Incubation Period Of COVID-19 Research Articles

An Investigation on Inception V3 Network Models for Disease Severity Identification

Due to the high incubation period of COVID-19 and the use of restricted data, it is difficult to anticipate the number of casualties and the rate at which the virus would spread in the COVID-19 scenario. Monitoring those who are impacted and those who have interacted with them is perhaps the most difficult procedure. Since COVID-19 does require 14 days to incubate, it is doubtful that patients have been detected earlier. Patients have the ability to influence everyone they interact with while they are in the designated incubation period. Typically, the various machine learning algorithms are given the COVID-19 deep properties in order to classify the illness severity levels. Consequently, this may help in the early diagnosis of COVID-19. The created a deep feature extraction and classification model that successfully classified the COVID-19 severity levels using a variety of deep and machine learning algorithms. It has the ability to classify COVID-19 severity levels for early, accurate diagnosis. Ultimately, the results showed that the Inception V3 classifier outperformed all other models in both feature extraction and classificational, successfully extracting deep features from CT images and classifying the severity levels of COVID-19 infection. The testing results also showed that the classification of deep characteristics achieves promising use in COVID-19 severity prediction and diagnosis.

Investigation on KAP Model of Urban Residents in Prevention and Control of COVID-19

Objective: To investigate the knowledge, attitude and practice of the residents in Changxing community in the prevention and control of novel coronavirus pneumonia, and put forward targeted suggestions for formulating epidemic prevention and control measures. Methods: Convenience sampling method was used to invite residents to fill in the self-designed questionnaire online. Results: Total of 294 valid questionnaires were obtained. Among them, the awareness rates of the infectious source, transmission route, incubation period and epidemic situation of COVID-19 were 84.7%, 94.2%, 90.1% and 83.0% respectively. The proportions of judging that COVID-19 has high infectious characteristics, low mortality and high cure rate were 89.5%, 40.1% and 62.6%. The proportions of mastering the knowledge of preventive behaviors such as wearing masks, avoiding family and friends' gatherings, and washing hands correctly were 98.0%, 96.6% and 90.8%; The level of attitude towards epidemic prevention and control measures and awareness of prevention behavior exceeded 90%. Conclusion: The knowledge, attitude and practice of residents in Changxing community on COVID-19 are good.

On bias reduction in parametric estimation in stage structured development models

Abstract Multi-stage models for cohort data are popular statistical models in several fields such as disease progressions, biological development of plants and animals, and laboratory studies of life cycle development. A Bayesian approach on adopting deterministic transformations in the Metropolis–Hastings (MH) algorithm was used to estimate parameters for these stage structured models. However, the biases in later stages are limitations of this methodology, especially the accuracy of estimates for the models having more than three stages. The main aim of this paper is to reduce these biases in parameter estimation. In particular, we conjoin insignificant previous stages or negligible later stages to estimate parameters of a desired stage, while an adjusted MH algorithm based on deterministic transformations is applied for the non-hazard rate models. This means that current stage parameters are estimated separately from the information of its later stages. This proposed method is validated in simulation studies and applied for a case study of the incubation period of COVID-19. The results show that the proposed methods could reduce the biases in later stages for estimates in stage structured models, and the results of the case study can be regarded as a valuable continuation of pandemic prevention.

The application of SIR model in COVID-19

The SIR model was used to better comprehend and analyse the transmission dynamics of COVID-19. This mathematical framework splits the population into three compartments: suspectable, infectious, and recovered, allowing disease spread to be simulated across time. After making some essential assumptions of SIR model, the project illustrates the rate of suspectable, infected, recovered individuals over time by constructing several differential equations using specific parameters. Also, SIR model gives insights into expected disease trajectories, the impact of therapies, and other pertinent discoveries by including critical factors and assumptions. Researchers successfully anticipate disease trajectories using this simulation, indicating the usefulness of actions in preventing viral propagation. Researchers have found that the incubation period of COVID-19 has vital impact on the epidemic curve, which results in a slower growth in the number of infected people overtime and a delay in the upward slope of the infectious in the epidemic curve. The SIR models examination of epidemic curves has assisted in identifying the peak of infections, estimating the duration of outbreaks, and assessing the efficiency of public health measures in various context. Further study, continued data collecting, and integration with real-world data will improve the accuracy and usefulness of the SIR model, enabling evidence-based ways to combating COVID-19s issues.

