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1.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-304997

ABSTRACT

Introduction: From the start of COVID-19 pandemic governments have been taking many decisions to control the outbreak. The impact of these decisions and policy changes on the outbreak is required to be analyzed.Objective: This article aims to investigate the impact of interventions implemented by the Government of Pakistan on the recent outbreak of novel-coronavirus. It provides the changes in the behavior of the outbreak on the implementation of two different types of interventions.Material and Method: An interrupted time-series (ITS) Poisson regression model on the ratio of cases to tests conducted for COVID-19 to regional level data of Pakistan is implemented, after checking the over-dispersion and autocorrelation problems. Selecting the level and slope change models, the effects of interventions, and the comparison of the selected models was also made. To examine future behavior of the pandemic the new cases of COVID-19, after 30 days, 60 days, and 90 days was also predicted.Result and Discussions: The estimated changes in positive ratio due to first and second interventions were reported 21.1% and 46.7% respectively for Pakistan. The country-wide COVID-19 cases predicted assuming full lockdown show an increasing trend i.e. 18,404, 37,288, and 75,545 after 30, 60, and 90 days, respectively. Assuming the partial lockdown the COVID-19 cases in the country might again reach the spike. However, 1,428, 1,004, and 706 cases are predicted under smart lockdown after 30, 60, and 90 days, respectively.Funding Statement: None.Declaration of Interests: None.

2.
Emerg Infect Dis ; 28(2): 429-431, 2022 02.
Article in English | MEDLINE | ID: covidwho-1650705

ABSTRACT

A March-June 2021 representative serosurvey among Sitakunda subdistrict (Chattogram, Bangladesh) residents found an adjusted prevalence of severe acute respiratory syndrome coronavirus 2 antibodies of 64.1% (95% credible interval 60.0%-68.1%). Before the Delta variant surge, most residents had been infected, although cumulative confirmed coronavirus disease incidence was low.


Subject(s)
COVID-19 , SARS-CoV-2 , Antibodies, Viral , Bangladesh/epidemiology , Humans , Seroepidemiologic Studies
4.
Healthcare (Basel) ; 10(1)2022 Jan 02.
Article in English | MEDLINE | ID: covidwho-1613731

ABSTRACT

Machine Learning methods can play a key role in predicting the spread of respiratory infection with the help of predictive analytics. Machine Learning techniques help mine data to better estimate and predict the COVID-19 infection status. A Fine-tuned Ensemble Classification approach for predicting the death and cure rates of patients from infection using Machine Learning techniques has been proposed for different states of India. The proposed classification model is applied to the recent COVID-19 dataset for India, and a performance evaluation of various state-of-the-art classifiers to the proposed model is performed. The classifiers forecasted the patients' infection status in different regions to better plan resources and response care systems. The appropriate classification of the output class based on the extracted input features is essential to achieve accurate results of classifiers. The experimental outcome exhibits that the proposed Hybrid Model reached a maximum F1-score of 94% compared to Ensembles and other classifiers like Support Vector Machine, Decision Trees, and Gaussian Naïve Bayes on a dataset of 5004 instances through 10-fold cross-validation for predicting the right class. The feasibility of automated prediction for COVID-19 infection cure and death rates in the Indian states was demonstrated.

5.
2021.
Preprint in English | Other preprints | ID: ppcovidwho-294259

ABSTRACT

In a representative serosurvey conducted March–June 2021, 64.1% (95%CrI 60.0– 68.1%) of Sitakunda subdistrict (Bangladesh) had anti-SARS-CoV-2 IgG antibodies after adjusting for age, sex, household clustering and test performance. Before the surge of Delta, most of the population had been infected despite low incidence of virologically-confirmed COVID-19.

