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1.
Oral Surg ; 14(1): 93-94, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-1961767
2.
Nonlinear Dyn ; 101(3): 1777-1787, 2020.
Article in English | MEDLINE | ID: covidwho-1906357

ABSTRACT

Nowadays, the novel coronavirus (COVID-19) is spreading around the world and has attracted extremely wide public attention. From the beginning of the outbreak to now, there have been many mathematical models proposed to describe the spread of the pandemic, and most of them are established with the assumption that people contact with each other in a homogeneous pattern. However, owing to the difference of individuals in reality, social contact is usually heterogeneous, and the models on homogeneous networks cannot accurately describe the outbreak. Thus, we propose a susceptible-asymptomatic-infected-removed (SAIR) model on social networks to describe the spread of COVID-19 and analyse the outbreak based on the epidemic data of Wuhan from January 24 to March 2. Then, according to the results of the simulations, we discover that the measures that can curb the spread of COVID-19 include increasing the recovery rate and the removed rate, cutting off connections between symptomatically infected individuals and their neighbours, and cutting off connections between hub nodes and their neighbours. The feasible measures proposed in the paper are in fair agreement with the measures that the government took to suppress the outbreak. Furthermore, effective measures should be carried out immediately, otherwise the pandemic would spread more rapidly and last longer. In addition, we use the epidemic data of Wuhan from January 24 to March 2 to analyse the outbreak in the city and explain why the number of the infected rose in the early stage of the outbreak though a total lockdown was implemented. Moreover, besides the above measures, a feasible way to curb the spread of COVID-19 is to reduce the density of social networks, such as restricting mobility and decreasing in-person social contacts. This work provides a series of effective measures, which can facilitate the selection of appropriate approaches for controlling the spread of the COVID-19 pandemic to mitigate its adverse impact on people's livelihood, societies and economies.

3.
Nonlinear Dyn ; 100(3): 2953-2972, 2020.
Article in English | MEDLINE | ID: covidwho-1906356

ABSTRACT

Complex systems have characteristics that give rise to the emergence of rare and extreme events. This paper addresses an example of such type of crisis, namely the spread of the new Coronavirus disease 2019 (COVID-19). The study deals with the statistical comparison and visualization of country-based real-data for the period December 31, 2019, up to April 12, 2020, and does not intend to address the medical treatment of the disease. Two distinct approaches are considered, the description of the number of infected people across time by means of heuristic models fitting the real-world data, and the comparison of countries based on hierarchical clustering and multidimensional scaling. The computational and mathematical modeling lead to the emergence of patterns, highlighting similarities and differences between the countries, pointing toward the main characteristics of the complex dynamics.

4.
Disaster Med Public Health Prep ; 16(1): 177-186, 2022 02.
Article in English | MEDLINE | ID: covidwho-1900342

ABSTRACT

OBJECTIVE: This study aims to clarify the association between prosperity and the coronavirus disease (COVID-19) outcomes and its impact on the future management of pandemics. METHODS: This is an observational study using information from 2 online registries. The numbers of infected individuals and deaths and the prosperity rank of each country were obtained from worldometer.info and the Legatum Institute's Prosperity Index, respectively. RESULTS: There is a combination of countries with high and low prosperity on the list of COVID-19-infected countries. The risk of the virus pandemic seems to be more extensive in countries with high prosperity. A Spearman's rho test confirmed a significant correlation between prosperity, the number of COVID-19 cases, and the number of deaths at the 99% level. CONCLUSION: New emerging pandemics affect all nations. In order to increase the likelihood of successfully managing future events, it is important to consider preexisting health security, valid population-based management approaches, medical decision-making, communication, continuous assessment, triage, treatment, early and complete physical distancing strategies, and logistics. These elements cannot be taught on-site and on occasion. There is a need for innovative and regular educational activities for all stakeholders committed to safeguarding our future defense systems concerning diagnostic, protection, treatment, and rehabilitation in pandemics, as well as other emergencies.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Humans , Pandemics/prevention & control , Physical Distancing , Triage
5.
Sangyo Eiseigaku Zasshi ; 64(2): 107-113, 2022 Mar 25.
Article in Japanese | MEDLINE | ID: covidwho-1760008

