First and second COVID-19 waves in Japan: A comparison of disease severity and characteristics

Changes in laboratory value improvement and mortality rates over the course of the pandemic: an international retrospective cohort study of hospitalised patients infected with SARS-CoV-2

OBJECTIVE

To assess changes in international mortality rates and laboratory recovery rates during hospitalisation for patients hospitalised with SARS-CoV-2 between the first wave (1 March to 30 June 2020) and the second wave (1 July 2020 to 31 January 2021) of the COVID-19 pandemic.

DESIGN, SETTING AND PARTICIPANTS

This is a retrospective cohort study of 83 178 hospitalised patients admitted between 7 days before or 14 days after PCR-confirmed SARS-CoV-2 infection within the Consortium for Clinical Characterization of COVID-19 by Electronic Health Record, an international multihealthcare system collaborative of 288 hospitals in the USA and Europe. The laboratory recovery rates and mortality rates over time were compared between the two waves of the pandemic.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome was all-cause mortality rate within 28 days after hospitalisation stratified by predicted low, medium and high mortality risk at baseline. The secondary outcome was the average rate of change in laboratory values during the first week of hospitalisation.

RESULTS

Baseline Charlson Comorbidity Index and laboratory values at admission were not significantly different between the first and second waves. The improvement in laboratory values over time was faster in the second wave compared with the first. The average C reactive protein rate of change was -4.72 mg/dL vs -4.14 mg/dL per day (p=0.05). The mortality rates within each risk category significantly decreased over time, with the most substantial decrease in the high-risk group (42.3% in March-April 2020 vs 30.8% in November 2020 to January 2021, p<0.001) and a moderate decrease in the intermediate-risk group (21.5% in March-April 2020 vs 14.3% in November 2020 to January 2021, p<0.001).

CONCLUSIONS

Admission profiles of patients hospitalised with SARS-CoV-2 infection did not differ greatly between the first and second waves of the pandemic, but there were notable differences in laboratory improvement rates during hospitalisation. Mortality risks among patients with similar risk profiles decreased over the course of the pandemic. The improvement in laboratory values and mortality risk was consistent across multiple countries.

HbA1c measurement may save COVID-19 inpatients from overlooked diabetes

Aims/Introduction

To investigate overlooked diabetes in patients with coronavirus disease 2019 (COVID‐19).

Materials and Methods

In total, 462 COVID‐19 inpatients were included in this retrospective study. The presence of diabetes before COVID‐19 admission, and the HbA1c and blood glucose levels at admission were examined.

Results

Of the 462 patients, 116 had diabetes. Seventy‐six patients had been diagnosed with diabetes before COVID‐19 admission, and 40 patients were diagnosed for the first time. Of the patients with diabetes 72% required insulin. Patients with diabetes were significantly (P < 0.05) older, more likely to be male, heavier, and showed a lower eGFR. Patients with overlooked diabetes showed a lower HbA1c (average 7.1% vs 7.5%), a lower casual blood glucose (average 157 vs 179 mg/dL), and they used less insulin per day during hospitalization (average 16.0 units vs 34.5 units) than patients with previously diagnosed diabetes. Patients with overlooked diabetes tended to have more severe COVID‐19 than those with pre‐diagnosed diabetes. Multivariable logistic regression analyses showed that the increased odds ratios (ORs) of aggravation in all patients with COVID‐19 were associated with age [OR 1.04], BMI [OR 1.05], and diabetes [OR 2.15]. The risk factors for aggravation in patients with COVID‐19 and diabetes were age [OR 1.05] and HbA1c [OR 1.45].

Conclusions

Diabetes is a predictor of COVID‐19 aggravation. Furthermore, in COVID‐19 patients with diabetes, high HbA1c levels are a risk factor for severe COVID‐19. A total of 8.7% of COVID‐19 inpatients were diagnosed with diabetes after HbA1c was measured on admission. Therefore, it is important to measure HbA1c in COVID‐19 patients.

A Comprehensive Comparison of Clinical Presentation and Outcomes of Kidney Transplant Recipients with COVID-19 during Wave 1 versus Wave 2 at a Tertiary Care Center, India

Data comparing the clinical spectrum of COVID-19 in kidney transplant recipients (KTRs) during the first and second waves of the pandemic in India is limited. Our single-center retrospective study compared the clinical profile, mortality, and associated risk factors in KTRs with COVID-19 during the 1st wave (1^st February 2020 to 31^st January 2021) and the second wave (1^st March-31^st August 2021). 156 KTRs with PCR confirmed SARS-CoV-2 infection treated at a tertiary care hospital in New Delhi during the 1st and the second waves were analyzed. The demographics and baseline transplant characteristics of the patients diagnosed during both waves were comparable. Patients in the second wave reported less frequent hospitalization, though the intensive care unit (ICU) and ventilator requirements were similar. Strategies to modify immunosuppressants such as discontinuation of antinucleoside drugs with or without change in calcineurin inhibitors and the use of steroids were similar during both waves. Overall patient mortality was 27.5%. The demographics and baseline characteristics of survivors and nonsurvivors were comparable. A higher percentage of nonsurvivors presented with breathing difficulty, low SpO₂, and altered sensorium. Both wave risk factors for mortality included older age, severe disease, ICU/ventilator requirements, acute kidney injury (AKI) needing dialysis, Chest Computerized Tomographic (CT) scan abnormalities, and higher levels of inflammatory markers particularly D-dimer and interleukin-6 levels. Conclusions. KTRs in both COVID-19 waves had similar demographics and baseline characteristics, while fewer patients during the second wave required hospitalization. The D-dimer and IL-6 levels are directly correlated with mortality.

The Effects of Playing Video Games on Stress, Anxiety, Depression, Loneliness, and Gaming Disorder During the Early Stages of the COVID-19 Pandemic: PRISMA Systematic Review

During the initial phases of the COVID-19 pandemic, playing video games has been much more than just a pastime. Studies suggested that video games for many individuals have helped to cope with such difficult life experience. However, other research indicates that gaming may have had harmful effects. Within this context, this systematic review aimed to describe the literature on the effects of video games during the early stages of the COVID-19 crisis on stress, anxiety, depression, loneliness, and gaming disorder (GD), examining the study characteristics and outcomes. A systematic search of the literature was made following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. It was preregistered in the International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY)-INPLASY202180053. The search databases were PsycINFO, Web of Science, and Medline. The search string was: [("video game*") OR ("computer game*") OR ("gaming")] AND [("COVID-19")]. Twenty-four studies met the inclusion criteria. Four research explored the effects of playing video games during the COVID-19 pandemic on stress, anxiety, and depression. Four studies investigated loneliness, while 18 research investigated game disorder. Video games, especially augmented reality and online multiplayer ones, mitigated stress, anxiety, depression, and loneliness among adolescents and young adults during stay-at-home restrictions. However, in the case of at-risk individuals (i.e., particularly male youths), playing video games had detrimental effects.

Comparison of Two Waves of COVID-19 in Critically Ill Patients: A Retrospective Observational Study

Background

The SARS-CoV-2 virus caused the global COVID-19 pandemic, with waxing and waning course. This study was conducted to compare outcomes in the first two waves, in mechanically ventilated patients.

Methods

This retrospective observational study included all mechanically ventilated COVID-19 patients above 18 years of age, between March 2020 and January 2021. Patients were grouped into first wave from March 2020 to July 2020, and second wave from August 2020 to January 2021. Outcome measures were mortality, the development of acute kidney injury (AKI), and need for renal replacement therapy (RRT). Univariate and multivariate cox regression analysis were used to delineate risk factors for the outcome measures.

Results

A total of 426 patients, 285 in the first wave and 185 in the second wave, were included. The incidence of AKI was significantly lower in the second wave (72% vs. 63%; p=0.04). There was no significant difference in mortality (70% vs. 63%; p=0.16) and need for RRT (36% vs. 30%; p=0.1). Risk factors for mortality were increasing age and AKI in both waves, and chronic kidney disease (CKD) (adj. HR 1.7; 95% CI 1.02-2.68; p=0.04) in the second wave. Risk factors for AKI were CKD in both the waves, while it was diabetes (adj. HR 1.4; 95% CI 1.02-1.95; p=0.04) and increasing age in the first wave. Remdesivir (adj. HR 0.5; 95% CI 0.3-0.7; p < 0.01) decreased the risk of AKI, and convalescent plasma (adj. HR 0.5; 95% CI 0.3-0.9; p=0.02) decreased the risk of mortality in the first wave, however, such benefit was not observed in the second wave.

Conclusions

Our study shows a decrease in the incidence of AKI in critically ill patients, however, the reason for this decrease is still unknown. Studies comparing the waves of the pandemic would not only help in understanding disease evolution but also to develop tailored management strategies.

Time trends in social contacts of individuals according to comorbidity and vaccination status, before and during the COVID-19 pandemic

BACKGROUND

As we are confronted with more transmissible/severe variants with immune escape and the waning of vaccine efficacy, it is particularly relevant to understand how the social contacts of individuals at greater risk of COVID-19 complications evolved over time. We described time trends in social contacts of individuals according to comorbidity and vaccination status before and during the first three waves of the COVID-19 pandemic in Quebec, Canada.