6.
Clean Eng Technol ; 4: 100218, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1322032

ABSTRACT

On the eve of the outbreak of the COVID-19 pandemic, there is a tremendous increase in the production of facemasks across the world. The primary raw materials for the manufacturing of the facemasks are non-biodegradable synthetic polymers derived from petrochemicals. Disposal of these synthetic facemasks increases waste-load in the environment causing severe ecological issues for flora and fauna. The synthesis processes of the polymers from the petrochemical by-products were also not eco-friendly, which releases huge greenhouse and harmful gases. Therefore, many research organizations and entrepreneurs realize the need for biodegradable facemasks to render similar performance as the existing non-biodegradable masks. The conventional textile fabrics made of natural fibers like cotton, flax, hemp, etc., can also be used to prepare facemasks with multiple layers in use for general protection. Such natural textile masks can be made anti-microbial by applying various herbal anti-microbial extracts like turmeric, neem, basil, aloe vera, etc. As porosity is the exclusive feature of the masks for arresting tiny viruses, the filter of the masks should have a pore size in the nanometre scale, and that can be achieved in nanomembrane manufactured by electrospinning technology. This article reviews the various scopes of electrospinning technology for the preparation of nanomembrane biomasks. Besides protecting us from the virus, the biomasks can be useful for skin healing, skincare, auto-fragrance, and organized cooling which are also discussed in this review article.

7.
Diabetes Metab Syndr ; 14(6): 2031-2038, 2020.
Article in English | MEDLINE | ID: covidwho-893726

ABSTRACT

BACKGROUND AND AIMS: This study investigated the clinical manifestations, outcomes and long-term complications of COVID-19 inpatients in southern part of Bangladesh while emphasizing on individuals having diabetes. METHODS: A cross-sectional study was conducted for a sample of COVID-19 inpatients across four different hospitals of Bangladesh between April 1and June 30, 2020. Variation in clinical characteristics, contact history, comorbidities, treatment patterns, and immediate post COVID complications were investigated. RESULTS: There were 734 COVID-19 presentations in this study of which 19.8% of patients had diabetes and 76% of the COVID-19 patients were male. Among biochemical parameters, plasma glucose, D-dimer, and Troponin-I levels were significantly elevated amidst the cohort with diabetes. The frequency of patients requiring insulin increased threefold during infection with SARS CoV-2. 1.4% patients developed new onset of diabetes mellitus. A number of COVID-19 patients with diabetes have been suffering from complications post-recovery including pain, discomfort, and sleep disturbance. CONCLUSION: Individuals with diabetes have experienced a severe manifestation of COVID-19 and post disease complications. Further in-depth studies focused on larger sample sizes are entailed to assess the relationships elaborately.


Subject(s)
COVID-19/diagnosis , COVID-19/epidemiology , Diabetes Mellitus/diagnosis , Diabetes Mellitus/epidemiology , Recovery of Function/physiology , Adolescent , Adult , Bangladesh/epidemiology , COVID-19/blood , Child , Child, Preschool , Cross-Sectional Studies , Diabetes Mellitus/blood , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Risk Factors , Treatment Outcome , Young Adult
8.
Respir Med Case Rep ; 31: 101265, 2020.
Article in English | MEDLINE | ID: covidwho-885430

ABSTRACT

BACKGROUND: Coronavirus disease 2019 (Covid-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It mainly affects the lungs and common symptoms are fever, cough and shortness of breath. Pneumothorax has been noted to complicate Covid-19 cases requiring hospital admission, however the exact incidence and risk factors are still unknown. DISCUSSION: We present a series of 3 cases of primary spontaneous pneumothorax with Covid-19 pneumonia. All cases in our series did not require positive pressure ventilation and none had any pre-existing lung disease. All were never smokers and had favourable outcomes despite having severe Covid-19 with a pneumothorax during the course of the disease. In our literature review we discuss several plausible mechanisms and risk factors resulting in a pneumothorax with Covid-19. CONCLUSION: Our cases are a reminder that an acute deterioration with hypoxia in a Covid-19 patient could indicate a pneumothorax. Pneumothorax is one of the reported complications in Covid-19 and clinician vigilance is required during assessment of patients, as both share the common symptom of breathlessness and therefore can mimic each other.

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