ABSTRACT

OBJECTIVES: Immediately before the state of emergency was declared, there was an outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among special training participants with severe physical stress. For promoting the optimization of infection prevention measures by identifying acts and situations with high risk of infection, we conducted a survey and analysis to understand the detailed process of infection spread in these cases. METHODS: A structured interview was conducted for the special training participants on their health status, changes in symptoms, training methods, and behavior history in their private lives. Additionally, a patrol of the training facility was carried out to understand the training environment, and antibody tests were conducted on the close contacts for more accurately grasping the spread of infection, by identifying subclinical infected persons. RESULTS: Within 10 days of COVID-19 onset in the first patient, 15 of the 19 original training participants developed symptoms, and 14 patients tested positive for RT-PCR. PCR tests were also performed on four patients who did not develop the disease - two were positive and negative, each. The two negatives turned positive on a later antibody test, suggesting that there was an asymptomatic infection. In addition, all five patients who participated in the training for only a day developed symptoms and tested positive for PCR in a few days. Of the 64 people who underwent testing for antibodies as close contacts, all but one who was living together with a patient were negative on antibody testing. CONCLUSIONS: The onset of COVID-19 occurred after the start of practice-based training continuously; therefore, the practice-based training was thought to be the main cause of the transmission. We speculate that the main factors behind the rapid spread of infection are as follows: during practice-based training, increased ventilation made it difficult to wear a mask; repeated loud vocalizations at close range; and the training pair was not fixed. Physical training without shouting and desk work, however, did not possess the risk of COVID-19, and avoiding certain situations at high risk of respiratory infections may have significantly reduced SARS-CoV-2 transmission. If personnel become infected with SARS-CoV-2, emergency measures should be devised by identifying patients and close contacts and facilitating the investigation of their behavioral history. Furthermore, evaluating and improving the effectiveness of infection control measures is necessary by ascertaining potentially infected persons by performing PCR tests, antigen tests, antibody tests, etc. in combination.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Disease Outbreaks/prevention & control , Humans , Inservice Training , Surveys and Questionnaires
6.
Pak J Med Sci ; 36(COVID19-S4): S79-S84, 2020 May.
Article in English | MEDLINE | ID: covidwho-1726822

ABSTRACT

Coronavirus Disease 2019 (CoViD-19) is the third type of coronavirus disease after severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) that appears in human population from the past two decades. It is highly contagious and rapidly spread in the human population and compelled global public health institutions on high alert. Due to genetic similarity of this novel coronavirus 2019 with bat virus its emergence from bat to humans is possible. The virus survive in the droplets of coughing and sneezing and spread around the large areas through infected person resulting in its rapid spread among people. Clinical symptoms of CoViD-19 include fever, dry cough, dyspnea, loose stool, nausea and vomiting. The present review discuss the origin of CoViD-19, its rapid spread, mortality rate and recoveries ratio around the world. Since its origin from Wuhan, the CoViD-19 spread very rapidly all across the countries, on April 17, 2020 this disease has affected 210 countries of the globe. The data obtained showed over 2.4 million confirmed cases of CoViD-19. Higher mortality rate was found in Algeria and Belgium as 15% and 13.95%, respectively. Lower mortality rate was found in Qatar 0.17% and Singapore 0.2%. Recovery versus deceased ratio showed that recovery was 68, 59 and 35 times higher than the death in Singapore, Qatar and Thailand respectively. It is concluded that 2019-novel corona virus is a zoonotic pathogen similar to MERS and SARS. Therefore, a barrier should be maintained between and across the human, household and wild animals to avoid such pandemics.