METHODS

We used data from CONNECT, a repeated cross-sectional population-based survey of social contacts conducted before (2018/2019) and during the pandemic (April 2020 to July 2021). We recruited non-institutionalized adults from Quebec, Canada, by random digit dialling. We used a self-administered web-based questionnaire to measure the number of social contacts of participants (two-way conversation at a distance ≤2 m or a physical contact, irrespective of masking). We compared the mean number of contacts/day according to the comorbidity status of participants (pre-existing medical conditions with symptoms/medication in the past 12 months) and 1-dose vaccination status during the third wave. All analyses were performed using weighted generalized linear models with a Poisson distribution and robust variance.

RESULTS

A total of 1441 and 5185 participants with and without comorbidities, respectively, were included in the analyses. Contacts significantly decreased from a mean of 6.1 (95%CI 4.9-7.3) before the pandemic to 3.2 (95%CI 2.5-3.9) during the first wave among individuals with comorbidities and from 8.1 (95%CI 7.3-9.0) to 2.7 (95%CI 2.2-3.2) among individuals without comorbidities. Individuals with comorbidities maintained fewer contacts than those without comorbidities in the second wave, with a significant difference before the Christmas 2020/2021 holidays (2.9 (95%CI 2.5-3.2) vs 3.9 (95%CI 3.5-4.3); P<0.001). During the third wave, contacts were similar for individuals with (4.1, 95%CI 3.4-4.7) and without comorbidities (4.5, 95%CI 4.1-4.9; P=0.27). This could be partly explained by individuals with comorbidities vaccinated with their first dose who increased their contacts to the level of those without comorbidities.

CONCLUSIONS

It will be important to closely monitor COVID-19-related outcomes and social contacts by comorbidity and vaccination status to inform targeted or population-based interventions (e.g., booster doses of the vaccine).

One Year of Lung Ultrasound in Children with SARS-CoV-2 Admitted to a Tertiary Referral Children's Hospital: A Retrospective Study during 2020-2021

During the COVID-19 pandemic, the lung ultrasound (LU) turned out to be a pivotal tool to study the lung involvement in the adult population, but the same was not well evaluated in children. We detected the LU patterns through an integrated approach with clinical−laboratory features in children hospitalized for COVID-19 in relation to the temporal trend of the Italian epidemic. We conducted a retrospective study which took place at a pediatric tertiary hospital from 15 March 2020 to 15 March 2021. We compared the characteristics of the initial phase of the first COVID-19 year—in the spring and summer (15 March−30 September 2020)—and those of the second phase—in the autumn and winter (1 October 2020−15 March 2021). Twenty-eight patients were studied both in the first and in the second phase of the first COVID-19 year. The disease severity score (DSS) was significantly greater in the second phase (p = 0.015). In the second phase of the first COVID-19 year, we detected a more significant occurrence of the following LU features than in the first phase: the irregular pleural line (85.71% vs. 60.71%; p = 0.035), the B-lines (89.29% vs. 60%; p = 0.003) and the several but non-coalescent B-lines (89.29% vs. 60%; p = 0.003). The LU score correlated significantly with the DSS, with a moderate relationship (r = 0.51, p < 0.001). The combined clinical, laboratory and ultrasound approaches might be essential in the evaluation of pulmonary involvement in children affected by COVID-19 during different periods of the pandemic.

Critically ill COVID-19 patients in northeast Brazil: mortality predictors during the first and second waves including SAPS 3

BACKGROUND

The Simplified Acute Physiology Score (SAPS) 3 is a reliable score to predict mortality. This study aims to investigate the predictive values of SAPS 3 and other clinical parameters for death in critically ill coronavirus disease 2019 (COVID-19) patients.

METHODS

This is a prospective study in a tertiary hospital for patients who required intensive care due to COVID-19 infection in northeast Brazil. Two distinct groups were constructed according to the epidemiological data: first wave and second wave. The severity of patients admitted was estimated using the SAPS 3 score.

RESULTS

A total of 767 patients were included: 290 were enrolled in the first wave and 477 in the second wave. Patients in the first wave had more comorbidities, were put on mechanical ventilation and required dialysis and vasopressors more frequently (p<0.05). During the second wave, non-invasive ventilation was more often required (p<0.05). In both periods, older patients and higher SAPS 3 scores on admission were associated with death (p<0.05). Non-invasive ventilation use showed a negative association with death only in the second wave period. In the first wave, the SAPS 3 score was more useful (area under the curve [AUC] 0.897) in predicting death in critically ill COVID-19 patients than in the second wave (AUC 0.810).

CONCLUSION

The SAPS 3 showed very reliable predictive values for death during the waves of the COVID-19 pandemic, mostly together with kidney and pulmonary dysfunction.

Comparison of the clinical presentation across two waves of COVID-19: a retrospective cohort study

BACKGROUND

Only a few studies have performed comprehensive comparisons between hospitalized patients from different waves of COVID-19. Thus, we aimed to compare the clinical characteristics and laboratory data of patients admitted to the western part of Denmark during the first and second waves of COVID-19 in 2020. Furthermore, we aimed to identify risk factors for critical COVID-19 disease and to describe the available information on the sources of infection.

METHODS

We performed a retrospective study of medical records from 311 consecutive hospitalized patients, 157 patients from wave 1 and 154 patients from wave 2. The period from March 7 to June 30, 2020, was considered wave 1, and the period from July 1st to December 31, 2020, was considered wave 2. Data are presented as the total study population, as a comparison between waves 1 and 2, and as a comparison between patients with and without critical COVID-19 disease (nonsurvivors and patients admitted to the intensive care unit (ICU)).

RESULTS

Patients admitted during the first COVID-19 wave experienced a more severe course of disease than patients admitted during wave 2. Admissions to the ICU and fatal disease were significantly higher among patients admitted during wave 1 compared to wave 2. The percentage of patients infected at hospital decreased in wave 2 compared to wave 1, whereas more patients were infected at home during wave 2. We found no significant differences in sociodemographics, lifestyle information, or laboratory data in the comparison of patients from waves 1 and 2. However, age, sex, smoking status, comorbidities, fever, and dyspnea were identified as risk factors for critical COVID-19 disease. Furthermore, we observed significantly increased levels of C-reactive protein and creatinine, and lower hemoglobin levels among patients with critical disease.

CONCLUSIONS

At admission, patients were more severely ill during wave 1 than during wave 2, and the outcomes were worse during wave 1. We confirmed previously identified risk factors for critical COVID-19 disease. In addition, we found that most COVID-19 infections were acquired at home.

Clinical characteristics of the first three waves of hospitalised patients with COVID-19 in Japan prior to the widespread use of vaccination: a nationwide observational study

Background

Before widespread coronavirus disease (COVID-19) vaccinations, Japan experienced three COVID-19 epidemic waves. This study aimed to evaluate the characteristics of hospitalised COVID-19 patients and reveal temporal changes.

Methods

This study included 33,554 hospitalised patients with COVID-19 from 553 healthcare facilities. Data were analysed by age group and epidemic wave (first wave, 01/01/2020-05/31/2020; second wave, 06/01/2020-10/31/2020; and third wave, 11/01/2020-03/31/2021).

Findings

By age group, 3% (under 18), 22% (young), 34% (middle-aged), and 41% (older patients) were aged 0-17, 18-39, 40-64, and >65 years; while 16%, 35%, and 49% were in the first, second, and third wave, respectively. The patients' overall median age (58 years; interquartile range, 39-74) was lowest and highest during the second and third waves, respectively. The frequency of any comorbidity was lowest and highest during the second (44·5%) and third (63·6%) waves, respectively. The symptoms at admission and exposure history differed considerably with age. The overall case fatality rate (5%) was highest among older patients (11·4%). Case fatality rate was highest and lowest during the first (7·3%) and second (2·8%) waves, respectively. Medication use changed over time.

Interpretation

Although the overall case fatality rate remained relatively low, it was more than twice as high among older patients. After adjusting for age and comorbidities, the risk of death was highest in the first wave.

Funding

This work was supported by the Ministry of Health, Labour and Welfare "Research on Emerging and Re-emerging Infectious Diseases and Immunization" 19HA1003].

Clinical outcome of neurological patients with COVID-19: the impact of healthcare organization improvement between waves

Objective

The aim of this study is to evaluate the differences in clinical presentations and the impact of healthcare organization on outcomes of neurological COVID-19 patients admitted during the first and second pandemic waves.

Methods

In this single-center cohort study, we included all patients with SARS-CoV-2 infection admitted to a Neuro-COVID Unit. Demographic, clinical, and laboratory data were compared between patients admitted during the first and second waves of the COVID-19 pandemic.

Results

Two hundred twenty-three patients were included, of whom 112 and 111 were hospitalized during the first and second pandemic waves, respectively. Patients admitted during the second wave were younger and exhibited pulmonary COVID-19 severity, resulting in less oxygen support (n = 41, 36.9% vs n = 79, 70.5%, p < 0.001) and lower mortality rates (14.4% vs 31.3%, p = 0.004). The different healthcare strategies and early steroid treatment emerged as significant predictors of mortality independently from age, pre-morbid conditions and COVID-19 severity in Cox regression analyses.

Conclusions

Differences in healthcare strategies during the second phase of the COVID-19 pandemic probably explain the differences in clinical outcomes independently of disease severity, underlying the importance of standardized early management of neurological patients with SARS-CoV-2 infection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10072-022-05946-8.

