Number Of Positive COVID-19 Cases Research Articles

Promising role of traditional Indian Ayurvedic medicine in treatment, management and better clinical outcomes of COVID-19 patients: a retrospective study

IntroductionThe Coronavirus disease (COVID-19) has negatively impacted the lives of people globally. To date, no specific treatment has emerged to combat the disease. Hence, there is an urge for immediate therapy against infections like COVID-19 through the inclusion of various traditional medicines including Ayurveda. MethodsThis retrospective study was performed on 300 patients who were treated using the Holistic Ayurveda protocol at the COVID Health Care (CHC) centre. Out of 300 patients, 258 who took the AYURAKSHA Kit regularly along with the other Ayurvedic medicines for treatment were selected for this study. Demographic distribution, viral clearance, and haematological parameters of COVID-19 patients were analysed. ResultsThe maximum number of COVID-19 positive cases (31.4%) were found in the age group 20–29 years whereas the age group 40–49 years (11.52 days) and ≥ 60 years (11.5 days) took the maximum time (P = 0.035) for viral clearance. The haematological investigations showed that the Ayurveda treatment maintained the admitted patients' blood profile and coagulation profile. Strikingly, liver and kidney profiles improved post-treatment as Serum Glutamic-Oxaloacetic Transaminase (P = 0.000), Serum Glutamic Pyruvic Transaminase (P = 0.000), Urea (P = 0.000), and Creatinine (P = 0.002) levels were significantly reduced. Likewise, a significant reduction in inflammation markers like C-reactive Protein (P = 0.000), Erythrocyte Sedimentation Rate (P = 0.003), and serum Ferritin (P = 0.000) was also observed. No adverse treatment effects were observed during follow-up of the patients. ConclusionThe above outcomes showed that the Holistic Ayurveda Protocol in treating COVID-19 patients is safe, acceptable and effective. Thus, suggesting the possible integration of Ayurvedic treatment in combating such deadly diseases.

A Truth or a Rumor: Effects of Addictive Substances ‎on Prevention of COVID-19; an Investigation of Homeless Drug Abusers in Southeastern Iran

Background: In a crisis, rumors often get started, and societies use them to cope with ambiguous situations. Southeastern Iran, with its high rate of homeless addicts per population, is a suitable area to examine the accuracy of the rumor about the positive effect of addictive substances on preventing COVID-19. Objectives: This cross-sectional study aimed to investigate the abundance of COVID-19 infection among homeless drug abusers in this area. Methods: For each participant, the health experts completed a questionnaire form. For a definite diagnosis of COVID-19, a combined oropharyngeal/nasal sampling method was used in the laboratory under standard polymerase chain reaction (RT-PCR). Data was analyzed with SPSS v. 19. The chi-square test was used to compare COVID-19 cases across substance types, abuse methods, and consumption frequencies. Results: In total, 295 homeless drug abusers participated, and positive COVID-19 was recorded for 21(7.1%). Most participants were waste pickers (60.5%), and 3.9% had COVID-19. The statistical analysis ‎showed no significant difference in the number of positive COVID-19 cases between narcotics, stimulants, and both combinations. Our study also did not prove the positive effect of drug abuse methods and the frequency of daily drug abuse on the incidence of this disease. Conclusions: During the COVID-19 pandemic, unreliable, incorrect, and incomplete information on its prevention spread in societies. It is recommended that health-related rumors be ‎investigated and officials publicly announce the results.‎

Employee Benefits Program Valuation with Multiple Decrement Model Based on PSAK 24 Post-COVID-19 Pandemic

In this article, we evaluate the post-labor compensation program based on PSAK-24 in the new normal era of the COVID-19 pandemic. In order to create a table multiple decrements based on a single table decrement namely, death, withdrawal, total permanent disability, and retirement. In the new normal era of the COVID-19 pandemic, the benefits of death, death caused by COVID-19, withdrawal, total permanent disability, and retirement were then aggregated. The method used in this study is a quantitative method with a case study approach of COVID-19. The data used is secondary data on the number of COVID-19 positive cases in Indonesia from January 2021 to December 2022. In this study, an actuarial model, the Multiple Decrement Model, was applied to calculate the valuation of the post-labor compensation program based on PSAK-24 using five decrements as the cause of claims consisting of death, death cause of COVID-19, withdrawal, total permanent disability and retirement. The calculation results that can be seen that large annual net premiums multiple decrement cases that provide benefits according to the cause of failure getting bigger as that person gets older.