7.
Pak J Med Sci ; 36(COVID19-S4): S111-S114, 2020 May.
Article in English | MEDLINE | ID: covidwho-1726817

ABSTRACT

Pakistan is in the grip of COVID-19, due to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) since 26 February 2020, and the number of infected people and mortality is rising gradually. The health workers, doctors, pathologists and laboratory staff are front line fighters who are facing the risk. Few things are important for public and health workers, human behavior is at the core of preparedness and response i.e, personal protective measures, (handwashing, face masks, respiratory etiquette, surface and objects cleansing), social distancing and travel measures because the virus spreads through the respiratory channels, eyes, nose and mouth. While working in the Pathology labs, use the personal protection equipment (PPE), during the work in the duty. Avoiding the over duties and long shifts. It is good to keep the immune system healthy by taking a healthy balanced diet, vitamin supplements, and a night of proper sleep. It is also important to avoid taking food during duties and avoid making close contact without wearing safety dress.

8.
Viruses ; 12(6)2020 05 27.
Article in English | MEDLINE | ID: covidwho-1726016

ABSTRACT

The global outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causing coronavirus disease 2019 (COVID-19) has reached over five million confirmed cases worldwide, and numbers are still growing at a fast rate. Despite the wide outbreak of the infection, a remarkable asymmetry is observed in the number of cases and in the distribution of the severity of the COVID-19 symptoms in patients with respect to the countries/regions. In the early stages of a new pathogen outbreak, it is critical to understand the dynamics of the infection transmission, in order to follow contagion over time and project the epidemiological situation in the near future. While it is possible to reason that observed variation in the number and severity of cases stems from the initial number of infected individuals, the difference in the testing policies and social aspects of community transmissions, the factors that could explain high discrepancy in areas with a similar level of healthcare still remain unknown. Here, we introduce a binary classifier based on an artificial neural network that can help in explaining those differences and that can be used to support the design of containment policies. We found that SARS-CoV-2 infection frequency positively correlates with particulate air pollutants, and specifically with particulate matter 2.5 (PM2.5), while ozone gas is oppositely related with the number of infected individuals. We propose that atmospheric air pollutants could thus serve as surrogate markers to complement the infection outbreak anticipation.


Subject(s)
Atmosphere/analysis , Coronavirus Infections/epidemiology , Disease Outbreaks , Ozone , Particulate Matter/analysis , Pneumonia, Viral/epidemiology , Betacoronavirus/isolation & purification , COVID-19 , Humans , Italy/epidemiology , Models, Theoretical , Ozone/analysis , Pandemics , Particulate Matter/adverse effects , SARS-CoV-2
9.
Curr Opin Clin Nutr Metab Care ; 23(4): 288-293, 2020 07.
Article in English | MEDLINE | ID: covidwho-1722683

ABSTRACT

PURPOSE OF REVIEW: The Covid-19 pandemic has daunted the world with its enormous impact on healthcare, economic recession, and psychological distress. Nutrition is an integral part of every person life care, and should also be mandatorily integrated to patient care under the Covid-19 pandemic. It is crucial to understand how the Covid-19 does develop and which risk factors are associated with negative outcomes and death. Therefore, it is of utmost importance to have studies that respect the basic tenets of the scientific method in order to be trusted. The goal of this review is to discuss the deluge of scientific data and how it might influence clinical reasoning and practice. RECENT FINDINGS: A large number of scientific manuscripts are daily published worldwide, and the Covid-19 makes no exception. Up to now, data on Covid-19 have come from countries initially affected by the disease and mostly pertain either epidemiological observations or opinion papers. Many of them do not fulfil the essential principles characterizing the adequate scientific method. SUMMARY: It is crucial to be able to critical appraise the scientific literature, in order to provide adequate nutrition therapy to patients, and in particular, to Covid-19 infected individuals.


