Early epidemiological indicators, outcomes, and interventions of COVID-19 pandemic: A systematic review

Gastrointestinal Manifestations and Outcomes of COVID-19: A Comprehensive Systematic Review and Meta-analysis

Introduction Pulmonary symptoms are the most prominent manifestations of Coronavirus disease 2019 (COVID-19). However, gastrointestinal (GI) symptoms have been reported widely as well. Literature describing the relation of these symptoms with outcomes of COVID-19 patients is limited in terms of sample size, geographic diversity, and the spectrum of GI symptoms included. We aim to evaluate the association of GI symptoms with outcomes of hospitalized COVID-19 patients. Methods A systematic review and meta-analysis of observational studies assessing GI symptoms and outcomes in COVID-19 patients were undertaken using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria and the Meta-analysis of Observational Studies in Epidemiology (MOOSE) checklist. Details on outcomes included ICU vs. non-ICU admission, severe vs. non-severe disease, invasive mechanical ventilation (IMV) vs. no-IMV use, oxygen saturation <90% vs. >90%, in-hospital mortality vs. discharged alive and survivors. We obtained the odds ratio (OR), 95% confidence interval (95%CI), and forest plots. Sensitivity analysis was used to analyze publication bias and heterogeneity. Results In 35 studies with 7931 confirmed COVID-19 patients, we found that anorexia (pooled OR:2.05; 95%CI: 1.36-3.09, p=0.0006) and abdominal pain (OR 2.80; 95%CI: 1.41-5.54, p=0.003) were associated with a higher risk of poor outcomes and no such association was found for diarrhea (OR 1.04; 95%CI: 0.85-1.26, p=0.71), nausea (OR 0.73; 95%CI: 0.38-1.39, p=0.34) and vomiting (OR 1.24; 95%CI 0.86-1.79, p=0.25). Conclusion The meta-analysis concludes that anorexia and abdominal pain are associated with poor outcomes in hospitalized COVID-19 patients, while diarrhea, nausea, and vomiting have no association. Future research should focus on whether detecting GI invasion in conjunction with fecal polymerase chain reaction (PCR) testing can aid in the early triage of high-risk individuals and improve outcomes.

Barriers to and facilitators of populational adherence to prevention and control measures of COVID-19 and other respiratory infectious diseases: a qualitative evidence synthesis

AIMS

To summarise the evidence on barriers to and facilitators of population adherence to prevention and control measures for coronavirus disease 2019 (COVID-19) and other respiratory infectious diseases.

METHODS

A qualitative synthesis was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis and the Cochrane Effective Practice and Organization of Care: Qualitative Evidence Synthesis. We performed an electronic search on MEDLINE, Embase and PsycINFO from their inception to March 2023.

RESULTS

We included 71 studies regarding COVID-19, pneumonia, tuberculosis, influenza, pertussis and H1N1, representing 5966 participants. The measures reported were vaccinations, physical distancing, stay-at-home policy, quarantine, self-isolation, facemasks, hand hygiene, contact investigation, lockdown, infection prevention and control guidelines, and treatment. Tuberculosis-related measures were access to care, diagnosis and treatment completion. Analysis of the included studies yielded 37 barriers and 23 facilitators.

CONCLUSIONS

This review suggests that financial and social support, assertive communication, trust in political authorities and greater regulation of social media enhance adherence to prevention and control measures for COVID-19 and infectious respiratory diseases. Designing and implementing effective educational public health interventions targeting the findings of barriers and facilitators highlighted in this review are key to reducing the impact of infectious respiratory diseases at the population level.

Tracking Covid-19 cases and deaths in the United States: metrics of pandemic progression derived from a queueing framework

We analyze the progression of COVID-19 in the United States over a nearly one-year period beginning March 1, 2020 with a novel metric motivated by queueing models, tracking partial-average day-of-event and cumulative probability distributions for events, where events are points in time when new cases and new deaths are reported. The partial average represents the average day of all events preceding a point of time, and is an indicator as to whether the pandemic is accelerating or decelerating in the context of the entire history of the pandemic. The measure supplements traditional metrics, and also enables direct comparisons of case and death histories on a common scale. We also compare methods for estimating actual infections and deaths to assess the timing and dynamics of the pandemic by location. Three example states are graphically compared as functions of date, as well as Hong Kong as an example that experienced a pronounced recent wave of the pandemic. In addition, statistics are compared for all 50 states. Over the period studied, average case day and average death day varied by two to five months among the 50 states, depending on data source, with the earliest averages in New York and surrounding states, as well as Louisiana.

Clinical features and haematological parameters associated with COVID-19 severity among hospitalized patients: A retrospective observational study from Tribal Central India

Background

Reports describing demographics, clinical characteristics, hospital course, morbidity, and mortality in patients in the Indian setting have been published, but they are based on limited numbers of cases. The present study among the patients with known outcomes enabled us to better understand the disease process and progression of COVID-19 cases and to correlate the factors affecting the outcome.

