Comparative Study Between the First and Second Wave of COVID-19 Deaths in India: A Single Center Study.

Introduction  The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is continuously evolving, and many mutant variants of the virus are circulating in the world. Recurrent waves of COVID-19 have caused enormous mortality all across the globe. Considering the novelty of the virus, it becomes crucial for healthcare experts and policymakers to understand the demographic and clinical attributes of inpatient deaths in the first and second waves of COVID-19. Methods This hospital record-based comparative study was conducted at a tertiary care hospital in Uttarakhand, India. The study included all COVID-19 RT PCR-positive patients admitted to the hospital during the first wave, from 1st April 2020 to 31st January 2021, and the second wave from 1st March 2021 to 30th June 2021. Comparisons were made with respect to demographic, clinical, laboratory parameters, and course of hospital stay. Results The study exhibited 11.34% more casualties in the second wave, with the number of deaths being 424 and 475 for the first and second waves, respectively. A male preponderance of mortality was evident in both waves with significant differences (p=0.004). There was no significant difference in age between the two waves (p=0.809). The significantly different comorbidities were hypertension (p=0.003) and coronary artery disease (p=0.014). The clinical manifestations demonstrating a significant difference were cough (p=0.000), sore throat (p=0.002), altered mental status (p=0.002), headache (p=0.025), loss of taste and smell (p=0.001), and tachypnea (p=0.000). The lab parameters with a significant difference across both waves were lymphopenia (p=0.000), elevated aspartate aminotransferase (p=0.004), leukocytosis (p=0.008), and thrombocytopenia (p=0.004). During the hospital course of the second wave, in terms of intensive care unit stay, the need for non-invasive ventilation and inotrope support was higher. The complications manifesting in the form of acute respiratory distress syndrome and sepsis were observed more in the second wave. A significant difference was discerned in the median duration of hospital stay in both waves (p=0.000). Conclusion Despite being of shorter duration, the second wave of COVID-19 culminated in more deaths. The study demonstrated that most of the baseline demographic and clinical characteristics attributed to mortality were more common during the second wave of COVID-19, including lab parameters, complications, and duration of hospital stays. The unpredictable nature of COVID-19 waves calls for instituting a well-planned surveillance mechanism in place to identify the surge in cases at the earliest possible time and prompt response, along with developing infrastructure and capacity to manage complications.

Geographic Patterns of COVID-19 Vaccination, Infection, and Mortality in the United States During Year Two of the Pandemic and the Influence of Political Orientations

The second year of the COVID-19 (SARS-CoV-2) pandemic in the United States witnessed the widespread availability of effective vaccines and a new presidential administration promising a more coherent and science-based approach. Despite this, the US in 2021 also experienced a continued series of waves in infection and mortality, driven in part by the emergence of the more transmittable Delta and Omicron variants. As was the case in 2020, the magnitude of per-capita infection and mortality varied substantially between states in 2021. State vaccination rates also showed appreciable geographic variations and were significantly negatively correlated with infection rates and strongly so with death rates. Wave severity through 2021 differed somewhat across climatic zones, consistent with weather-induced behavioral changes influencing transmission. Political orientation appears to be an important factor contributing to geographic variations in the pandemic. In particular, the percentage of voters who supported the Republican presidential candidate in the 2020 election was strongly negatively correlated with states' vaccination rates and positively correlated with death rates. The political divide on vaccination contributes to interstate geographic differences in the outcomes of the pandemic and poses an ongoing challenge to combating COVID-19 in the United States. © TheEditor(s) (ifapplicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021, 2022.

Temporal variation of excess deaths from diabetes during the COVID-19 pandemic in the United States.