Subject(s)
Coronavirus Infections , Nutrition Disorders , Nutrition Therapy/standards , Nutritional Physiological Phenomena , Pandemics , Pneumonia, Viral , COVID-19 , Coronavirus Infections/complications , Coronavirus Infections/epidemiology , Coronavirus Infections/physiopathology , Coronavirus Infections/therapy , Humans , Nutrition Disorders/epidemiology , Nutrition Disorders/etiology , Nutrition Disorders/therapy , Nutrition Therapy/methods , Pneumonia, Viral/complications , Pneumonia, Viral/epidemiology , Pneumonia, Viral/physiopathology , Pneumonia, Viral/therapy , Risk Factors
10.
Brain Behav Immun ; 87: 11-17, 2020 07.
Article in English | MEDLINE | ID: covidwho-1719332

ABSTRACT

The severe 2019 outbreak of novel coronavirus disease (COVID-19), which was first reported in Wuhan, would be expected to impact the mental health of local medical and nursing staff and thus lead them to seek help. However, those outcomes have yet to be established using epidemiological data. To explore the mental health status of medical and nursing staff and the efficacy, or lack thereof, of critically connecting psychological needs to receiving psychological care, we conducted a quantitative study. This is the first paper on the mental health of medical and nursing staff in Wuhan. Notably, among 994 medical and nursing staff working in Wuhan, 36.9% had subthreshold mental health disturbances (mean PHQ-9: 2.4), 34.4% had mild disturbances (mean PHQ-9: 5.4), 22.4% had moderate disturbances (mean PHQ-9: 9.0), and 6.2% had severe disturbance (mean PHQ-9: 15.1) in the immediate wake of the viral epidemic. The noted burden fell particularly heavily on young women. Of all participants, 36.3% had accessed psychological materials (such as books on mental health), 50.4% had accessed psychological resources available through media (such as online push messages on mental health self-help coping methods), and 17.5% had participated in counseling or psychotherapy. Trends in levels of psychological distress and factors such as exposure to infected people and psychological assistance were identified. Although staff accessed limited mental healthcare services, distressed staff nonetheless saw these services as important resources to alleviate acute mental health disturbances and improve their physical health perceptions. These findings emphasize the importance of being prepared to support frontline workers through mental health interventions at times of widespread crisis.


Subject(s)
Anxiety Disorders/psychology , Coronavirus Infections/therapy , Depressive Disorder/psychology , Nurses/psychology , Physicians/psychology , Pneumonia, Viral/therapy , Sleep Initiation and Maintenance Disorders/psychology , Adaptation, Psychological , Adolescent , Adult , Anxiety/epidemiology , Anxiety/psychology , Anxiety Disorders/epidemiology , Betacoronavirus , COVID-19 , China/epidemiology , Coronavirus Infections/epidemiology , Cross-Sectional Studies , Depression/epidemiology , Depression/psychology , Depressive Disorder/epidemiology , Disease Outbreaks , Female , Health Services Accessibility , Humans , Male , Mental Health , Mental Health Services , Middle Aged , Nurses/statistics & numerical data , Pandemics , Patient Health Questionnaire , Physicians/statistics & numerical data , Pneumonia, Viral/epidemiology , Psychological Distress , SARS-CoV-2 , Sleep Initiation and Maintenance Disorders/epidemiology , Surveys and Questionnaires , Young Adult
11.
Curr Med Chem ; 28(41): 8559-8594, 2021.
Article in English | MEDLINE | ID: covidwho-1690554

ABSTRACT

There is a new public health crisis threatening the world with the emergence and spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease was later named novel coronavirus disease or COVID-19. It was then declared a pandemic by the World Health Organization on March 11, 2020. The virus originated in bats and was transmitted to humans through unknown intermediary animals in Wuhan, Hubei province, China, in December 2019. As of February 5, 2021, 103 million laboratory-confirmed cases and nearly 2.3 million deaths were reported globally. The number of death tolls continues to rise, and a large number of countries have been forced to maintain social distance in public place and enforce lockdown. As per literature, coronavirus is transmitted human to human or human to animal via airborne droplets. Coronavirus enters the human cell through the membrane ACE-2 exopeptidase receptor. WHO, ECDC, and ICMR advised avoiding public places and close contact with infected persons and pet animals. To date, there is no evidence of any effective treatment for COVID-19. The main therapies being used to treat the disease are antiviral drugs, chloroquine/hydroxychloroquine, and respiratory therapy. Although several therapies have been proposed, quarantine is the only intervention that appears to be effective in decreasing the contagion rate. We conducted a literature review of publicly available information to summarize knowledge about the pathogen and the current epidemic. In the present literature review, the causative agent of the pandemic, epidemiology, pathogenesis, and diagnostic techniques are discussed. Further, currently used treatment, preventive strategies along with vaccine trials and computational tools are all described in detail.