The Correlates and Predictive Factors of Work Stress, Job Satisfaction, and Resilience in Nurses in the Post-COVID-19 Era

Individuals in the asymptomatic incubation period of COVID-19 are highly contagious. This threat of asymptomatic transmission contributes to increased stress among nursing staffs and undermines their resilience. This study was designed to explore the correlates and predictive factors of resilience in the contexts of work stress and job satisfaction among nursing staffs. A cross-sectional study design was employed on a convenience sample of 408 nurses. The survey included a demographic datasheet, the Nurse Occupational Stressor Scale, Job Satisfaction Scale, and Resilience Scale. Inferential statistics were conducted using independent sample t test, Pearson correlation analysis, and stepwise multiple linear regression. The participants were an average 32.6 years old. The average resilience score indicated a "moderate" resilience level. Resilience was treated as the dependent variable, while the demographic variables, Nurse Occupational Stressor Scale score, and job satisfaction dimension scores were treated as independent variables. Stepwise regression analysis was used to identify the key predictors of resilience, which included professional autonomy and development (β = .468, p <.001), occupational hazards (β = .163, p <.001), interpersonal interaction and collaboration (β = .223, p < .001), self-perceived economic status (β = -.093, p < .05), supervisor's leadership style (β = -.118, p < .05), and marital status (β = .078, p < .05). The model explained 39.4% of the total variance. The results of this study support healthcare providers promoting resilience in several specific ways. Healthcare organizations should enhance professional competence through professional education and training programs; improve workplace safety; foster an atmosphere conducive to team cooperation; provide job support through mentorship and apprenticeship systems and caring leadership from nursing supervisors; continuously conduct caring and stress-relief activities; and utilize online self-report health questionnaires to enable nursing staff facing psychological and emotional challenges to seek professional counseling and support. Enhancing resilience strategies on a long-term basis can improve the mental health of nursing staff, which may be expected to enhance the quality of patient care.

Measuring the missing: Knowledge, risk perceptions and self-protection practices of COVID-19 among the Asian population in New Zealand: An online survey

AimAsians are the second largest and fastest growing non-European population in New Zealand but are under-researched in terms of their COVID-19 pandemic response. The paper aims to illustrates Asians’ risk perceptions and knowledge of COVID-19, and self-protection practices to avoid infection and prevent community transmission.Subject and methodsAn online survey was used to collect data and received 402 valid responses. Data analyses included: 1) a descriptive analysis by using Chi-square tests and a Kruskal-Wallis rank sum tests to explore associations between responses and the four demographic variables (i.e. age, gender, country of origin/ethnicity, and region); and 2) a correlation analysis between different survey objectives.ResultsThe descriptive analysis of the survey found that while ethnicity (within the Asian category) was the most influential variable that resulted in varying responses to many questions, gender and age were other two important variables in influencing the answering patterns. The correlation analysis found a positive correlation between the perceived ‘dangerousness’ of COVID-19 and respondents’ overall compliance behaviour to New Zealand authorities’ recommendations to prevent spread of COVID-19.ConclusionThe majority of the respondents provided correct answers to the questions about the vulnerable populations, symptoms, asymptomatic transmission and potential sequelae of COVID-19; however, their understanding of the availability of a cure for, and the incubation period of COVID-19 was not consistent with the official information. The research also found that the higher perceived dangerousness of COVID-19, the better compliance to self-protection practices among the surveyed population.

