First and Second Waves of Covid-19: A Comparative Study of the Clinical Presentation and Outcome among Hospitalized Patients in Lagos Nigeria.

OBJECTIVE: Nigeria experienced many waves of the COVID-19 pandemic. This study compared the clinical presentations and mortality among hospitalized patients during the first and second waves of the pandemic in Lagos State, Nigeria. METHODS: A retrospective cohort study was conducted. Deidentified medical records of laboratory-confirmed COVID-19 patients admitted into 15 isolation centers in Lagos, Nigeria between February 27, 2020, and September 30, 2020 (first wave) and October 1, 2020, and April 30, 2021 (second wave) were reviewed. IBM Statistics version 25 was used for data analysis. RESULTS: More patients were hospitalized during the first wave of the pandemic. The mean age of patients was higher during the second wave (54.5±15.8 years vs. 42.2±15.5 years, p <0.001). More patients admitted during the second wave had comorbidities (56.0% vs 28.6%, p <0.001), were symptomatic (90.8% vs 52.0%, p <0.001), had severe COVID-19 disease (58.9% vs 25%, p <0.001) and died (14.9% vs 6.4%, p<0.001) compared with the first wave. The odds of death increased with age and severity of COVID-19 disease during the first and second waves. CONCLUSION: A higher proportion of the patients admitted in Lagos, Nigeria during the second wave were older, had comorbidities, and had severe COVID-19 disease than the first wave. Despite the fewer hospitalized patients, there were more deaths during the second wave.

OBJECTIF: Le Nigeria a connu plusieurs vagues de la pandémie de la COVID-19. Cette étude a comparé les présentations cliniques et la mortalité chez les patients hospitalisés lors des première et deuxième vagues de la pandémie dans l'État de Lagos, Nigeria. MÉTHODES: Une étude de cohorte rétrospective a été réalisée. Les dossiers médicaux déidentifiés des patients atteints de la COVID-19 confirmée par laboratoire, admis dans 15 centres d'isolement à Lagos, Nigeria, entre le 27 février 2020 et le 30 septembre 2020 (première vague) et entre le 1er octobre 2020 et le 30 avril 2021 (deuxième vague), ont été examinés. IBM Statistics version 25 a été utilisé pour l'analyse des données. RÉSULTATS: Un plus grand nombre de patients ont été hospitalisés lors de la première vague de la pandémie. L'âge moyen des patients était plus élevé lors de la deuxième vague (54,5±15,8 ans vs. 42,2±15,5 ans, p <0,001). Un plus grand nombre de patients admis lors de la deuxième vague avaient des comorbidités (56,0% vs. 28,6%, p <0,001), étaient symptomatiques (90,8% vs. 52,0%, p <0,001), avaient une forme grave de la maladie à la COVID-19 (58,9% vs. 25%, p <0,001) et sont décédés (14,9% vs. 6,4%, p<0,001) par rapport à la première vague. Les chances de décès ont augmenté avec l'âge et la gravité de la maladie à la COVID-19 lors des première et deuxième vagues. CONCLUSION: Une proportion plus élevée des patients admis à Lagos, Nigeria, lors de la deuxième vague étaient plus âgés, avaient des comorbidités et présentaient une forme grave de la maladie à la COVID-19 par rapport à la première vague. Malgré un nombre moindre de patients hospitalisés, il y a eu plus de décès lors de la deuxième vague. MOTS-CLÉS: Présentation Clinique, Covid-19, Première Vague, Mortalité, Nigeria, Deuxième Vague.

High SARS-CoV-2 Seroprevalence after Second COVID-19 Wave (October 2020-April 2021), Democratic Republic of the Congo.

