ABSTRACT
The article considers the approaches to assessing the financial security of enterprises presented in the literature, determines the rsistance of the textile industry of Uzbekistan to the negative impact of the coronavirus pandemic on the basis of statistical data, and reveals a significant differentiation of textile industry enterprises in terms of financial stability. Based on data on small enterprises in the textile industry of Uzbekistan, a method for assessing the financial security of an enterprise in the post-pandemic period is proposed and tested, taking into account the complex influence of non-financial parameters of economic security and assessing the deviations of the economic situation at a given enterprise from the patterns emerging in the relevant segment of the economy. In this research an econometric model was developed to determine the factors affecting the chemical industry and express their interrelationship, based on the conducted econometric analysis, the directions of development in our country were determined. According to the authors, it is necessary to continue these directions in order to ensure the economic security of industry enterprises in the country. © 2022 ACM.
ABSTRACT
The rapidly spreading COVID-19 disease had already infected more than 190 countries. As a result of this scenario, nations everywhere monitored confirmed cases of infection, cures, and fatalities and made predictions about what the future would hold. In the event of a pandemic, governments had set limit rules for the spread of the virus and save lives. Multiple computer methods existed for forecasting epidemic time series. Deep learning was one of the most promising methods for time-series prediction. In this research, we propose a model for predicting the spread of COVID-19 in Egypt based on deep learning sequence-to-sequence regression, which makes use of data on the population mobility reports. The presented model utilized a new combined dataset from two different sources. The first source is Google population mobility reports, and the second source is the number of infected cases reported daily "world in data” website. The suggested model could predict new cases of COVID-19 infection within 3–7 days with the least amount of prediction error. The proposed model achieved 96.69% accuracy for 3 days of prediction. This study is noteworthy since it is one of the first trials to estimate the daily influx of new COVID-19 infections using population mobility data instead of daily infection rates. © 2023, The Author(s).
ABSTRACT
Aims: Since the onset of the COVID-19 pandemic, a significant rise in mental ill-health has been observed globally in young people, particularly amongst those in their final years of secondary school. The students' negative experiences coincide with a critical transitional period, which can subsequently disrupt milestones in social and educational development. This study aims to use innovative population-level data to map the impact of the pandemic on students entering higher education. Method(s): Tertiary education application data for Victorian students were obtained from the Victorian Tertiary Admissions Centre both pre-pandemic (2019/2020) and pandemic (2020/2021). Prevalence of mental health special considerations were compared between cohorts across geographical areas and applicant demographic subgroups. Relative risk regression models were used to understand the role of different risk factors. Result(s): The rate of mental health special considerations increased by 38% amongst all applications (pre-pandemic: 7.8%, n = 56 916;pandemic: 10.8%, n = 58 260). The highest increases were observed amongst students in areas with severe lockdown experiences and areas impacted by 2019/2020 black summer bushfires. The increases were higher amongst year 12 students and students with other preexisting risk factors (e.g., physical condition, learning disability). However, interestingly slightly higher increases were observed in areas with higher socioeconomic status, which is potentially related to inequality in mental health service access. Conclusion(s): As the consequences of mental health difficulties and academic disruption in youth can be long-lasting, it is critical to establish a mental health supportive framework both in and outside of higher education to facilitate young people's recovery from the pandemic.
ABSTRACT
Background: Although over 100 million pregnant women worldwide are at risk of infection with SARS-CoV-2, little data exists on the impact of COVID-19 and related treatments on maternal/neonatal health. Objective(s): (1) To quantify the prevalence of medication use in pregnancy to treat COVID-19, and (2) To quantify and compare the risk of adverse pregnancy/neonatal outcomes in those with and without COVID-19. Method(s): In the Canadian Mother-Child population-based cohort (CAMCCO), two sub-cohorts were identified using prospective data collection of medical services, prescription drugs, hospitalization archives data, and COVID-19 surveillance testing program (02/28/2020- 2021). The first cohort included all pregnant women during the study period regardless of pregnancy status (delivery, induced/planned or spontaneous abortion);this cohort was further stratified on COVID-19 status. The second cohort included all nonpregnant women (aged 15-45) with a positive COVID-19 test. COVID-19 in pregnant or nonpregnant women was assessed using COVID-19 test results or ICD-10CM code U07.1 from hospital data. COVID-19 severity was categorized based on hospital admission. Women were considered exposed to COVID-19 medications if they filled at least one prescription for a medicine included in the WHO list in the 30 days pre- or 30 days post-COVID-19 positive test/diagnosis. Considering potential confounders, association between COVID-19 during pregnancy, treated vs not, and perinatal outcomes were quantified using log-binomial regression models. Result(s): 150,345 pregnant women (3,464 (2.3%) had COVID-19), and 112,073 nonpregnant women with COVID-19 diagnoses were included. Pregnant women with COVID-19 were more likely to have severe infections compared to nonpregnant women with COVID-19 (11.4% vs 1.6%, p<0.001). The most frequent medications used in pregnancy to treat COVID-19 were antibacterials (13.96%), psychoanaleptics (7.35%), and medicines for obstructive airway disease (3.20%). In pregnancy COVID-19 was associated with spontaneous abortions (adjRR 1.76, 95%CI 1.37, 2.25), gestational diabetes (adjRR 1.52, 95%CI 1.18, 1.97), prematurity (adjRR 1.30, 95%CI 1.01, 1.67), NICU admissions (adjRR 1.32, 95%CI 1.10, 1.59);COVID-19 severity was increasing these risks but exposures to COVID-19 medications reduced all risks. Conclusion(s): COVID-19 severity was higher in pregnancy. Antibacterials, psychoanaleptics, and medicines for obstructive airway disease were the most used overall. COVID-19 was associated with adverse outcomes for mothers and newborns.