Estimate the incubation period of coronavirus 2019 (COVID-19)

COVID-19 is an infectious disease that presents unprecedented challenges to society. Accurately estimating the incubation period of the coronavirus is critical for effective prevention and control. However, the exact incubation period remains unclear, as COVID-19 symptoms can appear in as little as 2 days or as long as 14 days or more after exposure. Accurate estimation requires original chain-of-infection data, which may not be fully available from the original outbreak in Wuhan, China. In this study, we estimated the incubation period of COVID-19 by leveraging well-documented and epidemiologically informative chain-of-infection data collected from 10 regions outside the original Wuhan areas prior to February 10, 2020. We employed a proposed Monte Carlo simulation approach and nonparametric methods to estimate the incubation period of COVID-19. We also utilized manifold learning and related statistical analysis to uncover incubation relationships between different age and gender groups. Our findings revealed that the incubation period of COVID-19 did not follow general distributions such as lognormal, Weibull, or Gamma. Using proposed Monte Carlo simulations and nonparametric bootstrap methods, we estimated the mean and median incubation periods as 5.84 (95% CI, 5.42–6.25 days) and 5.01 days (95% CI 4.00–6.00 days), respectively. We also found that the incubation periods of groups with ages greater than or equal to 40 years and less than 40 years demonstrated a statistically significant difference. The former group had a longer incubation period and a larger variance than the latter, suggesting the need for different quarantine times or medical intervention strategies. Our machine-learning results further demonstrated that the two age groups were linearly separable, consistent with previous statistical analyses. Additionally, our results indicated that the incubation period difference between males and females was not statistically significant.

The COVID-19 pandemic and the exchange rate: a lesson learned from Indonesia

This paper aims to capture the relationship between the COVID-19 pandemic and the exchange rate. We utilized high-frequency data by utilizing daily data from January 21st, 2020, through June 29th, 2022. In contrast to the vast majority of research that disregards the incubation period of COVID-19 in the number of daily transmission cases, we use the growth of COVID-19 as a 14-day moving average of confirmed cases as the main independent variables. Findings indicate that the devaluation of the rupiah exchange rate is long-term associated with the increase in COVID-19 cases and deaths. According to the efficient market hypothesis, the rupiah depreciates due to the increase of COVID-19 transmission, which is publicized by the media. In the midst of the debate over the impact of the pandemic on the exchange rate and using Indonesia as a lesson learned for emerging market economies, our research is a recent study that examines this topic with completed data-generating processes – when the pandemic entered its last wave phase. In regard to exchange rate behavior, the disease outbreak channel exists. The government must restrict widespread media coverage of data on the spread of COVID-19 while focusing on accelerating measures to control the pandemic. A low-interest rate imposed by the monetary authorities as an effort to stimulate economic recovery can also exert pressure on the exchange rate, necessitating the optimization of other instruments, such as foreign exchange intervention.

Low-Cost Systematic Methodology for Rapidly Constructing a Physiological Monitoring Interface in ICU

During the COVID-19 pandemic, which emerged in 2020, many patients were treated in isolation wards because of the high infectivity and long incubation period of COVID-19. Therefore, monitoring systems have become critical to patient care and to safeguard medical professional safety. The user interface is very important to the surveillance system; therefore, we used web technology to develop a system that can create an interface based on user needs. When the surveillance scene needs to be changed, the surveillance location can be changed at any time, effectively reducing the costs and time required, so that patients can achieve timely and appropriate goals of treatment. ZigBee was employed to develop a monitoring system for intensive care units (ICUs). Unlike conventional GUIs, the proposed GUI enables the monitoring of various aspects of a patient, and the monitoring interface can be modified according to the user needs. A simulated ICU environment monitoring system was designed to test the effectiveness of the system. The simulated environment and monitoring nodes were set up at positions consistent with the actual clinical environments to measure the time required to switch between the monitoring scenes or targets on the GUI. A novel system that can construct ZigBee-simulated graphical monitoring interfaces on demand was proposed in this study. The locations of the ZigBee monitoring nodes in the user interface can be changed at any time. The time required to deploy the monitoring system developed in this study was 4 min on average, which is much shorter than the time required for conventional methods (131 min). The system can effectively overcome the limitations of the conventional design methods for monitoring interfaces. This system can be used to simultaneously monitor the basic physiological data of numerous patients, enabling nursing professionals to instantly determine patient status and provide appropriate treatments. The proposed monitoring system can be applied to remote medical care after official adoption.

