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1.
JMIR Public Health Surveill ; 7(6): e24251, 2021 06 17.
Article in English | MEDLINE | ID: covidwho-2197876

ABSTRACT

BACKGROUND: COVID-19 transmission rates in South Asia initially were under control when governments implemented health policies aimed at controlling the pandemic such as quarantines, travel bans, and border, business, and school closures. Governments have since relaxed public health restrictions, which resulted in significant outbreaks, shifting the global epicenter of COVID-19 to India. Ongoing systematic public health surveillance of the COVID-19 pandemic is needed to inform disease prevention policy to re-establish control over the pandemic within South Asia. OBJECTIVE: This study aimed to inform public health leaders about the state of the COVID-19 pandemic, how South Asia displays differences within and among countries and other global regions, and where immediate action is needed to control the outbreaks. METHODS: We extracted COVID-19 data spanning 62 days from public health registries and calculated traditional and enhanced surveillance metrics. We use an empirical difference equation to measure the daily number of cases in South Asia as a function of the prior number of cases, the level of testing, and weekly shifts in variables with a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. RESULTS: Traditional surveillance metrics indicate that South Asian countries have an alarming outbreak, with India leading the region with 310,310 new daily cases in accordance with the 7-day moving average. Enhanced surveillance indicates that while Pakistan and Bangladesh still have a high daily number of new COVID-19 cases (n=4819 and n=3878, respectively), their speed of new infections declined from April 12-25, 2021, from 2.28 to 2.18 and 3.15 to 2.35 daily new infections per 100,000 population, respectively, which suggests that their outbreaks are decreasing and that these countries are headed in the right direction. In contrast, India's speed of new infections per 100,000 population increased by 52% during the same period from 14.79 to 22.49 new cases per day per 100,000 population, which constitutes an increased outbreak. CONCLUSIONS: Relaxation of public health restrictions and the spread of novel variants fueled the second wave of the COVID-19 pandemic in South Asia. Public health surveillance indicates that shifts in policy and the spread of new variants correlate with a drastic expansion in the pandemic, requiring immediate action to mitigate the spread of COVID-19. Surveillance is needed to inform leaders whether policies help control the pandemic.


Subject(s)
COVID-19/epidemiology , Communicable Disease Control/statistics & numerical data , Disease Outbreaks/statistics & numerical data , Health Policy , Public Health/statistics & numerical data , Adult , Aged , Aged, 80 and over , Asia/epidemiology , COVID-19/prevention & control , Communicable Disease Control/legislation & jurisprudence , Female , Humans , Longitudinal Studies , Male , Middle Aged , Public Health Surveillance , SARS-CoV-2
3.
Curr Issues Mol Biol ; 44(10): 4540-4556, 2022 Sep 30.
Article in English | MEDLINE | ID: covidwho-2065737

ABSTRACT

A novel series of bis-[1,3,4]thiadiazolimines, and bis-thiazolimines, with alkyl linker, were synthesized through general routes from cyclization of 1,1'-(hexane-1,6-diyl)bis(3-phenylthiourea) and hydrazonoyl halides or α-haloketones, respectively. Docking studies were applied to test the binding affinity of the synthesized products against the Mpro of SARS-CoV-2. The best compound, 5h, has average binding energy (-7.50 ± 0.58 kcal/mol) better than that of the positive controls O6K and N3 (-7.36 ± 0.34 and -6.36 ± 0.31 kcal/mol). Additionally, the docking poses (H-bonds and hydrophobic contacts) of the tested compounds against the Mpro using the PLIP web server were analyzed.

4.
Traitement Du Signal ; 39(1):205-219, 2022.
Article in English | Web of Science | ID: covidwho-1791615

ABSTRACT

Since the end of 2019, a COVID-19 outbreak has put healthcare systems worldwide on edge. In rural areas, where traditional testing is unfeasible, innovative computer-aided diagnostic approaches must deliver speedy and cost-effective screenings. Conducting a full scoping review is essential for academics despite several studies on the use of Deep Learning (DL) to combat COVID-19. This review examines the application of DL techniques in CT and ULS images for the early detection of COVID-19. In this review, the PRISMA literature review approach was followed. All studies are retrieved from IEEE, ACM, Medline, and Science Direct. Performance metrics were highlighted for each study to measure the proposed solutions' performance and conceptualization;A set of publicly available datasets were appointed;DL architectures based on more than one image modality such as CT and ULS are explored. Out of 32 studies, the combined U-Net segmentation and 3D classification VGG19 network had the best F1 score (98%) on ultrasound images, while ResNet-101 had the best accuracy (99.51%) on CT images for COVID-19 detection. Hence, data augmentation techniques such as rotation, flipping, and shifting were frequently used. Grad-CAM was used in eight studies to identify anomalies on the lung surface. Our research found that transfer learning outperformed all other AI-based prediction approaches. Using a UNET with a predefined backbone, like VGG19, a practical computer-assisted COVID-19 screening approach can be developed. More collaboration is required from healthcare professionals and the computer science community to provide an efficient deep learning framework for the early detection of COVID-19.

5.
4th International Conference on Robotics and Automation in Industry, ICRAI 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1701922

ABSTRACT

In this paper, we have performed transfer learning using different pre-trained convolutional neural networks for binary classification of X-ray images into COVID-19 disease and normal. The dataset is gathered from two open sources. Our dataset is consisting of 254 COVID-19 and 310 Normal X-ray images. The pandemic situation all around the world demands an efficient solution so that the disturbance of global health, daily life, and economy can be controlled. In this regard, we introduced the deep feature fusion-based technique which could help to design an embedded system. We fine-tuned and trained the thirteen independent pre-trained models and we found that the Resnet50V2 model performed efficiently for binary classification scenarios. Our proposed technique using transfer learning gives a detection rate of 99.5% for binary classification (Normal and COVID). © 2021 IEEE.

6.
J Med Internet Res ; 23(2): e26081, 2021 02 09.
Article in English | MEDLINE | ID: covidwho-1575190

ABSTRACT

BACKGROUND: The COVID-19 pandemic has had profound and differential impacts on metropolitan areas across the United States and around the world. Within the United States, metropolitan areas that were hit earliest with the pandemic and reacted with scientifically based health policy were able to contain the virus by late spring. For other areas that kept businesses open, the first wave in the United States hit in mid-summer. As the weather turns colder, universities resume classes, and people tire of lockdowns, a second wave is ascending in both metropolitan and rural areas. It becomes more obvious that additional SARS-CoV-2 surveillance is needed at the local level to track recent shifts in the pandemic, rates of increase, and persistence. OBJECTIVE: The goal of this study is to provide advanced surveillance metrics for COVID-19 transmission that account for speed, acceleration, jerk and persistence, and weekly shifts, to better understand and manage risk in metropolitan areas. Existing surveillance measures coupled with our dynamic metrics of transmission will inform health policy to control the COVID-19 pandemic until, and after, an effective vaccine is developed. Here, we provide values for novel indicators to measure COVID-19 transmission at the metropolitan area level. METHODS: Using a longitudinal trend analysis study design, we extracted 260 days of COVID-19 data from public health registries. We used an empirical difference equation to measure the daily number of cases in the 25 largest US metropolitan areas as a function of the prior number of cases and weekly shift variables based on a dynamic panel data model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. RESULTS: Minneapolis and Chicago have the greatest average number of daily new positive results per standardized 100,000 population (which we refer to as speed). Extreme behavior in Minneapolis showed an increase in speed from 17 to 30 (67%) in 1 week. The jerk and acceleration calculated for these areas also showed extreme behavior. The dynamic panel data model shows that Minneapolis, Chicago, and Detroit have the largest persistence effects, meaning that new cases pertaining to a specific week are statistically attributable to new cases from the prior week. CONCLUSIONS: Three of the metropolitan areas with historically early and harsh winters have the highest persistence effects out of the top 25 most populous metropolitan areas in the United States at the beginning of their cold weather season. With these persistence effects, and with indoor activities becoming more popular as the weather gets colder, stringent COVID-19 regulations will be more important than ever to flatten the second wave of the pandemic. As colder weather grips more of the nation, southern metropolitan areas may also see large spikes in the number of cases.


Subject(s)
COVID-19/epidemiology , Communicable Disease Control , COVID-19/prevention & control , COVID-19/transmission , Health Policy , Humans , Longitudinal Studies , Models, Statistical , Pandemics , Public Health , Public Health Surveillance , Registries , SARS-CoV-2 , United States/epidemiology
7.
34th Annual ACM Symposium on User Interface Software and Technology, UIST 2021 ; : 894-909, 2021.
Article in English | Scopus | ID: covidwho-1499134

ABSTRACT

Model-driven policymaking for epidemic control is a challenging collaborative process. It begins when a team of public-health officials, epidemiologists, and economists construct a reasonably predictive disease model representative of the team's region of interest as a function of its unique socio-economic and demographic characteristics. As the team considers possible interventions such as school closures, social distancing, vaccination drives, etc., they need to simultaneously model each intervention's effect on disease spread and economic cost. The team then engages in an extensive what-if analysis process to determine a cost-effective policy: a schedule of when, where and how extensively each intervention should be applied. This policymaking process is often an iterative and laborious programming-intensive effort where parameters are introduced and refined, model and intervention behaviors are modified, and schedules changed. We have designed and developed EpiPolicy to support this effort. EpiPolicy is a policy aid and epidemic simulation tool that supports the mathematical specification and simulation of disease and population models, the programmatic specification of interventions and the declarative construction of schedules. EpiPolicy's design supports a separation of concerns in the modeling process and enables capabilities such as the iterative and automatic exploration of intervention plans with Monte Carlo simulations to find a cost-effective one. We report expert feedback on EpiPolicy. In general, experts found EpiPolicy's capabilities powerful and transformative, when compared with their current practice. © 2021 ACM.

8.
Pakistan Journal of Medical and Health Sciences ; 15(5):1196-1199, 2021.
Article in English | EMBASE | ID: covidwho-1315209

ABSTRACT

Aim: To assess the results of chest x ray radiographs of patients positive for Covid-19, presented at the tertiary care hospital according to the classification by the British Society of Thoracic Imaging (BSTI. Place and Duration: In COVID-19 Ward (Department of Medicine) Sheikh Zayed Hospital, Lahore for three months duration from January 2021 to March 2021. Methods: A total of 96 patients were selected. In this observational study, positive COVID-19 patient determined by the reverse transcriptase polymerase chain reaction (RT-PCR) were enrolled for this study above the age of 14 years. CXR results were classified conferring to BSTI documentation and classification in terms of percentage and frequency. Results: Chest rays of 96 patients who tested positive for Covid-19 by RT-PCR over the age of 14 years were examined. Chest X-rays are classified according to the BSTI Covid-19 X-ray classification. Out of 96 patients, 10 patients (10.41%) had normal chest x-rays, 19 (19.80%) patients had classic bilateral, peripheral and basal consolidation / ground glass opacity (GMO), 60 (62.5%) had unspecified group,7(7.29%) patients have poor quality X-ray film. The unilateral involvement was noticed in 15 and bilateral in 49 patients, 12 of the patients had diffuse involvement on chest radiograph and peripheral involvement in 39 patients. According to regional dominance, 41 of the unspecified (42.70%) had middle and lower lung involvement, 7 (7.29%) had only the middle zone, and 8 (8.33%) had involvement of lower zone. Conclusions: In this study, Covid-19 chest X-rays are usually presented as ground glass opacity, mixed consolidation with GGOs in the middle and lower peripheral areas of the bilateral lung. Chest X-ray BSTI classification is used to classify Covid-19 severity in our patients, thus differentiating in the classic Covid-19 of the middle zone versus low zone involvement.

9.
Endoscopy ; 53(SUPPL 1):S260-S261, 2021.
Article in English | EMBASE | ID: covidwho-1254067

ABSTRACT

Aims The rate of incidence and outcome of COVID-19 infection following endoscopic procedures during the first UKlockdown period was evaluated. We also assessed risk factors for transmission of COVID-19 infection post-endoscopy. Methods Patients who had endoscopic procedures in our unit from 23/3/2020 to 31/5/2020 were included. During thisperiod, only emergency and urgent procedures were undertaken. Follow up calls were made subsequently to all patients toenquire about COVID-19 symptoms, hospital admissions and COVID-19 testing within 14 days of their procedures. Toidentify risk factors for COVID-19 transmission post-endoscopy, we performed binominal logistic regression. Results 391 endoscopies were included (table). 1.5 % (6/391) patients developed COVID-19 symptoms post-endoscopy.Median age is 80 (mean 75.8) with female to male ratio 2:1. The most common symptoms were fever, cough andbreathlessness 83.3 % (5/6). The percentage of the confirmed cases by COVID-19 PCR swab test was 1.3 % (5/391). Themedian days that those 5 patients developed confirmed COVID-19 post-endoscopy was 7 (range 3-13). 0.8 % (3/391) diedfrom COVID-19-related complications within 30 days after endoscopic procedure. One had gastroscopy, one flexiblesigmoidoscopy and one ERCP, these procedures were performed on different dates and by different teams. The unadjusted30-days all-cause mortality rate post-endoscopy was 3.6 % (14/391), all of them were inpatients. On univariate binominal logistic regression, age as a continuous variable (OR 1.122;95 % CI [1.021-1.234];p = 0.017), lessthan 10 day hospital stay (OR 0.057;95 % CI [0.008-0.400];p = 0.004) and hospital stay between 11-20 days (OR 0.067;95 % CI [0.005-0.842];p = 0.036) were associated with COVID-19 transmission. Combining the above factors into amultivariable regression model, no factor achieved statistical significance. Conclusions The risk of transmission of clinical COVID-19 seems to be low for patients in the context of endoscopyprocedures when the appropriate personal protective measures are in place. No risk factor reached statistical significance.

