The impact of the Covid-19 pandemic on the diabetes antenatal clinic

Aims: The Covid-19 pandemic and subsequent restrictions impacted both health outcomes and clinical practice. We explored the impact on the diabetes antenatal clinic (DANC) attendance and outcomes. Method(s): Pre and during pandemic periods were defined as January 2019 to February 2020 and March 2020 to March 2022, respectively. DANC attendance, maternal and perinatal data were analysed. Adverse neonatal outcomes included stillbirth, neonatal hypoglycaemia, jaundice, shoulder dystocia and respiratory distress. Result(s): DANC attendance increased in the pandemic compared to the pre-pandemic period (297 (Interquartile range (IQR) 269-358) vs 196 (IQR 176-211) monthly, p < 0.001) with 36.7% (IQR 33-49) virtual appointments, representing a 34% overall increase. Body mass index (BMI) increased (29.7 kg/m2 (IQR 26.4-32.2) vs 31.4 kg/ m2 (IQR 26.5-34.2)) during the pandemic (p = 0.007), but maternal age and parity remained unchanged. There was no difference in gestational age at delivery;however, induction rates reduced from 58.5% to 37.5% (p = 0.0009) and spontaneous vaginal deliveries increased from 13.7% to 34.5% during the pandemic (p = 0.0004). Instrumental deliveries reduced from 21.5% to 11.3% (p = 0.03) but there was no change in number of caesarean sections including emergency ones. There was no difference in the rates of macrosomia or neonatal admissions. There was an overall reduction in adverse neonatal outcomes (37/102 (36.2%) vs 33/142 (23.2%) p = 0.03). Conclusion(s): Clinic numbers and maternal BMI increased during the pandemic. However, delivery and perinatal outcomes improved. Out data are reassuring and align with other studies indicating maternity outcomes did not deteriorate during the pandemic, possibly explained by improved care provision and organisation culture under crisis.

Assessment of Knowledge and Perception of Pharmacy Students Regarding Herbal Drugs: a Cross-Sectional Analysis from Pakistan

Herbal drug therapy is a beneficial and easily accessible modality of treatment.Pharmacist can play a pivotal role in rationalizing its use. This study was aimed to assess the knowledge and perception ofpharmacy students regarding herbal drugs.We conducted a cross-sectional survey using avalidated study instrument. The survey included pharmacy students from various universities across Pakistan.There were 342 (54.3%) 4(t)h yearand 288 (45.7%) 5(th) year students. We found statistically significant variations (p < 0.05) in the knowledge of male and female respondentsregarding;'the carminative use of Hyoscyamus niger' and 'effectiveness of Citrus aurantifolia in vomiting and chest burning'. Similarly, significant variations were found in perception of students regarding the 'inclusion of herbal drugs in every medical degree course', 'evidence-based herbal drugs use', and 'necessity of specific portion of herbal drugs in every pharmacy'. More than 40% of students agreed that it was fine to use Senna alexandrina during COVID-19 pandemic-era without evidence-based studies.The knowledge of pharmacy students about herbal drugs is not satisfactory and evidence-based drug use is to be improved to enhance their skills in the rational therapy of herbal drugs, which will be fruitful in managing the community's disease conditions.

The Metabolic Subphenotype: A Protective Factor in Ards Secondary to Sepsis or Pneumonia

