Demand for longer quarantine period among common and uncommon COVID-19 infections: a scoping review

LSTM-Powered COVID-19 prediction in central Thailand incorporating meteorological and particulate matter data with a multi-feature selection approach

The COVID-19 pandemic has significantly impacted public health and necessitated urgent actions to mitigate its spread. Monitoring and predicting the outbreak's progression have become vital to devise effective strategies and allocate resources efficiently. This study presents a novel approach utilizing Multivariate Long Short-Term Memory (LSTM) to analyze and predict COVID-19 trends in Central Thailand, particularly emphasizing the multi-feature selection process. To consider a comprehensive view of the pandemic's dynamics, our research dataset encompasses epidemiological, meteorological, and particulate matter features, which were gathered from reliable sources. We propose a multi-feature selection technique to identify the most relevant and influential features that significantly impact the spread of COVID-19 in the region to enhance the model's performance. Our results highlight that relative humidity is the key factor driving COVID-19 transmission in Central Thailand. The proposed multi-feature selection technique significantly improves the model's accuracy, ensuring that only the most informative variables contribute to the predictions, avoiding the potential noise or redundancy from less relevant features. The proposed LSTM model demonstrates its capability to forecast COVID-19 cases, facilitating informed decision-making for public health authorities and policymakers.

COVID-19 isolation and quarantine orders in Berlin-Reinickendorf (Germany): How many, how long and to whom?

Isolating COVID-19 cases and quarantining their close contacts can prevent COVID-19 transmissions but also inflict harm. We analysed isolation and quarantine orders by the local public health agency in Berlin-Reinickendorf (Germany) and their dependence on the recommendations by the Robert Koch Institute, the national public health institute. Between 3 March 2020 and 18 December 2021 the local public health agency ordered 24 603 isolations (9.2 per 100 inhabitants) and 45 014 quarantines (17 per 100 inhabitants) in a population of 266 123. The mean contacts per case was 1.9. More days of quarantine per 100 inhabitants were ordered for children than for adults: 4.1 for children aged 0-6, 5.2 for children aged 7-17, 0.9 for adults aged 18-64 and 0.3 for senior citizens aged 65-110. The mean duration for isolation orders was 10.2 and for quarantine orders 8.2 days. We calculated a delay of 4 days between contact and quarantine order. 3484 contact persons were in quarantine when they developed an infection. This represents 8% of all individuals in quarantine and 14% of those in isolation. Our study quantifies isolation and quarantine orders, shows that children had been ordered to quarantine more than adults and that there were fewer school days lost to isolation or quarantine as compared to school closures. Our results indicate that the recommendations of the Robert Koch Institute had an influence on isolation and quarantine duration as well as contact identification and that the local public health agency was not able to provide rigorous contact tracing, as the mean number of contacts was lower than the mean number of contacts per person known from literature. Additionally, a considerable portion of the population underwent isolation or quarantine, with a notable number of cases emerging during the quarantine period.

"Low-risk groups" deserve more attention than "high-risk groups" in imported COVID-19 cases

Objective

To estimate the optimal quarantine period for inbound travelers and identify key risk factors to provide scientific reference for emerging infectious diseases.

Methods

A parametric survival analysis model was used to calculate the time interval between entry and first positive nucleic acid test of imported cases in Guangzhou, to identify the influencing factors. And the COVID-19 epidemic risk prediction model based on multiple risk factors among inbound travelers was constructed.

Results

The approximate 95th percentile of the time interval was 14 days. Multivariate analysis found that the mean time interval for inbound travelers in entry/exit high-risk occupations was 29% shorter (OR 0.29, 95% CI 0.18-0.46, p < 0.0001) than that of low-risk occupations, those from Africa were 37% shorter (OR 0.37, 95% CI 0.17-0.78, p = 0.01) than those from Asia, those who were fully vaccinated were 1.88 times higher (OR 1.88, 95% CI 1.13-3.12, p = 0.01) than that of those who were unvaccinated, and those in other VOC periods were lower than in the Delta period. Decision tree analysis showed that a combined entry/exit low-risk occupation group with Delta period could create a high indigenous epidemic risk by 0.24.