Impact of prioritized vaccinations for the elderly on the COVID-19 pandemic in Japan

The Japanese government implemented a large-scale vaccination policy against the coronavirus disease 2019 (COVID-19) pandemic, primarily using messenger RNA vaccines in 2021. Its hallmark was prioritized vaccination for the elderly after healthcare workers in a short period of time. Vaccination for the elderly, vulnerable to infection and severe disease, was carried out rapidly in approximately 4 months since April 2021. We evaluated the impact of Japan's vaccination policy against COVID-19 during the pandemic, with a particular focus on how prioritized vaccination for the elderly affected the pandemic. We observed a remarkable decrease in the number of infections, cluster events in long-term care facilities, and severe disease among the elderly during the fifth wave (August 2021) despite rising incidence of infections in the overall population. In conclusion, we think that prioritized vaccination for the elderly was efficacious in preventing infections and severe COVID-19 among the elderly during the fifth wave in Japan.

False-negative rate of SARS-CoV-2 RT-PCR tests and its relationship to test timing and illness severity: A case series

Objective

To determine the false-negative rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reverse-transcription polymerase chain reaction (RT-PCR) test results, and to describe the characteristics of coronavirus disease 2019 (COVID-19) patients with false-negative results.

Methods

We validated SARS-CoV-2-positive RT-PCR test results performed in hospitalized patients between February 1 and August 31, 2020 and classified the patients according to disease severity.

Results

In total, 2038 SARS-CoV-2 RT-PCR tests were performed on 1890 patients. Of these, 145 patients had positive results and were diagnosed with COVID-19. Among the 145 patients with COVID-19, the initial RT-PCR tests were negative in five patients. Of these, three had moderate illness and were initially tested in the early stage of disease, and two had severe illness and were initially tested in the late stage of disease, when RT-PCR testing has lower sensitivity due to viral clearance.

Conclusions

These findings suggest that false-negative results can be caused by both observer errors and by low viral RNA levels in the later stages of disease, after the infection has cleared. Clinicians should be aware that patients with COVID-19 can have negative RT-PCR test results in the later stages of infection.

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All SARS-CoV-2 RT-PCR test results of hospitalized COVID-19 patients were reviewed.

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Of 145 confirmed COVID-19 cases, 5 (3.45%) had a negative first RT-PCR test result.

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Of the 5 patients, 3 with moderate disease first tested soon after symptom onset.

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The initial testing was delayed in 2 patients with severe/critical disease.

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False-negative results can occur in deteriorating patients who have delayed testing.

High mortality of COVID-19 early after allogeneic stem cell transplantation – a retrospective multicenter analysis on behalf of the German Cooperative Transplant Study Group

Recipients of allogeneic stem cell transplantation (alloSCT) are at high risk for contracting infectious diseases with high morbidity and mortality. Coronavirus disease 2019 (COVID-19) is a viral respiratory disease that can lead to severe pneumonia and acute respiratory distress syndrome, with a potentially fatal outcome. In this retrospective study conducted on behalf of the German Cooperative Transplant Study Group, we aimed to analyze risk factors, disease course, and outcomes of COVID-19 in patients who underwent alloSCT. AlloSCT recipients who became infected with SARS-CoV-2 at German and Austrian transplant centers between February 2020 and July 2021 were included. Classification of COVID-19 severity into mild, moderate-severe, or critical disease and division of the course of the pandemic into 4 phases were done according to the German Robert Koch Institute. The main endpoint was overall mortality at the end of follow-up. We further analyzed the need for treatment in an intensive care unit (ICU) and the severity of disease. Risk factors were evaluated using univariate and multivariate analyses, and survival analysis was performed using Kaplan-Meier method. The study cohort comprised 130 patients from 14 transplant centers, with a median age at diagnosis of COVID-19 of 59 years (range, 20 to 81 years) and a median interval between alloSCT and COVID-19 of 787 days (range, 19 to 8138 days). The most common underlying diseases were acute myeloid leukemia (45.4%) and lymphoma (10.8%). The majority of patients (84.9%) were infected in the later phases of the pandemic; 20.8% had moderate-severe disease, 12.3% had critical disease, and 19.2% were treated in an ICU. After a median follow-up of 127 days, overall mortality was 16.2%, 52.0% among patients treated in an ICU. Risk factors for mortality in multivariate analysis were active disease (odds ratio [OR], 4.46), infection with SARS-CoV-2 ≤365 days after alloSCT (OR, 5.60), age >60 years (OR, 5.39), and ongoing immunosuppression with cyclosporine (OR, 8.55). Risk factors for developing moderate-severe or critical disease were concurrent immunosuppression (OR, 4.06) and age >40 years (OR, 4.08). Patients after alloSCT exhibit a substantially increased mortality risk after COVID-19 infection compared with the normal population, without considerable improvement over the course of the pandemic. Risk factors include age, early infection post-alloSCT, and active immunosuppression. Further studies are needed to improve prevention and treatment in this high-risk patient group.

Risk factors associated with hospital transfer among mild or asymptomatic COVID-19 patients in isolation facilities in Tokyo: a case-control study

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Facility-based isolation for COVID-19 in Tokyo involved remote health observation.

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This study was conducted in a prehospital setting using multivariable analysis.

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Older age, male sex, and higher BMI were associated with transfers to hospital.

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Comorbidities, such as bronchial asthma, increased the risk for hospital transfer.

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Some patients requiring urgent oxygenation showed few signs of dyspnea (silent hypoxia).

Objectives

The Tokyo Metropolitan Government has been implementing facility-based isolation of asymptomatic/mild coronavirus disease (COVID-19) patients to facilitate timely hospital referral. However, there are only a few published studies in prehospital settings, and the factors associated with hospital transfer are unclear. Our study identified the factors associated with COVID-19 deterioration in a prehospital setting.

Methods

This case-control study assessed the risk factors for hospital transfer from isolation facilities and the need for ambulance transport due to deterioration among COVID-19 patients, using multivariate logistic regression analysis.

Results

In total, 10 590 patients (median age 34 years), with male predominance (61.1%), were included. 367 (3.5%) were transferred to hospital, of whom 44 (12.0%) required ambulance transport. Hypertension, diabetes, and bronchial asthma were prevalent in 704 (6.6%), 195 (1.8%), and 305 (2.9%) patients, respectively. After adjustment, older age, male sex, higher body mass index (BMI), and comorbidities (including diabetes, inflammatory bowel disease, and bronchial asthma) were associated with hospital transfer. Older age, male sex, and higher BMI significantly increased the risk of transfer by ambulance.

Conclusions

Our results may be beneficial for the development of intervention measures for probable future COVID-19 waves.

Association between Frequency of Going Out and Psychological Condition among Community-Dwelling Older Adults after the COVID-19 Pandemic in Japan

Background: The psychological condition and frequency of going out (FGO) of community-dwelling older adults after the spread of COVID-19 will provide insights for supporting the daily lives of community-dwelling older adults. Going out is defined as moving from one’s own home to a place or region beyond one’s own home and is considered to reflect the daily and social life of community-dwelling older adults. This study investigates the relationship between the FGO and current psychological condition after the second wave of COVID-19 in community-dwelling older adults in Japan. Methods: This study adopted a self-administered questionnaire by mail. A total of 493 members of CO-OP Kagoshima were included in the analysis and divided into two groups according to the change in FGO. Multiple logistic regression analysis was conducted after a bivariate analysis to investigate the relationship between the FGO and psychological condition. Results: Significant differences were noted between the groups with decreased FGO and those with increased/unchanged FGO in general and pandemic-related psychological condition. Multiple logistic regression analysis showed a significant relationship between FGO and psychological condition, such as mental fatigue, not smiling as much as before, and anxiousness to go outside. Conclusion: Community-dwelling older adults may have experienced a decrease in the frequency of going out and a detrimental effect on their psychological condition after the COVID-19 pandemic. This finding may inform strategies to identify priorities for psychological approaches altered by COVID-19 to prevent confinement and stress in older adults.

Descriptive comparison of admission characteristics between pandemic waves and multivariable analysis of the association of the Alpha variant (B.1.1.7 lineage) of SARS-CoV-2 with disease severity in inner London

BACKGROUND

The Alpha variant (B.1.1.7 lineage) of SARS-CoV-2 emerged and became the dominant circulating variant in the UK in late 2020. Current literature is unclear on whether the Alpha variant is associated with increased severity. We linked clinical data with viral genome sequence data to compare admitted cases between SARS-CoV-2 waves in London and to investigate the association between the Alpha variant and the severity of disease.

METHODS

Clinical, demographic, laboratory and viral sequence data from electronic health record systems were collected for all cases with a positive SARS-CoV-2 RNA test between 13 March 2020 and 17 February 2021 in a multisite London healthcare institution. Multivariate analysis using logistic regression assessed risk factors for severity as defined by hypoxia at admission.

RESULTS

There were 5810 SARS-CoV-2 RNA-positive cases of which 2341 were admitted (838 in wave 1 and 1503 in wave 2). Both waves had a temporally aligned rise in nosocomial cases (96 in wave 1 and 137 in wave 2). The Alpha variant was first identified on 15 November 2020 and increased rapidly to comprise 400/472 (85%) of sequenced isolates from admitted cases in wave 2. A multivariate analysis identified risk factors for severity on admission, such as age (OR 1.02, 95% CI 1.01 to 1.03, for every year older; p<0.001), obesity (OR 1.70, 95% CI 1.28 to 2.26; p<0.001) and infection with the Alpha variant (OR 1.68, 95% CI 1.26 to 2.24; p<0.001).