ABSTRACT
This paper investigates whether global uncertainty predicts economic growth rates using a global sample of 136 countries. We use the panel regression model and find strong evidence that global uncertainty negatively predicts the economic growth rate. Further, the negative impact of global uncertainty on economic growth rates is amplified during pandemic periods versus non-pandemic periods. Our main findings hold after a range of robustness tests.
ABSTRACT
Background. After the first wave of the new SARS-CoV-2 coronavirus infection, the researchers focused on identifying potential short-and long-term complications of COVID-19, especially in high-risk patients, after prolonged hospitalization and intensive care. Objective. To study the outcomes, adverse effects of severe COVID-19 and their predictors 90 days after hospital discharge in elderly patients with asthma. Material and methods. The study included elderly patients (101 subjects, 42 males and 59 females;median age 74 (67;79) years) with asthma, discharged from the hospital after treatment of severe COVID-19. They were followed up for 90 days after discharge. In the hospital, COVID-19 was confirmed by laboratory tests (polymerase chain reaction method) and/or clinically and radiologically. All patients had a documented history of asthma according to GINA 2020 criteria. Results and discussion. During the 90-day post-hospital follow-up, 86 (85%) patients survived, and 15 (15%) died after discharge. Deaths were reported within 1 to 4 weeks after discharge: 6 subjects died during re-hospitalization, 6 at home, and 3 in a rehabilitation center. The multivariate regression analysis model, adjusted for all statistically significant indicators, and the ROC analysis showed the most significant predictors of 90-day post-hospital mortality and their threshold values. They include the Charlson comorbidity index >=4 points, lung damage according to computed tomography >=30%, the absolute number of eosinophils <=100 cells/muL, and concomitant diabetes mellitus. The analysis showed that 90-day post-hospital mortality depends on combinations of identified risk factors;a combination of two, three, and especially four risk factors statistically significantly is associated with patients' lower average survival time. Conclusion. The key risk factors for 90-day post-hospital mortality in elderly patients with asthma after severe COVID-19 include the Charlson comorbidity index, lung damage >=30% according to computed tomography, the absolute number of eosinophils <=100 cells/muL, and concomitant diabetes mellitus. The 90-day post-hospital survival rate is correlated with the number of risk factors identified in patients. The effect of asthma severity on 90-day post-hospital mortality in elderly patients was not observed.Copyright © 2023, Media Sphera Publishing Group. All rights reserved.
