Active COVID-19 Cases Research Articles

Evaluating the Impact of Social Distancing on COVID-19 Spread in Vietnam by using Logistic Growth Curve Model

The regular increase in COVID-19 cases and deaths has resulted in a worldwide lockdown, quarantine and some restrictions. Due to the lack of a COVID-19 vaccine, it is critical for developing and least developed countries like Vietnam to investigate the efficacy of non-pharmaceutical treatments like social distance or national lockdown in preventing COVID-19 transmission. To address this need, the goal of this study was to develop a clear and reliable model for assessing the impact of social distancing on the spread of coronavirus in Vietnam. For the case study, the Logistic Growth Curve (LGC) model, also known as the Sigmoid model, was chosen to fit COVID-19 infection data from January 23, 2020 to April 30, 2020 in Vietnam. To determine the optimal set of LGC model parameters, we used the gradient descent technique. We were pleasantly surprised to discover that the LGC model accurately predicted COVID-19 community transmission cases over this time period, with very high correlation coefficient value r = 0.993. The results of this study imply that using social distancing technique to flatten the curve of coronavirus disease infections will help minimize the surge in active COVID-19 cases and the spread of COVID-19 infections. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

Influence of Population Density for COVID-19 Spread in Malaysia: An Ecological Study.

The rapid transmission of highly contagious infectious diseases within communities can yield potential hotspots or clusters across geographies. For COVID-19, the impact of population density on transmission models demonstrates mixed findings. This study aims to determine the correlations between population density, clusters, and COVID-19 incidence across districts and regions in Malaysia. This countrywide ecological study was conducted between 22 January 2021 and 4 February 2021 involving 51,476 active COVID-19 cases during Malaysia’s third wave of the pandemic, prior to the reimplementation of lockdowns. Population data from multiple sources was aggregated and spatial analytics were performed to visualize distributional choropleths of COVID-19 cases in relation to population density. Hierarchical cluster analysis was used to synthesize dendrograms to demarcate potential clusters against population density. Region-wise correlations and simple linear regression models were deduced to observe the strength of the correlations and the propagation effects of COVID-19 infections relative to population density. Distributional heats in choropleths and cluster analysis showed that districts with a high number of inhabitants and a high population density had a greater number of cases in proportion to the population in that area. The Central region had the strongest correlation between COVID-19 cases and population density (r = 0.912; 95% CI 0.911, 0.913; p < 0.001). The propagation effect and the spread of disease was greater in urbanized districts or cities. Population density is an important factor for the spread of COVID-19 in Malaysia.

Sosialisasi Kegiatan PPKM ( Pemberlakuan Kegiatan Pembatasan Masyarakat ) Ditingkat Desa Bersama Pemuda Karang Taruna

Until now the development of Covid-19 in Indonesia is still increasing in number. Due to the increase in Covid-19 cases, the government implemented various policies in the form of PSBB, lockdown, restrictions on a limited scale, social distancing, new normal, obeying health protocols, and other policies. The effectiveness of the PSBB in practice in the field will only be successful if every member of the community is willing to do so. Since the implementation of the Micro PPKM policy on February 9, 2021, active cases of COVID-19 have begun to be suppressed. In Gondosari Hamlet, Tamansari Village, the handling that has been carried out by the Village Government (Pemdes) and RT / RW is only limited to spraying disinfectants, starting from 1 week 1x, 1 month 1x, and currently 3 months 1x, socialization using loudspeakers regarding prevention the dangers of Covid-19. The method of activity used is the online and offline method which will be carried out by lecturers and students and students together with village youth organizations. Service activities in the form of Socialization of PPKM Activities (Enforcement of Community Restriction Activities) at the Village Level Together with Karang Taruna Youth in the form of providing education through leaflets and posters media are also accompanied by donations in the form of 100 masks, Service activities are part of efforts to increase public knowledge in terms of policy delivery and the Government's message regarding restrictions on activities in the community through PPKM, as well as about the dangers of covid-19 and prevention efforts that can be done, as well as providing masks to the community in the hope of increasing public awareness and as one of the steps to minimize the transmission of covid-19.

