Defence Medical Rehabilitation Centre (DMRC) COVID-19 Recovery Service.

Coronavirus disease 2019 (COVID-19) causes significant mortality and morbidity, with an unknown impact in the medium to long term. Evidence from previous coronavirus epidemics indicates that there is likely to be a substantial burden of disease, potentially even in those with a mild acute illness. The clinical and occupational effects of COVID-19 are likely to impact on the operational effectiveness of the Armed Forces. Collaboration between Defence Primary Healthcare, Defence Secondary Healthcare, Defence Rehabilitation and Defence Occupational Medicine resulted in the Defence Medical Rehabilitation Centre COVID-19 Recovery Service (DCRS). This integrated clinical and occupational pathway uses cardiopulmonary assessment as a cornerstone to identify, diagnose and manage post-COVID-19 pathology.

Reflection of Epidemiological Impact on Burden of Injury in Tertiary Care Centre, Pre-COVID and COVID Era: "Lockdown, a Good Fortune for Saving Life and Limb".

Road traffic injuries continue to be a major public health concern and are a leading cause of death and injury across the world. Road transport remains the most favoured mode of transport for both freight and passenger movement in India. As per the World Health Organization, approximately 1.35 million people die annually on the world's roads, and another 20 to 50 million sustain nonfatal injuries as a result of road traffic crashes. These injuries and deaths have an immeasurable impact on the families affected, whose lives are often changed irrevocably by these tragedies, and on the communities in which these people lived and worked. India ranks 1 in the total number of traffic-related deaths across the 199 countries reported in the World Road Statistics, 2018, followed by China and the USA due to its large population (India, 21.7, and China, 18.6, fatalities per 100,000), although several Central American and African countries have higher fatality rates. During COVID-19 (coronavirus disease-19) pandemic, a national lockdown was implemented by Government of India from 24 March to 31 May 2020, in four phases to control the spread of SARS CoV-2 (severe acute respiratory syndrome coronavirus-2) infection. In our observational study, we compared the epidemiology of trauma patients of two periods from 1 April to 31 May 2019 and 24 March to 31 May 2020 and found out that unique concept of lockdown with stringent implementation of discipline, alcohol ban, behavioural change in visiting family and friends as minimum as possible, promoting work from home and digital classes for school and colleges lead to phenomenal decrease in traffic-related injuries and fatality. The lockdown has grossly decreased 'disability-adjusted life year'(DALY), an outcome indicator for cost-effective analysis, which is calculated as the value of future years of healthy life lost to morbidity/disability and future years of life lost to premature mortality.

Some clinical and epidemiological aspects of the course of COVID-19 in people living with HIV

Objective. To describe the clinical and epidemical characteristics of a new coronavirus disease 2019 (COVID-19) in people living with HIV, for HIV infection implies the development of an immunosuppressive condition that may exacerbate the course of COVID-19. Material and methods. The research is based on retrospective and current epidemiological situation of HIV and SARS-CoV-2 infections in the Southern Russia regions during 2020 and survey of the patients with the co-infections concerning epidemiological, clinical, and laboratory diagnostic information. We collected all data from 15 regional centers for AIDS prevention and control in the Southern and North Caucasus Federal Districts. The survey sample consists of 121 patients. Statistical computation is done with Microsoft Office Excel 2010. Results and discussion. HIV patients of various age and social characteristics are involved in the COVID-19 epidemic process. Within registered HIV and SARS-CoV-2 co-infections all patients have apparent clinical symptoms. Asymptomatic cases are not presented. Mild cases prevail in the sample (48.8%). The frequency of severe and extremely severe was significantly higher in people living with HIV/AIDS on ART more than 2 months against naive PLHIV or using ART up two one month (p<0.05).Copyright © 2022 by the authors.

[Intertwined long COVID theories to explain its etiopathogenesis]

This editorial lists the main current theories on long COVID, such as the theory of viral persistence and the one of immunothrombosis associated with deregulation of the immune system;it is discussed as well their interrelation, which finally explains the etiopathogenesis and physiopathology of this new syndrome that afflicts the survivors of COVID-19;it is also discussed the link between viral persistence with the formation of amyloid microthrombi based on the hypothesis that the spike protein causes amyloidogenesis, inducing organic chronic damage that will characterize long COVID. Copyright © 2023 Revista Medica del Instituto Mexicano del Seguro Social.

