Case Fatality Risk of the First Pandemic Wave of Coronavirus Disease 2019 (COVID-19) in China

Estimation and prediction of the multiply exponentially decaying daily case fatality rate of COVID-19

The spread of the COVID-19 disease has had significant social and economic impacts all over the world. Numerous measures such as school closures, social distancing, and travel restrictions were implemented during the COVID-19 pandemic outbreak. Currently, as we move into the post-COVID-19 world, we must be prepared for another pandemic outbreak in the future. Having experienced the COVID-19 pandemic, it is imperative to ascertain the conclusion of the pandemic to return to normalcy and plan for the future. One of the beneficial features for deciding the termination of the pandemic disease is the small value of the case fatality rate (CFR) of coronavirus disease 2019 (COVID-19). There is a tendency of gradually decreasing CFR after several increases in CFR during the COVID-19 pandemic outbreak. However, it is difficult to capture the time-dependent CFR of a pandemic outbreak using a single exponential coefficient because it contains multiple exponential decays, i.e., fast and slow decays. Therefore, in this study, we develop a mathematical model for estimating and predicting the multiply exponentially decaying CFRs of the COVID-19 pandemic in different nations: the Republic of Korea, the USA, Japan, and the UK. We perform numerical experiments to validate the proposed method with COVID-19 data from the above-mentioned four nations.

What is the role of aerosol transmission in SARS-Cov-2 Omicron spread in Shanghai?

The Omicron transmission has infected nearly 600,000 people in Shanghai from March 26 to May 31, 2022. Combined with different control measures taken by the government in different periods, a dynamic model was constructed to investigate the impact of medical resources, shelter hospitals and aerosol transmission generated by clustered nucleic acid testing on the spread of Omicron. The parameters of the model were estimated by least square method and MCMC method, and the accuracy of the model was verified by the cumulative number of asymptomatic infected persons and confirmed cases in Shanghai from March 26 to May 31, 2022. The result of numerical simulation demonstrated that the aerosol transmission figured prominently in the transmission of Omicron in Shanghai from March 28 to April 30. Without aerosol transmission, the number of asymptomatic subjects and symptomatic cases would be reduced to 130,000 and 11,730 by May 31, respectively. Without the expansion of shelter hospitals in the second phase, the final size of asymptomatic subjects and symptomatic cases might reach 23.2 million and 4.88 million by May 31, respectively. Our results also revealed that expanded vaccination played a vital role in controlling the spread of Omicron. However, even if the vaccination rate were 100%, the transmission of Omicron should not be completely blocked. Therefore, other control measures should be taken to curb the spread of Omicron, such as widespread antiviral therapies, enhanced testing and strict tracking quarantine measures. This perspective could be utilized as a reference for the transmission and prevention of Omicron in other large cities with a population of 10 million like Shanghai.

Elucidating the role of digital technologies in bridling the ramifications of COVID-19 in restaurant services: moderation of pandemic susceptibility and severity

Purpose

The purpose of this study is to augment the perceived service quality (PSQ) dimensions as well as evaluate the effects of pandemic susceptibility and severity by appending crucial enablers of customer satisfaction (CS) in the restaurant industry (RI).

Design/methodology/approach

The top 10 restaurants from Mumbai and Kolkata were selected based on the Conde Nast Traveller Magazine List, 2020. The study used a cross-sectional design to collect responses from 840 respondents across the two major metropolitans of India after the second wave of COVID-19 by employing a structured questionnaire. The proffered hypotheses in this study were validated using factor analysis and structural equation modelling (SEM) techniques.

Findings

This research espies pivotal facilitators of CS and customers' perceived value (CPV). The results divulge that food quality (FQ) and tangibility dimensions markedly enhance CS while the FQ and digital technologies (DT) dimensions augment CPV in Indian restaurants. The study asserts that CPV acts as a partial mediator between FQ and DT on the one hand and CS on the other. In addition, perceived pandemic susceptibility (PPSU) and perceived pandemic severity (PPSE) moderate the association between CPV and CS in restaurants.

Research limitations/implications

This study exemplifies the critical enablers of CS and CPV that may invigorate restaurant owners, managers and policymakers to prioritize the identified dimensions to aggrandize CS and CPV quotients.

Originality/value

The study enriches the literature by assimilating DT and CPV dimensions in a comprehensive theoretical framework. The research is unique in attempting to unfurl the moderating effects of PPSU and PPSE in the RI.

Role of diabetes mellitus in the clinical course and outcome of SARS-CoV-2 infected patients

PURPOSE

Our aim was to study patients with diabetes mellitus and SARS-CoV-2-infection diagnosed during the first pandemic wave in Greece.

METHODS

Cases were retrieved from the national database of SARS-CoV-2 infections.

RESULTS

We studied 2624 SARS-CoV-2 infected cases, including 157 with diabetes. Patients with diabetes more often had other comorbidities (68.8 vs. 24.1%; p-value < 0.001). Among patients with diabetes, 149 (94.9%) developed symptomatic disease (COVID-19) compared to 1817 patients (73.7%) without diabetes (p-value < 0.001). A total of 126 patients with diabetes and COVID-19 were hospitalized and 41 died (27.5% case-fatality rate compared to 7.5% among patients without diabetes; p-value < 0.001). Patients with diabetes more often were hospitalized, developed complications, were admitted to the intensive care unit (ICU), received invasive mechanical ventilation, and died compared to patients without diabetes (p-values < 0.001 to 0.002 for all comparisons). Multivariate logistic regression analyses revealed that diabetes, having other comorbidities, and older age were significantly associated with higher risk for hospitalization, ICU admission, invasive mechanical ventilation, and death, and that obesity was significantly associated with higher risk for hospitalization, ICU admission, and mechanical intubation, while female gender protected against these outcomes.

CONCLUSION

COVID-19 is associated with increased rates of serious morbidity and adverse outcome in patients with diabetes and represents a severe illness for them.

Incubation period, clinical and lung CT features for early prediction of COVID-19 deterioration: development and internal verification of a risk model

Background

Most severe, critical, or mortal COVID-19 cases often had a relatively stable period before their status worsened. We developed a deterioration risk model of COVID-19 (DRM-COVID-19) to predict exacerbation risk and optimize disease management on admission.