INTRODUCTION: Poor metabolic health increases the risk of COVID-19 acute respiratory distress syndrome (ARDS), however, its relationship with non-COVID-19 ARDS remains controversial. ARDS is often considered a heterogeneous disease caused by sepsis, pneumonia, trauma, transfusions, and aspiration. In this study, we hypothesized that metabolic inflammation may contribute to differential outcomes in ARDS primarily caused by infection. METHOD(S): This was a secondary analysis of seven studies from the ARDS and Prevention and Early Treatment of Acute Lung Injury network trials within the Biologic Specimen and Data Repository Information Coordinating Center database. A metabolic subphenotype, defined by obesity, diabetes, and hypertension, was compared to a control population. The overall results showed lower adjusted mortality with this subphenotype. In this report, we performed stratified analyses to estimate effect modification by the metabolic subphenotype. We considered metabolic inflammation to reside along the causal pathway between infection and ARDS outcomes, and as such, stratified for primary ARDS etiology (e.g., sepsis or pneumonia as compared to other primary etiologies). The primary outcome was 28-day mortality. Secondary outcomes included 90-day mortality, ventilator free days, organ-failure free days, ICU free days, and length of hospital stay. RESULT(S): Among 4,288 ARDS trial participants, 3,205 (74.7%) had primary ARDS etiologies sepsis or pneumonia and 1,083 (25.3%) aspiration, trauma, transfusions, or other causes. of those with sepsis or pneumonia, 364 (11.4%) met criteria for the subphenotype versus 2,841 (88.6%) control. In the non-infectious cohort, 90 (8.3%) met subphenotype criteria versus 993 (91.7%) control. In adjusted analyses, the subphenotype stratified by sepsis and pneumonia was associated with lower 28- and 90-day mortality (adjusted odds ratio [aOR] 0.64 [95%CI, 0.48-0.84] and aOR 0.69 [95%CI, 0.53-0.89], respectively). However, in ARDS due to other causes, analyses were not significant (mortality at 28 days, aOR 1.18 [95% CI, 0.70-1.99] and 90 days, aOR 1.26 [95% CI, 0.77-2.06]). Secondary outcomes were not significantly different. CONCLUSION(S): A metabolic subphenotype of ARDS is associated with lower risk of mortality in non-COVID ARDS primarily caused by sepsis or pneumonia.

Severity of Acute Respiratory Distress Syndrome in Trial Participants with a Metabolic Subphenotype

INTRODUCTION: Data on obesity and diabetes in the acute respiratory distress syndrome (ARDS) are mixed. Metabolic Syndrome is a heterogeneous inflammatory state, and can be identified by metabolic risk factors. Previously, a metabolic sub-phenotype, characterized by obesity, diabetes, and hypertension, was associated with COVID-19 ARDS development and mortality. We showed this sub-phenotype was associated with lower mortality in non-COVID-19 ARDS, however, it is unclear how severity is impacted. METHOD(S): We performed a secondary analysis of individual patient-level data from seven randomized control trials in the ARDS and PETAL Networks from the Biologic Specimen and Data Repository Information Coordinating Center database. The preliminary mortality results from this study comparing the sub-phenotype to control was previously reported showing lower mortality for this sub-phenotype. Here, we studied each criterion in isolation, as an equally-weighted contributor, and also compared the outcome of severe ARDS, defined as PaO2/FiO2 ratio of less than 100 at enrollment, between cohorts. Multivariable regression models were performed. RESULT(S): Among 4,288 ARDS trial participants, 454 (10.6%) with a metabolic sub-phenotype were compared to 3,834 (89.4%) controls. Prevalence of metabolic disease was high with 2,831 (66 0%) participants carrying at least one metric of poor metabolic health (1,457-0/3 criteria, 1,398-1/3 criteria, 979-2/3 criteria, 454-3/3 criteria). The adjusted odds of dying before days 28 or 90 were progressively lower with each metabolic criterion added as compared to a nonmetabolic subgroup. Interestingly, each criterion in isolation was similarly associated with improved mortality without one particular risk factor contributing more than another, a finding supported by heterogeneity testing. Lastly, 212/454 (47%) of the metabolic sub-phenotype group met criteria for severe ARDS as compared with 1529/3834 (40%) control. The sub-phenotype was significantly associated with severe ARDS (adjusted OR 1.26 (95%CI 1.026 - 1.541). CONCLUSION(S): Obesity, diabetes, and hypertension are equal contributors to a metabolic sub-phenotype of non-COVID-19 ARDS that is significantly associated with lower mortality. However, this sub-phenotype was significantly associated with severe ARDS at enrollment.

TikTok as a Learning Tool for Archaeology

OverviewSince its launch, TikTok has become one of the world's most popular social media apps. Once primarily used by teenagers, this app is now used by people of all ages;this shift is largely attributable to the COVID-19 pandemic, when many people transitioned to engaging with others via social media instead of having in-person interactions. Now, anyone who has either the app or access to a web browser can view a plethora of videos, all 10 minutes and under, on any topic. Informational videos about archaeology may not be promoted on everyone's personalized home page & mdash;called the For You page (FYP)& mdash;but they are easily accessible through the search function. This review will discuss the impact TikTok has on the world of archaeology, with a focus on public engagement, museums, and especially teaching and learning. The social power of this app needs to be acknowledged. Archaeology can introduce the public to snapshots of daily life from the past, a task that fits well with the design of TikTok. This social platform can become a resource to create spaces to learn more, especially through interactive conversations such as in the comments section or response videos.