Comparative impact of COVID-19 and common diseases on poverty in Cameroon and sustainable response strategies

In the context of a developing country like Cameroon characterized by the scarcity of financial resources and the appearance of Covid-19, this article shows that this pandemic was not more important than the pre-existing health problems to the point of giving it more importance in funding compared to strengthening the health system. The theoretical elasticity model of the poverty rate to growth is used to estimate the impact of Covid-19 and the incidence of impoverishing health expenditure is used for the impact of common diseases. It is estimated through direct health payments that common diseases push about 340,865 people into extreme poverty annually. The Covid-19, through the loss of growth generated between 4.8 and 6.6 points according to the optimistic or pessimistic scenarios, would impoverish between 224,193 and 398,565 people: impact on the number of poor ranging from 0.7 to 1.2 times that of all common diseases, i.e., equivalent on average, but sensitive to the speed of spread of the virus and the duration of the crisis while the impact of common diseases is structural and linked to the poorly performing health system. The solutions proposed are endogenous and linked to the impact mechanisms.

The clinical trial of patients improved from COVID-19: the effectiveness of mindfulness-based cognitive therapy on mental health and life expectancy (single-subject study)

Background & Aims: In early January 2020, a new corona virus called corona was identified as an infectious agent by the World Health Organization and caused a viral pneumonia outbreak, the first of which was reported in Wuhan, China in December 2019. The virus has so far infected most countries in the world and has become a global problem. By this time in December 2021, about 265 million people in the world have been infected with this virus and 5 million 270 thousand people have died from this disease. According to the World Health Organization, the incidence of this disease is still increasing and will become the third leading cause of death in the world by 2030. This disease has a special complexity and has multiple dimensions and consequences that have caused many problems in the field of health, social and economic as well as psychological for people. The emergence of this disease is now a public health crisis. According to this research, exposure to news and restrictions caused by this disease can lead to many mental health problems. In fact, one of the situations that puts a lot of stress on people during the outbreak of covid 19 disease is the inability to predict and uncertainty about the control and end of the disease. Mental health is defined as a harmonious and harmonious behavior with society, recognizing and accepting social realities, the power to adapt to them and meeting one's balanced needs and is an important factor for the health of society. The prevalence of the disease can also increase feelings of loneliness, decrease social support, feelings of fear and anxiety to clinical stress and anxiety, obsessive-compulsive disorder associated with the disease, and decreased life expectancy. One of the hopeful factors is health and the disease can cause despair, fear and even despair of the patient. The outbreak of a disease has a much deeper and wider impact and affects not only the affected community and relatives, but the entire community. Because everyone finds themselves at risk, and therefore people's feel of safe and healthy changes, and this situation causes people to despair. Hope is the capacity to imagine the ability to create paths to desirable goals and to imagine the motivation to move in those paths. Hope predicts physical and mental health such as positive response to medical interventions, mental health, effective getting along, and health-promoting behaviors. Covid 19 disease can also lead to psychological problems due to its infectious nature and unpredictable nature. In this regard, various researchers consider the implementation of public health policies, including areas related to individual and collective mental health in accordance with the different stages of the epidemic of this disease is very necessary. Mindfulness can be an effective tool for achieving peace of mind and body that helps people become aware of their current feelings. Mindfulness-based interventions are considered as one of the third generation or third wave cognitive-behavioral therapies. Mindfulness is a form of meditation rooted in Eastern religious teachings and rituals, especially Buddhism. Segal has defined mindfulness as paying attention to specific and purposeful ways, in the present time, without judgment or prejudice. Linhan stressed for the first time the need to pay attention to mindfulness as one of the essential components of psychological therapy. Mindfulness requires the development of three components: judgment avoidance, purposeful awareness, and focus on the present moment. Focusing on the present and processing all aspects of the above experience makes one aware of the daily activities and automatic functioning of the mind in the past and future world and he controls emotions, thoughts, and physical states through moment-to-moment awareness of thoughts. As a result, it is released from the everyday and automatic mind focused on the past and the future. Although general vaccination has reduced the virus in some countries, including Iran, and reduced the number of infected people, a large num

Machine Learning Approaches for Temporal and Spatio-Temporal Covid-19 Forecasting: A Brief Review and a Contribution