Methods

This was a record-based, retrospective observational study of patients admitted to COVID-19 Hospital. We have retrieved medical records for all the hospitalized patients with a laboratory confirmed COVID-19 diagnosis with a known outcome (discharged or died) between April 1, 2020 and February 28, 2021. The extracted data included basic demographics, signs and symptoms, duration of hospitalization, and laboratory parameters. Categorical variables were analysed using either the chisquare test or Fisher's exact test. The level of significance was set at P < 0.05.

Results

The mean age of severe and moderate patients was 38.71 years, compared to 34.95 years for mild patients. No gender difference was observed for the severe/moderate, and mild cases. The mortality rate among severe/moderate cases was 11.6%, whereas it was 3.9% in mild patients. Laboratory parameters which were significantly (p < 0.05) raised among the dead compared to discharged patients included CT score, D-dimer, CRP, ALT, AST, and alkaline phosphatase.

Conclusion

Clinical and laboratory characteristics reflect the pathophysiology of disease and thus help clinicians recognise the severity of medical illness. They also facilitate the creation of management protocols for clinical care that results in improvement in patient related outcomes.

A novel method to detect the early warning signal of COVID-19 transmission

Background

Infectious illness outbreaks, particularly the corona-virus disease 2019 (COVID-19) pandemics in recent years, have wreaked havoc on human society, and the growing number of infected patients has put a strain on medical facilities. It’s necessary to forecast early warning signals of potential outbreaks of COVID-19, which would facilitate the health ministry to take some suitable control measures timely to prevent or slow the spread of COVID-19. However, since the intricacy of COVID-19 transmission, which connects biological and social systems, it is a difficult task to predict outbreaks of COVID-19 epidemics timely.

Results

In this work, we developed a new model-free approach, called, the landscape network entropy based on Auto-Reservoir Neural Network (ARNN-LNE), for quantitative analysis of COVID-19 propagation, by mining dynamic information from regional networks and short-term high-dimensional time-series data. Through this approach, we successfully identified the early warning signals in six nations or areas based on historical data of COVID-19 infections.

Conclusion

Based on the newly published data on new COVID-19 disease, the ARNN-LNE method can give early warning signals for the outbreak of COVID-19. It’s worth noting that ARNN-LNE only relies on small samples data. Thus, it has great application potential for monitoring outbreaks of infectious diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07603-z.

Performance of the APOP-screener for predicting in-hospital mortality in older COVID-19 patients: a retrospective study

BACKGROUND

A variety of prediction models concerning COVID-19 have been proposed since onset of the pandemic, but to this date no gold standard exists. Mortality rates show a sharp increase with advancing age but with the large heterogeneity of this population in terms of comorbidities, vulnerability and disabilities, identifying risk factors is difficult. Therefore, we aimed to research the multidimensional concept of frailty, measured by the Acute Presenting Older Patient (APOP)-screener, as a risk factor for in-hospital mortality in older COVID-19 patients.

METHODS

All consecutive patients of 70 years or older, with a PCR confirmed COVID-19 infection and a completed APOP-score, presenting at the Emergency Department (ED) of the Jeroen Bosch Hospital, the Netherlands, between February 27th 2020 and February 1st 2021 were retrospectively included. We gathered baseline characteristics and scored the CCI and CFS from patient records. The primary outcome was in-hospital mortality.

RESULTS

A total of 292 patients met the inclusion criteria. Approximately half of the patients were considered frail by the APOP or CFS. 127 patients (43.5%) scored frail on the CFS, 158 (54.1%) scored high risk on the APOP-screener. 79 patients (27.1%) died during their hospital admission. The APOP-screener showed a significantly elevated risk of in-hospital mortality when patients scored both high risk of functional and evidence of cognitive impairment (OR 2.24, 95% 1.18-4.25). Significant elevation of in-hospital mortality was found for the high CCI-scores (≥ 5)(OR 1.78, 95% 1.02-3.11), but not for the highest CFS category (5-9, frail) (OR 1.35, 95% 0.75-2.47). The discriminatory performance of the APOP, CFS and CCI were comparable (AUC resp. 0.59 (0.52-0.66), 0.54 (0.46-0.62) and 0.58 (0.51-0.65)).

CONCLUSION

Although the elevated risk for in-hospital mortality found for the most frail patients as scored by the APOP, this instrument has poor discriminatory value. Additionally, the CFS did not show significance in predicting in-hospital mortality and had a poor discriminatory value as well. Therefore, treatment decisions based on frailty or comorbidities alone should be made with caution. Approaching the heterogeneity of the older population by adding frailty as assessed by the APOP-score to existing prediction models may enhance the predictive value of these models.