Serologic surveys are important tools for estimating the true burden of COVID-19 in a given population. After the first wave of SARS-CoV-2 infections, a household-based survey conducted in Kinshasa, Democratic Republic of the Congo, estimated >292 infections going undiagnosed for every laboratory-confirmed case. To ascertain the cumulative population exposure in Kinshasa after the second wave of COVID-19, we conducted a prospective population-based cross-sectional study using a highly sensitive and specific ELISA kit. The survey included 2,560 consenting persons from 585 households; 55% were female and 45% male. The overall population-weighted, test kit-adjusted SARS-CoV-2 seroprevalence was 76.5% (95% CI 74.5%-78.5%). The seroprevalence was 4-fold higher than during the first wave, and positivity was associated with age, household average monthly income, and level of education. Evidence generated from this population-based survey can inform COVID-19 response, especially vaccination campaign strategies in the context of vaccine shortages and hesitancy.

COVID-19 second wave and clinical characteristics of cases in Uganda: A retrospective cross-sectional survey of confirmed SARS-CoV-2 cases, March-June 2021.

We conducted a retrospective cross-sectional population-based survey among recovered COVID-19 cases in Uganda to establish the case presentations of the second wave SARS-CoV-2 infections. We interviewed 1,120 recovered COVID-19 cases from 10 selected districts in Uganda. We further conducted 38 key informant interviews with members of the COVID-19 District Taskforce and 19 in-depth interviews among COVID-19 survivors from March to June 2021. Among them, 62% were aged 39 years and below and 51.5% were female with 90.9% under home-based care management. Cases were more prevalent among businesspeople (25.9%), students (16.2%), farmers (16.1%), and health workers (12.4%). Being asymptomatic was found to be associated with not seeking healthcare (APR 2, P < 0.001). The mortality rate was 3.6% mostly among the elderly (6.3%) and 31.3% aged 40 years and above had comorbidities of high blood pressure, diabetes, and asthma. Being asymptomatic, or under home-based care management (HBCM), working/operating/studying at schools, and not being vaccinated were among the major drivers of the second wave of the resurgence of COVID19 in Uganda. Managing future COVID-19 waves calls for proactive efforts for improving homebased care services, ensuring strict observation of SOPs in schools, and increasing the uptake of COVID-19 vaccination.

Clinical characteristics & severity profile of children with COVID-19 during the second wave pandemic: An experience from tertiary care hospital in Mumbai.

This retrospective observational study was aimed at defining the demographic and clinical characteristics as well as severity profile of COVID-19 disease in children admitted to dedicated COVID-19 tertiary care hospital in Mumbai, India, during the second wave. COVID-19 infection detected in children (1 month-12 years) by the rapid antigen test or reverse transcriptase polymerase chain reaction or TRUENAT from March 1 to July 31, 2021 on throat/nasopharyngeal samples were enrolled and their clinical features and outcomes were studied. During the study period, 77 children with COVID-19 infection were admitted, of whom two-third (59.7%) were <5 yr old. The common presenting symptom was fever (77%), followed by respiratory distress. Comorbidities were noted in 34 (44.2%) children. Most of the patients belonged to the mild severity category (41.55%). While 25.97 per cent of patients presented in severe category and 19.48 per cent were asymptomatic. Admission to intensive care was needed in 20 (25.9%) patients, with 13 patients needing invasive ventilation. Nine patients succumbed while 68 were discharged. The results might help understand the course, severity profile and outcomes of the second wave of the COVID-19 pandemic in the paediatric population.

Readiness of health facilities to manage individuals infected with COVID-19, Uganda, June 2021.

