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1.
Public Health Res Pract ; 31(3)2021 Sep 08.
Article in English | MEDLINE | ID: covidwho-1471205

ABSTRACT

Emerging evidence, based on the synthesis of reports from past infectious disease-related public health emergencies, supports an association between previous pandemics and a heightened risk of suicide or suicide-related behaviours and outcomes. Anxiety associated with pandemic media reporting appears to be one critical contributing factor. Social isolation, loneliness, and the disconnect that can result from public health strategies during global pandemics also appear to increase suicide risk in vulnerable individuals. Innovative suicide risk assessment and prevention strategies are needed to recognise and adapt to the negative impacts of pandemics on population mental health.


Subject(s)
COVID-19/epidemiology , Pandemics , Suicide/prevention & control , Suicide/statistics & numerical data , Anxiety/epidemiology , Anxiety/psychology , COVID-19/psychology , Humans , Loneliness/psychology , Mental Health , Public Health , Risk Assessment/methods , SARS-CoV-2 , Social Isolation/psychology , Suicide/psychology
2.
Sensors (Basel) ; 21(19)2021 Sep 27.
Article in English | MEDLINE | ID: covidwho-1468448

ABSTRACT

Early and self-identification of locomotive degradation facilitates us with awareness and motivation to prevent further deterioration. We propose the usage of nine squat and four one-leg standing exercise features as input parameters to Machine Learning (ML) classifiers in order to perform lower limb skill assessment. The significance of this approach is that it does not demand manpower and infrastructure, unlike traditional methods. We base the output layer of the classifiers on the Short Test Battery Locomotive Syndrome (STBLS) test used to detect Locomotive Syndrome (LS) approved by the Japanese Orthopedic Association (JOA). We obtained three assessment scores by using this test, namely sit-stand, 2-stride, and Geriatric Locomotive Function Scale (GLFS-25). We tested two ML methods, namely an Artificial Neural Network (ANN) comprised of two hidden layers with six nodes per layer configured with Rectified-Linear-Unit (ReLU) activation function and a Random Forest (RF) regressor with number of estimators varied from 5 to 100. We could predict the stand-up and 2-stride scores of the STBLS test with correlation of 0.59 and 0.76 between the real and predicted data, respectively, by using the ANN. The best accuracies (R-squared values) obtained through the RF regressor were 0.86, 0.79, and 0.73 for stand-up, 2-stride, and GLFS-25 scores, respectively.


Subject(s)
Locomotion , Machine Learning , Feasibility Studies , Lower Extremity , Risk Assessment
5.
J Med Ethics ; 46(8): 505-507, 2020 08.
Article in English | MEDLINE | ID: covidwho-1467731

ABSTRACT

COVID-19 is reducing the ability to perform surgical procedures worldwide, giving rise to a multitude of ethical, practical and medical dilemmas. Adapting to crisis conditions requires a rethink of traditional best practices in surgical management, delving into an area of unknown risk profiles. Key challenging areas include cancelling elective operations, modifying procedures to adapt local services and updating the consenting process. We aim to provide an ethical rationale to support change in practice and guide future decision-making. Using the four principles approach as a structure, Medline was searched for existing ethical frameworks aimed at resolving conflicting moral duties. Where insufficient data were available, best guidance was sought from educational institutions: National Health Service England and The Royal College of Surgeons. Multiple papers presenting high-quality, reasoned, ethical theory and practice guidance were collected. Using this as a basis to assess current practice, multiple requirements were generated to ensure preservation of ethical integrity when making management decisions. Careful consideration of ethical principles must guide production of local guidance ensuring consistent patient selection thus preserving equality as well as quality of clinical services. A critical issue is balancing the benefit of surgery against the unknown risk of developing COVID-19 and its associated complications. As such, the need for surgery must be sufficiently pressing to proceed with conventional or non-conventional operative management; otherwise, delaying intervention is justified. For delayed operations, it is our duty to quantify the long-term impact on patients' outcome within the constraints of pandemic management and its long-term outlook.