The trend analysis of COVID-19 cases before and after the Large-Scale Social Restriction (PSBB) in four provinces in Indonesia

Purpose: As the intervention of COVID-19 pandemic, Indonesia implemented Large Scale Social Restriction (PSBB). The aim of present research was to evaluate daily new cases, active cases, and daily death of COVID-19 before and after the implementation of PSBB in 4 provinces: Jakarta, West Sumatra, Gorontalo, West Java.Methods: Each parameter observed on four different time P0 (14 days before PSBB), P1 (0-13 days after PSBB), P2 (14-27 days after PSBB), and P3 (28-41 days after PSBB) from March 27, 2020 until May 22, 2020. Polynomial model was used to construct the trend of new cases and predicted active cases. The difference of the increase of new cases and the mean of death rate between periods was analysed using dependent T-test. The difference between predicted and measured active cases was analysed by independent T-test.Results: COVID-19 daily new cases increased at P1 in Jakarta and West Sumatra and differed at P2 and P3, while declined since P1 in Gorontalo and West Java. There was significant higher of COVID-19 active cases compare to predicted active cases at P1 in all provinces, except West Java. The trend of declining daily death after PSBB implementation was observed in all provinces.Conclusion: Different trends were observed in four provinces after the implementation of PSBB, which showed random trend of daily cases, mainly increase trend of active cases, and decrease trend of daily death. However, the length of PSBB implementation also differ, therefore prolonged observation was needed to evaluate the consideration of PSBB program continuation.

The Persistence of the Impact of COVID-19-Related Distress, Mood Inertia, and Loneliness on Mental Health During a Postlockdown Period in Germany: An Ecological Momentary Assessment Study.

BackgroundThe first wave of the COVID-19 pandemic in early 2020 increased mental health problems globally. However, little is known about mental health problems during a low-incidence period of the pandemic without strict public health measures.ObjectiveWe aim to investigate whether COVID-19–related risk factors for mental health problems persist beyond lockdown measures. We targeted a vulnerable population that is at risk of developing low mental health and assessed their daily dynamics of mood and emotion regulation after a strict lockdown.MethodsDuring a postlockdown period in Germany (between August 8, 2020, and November 1, 2020), we conducted an ecological momentary assessment with 131 participants who experienced at least mild COVID-19–related distress and loneliness. To estimate negative mood inertia, we built a lag-1 three-level autoregressive model.ResultsWe found that information exposure and active daily COVID-19 cases did not have an impact on negative mood amid a postlockdown period. However, there was a day-to-day carryover effect of negative mood. In addition, worrying about COVID-19, feeling restricted by COVID-19, and feeling lonely increased negative mood.ConclusionsThe mental health of a vulnerable population is still challenged by COVID-19–related stressors after the lifting of a strict lockdown. This study highlights the need to protect mental health during postpandemic periods.

Sarawak Covid-19: Effects of Pre-Festival Mobility and Festival Gatherings

Gathering to celebrate festivals is a common socio-cultural practice amongst Sarawak’s diverse groups. For untold years, individuals, households, villages and at times the entire communities get together to observe their various religious, cultural and community festivals. However, during the COVID-19 pandemic period, the practice of gathering to celebrate those festivals became a challenging practice. This is because density of population and intensity of social contacts are deemed to increase SARS-CoV-2 high transmissibility. In this paper, we analyzed the trend of COVID-19 active cases in Sarawak in the first half of the year 2021 and calibrated the parameter signifying the proportion of exposed population taking effective precautionary measures, κ in our model. Our findings suggest that after every festival celebration the value of κ is decreased, leading to the increased number of active cases. In addition, the pre-festival mobility change involving visits to the retail and grocery stores are higher than any other time. Therefore, the festival gatherings and increased pre-festival mobility are catalysts that accelerated the increment of the number of active COVID-19 cases in Sarawak. In light of this, we proposed that any form of festival related gathering ought to be avoided in order to curb any forms of outbreak in Sarawak.