BACKGROUND: The COVID-19 pandemic overwhelmed the capacity of health facilities globally, emphasizing the need for readiness to respond to rapid increases in cases. The first wave of COVID-19 in Uganda peaked in late 2020 and demonstrated challenges with facility readiness to manage cases. The second wave began in May 2021. In June 2021, we assessed the readiness of health facilities in Uganda to manage the second wave of COVID-19. METHODS: Referral hospitals managed severe COVID-19 patients, while lower-level health facilities screened, isolated, and managed mild cases. We assessed 17 of 20 referral hospitals in Uganda and 71 of 3,107 lower-level health facilities, selected using multistage sampling. We interviewed health facility heads in person about case management, coordination and communication and reporting, and preparation for the surge of COVID-19 during first and the start of the second waves of COVID-19, inspected COVID-19 treatment units (CTUs) and other service delivery points. We used an observational checklist to evaluate capacity in infection prevention, medicines, personal protective equipment (PPE), and CTU surge capacity. We used the "ReadyScore" criteria to classify readiness levels as > 80% ('ready'), 40-80% ('work to do'), and < 40% ('not ready') and tailored the assessments to the health facility level. Scores for the lower-level health facilities were weighted to approximate representativeness for their health facility type in Uganda. RESULTS: The median (interquartile range (IQR)) readiness scores were: 39% (IQR: 30, 51%) for all health facilities, 63% (IQR: 56, 75%) for referral hospitals, and 32% (IQR: 24, 37%) for lower-level facilities. Of 17 referral facilities, two (12%) were 'ready' and 15 (88%) were in the "work to do" category. Fourteen (82%) had an inadequate supply of medicines, 12 (71%) lacked adequate supply of oxygen, and 11 (65%) lacked space to expand their CTU. Fifty-five (77%) lower-level health facilities were "not ready," and 16 (23%) were in the "work to do" category. Seventy (99%) lower-level health facilities lacked medicines, 65 (92%) lacked PPE, and 53 (73%) lacked an emergency plan for COVID-19. CONCLUSION: Few health facilities were ready to manage the second wave of COVID-19 in Uganda during June 2021. Significant gaps existed for essential medicines, PPE, oxygen, and space to expand CTUs. The Uganda Ministry of Health utilized our findings to set up additional COVID-19 wards in hospitals and deliver medicines and PPE to referral hospitals. Adequate readiness for future waves of COVID-19 requires additional support and action in Uganda.

Proteomic Investigation of COVID-19 Severity During the Tsunamic Second Wave in Mumbai.

Maharashtra was severely affected during the noxious second wave of COVID-19, with the highest number of cases recorded across India. The emergence of new symptoms and dysregulation of multiple organs resulted in high disease severity during the second wave which led to increased difficulties in understanding the molecular mechanisms behind the disease pathology. Exploring the underlying factors can help to relieve the burden on the medical communities to some extent by prioritizing the patients and, at the same time, opening avenues for improved treatments. In the current study, we have performed a mass-spectrometry-based proteomic analysis to investigate the disease pathology using nasopharyngeal swab samples collected from the COVID-19 patients in the Mumbai region of Maharashtra over the period of March-June 2021, the peak of the second wave. A total of 59 patients, including 32 non-severe and 27 severe cases, were considered for this proteomic study. We identified 23 differentially regulated proteins in severe patients as a host response to infection. In addition to the previously identified innate mechanisms of neutrophil and platelet degranulation, this study revealed significant alterations of anti-microbial peptide pathways in severe conditions, illustrating its role in the severity of the infectious strain of COVID-19 during the second wave. Furthermore, myeloperoxidase, cathepsin G, and profilin-1 were identified as potential therapeutic targets of the FDA-approved drugs dabrafenib, ZINC4097343, and ritonavir. This study has enlightened the role of the anti-microbial peptide pathway associated with the second wave in India and proposed its importance in potential therapeutics for COVID-19.

Knowledge, attitudes and practices of university students toward COVID-19 in Southern region, Afghanistan: a cross-sectional study.

BACKGROUND: Successful implementation of preventive measures and level of awareness in particular among university students in Afghanistan could play a crucial role in spreading the information for better control of the ongoing pandemic. Therefore, the aim of this study was to determine the level of knowledge, attitudes and practices (KAP) regarding COVID-19 among Kandahar university students. METHODS: A cross-sectional study conducted among undergraduate students to investigate their KAP regarding COVID-19 from January to March, 2021. The data were collected using a structured questionnaire (socio-demographic characteristics, KAP questionnaire) by phone call interviews. RESULTS: From 359 participants, 88.9% were males, 81.3% were single, 65.1% lived in urban areas, and more than 64% of the students were less than 23 years old. Overall, 86.6% of the study participants had adequate level of knowledge and 87.5% had positive attitudes toward COVID-19. Almost one-third of the participants had good practices regarding COVID-19. All KAP scores were higher in male students. Significant difference of good practice (p < 0.001) was observed among students who were in high socioeconomic status (SES) group. In univariate analysis, female sex (ß: -0.75, p = 0.007) was negatively and watching television (ß: 0.44; p = 0.014) was positively associated with knowledge score. However, in multivariate linear regression analysis, the knowledge score was significantly associated with age (ß: -0.115; p = 0.004); attitude score was significantly associated with female sex (ß: -2.776; p < 0.001) and radio use (ß: -0.974; p = 0.031); and practice score was significantly associated with female sex (ß: -3.704; p = 0.002) and urban area (ß: 1.702; p = 0.016). CONCLUSIONS: The overall knowledge and attitudes regarding COVID-19 among university students were desirable. Higher university year, young age, male sex and living in urban areas were significantly associated with good KAP regarding COVID-19. Good practices towards COVID-19 should be increased through awareness programs.