In December 2019 an outbreak of a new disease happened, in Wuhan city, China, in which the symptoms were very similar to pneumonia. The disease was attributed to SARS-CoV-2 as the infectious agent and it was called the new coronavirus or Covid-19. In March 2020, the World Health Organization declared a worldwide pandemic of the new coronavirus. We have already counted more than 110 million cases and almost 2.5 million deaths worldwide. In order to assist in decision-making to contain the disease, several scientists around the world have engaged in various efforts, and they have proposed a lot of systems and solutions for tracking, monitoring, and predicting confirmed cases and deaths from Covid-19. Mathematical models help to analyze and understand the evolution of the disease, but understanding the disease was not enough, it was necessary to understand the problem in a quantitative way to lead the decision-making during the pandemic. Several initiatives have made use of Artificial Intelligence, and models were designed using machine learning algorithms with features for temporal and spatio-temporal investigation and prediction of cases of Covid-19. Among the algorithms used are Support Vector Machine (SVM), Random Forest, Multilayer Perceptron (MLP), Graph Neural Networks (GNNs), Ecological Niche Models (ENMs), Long-Short Term Memory Networks (LSTM), linear regression, and others. And these had good results, and to analyze them, the Root Mean Squared Error (RMSE), Log Root Mean Squared Error (RMSLE), correlation coefficient, and others were used as metrics. Covid-19 presents a huge problem to public health worldwide, so it is of utmost importance to investigate it, and with these two approaches it is possible to track not only how the disease evolves but also to know which areas are at risk. And these solutions can help in supporting decision-making by health managers to make the best decisions for the disease that is in the outbreak. This chapter aims to present a literature review and a brief contribution to the use of machine learning methods for temporal and spatio-temporal prediction of Covid-19, using Brazil and its federative units as a case study. From canonical methods to deep networks and hybrid committee-based, approaches will be investigated. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Characteristics of viral shedding in people infected with SARS-CoV-2 during difference stages

Viral shedding of SARS-CoV-2 is a continuous dynamic process, which can be divided into latent stage, initial stage, peak stage and decreasing stage according to the characteristics of viral shedding. After being infected with SARS-CoV-2, the infected person generally stays in the latent period for 1-3 days, which is characterized by continuous negative nucleic acid test results and no infectiousness, and the risk of infection for close contacts is very low. At the initial stage of viral shedding is characterized by a rapid decline in the Ct value of nucleic acid tests in a short time, and clinical symptoms gradually appear. The infectiousness of the infected person gradually increases during this period, and the risk of infection for close contacts also gradually increases, but it is still in the early stage of infection, the possibility of viral shedding is low, and the risk of infection of secondary close contacts is low. The peak of viral shedding is characterized by low Ct value in nucleic acid test and obvious clinical symptoms;during this period, the infected person is the most infectious, and the risk of infection of the contact is the highest, so the scope of close contacts should be expanded appropriately. The decreasing period is characterized by the gradual increase of Ct value of nucleic acid test and the gradual disappearance of clinical symptoms;during this period, the infectiousness of the infected person gradually decreases to disappear. In an outbreak, an infected person in the decreasing phase is more likely to be an early infected person in the transmission chain. If infected individuals in the decreasing phase are found in an area without a SARS-CoV-2 epidemic, it suggests that the local outbreak epidemic has been spreading for some time and may be larger in scale. According to the characteristics of viral shedding, risk personnel can be determined more scientifically and accurately, so as to minimize the risk and reduce the waste of epidemic prevention resources.

Changing patterns in the distribution of skin lesions of scabies during the COVID-19 pandemic - a cross-sectional observational study

BACKGROUND: An ectoparasitic disease, scabies, caused by the mite Sarcoptes scabiei var hominis. Some of the predisposing factors are overcrowding, unhygienic surroundings, immunocompromised status, dementia, homelessness, and sexual contact. In this study, we wanted to evaluate the changed distribution of lesions of scabies during pandemic. METHODS: A cross sectional study was performed on 600 patients attending the skin department of our tertiary care hospital over a period of 6 months. The sites of the scabies lesions were noted along with types of lesions. Demographic data and history of regular hand washing and sanitization were also documented. RESULTS: Our study revealed an important correlation between change in pattern of distribution of scabies lesions from being less frequent on finger webs (19%) to being more frequent on abdomen (periumbilical area) (73%) and groins (67%) due to regular hand washing and frequent sanitization, in this pandemic era. CONCLUSIONS: A significant change in distribution of skin lesions in scabies can be noticed during this COVID-19 pandemic.