Assessment of Knowledge and Perception of Pharmacy Students Regarding Herbal Drugs: a Cross-Sectional Analysis from Pakistan

Herbal drug therapy is a beneficial and easily accessible modality of treatment.Pharmacist can play a pivotal role in rationalizing its use. This study was aimed to assess the knowledge and perception ofpharmacy students regarding herbal drugs.We conducted a cross-sectional survey using avalidated study instrument. The survey included pharmacy students from various universities across Pakistan.There were 342 (54.3%) 4th yearand 288 (45.7%) 5th year students. We found statistically significant variations (p < 0.05) in the knowledge of male and female respondentsregarding;'the carminative use of Hyoscyamus niger' and 'effectiveness of Citrus aurantifolia in vomiting and chest burning'. Similarly, significant variations were found in perception of students regarding the 'inclusion of herbal drugs in every medical degree course', 'evidence-based herbal drugs use', and 'necessity of specific portion of herbal drugs in every pharmacy'. More than 40% of students agreed that it was fine to use Senna alexandrina during COVID-19 pandemic-era without evidence-based studies.The knowledge of pharmacy students about herbal drugs is not satisfactory and evidence-based drug use is to be improved to enhance their skills in the rational therapy of herbal drugs, which will be fruitful in managing the community's disease conditions. Copyright © 2022, Colegio de Farmaceuticos de la Provincia de Buenos Aires. All rights reserved.

Foresight methodologies to unravel the indirect health economic impact of the COVID-19 pandemic on cancer care and management in Belgium studied in the HELICON project : Yasmine Khan

Background The COVID-19 pandemic had indirect effects on segments of the population affected with non-COVID-19 diseases e.g. through delayed care and management of cancer patients. Early diagnosis and appropriate treatment are key to improving patient outcomes and reducing societal and health care costs. Tio support policymakers to anticipate these trends a public health foresight study (PHFS) was done. Methods The PHFS follows a structured approach provided through a compact guide and is supervised by PHIRI team members. Its evolution is measured through a template gathering data on the study's contextual information, objective, main target groups, conceptual model, indicators, driving forces, time horizon, spatial unit, identifying uncertainties, scenario logics, scenario type, stakeholders, data, tools and instruments, projection methods, communication strategy/products, and the uptake of results and evaluation. Results Several foresight elements were identified. Contextual information on the resources and governance structure were elucidated. The objective was made clear by identifying the topic, general issue, and sub-issues of the initial study. A conceptual model was developed to analyse the interaction of the topic with other aspects that could influence it. The main driving forces, which are factors that influence the studied topic, were then determined through the DESTEP method. Stakeholders were identified and classified through the power-interest matrix. Conclusions Establishing a foresight study on the indirect impact of the COVID-19 pandemic on the care and management of cancer patients allows exploring potential and unsuspected issues that may affect society, health care systems, and patients. Those groups should not be considered individually but as an ecosystem continuously interacting, where a decision may affect everyone. This type of information may be of high relevance to policy- and decision-makers in their public health interventions.