Satellite Epidemic of Covid-19 Associated Mucormycosis in India: A Multi-Site Observational Study.

BACKGROUND: Sudden upsurge in cases of COVID-19 Associated Mucormycosis (CAM) following the second wave of the COVID-19 pandemic was recorded in India. This study describes the clinical characteristics, management and outcomes of CAM cases, and factors associated with mortality. METHODS: Microbiologically confirmed CAM cases were enrolled from April 2021 to September 2021 from ten diverse geographical locations in India. Data were collected using a structured questionnaire and entered into a web portal designed specifically for this investigation. Bivariate analyses and logistic regression were conducted using R version 4.0.2. RESULTS: A total of 336 CAM patients were enrolled; the majority were male (n = 232, 69.1%), literate (n = 261, 77.7%), and employed (n = 224, 66.7%). The commonest presenting symptoms in our cohort of patients were oro-facial and ophthalmological in nature. The median (Interquartile Range; IQR) interval between COVID diagnosis and admission due to mucormycosis was 31 (18, 47) days, whereas the median duration of symptoms of CAM before hospitalization was 10 (5, 20) days. All CAM cases received antifungal treatment, and debridement (either surgical or endoscopic or both) was carried out in the majority of them (326, 97.02%). Twenty-three (6.9%) of the enrolled CAM cases expired. The odds of death in CAM patients increased with an increase in HbA1c level (aOR: 1.34, 95%CI: 1.05, 1.72) following adjustment for age, gender, education and employment status. CONCLUSION: A longer vigil of around 4-6 weeks post-COVID-19 diagnosis is suggested for earlier diagnosis of CAM. Better glycemic control may avert mortality in admitted CAM cases.

A fungal epidemic amidst a viral pandemic: Risk factors for development of COVID-19 associated rhino-orbital-cerebral mucormycosis in India.

PURPOSE: To study the risk factors for development of COVID-19 associated rhino-orbital-cerebral mucormycosis (ROCM) during the COVID-19 pandemic in India. METHODS: Multi-centric retrospective case-control study conducted from October 2020 to May 2021. Cases comprised of consecutive patients of COVID-19-associated ROCM (CA-ROCM) presenting at the participating ophthalmic institutes. Controls comprised of COVID-19-positive or COVID-19-recovered patients who did not develop ROCM. Comparative analysis of demographic, COVID-19 infection, treatment parameters and vaccination status between cases and controls performed. Clinical and imaging features of CA-ROCM analyzed. RESULTS: There were 179 cases and 361 controls. Mean age of presentation in cases was 52.06 years (p = .001) with male predominance (69.83%, p = .000011). Active COVID-19 infection at the time of presentation of ROCM (57.54%, p < .0001), moderate to severe COVID-19 (p < .0001), steroid administration (OR 3.63, p < .00001), uncontrolled diabetes (OR 32.83, p < .00001), random blood sugar >178 mg/dl were associated with development of CA-ROCM. Vaccination showed a protective effect (p = .0049). In cases with intracranial or cavernous sinus extension there was history of steroid administration (OR 2.89, p = .024) and orbital apex involvement on imaging (OR 6.202, p = .000037) compared to those with only rhino-orbital disease. CONCLUSION: Male gender, active COVID-19 infection, moderate or severe COVID-19, uncontrolled diabetes, steroid administration during COVID-19 treatment are risk factors for developing rhino-orbital-cerebral mucormycosis. Vaccination is protective. Random blood sugar of >178 mg/dl in COVID-19 positive or recovered patients should warrant close observation and early detection of ROCM. Presence of ophthalmoplegia, blepharoptosis at first clinical presentation and orbital apex involvement on imaging are associated with intracranial extension in ROCM.