A Contact Matrix-Based Approach for Predicting COVID-19 Using Influenza Data

The global pandemic Corona Virus Disease 2019 (COVID-19) has become one of the deadliest epidemics in human history, bringing enormous harm to human society. To help health policymakers respond to the threat of COVID-19, prediction of outbreaks is needed. Research on COVID-19 prediction usually uses data-driven models and mechanism models. However, in the early stages of the epidemic, there were not enough data to establish a data-driven model. The inadequate understanding of the virus that causes COVID-19, SARS-COV-2, has also led to the inaccuracies of the mechanism model. This has left the government with the toughest Non-pharmaceutical interventions (NPIs) to curb the spread of the virus, such as the lockdown of Wuhan in 2020. Yet man is a social animal, and social relations and interactions are necessary for his existence. The novel coronavirus and containment measures have challenged human and community interactions, affecting the lives of individuals and collective societies. To help governments take appropriate and necessary actions in the early stages of an epidemic, and to mitigate its impact on people's psychology and lives, we used the COVID-19 pandemic as an example to develop a model that uses surveillance data from one epidemic to predict the development trend of another. Based on the fact that both influenza and COVID-19 are transmitted through infectious respiratory droplets, we hypothesized that they may have the same underlying contact structure, and we proposed the influenza data-based COVID-19 prediction (ICP) model. In this model, the underlying contact pattern is firstly inferred by using a singular value decomposition method from influenza surveillance data. Then the contact matrix was used to simulate the influenza virus transmission through close contact of people, and the influenza virus transmission model was established. In order to be able to simulate the spread of COVID-19 virus using influenza transmission models, we used influenza contact matrix and COVID-19 infection data to estimate the risk of a population contracting COVID-19, i.e. force of infection of COVID-19. Finally, we used force of infection and influenza virus transmission model to simulate and predict the spread of COVID-19 in the population. We obtained age-disaggregated influenza and COVID-19 infection data for the United States in 2020, as well as data for Europe, which was not disaggregated by age. We use correlation coefficients as an evaluation indicator, and the final results prove that the predicted value and the actual value are positively correlated. So, the development trend of COVID-19 can be predicted using influenza surveillance data. © 2022 IEEE.

Outbreak trends of fatality rate into coronavirus disease-2019 using deep learning

The World Health Organization (WHO) has declared the novel coronavirus as global pandemic on 11 March 2020. It was known to originate from Wuhan, China and its spread is unstoppable due to no proper medication and vaccine. The developed forecasting models predict the number of cases and its fatality rate for coronavirus disease 2019 (COVID-19), which is highly impulsive. This paper provides intrinsic algorithms namely - linear regression and long short-term memory (LSTM) using deep learning for time series-based prediction. It also uses the ReLU activation function and Adam optimiser. This paper also reports a comparative study on existing models for COVID-19 cases from different continents in the world. It also provides an extensive model that shows a brief prediction about the number of cases and time for recovered, active and deaths rate till January 2021.Copyright © 2023 Inderscience Enterprises Ltd.

[Epidemiological characterization of COVID-2019 in Mexican pregnant women: a cohort study]

Background: COVID-19 in pregnancy can increase the risk of complications due to the cardiorespiratory and immunological changes typical of pregnancy. Objective: To report the epidemiological characterization of COVID-19 in Mexican pregnant women. Material and methods: Cohort study on pregnant women with a positive COVID-19 test, which were followed until delivery and one month later. Results: 758 pregnant women were included in the analysis. Mothers' mean age was 28.8 +/- 6.1 years;the majority were workers 497 (65.6%) and with an urban origin (482, 63.6%);the most common blood group was O with 458 (63.0%);478 (63.0%) were nulliparous women and more than 25% had some comorbidities;the average gestation weeks at infection were 34.4 +/- 5.1 weeks;only 170 pregnant women (22.4%) received vaccination;the most frequent vaccine was BioNTech Pfizer (96, 60%);there were no serious adverse events attributed to vaccination. The mean gestational age at delivery was 35.4 +/- 5.2 weeks;85% of pregnancies were cesarean section;the most frequent complication was prematurity (406, 53.5%), followed by preeclampsia (199, 26.2%);there were 5 cases of maternal death and 39 cases of perinatal death. Conclusions: COVID-19 in pregnancy increases the risk of preterm birth, preeclampsia, and maternal death. Vaccination against COVID-19 in this series showed no risk for pregnant women and their newborns. Copyright © 2023 Revista Medica del Instituto Mexicano del Seguro Social.