Post COVID-19 Vaccine Uveitis: A Case Series

Purpose : With the recent emergence and worldwide distribution of COVID-19 vaccines, many side effects may be underreported and possibly unknown. Cases of vaccine-associated uveitis have been linked to almost all vaccines administered in the past, however, there is scarcity of literature providing insight into post COVID-19 vaccine associated uveitis / episcleritis. By documenting patients presenting with uveitis / episcleritis after the administration of mRNA Pfizer and Moderna vaccines, this case series significantly advances our current understanding of potential COVID-19 vaccine ocular complications. Methods : Patients with ocular symptoms consistent with uveitis / episcleritis within 15 days of the administration of the Pfizer or Moderna COVID-19 vaccine were included in this study. Ocular assessment included a Snellen best-corrected visual acuity (BCVA) converted to logMAR, intraocular pressure (IOP) with Goldmann Applanation Tonometry, pupil check, anterior and dilated posterior segment assessment with slit-lamp, and optical coherence tomography (OCT) imaging. Patients were anonymized and demographics including sex, race, age, and other necessary clinical data were recorded. Results : A total of 9 patients (6 female and 3 males) with a mean age of 42.9 (range, 19-83) were included. 7 patients received a Pfizer vaccine and 2 received a Moderna vaccine. 5 patients presented with symptoms after their first dose, 2 after their second dose, and 1 after both doses. The mean time of ocular symptoms post vaccine was 6.15 days (range, 1-14) and the mean BCVA was 0.657. Patients were diagnosed with bilateral anterior granulomatous uveitis (case 1), unilateral nongranulomatous anterior uveitis (case 2, 6-9), bilateral nongranulomatous anterior uveitis (case 3-4), and episcleritis (case 5). Case 1 and 9 have been highlighted and summarized in figure 1 and 2, respectively. Conclusions : The pathogenesis of vaccine induced uveitis is not properly understood, however, the outcomes of this case series aids in establishing a temporal association between the Pfizer and Moderna COVID-19 vaccines and the onset of uveitis / episcleritis. As the rate of COVID-19 vaccinations increase globally, it is imperative for physicians to be aware of the possible association and presentation of these ocular findings and diagnoses to effectively treat patients.

Fake News Detection of South African COVID-19 Related Tweets using Machine Learning

Social Media has grown in popularity in recent years comprising of billions of users who in turn exchange and communicate content at a volume and rate impractical to examine manually. Fake News are now being used on these platforms to manipulate and affect societies across the world as was the case in the 2016 United States of America (USA) elections and of recent during the 2019 coronavirus disease (COVID-19) pandemic. South Africa is not immune to the spread of Fake News, particularly, through Social Media platforms such as Twitter, Facebook and TikTok. It is, therefore, important to detect the presence of Fake News computationally in order assist the mitigation of its spread and prevent perceivable negative effects. This study addresses the issue by developing a Machine Learning (ML) model to analyze large amounts of data associated with Social Media. Curated annotated datasets from CONSTRAINT AAAI 2021;COVID-19 Rumour, FNIR and Zenodo's COVID-19 datasets;Google and Polifact Fact Checked websites;were utilized to develop the ML model. Specifically, the model was trained on 36254 data points and applied on a South African related COVID-19 Twitter dataset collected for cursory analysis. In total, 27 ML models were experimented with and the collected South African COVID-19 related Twitter dataset comprised of 976087 tweets from 8 November 2020 until 19 July 2021. The results detected 329107 tweets as being 'Fake' based on the LightGBM Classifier which was chosen as the most feasible model in terms of speed and a balanced accuracy score of 0.82. The proposed model is unique as it is trained on a larger combined dataset and supplements existing efforts to combat misinformation, disinformation and malinformation spread on Twitter. © 2022 IEEE.

OUTCOMES OF A CONSULTANT DELIVERED VS SPECIALIST REGISTRAR LED OOH ENDOSCOPY SERVICE FOR SUSPECTED AUGIB

Introduction Acute upper gastrointestinal bleeding (AUGIB) has an incidence between 84-172 per 100,000 people per year resulting in 50-70000 hospital admissions every year. Out -of-hours (OOH) endoscopy rotas for AUGIB are typically delivered by Consultant Gastroenterologists. Prior to the COVID-19 pandemic, the AUGIB OOH service was Specialty Registrar (SpR) led at Leeds Teaching Hospitals, and was felt to provide invaluable exposure and experience for SpRs in the endoscopic management of patients presenting with AUGIB. Following the start of the COVID pandemic, and subsequent redeployment of SpRs, the AUGIB OOH service has been a Consultant delivered one. The aim of this retrospective study was to compare the safety and efficacy of a SpR led OOH AUGIB service (2016 database) with a Consultant delivered service (2020-21 database) at the same trust. Methods We included adult patients (>16 years), presenting to LTHT between March and September 2016 with suspected AUGIB having an endoscopy procedure performed on a SpR led OOH rota and compared this with patients presenting with suspected AUGIB between September 2020 and March 2021 during which period the service was entirely consultant delivered. Baseline clinical, laboratory, admission Glasgow- Blatchford Score, demographic data, grade of endoscopist, place of endoscopy, findings of endoscopy and treatments applied were recorded. Primary outcome was 30-day mortality secondary to GI bleeding. Secondary outcomes included time to endoscopy and rebleed rate Results 177 patients from the 2016 database (62% male, median age 67, range 18-97) and 100 patients from the 2020-21 database (60% male, median age 63, range 18-96) were included in the study. 97.2% patients (2016) vs 93% (2020-21) had a GBS score ≥7. 30-day GI bleed related mortality was 2.89% (2016) vs 3% (2020-21) (p value 0.93). The median time to endoscopy was 16.3 hours (2016) vs 17.2 hours (2020-21). 8.9% (2016) vs 7% (2020-21) experienced a rebleed. Conclusions This study has shown that a Registrar led OOH AUGIB service has comparable outcomes to a Consultant delivered rota in important outcomes such as time to endoscopy and 30-day mortality. Where service configuration allows, a registrar led rota can aid in improving the standard of SpR training whilst also freeing up Consultants to undertake increased elective work and reduce the backlog created by the COVID-19 pandemic.