Method

We conducted a multicenter retrospective cohort study with 239 confirmed symptomatic COVID-19 patients. A combination of the least absolute shrinkage and selection operator (LASSO), change-in-estimate (CIE) screened out independent risk factors for the multivariate logistic regression model (DRM-COVID-19) from 44 variables, including epidemiological, demographic, clinical, and lung CT features. The compound study endpoint was progression to severe, critical, or mortal status. Additionally, the model's performance was evaluated for discrimination, accuracy, calibration, and clinical utility, through internal validation using bootstrap resampling (1000 times). We used a nomogram and a network platform for model visualization.

Results

In the cohort study, 62 cases reached the compound endpoint, including 42 severe, 18 critical, and two mortal cases. DRM-COVID-19 included six factors: dyspnea [odds ratio (OR) 4.89;confidence interval (95% CI) 1.53–15.80], incubation period (OR 0.83; 95% CI 0.68–0.99), number of comorbidities (OR 1.76; 95% CI 1.03–3.05), D-dimer (OR 7.05; 95% CI, 1.35–45.7), C-reactive protein (OR 1.06; 95% CI 1.02–1.1), and semi-quantitative CT score (OR 1.50; 95% CI 1.27–1.82). The model showed good fitting (Hosmer–Lemeshow goodness, X²(8) = 7.0194, P = 0.53), high discrimination (the area under the receiver operating characteristic curve, AUROC, 0.971; 95% CI, 0.949–0.992), precision (Brier score = 0.051) as well as excellent calibration and clinical benefits. The precision-recall (PR) curve showed excellent classification performance of the model (AUC_PR = 0.934). We prepared a nomogram and a freely available online prediction platform (https://deterioration-risk-model-of-covid-19.shinyapps.io/DRMapp/).

Conclusion

We developed a predictive model, which includes the including incubation period along with clinical and lung CT features. The model presented satisfactory prediction and discrimination performance for COVID-19 patients who might progress from mild or moderate to severe or critical on admission, improving the clinical prognosis and optimizing the medical resources.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-01986-0.

Healthcare Disparities and Outcomes of Cancer Patients in a Community Setting from a COVID-19 Epicenter

There have been numerous studies demonstrating how cancer patients are at an increased risk of mortality. Within New York City, our community hospital emerged as an epicenter of the first wave of the pandemic in the spring of 2020 and serves a unique population that is predominately uninsured, of a lower income, and racially/ethnically diverse. In this single institution retrospective study, the authors seek to investigate COVID-19 diagnosis, severity and mortality in patients with an active cancer diagnosis. Demographic, clinical characteristics, treatment, SARS-CoV-2 laboratory results, and outcomes were evaluated. In our community hospital during the first wave of the COVID-19 pandemic in the United States, patients with active cancer diagnosis appear to be at increased risk for mortality (30%) and severe events (50%) due to the SARS-CoV-2 infection compared to the general population. A higher proportion of active cancer patients with Medicaid insurance, Hispanic ethnicity, other race, and male sex had complications and death from COVID-19 infection. The pandemic has highlighted the health inequities that exist in vulnerable patient populations and underserved communities such as ours.

Modeling transmission of SARS-CoV-2 Omicron in China

Having adopted a dynamic zero-COVID strategy to respond to SARS-CoV-2 variants with higher transmissibility since August 2021, China is now considering whether, and for how long, this policy can remain in place. The debate has thus shifted towards the identification of mitigation strategies for minimizing disruption to the healthcare system in the case of a nationwide epidemic. To this aim, we developed an age-structured stochastic compartmental susceptible-latent-infectious-removed-susceptible model of SARS-CoV-2 transmission calibrated on the initial growth phase for the 2022 Omicron outbreak in Shanghai, to project COVID-19 burden (that is, number of cases, patients requiring hospitalization and intensive care, and deaths) under hypothetical mitigation scenarios. The model also considers age-specific vaccine coverage data, vaccine efficacy against different clinical endpoints, waning of immunity, different antiviral therapies and nonpharmaceutical interventions. We find that the level of immunity induced by the March 2022 vaccination campaign would be insufficient to prevent an Omicron wave that would result in exceeding critical care capacity with a projected intensive care unit peak demand of 15.6 times the existing capacity and causing approximately 1.55 million deaths. However, we also estimate that protecting vulnerable individuals by ensuring accessibility to vaccines and antiviral therapies, and maintaining implementation of nonpharmaceutical interventions could be sufficient to prevent overwhelming the healthcare system, suggesting that these factors should be points of emphasis in future mitigation policies.

Pressure on the Health-Care System and Intensive Care Utilization During the COVID-19 Outbreak in the Lombardy Region of Italy: A Retrospective Observational Study in 43,538 Hospitalized Patients

During the spring of 2020, the COVID-19 epidemic caused an unprecedented demand for intensive care resources in Lombardy, Italy. Using data on 43,538 hospitalized patients admitted between February 21 and July 12, 2020, we evaluated variations in intensive care unit (ICU) admissions and mortality over three periods: the early phase (February 20-March 13), the period of highest pressure on healthcare (March 14-April 25, when COVID-19 patients exceeded the ICU pre-pandemic bed capacity), and the declining phase (April 26-July 12).

Compared to the early phase, patients above 70 years of age were admitted less often to an ICU during highest pressure on healthcare (odds ratio OR 0.47, 95%CI: 0.41-0.54) with longer delays (incidence rate ratio IRR 1.82, 95%CI: 1.52-2.18), and lower chances of death in ICU (OR 0.47, 95%CI: 0.34-0.64). Patients under 56 years of age reported more limited changes in the probability (OR 0.65, 95%CI: 0.56-0.76) and delay to ICU admission (IRR 1.16, 95%CI: 0.95-1.42) and an increased mortality (OR 1.43, 95%CI: 1.00-2.07). In the declining phase, all quantities decreased for all age groups.

These patterns may suggest that limited healthcare resources during the peak epidemic phase in Lombardy forced a shift in ICU admission criteria to prioritize patients with higher chances of survival.