Post COVID-19 condition and its physical, mental and social implications: protocol of a 2-year longitudinal cohort study in the Belgian adult population

Background

Since the onset of the COVID-19 pandemic, most research has focused on the pathophysiology and management of the acute symptoms of COVID-19, yet some people tend to experience symptoms beyond the acute phase of infection, that is, Post COVID-19 condition (PCC). However, evidence on the long-term health impacts of a COVID-19 infection are still scarce. The purpose of this paper is to describe the COVIMPACT study, which aims to set up a cohort of people who have been tested positive for COVID-19 and study the evolution of their physical, mental and social health over the medium (3 months) and long term (two years), and the factors associated with an (un)favorable evolution.

Methods

COVIMPACT is a longitudinal cohort study organised over a two-years period between April 2021 and April 2023. The eligible population is all people aged 18 years and older, living in Belgium, with a recent COVID-19 infection and contacted by the health authorities for contact tracing. Two questionnaires are used: a baseline questionnaire that aims to assess the initial health status of the participants and their status during the acute phase of the illness, and a follow-up questionnaire that is sent every three months after participants enter into the cohort. A matched non-COVID-19 control group was also selected. As of November 1, 2021, 10,708 people completed the baseline questionnaire (5% of the eligible population) and the follow-up participation rate was 79%. In total, 48% of the cohort participants appeared to fit the proposed case definition of PCC (i.e. report at least one symptom related to their COVID-19 infection three months afterwards).

Discussion

This study was designed to provide timely information on the short and long term impact of a COVID-19 infection, to stakeholders such as policymakers, health practitioners and people with PCC. Although the follow-up participation rate was good (79%), the participation rate of the eligible population was low (5%). Compared to other studies, this study has a large sample, of non-hospitalised and hospitalised people, who will be followed over a long period of 3 months to two years post infection, and with a global approach to their health.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13690-022-00906-2.

COVID-19 and Influenza Vaccination Campaign in a Research and University Hospital in Milan, Italy

Background: Healthcare workers (HCWs) are a historical key target of influenza vaccination programs. For the 2021–2022 season, WHO considered the coadministration of a flu and a COVID-19 vaccine as acceptable and recommended it to allow for higher uptake of both vaccines. The aim of this study was to investigate demographic and occupational features of vaccinated HCWs, reasons behind flu vaccine acceptance and a possible effect of the coadministration of a COVID-19 vaccine, in order to potentially draw general conclusions on HCWs’ attitude towards flu vaccination and inform further strategies for consistent improvement of vaccine acceptance. Methods: a promotional and educational campaign, a gaming strategy, and vaccination delivery through both a large central hub and on-site ambulatories, were the implemented strategies. In the central hub, the flu/COVID-19 vaccine coadministration was offered. Statistical descriptive analysis, multiple correspondence analysis (MCA) and logistic regression models were performed. Results: 2381 HCWs received the flu vaccine, prompting a vaccination coverage rate (VCR) of 52.0% versus 43.1% in the 2020–2021 campaign. Furthermore, 50.6% vaccinated HCWs belonged to the 18–39 years-old age group. The most expressed reasons for vaccine uptake were “Vaccination is the most effective strategy of prevention” (n = 1928, 81.0%), “As HCW it’s my duty to get vaccinated to protect my patients” (n = 766, 32.2%), and the group of COVID-19-related reasons (n = 586, 24.6%). In addition, 23.3% HCWs received the flu vaccine in the current campaign but not in the previous one (newly vaccinated) and the flu/COVID-19 vaccine coadministration was more frequent in this group. A total of 51.0% HCWs were hesitant towards the coadministration, while residents and nurses showed the highest propensity to receive it. Conclusions: in the second year of the COVID-19 pandemic, the Fondazione’s influenza VCR continued to increase, with the greatest participation among HCWs aged 18–39 years. A potential propelling role of the COVID-19 vaccine coadministration was highlighted.

What Is the Impact of Early and Subsequent Epidemic Characteristics on the Pre-delta COVID-19 Epidemic Size in the United States?

It is still uncertain how the epidemic characteristics of COVID-19 in its early phase and subsequent waves contributed to the pre-delta epidemic size in the United States. We identified the early and subsequent characteristics of the COVID-19 epidemic and the correlation between these characteristics and the pre-delta epidemic size. Most (96.1% (49/51)) of the states entered a fast-growing phase before the accumulative number of cases reached (30). The days required for the number of confirmed cases to increase from 30 to 100 was 5.6 (5.1−6.1) days. As of 31 March 2021, all 51 states experienced at least 2 waves of COVID-19 outbreaks, 23.5% (12/51) experienced 3 waves, and 15.7% (8/51) experienced 4 waves, the epidemic size of COVID-19 was 19,275−3,669,048 cases across the states. The pre-delta epidemic size was significantly correlated with the duration from 30 to 100 cases (p = 0.003, r = −0.405), the growth rate of the fast-growing phase (p = 0.012, r = 0.351), and the peak cases in the subsequent waves (K1 (p < 0.001, r = 0.794), K2 (p < 0.001, r = 0.595), K3 (p < 0.001, r = 0.977), and K4 (p = 0.002, r = 0.905)). We observed that both early and subsequent epidemic characteristics contribute to the pre-delta epidemic size of COVID-19. This identification is important to the prediction of the emerging viral infectious diseases in the primary stage.