Artificial intelligence in healthcare: combining deep learning and Bayesian optimization to forecast COVID-19 confirmed cases.

Healthcare is a topic of significant concern within the academic and business sectors. The COVID-19 pandemic has had a considerable effect on the health of people worldwide. The rapid increase in cases adversely affects a nation's economy, public health, and residents' social and personal well-being. Improving the precision of COVID-19 infection forecasts can aid in making informed decisions regarding interventions, given the pandemic's harmful impact on numerous aspects of human life, such as health and the economy. This study aims to predict the number of confirmed COVID-19 cases in Saudi Arabia using Bayesian optimization (BOA) and deep learning (DL) methods. Two methods were assessed for their efficacy in predicting the occurrence of positive cases of COVID-19. The research employed data from confirmed COVID-19 cases in Saudi Arabia (SA), the United Kingdom (UK), and Tunisia (TU) from 2020 to 2021. The findings from the BOA model indicate that accurately predicting the number of COVID-19 positive cases is difficult due to the BOA projections needing to align with the assumptions. Thus, a DL approach was utilized to enhance the precision of COVID-19 positive case prediction in South Africa. The DQN model performed better than the BOA model when assessing RMSE and MAPE values. The model operates on a local server infrastructure, where the trained policy is transmitted solely to DQN. DQN formulated a reward function to amplify the efficiency of the DQN algorithm. By examining the rate of change and duration of sleep in the test data, this function can enhance the DQN model's training. Based on simulation findings, it can decrease the DQN work cycle by roughly 28% and diminish data overhead by more than 50% on average.

Nanoencapsulation of Curcumin compounds from Curcuma plants (Curcuma xanthorrhiza) as an anticoagulant therapy in Covid-19 patients

Introduction: The COVID-19 is brought about by the SARS-CoV-2 virus (Severe Acute Respiratory Syndrome Coronavirus-2). This pandemic has become a problem in various parts of the world due to the increasing number of positive COVID-19 cases. Severe COVID-19 patients often experience coagulopathy such as thrombosis and venous thromboembolism, which are associated with increased mortality. COVID-19 patients who have coagulopathy have increased D-dimer concentrations, prolonged prothrombin time (PT) or activated partial thromboplastin time (aPTT), increased fibrinogen, and thrombocytopenia. The objective of this study is to find an alternative solution for COVID-19 patients who have coagulopathy using the literature review method by searching the data from in vitro, in vivo, and clinical reports by analyzing the potential of the curcumin compound from ginger as an anticoagulant therapy in Covid-19 patients through its thrombosis, platelet, and anti-inflammatory mechanisms. Main Text. The nanoencapsulation of curcumin from Curcuma plants (Curcuma xanthorrhiza) can be an alternative prophylactic anticoagulant for COVID-19 patients. This research uses a qualitative method of conceptual analysis, where the focus of the research is based on pre-existing concepts, which are then understood and developed so that they can be described clearly and can be implemented in the field. The result is curcumin can inhibit the pathways of blood coagulation, so it could be the key to reducing mortality. Conclusion: Nanoencapsulation has proven to be suitable for alternative application in COVID-19 patients considering bioavailability, effectiveness, and minimum side effects.

Evaluation of an infection control protocol to limit COVID-19 at residential summer camps in 2021.