BACKGROUND: Although the COVID-19 pandemic has persisted for more than two years with the evident excess mortality from diabetes, few studies have investigated its temporal patterns. This study aims to estimate the excess deaths from diabetes in the United States (US) during the COVID-19 pandemic and evaluate the excess deaths by spatiotemporal pattern, age groups, sex, and race/ethnicity. METHODS: Diabetes as one of multiple causes of death or an underlying cause of death were both considered into analyses. The Poisson log-linear regression model was used to estimate weekly expected counts of deaths during the pandemic with adjustments for long-term trend and seasonality. Excess deaths were measured by the difference between observed and expected death counts, including weekly average excess deaths, excess death rate, and excess risk. We calculated the excess estimates by pandemic wave, US state, and demographic characteristic. RESULTS: From March 2020 to March 2022, deaths that diabetes as one of multiple causes of death and an underlying cause of death were about 47.6 % and 18.4 % higher than the expected. The excess deaths of diabetes had evident temporal patterns with two large percentage increases observed during March 2020, to June 2020, and June 2021 to November 2021. The regional heterogeneity and underlying age and racial/ethnic disparities of the excess deaths were also clearly observed. CONCLUSIONS: This study highlighted the increased risks of diabetes mortality, heterogeneous spatiotemporal patterns, and associated demographic disparities during the pandemic. Practical actions are warranted to monitor disease progression, and lessen health disparities in patients with diabetes during the COVID-19 pandemic.

Comparison of the epidemiological features of COVID-19 patients in the first and second waves: A study from South India.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has seen multiple surges globally since its emergence in 2019. The second wave of the pandemic was generally more aggressive than the first, with more cases and deaths. This study compares the epidemiological features of the first and second COVID-19 waves in Kozhikode district of Kerala and identifies the factors associated with this change. Methods: A comparative cross-sectional study was conducted in Kozhikode district. A total of 132,089 cases from each wave were selected for the study using a consecutive sampling method. Data were collected from the District COVID-19 line list using a semistructured proforma and analyzed using Statistical Package for Social Sciences (SPSS) ver. 18. Results: The second wave had a higher proportion of symptomatic cases (17.3%; 20.1%), cases with severe symptoms (0.3%; 0.6%), intensive care unit (ICU) admissions (11.2%; 17.9%), and case fatality rate (0.69%; 0.72%). Significant difference was noted in the age, gender, locality, source of infection, comorbidity profile, symptom, and the pattern of admission in various healthcare settings between the first and second wave. Among the deceased, gender, duration between onset of symptoms and death, comorbidity status, and cause of death were significantly different in both waves. Conclusion: The presence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant, as well as changes in human behavior and threat perception as the pandemic progressed, resulted in significant differences in various epidemiological features of the pandemic in both waves, indicating the need for continued vigilance during each COVID-19 wave.

Clinical and Virological Features of SARS-CoV-2 Variants during the Four Waves of the Pandemic in the Mexican Southeast.

We conducted a retrospective study using a population of patients who were hospitalized at Dr. Juan Graham Casasus Hospital in Villahermosa (Tabasco, Mexico) and had a positive RT-PCR test for SARS-CoV-2 between June 2020 and January 2022. We analyzed all medical records, including demographic data, SARS-CoV-2 exposure history, underlying comorbidities, symptoms, signs at admission, laboratory findings during the hospital stay, outcome, and whole-genome sequencing data. Finally, the data were analyzed in different sub-groups according to distribution during waves of the COVID-19 pandemic regarding Mexican reports from June 2020 to January 2022. Of the 200 patients who tested positive via PCR for SARS-CoV-2, only 197 had samples that could be sequenced. Of the samples, 58.9% (n = 116) were males and 41.1% (n = 81) females, with a median age of 61.7 ± 17.0 years. Comparisons between the waves of the pandemic revealed there were significant differences in the fourth wave: the age of patients was higher (p = 0.002); comorbidities such as obesity were lower (p = 0.000), while CKD was higher (p = 0.011); and hospital stays were shorter (p = 0.003). The SARS-CoV-2 sequences revealed the presence of 11 clades in the study population. Overall, we found that adult patients admitted to a third-level Mexican hospital had a wide range of clinical presentations. The current study provides evidence for the simultaneous circulation of SARS-CoV-2 variants during the four pandemic waves.

Understanding Digital Mental Health Needs and Usage With an Artificial Intelligence-Led Mental Health App (Wysa) During the COVID-19 Pandemic: Retrospective Analysis.