Organization of immunobiological therapy for severe bronchial asthma in the Sverdlovsk region

BACKGROUND: Biologicals use in severe asthma (SA) is associated with targeted therapy (TT) availability problem. Ensuring the availability of biologicals can be resolved within the territorial compulsory medical insurance program (TCMIP) in day-stay or round-the-clock hospital. AIMS: This study aimed to develop and implement a program for immunobiological therapy (IBT) introduction for SA in Sverdlovsk Region (SR). MATERIALS AND METHODS: Program for introduction of IBT for SA was developed in SR in 2018 to provide patients with expensive biologicals within the TCMIP. Program includes the following: SA prevalence study in SR;practitioners training in differential diagnosis of SA;organization of affordable therapy for patients with SA;registration of patients with SA creation and maintenance;and selection and management of patients with SA in accordance with federal clinical guidelines. RESULT(S): Atopic phenotype in SA was detected in 5%, eosinophilic - in 2.3% of all analyzed cases of asthma (n=216). Practitioners of SR were trained in differential diagnosis of SA. Orders of the Ministry of Health of SR were issued as follows: regulating the procedure for referring patients with SA to IBT, with a list of municipal medical organizations providing IBT in a day-stay or round-the-clock hospital;approving regional registration form of patients with SA requiring biologicals use;ungrouping of clinical and statistical groups of day-stay hospital was depending on INN and dosage of biologicals;and selecting patients with SA for TT and including them in the regional register. Initiating of TT in round-the-clock hospital and continuation therapy in day-stay hospital provides a significant savings in compulsory medical insurance funds. CONCLUSION(S): IBT introduction for SA in SR is carried out within the framework of the developed program. Principle of decentralization brings highly specialized types of medical care closer to patients making it possible to provide routine medical care in "allergology-immunology" profile in the context of restrictions caused by coronavirus disease 2019 pandemic.Copyright © 2020 Pharmarus Print Media All rights reserved.

Randomized regulation: the impact of minimum quality standards on health markets

We report results from the first randomization of a regulatory reform in the health sector. The reform established minimum quality standards for patient safety, an issue that has become increasingly salient following the Ebola and COVID-19 epidemics. In our experiment, all 1348 health facilities in three Kenyan counties were classified into 273 markets, and the markets were then randomly allocated to treatment and control groups. Government inspectors visited health facilities and, depending on the results of their inspection, recommended closure or a timeline for improvements. The intervention increased compliance with patient safety measures in both public and private facilities (more so in the latter) and reallocated patients from private to public facilities without increasing out-of-pocket payments or decreasing facility use. In treated markets, improvements were equally marked throughout the quality distribution, consistent with a simple model of vertical differentiation in oligopolies. Our paper thus establishes the use of experimental techniques to study regulatory reforms and, in doing so, shows that minimum standards can improve quality across the board without adversely affecting utilization.

Metavirome in Sewage and Fecally-Tainted River Waters in the Philippines: Highlighting the Role of Environmental Surveillance in the Covid-19 Pandemic