CONCLUSIONS

Our analysis is the first in hospitalised cohorts to show increased severity of disease associated with the Alpha variant. The number of nosocomial cases was similar in both waves despite the introduction of many infection control interventions before wave 2.

Forecasting COVID-19 Case Trends Using SARIMA Models during the Third Wave of COVID-19 in Malaysia

With many countries experiencing a resurgence in COVID-19 cases, it is important to forecast disease trends to enable effective planning and implementation of control measures. This study aims to develop Seasonal Autoregressive Integrated Moving Average (SARIMA) models using 593 data points and smoothened case and covariate time-series data to generate a 28-day forecast of COVID-19 case trends during the third wave in Malaysia. SARIMA models were developed using COVID-19 case data sourced from the Ministry of Health Malaysia’s official website. Model training and validation was conducted from 22 January 2020 to 5 September 2021 using daily COVID-19 case data. The SARIMA model with the lowest root mean square error (RMSE), mean absolute percentage error (MAE) and Bayesian information criterion (BIC) was selected to generate forecasts from 6 September to 3 October 2021. The best SARIMA model with a RMSE = 73.374, MAE = 39.716 and BIC = 8.656 showed a downward trend of COVID-19 cases during the forecast period, wherein the observed daily cases were within the forecast range. The majority (89%) of the difference between the forecasted and observed values was well within a deviation range of 25%. Based on this work, we conclude that SARIMA models developed in this paper using 593 data points and smoothened data and sensitive covariates can generate accurate forecast of COVID-19 case trends.

Comparison of patient characteristics and in-hospital mortality between patients with COVID-19 in 2020 and those with influenza in 2017-2020: a multicenter, retrospective cohort study in Japan

Background

COVID-19 has worse mortality than influenza in American and European studies, but evidence from the Western Pacific region is scarce.

Methods

Using a large-scale multicenter inpatient claims data in Japan, we identified individuals hospitalised with COVID-19 in 2020 or influenza in 2017–2020. We compared patient characteristics, supportive care, and in-hospital mortality, with multivariable logistic regression analyses for in-hospital mortality overall, by age group, and among patients with mechanical ventilation.

Findings

We identified 16,790 COVID-19 patients and 27,870 influenza patients, with the different age distribution (peak at 70–89 years in COVID-19 vs. bimodal peaks at 0–9 and 80–89 years in influenza). On admission, the use of mechanical ventilation was similar in both groups (1·4% vs. 1·4%) but higher in the COVID-19 group (3·3% vs. 2·5%; p<0·0001) during the entire hospitalisation. The crude in-hospital mortality was 5·1% (856/16,790) for COVID-19 and 2·8% (791/27,870) for influenza. Adjusted for potential confounders, the in-hospital mortality was higher for COVID-19 than for influenza (adjusted odds ratio [aOR] 1·83, 95% confidence interval [CI] 1·64–2·04). In age-stratified analyses, the aOR (95%CI) were 0·78 (0·56–1·08) and 2·05 (1·83–2·30) in patients aged 20–69 years and ≥70 years, respectively (p-for-interaction<0·0001). Among patients with mechanical ventilation, the aOR was 0·79 (0·59–1·05).

Interpretation

Patients hospitalised with COVID-19 in Japan were more likely to die than those with influenza. However, this was mainly driven by findings in older people, and there was no difference once mechanical ventilation was started.

Funding

Ministry of Health, Labour and Welfare of Japan (21AA2007).

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.

Trends in all-cause mortality of hospitalized patients due to SARS-CoV-2 infection from a monocentric cohort in Milan (Lombardy, Italy)

Background

Robust data on case fatality rate (CFR) among inpatients with COVID-19 are still lacking, and the role of patient characteristics in in-hospital deaths remains under-investigated. This study quantified the overall CFR and described its trend in a cohort of hospitalized patients with SARS-CoV-2 in Italy. Admission to ICU, death, or discharge were the secondary outcomes.

Methods

This retrospective study is based on administrative health data and electronic case records of inpatients consecutively admitted to Niguarda Hospital between 21 February and 8 November 2020.

Results

An overall CFR of 18% was observed. CFR was significantly reduced during the second wave of contagion (1 June to 30 September, 16%) compared with the first wave (21 February to 31 May, 21% p = 0.015). Such reduction was mainly observed among male inpatients between 40 and 80 years with limited comorbidities. Admission to ICU was associated with a high risk of mortality in both waves. The incidence of severe disease and the need for ICU admission were lower in the second wave.

Conclusion

CFR in SARS-CoV-2 inpatients was demonstrated to decrease over time. This reduction may partly reflect the changes in hospital strategy and clinical practice. The reasons for this improvement should be further investigated to plan an exit strategy in case of future outbreaks.

Key messages

What is already known on this topic

Before the advent of anti-COVID-19 vaccines, a multi-wave pattern of contagion was observed, and this trend conditioned the inpatient case fatality rate (CFR), which varied over time accordingly to the waves of contagion.

Only preliminary results on the in-hospital mortality trend are available, along with a partial analysis of its determinants. Consequently, robust data on CFR among inpatients with SARS-CoV-2 infection are still lacking, and the role of patient characteristics in in-hospital deaths remains under-investigated.

What this study adds

This study shows that the in-hospital mortality in patients with SARS-CoV-2 infection decreases over time.

Such reduction was mainly observed among male inpatients between 40 and 80 years with limited comorbidities. Admission to ICU was invariably associated with a high risk of mortality during the whole study period (21 February to 8 November 2020), but the incidence of severe disease and the need for ICU admission were lower in the second wave of contagions (1 October to 8 November 2020). This reduction may partly reflect the impact of changes in hospital strategy and clinical practice. The reasons for this improvement should be further investigated to inform the response to future outbreaks and to plan exit strategy by prioritizing high-risk populations.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10389-021-01675-y.

First and second waves among hospitalised patients with COVID-19 with severe pneumonia: a comparison of 28-day mortality over the 1-year pandemic in a tertiary university hospital in Italy

OBJECTIVE

The first COVID-19-19 epidemic wave was over the period of February-May 2020. Since 1 October 2020, Italy, as many other European countries, faced a second wave. The aim of this analysis was to compare the 28-day mortality between the two waves among COVID-19 hospitalised patients.

DESIGN

Observational cohort study. Standard survival analysis was performed to compare all-cause mortality within 28 days after hospital admission in the two waves. Kaplan-Meier curves as well as Cox regression model analysis were used. The effect of wave on risk of death was shown by means of HRs with 95% CIs. A sensitivity analysis around the impact of the circulating variant as a potential unmeasured confounder was performed.

SETTING

University Hospital of Modena, Italy. Patients admitted to the hospital for severe COVID-19 pneumonia during the first (22 February-31 May 2020) and second (1 October-31 December 2020) waves were included.

RESULTS

During the two study periods, a total of 1472 patients with severe COVID-19 pneumonia were admitted to our hospital, 449 during the first wave and 1023 during the second. Median age was 70 years (IQR 56-80), 37% women, 49% with PaO2/FiO2 <250 mm Hg, 82% with ≥1 comorbidity, median duration of symptoms was 6 days. 28-day mortality rate was 20.0% (95% CI 16.3 to 23.7) during the first wave vs 14.2% (95% CI 12.0 to 16.3) in the second (log-rank test p value=0.03). After including key predictors of death in the multivariable Cox regression model, the data still strongly suggested a lower 28-day mortality rate in the second wave (aHR=0.64, 95% CI 0.45 to 0.90, p value=0.01).

CONCLUSIONS

In our hospitalised patients with COVID-19 with severe pneumonia, the 28-day mortality appeared to be reduced by 36% during the second as compared with the first wave. Further studies are needed to identify factors that may have contributed to this improved survival.

Correlation of AKI with risk factors, ventilatory support, renal replacement therapy in a cohort of COVID-19 patients

Introduction:

There is a scarcity of information on the incidence and outcomes of acute kidney injury (AKI) in COVID-19 patients in India. Therefore, we analyzed the correlation of AKI risk factors, ventilatory support, and renal replacement therapy and compared the outcomes of first and second COVID-19 waves in this tertiary care center.

Methods:

We retrospectively analyzed the patients' medical records with a positive RT-PCR for COVID-19 between July 2020 and May 2021. We looked at the clinical outcomes of the first and second COVID-19 waves and documented the frequency, risk factors for AKI, and the relationship between AKI and in-hospital mortality. Univariate and multivariate binomial logistic regression yielded odds ratios for the risk variables of AKI. Risk differences and age-adjusted odds ratios, as well as 99.5% confidence intervals, were used to compare COVID-19 outcomes between the first and second waves.

