Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 11 de 11
Filter
1.
Environ Sci Pollut Res Int ; 2021 Nov 12.
Article in English | MEDLINE | ID: covidwho-1509301

ABSTRACT

The COVID-19 pandemic affected the world through its ability to cause widespread infection. The Middle East including the Kingdom of Saudi Arabia (KSA) has also been hit by the COVID-19 pandemic like the rest of the world. This study aims to examine the relationships between meteorological factors and COVID-19 case counts in three cities of the KSA. The distribution of the COVID-19 case counts was observed for all three cities followed by cross-correlation analysis which was carried out to estimate the lag effects of meteorological factors on COVID-19 case counts. Moreover, the Poisson model and negative binomial (NB) model with their zero-inflated versions (i.e., ZIP and ZINB) were fitted to estimate city-specific impacts of weather variables on confirmed case counts, and the best model is evaluated by comparative analysis for each city. We found significant associations between meteorological factors and COVID-19 case counts in three cities of KSA. We also perceived that the ZINB model was the best fitted for COVID-19 case counts. In this case study, temperature, humidity, and wind speed were the factors that affected COVID-19 case counts. The results can be used to make policies to overcome this pandemic situation in the future such as deploying more resources through testing and tracking in such areas where we observe significantly higher wind speed or higher humidity. Moreover, the selected models can be used for predicting the probability of COVID-19 incidence across various regions.

2.
Eur J Obstet Gynecol Reprod Biol ; 266: 111-113, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1433181

ABSTRACT

Maternal morbidity and mortality remain stubborn highly in many parts of the world. Similarly Neonatal morbidity, mortality and five years survival in most of the under-resourced countries has not declined significantly over the past decades. Furthermore sexual reproductive health services provision has not met the needs of the women and there remains a huge unmet need for reliable contraception globally. This is the time for a global action plan and for all agencies to work together to achieve meaningful outcomes to improve health of women and their babies. Covid 19 pandemic has led to increase in gender based violence as well which is deplorable. European Board and College of Obstetrics and Gynaecology welcome this initiative and commits to work with all the stakeholders to improve safety and quality of care for women and the newborn.


Subject(s)
COVID-19 , Gynecology , Obstetrics , Female , Humans , Infant, Newborn , Patient Safety , Pregnancy , SARS-CoV-2
3.
Vaccines (Basel) ; 9(7)2021 Jul 01.
Article in English | MEDLINE | ID: covidwho-1295945

ABSTRACT

The current study aims to assess the beliefs of the general public in Pakistan towards conspiracy theories, acceptance, willingness to pay, and preference for the COVID-19 vaccine. A cross-sectional study was conducted through an online self-administered questionnaire during January 2021. The Chi-square test or Fisher exact test was utilized for statistical data analysis. A total of 2158 respondents completed the questionnaire, among them 1192 (55.2%) were male with 23.87 (SD: ±6.23) years as mean age. The conspiracy beliefs circulating regarding the COVID-19 vaccine were believed by 9.3% to 28.4% of the study participants. Among them, 1040 (48.2%) agreed to vaccinate on its availability while 934 (43.3%) reported the Chinese vaccine as their preference. The conspiracy beliefs of the participants were significantly associated with acceptance of the COVID-19 vaccine. The existence of conspiracy beliefs and low vaccine acceptance among the general population is a serious threat to successful COVID-19 vaccination.

4.
Eur J Obstet Gynecol Reprod Biol ; 262: 256-258, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1230458

ABSTRACT

Covid 19 pandemic has led to significant mortality and long term morbidity globally. Pregnant women are at increased risk of severe illness from COVID 19 infection. There is an urgent need for all health authorities and Governments to offer vaccination to all pregnant women especially those with high risk pregnancy.


Subject(s)
COVID-19 , Pregnancy Complications, Infectious , Breast Feeding , COVID-19 Vaccines , Female , Humans , Pregnancy , SARS-CoV-2 , Vaccination
5.
Appl Soft Comput ; 108: 107490, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1230370