ABSTRACT
Background/Aims Rheumatic and musculoskeletal diseases (RMDs) are some of the most common indications for prescribed opioids. It is unclear how opioid prescribing has changed in the UK for RMDs, especially during the COVID-19 pandemic with limited healthcare access and cancelled elective-surgical interventions, which could impact prescribing in either direction. We aimed to investigate trends in opioid prescribing in RMDs and assess the impact of the pandemic in the UK. Methods Adult patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), axial spondyloarthritis (AxSpA), systemic lupus erythematosus (SLE), osteoarthritis (OA) and fibromyalgia with opioid prescriptions between 01/Jan/2006-31/Aug/2021 without prior cancer in the UK Clinical Practice Research Datalink (CPRD) were included. We calculated ageand gender-standardised yearly rates of people with opioid prescriptions between 2006-2021, and identified change points in trends by checking whether the rate of change of standardised rates crossed zero. For people with opioid prescriptions, monthly measures of mean morphine milligram equivalents (MME)/day were calculated between 2006-2021. To assess the impact of the pandemic, we fitted regression models to the monthly number of people with opioid prescriptions between Jan/2015-Aug/2021. The time coefficient reflects the trend pre-pandemic and the interaction term coefficient represents the change in the trend during the pandemic. Results We included 1,313,519 patients: 36,932 with RA, 12,649 with PsA, 6,811 with AxSpA, 6,423 with SLE, 1,255,999 with OA, and 66,944 with fibromyalgia. People with opioid prescriptions increased from 2006 to 2018 for OA, to 2019 for RA, AxSpA and SLE, to 2020 for PsA, and to 2021 for fibromyalgia, and all plateaued/decreased afterwards. OA patients on opioids increased from 466.8/10,000 persons in 2006 to a peak of 703.0 in 2018, followed by a decline to 575.3 in 2021. From 2006 to 2021, there was a 4.5-fold increase in fibromyalgia opioid users (17.7 vs.78.5/10,000 persons). In this period, MME/day increased for all RMDs, with the highest for fibromyalgia (>=35). During COVID-19 lockdowns, RA, PsA and fibromyalgia showed significant changes in the trend of people with opioid prescriptions. With a decreasing trend for RA (-0.001,95%CI=-0.002,-0.001) and a decreasing-to-flat curve for PsA (0.0010,95%CI=0.0006,0.0015) prepandemic until Feb/2020, the trends changed by -0.005 (95%CI=-0.008,-0.002) for RA and -0.003 (95%CI=-0.006,-0.0003) for PsA, leading to steeper decreasing trends during the pandemic (Mar/2020-Aug/2021). Fibromyalgia, conversely, had an increasing trend (0.009,95%CI=0.008,0.009) pre-pandemic, and this trend started decreasing by -0.009 (95%CI=-0.011,-0.006) during the pandemic. Conclusion The plateauing/decreasing trend of people with opioid prescriptions in RMDs after 2018 may reflect the efforts to tackle the rising opioid prescribing in UK primary care. Of all RMDs, fibromyalgia patients had the highest MME/day throughout the study period. COVID-19 lockdowns contribute to fewer people on opioids for most RMDs, reassuring there was no sudden increase in opioid prescribing during the pandemic.
ABSTRACT
Background/Aims Post COVID-19 syndrome (PCS) is an emerging cause of morbidity and poor quality of life in COVID-19 survivors. We aimed to assess the prevalence, risk factors, outcomes, and association with disease flares of PCS in patients with autoimmune rheumatic diseases (AIRDs) and non-rheumatic autoimmune diseases (nrAIDs), both vulnerable groups understudied in the current literature using data from the 2nd COVID-19 Vaccination in Autoimmune Diseases (COVAD) global multicentre patient self-reported e-survey. Methods The survey was circulated from February to July 2022 by the international COVAD Study Group (157 collaborators from 106 countries), and demographics, comorbidities, AIRD/nrAID status, COVID-19 history, vaccination details, and PROMIS physical and mental function were recorded. PCS was defined as symptom resolution time >90 days following acute COVID-19. Predictors of PCS were analysed using regression models for the different groups. Results 7666 total respondents completed the survey. Of these, 2650 respondents with complete responses had positive COVID-19 infection, and 1677 (45.0% AIRDs, 12.5% nrAIDs, 42.5% HCs) completed the survey >90 days post acute COVID-19. Of these, 136 (8.1%) had PCS. Prevalence of PCS was higher in AIRDs (10.8%) than healthy controls HCs (5.3%) (OR: 2.1;95%CI: 1.4-3.1, p=0.002). Across the entire cohort, a higher risk of PCS was seen in women (OR: 2.9;95%CI: 1.1-7.7, p=0.037), patients with long duration of AIRDs/ nrAIDs (OR 1.01;95%CI: 1.0-1.02, p=0.016), those with comorbidities (OR: 2.8;95%CI: 1.4-5.7, p=0.005), and patients requiring oxygen supplementation for severe acute COVID-19 (OR: 3.8;95%CI: 1.1- 13.6, p=0.039). Among patients with AIRDs, comorbidities (OR 2.0;95%CI: 1.08-3.6, p=0.026), and advanced treatment (OR: 1.9;95%CI: 1.08-3.3, p=0.024), or intensive care (OR: 3.8;95%CI: 1.01-14.4, p=0.047) for severe COVID-19 were risk factors for PCS. Notably, patients who developed PCS had poorer PROMIS global physical [15 (12-17) vs 12 (9-15)] and mental health [14 (11-16) vs 11 (8-14)] scores than those without PCS. Conclusion Individuals with AIRDs have a greater risk of PCS than HCs. Associated comorbid conditions, and advanced treatment or intensive care unit admission for severe COVID-19 confer a higher risk of PCS. It is imperative to identify risk factors for PCS for immediate multidisciplinary management in anticipation of poor physical and mental health.