10.
Aesthet Surg J ; 41(9): NP1199-NP1205, 2021 08 13.
Article in English | MEDLINE | ID: covidwho-1191098

ABSTRACT

BACKGROUND: The emergence of COVID-19 led rapidly to one of the most severe disease outbreaks in modern history. This caused many aesthetic practices to close temporarily, providing a unique opportunity to evaluate the impact of neurotoxin use in the setting of an ongoing pandemic. OBJECTIVES: The aim of this study was to examine whether administration of onabotulinumtoxinA (BOTOX Cosmetic, Allergan plc, Dublin, Ireland) to regular users synergistically amplifies the elevation in mood/happiness, self-satisfaction with appearance, and overall satisfaction in the context of the ongoing pandemic. METHODS: A randomized, single-blind, crossover study was designed to evaluate the impact of neurotoxin treatment in the upper third of the face on mood, self-satisfaction with appearance, and overall satisfaction. The placebo group crossed over to treatment after 1 month. Surveys evaluating patient happiness, self-satisfaction with appearance, and overall efficacy were completed by both groups, and again by the placebo group following crossover to treatment. RESULTS: Forty-five subjects were enrolled: 30 in the treatment group and 15 in the control/crossover group. The placebo group demonstrated no change in happiness or self-satisfaction in appearance until crossover to the treatment group. Both groups, once receiving onabotulinumtoxinA, reported increased happiness, self-satisfaction with appearance, and overall treatment satisfaction. CONCLUSIONS: OnabotulinumtoxinA treatment to the upper face in the midst of the COVID-19 pandemic was found to increase patient happiness, self-satisfaction with appearance, and overall treatment satisfaction.


Subject(s)
Botulinum Toxins, Type A , COVID-19 , Neuromuscular Agents , Skin Aging , Botulinum Toxins, Type A/adverse effects , Cross-Over Studies , Double-Blind Method , Humans , Neuromuscular Agents/adverse effects , Pandemics , Patient Satisfaction , SARS-CoV-2 , Single-Blind Method , Treatment Outcome
11.
Open Forum Infectious Diseases ; 7(SUPPL 1):S269-S270, 2020.
Article in English | EMBASE | ID: covidwho-1185768

ABSTRACT

Background: Michigan was one of the severely impacted regions during the initial COVID-19 surge. An institutional protocol with early methylprednisolone (MP) to treat COVID-19 patients requiring supplemental oxygen was implemented. We sought to study characteristics of these patients who were readmitted with infectious and non-infectious diagnoses. Methods: A retrospective analysis of 21 COVID-19 readmitted patients initially admitted between 3/10/2020 and 4/20/2020 (early 0-7, late 8-30 days) was done. Total of 455 COVID-19 patients, confirmed by a positive nasopharyngeal RT-PCR were admitted during this time period. Demographic data, clinical characteristics, laboratory and radiographic results and treatments were compared among the early and late readmission groups. Univariate and logistic regression analysis were performed to study the risk factors associated with early readmission and worsening of COVID-19 pneumonia. Secondary analyses were performed comparing worsening COVID-19 pneumonia with other readmission diagnoses. Results: 4.6% (21/455) were readmitted, 14 early vs 7 late (median age 75 vs 65 yrs). Most early readmissions were COVID-19 related and 8 out of 14 had worsening COVID-19 pneumonia based on clinical picture, laboratory and imaging findings. Readmitted patients with worsening COVID-19 related pneumonia had significantly elevated CRP and lower ALC compared to last discharge value (Table 1). None of the late readmissions required MP. A total of 8 readmissions had bacterial coinfections (1/8 COVID-19 related) (Table 2). Bacterial infections unrelated to COVID-19 were aspiration pneumonia (2), urinary tract infection (2), enterococcal bacteremia from stercoral colitis (1), sacral osteomyelitis (1), and infected BKA stump (1). Each increasing day of MP duration during the first admission reduced the likelihood of early readmission by approximately 10% (OR 0.90, 95% CI 0.63-1.2, p=0.56) (Table 3). 1/14 and 0/7 patients died amongst early and late readmissions respectively. Conclusion: Early MP in COVID-19 pneumonia was not associated with increased risk of early secondary bacterial infections in the readmitted patients. Optimal duration of MP in patients with COVID-19 pneumonia needs to be defined.

