The incubation period during the pandemic of COVID-19: a systematic review and meta-analysis

Two biases in incubation time estimation related to exposure

BACKGROUND

Estimation of the SARS-CoV-2 incubation time distribution is hampered by incomplete data about infection. We discuss two biases that may result from incorrect handling of such data. Notified cases may recall recent exposures more precisely (differential recall). This creates bias if the analysis is restricted to observations with well-defined exposures, as longer incubation times are more likely to be excluded. Another bias occurred in the initial estimates based on data concerning travellers from Wuhan. Only individuals who developed symptoms after their departure were included, leading to under-representation of cases with shorter incubation times (left truncation). This issue was not addressed in the analyses performed in the literature.

METHODS

We performed simulations and provide a literature review to investigate the amount of bias in estimated percentiles of the SARS-CoV-2 incubation time distribution.

RESULTS

Depending on the rate of differential recall, restricting the analysis to a subset of narrow exposure windows resulted in underestimation in the median and even more in the 95th percentile. Failing to account for left truncation led to an overestimation of multiple days in both the median and the 95th percentile.

CONCLUSION

We examined two overlooked sources of bias concerning exposure information that the researcher engaged in incubation time estimation needs to be aware of.

Emerging infectious diseases, focus on infection prevention, environmental survival and germicide susceptibility: SARS-CoV-2, