Number Of Coronavirus Disease 2019 Cases Research Articles

Model-based cost-effectiveness analysis of oral antivirals against SARS-CoV-2 in Korea.

OBJECTIVESMany countries have authorized the emergency use of oral antiviral agents for patients with mild-to-moderate cases of coronavirus disease 2019 (COVID-19). We assessed the cost-effectiveness of these agents for reducing the number of severe COVID-19 cases and the burden on Korea’s medical system.METHODSUsing an existing model, we estimated the number of people who would require hospital/intensive care unit (ICU) admission in Korea in 2022. The treatment scenarios included (1) all adult patients, (2) elderly patients only, and (3) adult patients with underlying diseases only, compared to standard care. Based on the current health system capacity, we calculated the incremental costs per severe case averted and hospital admission for each scenario.RESULTSWe estimated that 236,510 COVID-19 patients would require hospital/ICU admission in 2022 with standard care only. Nirmatrelvir/ritonavir (87% efficacy) was predicted to reduce this number by 80%, 24%, and 17% when targeting all adults, adults with underlying diseases, and elderly patients (25, 8, and 4%, respectively, for molnupiravir, with 30% efficacy). Nirmatrelvir/ritonavir use is likely to be cost-effective, with predicted costs of US$8,878, US$8,964, and US$1,454, per severe patient averted for the target groups listed above, respectively, while molnupiravir is likely to be less cost-effective, with costs of US$28,492, US$29,575, and US$7,915, respectively.CONCLUSIONSIn Korea, oral treatment using nirmatrelvir/ritonavir for symptomatic COVID-19 patients targeting elderly patients would be highly cost-effective and would substantially reduce the demand for hospital admission to below the capacity of the health system if targeted to all adult patients instead of standard care.

Coronavirus disease 2019 (COVID-19) in assisted living communities: Neighborhood deprivation and state social distancing policies matter.

Residents of long-term care facilities face significantly greater risk of contracting or dying from coronavirus disease 2019 (COVID-19). However, little is known about COVID-19 in assisted living communities (ALCs) and the potential determinants of its spread. We examined the association between COVID-19 cases in ALCs and the proportion of Medicare-Medicaid (dual) eligible minority residents, neighborhood area deprivation, and state COVID-19 policy stringency. We conducted longitudinal analyses employing data on confirmed COVID-19 cases in ALCs in 5 states. We sought to determine the weekly cumulative number of COVID-19 cases in ALCs. Covariates were ALC characteristics, area deprivation index, and state COVID-19 policy stringency. Multivariate 2-part models were used to determine the associations between independent variables and the likelihood of an outbreak and the overall count of cases. In our study sample, 201 ALCs (7.04%) reported 1 or more COVID-19 cases as of August 17, 2020. A higher percentage of minority residents was associated with an increased likelihood of an ALC reporting at least 1 COVID-19 case (odds ratio [OR], 1.06; P = .032). Conditional on having at least 1 case, ALCs in states with stricter social distancing policies had lower case counts (incidence rate ratio [IRR], 0.98; P < .001). Greater neighborhood deprivation was associated with higher case count (IRR, 1.36; P = .049). ALCs with higher proportions of dual-eligible minority residents were more likely to have COVID-19 outbreaks within their communities. ALCs located in more socioeconomically deprived neighborhoods, and in states with less stringent state social distancing policies, tended to have more COVID-19 cases.

Description of Waste Management of COVID-19 Patients without Symptoms in Self-Isolation Period Mamuju District

Background: COVID-19 (coronavirus disease 2019) is a disease caused by a new type of coronavirus, namely Sars-CoV-2, which was first reported in Wuhan, China. In Indonesia May 2020, the death toll is continuing. Globally, there were 4,170,424 cases of COVID-19 with 287,399 deaths. Citing the recap of the COVID-19 data from the West Sulawesi Provincial Health Office, as of February 6, 2021, the cumulative number of positive COVID-19 cases was 4,380, an increase of 73%. Purpose: This research is to find out the description of Waste Management of Covid-19 Patients Without Symptoms (OTG) During the Independent Isolation Period of Mamuju District. The Research Method used in this research is the descriptive research method. The location of the research was carried out in Mamuju District. The number of samples in this study was 30 respondents. The data collection technique used was interviewed using a questionnaire. Results: The results showed that there was waste management that was not by the standards. This is due to the lack of facilities in the patient's home and lack of knowledge. Conclusion: Waste management by asymptomatic Covid-19 sufferers does not meet waste processing standards. Keywords: Covid 19, isolation, waste.