Meta-analysis and adjusted estimation of COVID-19 case fatality risk in India and its association with the underlying comorbidities

Management of coronavirus disease 2019 (COVID-19) in India is a top government priority. However, there is a lack of COVID-19 adjusted case fatality risk (aCFR) estimates and information on states with high aCFR. Data on COVID-19 cases and deaths in the first pandemic wave and 17 state-specific geodemographic, socio-economic, health and comorbidity-related factors were collected. State-specific aCFRs were estimated, using a 13-day lag for fatality. To estimate country-level aCFR in the first wave, state estimates were meta-analysed based on inverse-variance weighting and aCFR as either a fixed- or random-effect. Multiple correspondence analyses, followed by univariable logistic regression, were conducted to understand the association between aCFR and geodemographic, health and social indicators. Based on health indicators, states likely to report a higher aCFR were identified. Using random- and fixed-effects models, cumulative aCFRs in the first pandemic wave on 27 July 2020 in India were 1.42% (95% CI 1.19%-1.70%) and 2.97% (95% CI 2.94%-3.00%), respectively. At the end of the first wave, as of 15 February 2021, a cumulative aCFR of 1.18% (95% CI 0.99%-1.41%) using random and 1.64% (95% CI 1.64%-1.65%) using fixed-effects models was estimated. Based on high heterogeneity among states, we inferred that the random-effects model likely provided more accurate estimates of the aCFR for India. The aCFR was grouped with the incidence of diabetes, hypertension, cardiovascular diseases and acute respiratory infections in the first and second dimensions of multiple correspondence analyses. Univariable logistic regression confirmed associations between the aCFR and the proportion of urban population, and between aCFR and the number of persons diagnosed with diabetes, hypertension, cardiovascular diseases and stroke per 10,000 population that had visited NCD (Non-communicable disease) clinics. Incidence of pneumonia was also associated with COVID-19 aCFR. Based on predictor variables, we categorised 10, 17 and one Indian state(s) expected to have a high, medium and low aCFR risk, respectively. The current study demonstrated the value of using meta-analysis to estimate aCFR. To decrease COVID-19 associated fatalities, states estimated to have a high aCFR must take steps to reduce co-morbidities.

Comparison of first and second waves of COVID-19 through severity markers in ICU patients of a developing country

Background: Many countries are experiencing outbreaks of the second wave of COVID-19 infection. With these outbreaks, the severity of the disease is still ambiguously projected. Certain inflammatory markers are known to be associated with the severity of the disease and regular monitoring of these biomarkers in intensive care unit admissions is paramount to improve clinical outcomes.Objectives: This study was aimed to compare the severity markers of the patients infected during the first wave versus the second wave in an intensive care unit.Methods: We conducted a retrospective study obtaining patient's data from hospital records, admitted during the first wave in March-May 2020, and compared the data with those COVID-19 patients admitted during the second wave from October-November 2020. A descriptive comparison was done among the patients admitted to intensive care unit (ICU) during both waves of the pandemic.Results: 92 patients from first wave and 68 patients from second wave were included in the analysis, all admitted to ICU with equal gender distribution. Increased age and length of ICU stay was observed during the first wave. BMI, in-hospital mortality and invasive ventilation were statistically indifferent between both the waves. There was significantly higher APACHE-II during first wave (p = 0.007), but SOFA at day 1 (p = 0.213) and day 7 of ICU stay remain indifferent (p = 0.119). Inflammatory markers were less severe during second wave while only neutrophils and lymphocytes were found to peak higher.Conclusion: Most of the severity markers were less intense during the early analysis of second wave.

Hereditary colorectal cancer syndromes and the COVID-19 pandemic: results from a survey conducted in patients enrolled in a dedicated registry

Purpose

The coronavirus 2019 (COVID-19) pandemic has had profound consequences also for non-infected patients. This study aimed to evaluate the impact of the pandemic on the quality of life of a population with hereditary gastrointestinal cancer predisposition syndromes and on the surveillance/oncological care program of patients enrolled in a dedicated registry.

Methods

The study was conducted by means of an online self-report survey during the first Italian national lockdown. The survey comprised four sections: demographics; perception/knowledge of COVID-19; impact of the COVID-19 pandemic on surveillance and cancer care; health status (SF-12 questionnaire).

Results

211 complete questionnaires were considered. 25.12% of respondents reported being not at all frightened by COVID-19, 63.98% felt “not at all” or “a little” more fragile than the healthy general population, and 66.82% felt the coronavirus to be no more dangerous to them than the healthy general population. 88.15% of respondents felt protected knowing they were monitored by a team of dedicated professionals.

Conclusion

Patients with hereditary gastrointestinal cancer predisposition syndromes reported experiencing less fear related to COVID-19 than the healthy general population. The study results suggest that being enrolled in a dedicated registry can reassure patients, especially during health crises.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11136-021-02973-4.

Meteorological conditions are heterogeneous factors for COVID-19 risk in China

Whether meteorological factors influence COVID-19 transmission is an issue of major public health concern, but available evidence remains unclear and limited for several reasons, including the use of report date which can lag date of symptom onset by a considerable period. We aimed to generate reliable and robust evidence of this relationship based on date of onset of symptoms. We evaluated important meteorological factors associated with daily COVID-19 counts and effective reproduction number (R_t) in China using a two-stage approach with overdispersed generalized additive models and random-effects meta-analysis. Spatial heterogeneity and stratified analyses by sex and age groups were quantified and potential effect modification was analyzed. Nationwide, there was no evidence that temperature and relative humidity affected COVID-19 incidence and R_t. However, there were heterogeneous impacts on COVID-19 risk across different regions. Importantly, there was a negative association between relative humidity and COVID-19 incidence in Central China: a 1% increase in relative humidity was associated with a 3.92% (95% CI, 1.98%-5.82%) decrease in daily counts. Older population appeared to be more sensitive to meteorological conditions, but there was no obvious difference between sexes. Linear relationships were found between meteorological variables and COVID-19 incidence. Sensitivity analysis confirmed the robustness of the association and the results based on report date were biased. Meteorological factors play heterogenous roles on COVID-19 transmission, increasing the possibility of seasonality and suggesting the epidemic is far from over. Considering potential climatic associations, we should maintain, not ease, current control measures and surveillance.