Conclusion

Different strata of imported cases can result in varying degrees of risk of indigenous outbreaks. "low-risk groups" with entry/exit low-risk occupations, fully vaccinated, or from Asia deserve more attention than "high-risk groups."

Global border restrictions in 2020-2021: Adherence and the effectiveness in long-term COVID-19 epidemic control

BACKGROUND

Restrictions on international travel were widely applied to contain cross-border COVID-19 diffusion, while such applications varied globally, and little was known about their impacts on the long-term epidemic progression.

METHODS

We explored the global diversity in maintaining border policies classified to four levels (screening, quarantine, ban on regions and total border closure) using data of 185 countries and regions between 01 January 2020 to 31 December 2021. By using Ordinary least squares (OLS) regression and quantile regression (QR) models, we examined the relationship between total COVID-19 incidence and the cumulative duration of each policy level in 2020-2021, and the heterogeneity of such association across different transmission severity countries.

RESULTS

Firstly, "ban on regions" was the most durable policy applied in high-income countries, while in low-income countries, less stringent measures of screening and quarantine arrivals were applied the longest. Secondly, the cumulatively longer maintenance of the border quarantine was significantly associated with lower infections (log) in COVID-19 high-prevalent countries (75th QR, coefficient estimates [β] = -0.0038, 95% confidence interval: -0.0066 to -0.0010). By contrast, in medium and high transmission severity countries, those with longer duration of imposing bans on regions showed no suppressing effects but significantly higher COVID-19 incidence (OLS regression, β = 0.0028, 95% CI: 0.0009-0.0047; 75th QR, β = 0.0039, 95% CI: 0.0014-0.0063). No other significant results were found.

CONCLUSION

From the long-term perspective, inbound quarantine was effective in mitigating severe epidemics. However, in countries with medium or high COVID-19 prevalence, our findings of ban on regions highlighted its ineffectiveness in the long-term epidemic progression.

Incubation period of wild type of SARS-CoV-2 infections by age, gender, and epidemic periods

Background

The incubation period of the coronavirus disease 2019 (COVID-19) is estimated to vary by demographic factors and the COVID-19 epidemic periods.

Objective

This study examined the incubation period of the wild type of SARS-CoV-2 infections by the different age groups, gender, and epidemic periods in South Korea.

Methods

We collected COVID-19 patient data from the Korean public health authorities and estimated the incubation period by fitting three different distributions, including log-normal, gamma, and Weibull distributions, after stratification by gender and age groups. To identify any temporal impact on the incubation period, we divided the study period into two different epidemic periods (Period-1: 19 January−19 April 2020 and Period-2: 20 April−16 October 2020), and assessed for any differences.

Results

We identified the log-normal as the best-fit model. The estimated median incubation period was 4.6 (95% CI: 3.9–4.9) days, and the 95th percentile was 11.7 (95% CI: 10.2–12.2) days. We found that the incubation period did not differ significantly between males and females (p = 0.42), age groups (p = 0.60), and the two different epidemic periods (p = 0.77).

Conclusions

The incubation period of wild type of SARS-CoV-2 infection during the COVID-19 pandemic 2020, in South Korea, does not likely differ by age group, gender and epidemic period.