Detection of SARS-CoV-2 RNA in wastewater, river water, and hospital wastewater of Nepal

The applicability of wastewater-based epidemiology (WBE) has been extensively studied throughout the world with remarkable findings. This study reports the presence and reduction of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at two wastewater treatment plants (WWTPs) of Nepal, along with river water, hospital wastewater (HWW), and wastewater from sewer lines collected between July 2020 and February 2021. SARS-CoV-2 RNA was detected in 50%, 54%, 100%, and 100% of water samples from WWTPs, river hospitals, and sewer lines, respectively, by at least one of four quantitative PCR assays tested (CDC-N1, CDC-N2, NIID_2019-nCOV_N, and N_Sarbeco). The CDC-N2 assay detected SARS-CoV-2 RNA in the highest number of raw influent samples of both WWTPs. The highest concentration was observed for an influent sample of WWTP A (5.5 ± 1.0 log10 genome copies/L) by the N_Sarbeco assay. SARS-CoV-2 was detected in 47% (16/34) of the total treated effluents of WWTPs, indicating that biological treatments installed at the tested WWTPs are not enough to eliminate SARS-CoV-2 RNA. One influent sample was positive for N501Y mutation using the mutation-specific qPCR, highlighting a need for further typing of water samples to detect Variants of Concern. Furthermore, crAssphage-normalized SARS-CoV-2 RNA concentrations in raw wastewater did not show any significant association with the number of new coronavirus disease 2019 (COVID-19) cases in the whole district where the WWTPs were located, suggesting a need for further studies focusing on suitability of viral as well as biochemical markers as a population normalizing factor. Detection of SARS-CoV-2 RNA before, after, and during the peaking in number of COVID-19 cases suggests that WBE is a useful tool for COVID-19 case estimation in developing countries.

Early impact of COVID-19 pandemic on heart transplant volumes in Asia and Oceania: results from the Global Observatory on Donation and Transplantation (GODT)

Funding AcknowledgementsType of funding sources: None.IntroductionMassive demand for healthcare services worldwide following the emergence of coronavirus disease 2019 (COVID-19) has limited the availability of healthcare resources needed for certain high-complexity procedures, including orthotopic heart transplantation (OHT). Whereas the negative impact of COVID-19 pandemic on several elective procedures has been well-documented, data on regional changes in OHT volumes after COVID-19 are limited. Therefore, we aimed to quantify the impact of COVID-19 pandemic on OHT volumes in Asia and Oceania.MethodsUsing data from the Global Observatory on Donation and Transplantation (GODT), the world"s most comprehensive source of data on organ donation and transplantation, we recorded the number of OHT procedures performed in years 2019 (pre-COVID-19 era) and 2020 (COVID-19 era). The analysis was limited to countries with reported OHT data within Asia and Oceania (Australia, China, India, Iran, Israel, Japan, New Zealand, Russian Federation, Saudi Arabia, Thailand, Turkey, and the United Arab Emirates). OHT rates were reported for each country per million population (PMP), and change in the COVID-19 era was reported as percentage of the pre-COVID-19 rates. The association of total COVID-19 cases with relative reduction in OHT was evaluated using linear regression.ResultsAcross the Asia/Oceania region, number of OHT in COVID-19 era (median 0.64 procedures PMP, IQR 0.28, 2.15) was significantly lower compared with the pre-COVID-19 era (median 1.18 procedures PMP, IQR 0.49, 2.50), with a median change of -0.29 (IQR -0.70, -0.08; P = 0.04). The impact of COVID-19 on OHT was most pronounced in Turkey, United Arab Emirates, and India, where OHT volumes decreased by 75.4%, 60.8%, and 53%, respectively. Country-level reduction in OHT volumes was not associated with total number of COVID-19 cases during the year 2020 in that country (r = 0.31; P-value = 0.3).ConclusionThe number of heart transplants during the early phase of COVID-19 pandemic significantly decreased in ­­­most countries of the Asia/Oceania region. Furthermore, the change in OHT volumes did not correlate with the total number of recorded COVID-19 cases, suggesting the pandemic’s impact on OHT numbers extended beyond limiting availability of resources. Identifying factors leading to OHT deferral during COVID-19 pandemic will advance our understanding of the pandemic’s true impact on the care of advanced heart failure patients in the region. Figure.