Subject(s)
Coronavirus Infections/complications , Decision Making/ethics , Ethics, Medical , General Surgery/ethics , Health Equity/ethics , Pandemics/ethics , Patient Selection/ethics , Pneumonia, Viral/complications , Betacoronavirus , COVID-19 , Coronavirus Infections/virology , Cost-Benefit Analysis , England , Ethical Analysis , Ethical Theory , Humans , Informed Consent/ethics , Moral Obligations , Pneumonia, Viral/virology , Practice Guidelines as Topic , Principle-Based Ethics , Risk Assessment , SARS-CoV-2 , State Medicine , Surgeons , Surgical Procedures, Operative
7.
J Vasc Interv Radiol ; 32(1): 33-38, 2021 01.
Article in English | MEDLINE | ID: covidwho-1454337

ABSTRACT

PURPOSE: To determine effect of body mass index (BMI) on safety and cancer-related outcomes of thermal ablation for renal cell carcinoma (RRC). MATERIALS AND METHODS: This retrospective study evaluated 427 patients (287 men and 140 women; mean [SD] age, 72 [12] y) who were treated with thermal ablation for RCC between October 2006 and December 2017. Patients were stratified by BMI into 3 categories: normal weight (18.5-24.9 kg/m2), overweight (25-29.9 kg/m2), and obese (≥ 30 kg/m2). Of 427 patients, 71 (16%) were normal weight, 157 (37%) were overweight, and 199 (47%) were obese. Complication rates, local recurrence, and residual disease were compared in the 3 cohorts. RESULTS: No differences in technical success between normal-weight, overweight, and obese patients were identified (P = .72). Primary technique efficacy rates for normal-weight, overweight, and obese patients were 91%, 94%, and 93% (P = .71). There was no significant difference in RCC specific-free survival, disease-free survival, and metastasis-free survival between obese, overweight, and normal-weight groups (P = .72, P = .43, P = .99). Complication rates between the 3 cohorts were similar (normal weight 4%, overweight 2%, obese 3%; P = .71). CONCLUSIONS: CT-guided renal ablation is safe, feasible, and effective regardless of BMI.


Subject(s)
Body Mass Index , Carcinoma, Renal Cell/surgery , Cryosurgery , Kidney Neoplasms/surgery , Microwaves/therapeutic use , Obesity/diagnosis , Radiofrequency Ablation , Aged , Aged, 80 and over , Carcinoma, Renal Cell/mortality , Carcinoma, Renal Cell/secondary , Cryosurgery/adverse effects , Cryosurgery/mortality , Disease Progression , Disease-Free Survival , Female , Humans , Kidney Neoplasms/mortality , Kidney Neoplasms/pathology , Male , Microwaves/adverse effects , Middle Aged , Neoplasm Recurrence, Local , Obesity/mortality , Patient Safety , Radiofrequency Ablation/adverse effects , Radiofrequency Ablation/mortality , Retrospective Studies , Risk Assessment , Risk Factors , Time Factors , Treatment Outcome
8.
PLoS One ; 16(10): e0257807, 2021.
Article in English | MEDLINE | ID: covidwho-1456087

ABSTRACT

Patients after lung transplantation are at risk for life-threatening infections. Recently, several publications on COVID-19 outcomes in this patient population appeared, but knowledge on optimal treatment, mortality, outcomes, and appropriate risk predictors is limited. A retrospective analysis was performed in a German high-volume lung transplant center between 19th March 2020 and 18th May 2021. Impact of COVID-19 on physical and psychological health, clinical outcomes, and mortality were analyzed including follow-up visits up to 12 weeks after infection in survivors. Predictive parameters on survival were assessed using univariate and multivariate proportional hazards regression models. Out of 1,046 patients in follow-up, 31 acquired COVID-19 during the pandemic. 12 of 31 (39%) died and 26 (84%) were hospitalized. In survivors a significant decline in exercise capacity (p = 0.034), TLC (p = 0.02), and DLCO (p = 0.007) was observed at follow-up after 3 months. Anxiety, depression, and self-assessed quality of life remained stable. Charlson comorbidity index predicted mortality (HR 1.5, 1.1-2.2; p = 0.023). In recipients with pre-existing CLAD, mortality and clinical outcomes were inferior. However, pre-existing CLAD did not predict mortality. COVID-19 remains a life-threatening disease for lung transplant recipients, particularly in case comorbidities. Further studies on long term outcomes and impact on pre-existing CLAD are needed.