Association Between Drug Treatments and the Incidence of Liver Injury in Hospitalized Patients With COVID-19

The outbreak of coronavirus disease 2019 (COVID-19) has led to the emergence of global health care. In this study, we aimed to explore the association between drug treatments and the incidence of drug-induced liver injury (DILI) in hospitalized patients with COVID-19. A retrospective study was conducted on 5113 COVID-19 patients in Hubei province, among which 395 incurred liver injury. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated by Cox proportional hazards models. The results showed that COVID-19 patients who received antibiotics (HR 1.97, 95% CI: 1.55–2.51, p < 0.001), antifungal agents (HR 3.10, 95% CI: 1.93–4.99, p < 0.001) and corticosteroids (HR 2.31, 95% CI: 1.80–2.96, p < 0.001) had a higher risk of DILI compared to non-users. Special attention was given to the use of parenteral nutrition (HR 1.82, 95% CI: 1.31–2.52, p < 0.001) and enteral nutrition (HR 2.71, 95% CI: 1.98–3.71, p < 0.001), which were the risk factors for liver injury. In conclusion, this study suggests that the development of DILI in hospitalized patients with COVID-19 needs to be closely monitored, and the above-mentioned drug treatments may contribute to the risk of DILI.

Antibody-mediated procoagulant platelet formation in COVID-19 is AKT dependent

BACKGROUND

Thromboembolic events are frequently reported in patients infected with the SARS-CoV-2. Recently, we observed that platelets from patients with severe COVID-19 infection express procoagulant phenotype. The molecular mechanisms that induce the generation of procoagulant platelets in COVID-19 patients are not completely understood.

OBJECTIVES

In this study, we investigated the role of AKT (also known as Protein Kinase B), which is the major downstream effector of PI3K (phosphoinositid-3-kinase) (PI3K/AKT) signaling pathway in platelets from patients with COVID-19.

PATIENTS AND METHODS

Platelets, Sera and IgG from COVID-19 patients who were admitted to the intensive care unit (ICU) were analyzed by flow cytometry as well as western blot and adhesion assays.

RESULTS

Platelets from COVID-19 patients showed significantly higher levels of phosphorylated AKT, which was correlated with CD62p expression and phosphatidylserine (PS) externalization. In addition, healthy platelets incubated with sera or IgGs from ICU COVID-19 patients induced phosphorylation of PI3K and AKT and were dependent on Fc-gamma-RIIA (FcγRIIA). In contrast, ICU COVID-19 sera mediated generation of procoagulant platelets was not dependent on GPIIb/IIIa. Interestingly, the inhibition of phosphorylation of both proteins AKT and PI3K prevented the generation of procoagulant platelets.

CONCLUSIONS

Our study shows that pAKT/AKT signaling pathway is associated with the formation of procoagulant platelets in severe COVID-19 patients without integrin GPIIb/IIIa engagement. The inhibition of PI3K/AKT phosphorylation might represent a promising strategy to reduce the risk for thrombosis in patients with severe COVID-19.

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.

Delayed Diagnosis and Treatment of Cancer Patients During the COVID-19 Pandemic in Henan, China: An Interrupted Time Series Analysis

Objective

To investigate the possible impact of lockdown policies on the diagnosis and treatment of cancer patients in Henan, China.

Design Setting and Participants

We collected data from the Henan Cancer Hospital, affiliated with Zhengzhou University. The monthly numbers of inpatient admissions from January 2014 to December 2019 were used to forecast the number of inpatient admissions in 2020, which was then compared to the actual number of patients admitted during the pandemic to evaluate how the actual number diverges from this forecast. We conducted an interrupted time series analysis using the autoregressive integrated moving average (ARIMA) model.

Main Outcomes and Measures

For specific diagnoses, treatment modalities, and age groups, we compared the changes in monthly admissions after the pandemic with the forecasted changes from the model.

Results

The observed overall monthly number of inpatient admissions decreased by 20.2% [95% confidence interval (CI), 11.7-27.2%], 78.9% (95% CI, 77.3-80.4%), and 40.9% (95% CI, 35.6-45.5%) in January, February, and March 2020, respectively, as compared with those predicted using the ARIMA model. After the lockdown, visits for all treatment modalities decreased sharply. However, apparent compensation and recovery of the backlog appeared in later surgeries. As a result, the number of patients who underwent surgery in 2020 (30,478) was close to the number forecasted by the ARIMA model (30,185). In the same period, patients who received other treatments or underwent examinations were 106,074 and 36,968, respectively; the respective numbers that were forecasted by ARIMA were 127,775 and 60,025, respectively. These findings depict a decrease of 16.9 and 38.4% in patients who received other treatments or underwent examinations only, respectively. Regarding diagnosis, the reported incidence of various cancers decreased dramatically in February, with varying extent and speed of recovery.