Causal Effect of the Tokyo 2020 Olympic and Paralympic Games on the Number of COVID-19 Cases under COVID-19 Pandemic: An Ecological Study Using the Synthetic Control Method.

Previous studies have not assessed the causal effect of the Olympic Games on the spread of pandemics. Using the synthetic control method and the national public city data in Japan recorded from February to September 2021, we estimated the causal effects of the Tokyo 2020 Olympic and Paralympic Games on the number of coronavirus disease 2019 (COVID-19) cases. The difference between the number of COVID-19 cases in Tokyo and a counterfactual “synthetic Tokyo” (created using synthetic control method) after the opening of the Tokyo 2020 Games (23 July 2021) widened gradually and then considerably over time. It was predicted that the Tokyo 2020 Games increased the number of COVID-19 cases in Tokyo by approximately 469.4 per 100,000 population from the opening of the event to 30 September. However, sensitivity analysis of the ratio of the pre- and post-game root mean square prediction errors using regression weights did not suggest robustness. Our results showed that the Tokyo 2020 Games probably increased the number of COVID-19 cases even under preventive regulations; however, the extent of this increase was difficult to estimate clearly due to an overlap with the fifth wave associated with the Delta variant.

Predicting the Epidemics Trend of COVID-19 Using Epidemiological-Based Generative Adversarial Networks

The Coronavirus disease 2019 (COVID-19) is a respiratory illness that can spread from person to person. Since the COVID-19 pandemic is spreading rapidly over the world and its outbreak has affected different people in different ways, it is significant to study or predict the evolution of its epidemic trend. However, most of the studies focused solely on either classical epidemiological models or machine learning models for COVID-19 pandemic forecasting, which either suffer from the limitation of the generalization ability and scalability or the lack of surveillance data. In this work, we propose T-SIRGAN that integrates the strengths of the epidemiological theories and deep learning models to be able to represent complex epidemic processes and model the non-linear relationship for more accurate prediction of the growth of COVID-19. T-SIRGAN first adopts the Susceptible-Infectious-Recovered (SIR) model to generate epidemiological-based simulation data, which are then fed into a generative adversarial network (GAN) as adversarial examples for data augmentation. Then, Transformers are used to predict the future trends of COVID-19 based on the generated synthetic data. Extensive experiments on real-world datasets demonstrate the superiority of our method. We also discuss the effectiveness of vaccine based on the difference between the predicted and the reported number of COVID-19 cases.

Colorectal Surgery in the COVID-19 Pandemic Era.

The novel coronavirus disease 2019 (COVID-19) caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread at a very fast rate, overwhelming and disrupting healthcare systems around the world since its outbreak in December 2019 in China. As of October 2021, the total number of COVID-19 cases exceeds 240,000,000, and the total number of deaths is close to 5,000,000. In the situation of widespread SARS-CoV-2 infection, restrictions on the medical system due to shifts in medical care to accommodate the pandemic will occur, and its impact on surgical and endoscopic treatment for colorectal cancer is inevitable. Therefore, it is necessary to satisfy all of the following requirements: patient safety, prevention of exposure of healthcare workers including surgeons, prevention of nosocomial infection, and a decision on how to treat the primary disease. Surgical triage is also required, based on comprehensive consideration of the patient's condition, the severity of the disease, the SARS-CoV-2 infection situation in the region, and the medical supply system at each facility, including medical resources, human resources, and the availability of medical equipment. Understanding the diagnostic and treatment environment that the COVID-19 pandemic has dramatically changed is important in providing appropriate surgical care to patients who require surgery while taking utmost care to prevent the spread of COVID-19.

Association of city-level walkability, accessibility to biking and public transportation and socio-economic features with COVID-19 infection in Massachusetts, USA: An ecological study.

With people restricted to their residences, neighbourhood characteristics may affect behaviour and risk of coronavirus disease 2019 (COVID-19) infection. We aimed to analyse whether neighbourhoods with higher walkability, public transit, biking services and higher socio-economic status were associated with lower COVID-19 infection during the peak of the COVID-19 pandemic in Massachusetts. We used Walk Score®, Bike Score®, and Transit Score® indices to assess the walkability and transportation of 72 cities in Massachusetts, USA based on availability of data and collected the total COVID-19 case numbers of each city up to 10 April 2021. We used univariate and multivariate linear models to analyse the effects of these scores on COVID-19 cases per 100,000 in each city, adjusting for demographic covariates and all covariates, respectively. In the 72 cities studied, the average Walk Score, Transit Score and Bike Score was 48.7, 36.5 and 44.1, respectively, with a total of 426,182 COVID-19 cases. Higher Walk Score, Transit Score, and Bike Score rankings were negatively associated with COVID-19 cases per 100,000 persons (<0.05). Cities with a higher proportion of Hispanic population and a lower median household income were associated with more COVID-19 cases per 100,000 (P<0.05). Higher Walk Score, Transit Score and Bike Score were shown to be protective against COVID-19 transmission, while socio-demographic factors were associated with COVID-19 infection. Understanding the complex relationship of how the structure of the urban environment may constrain commuting patterns for residents and essential workers during COVID-19 would offer potential insights on future pandemic preparedness and response.

Surgical Management During the COVID-19 Era at a Private Tertiary Care Hospital of Karachi, Pakistan: A Cross-Sectional Study.

BackgroundThe coronavirus disease 2019 (COVID-19), declared a pandemic in March 2020, has affected the entire healthcare system, including the surgical practice. Guidelines for the management of surgical patients during this COVID-19 era need to be established to provide timely yet safe surgical care. In this study, we aimed to evaluate the outcomes of the COVID-19 testing algorithm established for surgery patients presenting to a tertiary care hospital in Karachi, Pakistan, and to compare the outcomes among patients who underwent elective versus emergency surgery.MethodologyThis is a cross-sectional study conducted at a tertiary care hospital in Pakistan to apply and assess the outcomes of the COVID-19 testing algorithm established for patients presenting for surgery. We included all patients who underwent any surgery from May to October 2020. The total sample size was 6,846. The data were analyzed using SPSS version 23 (IBM Corp., Armonk, NY, USA). The categorical variables were assessed using the chi-square or Fisher’s exact test. A p-value of <0.05 was considered significant.ResultsA total of 6,846 surgeries were performed from May 1 to October 31, 2020. In total, 74% of the surgeries were elective procedures. We observed that a significantly higher proportion of emergency surgery patients tested positive for COVID-19 (4.2%) compared to elective surgery patients (25/5,063, 0.5%). A higher proportion of surgeries were performed in September (1,437, 21%) and October (1,445, 21%) while the lowest number of surgeries were performed in May (625, 9.1%). From week one to week five, a higher proportion of emergency surgeries were performed (32%) compared to elective surgeries (25%). Only 1.9% of the patients who were undergoing surgery were COVID-19 positive, with the highest number of COVID-19 cases presenting in June. Overall, 74 (4.2%) of the COVID-19-positive patients underwent emergency surgeries.ConclusionsThe timely establishment of well-defined guidelines for surgical management during the pandemic allowed us to provide timely and effective surgical care to patients with the priority of minimizing the spread of COVID-19 and preventing unnecessary deferral of surgeries.