Subject(s)
COVID-19/epidemiology , Lung Transplantation/statistics & numerical data , Transplant Recipients/statistics & numerical data , Adult , Female , Hospitalization , Humans , Male , Middle Aged , Quality of Life , Retrospective Studies , Risk Assessment
9.
Eur J Radiol ; 127: 109019, 2020 Jun.
Article in English | MEDLINE | ID: covidwho-1454121

ABSTRACT

PURPOSE: Assessment of a woman's risk of breast cancer is essential when moving towards personalized screening. Breast density is a well-known risk factor and has the potential to improve accuracy of risk prediction models. In this study we reviewed the impact on model performance of adding breast density to clinical breast cancer risk prediction models. METHODS: We conducted a systematic review using a pre-specified search strategy for PubMed, EMBASE, Web of Science, and Cochrane Library from January 2007 until November 2019. Studies were screened using the Covidence software. Eligible studies developed or modified existing breast cancer risk prediction models applicable to the general population of women by adding breast density to the model. Improvement in discriminatory accuracy was measured as an increase in the Area Under the Curve or concordance statistics. RESULTS: Eleven eligible studies were identified by the search and one by reference check. Four studies modified the Gail model, four modified the Tyrer-Cuzick model, and five studies developed new models. Several methods were used to measure breast density, including visual, semi- and fully automated methods. Eleven studies reported discriminatory accuracy and one study reported calibration. Seven studies found a statistically significantly increased discriminatory accuracy when including density in the model. The increase in AUC ranged 0.03 to 0.14. Four studies did not report on statistical significance, but reported an increased AUC ranging from 0.01 to 0.06. CONCLUSION: Including mammographic breast density has the potential to improve breast cancer risk prediction models. However, all models demonstrated limited discrimination accuracy.


Subject(s)
Breast Density , Breast Neoplasms/diagnostic imaging , Mammography/methods , Aged , Breast/diagnostic imaging , Female , Humans , Middle Aged , Risk Assessment/methods
10.
Ann Vasc Surg ; 66: 104-109, 2020 Jul.
Article in English | MEDLINE | ID: covidwho-1454026

ABSTRACT

BACKGROUND: Type 2 endoleaks (T2Es) are the main cause of reintervention after endovascular repair of abdominal aortic aneurysms (EVAR). The objective of this study is to quantify success rates of T2E treatment. METHODS: This study involves a retrospective analysis of a prospectively maintained database containing data on all consecutive patients treated for a T2E between 2003 and 2017 in a single center. Technical success was defined as absence of endoleak in the final angiographic control after treatment. Clinical success was defined as absence of sac growth over 5 mm in the contrast-enhanced computed tomography performed a year thereafter. Statistics included Kaplan-Meier survival estimates. RESULTS: A total of 528 elective EVARs were performed in the period. Thirty-six of these (6.8%) developed a T2E requiring reintervention, a median of 37.9 months after EVAR. Twenty-five percent of the treatments were performed more than 5 years after intervention. Twenty-eight of the 36 treatments were performed via transarterial embolization. For this technique, technical success was 71.4% and clinical success was 62.5%. A subsequent reintervention was required in 35.7% of patients. In this cohort, the rate of aneurysm rupture was 10.7% (n = 3/28), open surgical conversion was needed in 2 of 28 cases (7.1%), and rate of aneurysm-related death was 14.3% (n = 4/28) over follow-up. CONCLUSIONS: A high percentage of patients are at risk of adverse outcomes after T2E treatment. Strict imaging follow-up is still needed in this population.


Subject(s)
Aortic Aneurysm, Abdominal/surgery , Blood Vessel Prosthesis Implantation/adverse effects , Embolization, Therapeutic , Endoleak/therapy , Endovascular Procedures/adverse effects , Aortic Aneurysm, Abdominal/diagnostic imaging , Aortic Aneurysm, Abdominal/mortality , Blood Vessel Prosthesis Implantation/mortality , Databases, Factual , Embolization, Therapeutic/adverse effects , Embolization, Therapeutic/mortality , Endoleak/diagnostic imaging , Endoleak/etiology , Endoleak/mortality , Endovascular Procedures/mortality , Humans , Retreatment , Retrospective Studies , Risk Assessment , Risk Factors , Time Factors , Treatment Outcome
11.
Front Endocrinol (Lausanne) ; 12: 708494, 2021.
Article in English | MEDLINE | ID: covidwho-1450802