A study of the impact of policy interventions on daily COVID scenario in India using interrupted time series analysis

Abstract Objectives The rapid increase both in daily cases and daily deaths made the second wave of COVID-19 pandemic in India more lethal than the first wave. Record number of infections and casualties were reported all over India during this period. Delhi and Maharashtra are the two most affected places in India during the second wave. So in response to this, the Indian government implemented strict intervention policies (“lockdowns”, “social distancing” and “vaccination drive”) in every state during this period to prohibit the spread of this virus. The objective of this article is to conduct an interrupted time series (ITS) analysis to study the impact of the interventions on the daily cases and deaths. Methods We collect daily data for Delhi and Maharashtra before and after the intervention points with a 14-day (incubation period of COVID-19) observation window. A segmented linear regression analysis is done to study the post-intervention slopes as well as whether there were any immediate changes after the interventions or not. We also add the counterfactuals and delayed time effects in the analysis to investigate the significance of our ITS design. Results Here, we observe the post-intervention trends to be statistically significant and negative for both the daily cases and the daily deaths. We also find that there is no immediate change in trend after the start of intervention, and hence we study some delayed time effects which display how changes in the trends happened over time. And from the Counterfactuals in our study, we can have an idea what would have happened to the COVID scenario had the interventions not been implemented. Conclusions We statistically try to figure out different circumstances of COVID scenario for both Delhi and Maharashtra by exploring all possible ingredients of ITS design in our analysis in order to present a feasible design to show the importance of implementation of proper intervention policies for tackling this type of pandemic which can have various highly contagious variants.

Gender-based incidence, recovery period, and mortality rate of COVID-19 among the population of district Attock, Pakistan.

COVID-19 is reported as an extremely contagious disease with common symptoms of fever, dry cough, sore throat, and tiredness. The published literature on incidence and gender-wise prevalence of COVID-19 is scarce in Pakistan. Therefore, the present study was designed to compare the distribution, incubation period and mortality rate of COVID-19 among the male and female population of district Attock. The data were collected between 01 April 2020 and 07 December 2020 from the population of district Attock, Pakistan. A total of 22,962 individuals were screened and 843 were found positive for RT-qPCR for SARS-CoV-2. The confirmed positive cases were monitored carefully. Among the positive cases, the incidence of COVID-19 was 61.7% among males and 38.2% among females. The average recovery period of males was 18.89±7.75 days and females were 19±8.40 days from SARS-CoV-2. The overall mortality rate was 8.06%. The death rate of male patients was significantly higher (P<0.05) compared to female patients. Also, the mortality rate was higher (P<0.05) in male patients of 40-60 years of age compared to female patients of the same age group. Moreover, the mortality rate significantly increased (P<0.05) with the increase of age irrespective of gender. In conclusion, the incidence and mortality rate of COVID-19 is higher in males compared to the female population. Moreover, irrespective of gender the mortality rate was significantly lower among patients aged <40 years.

Analysis of COVID-19's Influence on Enterprise Management Performance

COVID-19 outbreak in early 2020 had a serious impact on the management performance of enterprises because of the long incubation period and strong infectivity of Covid-19. Taking the listed companies covered by domestic CSI 500 Index and US S&P 500 Index from 2018 to 2020 as the research object, this article makes a comparative study on the impact of sudden COVID-19 epidemic on the operating performance of listed companies and its action path. The results show that the epidemic situation has a negative impact on business performance by reducing the asset utilization efficiency of enterprises and increasing the comprehensive cost rate; Domestic epidemic prevention policies have promoted the improvement of business performance, and the impact of domestic enterprises on the epidemic situation will be less than that of the United States in 2020; In addition, the extent to which enterprises are affected by the epidemic is closely related to their industries, the nature of property rights and the degree of epidemic prevention and control in their regions. This study extends the analysis of influencing factors of business performance to the field of public health, reveals the path of public health events' influence on business performance, and provides reference for improving business performance during the epidemic period.

Predictors of Mortality among COVID-19 Patients - A Case Control Study at Tertiary Care Center, Nanded (Maharashtra).