Despite vaccination, China needs non-pharmaceutical interventions to prevent widespread outbreaks of COVID-19 in 2021

COVID-19 vaccination is being conducted in over 200 countries and regions to control SARS-CoV-2 transmission and return to a pre-pandemic lifestyle. However, understanding when non-pharmaceutical interventions (NPIs) can be lifted as immunity builds up remains a key question for policy makers. To address this, we built a data-driven model of SARS-CoV-2 transmission for China. We estimated that, to prevent the escalation of local outbreaks to widespread epidemics, stringent NPIs need to remain in place at least one year after the start of vaccination. Should NPIs alone be capable of keeping the reproduction number (R_t) around 1.3, the synergetic effect of NPIs and vaccination could reduce the COVID-19 burden by up to 99% and bring R_t below the epidemic threshold in about 9 months. Maintaining strict NPIs throughout 2021 is of paramount importance to reduce COVID-19 burden while vaccines are distributed to the population, especially in large populations with little natural immunity.

Using data-driven epidemiological modelling, Yu et al. estimate that, even with increasing vaccine availability, China will have to maintain stringent non-pharmaceutical interventions for at least a year to prevent new widespread outbreaks of COVID-19.

Estimating age-specific COVID-19 fatality risk and time to death by comparing population diagnosis and death patterns: Australian data

Background

Mortality is a key component of the natural history of COVID-19 infection. Surveillance data on COVID-19 deaths and case diagnoses are widely available in the public domain, but they are not used to model time to death because they typically do not link diagnosis and death at an individual level. This paper demonstrates that by comparing the unlinked patterns of new diagnoses and deaths over age and time, age-specific mortality and time to death may be estimated using a statistical method called deconvolution.

Methods

Age-specific data were analysed on 816 deaths among 6235 cases over age 50 years in Victoria, Australia, from the period January through December 2020. Deconvolution was applied assuming logistic dependence of case fatality risk (CFR) on age and a gamma time to death distribution. Non-parametric deconvolution analyses stratified into separate age groups were used to assess the model assumptions.

Results

It was found that age-specific CFR rose from 2.9% at age 65 years (95% CI:2.2 – 3.5) to 40.0% at age 95 years (CI: 36.6 – 43.6). The estimated mean time between diagnosis and death was 18.1 days (CI: 16.9 – 19.3) and showed no evidence of varying by age (heterogeneity P = 0.97). The estimated 90% percentile of time to death was 33.3 days (CI: 30.4 – 36.3; heterogeneity P = 0.85). The final age-specific model provided a good fit to the observed age-stratified mortality patterns.

Conclusions

Deconvolution was demonstrated to be a powerful analysis method that could be applied to extensive data sources worldwide. Such analyses can inform transmission dynamics models and CFR assessment in emerging outbreaks. Based on these Australian data it is concluded that death from COVID-19 occurs within three weeks of diagnosis on average but takes five weeks in 10% of fatal cases. Fatality risk is negligible in the young but rises above 40% in the elderly, while time to death does not seem to vary by age.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01314-w.

Estimation of novel coronavirus (COVID-19) reproduction number and case fatality rate: A systematic review and meta-analysis

BACKGROUND AND AIMS

Realizing the transmission potential and the magnitude of the coronavirus disease 2019 (COVID-19) aids public health monitoring, strategies, and preparation. Two fundamental parameters, the basic reproduction number (R 0) and case fatality rate (CFR) of COVID-19, help in this understanding process. The objective of this study was to estimate the R 0 and CFR of COVID-19 and assess whether the parameters vary in different regions of the world.

METHODS

We carried out a systematic review to find the reported estimates of the R 0 and the CFR in articles from international databases between January 1 and August 31, 2020. Random-effect models and Forest plots were implemented to evaluate the mean effect size of R 0 and the CFR. Furthermore, R 0 and CFR of the studies were quantified based on geographic location, the tests/thousand population, and the median population age of the countries where the studies were conducted. To assess statistical heterogeneity among the selected articles, the I 2 statistic and the Cochran's Q test were used.

RESULTS

Forty-five studies involving R 0 and 34 studies involving CFR were included. The pooled estimation of R 0 was 2.69 (95% CI: 2.40, 2.98), and that of the CFR was 2.67 (2.25, 3.13). The CFR in different regions of the world varied significantly, from 2.49 (2.08, 2.94) in Asia to 3.40 (2.81, 4.04) in North America. We observed higher mean CFR values for the countries with lower tests (3.15 vs 2.16) and greater median population age (3.13 vs 2.27). However, R 0 did not vary significantly in different regions of the world.

CONCLUSIONS

An R 0 of 2.69 and a CFR of 2.67 indicate the severity of the COVID-19. Although R 0 and CFR may vary over time, space, and demographics, we recommend considering these figures in control and prevention measures.

The differential demographic pattern of coronavirus disease 2019 fatality outside Hubei and from six hospitals in Hubei, China: a descriptive analysis

BACKGROUND

The coronavirus disease 2019 (COVID-19) epidemic has been largely controlled in China, to the point where case fatality rate (CFR) data can be comprehensively evaluated.

METHODS

Data on confirmed patients, with a final outcome reported as of 29 March 2020, were obtained from official websites and other internet sources. The hospitalized CFR (HCFR) was estimated, epidemiological features described, and risk factors for a fatal outcome identified.

RESULTS

The overall HCFR in China was estimated to be 4.6% (95% CI 4.5-4.8%, P < 0.001). It increased with age and was higher in males than females. Although the highest HCFR observed was in male patients ≥70 years old, the relative risks for death outcome by sex varied across age groups, and the greatest HCFR risk ratio for males vs. females was shown in the age group of 50-60 years, higher than age groups of 60-70 and ≥ 70 years. Differential age/sex HCFR patterns across geographical regions were found: the age effect on HCFR was greater in other provinces outside Hubei than in Wuhan. An effect of longer interval from symptom onset to admission was only observed outside Hubei, not in Wuhan. By performing multivariate analysis and survival analysis, the higher HCFR was associated with older age (both P < 0.001), and male sex (both P < 0.001). Only in regions outside Hubei, longer interval from symptom onset to admission, were associated with higher HCFR.

