cases and fatality in India

The paper aims to reveal the spatial pattern of the concentration of COVID-19 confirmed cases and the spread of the pandemic from the Case Fatality Ratio. The study has been accomplished with district-level data. The analysis of the spatial pattern decoding has been done considering the Global and Local Moran's I statistics comprising the linear trend of spatial autocorrelation for the whole India. The timeframe has been divided considering the surge of the second wave in March, 2021 and the peak of the wave in May 2021. The spatial clustering technique presents both the concentration of confirmed cases using Location Quotient analysis and the pattern of spread of the infection-related fatality throughout the country. The high Location Quotient of the confirmed cases strongly clustered around the Mumbai-Puna region, Kerala-Karnataka region, Garhwal Himachal, NCT of Delhi and Ladakh-Kashmir-Himachal Pradesh region during the period of the study. In May, the concentration has randomly clustered around the middle part of India. The Case Fatality Ratio was high in Maharashtra, Madhya Pradesh, Punjab and Haryana at the surge of the second wave. During the peak (May), two significant clusters of high Case Fatality Ratio are observed in and around the Mumbai urban (Maharashtra) and NCT of Delhi (including Punjab-Haryana).

Saving Resources: SARS-CoV-2 Diagnostics by Real-Time RT-PCR Using Reduced Reaction Volumes

Since the beginning of 2020, the betacoronavirus SARS-CoV-2 is causing a global pandemic of an acute respiratory disease termed COVID-19. The diagnostics of the novel disease is primarily based on direct virus detection by RT-PCR; however, the availability of test kits may become a major bottleneck, when millions of tests are performed per week. To increase the flexibility of SARS-CoV-2 diagnostics, three real-time RT-PCR assays listed on the homepage of the World Health Organization were selected and investigated regarding their compatibility with three different RT-PCR kits. Furthermore, the reaction volume of the PCR chemistry was reduced up to half of the original protocol to make the individual reactions more cost- and resource-effective. When testing dilution series of culture-grown virus, nearly identical quantification cycle values (Cq) were obtained for all RT-PCR assay/chemistry combinations. Regarding the SARS-CoV-2 detection in clinical samples, agreeing results were obtained for all combinations for virus negative specimens and swabs containing high to medium viral genome loads. In cases of very low SARS-CoV-2 genome loads (Cq > 36), inconsistent results were observed, with some test runs scoring negative and some positive. However, no preference of a specific target within the viral genome (E, RdRp, or N) or of a certain chemistry was seen. In summary, a reduction of the reaction volume and the type of PCR chemistry did not influence the PCR sensitivity.

Comparing community mobility reduction between first and second COVID-19 waves

BACKGROUND

In this paper, we conduct a mobility reduction rate comparison between the first and second COVID-19 waves in several localities from America and Europe using Google community mobility reports (CMR) data. Through multi-dimensional visualization, we are able to compare the reduction in mobility from the different lockdown periods for each locality selected, simultaneously considering multiple place categories provided in CMR. In addition, our analysis comprises a 56-day lockdown period for each locality and COVID-19 wave, which we analyze both as 56-day periods and as 14-day consecutive windows.

METHODS

We use locality-wise calibrated CMR data, which we process through seasonal-trend decomposition by LOESS (STL) to isolate trend from seasonal and noise effects. We scale trend data to draw Pareto-compliant conclusions using radar charts. For each temporal granularity considered, data for a given place category is aggregated using the area under the curve (AUC) approach.

RESULTS

In general, reduction rates observed during the first wave were much higher than during the second. Alarmingly, December holiday season mobility in some of the localities reached pre-pandemic levels for some of the place categories reported. Manaus was the only locality where second wave mobility was nearly as reduced as during the first wave, likely due to the P1 variant outbreak and oxygen supply crisis.

Clinical features of patients who had two COVID-19 episodes: a European multicentre case series

OBJECTIVE

To investigate the clinical features of patients who had two demonstrated coronavirus disease 2019 (COVID-19) episodes.