ABSTRACT
The world has suffered a lot from COVID-19 and is still on the verge of a new outbreak. The infected regions of coronavirus have been classified into four categories: SIRD model, (1) suspected, (2) infected, (3) recovered, and (4) deaths, where the COVID-19 transmission is evaluated using a stochastic model. A study in Pakistan modeled COVID-19 data using stochastic models like PRM and NBR. The findings were evaluated based on these models, as the country faces its third wave of the virus. Our study predicts COVID-19 casualties in Pakistan using a count data model. We've used a Poisson process, SIRD-type framework, and a stochastic model to find the solution. We took data from NCOC (National Command and Operation Center) website to choose the best prediction model based on all provinces of Pakistan, On the values of log L and AIC criteria. The best model among PRM and NBR is NBR because when over-dispersion happens; NBR is the best model for modelling the total suspected, infected, and recovered COVID-19 occurrences in Pakistan as it has the maximum log L and smallest AIC of the other count regression model. It was also observed that the active and critical cases positively and significantly affect COVID-19-related deaths in Pakistan using the NBR model.
Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , SARS-CoV-2 , Pakistan/epidemiology , Disease OutbreaksABSTRACT
The paper investigates the co-movement of COVID-19 pandemic and performance of stock markets of four emerging economies. The Quantile-on-Quantile regression model was applied to daily share prices of stock markets from March 13, 2020 to November 30, 2021 in these economies. The results indicate varied relationships across various quantiles of COVID-19 cases and share prices. Whilst both positive and negative relationships are established at different quantiles of share prices for Brazil and Kenya, negative co-movements are recorded for India and South Africa for all quantiles of share prices. The varying dependence between COVID-19 and stock markets provide critical insights to policy makers.
ABSTRACT
Background: Immunocompromised persons are disproportionately affected by severe SARS-CoV-2 infection, but immune compromise is heterogenous, which may impact viral dynamics. We hypothesized that higher degrees of compromised immunity are associated with higher viral shedding and slower viral clearance in the absence of COVID-19 therapeutics. Method(s): Participants enrolled in ACTIV-2/A5401, a platform trial for COVID-19 therapeutics in non-hospitalized adults within 10 days of symptom onset, received either an active treatment or placebo between 8/2020 and 7/2021. Participants were categorized based on the extent of immunosuppression into none, mild, moderate and severe categories at enrollment (day 0). Longitudinal anterior nasal (AN) and plasma SARS-CoV-2 levels were measured with a quantitative PCR assay. Regression models assessed associations between immunocompromise severity and viral levels (VL) at day 0, and longitudinally among those on placebo with quantifiable RNA at day 0. Multivariate analyses adjusted for demographics and symptom duration and vaccination status at day 0. Result(s): Immunocompromised (mild 383, moderate 159, severe 35) and immunocompetent (1956) participants had comparable symptom durations at day 0 (median 6 days) and most were unvaccinated (~95%). AN VL at day 0 was higher in the moderate/severe group compared to the immunocompetent group (adjusted difference in means: 0.47 log10 copies/mL, 95% CI 0.12, 0.83). While AN VL decayed at similar rates among all groups from day 0 to 3, there was a trend towards higher cumulative AN VLs across the 28-day follow-up in the moderate/severe group compared to immunocompetent group (adjusted fold difference in VL AUC 1.63, 95%CI 0.95, 2.77). The mild group showed no differences in day 0 VL or AUC compared to the immunocompetent group. The frequency of detectable plasma SARS-CoV-2 RNA was similar at day 0 across all groups (overall 21%), but there appeared to be a higher proportion of immunocompromised participants with detectable plasma viral RNA at day 7 (moderate/severe 2/23 [9%], mild 5/44 [11%]) compared to the immunocompetent group (8/282, 3%). Conclusion(s): Before emergence of Omicron and widespread vaccination, moderate/severe immunocompromised status was associated with higher nasal viral levels at study enrollment and showed a trend towards higher cumulative AN viral load, and all immunocompromised groups appeared to have more persistent plasma viremia during follow-up.