The novel Coronavirus is belonging to the family of SARS & MERS-CoV, the impact of the earlier is more dreadful as demonstrated by the steady increase in morbid cases. The average incubation period of COVID-19 is 1-14 days with a mean of 6 days. Aim - To evaluate predictors of mortality among COVID-19 patients. Objectives - 1. To assess risk predictors associated with mortality among COVID-19 patients 2. To a suggest prediction model for preventing mortality in future outbreaks. Study design - A case-control study. Study place -Tertiary care center, Nanded, Maharashtra. The present study included 400 cases that died off due to Covid-19 and 400 controls survived COVID-19 disease in a 1:1 proportion. On admission, a significant difference was observed among cases and controls with reference to the percentage of SpO2 (p < 0.05). The proportion of associated co-morbidities among cases was very high i.e., 75.75% as compared to controls with a proportion of 29.25% co-morbidities. The median days of hospital stay were significantly lower in cases compared to controls (3 days vs 12 days, P < 0.001). Length of hospital stay (in days) was showing a significant difference among cases and control (3 days Vs 12 days); hospital stay was less (median 3 days) for cases, as they reported late and thus died earlier; hence concluded that early hospital admission will decrease chances of death due to COVID-19.

Study on Knowledge and Perception towards COVID-19 Disease among 3rd Year Medical Students of Sir Salimullah Medical College and Mitford Hospital, Dhaka, Bangladesh

This descriptive cross sectional study was conducted to determine the level of knowledge &amp; perception towards COVID-19 disease among 3rd year medical students of Sir Salimullah Medical College &amp; Mitford Hospital. This study was done in the period of September, 2021 to April, 2022. Our sample size was 152, and data was collected over the telephone with a semi-structured questionnaire. Most of the respondents (61.18%) were female, majority (86.18%) were Muslim. Among them most of the respondents 43(27.04%) were from Khulna division. From our study, we found that all of the students (100%) stated that they heard about covid, mild covid patients can recover at home &amp; hand hygiene, social distancing help in prevention of COVID. Among them most of the students (43.42%) heard about the ongoing pandemic from News &amp; Social Media. Among the respondents almost all of them (99.34%) knew about the incubation period of COVID-19, which is 2-14 days. Most of them (71.02%) knew about the symptoms of COVID-19 are Fever, Headache, Dry Cough, Sore Throat, Tiredness. It is considered that the findings of the study will serve as a useful basis for further research and planning in covid-19 disease prevention.

Nosocomial transmission of SARS-CoV-2 from infected children to uninfected caregivers: A retrospective cohort study in a Japanese tertiary children's hospital

BackgroundThe transmission rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unclear when caregivers accompany pediatric COVID-19 patients in the same isolation room in a hospital setting. AimWe investigated SARS-CoV-2 transmission from infected children to caregivers at our hospital. MethodsThis retrospective cohort study included 34 discordant pairs of patients admitted between September 2020 and April 2022. FindingsThe median ages of the children and caregivers were 3.7 years (interquartile range [IQR]: 1.6–8.1) and 33.1 years (IQR: 28.3–43.4), respectively. Of the 34 caregivers, 31 were mothers, two were fathers, and one was a relative. Sixteen caregivers received at least two doses of the mRNA vaccine. The mean duration of the hospital stays was 7.7 ± 4.1 days (range: 3–19). Two unvaccinated caregivers developed COVID-19 after admission; the onset was within 48 h after admission. It is likely that they had been infected in their household prior to admission, since the incubation period for COVID-19 is usually >2 days. ConclusionsNosocomial SARS-CoV-2 transmission from infected children to caregivers was not confirmed in this study. The combination of negative-pressure rooms, vaccinations, and infection-control bundles appears to be effective at preventing SARS-CoV-2 transmission. It is acceptable to allow caregivers to accompany pediatric COVID-19 patients in a hospital ward if they can comply with basic infection control measures.

The Association Between Clinical Severity and Incubation Period of SARS-CoV-2 Delta Variants: Retrospective Observational Study.