BACKGROUND: There has been a surge in mental health concerns during the COVID-19 pandemic, which has prompted the increased use of digital platforms. However, there is little known about the mental health needs and behaviors of the global population during the pandemic. This study aims to fill this knowledge gap through the analysis of real-world data collected from users of a digital mental health app (Wysa) regarding their engagement patterns and behaviors, as shown by their usage of the service. OBJECTIVE: This study aims to (1) examine the relationship between mental health distress, digital health uptake, and COVID-19 case numbers; (2) evaluate engagement patterns with the app during the study period; and (3) examine the efficacy of the app in improving mental health outcomes for its users during the pandemic. METHODS: This study used a retrospective observational design. During the COVID-19 pandemic, the app's installations and emotional utterances were measured from March 2020 to October 2021 for the United Kingdom, the United States of America, and India and were mapped against COVID-19 case numbers and their peaks. The engagement of the users from this period (N=4541) with the Wysa app was compared to that of equivalent samples of users from a pre-COVID-19 period (1000 iterations). The efficacy was assessed for users who completed pre-post assessments for symptoms of depression (n=2061) and anxiety (n=1995) on the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) test measures, respectively. RESULTS: Our findings demonstrate a significant positive correlation between the increase in the number of installs of the Wysa mental health app and the peaks of COVID-19 case numbers in the United Kingdom (P=.02) and India (P<.001). Findings indicate that users (N=4541) during the COVID period had a significantly higher engagement than the samples from the pre-COVID period, with a medium to large effect size for 80% of these 1000 iterative samples, as observed on the Mann-Whitney test. The PHQ-9 and GAD-7 pre-post assessments indicated statistically significant improvement with a medium effect size (PHQ-9: P=.57; GAD-7: P=.56). CONCLUSIONS: This study demonstrates that emotional distress increased substantially during the pandemic, prompting the increased uptake of an artificial intelligence-led mental health app (Wysa), and also offers evidence that the Wysa app could support its users and its usage could result in a significant reduction in symptoms of anxiety and depression. This study also highlights the importance of contextualizing interventions and suggests that digital health interventions can provide large populations with scalable and evidence-based support for mental health care.

Genitourinary tract symptoms in patients admitted with COVID-19: Exploring changes in frequency by determinants and pandemic waves.

Background: Urothelial cells exhibit increased expression of angiotensin-converting enzyme-2 receptor, which is the binding site of severe acute respiratory syndrome coronavirus 2 to cells. The frequency and distribution of genitourinary tract symptoms in patients diagnosed with coronavirus disease 2019 (COVID-19) is unknown. Objective: We explored trends in genitourinary tract symptoms by gender and each of six pandemic waves in patients admitted for COVID-19, and related them with severity, death and length of hospitalization. Design Setting and Participants: A retrospective study took place in our institution of COVID-19 admitted patients. Only patients with RT-PCR or antigen test confirmed SARS-CoV-2 infection were included. Demographic, clinical, and genitourinary symptoms were explored. Outcome Measurements and Statistical Analysis: COVID-19 patients with genitourinary tract symptoms were compared with those without. Statistical comparisons were conducted by parametric and nonparametric tests for quantitative variables, and χ 2 test for qualitative variables. Results and limitations: Out of a total of 4,661 COVID-19 patients, genitourinary symptoms were found in 21,1%. These symptoms were more frequent in patients admitted for longer than 30 days, except for urinary incontinence (UI) and erectile dysfunction (ED). Acute kidney injury (AKI) and urinary tract infections (UTI) had a higher presence in the 5th (16.7%; 12.8% respectively) and 3rd wave (13.3%; 12.6% respectively). Genitourinary symptoms were higher for those patients admitted in critical care units. Frequency of AKI, UI, UTI and acute urinary retention (AUR) were higher for patients who were finally deceased (26.2%; 3.5%; 13.6% and 3.6% respectively). Conclusions: A high frequency of genitourinary symptoms in patients admitted for COVID-19 was observed, whose frequency and distribution varied according to pandemic waves. Specific genitourinary conditions were associated with worse outcomes and poorer prognosis.

Comparison of Clinical Features, Complete Blood Count Parameters, and Outcomes between Two Distinct Waves of COVID-19: A Monocentric Report from Italy.