ABSTRACT
Purpose of Study: Ethnic disparities are associated with increased risk for severe disease in pediatric patients with COVID-19. Identifying the underlying social determinants of health are necessary to lead to improved health care utilization and mitigation strategies. Methods Used: This is an observational cohort study of children with COVID-19 in Colorado (the CCC study) from March 15 2020-October 31 2020. Pediatric patients between 2-20 years of age with positive SARS-CoV-2 PCR were included. Multivariable logistical regression models were fitted to identify demographic, socioeconomic, and comorbid health conditions as predictors of severe COVID-19 disease, as defined by hospital admission and need for respiratory support. Summary of Results: We identified 1572 pediatric patients with COVID-19 (45% Hispanic, 54% Medicaid or uninsured, 16% non-English language, and 20% obese). In univariable analyses, Hispanic ethnicity was associated with severe outcomes, including hospital admission (OR 2.4, CI: 1.57, 3.80, p<0.01) and respiratory support (OR 2.4, CI: 1.38, 4.14, p<0.01). Patients who identified as Hispanic or Latino had significantly increased rates of obesity (28% vs. 14%, p<0.01), preferred non-English language (31% vs. 3%, p<0.01), and had Medicaid or no insurance (79% vs. 33%, p<0.01) when compared to non-Hispanic or Latino children. After adjusting for covariables, ethnicity was no longer associated with hospital admission (OR 0.9, CI: 0.53, 1.63, p=0.79) or respiratory support (OR 0.6, CI: 0.29, 1.21, p=0.15). Obesity (OR 1.9, CI: 1.15, 3.08, p=0.01), non-English language (OR 2.4, CI: 1.35, 4.23, p<0.01), and Medicaid insurance (OR 2.0, CI: 1.10, 3.71, p=0.02) were identified as independent risk factors for severe disease. Conclusion(s): Severe COVID-19 disease observed in Hispanic or Latino patients early in the pandemic appears to be secondary to underlying comorbid conditions, such as obesity, and socioeconomic disadvantages that may have influenced access to care, such as language and insurance status. Pediatric healthcare providers and public health officials should use this knowledge to tailor resource allocation to better target this underserved patient population.
ABSTRACT
Background: Non-pharmaceutical interventions (NPIs) and vaccines have been used by many countries to manage the dynamics of the COVID-19 pandemic. Despite numerous studies, considerable uncertainty remains about the effects of these public health interventions due to data quality issues and methodological challenges to estimating effects. However, producing accurate and precise estimates of the effects of these interventions is of utmost importance for the preparedness of any new epidemic. Method(s): We developed a population-based mechanistic compartmental model that includes the effect of NPIs on SARS-CoV-2 transmission and the effect of vaccination on the transmission and the rate of hospitalization. Our statistical approach estimated all parameters in one step, thus accurately propagating uncertainty, and representing spatial heterogeneity. We fitted the model to all available epidemiological data (hospital admissions and occupancy, cases, and deaths) from March 2020 to October 2021 in France. Hence, we estimated the time-varying transmission rate, and derived the effect of NPIs through an integrated regression model. We simulated counterfactual scenarios of the interplay of NPIs and vaccine availability and rollout with the same model. Result(s): We found that the first lockdown reduced transmission by 84% (95% CI [83-85]) and was more effective than the second and third lockdowns (reduction of 75% [72-77] and 9% [6-13], respectively). A 6pm curfew was more effective than an 8 pm curfew (transmission reduction of 69% [67-70] vs. 50% [48-53]). School closures had a smaller effect on transmission (15% [12-19]). By the end of the study period, the protection conferred by vaccines against hospitalization and against infection, considering viral variants and population vaccine coverage, ranged between 69-92% and 29-40%, respectively. In a scenario without vaccines, we predicted 209% (95% PI [34-520]) more deaths and 346% [101-798] more hospitalizations throughout the study period. Conversely, if an effective vaccine had been available after 100 days, 65% [36-80] deaths and 72% [45-84] hospitalizations could have been averted. Conclusion(s): Our results provide reliable effect and uncertainty estimates of each NPI and demonstrate that NPIs and vaccination synergistically reduced COVID-19 transmission, hospitalization, and deaths. This emphasizes the importance of stringent NPIs and a high vaccination rate to prevent further epidemic resurgences and control other emerging respiratory infectious diseases.
ABSTRACT
Background: Whether early antiviral therapy reduces the risk of Long COVID is not known. The combination SARS-CoV-2 monoclonal antibodies amubarvimab+romlusevimab (A+R) were highly effective in reducing 28-day all-cause hospitalization/death among high-risk adults with mild-to-moderate COVID-19 in the randomized, placebo-controlled ACTIV-2/A5401 trial. We assessed the impact of A+R on late outcomes including Long COVID in ACTIV-2. Method(s): A long-term (LT) symptom diary and 2 health-related quality of life questionnaires (EQ-5D-5L and SF-36v2) were completed at week 36. The primary analysis compared the proportion of participants with the composite outcome of self-reported Long COVID (having any COVID-19 symptoms present on a global assessment question in LT diary) at week 36, or hospitalization or death by week 36 between A+R and placebo using regression models with inverse probability weighting to account for incomplete outcome data;supplemental analysis compared the proportion with Long COVID among those alive. Other analyses were restricted to observed data only. Result(s): 807 were randomized and received A+R (n=405) or placebo (n=402) from Jan-July 2021. At entry, median age was 49 years, 51% were female, >99% cis-gender, 17% Black/African American, 50% Hispanic/Latino, and 9% previously received COVID vaccination. 70 (17%) on A+R and 93 (23%) on placebo met the primary outcome;113 (14%) had incomplete data for determining the outcome (Figure 1). Accounting for incomplete data, weighted Risk Ratio [wRR]=0.74;95% CI: 0.56, 0.97;p=0.03. The difference was driven by fewer hospitalizations/deaths in the A+R arm (5%) than placebo arm (15%), particularly by day 28. Excluding 12 participants who died by week 36, frequency of Long COVID was similar in the arms, 16% for A+R and 14% for placebo (wRR=1.09;95%CI: 0.75, 1.58;p=0.64). There were no differences in the proportions reporting return to pre-COVID health (global assessment) or individual symptoms, or in number of symptoms reported or distribution of worst symptom severity. RRs favored the A+R arm on several EQ-5D-5L domains, but none met statistical significance. No differences were observed on SF-36v2 assessments. Conclusion(s): While A+R was highly effective in preventing all-cause hospitalizations and deaths in high-risk outpatients with mild-to-moderate COVID-19, there was no meaningful effect of treatment on measures of Long COVID at 36 weeks. Additional interventions are needed for Long COVID prevention. (Figure Presented).