Conclusion and Relevance

The COVID-19 pandemic has significantly delayed the diagnosis and treatment of cancer in Henan, China. Long-term research should be conducted to assess the future effects of lockdown policies.

Data-driven case fatality rate estimation for the primary lineage of SARS-CoV-2 in Poland

After more than one and a half year since the COVID-19 pandemics outbreak the scientific world is constantly trying to understand its dynamics. In this paper of the case fatality rates (CFR) for COVID-19 we study the historic data regarding mortality in Poland during the first six months of pandemic, when no SARS-CoV-2 variants of concern were present among infected. To this end, we apply competing risk models to perform both uni- and multivariate analyses on specific subpopulations selected by different factors including the key indicators: age, sex, hospitalization. The study explores the case fatality rate to find out its decreasing trend in time. Furthermore, we describe the differences in mortality among hospitalized and other cases indicating a sudden increase of mortality among hospitalized cases at the end of the 2020 spring season. Exploratory and multivariate analysis revealed the real impact of each variable and besides the expected factors indicating increased mortality (age, comorbidities) we track more non-obvious indicators. Recent medical care as well as the identification of the source contact, independently of the comorbidities, significantly impact an individual mortality risk. As a result, the study provides a twofold insight into the COVID-19 mortality in Poland. On one hand we explore mortality in different groups with respect to different variables, on the other we indicate novel factors that may be crucial in reducing mortality. The later can be coped, e.g. by more efficient contact tracing and proper organization and management of the health care system to accompany those who need medical care independently of comorbidities or COVID-19 infection.

Transmission dynamics and successful control measures of SARS-CoV-2 in the mega-size city of Guangzhou, China

The severe acute respiratory syndrome coronavirus 2 has caused a worldwide pandemic. Control measures differ among countries and have a varying degree of effectiveness, which requires assessment. To evaluate the effectiveness of public health interventions of the coronavirus disease 2019 (COVID-19) in Guangzhou by 3 periods according to interventions: January 7 to 22 (no intervention), January 23 to February 23 (implemented intensive interventions), and February 24 to May 17 (the normalization mode of COVID-19 prevention and control).We collected the information of 745 COVID-19 patients and their close contacts as well as control measures in Guangzhou from January 7 to May 17, 2020. We estimated the epidemiological characteristics, disease spectrum of COVID-19 cases, key time-to-event intervals, and effective reproduction number over the 3 periods. The basic reproduction number of severe acute respiratory syndrome coronavirus 2 was also calculated over period 1.Approximately 45.8%, 49.8%, and 4.4% of cases from close contacts were asymptomatic, symptomatic, and severe, respectively. The median incubation period was 5.3 days (the percentiles of 2.5-97.5, 1.5-18.4 days) and the median serial interval fitted with gamma distribution was 5.1 days (the percentiles of 2.5-97.5, 0.8-15.9 days). The estimated median of onset-to-quarantined time in Period 1 to 3 were 7.5, 3.4, and 2.9 days (the percentiles of 2.5-97.5, 2.1-14.2, 3.9-14.7, and 6.0-20.0 days) respectively and the median of onset-to-confirmation time in period 1 to 3 were 8.9, 4.9 and 2.4 days (the percentiles of 2.5-97.5, 2.6-16.6, 0.9-14.6, and 0.5-11.8 days). In period 1, the reproduction number was 0.9 (95% confidence interval, 0.5-1.4) and fluctuated below 1.0 before January 22 except for January 14. The effective reproduction number gradually decreased in the period 2 with the lowest point of 0.1 on February 20, then increased again since March 27 and reach a spike of 1.8 on April 12. The number decreased to below 1.0 after April 17 and decreased further to <0.2 after May 7 in the period 3.Under prospective dynamic observation, close contacts turned into infected cases could provide a spectrum of COVID-19 cases from real-world settings. The lockdown of Wuhan and closed-loop management of people arriving Guangzhou were effective in halting the spread of the COVID-19 cases to Guangzhou. The spread of COVID-19 was successfully controlled in Guangzhou by social distancing, wearing a face mask, handwashing, disinfection in key places, mass testing, extensive contact tracing, and strict quarantine of close contacts.