Comparative Study of Clinical and Radiological Profile and Outcome of COVID-19 Patients with and without Co-morbidities: A Cross-sectional Study

Introduction: Coronavirus Disease-2019 (COVID-19) had devastating effects on the healthcare and economic sector worldwide. India stands second in the list of most number of COVID-19 cases. Most of the deaths due to COVID-19 were seen in patients with associated co-morbidities like hypertension, diabetes, chronic kidney disease and obesity. This study would like to examine specific co-morbidities in relation to the COVID19 disease progression and outcomes. Aim: To compare the clinicoradiological profile and outcome of COVID-19 in patients with and without co-morbidities (diabetes and hypertension). Materials and Methods: The present observational, crosssectional study was conducted at Jawaharlal Nehru Medical College, Aligarh, Uttar Pradesh between June 2020 to September 2020, after obtaining Institutional Ethics Committee (IEC) approval. A total of 148 patients with COVID-19 were included in the study. The COVID-19 patients admitted in the hospital were divided into four groups as those having only diabetes, only hypertension, both diabetes and hypertension, and those without any comorbidities. Those with any other co-morbidity were excluded from the study. The general clinical characteristics, laboratory parameters, disease severity, morbidity and mortality were compared among various groups and the data was analysed. Categorical data were analysed using the Chi-square test. Results: A total of 148 patients with COVID-19 were included in the study, of which 26 patients were diabetic, 36 were hypertensive, 24 were both hypertensive and diabetic and 62 patients didn’t had any significant co-morbidity. Severe COVID-19 disease was most commonly observed in those with diabetes (n=14) (53.8%). The highest proportion of patients requiring oxygen (84.6%) and Non Invasive Ventilator (NIV) support (46.1%) was also seen among diabetics. The presence of diabetes, severe disease and leukocytosis at presentation increased the risk of mortality. The association of hypertension with COVID-19 does not seem to affect the in-hospital mortality. Conclusion: COVID-19 in diabetics is associated with both increased risk of severe disease and increased odds of death. In diabetics, those with uncontrolled diabetes were more prone to severe disease and death than those with good glycaemic control. Hypertension, on the other hand, showed no association.

COVID-19: Situation analysis in the district of Ernakulam.

Context:Corona Virus Disease 2019 (COVID-19) has become a pandemic causing millions of deaths and causing a devastating blow to the global economy. Like all other countries and territories, the Ernakulam district (Kerala, India) is affected by COVID-19. When the number of COVID-19 cases reported in the other states started coming down, the Ernakulam district continued to record a large number of cases.Aims:To analyse the situation of the COVID-19 pandemic in the district of Ernakulam, Kerala.Material and Methods:The authors were part of the COVID-19 surveillance unit of Ernakulam district, and hence, had access to the data collected. The available data were analysed in the following phases of the pandemic: First phase: From the reporting of the first case in Kerala in January to the reporting of the first case in the Ernakulam district. Second phase: Cases reported mostly in those with a travel history and their contacts to the period of community spread. Third phase: From the start of community spread.Results and Discussion:As of July 5, 2021, the Ernakulam district reported 3,60,345 cases of the COVID-19 infection with 1,317 deaths and the recovery rate being 96.45%. Despite factors like high human development index (HDI), access to the Internet and social media, access to affordable healthcare, etc., factors like high population density, airports, seaports, railway stations, container terminals, IT parks, major highways, tourist spots, beaches, large shopping malls, large floating population, a huge number of migrant labourers, a large proportion of the elderly population, high prevalence of non-communicable diseases, etc., are the some of the major challenges. The preparedness of the fight against COVID-19 included the training of all healthcare workers, ward level rapid response teams (RRT), upgradation of health facilities, district-level patient management system, provisions to manage biomedical waste, etc., The containment zone strategy is currently based on the local self-government area-wise weekly test positivity rate (TPR). The cluster containment is focused on the early identification of clusters. Currently, the Ernakulam district reports one of the highest numbers of COVID-19 cases in India. This is mainly because of the high number of tests (five to six times to national average) and targeted testing strategy. This is scientifically proven by the very low case fatality rate (0.35%), low-bed occupancy rate of the COVID treatment facilities and the latest seroprevalence study by Indian Council for Medical Research (ICMR).Conclusions:So far, the Ernakulam district could excel in its efforts to fight against COVID-19. But even now, when we are moving forward with the immunisation of the healthcare workers, front-line workers, elderly population, our main strategies to prevent COVID-19 remain the same—proper social distancing, hand hygiene, use of masks, avoiding unnecessary travels and gathering, early identification of cases and treatment.