To assess the effectiveness of an infection control protocol developed to mitigate the spread of COVID-19 at two multi-week residential summer camps in 2021. Data were collected from 595 camp attendees and staff members at two wilderness camps in Northern Minnesota. Testing was undertaken in all unvaccinated campers before arrival at camp, on day 4 of camp, and in the event of respiratory symptoms. Campers were limited to cohorts during the first 4 days of camp and wore masks indoors. The number of positive COVID-19 cases measured the efficacy of the protocol. The testing and cohorting protocol successfully prevented the spread of COVID-19 among campers and staff. During the first summer session, there were zero positive cases of COVID-19 among 257 campers and 127 staff. During the second summer session, compliance with the protocol limited the spread of COVID-19 to just three individuals of 266 campers and 129 staff. Maintaining cohorts at arrival limited spread from a single positive case to only two tent companions. The testing and cohorting protocol limited the spread of COVID-19 among residential summer wilderness campers and staff. Post-arrival testing ensured newly acquired virus was limited in spread before COVID-19 precautions were relaxed on camp day 5. A strict evidence-based cohorting protocol limited in-camp spread and allowed for a successful summer camp season. The usefulness of this protocol with an evolving pandemic, increasing vaccination rates, and virus variants could have implications for future practice.

Factors associated with child marriage during the COVID-19 pandemic in Indonesia

AbstractThe aim of this study is to investigate factors associated with the applications of child marriage dispensation submitted to the Religious Courts during the COVID-19 pandemic in Indonesia, particularly in 2019–2021. The number of child marriage dispensation cases was analyzed together with other socioeconomic variables, including poverty and jobless rates, junior and senior high school completion rates, number of cerai talak (a divorce initiated by the husband) and cerai gugat (a divorce initiated by the wife) applications, number of COVID-19 positive cases, and number of deaths by COVID-19. The differences between 2021 and 2019 were analyzed using the paired t-test and repeated measures analysis of variance (ANOVA). The relationship between variables was analyzed using the Pearson product-moment correlation coefficient. Hierarchical multiple regression with the entering method was used to determine the predictors of the number of child marriage dispensation cases in the years 2019, 2020, and 2021 and the change from 2019 to 2021. New dispensation underage marriage applications in 2019, 2020, and 2021 were 24,457 (M =843, SD =1519), 63,391 (M = 2186, SD = 4085), and 62,167 (M = 2144, SD = 4058), which were significantly different (F(1.0, 28.6) = 7.63, p = .01) and positively correlated with poverty rate, jobless rate, cerai talak, cerai gugat, COVID-19 positive cases, and COVID-19 death cases. The multiple regression analysis for the change of dispensation underage marriage applications in the pandemic and before (years 2021–2019) was statistically significant, (F(6,22) = 117.62, p < .001), which the final model was able to account for 97% of the variance in new dispensation underage marriage applications. Collaborative multi-sector works are needed to decrease the skyrocketing child marriage numbers, especially in a crisis situation like the COVID-19 pandemic.

Community Knowledge and Stigma About COVID-19: An Indonesian Perspective

Corona Virus Disease (COVID-19) is a new infectious disease caused by a type of coronavirus. The high number of positive COVID-19 cases in Indonesia has created a negative stigma against people who are exposed to it, not even positive patients who get negative stigma. Knowledge is the community's way of understanding COVID-19 and knowing how dangerous the disease is by assessing every aspect of prevention and transmission by knowing and understanding the COVID-19 disease. This study aims to determine the relationship between knowledge and stigma in society about COVID-19, so that efforts to prevent the occurrence of social stigma related to COVID-19 that are sustainable in society can be carried out. The research method uses a quantitative design with a cross-sectional approach. The sampling technique used purposive sampling with 170 respondents. The results showed that the public's knowledge about COVID-19 consisted of 88 people (51.8%) of whom the majority had sufficient knowledge. Meanwhile, community stigma about COVID-19 was found 122 people (71.8%) did not have stigma. The results of the correlation test found that the p-value was 0.441 > 0.05, meaning that there was no significant relationship between knowledge and public stigma about COVID-19. It is not enough just to know about COVID-19 to minimize stigma in the community, other factors need to be investigated.