CONCLUSIONS

This up-to-date and comprehensive picture of COVID-19 HCFR and its drivers will help healthcare givers target limited medical resources to patients with high risk of fatality.

Infectivity, susceptibility, and risk factors associated with SARS-CoV-2 transmission under intensive contact tracing in Hunan, China

Several mechanisms driving SARS-CoV-2 transmission remain unclear. Based on individual records of 1178 potential SARS-CoV-2 infectors and their 15,648 contacts in Hunan, China, we estimated key transmission parameters. The mean generation time was estimated to be 5.7 (median: 5.5, IQR: 4.5, 6.8) days, with infectiousness peaking 1.8 days before symptom onset, with 95% of transmission events occurring between 8.8 days before and 9.5 days after symptom onset. Most transmission events occurred during the pre-symptomatic phase (59.2%). SARS-CoV-2 susceptibility to infection increases with age, while transmissibility is not significantly different between age groups and between symptomatic and asymptomatic individuals. Contacts in households and exposure to first-generation cases are associated with higher odds of transmission. Our findings support the hypothesis that children can effectively transmit SARS-CoV-2 and highlight how pre-symptomatic and asymptomatic transmission can hinder control efforts.

The Impact of COVID-19 Infection on the Postoperative Outcomes in Pancreatic Cancer Patients

BACKGROUND/AIM

The aim of this study is to report a case series of three patients who developed postoperative severe acute respiratory syndrome corona virus-2 (SARS-CoV-2) infection, although the initial tests were negative.

PATIENTS AND METHODS

Between April and September 2020, three patients submitted to pancreatoduodenectomy developed SARS-CoV-2 infection; their outcomes were compared to those of a similar group in which the postoperative outcomes were uneventful.

RESULTS

There were no significant differences between the two groups in terms of pre- and intraoperative outcomes; however, all of the three cases who developed SARS-CoV-2 infection postoperatively required re-admission in the intensive care unit and a longer hospital in stay. The overall mortality rate was null.

CONCLUSION

Patients submitted to pancreatoduodenectomy for pancreatic head cancer who develop SARS-COV-2 infection postoperatively need a more appropriate supportive care; however, the overall mortality does not appear to increase, justifying, in this way, the continuation of programmed oncological of surgeries.

Older Adults With Coronavirus Disease 2019: A Nationwide Study in Turkey

Background

A novel coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) occurred in China in December 2019 and has spread globally. In this study we aimed to describe the clinical characteristics and outcomes of hospitalized older adults with coronavirus disease 2019 (COVID-19) in Turkey.

Methods

We retrospectively analyzed the clinical data of hospitalized patients aged ≥ 60 years with confirmed COVID-19 from March 11, 2020, to May 27, 2020 using nationwide health database.

Results

In this nationwide cohort, a total of 16942 hospitalized older adults with COVID-19 were enrolled, of whom 8635 (51%) were women. Mean age was 71.2 ± 8.5 years, ranging from 60 to 113 years. Mortality rate before and after curfew was statistically different (32.2% vs 17.9%; p & 0.001, respectively). Through multivariate analysis of the causes of death in older patients, we found that male gender, diabetes mellitus, heart failure, chronic kidney disease, dementia, cancer, admission to intensive care unit, computed tomography finding compatible with COVID-19 were all significantly associated with mortality in entire cohort. In addition to abovementioned risk factors, in patients aged between 60-79 years, coronary artery disease, oxygen support need, total number of drugs, and cerebrovascular disease during hospitalization, and in patients 80 years of age and older acute coronary syndrome during hospitalization were also associated with increased risk of mortality.

Conclusions

In addition to the results of previous studies with smaller sample size, our results confirmed the age-related relationship between specific comorbidities and COVID-19 related mortality.

Antibody seroprevalence in the epicenter Wuhan, Hubei, and six selected provinces after containment of the first epidemic wave of COVID-19 in China

BACKGROUND

China implemented containment measures to stop SARS-CoV-2 transmission in response to the COVID-19 epidemic. After the first epidemic wave, we conducted population-based serological surveys to determine extent of infection, risk factors for infection, and neutralization antibody levels to assess the real infections in the random sampled population.

METHODS

We used a multistage, stratified cluster random sampling strategy to conduct serological surveys in three areas - Wuhan, Hubei Province outside Wuhan, and six provinces selected on COVID-19 incidence and containment strategy. Participants were consenting individuals >1 year old who resided in the survey area >14 days during the epidemic. Provinces screened sera for SARS-CoV-2-specific IgM, IgG, and total antibody by two lateral flow immunoassays and one magnetic chemiluminescence enzyme immunoassay; positive samples were verified by micro-neutralization assay.

FINDINGS

We enrolled 34,857 participants (overall response rate, 92%); 427 were positive by micro-neutralization assay. Wuhan had the highest weighted seroprevalence (4•43%, 95% confidence interval [95%CI]=3•48%-5•62%), followed by Hubei-ex-Wuhan (0•44%, 95%CI=0•26%-0•76%), and the other provinces (<0•1%). Living in Wuhan (adjusted odds ratio aOR=13•70, 95%CI= 7•91-23•75), contact with COVID-19 patients (aOR=7•35, 95%CI=5•05-10•69), and age over 40 (aOR=1•36, 95%CI=1•07-1•72) were significantly associated with SARS-CoV-2 infection. Among seropositives, 101 (24%) reported symptoms and had higher geometric mean neutralizing antibody titers than among the 326 (76%) without symptoms (30±2•4 vs 15±2•1, p<0•001).

INTERPRETATION

The low overall extent of infection and steep gradient of seropositivity from Wuhan to the outer provinces provide evidence supporting the success of containment of the first wave of COVID-19 in China. SARS-CoV-2 infection was largely asymptomatic, emphasizing the importance of active case finding and physical distancing. Virtually the entire population of China remains susceptible to SARS-CoV-2; vaccination will be needed for long-term protection.