The impact of meteorological factors and PM2.5 on COVID-19 transmission.

In this study, we analysed the relationship between meteorological factors and the number of patients with coronavirus disease 2019 (COVID-19). The study period was from 12 April 2020 to 13 October 2020, and daily meteorological data and the daily number of patients with COVID-19 in each state of the United States were collected. Based on the number of COVID-19 patients in each state of the United States, we selected four states (California, Florida, New York, Texas) for analysis. One-way analysis of variance ( ANOVA), scatter plot analysis, correlation analysis and distributed lag nonlinear model (DLNM) analysis were used to analyse the relationship between meteorological factors and the number of patients with COVID-19. We found that the significant influencing factors of the number of COVID-19 cases differed among the four states. Specifically, the number of COVID-19 confirmed cases in California and New York was negatively correlated with AWMD (P < 0.01) and positively correlated with AQI, PM2.5 and TAVG (P < 0.01) but not significantly correlated with other factors. Florida was significantly correlated with TAVG (positive) (P < 0.01) but not significantly correlated with other factors. The number of COVID-19 cases in Texas was only significantly negatively associated with AWND (P < 0.01). The influence of temperature and PM2.5 on the spread of COVID-19 is not obvious. This study shows that when the wind speed was 2 m/s, it had a significant positive correlation with COVID-19 cases. The impact of meteorological factors on COVID-19 may be very complicated. It is necessary to further explore the relationship between meteorological factors and COVID-19. By exploring the influence of meteorological factors on COVID-19, we can help people to establish a more accurate early warning system.

Natural Capital Exploration and Coronavirus Disease Spread in 2020

The potential relationship between nature and Coronavirus disease 2019 (COVID-19) is provided using cross-sectional macro-data collected including 17 countries of major developed and developing nations whose number of cases were greater than 500 in March 15th 2020. We found that the correlation coefficient is -0.46 between fisheries stock average growth rate per capita from 1994 to 2014 and number of COVID-19 cases in 2020. It suggests that the damage of lives under water and cases of COVID-19 might be associated.

Facilitators and Barriers to Infant Immunization during COVID-19 Pandemic

Introduction: The world is enveloped with the coronavirus disease 2019 (COVID-19) Pandemic with modern medicine and public health facing their most significant challenges ever posed. As the number of COVID-19 cases increased worldwide, an important issue of concern was the continuation of routine immunization services for children. This study has been conceptualized to assess the effect of the COVID-19 pandemic on infant Immunization. Materials and Methods: This study was a descriptive study conducted in an urban community amongst healthy children <1-year-old from January 2018 to September 2021. Immunization records of infants were obtained from data generated during each immunization session and strength, weakness, opportunity, and threat analysis was done using a questionnaire. Results: During the study, a total of 3518 vaccinations were done, a total of 3010 vaccinations (85.5%) were done on time, and the total delayed vaccinations were 508 (14.5%). The difference among the years was statistically significant, with the highest delay in the year 2020 (P < 0.001). However, in the year 2021, the number of vaccinations carried out from April to September was 568, with delayed vaccination of only 10.9%. Conclusion: The Armed Forces childhood immunization program could be sustained during the COVID-19 pandemic due to a multitude of contributing factors such as adherence to national guidelines that prioritized vaccination, infrastructure, and availability of trained workforce and most importantly commitment to strict COVID appropriate behavior.