BACKGROUND: Since the beginning of the SARS-CoV-2 pandemic, the ability to predict the trajectory of the disease has represented a major challenge for clinicians. There is recent evidence that complete blood cell count (CBC)-derived inflammation indexes have predictive value in COVID-19. We aimed to describe any changes in the clinical features, CBC-derived ratios, and outcomes of patients admitted to our hospital across two temporally distinct waves. METHODS: We retrospectively assessed and compared the clinical characteristics and blood cell count values of patients hospitalized during the second and fourth waves of COVID-19, and explored any outcome differences in terms of the level of respiratory support required and transfer to intensive care. RESULTS: We observed that fourth-wave patients were older, less male-predominant, and carried more comorbidities compared to the second-wave patients but, nevertheless, experienced more favorable outcomes. A strong internal correlation was documented for both waves between outcomes and CBC-derived ratios, with the fourth-wave cases displaying lower admission values of the neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), platelet-to-lymphocyte ratio (PLR), and systemic inflammation index (SII). No significant differences were found for lymphocyte-to-monocyte ratio (LMR), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI). CONCLUSIONS: We observed that both admission values of CBC-derived indexes and adverse respiratory outcomes decreased from the second to the fourth wave of COVID-19. These data represent a contribution to the existing knowledge on the role of CBC-derived indexes as a potential tool to help clinicians to quickly differentiate in-hospital patients at increased risk of serious illness and death.

Clinical Characterization of the Three Waves of COVID-19 Occurring in Southern Italy: Results of a Multicenter Cohort Study.

AIMS: To characterize patients hospitalized for COVID-19 in the three waves in Southern Italy. METHODS: We conducted a multicenter observational cohort study involving seventeen COVID-19 Units in Campania, southern Italy: All adult (≥18 years) patients, hospitalized with a diagnosis of SARS-CoV-2 infection from 28 February 2020 to 31 May 2021, were enrolled. RESULTS: Two thousand and fifteen COVID-19 hospitalized patients were enrolled; 392 (19%) in the first wave, 917 (45%) in the second and 706 (35%) in the third wave. Patients showed a less severe clinical outcome in the first wave than in the second and third waves (73%, 65% and 72%, respectively; p = 0.003), but hospitalization expressed in days was longer in the first wave [Median (Q1-Q3): 17 (13-25) v.s. 14 (9-21) and 14 (9-19), respectively, p = 0.001)] and also mortality during hospitalization was higher in the first wave than in the second and third waves: 16.6% v.s. 11.3% and 6.5%, respectively (p = 0.0001). Multivariate analysis showed that older age [OR: 1.069, CI (1046-1092); p = 0.001], a worse Charlson comorbidity index [OR: 1042, CI (1233-1594; p = 0.0001] and enrolment during the first-wave [OR: 1.917, CI (1.054-3.485; p = 0.033] were predictors of mortality in hospitalized patients. CONCLUSIONS: Improved organization of the healthcare facilities and the increase in knowledge of clinical and therapeutic management have contributed to a trend in the reduction in mortality during the three waves of COVID-19.

Four Waves of the COVID-19 Pandemic: Comparison of Clinical and Pregnancy Outcomes.

During the last two and a half years, clinical manifestations, disease severity, and pregnancy outcomes have differed among pregnant patients with SARS-CoV-2 infection. These changes were preceded by the presence of new variants of SARS-CoV-2, known in the literature as variants of concern. The aim of this study is to describe the differences between maternal clinical characteristics and perinatal outcomes among pregnant women with COVID-19 during four waves of the COVID-19 epidemic in Serbia. This retrospective study included a series of 192 pregnant patients who were hospitalized due to the severity of their clinical status of SARS-CoV-2 infection. During four outbreaks of COVID-19 infection in Serbia, we compared and analyzed three sets of variables, including signs, symptoms, and characteristics of COVID-19 infection, clinical endpoints, and maternal and newborn parameters. During the dominance of the Delta variant, the duration of hospitalization was the longest (10.67 ± 1.42 days), the frequency of stillbirths was the highest (17.4%), as well as the frequency of progression of COVID infection (28.9%) and the requirement for non-invasive oxygen support (37%). The dominance of the Delta variant was associated with the highest number of prescribed antibiotics (2.35 ± 0.28), the most common presence of nosocomial infections (21.7%), and the highest frequency of corticosteroid therapy use (34.8%). The observed differences during the dominance of four variants of concern are potential pathways for risk stratification and the establishment of timely and proper treatments for pregnant patients. Early identification of the Delta variant, and possibly some new variants with similar features in the future, should be a priority and, perhaps, even an opportunity to introduce more accurate and predictive clinical algorithms for pregnant patients.

