Realization of Coronavirus Testing Kit Using a Combination of a Triangular Photonic Crystal (PhC) Structure and a 412 nm Laser Beam

The design of a Covid-19 testing kit is proposed in this research using a photonic crystal structure (PhC) and a violet laser beam. The basic principle of this structure relies on the phenomenon of absorbance reflectance and transmission at the signal of a 412 nm laser beam. Finally, the transmitted light energy through the PhC structure is the conclusive factor to detect the types of virus which is the function of the reflectance and absorbance. The reflected light energy is computed by plane wave expansion (PWE) whereas the absorbance of light energy is obtained through numerical computation. The notable advantages of this technique are that the virus related to Covid-19 can be recognized by observing the colour of transmitted energy through a photo energy meter. Finally, the outcomes of the research affirm that the sample could be Covid-19 if the output energy would be infrared (IR). Similarly, the sample could be a normal coronavirus, if the output energy would lie within the visible regime.

Silicon photonic chip-based biosensor for COVID-19 and flu detection with high sensitivity and specificity

Since the end of 2021, Omicron, the new variant of SARS-CoV-2, has continued to spread as the predominant strain of COVID-19. Compared to previous variants, Omicron causes milder symptoms, which are similar to symptoms of other common respiratory infections, such as flu. In this work, we develop a silicon photonic chip-based biosensor for COVID-19 and flu detection using subwavelength grating micro-ring resonator. The biosensor realizes the detection of two pathogens with high sensitivity (1.31 fg/mL) and specificity. Besides, the microfluidic channel offers a promising solution for point-of-care detection. © 2023 SPIE.

How do the sectoral indices react to COVID-19? Evidence from an emerging economy

The study empirically examines the impact of the COVID-19 on different sectoral indices of the National Stock Exchange (India) using the event study method and a generalised autoregressive conditional heteroskedasticity (GARCH) model. We provide evidence of positive impacts on the auto, oil and gas, healthcare, and pharma sectors. While the bank, financial services, and private bank sectors are the most adversely impacted sectors, the PSU bank, media, and reality sectors are the least impacted, and the rest are moderately impacted sectors. The overall impact of COVID-19 was negative until the implementation of nationwide lockdowns and the announcement of stimulus packages. The GARCH results exhibit more substantial evidence for the negative impact of the pandemic on the FMCG, IT, metal, oil and gas, and PSU bank sectors. We also find a more favourable impact on FMCG, pharma, and healthcare sectors in India.

Multiple Fano Resonances in Plasmonic Waveguide Based Cavity and Detection of Pathogenic Virus

A technique is implemented for the generation of multiple Fano-resonances in a plasmonic waveguide based rectangular cavity. A rectangular cavity provides four Fano peaks which can further be increased to nine by inserting the metallic bars in it. The trapped surface plasmon polaritons by metallic bars cause the generation of multiple Fano peaks over the wavelength range of 450 nm - 1300 nm. The obtained response is validated through Fano profile and Fano shape parameter is calculated for each resonance peak. The performance of the proposed device is numerically studied as refractive index sensor and method for analyzing the detection of pathogenic virus like SARS-Cov-2 is reported. Out of nine Fano peaks, the best values of sensing performance indices are obtained with full-width, half-maxima of 1.7 nm, quality factor of 405, sensitivity of 1145.71 nm/RIU and figure of merit of 393.25 RIU-1. IEEE

J-wave in a patient with severe COVID-19

In the context of the current COVID-19 epidemic, numerous are the manifestations of the infected patients, including the alterations in the 12-lead electrocardiogram, where the presence ofa J-wave can be found, secondary to the generation ofa transmural voltage gradient, caused by the overexpression of the channels for transient outward potassium current (Ito), in the context of a severe infection with extensive myocardial injury. In this article is presented the case of an 83-year-old patient with a positive diagnosis of COVID-19, who progressed to septic shock, with mixed addosis and mild hyperkalemia. The electrocardiogram showed the presence of a Jwave, probably secondary to the effect ofpro-inflammatory cytokines on potassium channels and extensive areas of myocardial injury.