The Effect of Influenza Vaccination on COVID-19 Morbidity, Severity and Mortality: Systematic Review and Meta-Analysis

Coronavirus disease 2019 (COVID-19) pandemic is rapidly developing worldwide with a high mortality rate. In this meta-analysis study, the effect of influenza vaccination on the prevention of COVID-19 and its consequences in patients were investigated. The systematic search for this study was performed from November 2019 to 25 November 2020, in the databases of Medline, PubMed, Scopus, Web of Science, Embase, Ebsco, Cochrane and medRxiv. Search terms used included COVID-19, coronavirus, SARS-CoV-2, covid, influenza, flu, grippe and vaccine. The present study examined the association between influenza vaccination and COVID-19 including COVID-19 infection, mortality, hospitalisation and intensive care unit (ICU) admission. Finally, the pooled estimates for different outcomes were calculated by the software for statistics and data science (STATA) version 15 and I2 was used to determine the heterogeneity. By analysing the data of articles, the pooled estimates of these data indicated that influenza vaccination could lower probability of COVID-19 infection up to 24% (OR = 0.77; 95% CI: 0.65, 0.91), of death up to 32% (OR = 0.68; 95% CI: 0.42, 1.11), of the hospitalisation up to 25% (OR = 0.75; 95% CI: 0.46; 1.23) and of admission to ICU up to 29% (OR = 0.71; 95% CI: 0.40, 1.27). Influenza vaccination can help decrease the COVID-19 infection and reduce hospitalisation and the need for ICU and mortality rates.

Characteristics and severity of COVID-19 among Sudanese patients during the waves of the pandemic

COVID-19 is associated with marked morbidity and mortality. COVID-19 symptoms ranged from mild symptoms to severe pneumonia requiring admission to intensive care unit. Imperial College reported that, this second wave in Khartoum is expected to be similar to the first wave. The aim of our study was to study the characteristics and severity of COVID-19 among Sudanese patients during the waves of the pandemic. A hospital-based analytical Cross-Sectional study assessed the characteristics of COVID-19 patients who attended Imperial Hospital since November 2020, Khartoum, Sudan. Data were collected, retrospectively, from the medical records of COVID-19 patients. The characteristics of the patients were recorded. The statistical package for social sciences (SPSS-23) was used to describe and analyze the data. Descriptive statistics and chi-square test were used; tests were considered statistically significant when p < 0.05. Of the 138 participants, 75.4% were aged above 60 years. Males were 61.6%. Severe cases were 37.7%, with higher rate in the third wave (p = 0.000). Duration of hospitalization was ≤ 5 days in 60.9% of the cases, majority were from the 2nd wave (p = 0.001). Comorbidities of COVID-19 patients were more among non-severe cases (p = 0.001). COVID-19 symptoms were more prevalent in non-severe cases. Complications were more in severe cases (p = 0.000). Odds ratio of having ischemic stroke was 6.833 [95%CI: 2.092-22.321] based on COVID-19 severity. The elderly population were the majority. More males were getting admitted. Atypical symptoms were reported beside the common symptoms. Wider multi-center studies are recommended in order to complete the big picture of COVID-19 in Sudan.

General practice attendances among patients attending a post-COVID-19 clinic: a pilot study

Background

About 10–35% of people with COVID-19 need medical care within 3 weeks of infection. However, the prevalence of ongoing care needs among those experiencing severe COVID-19 illness is unclear.

Aim

This pilot study aimed to address this knowledge gap by examining GP attendance trends among patients attending a post-COVID-19 hospital follow-up clinic, 3–6 months after an initial clinic visit.

Design & setting

Data were collected from adult patients attending a post-COVID-19 follow-up clinic at the Mater Misericordiae University Hospital (MMUH), Dublin, Ireland.

Method

Participants completed questionnaires outlining their demographics; medical histories; emergency hospital admissions and readmissions where applicable; and, where relevant, GP attendances following hospital discharge. Analyses were conducted using descriptive and inferential statistics.

Results

Participants’ (n = 153) median age was 43.5 years (interquartile range [IQR] = 30.9–52.1 years). There were 105 females (68.6%, 95% confidence interval [CI] = 61.3% to 75.9%). Various medical histories were reported among participants. Sixty-seven (43.2%, 95% CI = 35.9% to 51.6%) received emergency COVID-19 hospital care. Older adults, males, intensive care unit [ICU] admissions, and readmissions were common among hospital attendees. Of the hospital attendees, 16 (24%, 95% CI = 13.7% to 34.2%) attended GPs within 7 days of hospital discharge, and 26 (39%, 95% CI = 27.3% to 50.7%) within 30 days. Older adults, people with pre-existing medical conditions, and individuals admitted to ICU and/or readmitted to hospital were common among general practice attendees.

Conclusion

Persistent health issues appear to be common among patients with severe COVID-19, particularly those who are older adults, have pre-existing health problems, and who had been in ICU and/or readmission care. Larger scale studies of ongoing COVID-19 care needs in primary care and general practice are required.

Biomarkers and outcomes of COVID-19 hospitalisations: systematic review and meta-analysis

OBJECTIVE

To evaluate association between biomarkers and outcomes in COVID-19 hospitalised patients. COVID-19 pandemic has been a challenge. Biomarkers have always played an important role in clinical decision making in various infectious diseases. It is crucial to assess the role of biomarkers in evaluating severity of disease and appropriate allocation of resources.