[Patients with COPD hospitalized due to COVID-19 in Spain: a comparison between the first and second wave]. / Pacientes con EPOC hospitalizados por COVID-19 en España: comparación entre la primera y la segunda ola.

Objective: This work aimed to compare the characteristics, progress, and prognosis of patients with COPD hospitalized due to COVID-19 in Spain in the first wave with those of the second wave. Material and methods: This is an observational study of patients hospitalized in Spain with a diagnosis of COPD included in the SEMI-COVID-19 registry. The medical history, symptoms, analytical and radiological results, treatment, and progress of patients with COPD hospitalized in the first wave (from March to June 2020) versus those hospitalized in the second wave (from July to December 2020) were compared. Factors associated with poor prognosis, defined as all-cause mortality and a composite endpoint that included mortality, high-flow oxygen therapy, mechanical ventilation, and ICU admission, were analyzed. Results: Of the 21,642 patients in the SEMI-COVID-19 Registry, 6.9% were diagnosed with COPD: 1,128 (6.8%) in WAVE1 and 374 (7.7%) in WAVE2 (p = 0.04). WAVE2 patients presented less dry cough, fever and dyspnea, hypoxemia (43% vs 36%, p < 0.05), and radiological condensation (46% vs 31%, p < 0.05) than WAVE1 patients. Mortality was lower in WAVE2 (35% vs 28.6%, p = 0.01). In the total sample, mortality and the composite outcome of poor prognosis were lower among patients who received inhalation therapy. Conclusions: Patients with COPD admitted to the hospital due to COVID-19 in the second wave had less respiratory failure and less radiological involvement as well as a better prognosis. These patients should receive bronchodilator treatment if there is no contraindication for it.

Comparison between Clinical Profile and Outcome of Patients Admitted with Moderate and Severe COVID-19 Illness in the First and Second Wave of COVID-19 in a Tertiary Care Centre in South India.

Background: SARS-coronavirus-2 has caused large number of infections globally. The infections have presented in a wave form in most of the countries. There have been differences in the clinical presentation, course, and the outcomes in the different waves. Aim: This study describes the clinical features and course of the patients admitted with COVID-19 illness between the first and second wave of COVID-19 in a tertiary care center in South India. Materials and Methods: This was a cross-sectional study where case record analysis of the patients admitted with moderate and severe COVID-19 illness in a tertiary care center in South India was performed. Patients admitted between August 1, 2020, and November 30, 2020, were considered to be affected in the first wave and those admitted between April 30, 2021, and July 30, 2021, were considered to be in the second wave of COVID-19. First wave and second wave periods were determined by a steep surge in infections in India as per the epidemiological data. The symptoms, comorbidities, clinical profile, severity, laboratory parameters, need for assisted ventilation, medications used, and outcome were compared between the two-time frames. Results: A total of 123 patients' data were analyzed in each wave. 72 (58%) patients had fever, while 64 (52%) patients had fever in COVID second wave. In the first wave, five (4%) patients had diarrhea, and four (3.2%) patients had vomiting, whereas in second wave, 43 (34%) patients had diarrhea, and 25 (20 percent) patients had vomiting (P < 0.001). It was seen in the present study that more number of patients in the age group of 31 to 40 years had more serious illness and adverse outcomes in second wave compared with patients in first wave where age group of 51-60 years was more seriously affected. In COVID first wave, 80 (65.0%) were having moderate COVID-19 illness and 43 (35%) had severe illness. In the second wave, 70 (57%) had moderate illness and 53 (43%) patients had severe illness. In the first wave, 31 patients (25%) required non-invasive ventilation (NIV), whereas 79 patients (64%) required NIV in second wave (P < 0.001). First wave resulted in 12 (9.7%) deaths, whereas second wave resulted in 20 (16.2%) deaths. Conclusion: The patients with COVID-19 illness in the second wave presented with more non-respiratory symptoms like vomiting, diarrhea, and joint pains. The patients who had severe illness in the second wave were comparatively younger than the patients of the first wave. The requirement of ventilatory support and immunosuppressants was more in the second wave.