The Effect of Covid-19 on Voters in the Medan Tuntungan District Election in 2020

The Covid Sickness (Coronavirus) flare-up that happens in all nations in this present reality is progressively widespread. This instance of pneumonia of obscure etiology or Coronavirus was first recognized in Wuhan City, Hubei Area, China on December 31, 2019. Medan City is one of the regions that held regional elections for the mayoral election, In the 2020 Medan city election, Medan was included in the red zone area where one of the areas with a positive number of covid-19 reached 4,261 people with this number Medan city accounting for 75 percent of corona virus cases in North Sumatra. But in fact, with the large number of positive Covid-19 cases in the city of Medan, there is no decrease in public enthusiasm to come to the Polling Station (TPS) compared to previous elections in Medan. This study uses a type of quantitative research because this study seeks to analyze whether there is an influence of the COVID-19 pandemic on voter participation in Medan Tuntungan sub-district. This type of research is a type of descriptive research. Influence of Covid-19 on Voters in the Medan Tuntungan District Election in 2020 is as follows: Voter participation in Medan Tuntungan District is also influenced by other variables outside the Covid-19 pandemic variable, which is 83.8%, so it is appropriate if research related to voter participation is carried out again using other variables outside the Covid-19 pandemic variable.

Nutrition Intake, Physical Activity, and Sleep Quality in the Month of Fast During Covid-19 Pandemic

Central Java is one of the provinces with the highest number of positive Covid-19 cases in Indonesia, with 46,903 positive infected cases, with a death rate of 2,110 people (4.49%). During the COVID-19 pandemic, community activities decrease, especially during the fasting month. Their diet has also changed. This study aimed to describe and analyse the relationship between nutritional intake and physical activity on people's sleep quality during the fasting month during the COVID-19 pandemic. The benefit of this research is to provide information on factors related to people's sleep quality, so as to improve public health. The novelty of this research is on aspects of physical activity, and people's sleep quality during the fasting month during the covid-19 pandemic. This research method is observational using a cross-sectional approach. The research was conducted during the fasting month (Ramadan 2021) to find out the nutritional intake, physical activity, and quality of people's sleep while fasting amid the COVID-19 pandemic. This study was attended by 520 respondents who were willing to fill out a questionnaire distributed via Googleform. Respondents in this study were limited to people who live in Central Java. The selection of respondents using the cluster sampling technique and then the snowball method. The questionnaires were the Pittsburgh Sleep Quality Index (PSQI), IPAQ and DQI. The results showed no relationship between physical activity and slept quality during the fasting month (p : 0.402). There is a relationship between food consumption, sleep quality (p: 0.0001), and physical activity (0.007) during the fasting month.

A counterfactual analysis of opioid-involved deaths during the COVID-19 pandemic using a spatiotemporal random forest modeling approach.

The global pandemic of SARS-CoV-2 (COVID-19) has been linked to adversely impacting individuals with opioid use disorder in the United States. This study focuses on analyzing opioid-involved mortality in the context of COVID-19 in the U.S. from a geospatial perspective. We investigated spatiotemporal patterns of opioid-involved deaths during 2020 and compared the spatiotemporal pattern of these deaths with patterns for the previous three years (2017-2019) to understand changes in the context of the COVID-19 pandemic. A counterfactual analysis framework together with a space-time random forest (STRF) model were used to estimate the increase in opioid-involved deaths related to the pandemic. To gain further insight into the relationship between opioid deaths and COVID-19-related factors, we built a space-time random forest model for the City of Chicago, that experienced a steep increase in opioid-related deaths during 2020. High ranking indicators identified by the model such as the number of positive COVID-19 cases adjusted by population and the change in stay-at-home dwell time during the pandemic were used to generate a vulnerability index for opioid overdoses during the COVID-19 pandemic in Chicago.

Has Covid-19 permanently changed online purchasing behavior?

This study examines how the COVID-19 pandemic has affected online purchasing behavior using data from a major online shopping platform in Japan. We focus on the effect of two measures of the pandemic, i.e., the number of positive COVID-19 cases and state declarations of emergency to mitigate the pandemic. We find that both measures promoted online purchases at the beginning of the pandemic, but in later periods, their effect faded. In addition, online purchases returned to normal after states of emergency ended, and the overall time trend in online purchases excluding the effects of the two measures was stable during the first two years of the pandemic. These results suggest that the effect of the pandemic on online purchasing behavior is temporary and will not persist after the pandemic.