ABSTRACT
Background: Pregnancy is both a risk factor for P. falciparum infection and development of severe malaria and, in Uganda, its control relies heavily in the administration of intermittent preventive treatment with sulfadoxinepyrimethamine (SP-IPTp) during antenatal care visits (ANC). COVID-19 pandemic severely impacted health systems globally. This study aims to assess trends in delivering malaria in pregnancy related healthcare services before and during Covid-19 in thirty health facilities in Northern Uganda. Method(s): Interrupted time series study comparing two periods: I) pre- Covid-19 (January 2018 to February 2020) and II) Covid-19 (from March 2020 to December 2021) period. Data were sourced from the District Health Information Management System II (DHIMS2) routinely collected indicators. Comparisons between the two periods were computed with a jointpoint regression model and Annual Average Percentage Changes (AAPC) were calculated. Result(s): The study involved data collected by 30 health facilities, 30 health facilities in Northern Uganda - including one hospital - with a catchment area of 506,276 inhabitants and an estimated number of pregnancies ranging from 21,440 to 23,315. Covid cumulative cases and deaths for Oyam districs are reported in Figure 1. As shown in Figure 2, during COVID period we found a significant reduction in the number of women accessing to at least 4 antenatal care (ANC) visits and taking at least three doses of intermittent preventive treatment (IPT) with sulfadoxine-pyrimethamine. The total number of pregnant women receiving Artemether-Lumefantrine for nonsevere malaria or being hospitalized for severe malaria, along with the total number of institutional deliveries and stillbirths followed kept following the trend recorded prior to the pandemic. Conclusion(s): The present study shows that, despite the international call for prioritization of maternal and reproductive health service delivery during COVID-19 pandemic, in Uganda, the essential care for malaria in pregnancy have been disrupted. This is concerning, as the failure to increase the delivery of SP-IPTp may impact malaria-related mortality.
ABSTRACT
Background: Coronavirus Disease 2019 (COVID-19) vaccine antigen dosage may affect protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but direct evidence to quantify this effect is lacking. Method(s): A matched, retrospective, cohort study that emulated a randomized control trial was conducted in Qatar between February 3, 2022 and November 8, 2022, to provide a head-to-head, controlled comparison of protection induced by two antigen dosages of the BNT162b2 vaccine. The study compared incidence of omicron infection in the national cohort of adolescents 12 years of age who received the two-dose primary-series of the 30-mug BNT162b2 vaccine to that in the national cohort of adolescents 11 years of age who received the two-dose primary-series of the pediatric 10-mug BNT162b2 vaccine. Associations were estimated using Cox proportional-hazard regression models. Result(s): Among adolescents with no record of prior infection, cumulative incidence of infection was 6.0% (95% CI: 4.9-7.3%) for the 30-mug cohort and 7.2% (95% CI: 6.1-8.5%) for the 10-mug cohort, 210 days after the start of follow-up. Incidence during follow-up was dominated by omicron subvariants including, consecutively, BA.1/BA.2, BA.4/BA.5, BA.2.75*, and XBB. The adjusted hazard ratio comparing incidence of infection in the 30-mug cohort to the 10-mug cohort was 0.77 (95% CI: 0.60-0.98). Corresponding relative effectiveness was 23.4% (95% CI: 1.6-40.4%). Relative effectiveness was -3.3% (95% CI: -68.0- 27.5%) among adolescents with a record of prior infection. Conclusion(s): Three-fold higher BNT162b2 dosage was associated with ~25% higher protection against infection in infection-naive adolescents of similar age. These findings may inform design of future COVID-19 vaccines and boosters for persons of different age groups.