Effect of Covid-19 pandemic on gender associated with risk factors: a retrospective data analysis, Thailand.

Background: The COVID-19 pandemic is having a serious impact around the world. Many countries have experienced a two or three wave pattern in reported cases. The virus's spread in Thailand was a cluster event distributed over multiple locations, multi-spender, and multiple waves of outbreaks. Objective: This study aims to study gender associated with age, risk factors, and nationality during coronavirus pandemic in Thailand. Material and methods: A retrospective cohort study was conducted from January 2020 to May 2021 (17 months) to determine the number of confirmed cases and identify gender associated with, age, various risk factors and nationality were analyzed by chi square test and binary logistic regression analyses. Results: The results show that the number of cases increased by over 100,000 over the course of three waves of outbreaks. The logistic regression analysis revealed that genders were significantly related with age, various risk factors, and nationality across different waves (p < 0.01). Across the primary risk factors were community risk, community cluster and close contact with a previously confirmed patient on confirmed cases during COVID-19 pandemic. Conclusion: Significant differences between genders were significantly associated with age, various risk factors, and nationality may be due to weak social distancing policies and the lack of public health interventions. A COVID-19 vaccination plan is needed for people who are at risk of suffering severe symptoms as well as the general population in outbreak areas to increase immunity.

Characterizing pandemic waves: A latent class analysis of COVID-19 spread across US counties.

The spread of the COVID-19 pandemic is observed to follow the shape of "waves" (i.e., the rise and fall of population-adjusted daily new infection cases with time). Different geographic regions of the world have experienced different position and span of these waves over time. The presence and strength of these waves broadly characterize the dynamics of the pandemic spread in a given area, so their characterization is important to draw meaningful intervention and mitigation plans tailored for that area. In this paper, we propose a novel technique to represent the trend of COVID-19 spread as a sequence of a fixed-length text string defined on three symbols: R (rise), S (Steady), and F (fall). These strings, termed as trend strings, enabled us searching for specific patterns in them (such as for waves). After analyzing county-level infection data, we observe that, US counties-despite their wide variation in trend strings-can be grouped into a number of heterogeneous classes each of which might have a representative COVID spread pattern over time (in terms of presence and propensity of waves). To this end, we conduct a latent class analysis to cluster 3142 US counties into four distinct classes based on their wave characteristics for one year pandemic data (January 2020 to January 2021). We observe that counties in each class have distinct socio-demographics, location, and human mobility characteristics. In short summary, counties have differing number of waves (class 1 counties have only one wave and class 3 counties have three) and their positions also vary (class 1 had the wave later in the year whereas class 3 had waves throughout the year). We believe that this way of characterizing pandemic waves would provide better insights in understanding the complex dynamics of COVID-19 spread and its future evolution, and would, therefore, help in taking class-specific policy interventions.

SARS-CoV-2 Seroprevalence among Healthcare Workers after the First and Second Pandemic Waves.

Background: The Grand Hôpital de Charleroi is a large non-academic Belgian hospital that treated a large number of COVID-19 inpatients. In the context of this pandemic, all professions-combined healthcare workers (HCWs), and not only direct caregivers, are a frontline workforce in contact with suspected and confirmed COVID-19 cases and seem to be a high-risk group for exposure. The aim of our study was to estimate the prevalence of anti-SARS-CoV-2 antibodies in HCWs in our hospital after the first and second pandemic waves and to characterize the distribution of this seroprevalence in relation to various criteria. Methods: At the end of the two recruitment periods, a total of 4008 serological tests were performed in this single-center cross-sectional study. After completing a questionnaire including demographic and personal data, possible previous COVID-19 diagnostic test results and/or the presence of symptoms potentially related to COVID-19, the study participants underwent blood sampling and serological testing using DiaSorin's LIAISON® SARS-CoV-2 S1/S2 IgG test for the first phase and LIAISON® SARS-CoV-2 TrimericS IgG test for the second phase of this study. Results: In total, 302 study participants (10.72%) in the first round of the study and 404 (33.92%) in the second round were positive for SARS-CoV-2-IgG antibodies. The prevalence of seropositivity observed after the second wave was 3.16 times higher than after the first wave. We confirmed that direct, prolonged, and repeated contact with patients or their environment was a predominant seroconversion factor, but more unexpectedly, that this was the case for all HCWs and not only caregivers. Finally, the notion of high-risk contact seemed more readily identifiable in one's workplace than in one's private life. Conclusions: Our study confirmed that HCWs are at a significantly higher risk of contracting COVID-19 than the general population, and suggests that repeated contacts with at-risk patients, regardless of the HCWs' professions, represents the most important risk factor for seroconversion (Clinicaltrials.gov number, NCT04723290).