Results:

Of the 1260 hospitalized patients with COVID-19, 86 (6.8%) presented with AKI and 8 (0.7%) patients required dialysis. The most common comorbidity was diabetes mellitus (55.2%), hypertension (42.1%), hypothyroidism (11.3%), and coronary artery disease (8.1%). A total of 229 (18.17%) patients were admitted to ICU, 574 (45.5%) received ventilation, and 26 (2.0%) required mechanical ventilation.The incidence of in-hospital death in the patients with AKI as per the stage from 1 to 3 was 9 (15.8%), 7 (35%), and 5 (55.6%), respectively.Compared to the first wave, the second wave cohort had a lower risk of AKI (adj OR: 0.426; CI: 0.232–0.782) and mortality (adj OR: 0.252; CI: 0.090–0.707).

Conclusions:

In our study, AKI prevalence was 6.8%, the need for ventilation was 45.5%, ECMO 0.2%, and the mortality rate 2.9%. Second wave of COVID-19 exhibits improved clinical outcomes compared to the first wave.

COVID-19 Pulmonary Pathology: The Experience of European Pulmonary Pathologists throughout the First Two Waves of the Pandemic

Autoptic studies of patients who died from COVID-19 constitute an important step forward in improving our knowledge in the pathophysiology of SARS-CoV-2 infection. Systematic analyses of lung tissue, the organ primarily targeted by the disease, were mostly performed during the first wave of the pandemic. Analyses of pathological lesions at different times offer a good opportunity to better understand the disease and how its evolution has been influenced mostly by new SARS-CoV-2 variants or the different therapeutic approaches. In this short report we summarize responses collected from a questionnaire survey that investigated important pathological data during the first two pandemic waves (spring-summer 2020; autumn-winter 2020–2021). The survey was submitted to expert lung pathologists from nine European countries involved in autoptic procedures in both pandemic waves. The frequency of each lung lesion was quite heterogeneous among the participants. However, a higher frequency of pulmonary superinfections, both bacterial and especially fungal, was observed in the second wave compared to the first. Obtaining a deeper knowledge of the pathological lesions at the basis of this complex and severe disease, which change over time, is crucial for correct patient management and treatment. Autoptic examination is a useful tool to achieve this goal.

The mechanism of governments' and individuals' influence on protective behaviours during the second wave of COVID-19: a multiple mediation model

Background: The SARS-CoV-2 virus continues to spread and resurge globally with signs of a second wave, despite actions by governments to curb the COVID-19 pandemic. However, evidence-based strategies to combat COVID-19 recurrence are poorly documented. Objective: To reveal how governments and individuals should act to effectively cope with future waves, this study proposed a preventive model of COVID-19 resurgence. Method: A questionnaire survey was conducted among 1,137 residents of Beijing, where the epidemic reoccurred. Structural equation model was used to explore the mechanism among government intervention, perceived efficacy, positive emotions, posttraumatic growth (PTG) and protective behaviours. Results: Data analysis revealed that during COVID-19 resurgence, government intervention could directly and indirectly influence protective behaviours through individual factors (i.e. perceived efficacy, positive emotions), and PTG could mediate the indirect pathway to protective behaviours. Conclusions: These findings implied that government intervention needs to be integrated with individual factors to effectively control repeated COVID-19 outbreaks.

Outcomes in neonates born to mothers with COVID-19 during the second wave in India

COVID-19 pandemic has affected all age groups globally including pregnant women and their neonates. The aim of the study was to understand outcomes in neonates of mothers with COVID-19 during the first and second waves of COVID-19 pandemic. A retrospective analysis of 2524 neonates born to SARS-CoV-2-infected mothers was conducted during the first wave (n = 1782) and second wave (n = 742) of the COVID-19 pandemic at five study sites of the PregCovid registry in Maharashtra, India. A significant difference was noted in preterm birth, which was higher in the second wave (15.0%, 111/742) compared to the first wave (7.8%, 139/1782) (P < 0.001). The proportion of neonates requiring NICU admission was significantly higher in the second wave (19.0%, 141/742) as compared to that in the first wave (14.8%, 264/1782) (P < 0.05). On comparing regional differences, significantly higher neonatal complications were reported from Mumbai metropolitan region (P < 0.05). During the second wave of COVID-19, birth asphyxia and prematurity were 3.8- and 2.1-fold higher respectively (P < 0.001). Neonatal resuscitation at birth was significantly higher in second wave (3.4%, 25/742 vs 1.8%, 32/1782) (P < 0.05). The prevalence of SARS-CoV-2 infection in neonates was comparable (4.2% vs 4.6%) with no significant difference between the two waves.

CONCLUSION

Higher incidence of adverse outcomes in neonates born to SARS-CoV-2-infected mothers in the second wave of COVID-19 as compared to the first wave.

TRIAL REGISTRATION

PregCovid study is registered with the Clinical Trial Registry of India (CTRI/2020/05/025423, Registered on 28/05/2020).

WHAT IS KNOWN

• The second wave of COVID-19 was more lethal to pregnant women than the first wave. Newborns are at risk of developing complications.

WHAT IS NEW

• Birth asphyxia, prematurity, and neonatal resuscitation at birth were significantly higher in the second wave as compared to those in the first wave of the COVID-19 pandemic in India.

Comparison of patients with severe COVID-19 admitted to an intensive care unit in South Africa during the first and second wave of the COVID-19 pandemic

Background

The second wave of coronavirus disease 2019 (COVID-19), dominated by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Beta variant, has been reported to be associated with increased severity in South Africa (SA).

Objectives

To describe and compare clinical characteristics, management and outcomes of COVID-19 patients admitted to an intensive care unit (ICU) in SA during the first and second waves.

Methods

In a prospective, single-centre, descriptive study, we compared all patients with severe COVID-19 admitted to ICU during the first and second waves. The primary outcomes assessed were ICU mortality and ICU length of stay (LOS).

Results

In 490 patients with comparable ages and comorbidities, no difference in mortality was demonstrated during the second compared with the first wave (65.9% v. 62.5%, p=0.57). ICU LOS was longer in the second wave (10 v. 6 days, p<0.001). More female admissions (67.1% v. 44.6%, p<0.001) and a greater proportion of patients were managed with invasive mechanical ventilation than with non-invasive respiratory support (39.0% v. 14%, p<0.001) in the second wave.

Conclusion

While clinical characteristics were comparable between the two waves, a higher proportion of patients was invasively ventilated and ICU stay was longer in the second. ICU mortality was unchanged.

Mid-Regional Pro-Adrenomedullin, Methemoglobin and Carboxyhemoglobin as Prognosis Biomarkers in Critically Ill Patients with COVID-19: An Observational Prospective Study

Mid-regional pro-adrenomedullin (MR-proADM), methemoglobin (MetHb), and carboxyhemoglobin (COHb) levels have been associated with sepsis. In this study, we assessed the role of this potential biomarkers in critically ill COVID-19 patients. Outcomes were mortality and a combined event (mortality, venous or arterial thrombosis, and orotracheal intubation (OTI)) during a 30-day follow-up. A total of 95 consecutive patients were included, 51.6% required OTI, 12.6% patients died, 8.4% developed VTE, and 3.1% developed arterial thrombosis. MetHb and COHb levels were not associated with mortality nor combined event. Higher MR-proADM levels were found in patients with mortality (median of 1.21 [interquartile range-IQR-0.84;2.33] nmol/L vs. 0.76 [IQR 0.60;1.03] nmol/L, p = 0.011) and combined event (median of 0.91 [IQR 0.66;1.39] nmol/L vs. 0.70 [IQR 0.51;0.82] nmol/L, p < 0.001); the positive likelihood ratio (LR+) and negative likelihood ratio (LR−) for mortality were 2.40 and 0.46, respectively. The LR+ and LR− for combined event were 3.16 and 0.63, respectively. MR-proADM ≥1 nmol/L was the optimal cut-off for mortality and combined event prediction. The predictive capacity of MR-proADM showed an area under the ROC curve of 0.73 (95% CI, 0.62–0.81) and 0.72 (95% CI, 0.62–0.81) for mortality and combined event, respectively. In conclusion, elevated on-admission MR-proADM levels were associated with higher risk of 30-day mortality and 30-day poor outcomes in a cohort of critically ill patients with COVID-19.

Status of online diet management program users in Japan during the 2020 Coronavirus disease 2019 pandemic

The spread of coronavirus disease 2019 (COVID-19) has led to drastic changes in people’s lifestyles, including teleworking and restrictions on socializing. In the context of observing social distancing for preventing infection, the need to maintain fitness and health has attracted particular attention. We aimed to determine the relationship between the increase in the number of active users of online diet management applications and COVID-19 infection rates in Japan. A total of 1.5 million rows of log data was analyzed. The active number of users of online diet management applications increased with increase in the number of COVID-19 infections. The active user number in Kanagawa Prefecture, where the first cases of COVID-19 were reported in Japan, was particularly high. Moreover, there was a significant increase in the user number in prefectures under a state of emergency when compared to that in prefectures not under a state of emergency. The social anxiety caused by COVID-19 is expected to increase the demand for online health management applications further. The use of such programs can aid in achieving social distancing while enabling users to maintain healthy lifestyles.