Upaya Pencegahan dan Pemberdayaan Ekonomi Masyarakat Terdampak Covid-19 di Kecamatan Kademangan Kota Probolinggo

The covid-19 virus is a virus that spreads through droplets between humans and comes in direct contact with objects exposed to the virus. The increase in active cases of Covid-19 in Probolinggo City, especially Kademangan District, is because the community is still lacking information about the spread and prevention of Covid-19. As a result, many people have been affected economically due to the Covid-19 pandemic. The purpose of this community service is to prevent the spread of the Covid-19 virus, foster healthy living patterns, and empower the economy of people affected by Covid-19. Our service partners are the managers of the Bayuangga terminal and Bakpia Manalagi UMKM. Methods of community service in the form of education about 3M, and distribution of hand washing assistance at the Bayuangga Terminal, as well as empowering Bakpia Manalagi MSMEs by helping expand marketing with digital marketing methods. With community service that has been carried out, an understanding of the importance of doing 3M when activities outside the home and by expanding marketing using digital marketing is able to increase the demand for products which has an impact on the need for employees who can empower the surrounding community.Keywords : Covid-19, healthy lifestyles, digital marketing, Covid-19 prevention, Community empowerment

SARS-CoV-2 in wastewater from Mexico City used for irrigation in the Mezquital Valley: quantification and modeling of geographic dispersion.

Quantification of SARS-CoV-2 in urban wastewaters has emerged as a cheap, efficient strategy to follow trends of active COVID-19 cases in populations. Moreover, mathematical models have been developed that allow the prediction of active cases following the temporal patterns of viral loads in wastewaters. In Mexico, no systematic efforts have been reported in the use of these strategies. In this work, we quantified SARS-CoV-2 in rivers and irrigation canals in the Mezquital Valley, Hidalgo, an agricultural region where wastewater from Mexico City is distributed and used for irrigation. Using quantitative RT-PCR, we detected the virus in six out of eight water samples from rivers and five out of eight water samples from irrigation canals. Notably, samples showed a general consistent trend of having the highest viral loads in the sites closer to Mexico City, indicating that this is the main source that contributes to detection. Using the data for SARS-CoV-2 concentration in the river samples, we generated a simplified transport model that describes the spatial patterns of dispersion of virus in the river. We suggest that this model can be extrapolated to other wastewater systems where knowledge of spatial patterns of viral dispersion, at a geographic scale, is required. Our work highlights the need for improved practices and policies related to the use of wastewater for irrigation in Mexico and other countries.

Physical Activity for Active Cases of COVID-19: Can Patients Do Physical Exercise?

Physical Activity for Active Cases of COVID-19: Can Patients Do Physical Exercise?

Provider attitudes and satisfaction with rapid preoperative point-of-care COVID-19 testing using IDNOW™.

PurposeHealthcare workers have experienced high levels of anxiety during the COVID-19 pandemic, particularly when caring for patients with unknown infection status. We trialled rapid preoperative point-of-care COVID-19 testing using the Abbott ID NOW™ COVID-19 for clinical validation in an urgent surgical population at a single centre in British Columbia, Canada. Here, we sought to determine the opinions and beliefs of operating room (OR) staff on the usefulness and effectiveness of point-of-care tests on workflow and wellbeing in the OR.MethodsThis descriptive study used a mixed-methods cross-sectional survey of all OR staff (nurses, anesthesiologists, surgeons, and ancillary staff) at a single centre after using the ID NOW for three months. Outcomes of interest included healthcare worker satisfaction with the ID NOW, effects on OR workflow, and worries about COVID-19 transmission.ResultsThe overall response rate was 56% (n = 133), and was highest among anesthesiologists (100%, n = 38). Respondents were satisfied with the performance of the ID NOW for rapid COVID-19 testing in preoperative patients, giving it a mean (standard deviation [SD]) rate of 4.4 [1.4] on a five-point scale. Most (115/128, 90%) recommended continued use of the ID NOW on asymptomatic patients while there are active cases of COVID-19 in the community. Respondents felt that preoperative COVID-19 testing with the ID NOW made the OR safer for staff (mean [SD] rate, 4.2 [0.8]) and patients (mean [SD] rate, 4.0 [0.9]).ConclusionDuring the COVID-19 pandemic, it is important to maintain the physical and mental wellbeing of hospital staff. Rapid point-of-care testing increased the sense of workplace safety, improved morale, and reduced worry associated with COVID-19 without excessive disruption of OR workflow.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12630-021-02073-4.