FUNDING

This study was supported by the Ministry of Science and Technology (2020YFC0846900) and the National Natural Science Foundation of China (82041026, 82041027, 82041028, 82041029, 82041030, 82041032, 82041033).

Can a COVID-19 vaccination program guarantee the return to a pre-pandemic lifestyle?

COVID-19 vaccination programs have been initiated in several countries to control SARS-CoV-2 transmission and return to a pre-pandemic lifestyle. However, understanding when non-pharmaceutical interventions (NPIs) can be lifted as vaccination builds up and how to update priority groups for vaccination in real-time remain key questions for policy makers. To address these questions, we built a data-driven model of SARS-CoV-2 transmission for China. We estimated that, to prevent local outbreaks to escalate to major widespread epidemics, stringent NPIs need to remain in place at least one year after the start of vaccination. Should NPIs be capable to keep the reproduction number (Rt) around 1.3, a vaccination program could reduce up to 99% of COVID-19 burden and bring Rt below the epidemic threshold in about 9 months. Maintaining strict NPIs throughout 2021 is of paramount importance to reduce COVID-19 burden while vaccines are distributed to the population, especially in large populations with little natural immunity.

Transmission dynamics and control measures of COVID-19 outbreak in China: a modelling study

COVID-19 is reported to have been brought under control in China. To understand the COVID-19 outbreak in China and provide potential lessons for other parts of the world, in this study we apply a mathematical model with multiple datasets to estimate the transmissibility of the SARS-CoV-2 virus and the severity of the illness associated with the infection, and how both were affected by unprecedented control measures. Our analyses show that before 19th January 2020, 3.5% (95% CI 1.7-8.3%) of  infected people were detected; this percentage increased to 36.6% (95% CI 26.1-55.4%) thereafter. The basic reproduction number (R0) was 2.33 (95% CI 1.96-3.69) before 8th February 2020; then the effective reproduction number dropped to 0.04(95% CI 0.01-0.10). This estimation also indicates that control measures taken since 23rd January 2020 affected the transmissibility about 2 weeks after they were introduced. The confirmed case fatality rate is estimated at 9.6% (95% CI 8.1-11.4%) before 15 February 2020, and then it reduced to 0.7% (95% CI 0.4-1.0%). This shows that SARS-CoV-2 virus is highly transmissible but may be less severe than SARS-CoV-1 and MERS-CoV. We found that at the early stage, the majority of R0 comes from undetected infectious people. This implies that successful control in China was achieved through reducing the contact rates among people in the general population and increasing the rate of detection and quarantine of the infectious cases.

Assessing the impact of non-pharmaceutical interventions on the transmissibility and severity of COVID-19 during the first five months in the Western Pacific Region

While most countries in the Western Pacific Region (WPR) had similar trajectories of COVID-19 from January to May, their implementations of non-pharmaceutical interventions (NPIs) differed by transmission stages. To offer a better understanding for an implementation of multidisciplinary policies in COVID-19 control, we compared the impact of NPIs by assessing the transmissibility and severity of COVID-19 in different phases of the epidemic during the first five months in WPR. In this study, we estimated the piecewise instantaneous reproduction number (R_t) and the reporting delay-adjusted case-fatality ratio (dCFR) of COVID-19 in seven WPR jurisdictions: Hong Kong Special Administrative Region, Japan, Malaysia, Shanghai, Singapore, South Korea, and Taiwan. According to the results, implementing NPIs was associated with an apparent reduction of the piecewise R_t in two epidemic waves in general. However, large cluster outbreaks raised the piecewise R_t to a high level. We also observed relaxing the NPIs could result in an increase of R_t. The estimated dCFR ranged from 0.09% to 1.59% among the jurisdictions, except in Japan where an estimate of 5.31% might be due to low testing efforts. To conclude, in conjunction with border control measures to reduce influx of imported cases which might cause local outbreaks, other NPIs including social distancing measures along with case finding by rapid tests are also necessary to prevent potential large cluster outbreaks and transmissions from undetected cases. A comparatively lower CFR may reflect the health system capacity of these jurisdictions. In order to keep track of sustained disease transmission due to resumption of economic activities, a close monitoring of disease transmissibility is recommended in the relaxation phase. The report of transmission of SARS CoV-2 to pets in Hong Kong and to mink in farm outbreaks highlight for the control of COVID-19 and emerging infectious disease, the One Health approach is critical in understanding and accounting for how human, animals and environment health are intricately connected.

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Multidisciplinary One Health policies to combat COVID-19 are required in WPR.

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NPIs were associated with an apparent reduction in transmissibility of COVID-19.

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However, some large cluster outbreaks raised the transmissibility to a high level.

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We observed an increase in transmissibility when NPIs were partially lifted.

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A lower case-fatality ratio in WPR may reflect the health system capacity.

Database of epidemic trends and control measures during the first wave of COVID-19 in mainland China

OBJECTIVES

In this data collation study, we aimed to provide a comprehensive database describing the epidemic trends and responses during the first wave of coronavirus disease 2019 (COVID-19) throughout the main provinces in China.

METHODS

From mid-January to March 2020, we extracted publicly available data regarding the spread and control of COVID-19 from 31 provincial health authorities and major media outlets in mainland China. Based on these data, we conducted descriptive analyses of the epidemic in the six most-affected provinces.

RESULTS

School closures, travel restrictions, community-level lockdown, and contact tracing were introduced concurrently around late January but subsequent epidemic trends differed among provinces. Compared with Hubei, the other five most-affected provinces reported a lower crude case fatality ratio and proportion of critical and severe hospitalised cases. From March 2020, as the local transmission of COVID-19 declined, switching the focus of measures to the testing and quarantine of inbound travellers may have helped to sustain the control of the epidemic.

CONCLUSIONS

Aggregated indicators of case notifications and severity distributions are essential for monitoring an epidemic. A publicly available database containing these indicators and information regarding control measures is a useful resource for further research and policy planning in response to the COVID-19 epidemic.