Subject(s)
COVID-19 , SARS-CoV-2 , Animals , Communicable Disease Control , Humans , Hydroxychloroquine , Pandemics
12.
Environ Dev Sustain ; 23(5): 6681-6697, 2021.
Article in English | MEDLINE | ID: covidwho-1681222

ABSTRACT

COVID-19 is a highly infectious disease caused by SARS-CoV-2, first identified in China and spread globally, resulting into pandemic. Transmission of virus takes place either directly through close contact with infected individual (symptomatic/asymptomatic) or indirectly by touching contaminated surfaces. Virus survives on the surfaces from few hours to days. It enters the human body through nose, eyes or mouth. Other sources of contamination are faeces, blood, food, water, semen etc. Parameters such as temperature/relative humidity also play an important role in transmission. As the disease is evolving, so are the number of cases. Proper planning and restriction are helping in influencing the trajectory of the transmission. Various measures are undertaken to prevent infection such as maintaining hygiene, using facemasks, isolation/quarantine, social/physical distancing, in extreme cases lockdown (restricted movement except essential services) in hot spot areas or throughout the country. Countries that introduced various mitigation measures had experienced control in transmission of COVID-19. Python programming is conducted for change point analysis (CPA) using Bayesian probability approach for understanding the impact of restrictions and mitigation methods in terms of either increase or stagnation in number of COVID-19 cases for eight countries. From analysis it is concluded that countries which acted late in bringing in the social distancing measures are suffering in terms of high number of cases with USA, leading among eight countries analysed. The CPA week in comparison with date of lockdown and first reported case strongly correlates (Pearson's r = - 0.86 to - 0.97) to cases, cases per unit area and cases per unit population, indicating earlier the mitigation strategy, lesser the number of cases. The overall paper will help the decision makers in understanding the possible steps for mitigation, more so in developing countries where the fight against COVID-19 seems to have just begun.

13.
IEEE Rev Biomed Eng ; 15: 325-340, 2022.
Article in English | MEDLINE | ID: covidwho-1642570

ABSTRACT

COVID-19 is a life threatening disease which has a enormous global impact. As the cause of the disease is a novel coronavirus whose gene information is unknown, drugs and vaccines are yet to be found. For the present situation, disease spread analysis and prediction with the help of mathematical and data driven model will be of great help to initiate prevention and control action, namely lockdown and qurantine. There are various mathematical and machine-learning models proposed for analyzing the spread and prediction. Each model has its own limitations and advantages for a particluar scenario. This article reviews the state-of-the art mathematical models for COVID-19, including compartment models, statistical models and machine learning models to provide more insight, so that an appropriate model can be well adopted for the disease spread analysis. Furthermore, accurate diagnose of COVID-19 is another essential process to identify the infected person and control further spreading. As the spreading is fast, there is a need for quick auotomated diagnosis mechanism to handle large population. Deep-learning and machine-learning based diagnostic mechanism will be more appropriate for this purpose. In this aspect, a comprehensive review on the deep learning models for the diagnosis of the disease is also provided in this article.


Subject(s)
COVID-19 , Deep Learning , Communicable Disease Control , Humans , Machine Learning , SARS-CoV-2
14.
J Infect Dis ; 2021 Apr 29.
Article in English | MEDLINE | ID: covidwho-1638156

ABSTRACT

BACKGROUND: In contrast to studies that relied on volunteers or convenience sampling, there are few population-based SARS-CoV-2 seroprevalence investigations and most were conducted early in the pandemic. The health department of the fourth largest city in the U.S. recognized that sound estimates of viral impact were needed to inform decision-making. METHODS: Adapting standardized disaster research methodology in September 2020, the city was divided into high and low strata based on RT-PCR positivity rates, and census block groups within each stratum were randomly selected with probability proportional to size, followed by random selection of households within each group. Using two immunoassays, the proportion of infected individuals was estimated for the city, as well as by positivity rate and by sociodemographic and other characteristics. The degree of under ascertainment of seroprevalence was estimated based on RT-PCR positive cases. RESULTS: Seroprevalence was estimated to be 14% with a near two-fold difference in areas with high (18%) versus low (10%) RT-PCR positivity rates and was four times higher compared to case-based surveillance data. CONCLUSIONS: Seroprevalence was higher than previously reported and is greater than that estimated from RT-PCR data. Results will be used to inform public health decisions about testing, outreach, and vaccine rollout.