Interpersonal Distance Tracking with mmWave Radar and IMUs

Tracking interpersonal distances is essential for real-time social distancing management and ex-post contact tracing to prevent spreads of contagious diseases. Bluetooth neighbor discovery has been employed for such purposes in combating COVID-19, but does not provide satisfactory spatiotemporal resolutions. This paper presents ImmTrack, a system that uses a millimeter wave radar and exploits the inertial measurement data from user-carried smartphones or wearables to track interpersonal distances. By matching the movement traces reconstructed from the radar and inertial data, the pseudo identities of the inertial data can be transferred to the radar sensing results in the global coordinate system. The re-identified, radar-sensed movement trajectories are then used to track interpersonal distances. In a broader sense, ImmTrack is the first system that fuses data from millimeter wave radar and inertial measurement units for simultaneous user tracking and re-identification. Evaluation with up to 27 people in various indoor/outdoor environments shows ImmTrack's decimeters-seconds spatiotemporal accuracy in contact tracing, which is similar to that of the privacy-intrusive camera surveillance and significantly outperforms the Bluetooth neighbor discovery approach. © 2023 Owner/Author.

Comparison of Obstetric Outcomes in First and Second COVID-19 Waves: Analysis from a COVID-19-dedicated Tertiary Care Hospital

Introduction: The physiological changes in the respiratory and cardiovascular systems in the immunosuppressed state of pregnancy may exacerbate clinical features and deteriorate outcomes due to COVID-19 infection. We aimed to compare the maternal and neonatal adverse effects in the first and second COVID-19 waves. Methodology: This study was a prospective cohort study conducted in a tertiary care COVID-19-dedicated hospital. In total, 104 (group A) and 96 (group B) COVID-19-positive pregnant women admitted during the first and second waves, respectively, were included in the study. Data on baseline variables, associated comorbidities, clinical presentations, management strategies, and neonatal and maternal outcomes were collected and compared using parametric and nonparametric tests and analyzed. Result(s): Around 2.08% in group A and 6.72% in group B of COVID-19-infected pregnant women, respectively, had moderate-to-severe disease and required intensive care unit stay. Almost 1.04% in group A and 3.84% in group B had maternal mortality, 13.4% and 19.8% babies of groups A and B required admission in neonatal intensive care units, and 8.6% and 7.3% of newborns in groups A and B had COVID-19-positive reports by reverse transcriptase polymerase chain reaction (RT-PCR) at birth, respectively. Of them, 2.1% newborns in group B had RT-PCR positive on day 7 of life and beyond, whereas none had positive RT-PCR reports on 7 days and beyond in group A. Conclusion(s): Dreadful maternal outcomes like requirement of ICU and mechanical ventilator and persistence of neonatal infections were higher during the second wave.Copyright © The Author(s). 2023.

USES OF THE SKEW-LOGISTIC FUNCTION FOR MULTI-WAVE FUNCTIONS

The Skew-Logistic (SL) function has been proposed to model a real-life dynamic process which rises monotonically to a peak followed by a monotonic falling back. It was introduced to model the first stage of the Covid-19 pandemic to forecast its behaviour. Then, with different controls and variants, Covid-19 - rose and fell in what might be called a Multi-Wave (MW) behaviour;with waves not necessarily the same size. This paper shows how using the SL function for one wave can be easily modified to model the MW situation. We apply it to two examples. One is to Covid-19, to examine its most recent behaviour. We also apply it to climate change, the most serious issue of our time. Ensuring that the world simply achieves carbon-equality is not enough. We have to rapidly achieve carbon-negativity to prevent bringing an end to the known world. © SW 2023.All rights reserved

Clinical profile and outcomes of COVID-19 infection during the first wave in children with hematological illnesses and cancer: An observational study from a tertiary care center in North India