Treatments, resource utilization, and outcomes of COVID-19 patients presenting to emergency departments across pandemic waves: an observational study by the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN).

BACKGROUND: Treatment for coronavirus disease 2019 (COVID-19) evolved between pandemic waves. Our objective was to compare treatments, acute care utilization, and outcomes of COVID-19 patients presenting to emergency departments (ED) across pandemic waves. METHODS: This observational study enrolled consecutive eligible COVID-19 patients presenting to 46 EDs participating in the Canadian COVID-19 ED Rapid Response Network (CCEDRRN) between March 1 and December 31, 2020. We collected data by retrospective chart review. Our primary outcome was in-hospital mortality. Secondary outcomes included treatments, hospital and ICU admissions, ED revisits and readmissions. Logistic regression modeling assessed the impact of pandemic wave on outcomes. RESULTS: We enrolled 9,967 patients in 8 provinces, 3,336 from the first and 6,631 from the second wave. Patients in the second wave were younger, fewer met criteria for severe COVID-19, and more were discharged from the ED. Adjusted for patient characteristics and disease severity, steroid use increased (odds ratio [OR] 7.4; 95% confidence interval [CI] 6.2-8.9), and invasive mechanical ventilation decreased (OR 0.5; 95% CI 0.4-0.7) in the second wave compared to the first. After adjusting for differences in patient characteristics and disease severity, the odds of hospitalization (OR 0.7; 95% CI 0.6-0.8) and critical care admission (OR 0.7; 95% CI 0.6-0.9) decreased, while mortality remained unchanged (OR 0.7; 95% CI 0.5-1.1). INTERPRETATION: In patients presenting to cute care facilities, we observed rapid uptake of evidence-based therapies and less use of experimental therapies in the second wave. We observed increased rates of ED discharges and lower hospital and critical care resource use over time. Substantial reductions in mechanical ventilation were not associated with increasing mortality. Advances in treatment strategies created health system efficiencies without compromising patient outcomes. TRIAL REGISTRATION: Clinicaltrials.gov, NCT04702945.

RéSUMé: CONTEXTE: Le traitement de la maladie à coronavirus 2019 (COVID-19) a évolué entre les vagues pandémiques. Notre objectif était de comparer les traitements, l'utilisation des soins aigus et les résultats des patients atteints de la maladie COVID-19 se présentant aux urgences à travers les vagues de pandémie. MéTHODES: Cette étude observationnelle a recruté des patients COVID-19 éligibles consécutifs se présentant à 46 services d'urgence participant au Réseau canadien de réponse rapide aux services d'urgence COVID-19 (CCEDRRN) entre le 1er mars et le 31 décembre 2020. Nous avons recueilli des données au moyen d'un examen rétrospectif des dossiers. Notre principal résultat a été la mortalité à l'hôpital. Les résultats secondaires incluaient les traitements, les admissions à l'hôpital et aux soins intensifs, les revisites aux urgences et les réadmissions. La modélisation par régression logistique a évalué l'impact de la vague de pandémie sur les résultats. RéSULTATS: Nous avons recruté 9 967 patients dans 8 provinces, 3 336 de la première vague et 6 631 de la deuxième vague. Les patients de la deuxième vague étaient plus jeunes, moins nombreux à répondre aux critères de gravité de la COVID-19 et plus nombreux à quitter les urgences. Après ajustement en fonction des caractéristiques des patients et de la gravité de la maladie, le recours aux stéroïdes a augmenté (rapport de cotes [RC] 7.4 ; intervalle de confiance à 95 % [IC] 6.2­8.9) et la ventilation mécanique invasive a diminué (RC 0.5 ; IC à 95 % 0.4­0.7) lors de la deuxième vague par rapport à la première. Après ajustement pour tenir compte des différences dans les caractéristiques des patients et la gravité de la maladie, les probabilités d'hospitalisation (RC 0.7 ; IC à 95 % 0.6­0.8) et d'admission en soins intensifs (RC 0.7 ; IC à 95 % 0.6­0.9) ont diminué, tandis que la mortalité est restée inchangée (RC 0.7 ; IC à 95 % 0.5­1.1). INTERPRéTATION: Chez les patients se présentant dans les établissements de soins de santé, nous avons observé une adoption rapide des thérapies fondées sur des données probantes et un moindre recours aux thérapies expérimentales lors de la deuxième vague. Nous avons observé une augmentation des taux de sortie des services d'urgence et une diminution de l'utilisation des ressources hospitalières et des soins intensifs au fil du temps. Les réductions substantielles de la ventilation mécanique n'étaient pas associées à une augmentation de la mortalité. Les progrès réalisés dans les stratégies de traitement ont permis d'améliorer l'efficacité des systèmes de santé sans compromettre les résultats pour les patients.