ATYPICAL PRESENTATION OF BIOT'S BREATHING IN A PATIENT WITH ARNOLD CHIARI MALFORMATION II WITH COMPLEX SLEEP APNEA/SLEEP HYPOVENTILATION/HYPOXEMIA NOT ON OPIOID AND WITH NO HISTORY OF MENINGITIS

Introduction: Sleep disordered breathing is very common in Arnold Chiari malformation but Biots's breathing has not been reported in these cases. Report of Cases: 3-year-old with history of Arnold Chiari II malformation with hydrocephalus (s/p VP shunt and surgical decompression), spina bifida myelomeningocele (s/p in utero repair), subglottic stenosis with prior tracheostomy and eventual decannulation presented for evaluation of sleep disordered breathing. Presenting symptoms included witnessed apneas, cyanosis, daytime sleepiness and frequent awakenings. Physical examination was largely unremarkable. Initial PSG demonstrated complex sleep apnea, with an AHI 20.6, REM AHI 57.8 per hour of sleep, ETCO2 peak of 69 cm H20 and an O2 saturation nadir of 34%, with sleep related hypoventilation/hypoxemia and Biot's breathing in the absence of opioid use and CNS infection. During titration study, Biot's breathing, complex apnea and sleep related hypoventilation/ hypoxemia responded well to BiPAP ST of IPAP 18 cm H20 and EPAP 14 cm H20 BUR of 12 and oxygen of 1 L/min. She later developed intolerance to BiPAP due to high pressures and was decreased to BIPAP 13/11 cm H2O. Later the patient discontinued the use of BIPAP due to intolerance and was switched to night time O2 at 3-4 L/min. Per the parents, the patient has been maintaining her oxygen saturation in the absence of BIPAP therapy with oxygen use. Due to COVID, patient was unable to follow up but will be scheduled for a repeat PSG in the near future. She followed with Neurosurgery for Arnold Chiari II and they recommended no surgical intervention at this time due to functional VP shunt. Conclusion: This is an atypical presentation of Biot's breathing in the absence of CNS infections and opioid use in a patient with Arnold Chiari malformation II. Patient has complex sleep apnea, initially well controlled with BiPAP ST, but developed BiPAP intolerance. She is on oxygen with good control of hypoxemia in the absence of BiPAP therapy.

Corporate Influence and the Role of Corporate Social Responsibility in Combating Trafficking in Persons—The India Story

Trafficking in persons (TIP) has become ‘an issue without borders’, where worldwide, 24.9 million people are prey to this act of human rights violation. India has been combatting this issue as a source, transit and destination country for both sex-based and non-sex-based exploitation. This is because, India, despite much development in the socio-economic sector in recent times, remains an emerging nation with dismal social indicators and porous international borders that nurtures unsafe migration. To make matters worse, the COVID-19 pandemic has further increased the vulnerability of certain sections of the people to trafficking. While the government has taken certain steps to tackle the issue of trafficking in persons, but the business sector, has remained oblivious to such pressing social matters. However, only recently, the Companies Act, 2013 was passed and the new statute incorporated Section 135 and Schedule VII within its purview that deals with mandated Corporate Social Responsibility (CSR) for certain large, stable companies. Section 135 lays down the requirement of the law for conducting CSR and Section VII lays down a list of broad areas in which the CSR resources need to be spent. Interestingly, much of the Schedule VII corresponds to the 17 broader goals of the Sustainable Development Goals (SDGs) as laid down by the United Nations in the year 2015, that became effective from 2016. This paper aims to document some of the causes of trafficking in persons in India as well as map the various ways in which the corporate sector can do its part in combatting such a social problem through its CSR interventions. © 2022, Springer Nature Singapore Pte Ltd.