Background: Patients with cancer are at a higher risk of getting infected with the severe acute respiratory syndrome coronavirus 2 owing to their immunocompromised state. Providing care to these patients amidst the first wave of the coronavirus disease-2019 (COVID-19) pandemic was extremely challenging. Objective(s): This study was aimed at evaluating the clinical profile and disease-related outcomes of pediatric patients with hematological illnesses and cancer. Material(s) and Method(s): This retrospective study was conducted at a tertiary care center in North India during the first wave of the pandemic from March 2020 to December 2020. Children aged up to 18 years, who were treated for a hematological illness or malignancy or underwent hematopoietic stem cell transplantation (HSCT) and tested positive for COVID-19 regardless of symptoms were included in the study. Baseline demographic data related to the age, diagnosis, treatment status, and chemotherapy protocol used were collected. Outcomes including the cure rates, comorbidities, and sequelae were recorded. Result(s): A total of 650 tests for COVID-19 were performed for 181 children;22 patients were found to be COVID-19 positive. The most common diagnosis was acute leukemia (63.6%). None of the patients developed COVID-19 pneumonia. The majority of patients had asymptomatic infection and were managed at home. Among those with a symptomatic infection, the most common symptoms were fever and cough. A total of 3 (13.6%) patients needed oxygen therapy, one developed multisystem inflammatory syndrome of children leading to cardiogenic shock. Three patients required intensive care or respiratory support;all the patients had favorable clinical outcomes. The median time from the onset of COVID-19 to a negative result on the reverse transcription-polymerase chain reaction test was 21.3 days. Cancer treatment was modified in 15 patients (68.2%). Conclusion(s): Our results suggest that children with hemato-oncological illnesses rarely experience severe COVID-19 disease. The impact of the first wave of COVID-19 primarily manifested as disruptions in the logistic planning and administration of essential treatment to these children rather than COVID-19 sequelae.Copyright © 2021 Cancer Research, Statistics, and Treatment Published by Wolters Kluwer - Medknow.

Atrial electromechanical delay in post-COVID-19 postural orthostatic tachycardia: Innocent bystander or pathologic factor.

BACKGROUND: Post-COVID-19 syndrome represents a wide range of ongoing symptoms that persist beyond weeks or even months, after recovery from the acute phase. Postural orthostatic tachycardia (POT) is one of these symptoms with a poorly recognized underlying pathophysiology. PURPOSE: We aimed to investigate atrial electromechanical delay (AEMD), demonstrated by electrocardiographic P wave dispersion (PWD) and tissue Doppler echocardiography (TDE) in patients with POST-COVID-19 POT (PCPOT). METHODS: 94 post-COVID-19 patients were enrolled and classified into two groups; PCPOT group, 34 (36.1%) patients, and normal heart rate (NR group), 60 (63.9%) patients. 31.9% of them were males and 68.1% were females, with a mean age of 35 ± 9 years. Both groups were compared in terms of PWD and AEMD. RESULTS: As compared to the NR group, the PCPOT group showed a significant increase in PWD (49 ± 6 versus 25.6 ± 7.8, p < 0.001), higher CRP (37 ± 9 versus 30 ± 6, p = 0.04), prolonged left-atrial EMD, right-atrial EMD and inter-atrial EMD at (p = 0.006, 0.001, 0.002 respectively). Multivariate logistic regression analysis revealed that P wave dispersion (ß 0.505, CI (0.224-1.138), p = 0.023), PA lateral (ß 0.357, CI (0.214-0.697), p = 0.005), PA septal (ß 0.651, CI. (0.325-0.861), p = 0.021), and intra-left atrial EMD (ß 0.535, CI (0.353-1.346) p < 0.012) were independent predictors of PCPOT. CONCLUSION: Atrial heterogenicity in the form of prolonged AEMD and PWD seems to be a reasonable underlying pathophysiology of PCPOT. This could provide a new concern during the management and novel pharmacological approaches in these patients.

Longitudinal Findings on the Oneiric Activity Changes Across the Pandemic.