Moving Direction Entropy as Index for Inter-community Activity

Since we presented the Stay with Your Community principle for suppressing the infection spread at the social level, policies on SWYC have been considered in the context of the tradeoff between the risk of infection spreading and the benefit of inter-community interaction on productive and innovative social activities. In this paper, Moving Direction Entropy is defined as a value representing the diversity of humans’ moving direction in each region. This value had been found to be positively correlated with the number of COVID-19 positive cases, and here it is shown to be in positive correlation with the regional population of inbound flow and its increase during the analyzed period from 2019 through 2022. The results have double implications (1) the dynamics of regional populations, regarded as the enhancement of inter-community interaction, diversify the movements and (2) such dynamics are likely to foster infection spreading.

Household secondary attack rate of COVID 19 and its associated housing factors affecting transmission

: Overcrowding and household environments are high-risk settings for transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To calculate the household secondary attack rate among household contacts of confirmed case of COVID-19. 2) To elicit the housing factors affecting the transmission of infection. 3) To know the sociodemographic of the discharge patients.A prospective study was conducted among the COVID 19 laboratory-confirmed discharged patients admitted at District Covid Hospital, Designated Covid health centre from period May 2020 to July 2020. Total 94 patients were able to contact telephonically. Sociodemographic details were taken after informed Verbal consent. Those who are not able to contact telephonically or didn't give consent are excluded. Household secondary attack rate is 14.5%. Mean rooms per person were 2.8 with a standard deviation of 1.38. The mean age of the patients was 39 years with a standard deviation of 14.9. A mild negative correlation between the number of positive COVID-19 cases and rooms per person (r= −0.045, p>0.05) and mild negative correlation was seen with the number of family members and proportion of family members (positive COVID-19 cases in family/total members in the family) being infected by COVID-19 (r= −0.20, p>0.05). Infection control and preventive strategies of household transmission such as good ventilation, isolation precautions of infected person at home, household disinfecting procedures, wearing of mask at home, hand hygiene needs to be encouraged at household level to lower the Secondary attack rate before recommendation of home isolation and home quarantine measures.

Pre- and post-COVID-19: The impact of the pandemic and stock market psychology on the growth and sustainability of consumer goods industries.

The objective of this study is to investigate the impact of the COVID-19 pandemic and stock market psychology on investor investment decisions in different business units operating in the Shandong stock market. The sample size of the study consists of 5,000 individuals from six different business units. The study used the event study statistical technique to analyze the market reaction to newly released information from the stock market perspective to assess whether the number of COVID-19 positive cases impacted it. With a Z score value of 40.345 and a P-value of 0.000, the Wilcoxon test indicated that stock prices before and after the pandemic were quite different. The test showed a positive relationship between the pandemic and the stock market. Further, the results indicated that COVID-19 and stock market psychology had a significant positive impact on investor investment decisions in cosmetic and beauty, consumer household, textiles and apparel, and consumer electronics industries; however, in the sporting and consumer appliance industries, it had an insignificant negative impact. This study serves to guide investors to make suitable changes in their stock market trading practices to counter these challenges to increase their required rate of return from their specific stock market investment. The findings have important insights for various stakeholders including governments, regulatory bodies, practitioners, academia, industry, and researchers.

Field experiment of signs promoting hand hygiene during the COVID-19 pandemic.

During the COVID-19 pandemic, the U.S. public was encouraged to practice good hand hygiene, such as hand washing or the use of hand sanitizer. Young adults reported lower levels of hand hygiene compared to adults of other ages. The aim of the current study was to test the effectiveness of different messages to promote hand sanitizer use among young adults. Over a 6-week period, we examined whether 3 brief messages (gain-frame, static descriptive norms, dynamic descriptive norms), placed next to sanitizer dispensers in university residence halls, predicted dispenser use in comparison to dispensers with no sign. Amount of sanitizer usage was measured 3 times per week via the weight of dispenser units. We tracked and controlled for the number of positive COVID-19 cases in residence halls because we expected it might influence sanitizer usage. Compared to no signage, dispensers with signs had 35% greater usage, with the static descriptive norms sign associated with greatest usage (46% compared to no sign), although differences did not reach conventional levels of significance. The strongest predictor of sanitizer use was a residence hall's degree of COVID-19 risk based on the hall's case positivity. Dispensers with signs had higher use than those without signs, but this difference was not statistically significant. We conclude that compared to prior research, "nudges" such as evidence-based messaging may have had less of an effect on health behavior engagement due to methodological differences across studies or characteristics of the COVID-19 context. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