Prediction of Daily COVID-19 Active Cases in Bangladesh

Recording daily active cases statistics benefits instantly when studying the ongoing COVID-19 dashboard for a country. It would help to illuminate the probable strategy of action for policy makers, as well as planners of a country. The goal of the paper is to forecast daily active COVID-19 cases for Bangladesh using various forecasting models, namely the regression model, the non-linear exponential regression model and some time series models based on the daily positive cases, daily deceased cases, daily recovered cases and some environmentally important variables. Our findings suggest that time series forecasting models have better ability to predict daily active cases as compared to other selected forecasting models.

Crowdsourcing Data To Visualize Potential Hotspots For Covid-19 Active Cases In Indonesia

As the COVID-19 outbreak spread worldwide, multidisciplinary researches on COVID-19 are vastly developed, not merely focusing on the medical sciences like epidemiology and virology. One of the studies that have developed is to understand the spread of the disease. This study aims to assess the contribution of crowdsourcing-based data from social media in understanding locations and the distribution patterns of COVID-19 in Indonesia. In this study, Twitter was used as the main source to retrieve location-based active cases of COVID-19 in Indonesia. We used Netlytic (www.netlytic.org) and Phyton’s script namely GetOldTweets3 to retrieve the relevant online content about COVID-19 cases including audiences’ information such as username, time of publication, and locations from January 2020 to August 2020 when COVID-19 active cases significantly increased in Indonesia. Subsequently, the accuracy of resulted data and visualization maps was assessed by comparing the results with the official data from the Ministry of Health of Indonesia. The results show that the number of active cases and locations are only promising during the early period of the disease spread on March – April 2020, while in the subsequent periods from April to August 2020, the error was continuously exaggerated. Although the accuracy of crowdsourcing data remains a challenge, we argue that crowdsourcing platforms can be a potential data source for an early assessment of the disease spread especially for countries lacking the capital and technical knowledge to build a systematic data structure to monitor the disease spread.

Effects of Movement Control Order on mitigating spread of COVID-19 in the early phase of the outbreak in Malaysia

We propose a mathematical model to investigate the early outbreak of COVID-19 in Malaysia. The model emphasizes the role of the government’s Movement Control Orders (MCOs) as population-wide lockdown measures and the potential benefit of mass testing on disease spread. We fit this model to the reported active COVID-19 cases to estimate model parameters. We also assume transmission rates change with respect to stages of MCOs and compare the differences in rates to assess the effectiveness of different levels of MCO restrictions. The estimated parameters match the observed data well, and our results suggest a slowing of the trajectory of COVID-19 outbreak in the country, indicating that the series of MCOs taken to counter COVID-19 transmission are having a significant positive effect.

Statistical models in trends of COVID-19 case fatality rates, India: a secondary data analysis

Background: The COVID-19 is potentially severe acute respiratory infectious disease, increasing day by day. Hence, to control of COVID-19 cases and deaths due to, study has been under taken with an objective to establish the models of trends in COVID-19 Case Fatality Rates for states of India, so that containment performance is assessed taking model as reference level. Materials and methods: The state-wise data from Kaggle website were used to study the levels and trends in Case Fatality Rate per 100 cases (Cured + Deaths) using Modified Logistic Regression Model, using SPSS-22 and Microsoft Office-10. The model is useful, where; deaths due to COVID-19 were more than one. Results: Himachal Pradesh was the best in controlling the disease, as per COVID-19 Active Cases and Case Fatality Rate. In Himachal Pradesh, COVID-19 stabilized by 45 days of presence of the disease, while, in Kerala by 100 days. Furthermore, the decline in COVID-19 in Himachal Pradesh was steadier and smoother as compared to comparable state Kerala. The worst group of states in controlling the COVID-19 Case Fatality Rate in poorest to better order was Maharashtra followed by Delhi, Rajasthan, Uttar Pradesh and Bihar, along with wide fluctuation in Active Cases and Case Fatality Rates. Conclusion: The worst affected state by COVID-19 was Maharashtra followed by Delhi, Rajasthan etc., reasons may be large movements of daily wagers/ temporary workers. Hence, the containment of COVID-19 is expected to be achieved by restriction in public movement and unrest in communities.