Prevalence and Associated Risk Factors of Mortality Among COVID-19 Patients: A Meta-Analysis

OBJECTIVES

The main aim of this study was to find the prevalence of mortality among hospitalized COVID-19 infected patients and associated risk factors for death.

METHODS

Three electronic databases including PubMed, Science Direct and Google Scholar were searched to identify relevant cohort studies of COVID-19 disease from January 1, 2020, to August 11, 2020. A random-effects model was used to calculate pooled prevalence rate (PR), risk ratio (RR) and 95% confidence interval (CI) for both effect measures. Cochrane chi-square test statistic Q, [Formula: see text], and [Formula: see text] tests were used to measure the presence of heterogeneity. Publication bias and sensitivity of the included studies were also tested.

RESULTS

In this meta-analysis, a total of 58 studies with 122,191 patients were analyzed. The pooled prevalence rate of mortality among the hospitalized COVID-19 patients was 18.88%, 95% CI (16.46-21.30), p < 0.001. Highest mortality was found in Europe [PR 26.85%, 95% CI (19.41-34.29), p < 0.001] followed by North America [PR 21.47%, 95% CI (16.27-26.68), p < 0.001] and Asia [PR 14.83%, 95% CI (12.46- 17.21), p < 0.001]. An significant association were found between mortality among COVID-19 infected patients and older age (> 65 years vs. < 65 years) [RR 3.59, 95% CI (1.87-6.90), p < 0.001], gender (male vs. female) [RR 1.63, 95% CI (1.43-1.87), p < 0.001], ICU admitted patients [RR 3.72, 95% CI (2.70-5.13), p < 0.001], obesity [RR 2.18, 95% CI (1.10-4.34), p < 0.05], hypertension [RR 2.08,95% CI (1.79-2.43) p < 0.001], diabetes [RR 1.87, 95% CI (1.23-2.84), p < 0.001], cardiovascular disease [RR 2.51, 95% CI (1.20-5.26), p < 0.05], and cancer [RR 2.31, 95% CI (1.80-2.97), p < 0.001]. In addition, significant association for high risk of mortality were also found for cerebrovascular disease, COPD, coronary heart disease, chronic renal disease, chronic liver disease, chronic lung disease and chronic kidney disease.

CONCLUSION

This meta-analysis revealed that the mortality rate among COVID-19 patients was highest in the European region and older age, gender, ICU patients, patients with comorbidity had a high risk for case fatality. Those findings would help the health care providers to reduce the mortality rate and combat this pandemic to save lives using limited resources.

COVID-19 in an international European liver transplant recipient cohort

OBJECTIVE

Knowledge on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in liver transplant recipients is lacking, particularly in terms of severity of the disease. The aim of this study was to describe the demographic, baseline clinical characteristics and early outcomes of a European cohort of liver transplant recipients with SARS-CoV-2 infection.

DESIGN

We conducted an international prospective study across Europe on liver transplant recipients with SARS-CoV-2 infection confirmed by microbiological assay during the first outbreak of COVID-19 pandemic. Baseline characteristics, clinical presentation, management of immunosuppressive therapy and outcomes were collected.

RESULTS

57 patients were included (70% male, median (IQR) age at diagnosis 65 (57-70) years). 21 (37%), 32 (56%) and 21 (37%) patients had one cardiovascular disease, arterial hypertension and diabetes mellitus, respectively. The most common symptoms were fever (79%), cough (55%), dyspnoea (46%), fatigue or myalgia (56%) and GI symptoms (33%). Immunosuppression was reduced in 22 recipients (37%) and discontinued in 4 (7%). With this regard, no impact on outcome was observed. Forty-one (72%) subjects were hospitalised and 11 (19%) developed acute respiratory distress syndrome. Overall, we estimated a case fatality rate of 12% (95% CI 5% to 24%), which increased to 17% (95% CI 7% to 32%) among hospitalised patients. Five out of the seven patients who died had a history of cancer.

CONCLUSION

In this European multicentre prospective study of liver transplant recipients, COVID-19 was associated with an overall and in-hospital fatality rate of 12% (95% CI 5% to 24%) and 17% (95% CI 7% to 32%), respectively. A history of cancer was more frequent in patients with poorer outcome.

United States County-level COVID-19 Death Rates and Case Fatality Rates Vary by Region and Urban Status

COVID-19 is a global pandemic with uncertain death rates. We examined county-level population morality rates (per 100,000) and case fatality rates by US region and rural-urban classification, while controlling for demographic, socioeconomic, and hospital variables. We found that population mortality rates and case fatality rates were significantly different across region, rural-urban classification, and their interaction. All significant comparisons had p < 0.001. Northeast counties had the highest population mortality rates (27.4) but had similar case fatality rates (5.9%) compared to other regions except the Southeast, which had significantly lower rates (4.1%). Population mortality rates were highest in urban counties but conversely, case fatality rates were highest in rural counties. Death rates in the Northeast were driven by urban areas (e.g., small, East Coast states), while case fatality rates tended to be highest in the most rural counties for all regions, especially the Southwest. However, on further inspection, high case fatality rate percentages in the Southwest, as well as in overall US counties, were driven by a low case number. This makes it hard to distinguish genuinely higher mortality or an artifact of a small sample size. In summary, coronavirus deaths are not homogenous across the United States but instead vary by region and population and highlight the importance of fine-scale analysis.

Estimating unobserved SARS-CoV-2 infections in the United States

By March 2020, COVID-19 led to thousands of deaths and disrupted economic activity worldwide. As a result of narrow case definitions and limited capacity for testing, the number of unobserved severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections during its initial invasion of the United States remains unknown. We developed an approach for estimating the number of unobserved infections based on data that are commonly available shortly after the emergence of a new infectious disease. The logic of our approach is, in essence, that there are bounds on the amount of exponential growth of new infections that can occur during the first few weeks after imported cases start appearing. Applying that logic to data on imported cases and local deaths in the United States through 12 March, we estimated that 108,689 (95% posterior predictive interval [95% PPI]: 1,023 to 14,182,310) infections occurred in the United States by this date. By comparing the model's predictions of symptomatic infections with local cases reported over time, we obtained daily estimates of the proportion of symptomatic infections detected by surveillance. This revealed that detection of symptomatic infections decreased throughout February as exponential growth of infections outpaced increases in testing. Between 24 February and 12 March, we estimated an increase in detection of symptomatic infections, which was strongly correlated (median: 0.98; 95% PPI: 0.66 to 0.98) with increases in testing. These results suggest that testing was a major limiting factor in assessing the extent of SARS-CoV-2 transmission during its initial invasion of the United States.