15.
Curr Med Imaging ; 18(2): 104-112, 2022.
Article in English | MEDLINE | ID: covidwho-1624417

ABSTRACT

OBJECTIVE: Coronavirus-related disease, a deadly illness, has raised public health issues worldwide. The majority of individuals infected are multiplying. The government is taking aggressive steps to quarantine people, people exposed to infection, and clinical trials for treatment. Subsequently recommends critical care for the aged, children, and health-care personnel. While machine learning methods have been previously used to augment clinical decisions, there is now a demand for "Emergency ML." With rapidly growing datasets, there also remain important considerations when developing and validating ML models. METHODS: This paper reviews the recent study that applies machine-learning technology addressing Corona virus-related disease issues' challenges in different perspectives. The report also discusses various treatment trials and procedures on Corona virus-related disease infected patients providing insights to physicians and the public on the current treatment challenges. RESULTS: The paper provides the individual with insights into certain precautions to prevent and control the spread of this deadly disease. CONCLUSION: This review highlights the utility of evidence-based machine learning prediction tools in several clinical settings, and how similar models can be deployed during the Corona virus-related disease pandemic to guide hospital frontlines and health-care administrators to make informed decisions about patient care and managing hospital volume. Further, the clinical trials conducted so far for infected patients with Corona virus-related disease addresses their results to improve community alertness from the viewpoint of a well-known saying, "prevention is always better."


Subject(s)
COVID-19 , Decision Support Systems, Clinical , Aged , Child , Humans , Machine Learning , Pandemics , SARS-CoV-2
16.
Front Pharmacol ; 12: 646570, 2021.
Article in English | MEDLINE | ID: covidwho-1607116

ABSTRACT

Background: Epidemiological studies show that BCG-vaccinated population seems to be more likely protected from COVID-19 infection, but WHO gave a stark warning on use of BCG vaccine without confirmed COVID-19 trials. The aim of the study is to evaluate whether TB vaccination, performed several years earlier, could confer protection against COVID-19. Methods: After the Ethical Committee authorization, professional orders were used to contact physicians with an online survey. Specialty, COVID-19 infection and previous BCG vaccination were recorded. Statistical data analysis was performed. Results: 1906 physicians answered the questionnaire, (M = 1068; F = 838; mean age 50.7 ± 13.3 years; range 24-87), more than half (1062; 55.7%) experienced BCG vaccination. Professional activity was recorded, and only 49 subjects (2.6%) of them were infected by SARS-CoV2. Among the group of infected people, asymptomatic form occurred in 12 subjects (24.5%); a pauci-symptomatic form in 24 subjects (49.0%); and a severe form (pneumonia and/or respiratory distress) in 13 (26.5%). Considering only the clinically relevant form of COVID-19, period prevalence was 2.2% (23/1062) in the vaccinated group and 1.7% (14/844) in the unvaccinated group (OR: 1.31, 95% C.I.: 0.68-2.63, p = 0.427). Conclusion: Our experience does not confirm the possible protective role of BCG vaccination, performed years earlier, against COVID-19. Although recent epidemiological studies point out in BCG-vaccinated population a lower prevalence of SARS-CoV2 infection, in our cohort of physicians no significant difference was found in terms of prevalence of COVID-19 infection. Our data underline the necessity to follow the WHO warning about the indiscriminate use of BCG vaccine, until clear evidence of protection by BCG vaccination against COVID-19 is fully demonstrated.