Is There a Temporal Relationship between COVID-19 Infections among Prison Staff, Incarcerated Persons and the Larger Community in the United States?

Background: Our objective was to examine the temporal relationship between COVID-19 infections among prison staff, incarcerated individuals, and the general population in the county where the prison is located among federal prisons in the United States. Methods: We employed population-standardized regressions with fixed effects for prisons to predict the number of active cases of COVID-19 among incarcerated persons using data from the Federal Bureau of Prisons (BOP) for the months of March to December in 2020 for 63 prisons. Results: There is a significant relationship between the COVID-19 prevalence among staff, and through them, the larger community, and COVID-19 prevalence among incarcerated persons in the US federal prison system. When staff rates are low or at zero, COVID-19 incidence in the larger community continues to have an association with COVID-19 prevalence among incarcerated persons, suggesting possible pre-symptomatic and asymptomatic transmission by staff. Masking policies slightly reduced COVID-19 prevalence among incarcerated persons, though the association between infections among staff, the community, and incarcerated persons remained significant and strong. Conclusion: The relationship between COVID-19 infections among staff and incarcerated persons shows that staff is vital to infection control, and correctional administrators should also focus infection containment efforts on staff, in addition to incarcerated persons.

COVID-19 and stock market nexus: evidence from Shanghai Stock Exchange

The outbreak of the contagious pandemic Covid-19 has disturbed various economic and business activities across the globe. This has resulted in the declination of cash flows and revenues, which significantly increases the probability of corporate bankruptcies and adversely affects the stock market performance. The current study investigated the Covid-19 and stock market nexus whilst considering the Shanghai Stock Exchange (SSX). Covid-19 active cases and deaths have been considered proxies for the Covid-19 from 1 April 2020 to 30 July 2020. For empirical analysis, this study utilised quantile regression and dynamic ordinary least squares (DOLS). Empirical findings of both quantile regression and DOLS illustrate that both the Covid-19 active cases and deaths significantly decline the SSX closing index. However, the quantile estimates reveal that from lower (0.25) quantile to medium (0.50) to higher (0.75) quantile, the magnitude of these variables is found declining. Moreover, the frequency domain causality test confirmed the unidirectional causal relationship between the study variables, running from Covid-19 cases and deaths to the SSX. The findings are robust, which leads to providing practical policy implications that identified the need to revise health-finance-related policies and financial education to combat such circumstances in the future.

First comparison of conventional activated sludge versus root-zone treatment for SARS-CoV-2 RNA removal from wastewaters: Statistical and temporal significance

In the initial pandemic phase, effluents from wastewater treatment facilities were reported mostly free from Severe Acute Respiratory Coronavirus 2 (SARS-CoV-2) RNA, and thus conventional wastewater treatments were generally considered effective. However, there is a lack of first-hand data on i) comparative efficacy of various treatment processes for SARS-CoV-2 RNA removal; and ii) temporal variations in the removal efficacy of a given treatment process in the backdrop of active COVID-19 cases. This work provides a comparative account of the removal efficacy of conventional activated sludge (CAS) and root zone treatments (RZT) based on weekly wastewater surveillance data, consisting of forty-four samples, during a two-month period. The average genome concentration was higher in the inlets of CAS-based wastewater treatment plant (WWTP) in the Sargasan ward (1.25 × 103 copies/ L), than that of RZT-based WWTP (7.07 × 102 copies/ L) in an academic institution campus of Gandhinagar, Gujarat, India. ORF 1ab and S genes appeared to be more sensitive to treatment i.e., significantly reduced (p < 0.05) than N genes (p > 0.05). CAS treatment exhibited better RNA removal efficacy (p = 0.014) than RZT (p = 0.032). Multivariate analyses suggested that the effective genome concentration should be calculated based on the presence/absence of multiple genes. The present study stresses that treated effluents are not always free from SARS-CoV-2 RNA, and the removal efficacy of a given WWTP is prone to exhibit temporal variability owing to variations in active COVID-19 cases in the vicinity and genetic material accumulation over the time. Disinfection seems less effective than the adsorption and coagulation processes for SARS-CoV-2 removal. Results stress the need for further research on mechanistic insight on SARS-CoV-2 removal through various treatment processes taking solid–liquid partitioning into account.