DESIGN AND SETTING

Systematic review and meta-analysis. English full text observational studies describing the laboratory findings and outcomes of COVID-19 hospitalised patients were identified searching PubMed, Web of Science, Scopus, medRxiv using Medical Subject Headings (MeSH) terms COVID-19 OR coronavirus OR SARS-CoV-2 OR 2019-nCoV from 1 December 2019 to 15 August 2020 following Meta-analyses Of Observational Studies in Epidemiology (MOOSE) guidelines.

PARTICIPANTS

Studies having biomarkers, including lymphocyte, platelets, D-dimer, lactate dehydrogenase (LDH), C reactive protein (CRP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine, procalcitonin (PCT) and creatine kinase (CK), and describing outcomes were selected with the consensus of three independent reviewers.

MAIN OUTCOME MEASURES

Composite poor outcomes include intensive care unit admission, oxygen saturation <90%, invasive mechanical ventilation utilisation, severe disease, in-hospital admission and mortality. The OR and 95% CI were obtained and forest plots were created using random-effects models. Publication bias and heterogeneity were assessed by sensitivity analysis.

RESULTS

32 studies with 10 491 confirmed COVID-19 patients were included. We found that lymphopenia (pooled-OR: 3.33 (95% CI: 2.51-4.41); p<0.00001), thrombocytopenia (2.36 (1.64-3.40); p<0.00001), elevated D-dimer (3.39 (2.66-4.33); p<0.00001), elevated CRP (4.37 (3.37-5.68); p<0.00001), elevated PCT (6.33 (4.24-9.45); p<0.00001), elevated CK (2.42 (1.35-4.32); p=0.003), elevated AST (2.75 (2.30-3.29); p<0.00001), elevated ALT (1.71 (1.32-2.20); p<0.00001), elevated creatinine (2.84 (1.80-4.46); p<0.00001) and LDH (5.48 (3.89-7.71); p<0.00001) were independently associated with higher risk of poor outcomes.

CONCLUSION

Our study found a significant association between lymphopenia, thrombocytopenia and elevated levels of CRP, PCT, LDH, D-dimer and COVID-19 severity. The results have the potential to be used as an early biomarker to improve the management of COVID-19 patients, by identification of high-risk patients and appropriate allocation of healthcare resources in the pandemic.

Cross-National Variations in COVID-19 Mortality: The Role of Diet, Obesity and Depression

Background: The COVID-19 pandemic has been characterized by wide variations in mortality across nations. Some of this variability may be explained by medical comorbidities such as obesity and depression, both of which are strongly correlated with dietary practices such as levels of sugar and seafood consumption. Methods: COVID-19 mortality indices for 156 countries were obtained from the Johns Hopkins University’s data aggregator. Correlations between these variables and (a) per capita consumption of sugar and seafood, and (b) country-wise prevalence of depression and obesity were examined. Results: Sugar consumption (r = 0.51, p < 0.001) and prevalence of obesity (r = 0.66, p < 0.001) and depression (r = 0.56, p < 0.001) were positively correlated with crude mortality rates, while seafood consumption was negatively correlated with the infection fatality rate (r = −0.28, p = 0.015). These effects were significant even after correcting for potential confounders. The associations with depression and obesity remained significant upon multivariate regression. Conclusions: Both obesity and depression, which are associated with inflammatory dysregulation, may be related to cross-national variations in COVID-19 mortality, while seafood consumption may be protective. These findings have implications in terms of protecting vulnerable individuals during the current pandemic.

Experiences of nurses caring for perinatal women and newborns during the COVID-19 pandemic: A descriptive qualitative study

Aim

Nurses are pivotal in caring for patients infected with COVID‐19. Little is known about experiences of nurses in maternity care during the pandemic. Therefore, this study aimed to describe nurses’ experiences of caring for perinatal women and newborns during the pandemic.

Design

A descriptive qualitative study was conducted.

Methods

Data were collected from August–November 2020 using focus group and in‐depth interviews. A total of 24 nurses working in maternity and newborn care units participated in the study. Content analysis method was used for data analysis.

Results

The participants’ clinical experience ranged from 6 months–26 years. Three major themes emerged as follows: “making every effort to prevent COVID‐19 infection,” “caring for perinatal women and newborns with COVID‐19 infection or suspected infection” and “job stress and professional growth during the pandemic.” Participants reported that they needed more support in terms of staffing and mental health.

COVID-19 Outcomes Amongst Patients With Pre-existing Cardiovascular Disease and Hypertension

INTRODUCTION

 Coronavirus disease 2019 (COVID-19) has multiorgan involvement and its severity varies with the presence of pre-existing risk factors like cardiovascular disease (CVD) and hypertension (HTN). Therefore, it is important to evaluate their effect on outcomes of COVID-19 patients. The objective of this meta-analysis and meta-regression is to evaluate outcomes of COVID-19 amongst patients with CVD and HTN.