As of August 25, 2021, Jiangsu province experienced the largest COVID-19 outbreak in eastern China that was seeded by SARS-CoV-2 Delta variants. As one of the key epidemiological parameters characterizing the transmission dynamics of COVID-19, the incubation period plays an essential role in informing public health measures for epidemic control. The incubation period of COVID-19 could vary by different age, sex, disease severity, and study settings. However, the impacts of these factors on the incubation period of Delta variants remains uninvestigated. The objective of this study is to characterize the incubation period of the Delta variant using detailed contact tracing data. The effects of age, sex, and disease severity on the incubation period were investigated by multivariate regression analysis and subgroup analysis. We extracted contact tracing data of 353 laboratory-confirmed cases of SARS-CoV-2 Delta variants' infection in Jiangsu province, China, from July to August 2021. The distribution of incubation period of Delta variants was estimated by using likelihood-based approach with adjustment for interval-censored observations. The effects of age, sex, and disease severity on the incubation period were expiated by using multivariate logistic regression model with interval censoring. The mean incubation period of the Delta variant was estimated at 6.64 days (95% credible interval: 6.27-7.00). We found that female cases and cases with severe symptoms had relatively longer mean incubation periods than male cases and those with nonsevere symptoms, respectively. One-day increase in the incubation period of Delta variants was associated with a weak decrease in the probability of having severe illness with an adjusted odds ratio of 0.88 (95% credible interval: 0.71-1.07). In this study, the incubation period was found to vary across different levels of sex, age, and disease severity of COVID-19. These findings provide additional information on the incubation period of Delta variants and highlight the importance of continuing surveillance and monitoring of the epidemiological characteristics of emerging SARS-CoV-2 variants as they evolve.

Pitfalls in Understanding and Handling of Covid-19 Vaccination (“Any Fool Can Know. The Point Is to Understand”)

The aim of this article is to critically review the managing of vaccination over the course of the present COVID-19 pandemic against the knowledge that had already been at hand and the scientific data that had yet to be learned. In the period before vaccines for COVID-19 became available, the startling similarity in epidemiologic behavior between COVID-19 and the Spanish flu could be observed. The development of vaccines against COVID-19 has evolved at an unprecedented speed resulting in highly immunogenic vaccines with incredible protective characteristics covering a relatively short follow-up time in clinical trials. The rollout in the general population turned out to take significantly longer time than the duration of immunity conferred by a 2-dose vaccination schedule (about 3-4 months). Therefore, the SARS-CoV-2 was left with the opportunity for random mutations with each replication cycle, resulting in immune evasion, shortened incubation, shortened serial interval, and increased transmissibility. The short incubation period of COVID-19 requires a steady protective antibody titer to be maintained to avert infection, achieve herd immunity, and terminate the pandemic spread. The protective neutralization titer needed to avert symptomatic infection and infection altogether is about 3% and 20%, respectively, of the mean convalescent titer. The latter corresponds to an absolute titer of 1:10–1:30. The intensity and duration of protective vaccinal and hybrid humoral immunity are explored. From the present perspective, it was naive to believe that a 2-dose vaccination would suffice to counter COVID-19 primarily due to its short incubation and a roll-out that was not catching up with the waning protective vaccinal antibody levels. Besides, the spacing of doses and boosters with respect to previous infection or vaccination, and differences in natural immunity and vaccine-induced immunity (adenovirus-vectored and mRNA) are discussed. The issue of vaccination and multisystem inflammatory syndrome in children is briefly presented. Finally, ethical points are discussed as some vaccine production platforms and neutralization tests use human cell lines derived from aborted fetuses.Conclusion – If the COVID-19 vaccines had been licensed as 3-dose vaccines, with more generous spacing, e.g. 0-2-6 months, providing for quantitatively larger and temporally more durable humoral immunity, that would have enabled attaining a steadier herd immunity and probably a paradoxical earlier effect on stopping the transmission.