ABSTRACT
Background: PWH are disproportionally affected by mpox and at high risk for severe complications. The recent mpox outbreak response included increasing awareness, encouraging behavioral changes and pre- and post-exposure vaccination. We assessed knowledge and perceptions of mpox, adoption of preventive behaviors, and attitudes towards vaccination among PWH in Washington, DC. Method(s): Data from a cross-sectional mpox survey were collected between August and December 2022 from PWH enrolled in a longitudinal HIV cohort, the DC Cohort. We conducted uni- and bivariable analyses comparing participants by vaccination status (vaccinated, plan to vaccinate, no plan to vaccinate) and by HIV risk group (MSM vs. non-MSM). We conducted multinomial regression to identify factors associated with vaccine acceptance. Result(s): Among 178 PWH completing the survey (median age 55;71% male, 81% non-Hispanic Black, 37% MSM), 162 (91%) had heard of mpox. Among 159 PWH who had heard of mpox and answered vaccination questions, 21% (n=33) were vaccinated, 43% (n=69) planned to vaccinate and 36% (n=57) did not plan to vaccinate. Comparing the 3 groups, significant differences were observed by age, gender, education, income, HIV risk group, and level of worry about mpox (all p< 0.01). Viral suppression, prior COVID and influenza vaccination, access to STI services, and STI diagnoses in the last year were not associated with vaccine status. Behaviorally, a higher proportion of vaccinated participants reported limiting their number of sexual partners (p< 0.001) and using more preventive behaviors (e.g., limiting gatherings, increased condom use, avoiding skin-to-skin contact;p=0.034) in response to mpox. A higher proportion of MSM reported limiting their number of sexual partners compared to non-MSM (33% vs 7%, p< 0.0001) and were more likely to be vaccinated or plan to vaccinate vs non-MSM (p< 0.001). In adjusted multinomial regression models comparing vaccinated PWH and those planning to vaccinate to those not planning to vaccinate, age (p= 0.0231) and HIV risk factor/gender (p< 0.0001) were significantly associated with vaccination status with younger PWH and MSM more likely to vaccinate (Figure). Conclusion(s): High levels of mpox awareness were observed among this cohort of PWH in Washington, DC with more MSM employing risk reduction behaviors and vaccination as mpox prevention strategies. Ensuring that all PWH, regardless of gender, sexual orientation, or age, understand the risks of mpox may improve vaccination uptake.
ABSTRACT
Background: Metformin has in vitro activity against SARS-CoV-2. In a published phase 3, quadruple-blinded, placebo-controlled randomized trial of outpatient COVID-19 therapy, metformin resulted in a 42% reduction in ER visits/hospitalizations/deaths by day 14, 58% reduction in hospitalizations/ death by day 28, and 42% reduction in Long Covid through 10 months. This analysis presents the results of viral load sampling performed during that clinical trial. Method(s): Covid-Out trial (NCT04510194) enrolled adults aged 30 to 85 within 3 days of a documented SARS-CoV-2 infection and < 7 days after symptom onset. The trial randomized 1323 participants to metformin (1000mg/day days 2-5;1500mg/day days 6 to 14), ivermectin, fluvoxamine, and/or exact-matching placebo in a 2x3 factorial trial design. Nasal swabs for viral load were an optional component, self-collected from the anterior nares on day 1, 5, and 10. Viral loads were measured via RT-qPCR using N1 and N2 targets in the SARSCoV- 2 nucleocapsid protein, with relative Ct values converted to absolute copy number via calibration to droplet digital PCR. A linear Tobit regression model was used to assess change over time while accounting for left censoring due to the viral load limit of detection. Results were adjusted for other treatment allocations within the factorial design, vaccination status, and baseline viral load. Repeated measures were accounted for using clustered standard errors within participants. Result(s): Samples were available from n = 945, 871, and 775 participants on days 1, 5, and 10, respectively. The mean change from baseline to followup was -0.64 log10 copies/mL (95%CI, -1.16 to -0.13) for metformin versus placebo, which equates to a 4.4-fold greater decrease. The mean change in SARS-CoV-2 from baseline to day 5 was -0.48 log10 copies/mL, and was -0.81 log10 copies/mL from baseline to day 10. The anti-viral effect increased with increased metformin dosing days 6-14. The antiviral effect was larger in those unvaccinated (mean -0.95 log copies/mL) than vaccinated (mean -0.39 log copies/mL). There was no change in viral load vs. placebo for ivermectin or fluvoxamine. Conclusion(s): Metformin lowered SARS-CoV-2 viral load in this quadrupleblinded, randomized clinical trial. The temporal relationship to dose titration suggests a dose-dependent effect. The magnitude of antiviral effect was similar to nirmatrelvir at day 5, greater than nirmatrelvir at day 10. Metformin is safe, widely available, and has few contraindications.