ABSTRACT

Aims: We conducted a systematic review and meta-analysis to assess various antidiabetic agents' association with mortality in patients with type 2 diabetes (T2DM) who have coronavirus disease 2019 (COVID-19). Methods: We performed comprehensive literature retrieval from the date of inception until February 2, 2021, in medical databases (PubMed, Web of Science, Embase, and Cochrane Library), regarding mortality outcomes in patients with T2DM who have COVID-19. Pooled OR and 95% CI data were used to assess relationships between antidiabetic agents and mortality. Results: Eighteen studies with 17,338 patients were included in the meta-analysis. Metformin (pooled OR, 0.69; P=0.001) and sulfonylurea (pooled OR, 0.80; P=0.016) were associated with lower mortality risk in patients with T2DM who had COVID-19. However, patients with T2DM who had COVID-19 and received insulin exhibited greater mortality (pooled OR, 2.20; P=0.002). Mortality did not significantly differ (pooled OR, 0.72; P=0.057) between DPP-4 inhibitor users and non-users. Conclusions: Metformin and sulfonylurea could be associated with reduced mortality risk in patients with T2DM who have COVID-19. Furthermore, insulin use could be associated with greater mortality, while DPP-4 inhibitor use could not be. The effects of antidiabetic agents in patients with T2DM who have COVID-19 require further exploration. Systematic Review Registration: PROSPERO (identifier, CRD42021242898).


Subject(s)
COVID-19/complications , Diabetes Mellitus, Type 2/drug therapy , Hypoglycemic Agents/adverse effects , Diabetes Mellitus, Type 2/complications , Humans , Hypoglycemic Agents/therapeutic use , Risk Assessment
12.
Pharmaceut Med ; 35(5): 287-295, 2021 09.
Article in English | MEDLINE | ID: covidwho-1439797

ABSTRACT

Pharmaceutical development was at the forefront of efforts to prevent infection with the SARS-CoV-2 virus as well as to treat its often-devastating effects. Drug development, and its multifaceted and multi-disciplined activity toward effective vaccines and drugs, became part of everyday news. I review several key areas of vaccine and drug development that were brought into the public mainstream over the evolution of the pandemic. These include the unprecedented speed of vaccine discovery and development, issues uncovered from early clinical studies, and regulatory concepts that were highlighted throughout the development process. Among these was the importance of pharmacovigilance as each new agent was rapidly deployed to a mostly eager public. Critical challenges around production, packaging, and procurement of product for patient use were often centre stage. Finally, the ever-important need to transition not only from scientific concept to vaccine and drug, but from their authorized and approved use to their implementation in health systems to insure the intended effects both in individuals and populations.


Subject(s)
COVID-19 Vaccines/therapeutic use , COVID-19/prevention & control , Drug Approval , Drug Development , Drug Discovery , Global Health , Animals , COVID-19/immunology , COVID-19/virology , COVID-19 Vaccines/adverse effects , COVID-19 Vaccines/supply & distribution , Drug Packaging , Health Knowledge, Attitudes, Practice , Humans , Patient Safety , Public Opinion , Risk Assessment , Risk Factors
13.
Sci Rep ; 11(1): 18959, 2021 09 23.
Article in English | MEDLINE | ID: covidwho-1437695

ABSTRACT

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


Subject(s)
COVID-19/epidemiology , Forecasting/methods , Intensive Care Units/trends , Area Under Curve , Computational Biology/methods , Critical Care/statistics & numerical data , Critical Care/trends , Denmark/epidemiology , Hospitalization/trends , Hospitals/trends , Humans , Machine Learning , Pandemics , ROC Curve , Respiration, Artificial/statistics & numerical data , Respiration, Artificial/trends , Retrospective Studies , Risk Assessment/methods , Risk Factors , SARS-CoV-2/pathogenicity , Ventilators, Mechanical/trends
14.
Rev Cardiovasc Med ; 22(3): 1063-1072, 2021 09 24.
Article in English | MEDLINE | ID: covidwho-1439023