Purpose: COVID-19 pandemic waves have strongly influenced individuals' behaviors and mental health. Here, we analyzed longitudinal data collected in the Spring 2020 and 2021 from a large Italian sample with the aim of assessing changes in dream features between the first and third wave. Specifically, we evaluated the modifications of pandemic dream activity as a function of the general distress variations over time. Also, we detected the best explanatory variables of nightmare frequency and distress. Materials and Methods: Participants previously involved in the web survey during the first wave of the pandemic were asked to complete a new online survey on sleep and dream features available in Spring 2021 (N=728). Subjects decreasing their level of psychological general distress in the third (T3) vs the first (T1) pandemic wave were defined as "Improved" (N=330). In contrast, participants with an unchanged or increased level of general distress were defined as "Not Improved" (N=398). Results: Statistical comparisons revealed that dream recall frequency, nightmare frequency, lucid dream frequency, and emotional intensity show a reduction in T3 than T1. Moreover, the Improved group is characterized by lower nightmare rate and nightmare distress than Not Improved people. Our findings confirmed that beyond the trait-like variables (ie, age, sex), specific sleep-related measures are related to nightmare features. In particular, poor sleep hygiene was one of the best determinants of nightmare distress among Not Improved subjects. Conclusion: Our findings revealed that people experienced an adaptation to the pandemic during the third wave. We also strengthen the notion that nightmares and their variations over time are strongly related to human well-being, suggesting that specific trait-like and sleep-related factors could modulate the relationship between mental health and nightmare features.

Impact of COVID-19 pandemic on blood culture practices and bacteremia epidemiology.

The COVID-19 pandemic has strongly impacted healthcare settings. We assess changes in blood culture practices and results during the COVID-19 era. All blood culture vials processed between January 1, 2017, and December 31, 2020, by 3 clinical laboratories were included. A baseline period from January 1, 2017 to December 31, 2019, was compared to the year 2020. COVID-19 "waves" were defined as follows: "wave 1" from March 16 to May 10, 2020, and "wave 2" from October 29 to December 14, 2020. A mean of 143.5 and 158.6 vials per day were processed in 2019 and 2020 respectively. Up to 300 and 220 vials per day were processed during waves 1 and 2. Among positive vials, a higher rate of contaminant was noticed during wave 1 (55.9% vs 45.0%; P < 0.0001) and interwave (46.0% vs 38.6%; P < 0.0001) in comparison to previous years. The prevalence of contaminants returned to the baseline level during wave 2. Streptococcus pneumonia prevalence fell in 2020 in comparison to the baseline (0.4% vs 1.4%; P < 0.0001). The COVID-19 pandemic was associated with an increase in the number of blood culture vials processed, the rate of contaminants, and a fall in the number of pneumococcal bloodstream infections.

Web-based surveillance of respiratory infection outbreaks: retrospective analysis of Italian COVID-19 epidemic waves using Google Trends.

Introduction: Large-scale diagnostic testing has been proven insufficient to promptly monitor the spread of the Coronavirus disease 2019. Electronic resources may provide better insight into the early detection of epidemics. We aimed to retrospectively explore whether the Google search volume has been useful in detecting Severe Acute Respiratory Syndrome Coronavirus outbreaks early compared to the swab-based surveillance system. Methods: The Google Trends website was used by applying the research to three Italian regions (Lombardy, Marche, and Sicily), covering 16 million Italian citizens. An autoregressive-moving-average model was fitted, and residual charts were plotted to detect outliers in weekly searches of five keywords. Signals that occurred during periods labelled as free from epidemics were used to measure Positive Predictive Values and False Negative Rates in anticipating the epidemic wave occurrence. Results: Signals from "fever," "cough," and "sore throat" showed better performance than those from "loss of smell" and "loss of taste." More than 80% of true epidemic waves were detected early by the occurrence of at least an outlier signal in Lombardy, although this implies a 20% false alarm signals. Performance was poorer for Sicily and Marche. Conclusion: Monitoring the volume of Google searches can be a valuable tool for early detection of respiratory infectious disease outbreaks, particularly in areas with high access to home internet. The inclusion of web-based syndromic keywords is promising as it could facilitate the containment of COVID-19 and perhaps other unknown infectious diseases in the future.