ABSTRACT

Currently, the coronavirus disease 2019 (COVID19) pandemic has killed more than one million people worldwide. In the present outbreak, radiological imaging modalities such as computed tomography (CT) and X-rays are being used to diagnose this disease, particularly in the early stage. However, the assessment of radiographic images includes a subjective evaluation that is time-consuming and requires substantial clinical skills. Nevertheless, the recent evolution in artificial intelligence (AI) has further strengthened the ability of computer-aided diagnosis tools and supported medical professionals in making effective diagnostic decisions. Therefore, in this study, the strength of various AI algorithms was analyzed to diagnose COVID19 infection from large-scale radiographic datasets. Based on this analysis, a light-weighted deep network is proposed, which is the first ensemble design (based on MobileNet, ShuffleNet, and FCNet) in medical domain (particularly for COVID19 diagnosis) that encompasses the reduced number of trainable parameters (a total of 3.16 million parameters) and outperforms the various existing models. Moreover, the addition of a multilevel activation visualization layer in the proposed network further visualizes the lesion patterns as multilevel class activation maps (ML-CAMs) along with the diagnostic result (either COVID19 positive or negative). Such additional output as ML-CAMs provides a visual insight of the computer decision and may assist radiologists in validating it, particularly in uncertain situations Additionally, a novel hierarchical training procedure was adopted to perform the training of the proposed network. It proceeds the network training by the adaptive number of epochs based on the validation dataset rather than using the fixed number of epochs. The quantitative results show the better performance of the proposed training method over the conventional end-to-end training procedure. A large collection of CT-scan and X-ray datasets (based on six publicly available datasets) was used to evaluate the performance of the proposed model and other baseline methods. The experimental results of the proposed network exhibit a promising performance in terms of diagnostic decision. An average F1 score (F1) of 94.60% and 95.94% and area under the curve (AUC) of 97.50% and 97.99% are achieved for the CT-scan and X-ray datasets, respectively. Finally, the detailed comparative analysis reveals that the proposed model outperforms the various state-of-the-art methods in terms of both quantitative and computational performance.

6.
IEEE J Biomed Health Inform ; 25(6): 1881-1891, 2021 06.
Article in English | MEDLINE | ID: covidwho-1174999

ABSTRACT

In the present epidemic of the coronavirus disease 2019 (COVID-19), radiological imaging modalities, such as X-ray and computed tomography (CT), have been identified as effective diagnostic tools. However, the subjective assessment of radiographic examination is a time-consuming task and demands expert radiologists. Recent advancements in artificial intelligence have enhanced the diagnostic power of computer-aided diagnosis (CAD) tools and assisted medical specialists in making efficient diagnostic decisions. In this work, we propose an optimal multilevel deep-aggregated boosted network to recognize COVID-19 infection from heterogeneous radiographic data, including X-ray and CT images. Our method leverages multilevel deep-aggregated features and multistage training via a mutually beneficial approach to maximize the overall CAD performance. To improve the interpretation of CAD predictions, these multilevel deep features are visualized as additional outputs that can assist radiologists in validating the CAD results. A total of six publicly available datasets were fused to build a single large-scale heterogeneous radiographic collection that was used to analyze the performance of the proposed technique and other baseline methods. To preserve generality of our method, we selected different patient data for training, validation, and testing, and consequently, the data of same patient were not included in training, validation, and testing subsets. In addition, fivefold cross-validation was performed in all the experiments for a fair evaluation. Our method exhibits promising performance values of 95.38%, 95.57%, 92.53%, 98.14%, 93.16%, and 98.55% in terms of average accuracy, F-measure, specificity, sensitivity, precision, and area under the curve, respectively and outperforms various state-of-the-art methods.


Subject(s)
COVID-19/diagnostic imaging , Deep Learning , COVID-19/virology , Diagnosis, Computer-Assisted/methods , Humans , Neural Networks, Computer , SARS-CoV-2/isolation & purification , Tomography, X-Ray Computed/methods
7.
Int J Environ Res Public Health ; 18(1)2020 12 29.
Article in English | MEDLINE | ID: covidwho-1004730

ABSTRACT

Transport planning and public health have been intertwined historically. The health impact of public transport services, such as social exclusion, is a widely discussed research topic. Social exclusion is a paramount concern for older adults' health in the wake of emerging global challenges. However, there remains a significant research gap on how psychosocial barriers faced by older adults in using public transport services influence the social exclusion behavior. The present research provides empirical evidence and shows the impact of certain psychosocial barriers of public transportation on older adults' social exclusion. A total of 243 Pakistani older adults (aged 60-89 years old) voluntarily participated in this cross-sectional study. The participants provided self-reports on their psychosocial barriers (including perceived norms, attitude, personal ability, habits, neighborhood social constraints, and intention) and the corresponding social exclusion. Partial Least Square Structural Equation Modeling (PLS-SEM) was utilized for the data analysis. The structural path model supported the significant associations between psychosocial barriers and social exclusion. Except for perceived descriptive norms, all other psychosocial barriers predicted older adults' social exclusion. The research portrays the significance of the psychosocial factors to examine social exclusion and offers practical implications for urban and transport planners. The concerned policymakers can use the research findings to develop age-sensitive, socially sustainable, and healthy cities.


Subject(s)
Social Isolation , Transportation , Aged , Aged, 80 and over , Cities , Cross-Sectional Studies , Humans , Middle Aged , Pakistan , Residence Characteristics
8.
Eur J Obstet Gynecol Reprod Biol ; 258: 457-458, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-970289

ABSTRACT

The specialty of Obstetrics and Gynaecology has been on the forefront of introducing simulation in post graduate education for the past two decades. Simulation training is known to enhance psychomotor skills and is considered an important step in the transition from classroom learning to clinical practice. Training on simulators allows trainees to acquire basic skills before getting involved in day to day care in real life situations. Clinical circumstances around the COVID 19 pandemic have highlighted the key importance of simulation training in delivering post graduate curriculum.