A cross-sectional study on the seroprevalence of the SARS-CoV-2 IgG antibody in patients with cancer from central Kerala

Background: Patients with cancer are vulnerable to coronavirus disease 2019 (COVID-19). Given the rising number of COVID-19 cases and relaxation of stringent COVID-19 protocols, assessment of the level of protective immunity to COVID-19 in patients with cancer has assumed importance.Objectives: Our primary objective was to evaluate the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in patients with cancer.Materials and Methods: We conducted a cross-sectional study on 100 patients with solid tumors attending our Oncology Department at the Believers Church Medical College, Kerala, India, between December 2020 and June 2021. Seroprevalence was assessed using the VITROS® Anti-SARS-CoV-2 IgG test (Ortho-Clinical Diagnostics, Rochester, NY, USA). Additionally, we assessed the factors associated with seropositivity and collected data regarding the general experience of patients with cancer during the pandemic.Results: The median age of the participants was 62 years (IQR, 53 - 69.8); 52 (52%) were males. The seroprevalence of the SARS-CoV-2 IgG antibodies was 11% (95% CI, 4.8–17.1). Age < 50 years was the only factor that was significantly associated with a higher rate of COVID-19 antibodies (77% vs 8.9% in patients ≥ 50 years; P = 0.007), and sex, smoking, and the use of alcohol did not show any association. The majority (77/100, 77%) of the patients were worried about contracting COVID-19 infection; some even deferred cancer-directed treatment because of the fear of visiting health care settings.Conclusion: Low seroprevalence of SARS-CoV-2 IgG antibodies in unvaccinated patients with cancer is a matter of concern as it indicates that many of these patients are still vulnerable to infection. There is an urgent need to continue implementing strict safety measures in oncology centers and to encourage widespread COVID-19 vaccination to prevent the uncontrolled spread of COVID-19 among patients with cancer. (Funded by the institution, Believers Church Medical College, Kerala)

CapsNet-COVID19: Lung CT image classification method based on CapsNet model.

The outbreak of the Corona Virus Disease 2019 (COVID-19) has posed a serious threat to human health and life around the world. As the number of COVID-19 cases continues to increase, many countries are facing problems such as errors in nucleic acid testing (RT-PCR), shortage of testing reagents, and lack of testing personnel. In order to solve such problems, it is necessary to propose a more accurate and efficient method as a supplement to the detection and diagnosis of COVID-19. This research uses a deep network model to classify some of the COVID-19, general pneumonia, and normal lung CT images in the 2019 Novel Coronavirus Information Database. The first level of the model uses convolutional neural networks to locate lung regions in lung CT images. The second level of the model uses the capsule network to classify and predict the segmented images. The accuracy of our method is 84.291% on the test set and 100% on the training set. Experiment shows that our classification method is suitable for medical image classification with complex background, low recognition rate, blurred boundaries and large image noise. We believe that this classification method is of great value for monitoring and controlling the growth of patients in COVID-19 infected areas.

Understanding COVID-19 Situation in Nepal and Implications for SARS-CoV-2 Transmission and Management.