Synergistic Effect between SARS-CoV-2 Wave and COVID-19 Vaccination on the Occurrence of Mild Symptoms in Healthcare Workers.

BACKGROUND: Since the beginning of the pandemic, five variants of epidemiological interest have been identified, each of them with its pattern of symptomology and disease severity. The aim of this study is to analyze the role of vaccination status in modulating the pattern of symptomatology associated with COVID-19 infection during four waves. METHODS: Data from the surveillance activity of healthcare workers were used to carry out descriptive analysis, association analyses and multivariable analysis. A synergism analysis between vaccination status and symptomatology during the waves was performed. RESULTS: Females were found at a higher risk of developing symptoms. Four SARS-CoV-2 waves were identified. Pharyngitis and rhinitis were more frequent during the fourth wave and among vaccinated subjects while cough, fever, flu syndrome, headache, anosmia, ageusia, arthralgia/arthritis and myalgia were more frequent during the first three waves and among unvaccinated subjects. A correlation was found between vaccination and the different waves in terms of developing pharyngitis and rhinitis. CONCLUSION: Vaccination status and viruses' mutations had a synergic effect in the mitigation of the symptomatology caused by SARS-CoV-2 in healthcare workers.

Pulmonary Functional Outcomes at 3 Months in Critical COVID-19 Survivors Hospitalized during the First, Second, and Third Pandemic Waves.

INTRODUCTION: Despite improved management of patients with COVID-19, we still ignore whether pharmacologic treatments and improved respiratory support have modified outcomes for intensive care unit (ICU) surviving patients of the three first consecutive waves (w) of the pandemic. The aim of this study was to evaluate whether developments in the management of ICU COVID-19 patients have positively impacted respiratory functional outcomes, quality of life (QoL), and chest CT scan patterns in ICU COVID-19 surviving patients at 3 months, according to pandemic waves. METHODS: We prospectively included all patients admitted to the ICU of two university hospitals with acute respiratory distress syndrome (ARDS) related to COVID-19. Data related to hospitalization (disease severity, complications), demographics, and medical history were collected. Patients were assessed 3 months post-ICU discharge using a 6 min walking distance test (6MWT), a pulmonary function test (PFT), a respiratory muscle strength (RMS) test, a chest CT scan, and a Short Form 36 (SF-36) questionnaire. RESULTS: We included 84 ARDS COVID-19 surviving patients. Disease severity, complications, demographics, and comorbidities were similar between groups, but there were more women in wave 3 (w3). Length of stay at the hospital was shorter during w3 vs. during wave 1 (w1) (23.4 ± 14.2 days vs. 34.7 ± 20.8 days, p = 0.0304). Fewer patients required mechanical ventilation (MV) during the second wave (w2) vs. during w1 (33.3% vs. 63.9%, p = 0.0038). Assessment at 3 months after ICU discharge revealed that PFTs and 6MWTs scores were worse for w3 > w2 > w1. QoL (SF-36) deteriorated (vitality and mental health) more for patients in w1 vs. in w3 (64.7 ± 16.3 vs. 49.2 ± 23.2, p = 0.0169). Mechanical ventilation was associated with reduced forced expiratory volume (FEV1), total lung capacity (TLC), diffusing capacity for carbon monoxide (DLCO), and respiratory muscle strength (RMS) (w1,2,3, p < 0.0500) on linear/logistic regression analysis. The use of glucocorticoids, as well as tocilizumab, was associated with improvements in the number of affected segments in chest CT, FEV1, TLC, and DLCO (p < 0.01). CONCLUSIONS: With better understanding and management of COVID-19, there was an improvement in PFT, 6MWT, and RMS in ICU survivors 3 months after ICU discharge, regardless of the pandemic wave during which they were hospitalized. However, immunomodulation and improved best practices for the management of COVID-19 do not appear to be sufficient to prevent significant morbidity in critically ill patients.