Socioeconomic disparities and COVID-19 vaccination acceptance: a nationwide ecologic study

ObjectiveTo analyse the correlation between COVID-19 vaccination percentage and socioeconomic status (SES). MethodsA nationwide ecologic study based on open-sourced, anonymized, aggregated data provided by the Israel Ministry of Health. The correlations between municipal SES, vaccination percentage and active COVID-19 cases during the vaccination campaign were analysed by using weighted Pearson correlations. To assess the adequacy of first dose vaccination rollout relative to the municipality COVID-19 disease burden, a metric termed the vaccination need ratio was devised by dividing the total number of active cases (per 10 000 people) by the vaccination percentage of the population over 60 in each municipality, and its correlation with the SES was examined. Results23 days after initiation of the vaccination campaign, 760 916 (56.8%) individuals over the age of 60 were vaccinated in Israel with the first dose of the BNT162b2 COVID-19 vaccine. A negative correlation was found between the COVID-19 active case burden and the vaccination percentage of the study population in each municipality (r = –0.47, 95% CI –0.59 to –0.30). The vaccination percentage significantly correlated with the municipal SES (r = 0.83, 95% CI 0.79 to 0.87). This finding persisted but was attenuated over a 5-week period. A negative correlation between the vaccination need ratio and municipal SES (r = –0.80, 95% CI –0.88 to –0.66) was found. DiscussionLower COVID-19 vaccination percentage was associated with lower SES and high active disease burden. Vaccination efforts should focus on areas with lower SES and high disease burden to assure equality of vaccine allocation and potentially provide a more diligent disease mitigation.

The asymmetric effects of COVID19 on wholesale fuel prices in Australia

This paper examines the effects of the number of active COVID19 cases on the wholesale prices of diesel and unleaded petrol (gasoline) across seven Australian states using daily data from 1 Jan 2020–11 September 2020. Our results indicate that statistically significant asymmetries with respect to COVID19 are observed in both wholesale unleaded petrol and diesel prices in all seven markets. When crude oil prices are falling substantially, the number of active COVID19 cases is highly significant in a negative relationship with petrol prices. However, when oil prices are rising (or not falling substantially), the negative effects of such a pandemic on fuel prices perplexingly disappear or become smaller. We find that the negative effects of COVID19 on diesel prices are more pronounced in more population-dense capital cities (i.e. Sydney and Melbourne). It is surprising to observe that the effects of COVID19 pandemic are driven by changes in oil prices: rising oil prices can substantially reduce the negative effect of this health pandemic on fuel prices. Our findings complement concerns from the national competition commission that while fuel prices have recently fallen to decades-long lows, fuel profit margins are at record high levels.

COVID-19 Surveillance in the Primary Health Care Population of Qatar: Experience of Prioritizing Timeliness Over Representativeness When Sampling the Population.

SARS-CoV2 a new emerging Corona Virus Disease in humans, which called for containment measures by many countries. The current paper aims to discuss the impact of two different sampling methodologies when executing a drive through COVID-19 survey on the quality of estimated disease burden measures. Secondary data analysis of a pilot cross-sectional survey targeting Qatar's primary health care registered population was done. Two groups with different sampling methods were compared for estimating COVID-19 point prevalence using molecular testing for nasopharyngeal swabs. The first group is a stratified random sample non-proportional to size (N = 260). A total of 16 population strata based on age group, gender, and nationality were sampled. The second group is the Open invitation group (N = 841). The results showed that the two groups were obviously and significantly different in age and nationality. Besides, reporting of COVID-19 symptoms was more frequent in the open invitation group (28.2%) than the random sample (16.2%). The open invitation group overestimated the symptomatic COVID-19 prevalence rate by more than four times, while it overestimated the asymptomatic COVID-19 cases by a small margin. The overall prevalence rate of active COVID-19 cases in the open invitation sample (13.3%) was almost double that of the random sample (6.9%). Furthermore, using population sampling weights reduced the prevalence rate to 0.8%. The lesson learned here is that it is wise to consider the magnitude of bias introduced in a surveillance system when relying on convenient sampling approaches in response to time constraints.