12.
Open Forum Infectious Diseases ; 7(SUPPL 1):S269, 2020.
Article in English | EMBASE | ID: covidwho-1185767

ABSTRACT

Background: Pneumothorax has been reported with the use of positive pressure ventilation in COVID-19 pneumonia. Literature on spontaneous pneumothorax (PTX) in COVID-19 patients is scant. We present a case series of 7 patients with COVID-19 pneumonia, who developed spontaneous pneumothorax without prior mechanical ventilation. Methods: A retrospective chart review of 7 cases was performed from two different hospitals in the US between 4/6/2020-5/15/2020. Hospitalized patients with confirmed COVID-19 by nasopharyngeal RT-PCR who developed spontaneous pneumothorax were included. Collected data included demographics, co-morbidities, inflammatory biomarkers, chest imaging and management strategies. Length of stay, transfer to intensive care unit and death were the assessed outcomes. A descriptive analysis was done. Results: There were 3 patients from Henry Ford Health System, Michigan and 4 patients from Silver Cross Hospital, Illinois. Median age was 75 years and 6 out of 7 (85.7%) were males (Table 1). There were no co-morbidities associated with spontaneous pneumothorax except for one patient with COPD. None of the patients' imaging prior to diagnosis of pneumothorax revealed any underlying blebs. Median time from symptom onset to diagnosis of pneumothorax was 17 days. One of the patients had tension pneumothorax, two had bilateral pneumothorax and three had pneumomediastinum (Figure 1). Four patients required chest tube placement, three required escalation to ICU, of which two died. Conclusion: Spontaneous pneumothorax may be an unrecognized late complication of COVID-19 pneumonia. In hospitalized patients with acute respiratory decompensation, spontaneous pneumothorax should be considered as part of the differential diagnosis. Repeat chest imaging should be considered in these cases.

13.
JMIR Public Health Surveill ; 7(5): e25753, 2021 05 10.
Article in English | MEDLINE | ID: covidwho-1183763

ABSTRACT

BACKGROUND: The COVID-19 global pandemic has disrupted structures and communities across the globe. Numerous regions of the world have had varying responses in their attempts to contain the spread of the virus. Factors such as public health policies, governance, and sociopolitical climate have led to differential levels of success at controlling the spread of SARS-CoV-2. Ultimately, a more advanced surveillance metric for COVID-19 transmission is necessary to help government systems and national leaders understand which responses have been effective and gauge where outbreaks occur. OBJECTIVE: The goal of this study is to provide advanced COVID-19 surveillance metrics for Canada at the country, province, and territory level that account for shifts in the pandemic including speed, acceleration, jerk, and persistence. Enhanced surveillance identifies risks for explosive growth and regions that have controlled outbreaks successfully. METHODS: Using a longitudinal trend analysis study design, we extracted 62 days of COVID-19 data from Canadian public health registries for 13 provinces and territories. We used an empirical difference equation to measure the daily number of cases in Canada as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. RESULTS: We compare the week of February 7-13, 2021, with the week of February 14-20, 2021. Canada, as a whole, had a decrease in speed from 8.4 daily new cases per 100,000 population to 7.5 daily new cases per 100,000 population. The persistence of new cases during the week of February 14-20 reported 7.5 cases that are a result of COVID-19 transmissions 7 days earlier. The two most populous provinces of Ontario and Quebec both experienced decreases in speed from 7.9 and 11.5 daily new cases per 100,000 population for the week of February 7-13 to speeds of 6.9 and 9.3 for the week of February 14-20, respectively. Nunavut experienced a significant increase in speed during this time, from 3.3 daily new cases per 100,000 population to 10.9 daily new cases per 100,000 population. CONCLUSIONS: Canada excelled at COVID-19 control early on in the pandemic, especially during the first COVID-19 shutdown. The second wave at the end of 2020 resulted in a resurgence of the outbreak, which has since been controlled. Enhanced surveillance identifies outbreaks and where there is the potential for explosive growth, which informs proactive health policy.


Subject(s)
COVID-19/epidemiology , COVID-19/prevention & control , Public Health Surveillance/methods , Canada/epidemiology , Humans , Longitudinal Studies
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