ABSTRACT
Background. After the first wave of the new SARS-CoV-2 coronavirus infection, the researchers focused on identifying potential short-and long-term complications of COVID-19, especially in high-risk patients, after prolonged hospitalization and intensive care. Objective. To study the outcomes, adverse effects of severe COVID-19 and their predictors 90 days after hospital discharge in elderly patients with asthma. Material and methods. The study included elderly patients (101 subjects, 42 males and 59 females;median age 74 (67;79) years) with asthma, discharged from the hospital after treatment of severe COVID-19. They were followed up for 90 days after discharge. In the hospital, COVID-19 was confirmed by laboratory tests (polymerase chain reaction method) and/or clinically and radiologically. All patients had a documented history of asthma according to GINA 2020 criteria. Results and discussion. During the 90-day post-hospital follow-up, 86 (85%) patients survived, and 15 (15%) died after discharge. Deaths were reported within 1 to 4 weeks after discharge: 6 subjects died during re-hospitalization, 6 at home, and 3 in a rehabilitation center. The multivariate regression analysis model, adjusted for all statistically significant indicators, and the ROC analysis showed the most significant predictors of 90-day post-hospital mortality and their threshold values. They include the Charlson comorbidity index >=4 points, lung damage according to computed tomography >=30%, the absolute number of eosinophils <=100 cells/muL, and concomitant diabetes mellitus. The analysis showed that 90-day post-hospital mortality depends on combinations of identified risk factors;a combination of two, three, and especially four risk factors statistically significantly is associated with patients' lower average survival time. Conclusion. The key risk factors for 90-day post-hospital mortality in elderly patients with asthma after severe COVID-19 include the Charlson comorbidity index, lung damage >=30% according to computed tomography, the absolute number of eosinophils <=100 cells/muL, and concomitant diabetes mellitus. The 90-day post-hospital survival rate is correlated with the number of risk factors identified in patients. The effect of asthma severity on 90-day post-hospital mortality in elderly patients was not observed.Copyright © 2023, Media Sphera Publishing Group. All rights reserved.
ABSTRACT
Background: In the third year of the coronavirus disease 2019 (COVID-19) pandemic, long-term post-COVID syndrome (PCS) following severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infections poses the significant challenge for patients and health systems globally. Whilst COVID-19 vaccinations prior to SARS-CoV-2 infection reduce the risk of PCS, the role of therapeutic vaccination in PCS recovery remains controversial. We present a 15 months longitudinal, prospective observational cohort study to examine long-term clinical courses, PCS recovery with and without vaccination as well as humoral immune responses in initially unvaccinated PCS patients. Method(s): A total of 227 COVID-19 convalescents of our initial mild COVID-19 outpatient cohort (N=958) from which longitudinal data was available were included in this study. PCS was defined according to the WHO definition. 76.7% (174/227) of individuals received at least one vaccination between 10 and 15 months after first SARS-CoV-2 infection. Receptor binding domain (RBD)- specific SARS-CoV-2 immunoglobulin G (IgG) and distinct symptom phenotypes (P) were longitudinally assessed for 15 months. Using binomial regression models, odds ratios (OR) with 95% confidence interval (95%CI) of descriptive, longitudinal variables associated with long-term PCS were calculated. Result(s): 35.8% (82/227) and 31.3% (71/227) of patients had PCS at months 10 and 15 (figure 1A). SARS-CoV-2 IgG titers were equally distributed over time among age groups, sex, and PCS. PCS occurred in 30.5% (53/174) of vaccinated and 34.0% (18/53) of unvaccinated patients. Between 6 and 10 months (DELTAT2/T3: not yet vaccinated) and 10 and 15 months (DELTAT3/T4: vaccinated) after symptom onset (figure 1B), a comparable fraction of PCS patients recovered (DELTAT2/T3: 22.5% and DELTAT3/T4: 20.0%). Fatigue/dyspnea (P2) and not anosmia/ageusia (P1) constituted PCS at month 15 (P2 23.9% versus P1 1.4%). Headache (P4) and diarrhea (P5) at baseline were risk factors for PCS at months 15, respectively (P4: OR 2.01 (95%CI 1.11-3.52), p= .018;P5: OR 3.01(95%CI 1.44-5.94), p= .002). Conclusion(s): Our results indicate, that distinct symptom phenotypes can constitute and predict long-term PCS 15 months after mild COVID. Recovery of PCS was observed similarly in both therapeutically vaccinated and unvaccinated patients. Thus, development of targeted PCS therapeutics is needed to improve patient care and future epidemiological investigations. (Figure Presented).