17.
Am J Epidemiol ; 190(8): 1452-1456, 2021 08 01.
Article in English | MEDLINE | ID: covidwho-1585169

ABSTRACT

The coronavirus disease 2019 pandemic, which was caused by the severe acute respiratory syndrome coronavirus 2, has led to an unprecedented effort to generate real-world evidence on the safety and effectiveness of various treatments. A growing number of observational studies in which the effects of certain drugs were evaluated have been conducted, including several in which researchers assessed whether hydroxychloroquine improved outcomes in infected individuals and whether renin-angiotensin-aldosterone system inhibitors have detrimental effects. In the present article, we review and illustrate how immortal time bias and selection bias were present in several of these studies. Understanding these biases and how they can be avoided may prove important for future observational studies assessing the effectiveness and safety of potentially promising drugs during the coronavirus 19 pandemic.


Subject(s)
COVID-19/drug therapy , Cohort Studies , Drug Evaluation/methods , Randomized Controlled Trials as Topic , Bias , Humans , Research Design , SARS-CoV-2
18.
PLoS One ; 16(3): e0248009, 2021.
Article in English | MEDLINE | ID: covidwho-1575841

ABSTRACT

INTRODUCTION: Since the start of the pandemic, millions of people have been infected, with thousands of deaths. Many foci worldwide have been identified in retirement nursing homes, with a high number of deaths. Our study aims were to evaluate the spread of SARS-CoV-2 in the retirement nursing homes, the predictors to develop symptoms, and death. METHODS AND FINDINGS: We conducted a retrospective study enrolling all people living in retirement nursing homes (PLRNH), where at least one SARS-CoV-2 infected person was present. Medical and clinical data were collected. Variables were compared with Student's t-test or Pearson chi-square test as appropriate. Uni- and multivariate analyses were conducted to evaluate variables' influence on infection and symptoms development. Cox proportional-hazards model was used to evaluate 30 days mortality predictors, considering death as the dependent variable. We enrolled 382 subjects. The mean age was 81.15±10.97 years, and males were 140(36.7%). At the multivariate analysis, mental disorders, malignancies, and angiotensin II receptor blockers were predictors of SARS-CoV-2 infection while having a neurological syndrome was associated with a lower risk. Only half of the people with SARS-CoV-2 infection developed symptoms. Chronic obstructive pulmonary disease and neurological syndrome were correlated with an increased risk of developing SARS-CoV-2 related symptoms. Fifty-six (21.2%) people with SARS-CoV-2 infection died; of these, 53 died in the first 30 days after the swab's positivity. Significant factors associated with 30-days mortality were male gender, hypokinetic disease, and the presence of fever and dyspnea. Patients' autonomy and early heparin treatment were related to lower mortality risk. CONCLUSIONS: We evidenced factors associated with infection's risk and death in a setting with high mortality such as retirement nursing homes, that should be carefully considered in the management of PLRNH.


Subject(s)
COVID-19/pathology , Aged , Aged, 80 and over , Angiotensin Receptor Antagonists/administration & dosage , COVID-19/complications , COVID-19/mortality , COVID-19/virology , Dyspnea/etiology , Female , Fever/etiology , Heparin, Low-Molecular-Weight/therapeutic use , Humans , Male , Mental Disorders/complications , Mental Disorders/pathology , Neoplasms/complications , Neoplasms/pathology , Nursing Homes , Proportional Hazards Models , Retrospective Studies , Risk Factors , SARS-CoV-2/isolation & purification , Sex Factors , Survival Rate
19.
J Med Internet Res ; 23(2): e21103, 2021 02 25.
Article in English | MEDLINE | ID: covidwho-1575226