Incubation Period of COVID-19 Caused by Unique SARS-CoV-2 Strains

Several studies were conducted to estimate the average incubation period of COVID-19; however, the incubation period of COVID-19 caused by different SARS-CoV-2 variants is not well described. To systematically assess the incubation period of COVID-19 and the incubation periods of COVID-19 caused by different SARS-CoV-2 variants in published studies. PubMed, EMBASE, and ScienceDirect were searched between December 1, 2019, and February 10, 2022. Original studies of the incubation period of COVID-19, defined as the time from infection to the onset of signs and symptoms. Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline, 3 reviewers independently extracted the data from the eligible studies in March 2022. The parameters, or sufficient information to facilitate calculation of those values, were derived from random-effects meta-analysis. The mean estimate of the incubation period and different SARS-CoV-2 strains. A total of 142 studies with 8112 patients were included. The pooled incubation period was 6.57 days (95% CI, 6.26-6.88) and ranged from 1.80 to 18.87 days. The incubation period of COVID-19 caused by the Alpha, Beta, Delta, and Omicron variants were reported in 1 study (with 6374 patients), 1 study (10 patients), 6 studies (2368 patients) and 5 studies (829 patients), respectively. The mean incubation period of COVID-19 was 5.00 days (95% CI, 4.94-5.06 days) for cases caused by the Alpha variant, 4.50 days (95% CI, 1.83-7.17 days) for the Beta variant, 4.41 days (95% CI, 3.76-5.05 days) for the Delta variant, and 3.42 days (95% CI, 2.88-3.96 days) for the Omicron variant. The mean incubation was 7.43 days (95% CI, 5.75-9.11 days) among older patients (ie, aged over 60 years old), 8.82 days (95% CI, 8.19-9.45 days) among infected children (ages 18 years or younger), 6.99 days (95% CI, 6.07-7.92 days) among patients with nonsevere illness, and 6.69 days (95% CI, 4.53-8.85 days) among patients with severe illness. The findings of this study suggest that SARS-CoV-2 has evolved and mutated continuously throughout the COVID-19 pandemic, producing variants with different enhanced transmission and virulence. Identifying the incubation period of different variants is a key factor in determining the isolation period.

Waiting for the COVID-19 vaccine: vaccine intention, trust in authorities and information needs in an Italian sample

ABSTRACT The COVID-19 vaccine development timelines offered a unique opportunity to explore the public’s vaccine intention in an unusual situation characterised by great uncertainty about the vaccine’s features and the disease it intended to prevent. To advance our knowledge of vaccine intention mechanisms under these unusual circumstances, to plan effective vaccination strategies, and to better direct communication efforts in similar scenarios, this study explored i) COVID19-related information needs, information-seeking behaviours, and perceived trustworthiness of news media; ii) COVID-19 vaccination intention and its determinants, during the first wave of COVID-19 pandemic in Italy. In particular, it was investigated whether and to what extent the perception of severity and susceptibility to the infection, trust in authorities, and demographics shaped people’s vaccine intention. Between April and May 2020 in a cross-sectional study, 1373 Italian participants completed an online survey measuring demographic features, perception of the disease severity, disease risk perception, COVID19-related worry, disease-related information needs and behaviours, vaccination intention, and level of trust in authorities and news media. The leading information needs were the COVID-19 incubation period and transmission modalities, with the majority of people actively looking for information from one to three times a day. Despite uncertainty around the details of a COVID-19 vaccination, 68% of participants reported intending to be vaccinated for COVID-19. Greater COVID-19 vaccination intention was associated with having a regular history of seasonal flu vaccine, a greater COVID19-related worry, a higher perception of disease severity, and a higher trust in the Government. These findings further our understanding of vaccine intention in a pandemic scenario where a vaccine is still hypothetical and provide valuable information on the public’s representation of the infection and future acceptance of a vaccine to inform the development of communication interventions aiming to maximise adherence to vaccination programmes and to modify disease-related dysfunctional representations.

The Relationship between Stress Levels and the Performance of Nurses Caring for Covid-19 Patients at Private Hospital, Central Jakarta

Covid-19 is a type of disease that is transmitted from one person to another through (droplets) when coughing or sneezing and the incubation period for COVID-19 is estimated to be between 1-14 days. The purpose of research are known the relationship between stress levels and the performance of nurses caring for Covid-19 patients at St Carolus Hospital, Central Jakarta. Descriptive correlation research with cross-sectional design was used. The sampling technique used purposive sampling and totaled 103 respondents. Data collected with questionnares using Google Forms. The results showed that the majority of respondents had severe stress levels (81.6%) and good performance (88.3%). The results of statistical analysis using Kendal Tau C showed there was no significant relationship between stress levels and nurse performance with p value (p = 0.597). Severe stress levels will affect the health of individuals physically, psychologically, socially and spiritually and have an impact on their performance. The suggestion for hospital can handle stress problems for nurses and maintain good nurse performance.