Forecasting Demand for Personal Protective Equipment for Ontario Acute Care Hospitals During the First Wave of the COVID-19 Pandemic

Maintaining an adequate supply of personal protective equipment (PPE) is a global challenge for health systems during the COVID-19 pandemic. Estimating PPE demand is critical for planning clinical activities and managing supplies. We used health system modelling to forecast PPE demand in Ontario’s acute care sector during the COVID-19 pandemic. In particular, we estimated PPE demand by integrating PPE requirements for patient contacts into an existing health system model that forecasts near-term (up to 60 days) COVID-19 cases and their care trajectory in Ontario’s acute care system. We modeled two PPE strategies to care for confirmed and suspected COVID-19 patients: a base case scenario considering provincial PPE use recommendations, and a hospital-level case study using a PPE policy of universal masking and conservation strategies. Our base case estimate of PPE required to care for confirmed or suspected COVID-19 patients in Ontario’s acute care hospitals over a 60-day period was substantial—over 4.5 million each of surgical masks, face shields, and gowns would be required. Our hospital-level case study demonstrated that reuse of PPE reduces demand and offsets the effects of healthcare worker point of care assessments for N95 masks. Our work shows that health system modelling can estimate demand for PPE across pandemic trajectories and PPE use policies. The PPE volume required to safely care for COVID-19 patients is substantial and different PPE policies have marked effects on demand, which needs to be taken into account in procurement decisions to ensure adequate supply. © 2022, Springer Nature Switzerland AG.

Paradigm shift in the surgical training: The era of innovation, simulation and beyond

This is an era of transformation of surgical education and training. Modern methods of training are being introduced at a rapid pace and are being adopted in surgical practice not only to improve the outcomes and patient satisfaction, but also to provide an opportunity to develop a new well-structured training curriculum by integrating both traditional and modern approaches to teach and learn surgical skills. Various surgical simulators are in use as training aids and are constantly undergoing further refinement and development. To achieve a smooth transition in surgical training to modern methods, a structured programme has to be developed and validated to bridge the gaps in terms of safety, efficiency and ethics during the training process.

Practices and Attitude of Self-medication during COVID-19 Pandemic in University Students with Interventional Role of Pharmacist: a Regional Analysis

Self-medication (SM) is a global practice and associated with disease masking, adverse drug reaction, drug-drug interaction, and antibiotic resistance. In COVID-19 pandemic SM become a first choice because of strict lockdown in the country. The current study aims to assess the practice and attitude of SM among university students in the COVID-19 pandemic. A cross-sectional web-based study was conducted to evaluate the practice and attitude from March 2020 to June 2020. A total of 520 responses were analyzed using SPSS version 21.00 and a p-value of 0.05 was considered significant. The prevalence of SM was found to be 58% with a mean age of 21.8 +/- 1.9 who practice SM, while females and medical students reported a higher prevalence. The commonest symptoms were seen to be headache (36.56%), fever (34.68%), cough (31.56%), and flu (27.5%). However, majority of the participants use analgesic (55.96%), antibiotics (38.7%), and antipyretic (34.43%) as a symptomatic treatment. The reason for practicing SM was minor symptoms while fear of adverse effects for not practicing SM. Students had a positive attitude towards SM due to fear of COVID-19 and almost half participants practiced SM once-a-day (44.7%). The participants who visit pharmacy meet with pharmacist (42%) to get information of drug use, dose recommendation, duration of use, and concomitant use. In COVID-19 pandemic higher rate of practicing SM was reported. Government should make policies and arrange awareness programs for students regarding SM, and ensure availability of pharmacist at pharmacies to guide them accurately.

Environmental impact of COVID-19 led lockdown: A satellite data-based assessment of air quality in Indian megacities.