Analysis of Covid-19 Hospital Admissions in Ivano-Frankivsk, Ukraine

The Covid-19 pandemic has a substantial impact on socioeconomic, political, demographic, and other aspects of life. Effective healthcare is, however, a primary determinant of successful fighting against Covid-19. The analysis of local healthcare indicators serves as a source for estimating pandemic magnitude and the adaptation of healthcare at a national level. In this study, the rates of Covid-19 hospital admissions to the Ivano-Frankivsk City Hospital, Ukraine, from April 2020 to May 2021 were analysed. All cases were grouped by age, sex, and the type of admission; data were analyzed monthly and seasonally. The peaks of hospital admissions were observed in November 2020 and March 2021; however, the highest mortality rates were seen from August to November 2020. The analysis of age- and sex-disaggregated Covid-19 mortality data showed the predominance of elderly males (61.9%, 66.6 ± 3.9 years) over females (38.1%, 71.8 ± 2.3 years). The ratio of hospital admissions was unstable: the percentage of emergency, GP-referred and self-referred admissions was similar from April to May 2020; however, GP-referred admissions prevailed, and the number of self-referral patients decreased twice between March and May 2021. In conclusions, the trends in hospital admissions were similar to those reported in other studies. However, the differences in time frames and socio-demographic characteristics were observed that highlights the importance of considering regional, social and geographic aspects of the population when improving the capacity of healthcare system and establishing effective preventive measures against the pandemic at the local level.

Mortality due to COVID-19 infection: A comparison of first and second waves

Background

The USA suffered an initial wave of COVID-19 cases from March to July in 2020. Cases again surged in August 2020 as business restrictions were lifted. We aimed to describe demographic, treatment, and mortality differences between both waves.

Methods

We identified all hospitalized patients with COVID-19 infection in one US six-hospital health system between 1 March 2020 and 31 January 2021. We compared data obtained on patient demographics, treatment received, and mortality between first and second waves of the pandemic.

Results

A total of 4434 hospitalized COVID patients were identified, including 1313 patients in the first wave and 3121 patients in the second wave. Mortality was significantly higher in the first wave as compared to the second wave (23.2% vs. 12.3%, p < 0.001). Age and sex were similar in each wave. In the first wave, there were significantly more Non-Hispanic Black patients (28.8 vs. 18.1%, p < 0.001) and Hispanic patients (26.6% vs. 14.9%, p < 0.001) as compared to the second wave. There was a higher mortality rate in the first wave as compared to the second, which persisted after multivariable adjustment for sex, age, ethnicity, laboratory results at admission, treatment received, high flow use and mechanical ventilation (OR: 2.66, 95% CI: 1.83–3.87, p < 0.001).

Conclusion

Mortality in the second wave was lower than the first wave with significantly higher utilization of steroids, remdesivir and convalescent plasma in second wave.

Epidemiological comparison of the first and second waves of the COVID-19 pandemic in Nigeria, February 2020-April 2021

Background

With reports of surges in COVID-19 case numbers across over 50 countries, country-level epidemiological analysis is required to inform context-appropriate response strategies for containment and mitigation of the outbreak. We aimed to compare the epidemiological features of the first and second waves of COVID-19 in Nigeria.

Methods

We conducted a retrospective analysis of the Surveillance Outbreak Response Management and Analysis System data of the first and second epidemiological waves, which were between 27 February and 24 October 2020, and 25 October 2020 to 3 April 2021, respectively. Descriptive statistical measures including frequencies and percentages, test positivity rate (TPR), cumulative incidence (CI) and case fatality rates (CFRs) were compared. A p value of <0.05 was considered statistically significant. All statistical analyses were carried out in STATA V.13.

Results

There were 802 143 tests recorded during the study period (362 550 and 439 593 in the first and second waves, respectively). Of these, 66 121 (18.2%) and 91 644 (20.8%) tested positive in the first and second waves, respectively. There was a 21.3% increase in the number of tests conducted in the second wave with TPR increasing by 14.3%. CI during the first and second waves were 30.3/100 000 and 42.0/100 000 respectively. During the second wave, confirmed COVID-19 cases increased among females and people 30 years old or younger and decreased among urban residents and individuals with travel history within 14 days of sample collection (p value <0.001). Most confirmed cases were asymptomatic at diagnosis during both waves: 74.9% in the first wave; 79.7% in the second wave. CFR decreased during the second wave (0.7%) compared with the first wave (1.8%).

Conclusion

Nigeria experienced a larger but less severe second wave of COVID-19. Continued implementation of public health and social measures is needed to mitigate the resurgence of another wave.

Delays in Presentation Time Under the COVID-19 Epidemic in Patients With Transient Ischemic Attack and Mild Stroke: A Retrospective Study of Three Hospitals in a Japanese Prefecture

Background: Coronavirus Disease 2019 (COVID-19) has spread worldwide with collateral damage and therefore might affect the behavior of stroke patients with mild symptoms seeking medical attention.

Methods: Patients with ischemic stroke who were admitted to hospitals within 7 days of onset were retrospectively registered. The clinical characteristics, including onset-to-door time (ODT), of patients with a transient ischemic attack (TIA)/mild stroke (National Institutes of Health Stroke Scale [NIHSS] score of ≤ 3 on admission) or moderate/severe stroke were compared between those admitted from April 2019 to March 2020 (pre-COVID-19 period) and from April to September 2020 (COVID-19 period). Multivariable regression analysis was performed to identify factors associated with the ODT.

Results: Of 1,100 patients (732 men, median age, 73 years), 754 were admitted during the pre-COVID-19 period, and 346 were admitted during the COVID-19 period. The number and proportion of patients with TIA/minor stroke were 464 (61.5%) in the pre-COVID-19 period and 216 (62.4%) during the COVID-19 period. Among patients with TIA/mild stroke, the ODT was longer in patients admitted during the COVID-19 period compared with that of the pre-COVID-19 period (median 864 min vs. 508 min, p = 0.003). Multivariable analysis revealed the COVID-19 period of admission was associated with longer ODT (standardized partial regression coefficient 0.09, p = 0.003) after adjustment for age, sex, route of arrival, NIHSS score on admission, and the presence of hypertension, diabetes mellitus, and wake-up stroke. No significant change in the ODT was seen in patients with moderate/severe stroke.

Conclusions: The COVID-19 epidemic might increase the ODT of patients with TIA/mild stroke.

First and second COVID-19 waves in Brazil: A cross-sectional study of patients' characteristics related to hospitalization and in-hospital mortality

Background

Background The second wave of the COVID-19 pandemic was more aggressive in Brazil compared to other countries around the globe. Considering the Brazilian peculiarities, we analyze the in-hospital mortality concerning socio-epidemiological characteristics of patients and the health system of all states during the first and second waves of COVID-19.

Methods

We performed a cross-sectional study of hospitalized patients with positive RT-PCR for SARS-CoV-2 in Brazil. Data was obtained from the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) and comprised the period from February 25, 2020, to April 30, 2021, separated in two waves on November 5, 2020. We performed a descriptive study of patients analyzing socio-demographic characteristics, symptoms, comorbidities, and risk factors stratified by age. In addition, we analyzed in-hospital and intensive care unit (ICU) mortality in both waves and how it varies in each Brazilian state.

Findings

Between February 25, 2020 and April 30, 2021, 678 235 patients were admitted with a positive RT-PCR for SARS-CoV-2, with 325 903 and 352 332 patients for the first and second wave, respectively. The mean age of patients was 59·65 (IQR 48·0 - 72·0). In total, 379 817 (56·00%) patients had a risk factor or comorbidity. In-hospital mortality increased from 34·81% in the first to 39·30% in the second wave. In the second wave, there were more ICU admissions, use of non-invasive and invasive ventilation, and increased mortality for younger age groups. The southern and southeastern regions of Brazil had the highest hospitalization rates per 100 000 inhabitants. However, the in-hospital mortality rate was higher in the northern and northeastern states of the country. Racial differences were observed in clinical outcomes, with White being the most prevalent hospitalized population, but with Blacks/Browns (Pardos) having higher mortality rates. Younger age groups had more considerable differences in mortality as compared to groups with and without comorbidities in both waves.

Interpretation

We observed a more considerable burden on the Brazilian hospital system throughout the second wave. Furthermore, the north and northeast of Brazil, which present lower Human Development Indexes, concentrated the worst in-hospital mortality rates. The highest mortality rates are also shown among vulnerable social groups. Finally, we believe that the results can help to understand the behavior of the COVID-19 pandemic in Brazil, helping to define public policies, allocate resources, and improve strategies for vaccination of priority groups.

Funding

Coordinating Agency for Advanced Training of Graduate Personnel (CAPES) (C.F. 001), and National Council for Scientific and Technological Development (CNPq) (No. 309537/2020-7).

Cytokine signature and COVID-19 prediction models in the two waves of pandemics

In Europe, multiple waves of infections with SARS-CoV-2 (COVID-19) have been observed. Here, we have investigated whether common patterns of cytokines could be detected in individuals with mild and severe forms of COVID-19 in two pandemic waves, and whether machine learning approach could be useful to identify the best predictors. An increasing trend of multiple cytokines was observed in patients with mild or severe/critical symptoms of COVID-19, compared with healthy volunteers. Linear Discriminant Analysis (LDA) clearly recognized the three groups based on cytokine patterns. Classification and Regression Tree (CART) further indicated that IL-6 discriminated controls and COVID-19 patients, whilst IL-8 defined disease severity. During the second wave of pandemics, a less intense cytokine storm was observed, as compared with the first. IL-6 was the most robust predictor of infection and discriminated moderate COVID-19 patients from healthy controls, regardless of epidemic peak curve. Thus, serum cytokine patterns provide biomarkers useful for COVID-19 diagnosis and prognosis. Further definition of individual cytokines may allow to envision novel therapeutic options and pave the way to set up innovative diagnostic tools.