A KdV-SIR equation and its analytical solutions: An application for COVID-19 data analysis.

To describe the time evolution of infected persons associated with an epidemic wave, we recently derived the KdV-SIR equation that is mathematically identical to the Kortewegde Vries (KdV) equation in the traveling wave coordinate and that represents the classical SIR model under a weakly nonlinear assumption. This study further discusses the feasibility of applying the KdV-SIR equation and its analytical solutions together with COVID-19 data in order to estimate a peak time for a maximum number of infected persons. To propose a prediction method and to verify its performance, three types of data were generated based on COVID-19 raw data, using the following procedures: (1) a curve fitting package, (2) the empirical mode decomposition (EMD) method, and (3) the 28-day running mean method. Using the produced data and our derived formulas for ensemble forecasts, we determined various estimates for growth rates, providing outcomes for possible peak times. Compared to other methods, our method mainly relies on one parameter, σo (i.e., a time independent growth rate), which represents the collective impact of a transmission rate (ß) and a recovery rate (ν). Utilizing an energy equation that describes the relationship between the time dependent and independent growth rates, our method offers a straightforward alternative for estimating peak times in ensemble predictions.

Probing environmental and tectonic changes underneath Mexico City with the urban seismic field

The sediments underneath Mexico City have unique mechanical properties that give rise to strong site effects. We investigated temporal changes in the seismic velocity at strong-motion and broadband seismic stations throughout Mexico City, including sites with different geologic characteristics ranging from city center locations situated on lacustrine clay to hillside locations on volcanic bedrock. We used autocorrelations of urban seismic noise, enhanced by waveform clustering, to extract subtle seismic velocity changes by coda wave interferometry. We observed and modeled seasonal, co- and post-seismic changes, as well as a long-term linear trend in seismic velocity. Seasonal variations can be explained by self-consistent models of thermoelastic and poroelastic changes in the subsurface shear wave velocity. Overall, sites on lacustrine clay-rich sediments appear to be more sensitive to seasonal surface temperature changes, whereas sites on alluvial and volcaniclastic sediments and on bedrock are sensitive to precipitation. The 2017 Mw 7.1 Puebla and 2020 Mw 7.4 Oaxaca earthquakes both caused a clear drop in seismic velocity, followed by a time-logarithmic recovery that may still be ongoing for the 2017 event at several sites or that may remain incomplete. The slope of the linear trend in seismic velocity is correlated with the downward vertical displacement of the ground measured by interferometric synthetic aperture radar, suggesting a causative relationship and supporting earlier studies on changes in the resonance frequency of sites in the Mexico City basin due to groundwater extraction. Our findings show how sensitively shallow seismic velocity and, in consequence, site effects react to environmental, tectonic and anthropogenic processes. They also demonstrate that urban strong-motion stations provide useful data for coda wave monitoring given sufficiently high-amplitude urban seismic noise.

An Observational Study of COVID-19 Infection in Pregnant Women at a Tertiary Care Center

Background: COVID-19 infection is a disease caused by severe acute respiratory syndrome coronavirus 2. The manifestations, effects, and severity of the infection are varied in different waves, especially during pregnancy. Material(s) and Method(s): The study was conducted in two equal time periods during the first and second waves. During the first wave, the period of study was between June and August 2020 corresponding to the peak of the first wave, and in the second wave, the study period was between May and July 2021 corresponding to the peak of the second wave. Result(s): A total of 3,791 pregnant women was screened for COVID-19 infection during the first wave and second wave, the pregnant mothers with COVID-19 positive were 4.2 (n = 163) and 5.1% (n = 191), respectively. Around 60% were antenatal mothers and 37% were postnatal mothers who were COVID-19-positive. The predominant age group affected was between 20 and 25 years of age. Gestational diabetes mellitus (GDM), gestational hypertension, anemia, previous lower segment cesarean section (LSCS), postdated pregnancy, and past history of infertility were the high-risk factors observed during the study. Hypoxia was observed in 15% of patients in the second wave. About 49.7% (n = 95) of the COVID-19-positive mothers in the second wave required steroids, anticoagulants, and antiviral drugs. Conclusion(s): The incidence of COVID-19 infection was mild and asymptomatic during the first wave and symptomatic as well as with complications during the second wave. The disease severity, intensive care unit (ICU) admissions, duration of stay, LSCS delivery, and need for antivirals, anticoagulants, and steroids were more during the second wave of COVID-19.Copyright © The Author(s). 2023.