The first two months of the COVID-19 pandemic in Bosnia and Herzegovina: Single-center experience

The novel coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still progressing and has been recorded in more than 210 countries and territories worldwide. In Bosnia and Herzegovina, the first cases of COVID- 19 were detected on March 5, 2020 in the entity of the Republic of Srpska and on March 9, 2020 in the entity of the Federation of Bosnia and Herzegovina. By May 16, 2020, more than 2,200 COVID-19 cases had been recorded in both entities, with a mortality rate of 5.8% (131 of 2,231 cases). The aim of this ongoing study is to present the current epidemiological and sociodemographic parameters of 380 COVID-19 patients diagnosed at the University Clinical Hospital Mostar (UCH Mostar) during the first two months of the COVID-19 pandemic. Of those 380 patients, 60 (15.8%) required hospitalization. The mortality rate was 5% (19/380). The highest mortality rate (15.2%, 12/79) was recorded in the patients aged ≥65 years. In addition to this single-center experience of the ongoing COVID-19 pandemic, we discuss the epidemiological mea-sures imposed in Bosnia and Herzegovina, with an emphasis on the restrictive measures. The COVID-19 pandemic is still ongoing in Bosnia and Herzegovina.

Delivery of hepato-pancreato-biliary surgery during the COVID-19 pandemic: an European-African Hepato-Pancreato-Biliary Association (E-AHPBA) cross-sectional survey

BACKGROUND

The extent of the COVID-19 pandemic and the resulting response has varied globally. The European and African Hepato-Pancreato-Biliary Association (E-AHPBA), the premier representative body for practicing HPB surgeons in Europe and Africa, conducted this survey to assess the impact of COVID-19 on HPB surgery.

METHODS

An online survey was disseminated to all E-AHPBA members to assess the effects of the pandemic on unit capacity, management of HPB cancers, use of COVID-19 screening and other aspects of service delivery.

RESULTS

Overall, 145 (25%) members responded. Most units, particularly in COVID-high countries (>100,000 cases) reported insufficient critical care capacity and reduced HPB operating sessions compared to COVID-low countries. Delayed access to cancer surgery necessitated alternatives including increased neoadjuvant chemotherapy for pancreatic cancer and colorectal liver metastases, and locoregional treatments for hepatocellular carcinoma. Other aspects of service delivery including COVID-19 screening and personal protective equipment varied between units and countries.

CONCLUSION

This study demonstrates that the COVID-19 pandemic has had a profound adverse impact on the delivery of HPB cancer care across the continents of Europe and Africa. The findings illustrate the need for safe resumption of cancer surgery in a "new" normal world with screening of patients and staff for COVID-19.

Risk of death by age and gender from CoVID-19 in Peru, March-May, 2020

Peru implemented strict social distancing measures during the early phase of the epidemic and is now experiencing one of the largest CoVID-19 epidemics in Latin America. Estimates of disease severity are an essential indicator to inform policy decisions about the intensity and duration of interventions needed to mitigate the outbreak. Here we derive delay-adjusted case fatality risks (aCFR) of CoVID-19 in a middle-income country in South America.We utilize government-reported time series of CoVID-19 cases and deaths in Peru stratified by age group and gender.As of May 25, 2020, we estimate the aCFR for men and women at 10.8% (95%CrI: 10.5-11.1%) and 6.5% (95%CrI: 6.2-6.8%), respectively, whereas the overall aCFR was estimated at 9.1% (95%CrI: 8.9-9.3%). Our results show that senior individuals have been the most severely affected by CoVID-19, particularly men, with an aCFR of nearly 60% for those aged 80- years. We also found that men have a significantly higher cumulative morbidity ratio across most age groups (proportion test, p-value< 0.001), with the exception of those aged 0-9 years.The ongoing CoVID-19 pandemic is generating a substantial mortality burden in Peru. Senior individuals, especially those older than 70 years, are being disproportionately affected by the CoVID-19 pandemic.

Sex differences in SARS-CoV-2 infection rates and the potential link to prostate cancer

The recent outbreak of infections and the pandemic caused by SARS-CoV-2 represent one of the most severe threats to human health in more than a century. Emerging data from the United States and elsewhere suggest that the disease is more severe in men. Knowledge gained, and lessons learned, from studies of the biological interactions and molecular links that may explain the reasons for the greater severity of disease in men, and specifically in the age group at risk for prostate cancer, will lead to better management of COVID-19 in prostate cancer patients. Such information will be indispensable in the current and post-pandemic scenarios.

From Influenza Virus to Novel Corona Virus (SARS-CoV-2)-The Contribution of Obesity

From the beginning of 2020, the governments and the health systems around the world are tackling infections and fatalities caused by the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) resulting in the coronavirus disease 2019 (COVID-19). This virus pandemic has turned more complicated as individuals with co-morbidities like diabetes, cardiovascular conditions and obesity are at a high risk of acquiring infection and suffering from a more severe course of disease. Prolonged viral infection and obesity are independently known to lower the immune response and a combination can thus result in a "cytokine storm" and a substantial weakening of the immune system. With the rise in obesity cases globally, the chances that obese individuals will acquire infection and need hospitalization are heightened. In this review, we discuss why obesity, a low-grade chronic inflammation, contributes toward the increased severity in COVID-19 patients. We suggest that increased inflammation, activation of renin-angiotensin-aldosterone system, elevated adipokines and higher ectopic fat may be the factors contributing to the disease severity, in particular deteriorating the cardiovascular and lung function, in obese individuals. We look at the many lessons learnt from the 2009 H1N1 influenza A pandemic and relate it to the very little but fast incoming information that is available from the SARS-CoV-2 infected individuals with overweight and obesity.