ABSTRACT

BACKGROUND: During the COVID-19 pandemic, there has been a rapid increase in the amount of information about the disease and SARS-CoV-2 on the internet. If the language used in video messages is not clear or understandable to deaf and hard of hearing (DHH) people with a high school degree or less, this can cause confusion and result in information gaps among DHH people during a health emergency. OBJECTIVE: The aim of this study is to investigate the relationship between DHH people's perception of the effectiveness of physical distancing and contagiousness of an asymptomatic person. METHODS: This is a cross-sectional survey study on DHH people's perceptions about COVID-19 (N=475). Items pertaining to COVID-19 knowledge were administered to US deaf adults from April 17, 2020, to May 1, 2020, via a bilingual American Sign Language/English online survey platform. RESULTS: The sample consisted of 475 DHH adults aged 18-88 years old, with 74% (n=352) identifying as White and 54% (n=256) as female. About 88% (n=418) of the sample felt they knew most things or a lot about physical distancing. This figure dropped to 72% (n=342) for the question about the effectiveness of physical distancing in reducing the spread of COVID-19 and 70% (n=333) for the question about the contagiousness of an infected person without symptoms. Education and a knowledge of the effectiveness of physical distancing significantly predicted knowledge about the contagiousness of an asymptomatic individual. Race, gender, and age did not emerge as significant predictors. CONCLUSIONS: This results of this study point to the strong connection between education and coronavirus-related knowledge. Education-related disparities can be remedied by making information fully accessible and easily understood during emergencies and pandemics.


Subject(s)
COVID-19/transmission , Disease Transmission, Infectious/prevention & control , Persons With Hearing Impairments/statistics & numerical data , Physical Distancing , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , COVID-19/psychology , Cross-Sectional Studies , Female , Humans , Male , Middle Aged , Pandemics , Perception , SARS-CoV-2/isolation & purification , United States , Young Adult
20.
PLoS One ; 16(3): e0248438, 2021.
Article in English | MEDLINE | ID: covidwho-1574763

ABSTRACT

OBJECTIVES: Accurate and reliable criteria to rapidly estimate the probability of infection with the novel coronavirus-2 that causes the severe acute respiratory syndrome (SARS-CoV-2) and associated disease (COVID-19) remain an urgent unmet need, especially in emergency care. The objective was to derive and validate a clinical prediction score for SARS-CoV-2 infection that uses simple criteria widely available at the point of care. METHODS: Data came from the registry data from the national REgistry of suspected COVID-19 in EmeRgency care (RECOVER network) comprising 116 hospitals from 25 states in the US. Clinical variables and 30-day outcomes were abstracted from medical records of 19,850 emergency department (ED) patients tested for SARS-CoV-2. The criterion standard for diagnosis of SARS-CoV-2 required a positive molecular test from a swabbed sample or positive antibody testing within 30 days. The prediction score was derived from a 50% random sample (n = 9,925) using unadjusted analysis of 107 candidate variables as a screening step, followed by stepwise forward logistic regression on 72 variables. RESULTS: Multivariable regression yielded a 13-variable score, which was simplified to a 13-point score: +1 point each for age>50 years, measured temperature>37.5°C, oxygen saturation<95%, Black race, Hispanic or Latino ethnicity, household contact with known or suspected COVID-19, patient reported history of dry cough, anosmia/dysgeusia, myalgias or fever; and -1 point each for White race, no direct contact with infected person, or smoking. In the validation sample (n = 9,975), the probability from logistic regression score produced an area under the receiver operating characteristic curve of 0.80 (95% CI: 0.79-0.81), and this level of accuracy was retained across patients enrolled from the early spring to summer of 2020. In the simplified score, a score of zero produced a sensitivity of 95.6% (94.8-96.3%), specificity of 20.0% (19.0-21.0%), negative likelihood ratio of 0.22 (0.19-0.26). Increasing points on the simplified score predicted higher probability of infection (e.g., >75% probability with +5 or more points). CONCLUSION: Criteria that are available at the point of care can accurately predict the probability of SARS-CoV-2 infection. These criteria could assist with decisions about isolation and testing at high throughput checkpoints.


Subject(s)
COVID-19/diagnosis , COVID-19/epidemiology , Emergency Service, Hospital/trends , Adult , Aged , Clinical Decision Rules , Coronavirus Infections/diagnosis , Cough , Databases, Factual , Decision Trees , Emergency Service, Hospital/statistics & numerical data , Female , Fever , Humans , Male , Mass Screening , Middle Aged , Registries , SARS-CoV-2/pathogenicity , United States/epidemiology
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