METHODS

English full-text observational studies having data on epidemiological characteristics of patients with COVID-19 were identified searching PubMed from December 1, 2019, to July 31, 2020, following Meta-analysis Of Observational Studies in Epidemiology (MOOSE) protocol. Studies having pre-existing CVD and HTN data that described outcomes including mortality and invasive mechanical ventilation (IMV) utilization were selected. Using random-effects models, risk of composite poor outcomes (meta-analysis) and isolated mortality and IMV utilization (meta-regression) were evaluated. Pooled prevalence of CVD and HTN, correlation coefficient (r) and odds ratio (OR) were estimated. The forest plots and correlation plots were created using random-effects models.

RESULTS

Out of 29 studies (n=27,950) that met the criteria, 28 and 27 studies had data on CVD and HTN, respectively. Pooled prevalence of CVD was 18.2% and HTN was 32.7%. In meta-analysis, CVD (OR: 3.36; 95% CI: 2.29-4.94) and HTN (OR: 1.94; 95% CI: 1.57-2.40) were associated with composite poor outcome. In age-adjusted meta-regression, pre-existing CVD was having significantly higher correlation of IMV utilization (r: 0.28; OR: 1.3; 95% CI: 1.1-1.6) without having any association with mortality (r: -0.01; OR: 0.9; 95% CI: 0.9-1.1) among COVID-19 hospitalizations. HTN was neither correlated with higher IMV utilization (r: 0.01; OR: 1.0; 95% CI: 0.9-1.1) nor correlated with higher mortality (r: 0.001; OR: 1.0; 95% CI: 0.9-1.1).

CONCLUSION

In age-adjusted analysis, though we identified pre-existing CVD as a risk factor for higher utilization of mechanical ventilation, pre-existing CVD and HTN had no independent role in increasing mortality.

Early impact of school closure and social distancing for COVID-19 on the number of inpatients with childhood non-COVID-19 acute infections in Japan

Many countries have implemented school closures as part of social distancing measures intended to control the spread of coronavirus disease 2019 (COVID-19). The aim of this study was to assess the early impact of nationwide school closure (March-May 2020) and social distancing for COVID-19 on the number of inpatients with major childhood infectious diseases in Japan. Using data from the Diagnosis Procedure Combination system in Japan, we identified patients aged 15 years or younger with admissions for a diagnosis of upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), influenza, gastrointestinal infection (GII), appendicitis, urinary tract infection (UTI), or skin and soft tissue infection (SSTI) between July 2018 and June 2020. Changes in the trend of the weekly number of inpatients between the two periods were assessed using interrupted time-series analysis. A total of 75,053 patients in 210 hospitals were included. The overall weekly number of inpatients was decreased by 52.5%, 77.4%, and by 83.4% in the last week of March, April, and May 2020, respectively, when compared on a year-on-year basis. The estimated impact was a reduction of 581 (standard error 42.9) inpatients per week in the post-school-closure period (p < 0.001). The main part of the reduction was for pre-school children. Remarkable decreases in the number of inpatients with URI, LRTI, and GII were observed, while there were relatively mild changes in the other groups.Conclusion: We confirmed a marked reduction in the number of inpatients with childhood non-COVID-19 acute infections in the post-school-closure period. What is Known: • Most countries have implemented social distancing measures to limit the spread of the novel coronavirus disease 2019 (COVID-19). • A large decrease in pediatric emergency visits has been reported from several countries after the social distancing. What is New: • Based on administrative claims data, a marked reduction in the number of inpatients for childhood non-COVID-19 acute infections was found in the post-school-closure period in Japan. • The magnitude of the reduction was different between the disease groups.

Obesity a predictor of outcomes of COVID-19 hospitalized patients-A systematic review and meta-analysis

Coronavirus disease 2019 (COVID-19) pandemic is a global health crisis. Very few studies have reported association between obesity and severity of COVID-19. In this meta-analysis, we assessed the association of obesity and outcomes in COVID-19 hospitalized patients. Data from observational studies describing the obesity or body mass index and outcomes of COVID-19 hospitalized patients from December 1, 2019, to August 15, 2020, was extracted following PRISMA guidelines with a consensus of two independent reviewers. Adverse outcomes defined as intensive care units, oxygen saturation less than 90%, invasive mechanical ventilation, severe disease, and in-hospital mortality. The odds ratio (OR) and 95% confidence interval (95% CI) were obtained and forest plots were created using random-effects models. A total of 10 studies with 10,233 confirmed COVID-19 patients were included. The overall prevalence of obesity in our study was 33.9% (3473/10,233). In meta-analysis, COVID-19 patient with obesity had higher odds of poor outcomes compared with better outcomes with a pooled OR of 1.88 (95% CI: 1.25-2.80; p = 0.002), with 86% heterogeneity between studies (p < 0.00001). Our study suggests a significant association between obesity and COVID-19 severity and poor outcomes. Our results findings may have important suggestions for the clinical management and future research of obesity and COVID-19.