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.

Insomnia, Pre-Sleep Arousal, Psychosocial Factors and Changes in Sleep Pattern during the Second Wave Lockdown of the COVID-19 Pandemic in Georgia.

Studies performed across the COVID-19 pandemic waves point to the persistent impact of the pandemic on sleep and mental health. We expand these data by examining insomnia, pre-sleep arousal, psychosocial factors, and retrospective changes in sleep pattern during the COVID-19 second wave lockdown period in Georgia. Data were collected through an online survey (n = 1117). The prevalence rate of probable insomnia disorder was 24.2%. Clinically relevant somatic and cognitive pre-sleep arousal was present in 49.8% and 58.0% of participants, and high levels of anxiety, depression and social isolation were found in 47.0%, 37.3%, 47.2% of respondents, respectively. We observed high prevalence rates of worse sleep quality, delayed bedtimes and risetimes, longer sleep latencies, higher awakenings and shorter sleep durations, relative to the pre-pandemic period. COVID-19-infected participants showed more severe sleep and mental problems. Specific predictors differentially affected insomnia, somatic and cognitive pre-sleep arousal. Depression and COVID-19 infection emerged as vulnerability factors for pre-sleep arousal, which, in turn, was associated with a higher predisposition to insomnia disorder. We confirm the strong deteriorating impact of the COVID-19 pandemic on sleep and psychosocial well-being during the second wave lockdown period. The specific association between pre-sleep arousal, insomnia, and psychosocial factors is of clinical relevance for the prevention of severity and persistence of sleep and mental problems across the repeated lockdown/reopening waves. Modulation of pre-sleep arousal may prove beneficial to implement targeted interventions.

Burden of COVID-19 and case fatality rate in Pune, India: an analysis of the first and second wave of the pandemic.

Objective: To assess trends in case incidence and fatality rate between the first and second waves, we analyzed programmatic COVID-19 data from Pune city, an epicenter of COVID-19 cases in India. Method: The trends of cases incidence, time-to-death and case fatality rate (CFR) were analyzed. Poisson regression models adjusted for age and gender were used to determine the independent effect of pandemic waves on mortality. Results: Of 465 192 COVID-19 cases, 162 182 (35%) were reported in the first wave and 4146 (2.5%) deaths, and 275 493 (59%) in the second wave and 3184 (1.1%) deaths (P<0.01). The overall CFR was 1.16 per 1000 person-days (PD), which declined from 1.80 per 1000 PD during the first wave to 0.77 per 1000 PD in the second. The risk of death was 1.49 times higher during the first wave (adjusted CFR ratio (aCFRR)1.49; 95% CI: 1.37-1.62) and 35% lower in the second wave (aCFRR 0.65; 95% CI: 0.59-0.70). Conclusion: The burden of COVID-19 cases and deaths was more significant in the second wave; however, the CFR declined as the pandemic progressed. Nevertheless, investigating new therapies and implementing mass vaccination against COVID-19 are urgently needed.

Sex differences in a cohort of COVID-19 Italian patients hospitalized during the first and second pandemic waves.