Background:The pandemic of Coronavirus Disease 2019 (COVID-19), one of the most infectious diseases in the modern history, is caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) and has had a profound health and economic toll, globally. This paper identifies the overall health status associated with COVID-19 pandemic in all 7 provinces of Nepal, a developing country in South Asia, analyzing data from January 2020 to February 2022. It focuses on the SARS-CoV-2 prevalence, transmission through wastewater and other routes, diagnostics, treatment options, and alternative medicines, thereby offering key perspectives for its management.Materials and Methods:Studies regarding coronavirus spanning the 2017 to 2022 period were searched on the web, Nepalese database, and Web of Science. Refined criteria included SARS-CoV-2 in wastewater of Nepal or worldwide. Demographic data (sex, age-group, and geographic location) were also obtained from websites and relevant reports of the Ministry of Health and Population (MOHP) of Nepal, ranging from January 2020 to February 2022. Moreover, trends concerning lockdown, business, and border activities in Nepal between February 2020 and October 2020 were evaluated. The viral dissemination pathways, diagnosis, and available treatment options, including the Ayurvedic medicine, were also examined.Results:Aerosols generated during the hospital, industrial, recreational, and household activities were found to contribute to the propagation of SARS-CoV-2 into environmental wastewater, thereby putting the surrounding communities at risk of infection. When lockdown ended and businesses opened in October 2020, the number of active cases of COVID-19 increased exponentially. Bagmati Province had the highest number of cases (53.84%), while the remaining 6 provinces tallied 46.16%. Kathmandu district had the highest number of COVID-19 cases (138, 319 cases), while Manang district had the smallest number of infections (81 cases). The male population was found to be predominantly infected (58.7%). The most affected age groups were the 31 to 40 years old males (25.92%) and the 21 to 30 years old females (26.85%).Conclusion:The pandemic impacted the public health and economic growth in our study duration. SARS-CoV-2 was prevalent in the wastewater of Nepal. The Terai districts and the megacities were mostly affected by SARS-CoV-2 infections. Working-age groups and males were identified as the highest risk groups. More investigations on the therapeutic and alternative cures are recommended. These findings may guide the researchers and professionals with handling the COVID-19 challenges in developing countries such as Nepal and better prepare for future pandemics.

Sociodemographic characteristics of professional categories most affected by COVID-19 in Mozambique, from March to July 2020

the risk of a worker becoming ill due to coronavirus disease 2019 (COVID-19) is related to occupational exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Due to the need to restore work activities in Mozambique, the study was conducted with the aim of identifying the occupational categories most affected by COVID-19 in the former in the period from March to July 2020. this is a cross-sectional descriptive study, in which data from professions of confirmed cases of COVID-19 from 22 March to 29 July 2020 in Mozambique were analyzed. The professionals' data were reported daily by the National Institute of Health (NIH) and merged into a single database and exported to Excel, the latter categorized according to standard operating procedure (SOP) and descriptive statistics performed for its analysis. in the period under analysis, 1,127 professionals were diagnosed with COVID-19, divided into 11 categories. Nampula province had the highest frequency of cases with 25.00% (277). The highest frequency of cases was registered in the domestic professional category, which had 16.77% (189/1,127) with the female sex being more frequent, 79.37% (150/189); and defense and security had 14.20% (160/1,127) of cases and male gender with 91.25% (146/160); Health workers had 13.04% (147/1,127), and the maximum number of COVID-19 cases was recorded in June with 58.50% (86/147). the professional categories most affected by COVID-19 in the period under review correspond to those groups that carry out activities requiring a physical presence at the workplace and from this; it is recommended that professionals reinforce preventive measures.

Helping Public Health Decision-Makers Refine Community Coronavirus Disease-2019 Vaccination Efforts--Association between Confirmed Coronavirus Disease-2019 Cases and Vaccinations

Introduction The response to the coronavirus disease-2019 (COVID-19) epidemic included biomedical and vaccine research as well as identification of COVID-19 cases, contact tracing, community health promotion and disease prevention and community vaccination. The COVID-19 vaccinations remind public health professionals and non-professionals alike of this essential public health intervention for controlling infectious diseases. Actions that seek to improve existing vaccination efforts are equally important for effective public health programming. Methods Secondary data analysis uses an ecological study design to examine any possible associations between the number of COVID-19 cases identified at medical facilities (facility names not identified) within a healthcare system and the number of COVID-19 vaccinations administered within the system and reflect upon the findings for public health action. A loess curve was plotted to help to identify if a curvature pattern was present in a scatter plot. Results The statistical algorithm for the loess curve identified a curvature pattern. All plots showed that values became more separated in moving from left to right. Discussion This aggregate pattern in number of COVID-19 cases and number of vaccinations administered might be present in other public health settings or healthcare systems. Four refinements were proposed to help public health decision-makers to improve vaccination efforts: explore the reasons for differences in COVID vaccination given the number of confirmed COVID cases between facilities; provide vaccination outside traditional settings; facilitate public health and primary care partnerships for community vaccination; and address vaccine knowledge-gaps in the community and other barriers to vaccination.