Intro: The COVID-19 pandemic has triggered global collaborative efforts on response and research to detect SARS-CoV-2 particles not just in the human population but also in wastewater. While the examination of clinical samples from COVID-19 patients links SARS-CoV-2 to specific individuals, the analysis of an amalgam of human feces through environmental surveillance (ES) links SARSCoV-2 to populations and communities served by the wastewater system. Studies on SARS-CoV-2 in the environment were already done in high-resource countries. However, its epidemiology in wastewater bodies in the Philippines is limited. In this study, we used the National ES for Polio and Other Pathogens Network to investigate the molecular epidemiology and transmission dynamics of SARS-CoV-2 at the outset of the pandemic. Method(s): This is a retrospective study of 250 wastewater samples collected from May 2020 to July 2021. Samples were processed using the two-phase concentration technique. Pepper mild mottle virus RNAs were quantified as the internal control. Real-time PCR was used to detect the N-gene of the SARS-CoV-2. Whole genomes were sequenced using the COVID-19 ARTIC v4.0. Phylogenetic and mutation analysis were done and lineage assignments were established using the PANGOLIN software. Finding(s): Forty-two percent (107/250) of the environmental samples detected SARS-CoV-2 particles. Fifty-nine samples with Ct values <=38 were sequenced and the whole genome analysis revealed B.1.1 and B.6. lineages of SARS-CoV-2. When viral load were plotted with the weekly cases in the respective site, we observed that SARS-CoV2 can be detected in wastewater weeks before the spike of cases in the community. Conclusion(s): This is the first report on the detection of B.1.1 and B.6 SARS-CoV-2 particles in waste/surface waters in the Philippines. With the declining incidence of COVID-19 cases, this study provided data regarding the feasibility of establishing environmental surveillance for SARS-CoV-2 as a supplemental tool for human or case monitoring especially in resource-limited settings.Copyright © 2023

Factors affecting admission to intensive care unit of COVID-19 patients in the Kingdom of Bahrain

Objective: Coronavirus disease-2019 (COVID-19) is a newly emerging infectious disease that has become a global pandemic. This study aimed to identify the risk factors at presentation to predict intensive care unit (ICU) admissions. Materials & Methods: This retrospective observational study recruited 188 confirmed laboratory COVID-19 patients who were hospitalized in Jidhafs Maternity Hospital (JMH) from 1st June to 5th July 2020. Univariate and multivariate analyses were used to Explore risk factors associated with the increased risk of ICU admission. Results: The study revealed that older age (>60 years old) (16[38.1%], P=0.044), male gender (30 [40.0%], P=0.000) were significantly associated with the increased risk of ICU admissions. The most prevalent symptoms in admission were myalgia (13[40.6%], P=0.035), fever (39[34.2%], P=0.002) and cough (37[31.4%], P=0.032). In addition, raised serum level of alanine amino-transferase (ALAT) (34.7% vs. 20.7%, P=0.033), D-dimers (30.7% vs 12.2%, P=0.012), lactate dehydrogenase (LDH) (31.6% vs 0.0%, P=0.025) and ferritin (37.7% vs 16.7%, P=0.011) found to be important predictor of ICU admission. Conclusion: The finding indicates that older age, male gender, with increased alanine transferase (ALT), increased lactate dehydrogenase (LDH), high D-dimer and high ferritin was associated with an increased risk of ICU admissions. Identification of such factors will help to detect people who are more likely to develop severe COVID-19 disease and will help physicians to determine if patients need regular health care or ICU admission.

The fate of SARS-CoV-2 viral RNA in coastal New England wastewater treatment plants

Municipal sewage carries SARS-CoV-2 viruses shed in the human stool by infected individuals to wastewater treatment plants (WWTPs). It is well-established that increasing prevalence of COVID-19 in a community increases the viral load in its WWTPs. Despite the fact that wastewater treatment facilities serve a critical role in protecting downstream human and environmental health through removal or inactivation of the virus, little is known about the fate of the virus along the treatment train. To assess the efficacy of differing WWTP size and treatment processes in viral RNA removal we quantified two SARS-CoV-2 nucleocapsid (N) biomarkers (N1 and N2) in both liquid and solids phases for multiple treatment train locations from seven coastal New England WWTPs. SARS-CoV-2 biomarkers were commonly detected in the influent, primary treated, and sludge samples (returned activated sludge, waste activated sludge, and digested sludge), and not detected after secondary clarification processes or disinfection. Solid fractions had 470 to 3,700-fold higher concentrations of viral biomarkers than liquid fractions, suggesting considerably higher affinity of the virus for the solid phase. Our findings indicate that a variety of wastewater treatment designs are efficient at achieving high removal of SARS CoV-2 from effluent;however, quantifiable viral RNA was commonly detected in wastewater solids at various points in the facility. This study supports the important role municipal wastewater treatment facilities serve in reducing the discharge of SARS-CoV-2 viral fragments to the environment and highlights the need to better understand the fate of this virus in wastewater solids.