BACKGROUND: Coronavirus disease 2019 (COVID-19) severity seems to be influenced by genetic background, sex, age, and presence of specific comorbidities. So far, little attention has been paid to sex-specific variations of demographic, clinical, and laboratory features of COVID-19 patients referred to the same hospital in the two consecutive pandemic waves. METHODS: Demographic, clinical, and laboratory data were collected in 1000 COVID-19 patients (367 females and 633 males), 500 hospitalized in the first wave and 500 in the second one, at the ASST Spedali Civili of Brescia from March to December 2020. Statistical analyses have been employed to compare data obtained in females and males, taking into account their age, and during the first and second COVID-19 waves. RESULTS: The mean age at the time of hospitalization was similar in females and males but was significantly higher for both in the second wave; the time elapsed from symptom onset to hospital admission did not differ between sexes in the two waves, and no correlation was observed between delayed hospital admission and length of hospitalization. The number of multi-symptomatic males was higher than that of females, and patients with a higher number of comorbidities were more frequently admitted to intensive care unit (ICU) and more frequently died. Older males remained in the ICU longer than females and showed a longer disease duration, mainly the first wave. The highest levels of white blood cells, neutrophils, C-reactive protein, and fibrinogen were significantly higher in males and in the first, and along with higher levels of D-dimer, ferritin, lactate dehydrogenase, and procalcitonin which were preferentially documented in patients requiring ICU or died. While the rate of death in ICU was higher in males, the overall death rate did not differ between the sexes; however, the deceased women were older. CONCLUSIONS: These data indicate that once patients were hospitalized, the risk of dying was similar between females and males. Therefore, future studies should aim at understanding the reasons why, for a given number of SARS-CoV-2 infections, fewer females develop the disease requiring hospitalization. HIGHLIGHTS: Although the hospitalized males were significantly more, the similar number of hospitalizations of the > 75-year-old females and males could be due to the fact that in Brescia province, elderly women are about twice as many as men. Although males spent more days in the hospital, had a longer disease duration, developed a critical illness more frequently, and were admitted and died in the ICU more than females, the total rate of deaths among patients was not significantly different between sexes. Overall, the most frequent comorbidities were cardiovascular diseases, which were preferentially seen among patients hospitalized in the second wave; it is possible that the knowledge gained in the first wave concerning the association between certain comorbidities and worse disease evolution has guided the preferential hospitalization of patients with these predominant comorbidities.

A swaying between successive pandemic waves and pandemic fatigue: Where does Jordan stand?

This article highlights the main aspects of Jordan's public health response in combating the COVID-19 pandemic. Also, it briefly describes the main characteristics of the pandemic waves. Although Jordan has successfully implemented various stringent control measures at the early stage of the pandemic which resulted in a slow pace of COVID-19 spread in the country, the dramatic and sudden surge in COVID-19 cases and deaths since September 2020 raises many concerns and questionable debates regarding the effectiveness of Jordan's COVID-19 mitigation strategies, the earlier epidemiological surveillance process, decision-making and decisions' execution at various sectors, as well as the degree of commitment to precautionary measures among the general population. Jordan has passed through three distinct pandemic stages so far, and each stage provides lessons that can be used to improve the national preparedness and response plan in the future. This pandemic has afflicted most life domains; thus, sharing the responsibility and efforts between the government and people in combating it, is expected to be more efficient and effective than a one-sided response. Pandemic fatigue can act as a major risk factor for losing such a battle. The people of Jordan have been already through an unforgettable 2020 year that impacted them physically, emotionally, and even financially. Therefore, reliable actions should be considered by the decision-makers to provide sufficient support for the society. Also, strengthening the government-public partnership is a cornerstone for a successful, solid, and effective public health response, especially in times of an exhaustive pandemic crisis like the COVID-19.

Quickest Detection of COVID-19 Pandemic Onset.

This paper develops an easily-implementable version of Page's CUSUM quickest-detection test, designed to work in certain composite hypothesis scenarios with time-varying data statistics. The decision statistic can be cast in a recursive form and is particularly suited for on-line analysis. By back-testing our approach on publicly-available COVID-19 data we find reliable early warning of infection flare-ups, in fact sufficiently early that the tool may be of use to decision-makers on the timing of restrictive measures that may in the future need to be taken.