COVID-19 Communication Management on Facebook Pages of Local Governments

We examine how Italian municipalities manage the COVID-19 communication on their official Facebook pages. For this purpose, we apply an automatic topic modelling procedure on a sample of 76,139 posts published on the official Facebook pages of 103 Italian provincial capital municipalities over the COVID-19 pandemic period from 1 March 2020 to 26 March 2021. We identify two topics related to COVID-19 consisting of COVID-19 restrictive measures and COVID-19 support measures. Using regression models with municipality and year-week fixed effects, we find that the prevalence of the topic on COVID-19 restrictive measures negatively affects the tone of the communication, computed through a sentiment analysis procedure, and it is negatively associated with the number of COVID-19 positive cases in the municipal area. In contrast, the prevalence of the topic on COVID-19 support measures positively affects the tone of the communication and it is positively associated with the number of positive cases. These associations are moderated by ideology, age, and political incentives of incumbent mayors. These results may reveal a strategic communication of municipalities to induce positive perceptions about the performance of municipal incumbents in responding to the pandemic and, therefore, enhance political consensus among voters. Finally, these findings may have practical implications for public regulators, public managers, and other followers of local governments’ social media.

Influence of Weather Conditions on COVID-19 Case in Several Regions of Indonesia

This study investigates the relationship between COVID-19 and weather conditions in six regions in Indonesia, namely South Jakarta, East Jakarta, North Jakarta, Jember Regency, Semarang City, and West Pasaman Regency. The study uses the daily number of positive cases of COVID-19 and weather data. Weather parameters used in this study are the average, maximum, and minimum temperature, rainfall, and relative humidity. Weather data were obtained from surface observation of Agency for Meteorology, Climatology and Geophysics (BMKG) and reanalysis product (ERA-5) from European Centre for Medium-Range Weather Forecasts (ECMWF). The effect of weather conditions on the number of COVID-19 cases was evaluated using the Spearman and Kendall correlation. It was found that the number of positive cases of COVID-19 had a relationship with weather parameters. A negative correlation was found between the temperature and the number of positive COVID-19 cases. Thus, the number of positive COVID-19 cases increases when the temperature decreases. On the other hand, rainfall and relative humidity positively correlate to the number of positive cases of COVID-19, which means that when the rainfall and relative humidity increase, the number of positive cases of COVID-19 increases. The relationship between weather conditions and the number of COVID-19 cases is more apparent in areas with a higher population density, such as Jakarta. The results of this study can be valuable information in handling COVID-19 cases.

Prediction of the Development of Covid-19 Case in Indonesia Based on Google Trend Analysis

The global outbreak of the coronavirus disease (COVID-19) has recently hit many countries around the world. Indonesia is one of the 10 most affected countries. Search engines such as Google provide data on search activity in a population, and this data may be useful for analyzing epidemics. Leveraging data mining methods on electronic resource data can provide better insights into the COVID-19 outbreak to manage health crises in every country and around the world. This study aims to predict the incidence of COVID-19 by utilizing data from the Covid 19 Task Force and the Google Trends website. Linear regression and long-term memory (LSTM) models were used to estimate the number of positive COVID-19 cases.

Prediction of the Development of Covid-19 Case in Indonesia Based on Google Trend Analysis

The global outbreak of the coronavirus disease (COVID-19) has recently hit many countries around the world. Indonesia is one of the 10 most affected countries. Search engines such as Google provide data on search activity in a population, and this data may be useful for analyzing epidemics. Leveraging data mining methods on electronic resource data can provide better insights into the COVID-19 outbreak to manage health crises in every country and around the world. This study aims to predict the incidence of COVID-19 by utilizing data from the Covid 19 Task Force and the Google Trends website. Linear regression and long-term memory (LSTM) models were used to estimate the number of positive COVID-19 cases.