Biological Properties of SARS-CoV-2 Variants: Epidemiological Impact and Clinical Consequences

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a virus that belongs to the coronavirus family and is the cause of coronavirus disease 2019 (COVID-19). As of May 2022, it had caused more than 500 million infections and more than 6 million deaths worldwide. Several vaccines have been produced and tested over the last two years. The SARS-CoV-2 virus, on the other hand, has mutated over time, resulting in genetic variation in the population of circulating variants during the COVID-19 pandemic. It has also shown immune-evading characteristics, suggesting that vaccinations against these variants could be potentially ineffective. The purpose of this review article is to investigate the key variants of concern (VOCs) and mutations of the virus driving the current pandemic, as well as to explore the transmission rates of SARS-CoV-2 VOCs in relation to epidemiological factors and to compare the virus's transmission rate to that of prior coronaviruses. We examined and provided key information on SARS-CoV-2 VOCs in this study, including their transmissibility, infectivity rate, disease severity, affinity for angiotensin-converting enzyme 2 (ACE2) receptors, viral load, reproduction number, vaccination effectiveness, and vaccine breakthrough.

COVID-19 Infection in Academic Dental Hospital Personnel; A Cross-Sectional Survey in Saudi Arabia

BACKGROUND

Close patient contact is an essential component of clinical dental education, which can expose students and faculty to risk of COVID-19 and its sequelae.

METHODS

The study was a cross-sectional survey conducted among faculty and clinical students at an academic dental hospital in Al Madinah western Saudi Arabia. An online questionnaire was distributed to collect data on prevalence, risk factors, clinical manifestations, and long-term health and socioeconomic complications of COVID-19 infection.

RESULTS

Prevalence of COVID-19 was 19.6% among a total of 316 students and faculty. Participants cited family and friends as the primary source of infection (40.3%). Among cross-infection control practices, they cited failure to practice distancing as the primary reason for infection transmission (61.3%). The disease was symptomatic in 85.5% of infected personnel. Most frequently reported clinical manifestations were: fever, cough, malaise, and diarrhoea (74.1%, 56.5%, 40.3%, 32.3%, respectively). A proportion of 37.1% of infected personnel stated that they had long COVID-19, and 58.3% of infected students reported deteriorated academic achievement.

CONCLUSIONS

One in five of clinical dental students and their faculty had COVID-19. Most cases were symptomatic, and a large proportion developed long COVID or adverse socioeconomic consequences. Regardless of the severity of symptoms encountered during the acute stage of COVID-19 infection, all infected dental healthcare personnel should be followed, especially those who report long COVID. Continuous follow-up and assistance for infected students may be warranted to mitigate the potential academic and mental drawbacks caused by the pandemic. Dental schools should adopt clear policies regarding COVID-19 transmission and prevention and should implement them in their infection-control education and training.

The incubation period of COVID-19: a global meta-analysis of 53 studies and a Chinese observation study of 11 545 patients

BACKGROUND

The incubation period is a crucial index of epidemiology in understanding the spread of the emerging Coronavirus disease 2019 (COVID-19). In this study, we aimed to describe the incubation period of COVID-19 globally and in the mainland of China.

METHODS

The searched studies were published from December 1, 2019 to May 26, 2021 in CNKI, Wanfang, PubMed, and Embase databases. A random-effect model was used to pool the mean incubation period. Meta-regression was used to explore the sources of heterogeneity. Meanwhile, we collected 11 545 patients in the mainland of China outside Hubei from January 19, 2020 to September 21, 2020. The incubation period fitted with the Log-normal model by the coarseDataTools package.

RESULTS

A total of 3235 articles were searched, 53 of which were included in the meta-analysis. The pooled mean incubation period of COVID-19 was 6.0 days (95% confidence interval [CI] 5.6-6.5) globally, 6.5 days (95% CI 6.1-6.9) in the mainland of China, and 4.6 days (95% CI 4.1-5.1) outside the mainland of China (P = 0.006). The incubation period varied with age (P = 0.005). Meanwhile, in 11 545 patients, the mean incubation period was 7.1 days (95% CI 7.0-7.2), which was similar to the finding in our meta-analysis.

CONCLUSIONS

For COVID-19, the mean incubation period was 6.0 days globally but near 7.0 days in the mainland of China, which will help identify the time of infection and make disease control decisions. Furthermore, attention should also be paid to the region- or age-specific incubation period.