Features of the course and medical and social aspects of a new coronavirus infection in the Republic of Tajikistan

The aim - to assess some medical and social aspects of the epidemic process during the first wave of a new coronavirus infectious disease - COVID-19 in the Republic of Tajikistan. Material and methods. The retrospective study was conducted on the basis of an epidemiological analysis of official statistics as part of the epidemiological surveillance of COVID-19 from April 2020 to April 2021. Results and discussion. At the beginning of April 2021, a total of 13 308 cases of COVID-19 were registered, of which the proportion of recovered was 99.3% (13 218 cases), and the number of cases with a fatal outcome was 0.68% (90 cases;the average age of the deceased was 62.3+/-0.07 years). The peak of infection during the first wave occurred in May and June 2020, when the average daily increase was 97 people. For 2 months of the epidemic in the republic, 44.6% of the total number of patients with COVID-19 became infected, and the number of deaths reached 52 people or 57.7%. Among the patients, men prevailed (65%). The largest number of deaths (76.7%;n=69) was among older people with comorbidities (diabetes mellitus, cardiovascular disease, chronic lung disease, metabolic syndrome, etc.). An analysis of the age structure showed that the main proportion of cases fell on the age group of 40-60 years (42.6%). It was found that a significant proportion of patients with COVID-19 was detected in the Sughd region (33.0%) and Dushanbe (30.1%). Conclusion. The COVID-19 pandemic showed that the national healthcare system of the Republic of Tajikistan was not sufficiently prepared for such a development of the COVID-19 epidemic process. There was an acute shortage of medical and preventive specialists in the republic. Given the current situation in the Republic of Tajikistan, within the framework of epidemiological surveillance, the features of the course of the COVID-19 epidemic process were analyzed, adequate emergency measures were developed and proposed to limit the spread of the virus and reduce the negative impact of COVID-19 on public health. The number of beds has been reasonably expanded, the capacity of the laboratory service has been increased, mass vaccination of the population has been started according to epidemic indications.Copyright © 2022 Geotar Media Publishing Group

How Work and Shopping Related Travel Changed During the COVID-19 Pandemic in Western Hungary in 2020

In early 2020 our lives changed profoundly: to stop - or at least to slow down - the spread of COVID-19, advice was issued, recommendations were given and measures were introduced all over the world. In Hungary in early March the first recommendations were given for social distancing: people were asked not to take unnecessary travel and stay home. On March 11th the Hungarian government declared a state of emergency and from the 28th of March a partial lockdown was in effect in Hungary. In order to see how the recommendations and the lockdown influenced work and shopping related behavior, an online survey was conducted in Western Hungary in May 2020. The survey compares shopping activities and shopping- and work-related travel before the pandemic (before March) and after the recommendations and restrictions were issued. First results show that shopping related travel did not change profoundly: place of purchase remained in most cases the same. The dynamics of offline shopping changed: people tried to go to shops as little as possible. Work related travel also changed: in cases where home offices were possible, people worked from home. A second survey was conducted in autumn 2020. The survey analyzes whether shopping related travel patterns changed back to normal during the summer, or consumers retained the behavior they adopted during spring 2020. The analysis also includes publicly available data about various ongoing consumer research surveys conducted by research institutes and trade organizations since April. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.