ABSTRACT

We evaluated the age-specific mortality of unselected adult outpatients infected with SARS-CoV-2 treated early in a dedicated COVID-19 day hospital and we assessed whether the use of hydroxychloroquine (HCQ) + azithromycin (AZ) was associated with improved survival in this cohort. A retrospective monocentric cohort study was conducted in the day hospital of our center from March to December 2020 in adults with PCR-proven infection who were treated as outpatients with a standardized protocol. The primary endpoint was 6-week mortality, and secondary endpoints were transfer to the intensive care unit and hospitalization rate. Among 10,429 patients (median age, 45 [IQR 32-57] years; 5597 [53.7%] women), 16 died (0.15%). The infection fatality rate was 0.06% among the 8315 patients treated with HCQ+AZ. No deaths occurred among the 8414 patients younger than 60 years. Older age and male sex were associated with a higher risk of death, ICU transfer, and hospitalization. Treatment with HCQ+AZ (0.17 [0.06-0.48]) was associated with a lower risk of death, independently of age, sex and epidemic period. Meta-analysis evidenced consistency with 4 previous outpatient studies (32,124 patients-Odds ratio 0.31 [0.20-0.47], I2 = 0%). Early ambulatory treatment of COVID-19 with HCQ+AZ as a standard of care is associated with very low mortality, and HCQ+AZ improve COVID-19 survival compared to other regimens.


Subject(s)
Ambulatory Care , Antiviral Agents/therapeutic use , Azithromycin/therapeutic use , COVID-19/drug therapy , Early Medical Intervention , Hydroxychloroquine/therapeutic use , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , Antiviral Agents/adverse effects , Azithromycin/adverse effects , COVID-19/diagnosis , COVID-19/mortality , Drug Therapy, Combination , Female , France , Hospitalization , Humans , Hydroxychloroquine/adverse effects , Male , Middle Aged , Outpatients , Retrospective Studies , Risk Assessment , Risk Factors , Sex Factors , Time Factors , Treatment Outcome , Young Adult
16.
EBioMedicine ; 70: 103540, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1433159

ABSTRACT

BACKGROUND: The rise of new SARS-CoV-2 variants worldwide requires global molecular surveillance strategies to support public health control. Early detection and evaluation of their associated risk of spreading within the population are pivotal. METHODS: Between April 2020 and February 2021, the UK Lighthouse Labs Network at Alderley Park tested more than eight million nose and throat swab samples for the presence of SARS-CoV-2, via PCR. The assay targeted three genomic regions of the virus: N, Orf1ab and S. Whole-genome next-generation sequencing was used to confirm positive PCR results. Positive results were mapped using the postal district origin of samples to allow real-time tracking of the spread of a new variant through the UK. FINDINGS: In mid-November 2020, the assay identified an increasing number of S gene negative, N and Orf1ab positive samples. Whole-genome sequencing demonstrated that the loss of S gene detection was due to the appearance of a SARS-CoV-2 lineage (B.1.1.7) designated as Variant of concern (VOC) 202012/01. By the beginning of January 2021, the new SARS-CoV-2 VOC comprised 70% of daily positive samples tested at Alderley Park and ∼98% by the end of February 2021. INTERPRETATION: The timeline view identified the rapid spread of the new SARS-CoV-2 variant across England during the first three weeks of December. Coupling high-throughput diagnostics and molecular surveillance was pivotal to the early detection of the spread of this variant. The availability of real-time tracking of an emerging variant is an important new tool to inform decision-making authorities for risk mitigation. In a respiratory pandemic, a tool for the timely response to the emergence and spread of a novel variant is vital, even more so when a variant is associated with the enhanced transmission, as has occurred with VOC 202012/01. FUNDING: None.


Subject(s)
COVID-19/virology , SARS-CoV-2/genetics , England , High-Throughput Nucleotide Sequencing/methods , Humans , Mutation/genetics , Pandemics/prevention & control , Risk Assessment
17.
JAMA Netw Open ; 4(9): e2126447, 2021 09 01.
Article in English | MEDLINE | ID: covidwho-1432337