Comparison of demographic and clinical characteristics of hospitalized COVID-19 patients with severe/critical illness in the first wave versus the second wave.

Due to current advances and growing experience in the management of coronavirus Disease 2019 (COVID-19), the outcome of COVID-19 patients with severe/critical illness would be expected to be better in the second wave compared with the first wave. As our hospitalization criteria changed in the second wave, we aimed to investigate whether a favorable outcome occurred in hospitalized COVID-19 patients with only severe/critical illness. Among 642 laboratory-confirmed hospitalized COVID-19 patients in the first wave and 1121 in the second wave, those who met World Health Organization (WHO) definitions for severe or critical illness on admission or during follow-up were surveyed. Data on demographics, comorbidities, C-reactive protein (CRP) levels on admission, and outcomes were obtained from an electronic hospital database. Univariate analysis was performed to compare the characteristics of patients in the first and second waves. There were 228 (35.5%) patients with severe/critical illness in the first wave and 681 (60.7%) in the second wave. Both groups were similar in terms of age, gender, and comorbidities, other than chronic kidney disease. Median serum CRP levels were significantly higher in patients in the second wave compared with those in the first wave [109 mg/L (interquartile range [IQR]: 65-157) vs. 87 mg/L (IQR: 39-140); p < 0.001]. However, intensive care unit admission and mortality rates were similar among the waves. Even though a lower mortality rate in the second wave has been reported in previous studies, including all hospitalized COVID-19 patients, we found similar demographics and outcomes among hospitalized COVID-19 patients with severe/critical illness in the first and second wave.

Genomic characterization unravelling the causative role of SARS-CoV-2 Delta variant of lineage B.1.617.2 in 2nd wave of COVID-19 pandemic in Chhattisgarh, India.

COVID-19 pandemic 2nd wave catastrophic effect in the state of Chhattisgarh, India, from where no exclusive genomic data yet published, has prompted us to undertake this study to unearth the causative variant. Whole-genome sequencing of SARS-CoV-2 isolated from COVID-19 infected nine vaccinated healthcare workers (HCW), thirty mild/moderate, seventeen severe, and twenty-seven deceased patients, was performed. The significant predominance of the SARS-CoV-2 variant of concern (VOC), Delta (lineage B.1.617.2) identified in sixty-four (77.1%) cases in contrast to B.1 and its sublineage in eleven (13.2%), variant under monitoring (VUM), Kappa (lineage B.1.617.1) in five (6.0%) and another VOC Alpha (lineage B.1.1.7) in three (3.6%) cases respectively (p < 0.05, χ2 = 162.49). 88.8% vaccine breakthrough, 60% mild/moderate, 94.4% severe and 81.5% dead patients were infected by Delta. Kappa presents exclusively in mild/moderate, Alpha in vaccine breakthrough, mild/moderate, and dead patient and B.1 and its sublineages in mild, severe, and dead patient categories. Delta variant spike mutation of T19R, G142D, E156G, L452R, and deletion (F157 and R158) helps in escaping antibody response, T478K and D614G enhance viral affinity with ACE2 receptor while P681R and D950N result in higher replication and transmissibility by cleaving S1/S2 at furin site. We conclude that Delta variant predominant role along with co-occurrence of Kappa, Alpha, and B.1 variant during COVID-19 2nd wave pandemic in Chhattisgarh may pose a potential threat of future outbreak through hybrid variant evolution. Thus, intensive genomic surveillance for monitoring variant evolution and a more efficacious vaccine against the Delta and Alpha variants are required.