Subject(s)
Gynecology/education , Obstetrics/education , Simulation Training/standards , COVID-19/epidemiology , Curriculum , Female , Humans , Pandemics , Pregnancy , SARS-CoV-2
9.
PeerJ ; 8: e10472, 2020.
Article in English | MEDLINE | ID: covidwho-946232

ABSTRACT

Background: Across the globe, lockdowns have been enforced as a pandemic response to COVID-19. Such lockdown coupled with school closures and stay-at-home orders made women more vulnerable in terms of higher responsibility and spending more time with an abusive partner, if any. Methods: This study investigates the situation of women during COVID-19 induced lockdown by focusing on their happiness and inquiring about the incidence of violence. Using the zero-inflated negative binomial model, our findings ascertained that family settings, type of relationship with a spouse, and age significantly affects the positive count of violence during the lockdown. We further estimated the determinants of happiness and found that years of schooling, the role of women in household decision making, and feeling empowered is affecting their happiness. Results: Women having higher education have more odds of zero violence. Unemployed women and women who are not working have higher odds of zero violence as compared to women who are working. During this lockdown after the COVID-19 pandemic, women living in urban areas, having higher education, having an adequate household income to meet the expenditures, having lesser anxiety, not facing violence, feeling empowered when their husband is around, and have higher decision-making power are happier. Discussion and conclusion: The study is important in the context of happiness and violence inflicted on women during the lockdown and provides the basis to improve the pandemic response policy. The inclusion of women's safety and happiness in pandemic response policy is important to ensure the well-being of women and to devise better health and economic policy. Our estimates suggest higher education results in less incidence of violence which could be argued as desirable outcomes for building healthy, productive, and happy communities. In addition to this, as pandemic induced lock-down is likely to result in higher unemployment across the globe including Pakistan, therefore, in light of our estimates pertaining to the role of unemployment in the incidence of violence, policymakers should deploy more resources to enhance income and to combat the rising unemployment. As a counter-intuitive outcome of these policy interventions, incidence of violence will be dampened, educational attainment and women empowerment will be increased which will certainly increase happiness.

10.
Hum Vaccin Immunother ; 16(12): 3001-3010, 2020 12 01.
Article in English | MEDLINE | ID: covidwho-744473

ABSTRACT

Coronaviruses are single-stranded RNA viruses that cause severe respiratory, enteric, and systemic infections in a vast range of hosts, including man, fish, mammals, and avian. Scientific interest has heightened on coronaviruses after the emergence of the 2019 novel Coronavirus (SARS-CoV-2). This review provides current perspectives on morphology, genetic diversity, transmission characteristics, replication cycle, diagnostic approaches, epidemiological assessment, and prevention strategies against the SARS-CoV-2. Moreover, different potential biotherapeutics such as small drug molecules, different vaccines, and immunotherapies to control severe acute respiratory infections caused by 2019 novel coronavirus (SARS-CoV-2) are repurposed and discussed with different mechanistic approaches. The current growth trends of the SARS-CoV-2/COVID-19 outbreak globally and preventive measures are briefly discussed. Furthermore, the lessons learned from the COVID-19 outbreak, so far, concluding remarks and future directions for controlling for COVID-19, are also recommended for a safer tomorrow.


Subject(s)
Antiviral Agents/immunology , COVID-19/immunology , COVID-19/prevention & control , Immunotherapy/methods , SARS-CoV-2/immunology , Animals , Antiviral Agents/administration & dosage , COVID-19/genetics , Coronavirus/drug effects , Coronavirus/genetics , Coronavirus/immunology , Disease Outbreaks/prevention & control , Humans , Immunity, Herd/drug effects , Immunity, Herd/immunology , Immunotherapy/trends , Quarantine/methods , Quarantine/trends , Respiratory Tract Infections , SARS-CoV-2/drug effects , SARS-CoV-2/genetics
11.
Eur J Obstet Gynecol Reprod Biol ; 250: 246-249, 2020 Jul.
Article in English | MEDLINE | ID: covidwho-741189

ABSTRACT

The risk of vertical transmission during vaginal delivery in COVID-19 pregnant patients is currently a topic of debate. Obstetric norms on vaginal birth assistance to reduce the potential risk of perinatal infection should be promoted by ensuring that the risk of contamination from maternal anus and faecal material is reduced during vaginal delivery.


Subject(s)
Betacoronavirus , Coronavirus Infections/transmission , Delivery, Obstetric/methods , Infectious Disease Transmission, Vertical/prevention & control , Pneumonia, Viral/transmission , Pregnancy Complications, Infectious/virology , COVID-19 , Coronavirus Infections/virology , Female , Humans , Pandemics , Pneumonia, Viral/virology , Pregnancy , SARS-CoV-2 , Vagina/virology
SELECTION OF CITATIONS
SEARCH DETAIL
...