ABSTRACT

Importance: Scalable programs for school-based SARS-CoV-2 testing and surveillance are needed to guide in-person learning practices and inform risk assessments in kindergarten through 12th grade settings. Objectives: To characterize SARS-CoV-2 infections in staff and students in an urban public school setting and evaluate test-based strategies to support ongoing risk assessment and mitigation for kindergarten through 12th grade in-person learning. Design, Setting, and Participants: This pilot quality improvement program engaged 3 schools in Omaha, Nebraska, for weekly saliva polymerase chain reaction testing of staff and students participating in in-person learning over a 5-week period from November 9 to December 11, 2020. Wastewater, air, and surface samples were collected weekly and tested for SARS-CoV-2 RNA to evaluate surrogacy for case detection and interrogate transmission risk of in-building activities. Main Outcomes and Measures: SARS-CoV-2 detection in saliva and environmental samples and risk factors for SARS-CoV-2 infection. Results: A total of 2885 supervised, self-collected saliva samples were tested from 458 asymptomatic staff members (mean [SD] age, 42.9 [12.4] years; 303 women [66.2%]; 25 Black or African American [5.5%], 83 Hispanic [18.1%], 312 White [68.1%], and 35 other or not provided [7.6%]) and 315 students (mean age, 14.2 [0.7] years; 151 female students [48%]; 20 Black or African American [6.3%], 201 Hispanic [63.8%], 75 White [23.8%], and 19 other race or not provided [6.0%]). A total of 46 cases of SARS-CoV-2 (22 students and 24 staff members) were detected, representing an increase in cumulative case detection rates from 1.2% (12 of 1000) to 7.0% (70 of 1000) among students and from 2.1% (21 of 1000) to 5.3% (53 of 1000) among staff compared with conventional reporting mechanisms during the pilot period. SARS-CoV-2 RNA was detected in wastewater samples from all pilot schools as well as in air samples collected from 2 choir rooms. Sequencing of 21 viral genomes in saliva specimens demonstrated minimal clustering associated with 1 school. Geographical analysis of SARS-CoV-2 cases reported district-wide demonstrated higher community risk in zip codes proximal to the pilot schools. Conclusions and Relevance: In this study of staff and students in 3 urban public schools in Omaha, Nebraska, weekly screening of asymptomatic staff and students by saliva polymerase chain reaction testing was associated with increased SARS-CoV-2 case detection, exceeding infection rates reported at the county level. Experiences differed among schools, and virus sequencing and geographical analyses suggested a dynamic interplay of school-based and community-derived transmission risk. Collectively, these findings provide insight into the performance and community value of test-based SARS-CoV-2 screening and surveillance strategies in the kindergarten through 12th grade educational setting.


Subject(s)
COVID-19 Testing/methods , COVID-19/epidemiology , Environmental Monitoring , Mass Screening , Program Evaluation , Schools , Urban Population , Adolescent , Adult , Air Microbiology , COVID-19/virology , Female , Humans , Male , Middle Aged , Nebraska , Pandemics , Pilot Projects , Polymerase Chain Reaction , Risk Assessment , SARS-CoV-2 , Saliva , School Teachers , Students , Waste Water/virology
18.
Rev Sci Tech ; 40(2): 533-544, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1431210

ABSTRACT

Animal health risk assessment is one of the key tasks of Veterinary Services. There are well-established protocols created by the World Organisation for Animal Health and Codex Alimentarius Commission for assessing risk. They cover terrestrial and aquatic animals and zoonotic infectious diseases, food safety, and the environment, taking into consideration the connections between them. Significant effort has been made in developing methods to estimate the probability, and consequences, of infectious disease incursion in diseasefree countries through legal or illegal trade or via the movements of insects and wildlife. Additional efforts have been made in the design of prevention strategies and contingency plans. Concerns about possible pandemics of avian influenza continue to be important motivation for monitoring viruses for selection of vaccine candidate strains. The recent COVID-19 pandemic was zoonotic in nature and caused extensive disruption throughout the world. Tools are becoming available for quantitative food safety risk assessments for bacteria, toxins, viruses, and antimicrobial resistance genes, including tools that allow simulations for the selection of effective control options. Applying participatory techniques facilitates the conduct of risk analysis in low- and middle-income countries. In internationally established frameworks, risk assessment is the first step towards elimination of important infectious diseases in endemic countries and it is an important contributor to the reduction of disease risks. Quantitative and qualitative socio-economic and behavioural studies have been developed to design risk management options that are acceptable and sustainable for actors throughout value chains.


Subject(s)
COVID-19 , Pandemics , Animals , Animals, Wild , COVID-19/veterinary , Food Safety , Risk Assessment , SARS-CoV-2
19.
Clin Appl Thromb Hemost ; 27: 10760296211040110, 2021.
Article in English | MEDLINE | ID: covidwho-1430348

ABSTRACT

Since the outbreak of Covid-19 in December, 2019, scientists worldwide have been committed to developing COVID-19 vaccines. Only when most people have immunity to SARS-CoV-2, COVID-19 can reduce even wholly overcome. So far, nine kinds of COVID-19 vaccines have passed the phase III clinical trials and have approved for use. At the same time, adverse reactions after COVID-19 vaccination have also reported. This paper focuses on the adverse effects of thrombosis and thrombocytopenia caused by the COVID-19 vaccine, especially the adenovirus-vector vaccine from AstraZeneca and Pfizer, and discusses its mechanism and possible countermeasures.