Impact of preoperative COVID infection on the outcomes of planned curative-intent cancer surgeries in the second wave of the pandemic from a tertiary care center in India.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic was an unforeseen calamity. Sudden disruption of nonemergency services led to disruption of treatment across all specialties. Oncology revolves around the tenet of timely detection and treatment. Disruption of any sort will jeopardize cure rates. The time interval between coronavirus infection and cancer surgery is variable and needs to be tailored to avoid the progression of the disease. METHODS: We analyzed the impact of preoperative coronavirus disease 2019 (COVID-19) infection on the planned cancer surgery, delay, disease progression, and change of intent of treatment from April 1 to May 31, 2021 at a tertiary care center. All preoperative positive patients were retested after 2 weeks and were considered for surgery if the repeat test was negative and asymptomatic. FINDINGS: Our study included 432 preoperative patients of which 91 (21%) were COVID-19 positive. Amongst this cohort, 76% were operated and the morbidity and mortality were comparable to the COVID-19 negative cohort. Around 10% of the COVID-19 positive were lost to follow up and 10% had disease progression and were deemed palliative INTERPRETATION: SARS-CoV-2 infection has adversely impacted cancer care and a 2-week waiting period postinfection seems to be a safe interval in asymptomatic individuals to consider radical cancer surgery.

Using postal change-of-address data to predict second waves in infections near pandemic epicentres.

We propose that postal Change-of-Address (CoA) data can be used to monitor/predict likely second wave caseloads in viral infections around urban epicentres. To illustrate the idea, we focus on the tri-state area consisting of New York City (NYC) and surrounding counties in New York, New Jersey and Connecticut States. NYC was an early epicentre of the coronavirus disease 2019 (Covid-19) pandemic, with a first peak in daily cases in early April 2020, followed by the second peak in May/June 2020. Using CoA data from the US Postal Service (USPS), we show that, despite a quarantine mandate, there was a large net movement of households from NYC to surrounding counties in the period April-June 2020. This net outward migration of households was strongly correlated with both the timing and the number of cases in the second peaks in Covid-19 cases in the surrounding counties. The timing of the second peak was also correlated with the distance of the county from NYC, suggesting that this was a directed flow and not random diffusion. Our analysis shows that CoA data is a useful method in tracking the spread of an infectious pandemic agent from urban epicentres.

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.

Consequences of the first and second COVID-19 wave on kidney transplant recipients at a large Indian transplant centre.

BACKGROUND: There is a scarcity of data comparing the consequences of first and second COVID-19 waves on kidney transplant recipients (KTRs) in India. METHODS: We conducted a single-centre retrospective study of 259 KTRs with COVID-19 to compare first wave (March 15-December 31 2020, n = 157) and second wave (April 1-May 31 2021, n = 102). RESULTS: KTRs during second wave were younger (43 vs. 40 years; p-value .04) and also included paediatric patients (0 vs. 5.9%; p-value .003). Symptoms were milder during the second wave (45 vs. 62.7%; p-value .007); COVID-19 positive patients had less frequent cough (32 vs. 13.8%; p-value .001), fever was less frequent (58 vs. 37%; p-value .001), and we observed fewer co-morbidities (11 vs. 20.6%; p-value .04). The percentages of neutrophils (77 vs. 83%; p-value .001) and serum ferritin (439 vs. 688; p-value .0006) were higher during second wave, while lymphocyte counts were reduced (20 vs. 14%; p-value .0001). Hydroxychloroquine (11 vs. 0%; p-value .0001) and tocilizumab (7 vs. 0%; p-value .004) were more frequently prescribed during first wave, while utilization of dexamethasone (6 vs. 27%; p-value .0001) and remdesivir (47 vs. 65%; p-value .03) increased during the second wave. Mucormycosis (1.3 vs. 10%; p-value .01) and ICU admissions (20 vs. 37.2%; p-value .002) were more frequent during second wave. The 28-day mortality rate (9.6 vs. 10%; p-value 1) was not different. CONCLUSIONS: There has been a different clinical spectrum of COVID-19 amongst KTR with similar mortality between the two waves at a large Indian transplant centre.