The strategies to contain the spread of COVID-19 pandemic, including restricted human movement and economic activities, have shown positive impacts on the environment. Present research analysed the effects of COVID-19 led lockdown on air quality with special reference to major pollutants, namely nitrogen dioxide (NO2), carbon monoxide (CO), sulphur dioxide (SO2) and aerosol optical depth (AOD). The assessment has been conducted for megacities of India (Delhi, Mumbai, Bengaluru, Chennai and Kolkata) for four months, that is, March and April in 2019 and 2020 using Sentinel 5P and MCD19A2 data. A decrease in concentrations of air pollutants, specifically NO2 and SO2, has been observed during the lockdown period in all the cities; whereas CO and AOD have exhibited discrete pattern of spatio-temporal variation. Four megacities except Kolkata have revealed a positive correlation between NO2 concentration and population density. The results conclude overall improvement in air quality during COVID-19 led lockdown. The current situation provides a unique opportunity to implement a structural economic change that could help us move towards a city with low emission economy. Realizing the achievable improvement of air quality, the study suggests further in-depth research on source attribution of individual pollutants to assess the prospect of emission reduction actions.

Consequences of COVID-19 on Imports and Exports of China with Forecasted Error and Future Trends

Purpose-The primary motivation behind this paper is to break down results of Coronavirus on imports and fares of China with anticipated mistake and future patterns. Design/methodology/approach-The paper depends on an Auto Backward Coordinated Moving Normal model with explicit suggestion of Box and Jenkins approach each year complete assessment of imports and fares of China as of the year 1950-2016 through supportive quantifiable programming R. It is found that ARIMA (0, 2, 2) and ARIMA (0, 2, 1) model appear to be to be sensible to measure full scale yearly imports and fares of China independently. Findings-After the control of COVID plague Chinese imports and fares will extend a tiny bit at a time and after the skirmish of three years get the figure (153609.6) in 2022, it will get the figure (153096.8) of 2019. After 2022, the advancement movement of Chinese imports and fares will be extended in a reliably close about a comparative rate before the attack of novel COVID. Research limitations/implications-The foremost restriction of the research work it is merely support on secondary data. Practical implications-The scientist can utilize these models for determining yearly imports and fares of China. Any way it ought to be refreshed opportunity to time with a consolidation of current information. It is most significant that the scientist ought to consistently follow the guideline of stinginess and attempt to fit straightforward model rather than model with enormous boundaries. Originality/value-The uniqueness of this article is that it features the select models for gauging import and fare of China. It was discovered that AIC based model determination methods provided ARIMA models with request (0, 2, 2) and request (0, 2, 1) for imports and fares of China separately were proper and helps in advancing money related incorporation with brings about higher monetary development and unfamiliar financial specialists.

Covid-19: Adaptation of a model to predict healthcare resource needs in valle del Cauca, Colombia

Background: Valle del Cauca is the region with the fourth-highest number of COVID-19 cases in Colombia (>50,000 on September 7, 2020). Due to the lack of anti-COVID-19 therapies, decision-makers require timely and accurate data to estimate the incidence of disease and the availability of hospital resources to contain the pandemic. Methods: We adapted an existing model to the local context to forecast COVID-19 incidence and hospital resource use assuming different scenarios: (1) the implementation of quarantine from September 1st to October 15th (average daily growth rate of 2%);(2-3) partial restrictions (at 4% and 8% growth rates);and (4) no restrictions, assuming a 10% growth rate. Previous scenarios with predictions from June to August were also presented. We estimated the number of new cases, diagnostic tests required, and the number of available hospital and intensive care unit (ICU) beds (with and without ventilators) for each scenario. Results: We estimated 67,700 cases by October 15th when assuming the implementation of a quarantine, 80,400 and 101,500 cases when assuming partial restrictions at 4% and 8% infection rates, respectively, and 208,500 with no restrictions. According to different scenarios, the estimated demand for reverse transcription-polymerase chain reaction tests ranged from 202,000 to 1,610,600 between September 1st and October 15th. The model predicted depletion of hospital and ICU beds by September 20th if all restrictions were to be lifted and the infection growth rate increased to 10%. Conclusion: Slowly lifting social distancing restrictions and reopening the economy is not expected to result in full resource depletion by October if the daily growth rate is maintained below 8%. Increasing the number of available beds provides a safeguard against slightly higher infection rates. Predictive models can be iteratively used to obtain nuanced predictions to aid decision-making.