METHODS

Data of patients with both COVID-19 episodes were recruited from 22 March to 27 December 2020. The following outcomes were studied: epidemiological, comorbidities, prevalence and severity of general and otolaryngological symptom, olfactory, aroma, and gustatory dysfunctions. A comparison between first and second episodes was performed.

RESULTS

Forty-five patients reported having two confirmed COVID-19 episodes. The majority of patients had mild infections in both episodes. The second clinical episode was significantly similar to the first. The symptom duration of the second episode was shorter than the first. The occurrence of loss of smell was unpredictable from the first to the second episode.

CONCLUSION

The recurrence of COVID-19 symptoms is associated with a similar clinical picture than the first episode in patients with initial mild-to-moderate COVID episode. The pathophysiological mechanisms underlying the development of second episode remain uncertain and may involve either true reinfection or virus reactivation from sanctuaries.

Surveillance of the Second Wave of COVID-19 in Europe: Longitudinal Trend Analyses

BACKGROUND

The COVID-19 pandemic has severely impacted Europe, resulting in a high caseload and deaths that varied by country. The second wave of the COVID-19 pandemic has breached the borders of Europe. Public health surveillance is necessary to inform policy and guide leaders.

OBJECTIVE

This study aimed to provide advanced surveillance metrics for COVID-19 transmission that account for weekly shifts in the pandemic, speed, acceleration, jerk, and persistence, to better understand countries at risk for explosive growth and those that are managing the pandemic effectively.

METHODS

We performed a longitudinal trend analysis and extracted 62 days of COVID-19 data from public health registries. We used an empirical difference equation to measure the daily number of cases in Europe as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R.

RESULTS

New COVID-19 cases slightly decreased from 158,741 (week 1, January 4-10, 2021) to 152,064 (week 2, January 11-17, 2021), and cumulative cases increased from 22,507,271 (week 1) to 23,890,761 (week 2), with a weekly increase of 1,383,490 between January 10 and January 17. France, Germany, Italy, Spain, and the United Kingdom had the largest 7-day moving averages for new cases during week 1. During week 2, the 7-day moving average for France and Spain increased. From week 1 to week 2, the speed decreased (37.72 to 33.02 per 100,000), acceleration decreased (0.39 to -0.16 per 100,000), and jerk increased (-1.30 to 1.37 per 100,000).

CONCLUSIONS

The United Kingdom, Spain, and Portugal, in particular, are at risk for a rapid expansion in COVID-19 transmission. An examination of the European region suggests that there was a decrease in the COVID-19 caseload between January 4 and January 17, 2021. Unfortunately, the rates of jerk, which were negative for Europe at the beginning of the month, reversed course and became positive, despite decreases in speed and acceleration. Finally, the 7-day persistence rate was higher during week 2 than during week 1. These measures indicate that the second wave of the pandemic may be subsiding, but some countries remain at risk for new outbreaks and increased transmission in the absence of rapid policy responses.

COVID-19 Dynamics: A Heterogeneous Model

The mathematical model reported here describes the dynamics of the ongoing coronavirus disease 2019 (COVID-19) epidemic, which is different in many aspects from the previous severe acute respiratory syndrome (SARS) epidemic. We developed this model when the COVID-19 epidemic was at its early phase. We reasoned that, with our model, the effects of different measures could be assessed for infection control. Unlike the homogeneous models, our model accounts for human population heterogeneity, where subpopulations (e.g., age groups) have different infection risks. The heterogeneous model estimates several characteristics of the epidemic more accurately compared to the homogeneous models. According to our analysis, the total number of infections and their peak number are lower compared to the assessment with the homogeneous models. Furthermore, the early-stage infection increase is little changed when population heterogeneity is considered, whereas the late-stage infection decrease slows. The model predicts that the anti-epidemic measures, like the ones undertaken in China and the rest of the world, decrease the basic reproductive number but do not result in the development of a sufficient collective immunity, which poses a risk of a second wave. More recent developments confirmed our conclusion that the epidemic has a high likelihood to restart after the quarantine measures are lifted.