Second wave of COVID-19 in Nigeria: Lessons from the first wave.

The COVID-19 pandemic struck the world unawares. The virus is now spreading as never before, despite the initial progress recorded by several countries towards kerbing the pandemic. As the pandemic continues to spread across Africa, there is a need for countries in the continent to re-evaluate, re-strategise, and re-invigorate their COVID-19 responses and efforts based on lessons from the first wave, and Nigeria is no exception. Before the second wave was officially announced by the health authorities on 17 December 2020, there were 78,434 confirmed cases and 1221 deaths reported with a case fatality rate (CFR) of 1.6%. To ensure that Nigeria achieves total pandemic control and reacts better given the possibility of a second wave, we propose workable recommendations to strengthen our preparedness and readiness efforts. Here, we argue that lessons learnt from the first wave of the COVID-19 pandemic can help Nigeria better react to the second wave.

IL-6-based mortality prediction model for COVID-19: Validation and update in multicenter and second wave cohorts.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a highly variable condition. Validated tools to assist in the early detection of patients at high risk of mortality can help guide medical decisions. OBJECTIVE: We sought to validate externally, as well as in patients from the second pandemic wave in Europe, our previously developed mortality prediction model for hospitalized COVID-19 patients. METHODS: Three validation cohorts were generated: 2 external with 185 and 730 patients from the first wave and 1 internal with 119 patients from the second wave. The probability of death was calculated for all subjects using our prediction model, which includes peripheral blood oxygen saturation/fraction of inspired oxygen ratio, neutrophil-to-lymphocyte ratio, lactate dehydrogenase, IL-6, and age. Discrimination and calibration were evaluated in the validation cohorts. The prediction model was updated by reestimating individual risk factor effects in the overall cohort (N = 1477). RESULTS: The mortality prediction model showed good performance in the external validation cohorts 1 and 2, and in the second wave validation cohort 3 (area under the receiver-operating characteristic curve, 0.94, 0.86, and 0.86, respectively), with excellent calibration (calibration slope, 0.86, 0.94, and 0.79; intercept, 0.05, 0.03, and 0.10, respectively). The updated model accurately predicted mortality in the overall cohort (area under the receiver-operating characteristic curve, 0.91), which included patients from both the first and second COVID-19 waves. The updated model was also useful to predict fatal outcome in patients without respiratory distress at the time of evaluation. CONCLUSIONS: This is the first COVID-19 mortality prediction model validated in patients from the first and second pandemic waves. The COR+12 online calculator is freely available to facilitate its implementation (https://utrero-rico.shinyapps.io/COR12_Score/).

Data analysis and prediction of the COVID-19 outbreak in the first and second waves for top 5 affected countries in the world.

In this paper, we introduce a SEIATR compartmental model to analyze and predict the COVID-19 outbreak in the Top 5 affected countries in the world, namely the USA, India, Brazil, France, and Russia. The officially confirmed cases and death due to COVID-19 from the day of the official confirmation to June 30, 2021 are considered for each country. Primarily, we use the data to make a comparison between the cumulative cases and deaths due to COVID-19 among these five different countries. This analysis allows us to infer the key parameters associated with the dynamics of the disease for these five different countries. For example, the analysis reveals that the infection rate is much higher in the USA, Brazil, and France compared to that of India and Russia, while the recovery rate is found almost the same for these countries. Further, the death rate is measured higher in Brazil as opposed to India, where it is found much lower among the remaining countries. We then use the SEIART compartmental model to characterize the first and second waves of these countries, as well as to investigate and identify the influential model parameters and nature of the virus transmissibility in respective countries. Besides estimating the time-dependent reproduction number (Rt) for these countries, we also use the model to predict the peak size and the time occurring peak in respective countries. The analysis demonstrates that COVID-19 was observed to be much more infectious in the second wave than the first wave in all countries except France. The results also demonstrate that the epidemic took off very quickly in the USA, India, and Brazil compared to two other countries considered in this study. Furthermore, the prediction of the epidemic peak size and time produced by our model provides a very good agreement with the officially confirmed cases data for all countries expect Brazil.