Subject(s)
Adenoviridae/genetics , COVID-19 Vaccines/adverse effects , Genetic Vectors , Thrombocytopenia/chemically induced , Thrombosis/chemically induced , Vaccination/adverse effects , Antibodies/blood , COVID-19 Vaccines/genetics , COVID-19 Vaccines/immunology , Humans , Platelet Factor 4/immunology , Risk Assessment , Risk Factors , Thrombocytopenia/blood , Thrombocytopenia/immunology , Thrombosis/blood , Thrombosis/immunology
20.
BMJ ; 374: n2244, 2021 09 17.
Article in English | MEDLINE | ID: covidwho-1430185

ABSTRACT

OBJECTIVES: To derive and validate risk prediction algorithms to estimate the risk of covid-19 related mortality and hospital admission in UK adults after one or two doses of covid-19 vaccination. DESIGN: Prospective, population based cohort study using the QResearch database linked to data on covid-19 vaccination, SARS-CoV-2 results, hospital admissions, systemic anticancer treatment, radiotherapy, and the national death and cancer registries. SETTINGS: Adults aged 19-100 years with one or two doses of covid-19 vaccination between 8 December 2020 and 15 June 2021. MAIN OUTCOME MEASURES: Primary outcome was covid-19 related death. Secondary outcome was covid-19 related hospital admission. Outcomes were assessed from 14 days after each vaccination dose. Models were fitted in the derivation cohort to derive risk equations using a range of predictor variables. Performance was evaluated in a separate validation cohort of general practices. RESULTS: Of 6 952 440 vaccinated patients in the derivation cohort, 5 150 310 (74.1%) had two vaccine doses. Of 2031 covid-19 deaths and 1929 covid-19 hospital admissions, 81 deaths (4.0%) and 71 admissions (3.7%) occurred 14 days or more after the second vaccine dose. The risk algorithms included age, sex, ethnic origin, deprivation, body mass index, a range of comorbidities, and SARS-CoV-2 infection rate. Incidence of covid-19 mortality increased with age and deprivation, male sex, and Indian and Pakistani ethnic origin. Cause specific hazard ratios were highest for patients with Down's syndrome (12.7-fold increase), kidney transplantation (8.1-fold), sickle cell disease (7.7-fold), care home residency (4.1-fold), chemotherapy (4.3-fold), HIV/AIDS (3.3-fold), liver cirrhosis (3.0-fold), neurological conditions (2.6-fold), recent bone marrow transplantation or a solid organ transplantation ever (2.5-fold), dementia (2.2-fold), and Parkinson's disease (2.2-fold). Other conditions with increased risk (ranging from 1.2-fold to 2.0-fold increases) included chronic kidney disease, blood cancer, epilepsy, chronic obstructive pulmonary disease, coronary heart disease, stroke, atrial fibrillation, heart failure, thromboembolism, peripheral vascular disease, and type 2 diabetes. A similar pattern of associations was seen for covid-19 related hospital admissions. No evidence indicated that associations differed after the second dose, although absolute risks were reduced. The risk algorithm explained 74.1% (95% confidence interval 71.1% to 77.0%) of the variation in time to covid-19 death in the validation cohort. Discrimination was high, with a D statistic of 3.46 (95% confidence interval 3.19 to 3.73) and C statistic of 92.5. Performance was similar after each vaccine dose. In the top 5% of patients with the highest predicted covid-19 mortality risk, sensitivity for identifying covid-19 deaths within 70 days was 78.7%. CONCLUSION: This population based risk algorithm performed well showing high levels of discrimination for identifying those patients at highest risk of covid-19 related death and hospital admission after vaccination.


Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19/mortality , Hospitalization/statistics & numerical data , Vaccination/statistics & numerical data , Adult , Aged , Aged, 80 and over , COVID-19/immunology , COVID-19 Vaccines/immunology , Comorbidity , Databases, Factual , Female , Humans , Male , Middle Aged , Prospective Studies , Risk Assessment , SARS-CoV-2 , United Kingdom/epidemiology
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