Mortality among adult hospitalized patients during the first wave and second wave of COVID-19 pandemic at a tertiary care center in India

The similarities and differences between the mortality patterns of the two waves in India remain largely unknown. This was a retrospective study of medical records conducted in the COVID data center of our hospital This study analyzed data of patients who died in the month of August, 2020 to October 2020 (one month before and after the peak of first wave i.e., 16th September, 2020) & April 2021 to June 2021 (one month before and after the peak of second wave i.e., 6th May, 2021), corresponding to an equal part of the pandemic during first (2020) and second (2021) wave. Out of 1893 patients in the study, 764 patients were admitted during the first wave and 1129 patients during the second wave of pandemic. In total, 420 patients died during the entire study period. Of those, 147 (35%) deaths occurred during the first wave and 273 (65%) during the second wave, reflecting a case fatality rate (CFR) of 19.2% during the first wave and a CFR of 24.18%. There were no significant differences in the Age Group, Gender, Presenting Complaints, Duration of Stay and Comorbidities. However, the deceased COVID-19 patients had an increase in Case Fatality Rate, average duration of symptoms from onset to Hospital Admission (DOSHA) and a major shift from MODS to ARDS being the Cause of Death during the second wave of Pandemic. This study demonstrates increased CFR, average DOSHA and a paradigm shift to ARDS as cause of mortality during the second peak of the Pandemic. It is necessary to remain vigilant of newer COVID-19 variants of concern, follow COVID-19 appropriate behaviors and keep emphasizing on care of high-risk groups including patients with comorbidities and elderly population to prevent mortality.

International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study

Background

Many countries have experienced 2 predominant waves of COVID-19–related hospitalizations. Comparing the clinical trajectories of patients hospitalized in separate waves of the pandemic enables further understanding of the evolving epidemiology, pathophysiology, and health care dynamics of the COVID-19 pandemic.

Objective

In this retrospective cohort study, we analyzed electronic health record (EHR) data from patients with SARS-CoV-2 infections hospitalized in participating health care systems representing 315 hospitals across 6 countries. We compared hospitalization rates, severe COVID-19 risk, and mean laboratory values between patients hospitalized during the first and second waves of the pandemic.

Methods

Using a federated approach, each participating health care system extracted patient-level clinical data on their first and second wave cohorts and submitted aggregated data to the central site. Data quality control steps were adopted at the central site to correct for implausible values and harmonize units. Statistical analyses were performed by computing individual health care system effect sizes and synthesizing these using random effect meta-analyses to account for heterogeneity. We focused the laboratory analysis on C-reactive protein (CRP), ferritin, fibrinogen, procalcitonin, D-dimer, and creatinine based on their reported associations with severe COVID-19.

Results

Data were available for 79,613 patients, of which 32,467 were hospitalized in the first wave and 47,146 in the second wave. The prevalence of male patients and patients aged 50 to 69 years decreased significantly between the first and second waves. Patients hospitalized in the second wave had a 9.9% reduction in the risk of severe COVID-19 compared to patients hospitalized in the first wave (95% CI 8.5%-11.3%). Demographic subgroup analyses indicated that patients aged 26 to 49 years and 50 to 69 years; male and female patients; and black patients had significantly lower risk for severe disease in the second wave than in the first wave. At admission, the mean values of CRP were significantly lower in the second wave than in the first wave. On the seventh hospital day, the mean values of CRP, ferritin, fibrinogen, and procalcitonin were significantly lower in the second wave than in the first wave. In general, countries exhibited variable changes in laboratory testing rates from the first to the second wave. At admission, there was a significantly higher testing rate for D-dimer in France, Germany, and Spain.

Conclusions

Patients hospitalized in the second wave were at significantly lower risk for severe COVID-19. This corresponded to mean laboratory values in the second wave that were more likely to be in typical physiological ranges on the seventh hospital day compared to the first wave. Our federated approach demonstrated the feasibility and power of harmonizing heterogeneous EHR data from multiple international health care systems to rapidly conduct large-scale studies to characterize how COVID-19 clinical trajectories evolve.

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.

Using machine learning for predicting intensive care unit resource use during the COVID-19 pandemic in Denmark

The COVID-19 pandemic has put massive strains on hospitals, and tools to guide hospital planners in resource allocation during the ebbs and flows of the pandemic are urgently needed. We investigate whether machine learning (ML) can be used for predictions of intensive care requirements a fixed number of days into the future. Retrospective design where health Records from 42,526 SARS-CoV-2 positive patients in Denmark was extracted. Random Forest (RF) models were trained to predict risk of ICU admission and use of mechanical ventilation after n days (n = 1, 2, …, 15). An extended analysis was provided for n = 5 and n = 10. Models predicted n-day risk of ICU admission with an area under the receiver operator characteristic curve (ROC-AUC) between 0.981 and 0.995, and n-day risk of use of ventilation with an ROC-AUC between 0.982 and 0.997. The corresponding n-day forecasting models predicted the needed ICU capacity with a coefficient of determination (R2) between 0.334 and 0.989 and use of ventilation with an R2 between 0.446 and 0.973. The forecasting models performed worst, when forecasting many days into the future (for large n). For n = 5, ICU capacity was predicted with ROC-AUC 0.990 and R2 0.928, and use of ventilator was predicted with ROC-AUC 0.994 and R2 0.854. Random Forest-based modelling can be used for accurate n-day forecasting predictions of ICU resource requirements, when n is not too large.

Fewer COVID-19-associated strokes and reduced severity during the second COVID-19 wave: The Madrid Stroke Network

Background and purpose

The experience gained during the first COVID‐19 wave could have mitigated the negative impact on stroke care in the following waves. Our aims were to analyze the characteristics and outcomes of patients with stroke admitted during the second COVID‐19 wave and to evaluate the differences in the stroke care provision compared with the first wave.

Methods

This retrospective multicenter cohort study included consecutive stroke patients admitted to any of the seven hospitals with stroke units (SUs) and endovascular treatment facilities in the Madrid Health Region. The characteristics of the stroke patients with or without a COVID‐19 diagnosis were compared and the organizational changes in stroke care between the first wave (25 February to 25 April 2020) and second wave (21 July to 21 November 2020) were analyzed.

Results

A total of 550 and 1191 stroke patients were admitted during the first and second COVID‐19 waves, respectively, with an average daily admission rate of nine patients in both waves. During the second wave, there was a decrease in stroke severity (median National Institutes of Health Stroke Scale 5 vs. 6; p = 0.000), in‐hospital strokes (3% vs. 8.1%) and in‐hospital mortality (9.9% vs. 15.9%). Furthermore, fewer patients experienced concurrent COVID‐19 (6.8% vs. 19.1%), and they presented milder COVID‐19 and less severe strokes. Fewer hospitals reported a reduction in the number of SU beds or deployment of SU personnel to COVID‐19 dedicated wards during the second wave.

Conclusions

During the second COVID‐19 wave, fewer stroke patients were diagnosed with COVID‐19, and they had less stroke severity and milder COVID‐19.

Effect of mutation and vaccination on spread, severity, and mortality of COVID-19 disease

Coronavirus disease 2019 (COVID‐19) has had different waves within the same country. The spread rate and severity showed different properties within the COVID‐19 different waves. The present work aims to compare the spread and the severity of the different waves using the available data of confirmed COVID‐19 cases and death cases. Real‐data sets collected from the Johns Hopkins University Center for Systems Science were used to perform a comparative study between COVID‐19 different waves in 12 countries with the highest total performed tests for severe acute respiratory syndrome coronavirus 2 detection in the world (Italy, Brazil, Japan, Germany, Spain, India, USA, UAE, Poland, Colombia, Turkey, and Switzerland). The total number of confirmed cases and death cases in different waves of COVID‐19 were compared to that of the previous one for equivalent periods. The total number of death cases in each wave was presented as a percentage of the total number of confirmed cases for the same periods. In all the selected 12 countries, Wave 2 had a much higher number of confirmed cases than that in Wave 1. However, the death cases increase was not comparable with that of the confirmed cases to the extent that some countries had lower death cases than in Wave 1, UAE, and Spain. The death cases as a percentage of the total number of confirmed cases in Wave 1 were much higher than that in Wave 2. Some countries have had Waves 3 and 4. Waves 3 and 4 have had lower confirmed cases than Wave 2, however, the death cases were variable in different countries. The death cases in Waves 3 and 4 were similar to or higher than Wave 2 in most countries. Wave 2 of COVID‐19 had a much higher spread rate but much lower severity resulting in a lower death rate in Wave 2 compared with that of the first wave. Waves 3 and 4 have had lower confirmed cases than Wave 2; that could be due to the presence of appropriate treatment and vaccination. However, that was not reflected in the death cases, which were similar to or higher than Wave 2 in most countries. Further studies are needed to explain these findings.

Clinical characteristics of the first and second COVID-19 waves in the Bronx, New York: A retrospective cohort study

Background

There is limited clinical patient data comparing the first and second waves of the coronavirus disease 2019 (COVID-19) in the United States and the effects of a COVID-19 resurgence on different age, racial and ethnic groups. We compared the first and second COVID-19 waves in the Bronx, New York, among a racially and ethnically diverse population.

Methods

Patients in this retrospective cohort study were included if they had a laboratory-confirmed SARS-CoV-2 infection by a real-time PCR test of a nasopharyngeal swab specimen detected between March 11, 2020, and January 21, 2021. Main outcome measures were critical care, in-hospital acquired disease and death. Patient demographics, comorbidities, vitals, and laboratory values were also collected.

Findings

A total of 122,983 individuals were tested for SARS-CoV-2 infection, of which 12,659 tested positive. The second wave was characterized by a younger demographic, fewer comorbidities, less extreme laboratory values at presentation, and lower risk of adverse outcomes, including in-hospital mortality (adj. OR = 0·23, 99·5% CI = 0·17 to 0·30), hospitalization (adj. OR = 0·65, 99·5% CI = 0·58 to 0·74), invasive mechanical ventilation (adj. OR = 0·70, 99·5% CI = 0·56 to 0·89), acute kidney injury (adj. OR = 0·62, 99·5% CI = 0·54 to 0·71), and length of stay (adj. OR = 0·71, 99·5% CI = 0·60 to 0·85), with Black and Hispanic patients demonstrating most improvement in clinical outcomes.

Interpretation

The second COVID-19 wave in the Bronx exhibits improved clinical outcomes compared to the first wave across all age, racial, and ethnic groups, with minority groups showing more improvement, which is encouraging news in the battle against health disparities.

A data driven agent-based model that recommends non-pharmaceutical interventions to suppress Coronavirus disease 2019 resurgence in megacities

Before herd immunity against Coronavirus disease 2019 (COVID-19) is achieved by mass vaccination, science-based guidelines for non-pharmaceutical interventions are urgently needed to reopen megacities. This study integrated massive mobile phone tracking records, census data and building characteristics into a spatially explicit agent-based model to simulate COVID-19 spread among 11.2 million individuals living in Shenzhen City, China. After validation by local epidemiological observations, the model was used to assess the probability of COVID-19 resurgence if sporadic cases occurred in a fully reopened city. Combined scenarios of three critical non-pharmaceutical interventions (contact tracing, mask wearing and prompt testing) were assessed at various levels of public compliance. Our results show a greater than 50% chance of disease resurgence if the city reopened without contact tracing. However, tracing household contacts, in combination with mandatory mask use and prompt testing, could suppress the probability of resurgence under 5% within four weeks. If household contact tracing could be expanded to work/class group members, the COVID resurgence could be avoided if 80% of the population wear facemasks and 40% comply with prompt testing. Our assessment, including modelling for different scenarios, helps public health practitioners tailor interventions within Shenzhen City and other world megacities under a variety of suppression timelines, risk tolerance, healthcare capacity and public compliance.

Predicting respiratory failure for COVID-19 patients in Japan: a simple clinical score for evaluating the need for hospitalisation

Predicting the need for hospitalisation of patients with coronavirus disease 2019 (COVID-19) is important for preventing healthcare disruptions. This observational study aimed to use the COVID-19 Registry Japan (COVIREGI-JP) to develop a simple scoring system to predict respiratory failure due to COVID-19 using only underlying diseases and symptoms. A total of 6873 patients with COVID-19 admitted to Japanese medical institutions between 1 June 2020 and 2 December 2020 were included and divided into derivation and validation cohorts according to the date of admission. We used multivariable logistic regression analysis to create a simple risk score model, with respiratory failure as the outcome for young (18-39 years), middle-aged (40-64 years) and older (≥65 years) groups, using sex, age, body mass index, medical history and symptoms. The models selected for each age group were quite different. Areas under the receiver operating characteristic curves for the simple risk score model were 0.87, 0.79 and 0.80 for young, middle-aged and elderly derivation cohorts, and 0.81, 0.80 and 0.67 in the validation cohorts. Calibration of the model was good. The simple scoring system may be useful in the appropriate allocation of medical resources during the COVID-19 pandemic.

Estimating the Impact of the COVID-19 Pandemic on Maternal and Perinatal Health Care Services in Italy: Results of a Self-Administered Survey

The coronavirus disease 2019 (COVID-19) pandemic is strongly changing the way most people live their lives, and disrupting specialist healthcare systems. Such public health disruptions have resulted in significant collateral damage with particular implications for vulnerable populations, including the perinatal population. This Study aims to estimate the impact of the COVID-19 pandemic on Italian maternal and perinatal health care services. A questionnaire was designed to evaluate the COVID-19 impact on Italian maternal and perinatal healthcare facilities and their activities and provision of services from March to May 2020. The survey was completed by hospital-based and community-based Italian maternal and perinatal healthcare facilities. Most of these were located in Lombardy or Veneto (the most affected Italian regions). 70% of all facilities reported that the first wave of the COVID-19 pandemic negatively influenced the functioning of one or more aspects of the perinatal service; only 28.4% of facilities all over the country continued to provide outpatient routine visits and examinations as usual; 23.4% of facilities became understaffed during the index period due to various reasons such as ward transfer and sick leave. This is the first Italian study, and among very few international studies that describe the effects of the COVID-19 pandemic on antenatal and postnatal healthcare facilities and their provision of activities and services. Our findings confirm that healthcare systems even in high-income countries were not entirely prepared to handle such a global health emergency; indeed, specialized maternal and perinatal healthcare services have been disrupted by this global health emergency.

Epidemiology of Coronavirus Disease 2019 in Japan: Descriptive Findings and Lessons Learned through Surveillance during the First Three Waves

Introduction

Coronavirus disease 2019 (COVID-19) has caused unprecedented global morbidity and mortality. Japan has faced three epidemic "waves" of COVID-19 from early 2020 through early 2021. Here we narratively review the three waves in Japan, describe the key epidemiologic features of COVID-19, and discuss lessons learned.

Methods

We assessed publicly available surveillance data, routine surveillance reports, and other relevant sources-multiple indicators were monitored to improve interpretation of surveillance data. Weekly trends for each wave were described based on the number of case notifications; number of tests performed; proportion of those tests that were positive for the novel coronavirus; the prevalent number of COVID-19 hospitalizations (total hospitalizations and those categorized as severe); and number of COVID-19 deaths. For each indicator and wave, we recorded the first calendar week to show an increase over two consecutive previous weeks, along with the peak week.

Results

The spring wave was characterized by detection of cases imported from China, followed by notifications of sporadic cases without travel history, clusters, and mild/asymptomatic cases. The summer wave saw a large increase in notifications and a younger age distribution, but in the context of increased testing with lower test positivity. The winter wave brought considerable morbidity and mortality, surpassing the cumulative case counts and fatalities from the earlier waves, with high peak values. Overall, relative to the first wave, the burden of severe outcomes was lower in the second and higher in the third wave, but varied by prefecture. In all three waves, severe outcomes peaked after notification counts and test positivity peaked; severe outcomes were also consistently skewed toward the elderly.

Conclusions

Important lessons were learned from each wave and across waves-some aspects remained constant, while others changed over time. In order to rapidly detect an increase in incidence, continuous, timely, and sensitive surveillance-using multiple information sources with careful interpretations-will be key in COVID-19 control.

Clinical profile of hospitalized COVID-19 patients in first & second wave of the pandemic: Insights from an Indian registry based observational study

Background & objectives:

India witnessed a massive second surge of COVID-19 cases since March 2021 after a period of decline from September 2020. Data collected under the National Clinical Registry for COVID-19 (NCRC) were analysed to describe the differences in demographic and clinical features of COVID-19 patients recruited during these two successive waves.

Methods:

The NCRC, launched in September 2020, is an ongoing multicentre observational initiative, which provided the platform for the current investigation. Demographic, clinical, treatment and outcome data of hospitalized, confirmed COVID-19 patients were captured in an electronic data portal from 41 hospitals across India. Patients enrolled during September 1, 2020 to January 31, 2021 and February 1 to May 11, 2021 constituted participants of the two successive waves, respectively.

Results:

As on May 11, 2021, 18961 individuals were recruited in the registry, 12059 and 6903 reflecting in-patients from the first and second waves, respectively. Mean age of the patients was significantly lower in the second wave [48.7 (18.1) yr vs. 50.7 (18.0) yr, P<0.001] with higher proportion of patients in the younger age group intervals of <20, and 20-39 yr. Approximately 70 per cent of the admitted patients were ≥ 40 yr of age in both waves of the pandemic. The proportion of males were slightly lower in second wave as compared to the first [4400 (63.7%) vs. 7886 (65.4%), P=0.02]. Commonest presenting symptom was fever in both waves. In the second wave, a significantly higher proportion [2625 (48.6%) vs. 4420 (42.8%), P<0.003] complained of shortness of breath, developed ARDS [422(13%) vs. 880 (7.9%), P<0.001], required supplemental oxygen [1637 (50.3%) vs. 4771 (42.7%), P<0.001], and mechanical ventilation [260 (15.9%) vs. 530 (11.1%), P<0.001]. Mortality also significantly increased in the second wave [OR: 1.35 (95% CI: 1.19, 1.52)] in all age groups except in <20 yr.

Interpretation & conclusions:

The second wave of COVID-19 in India was slightly different in presentation than the first wave, with a younger demography, lesser comorbidities, and presentation with breathlessness in greater frequency.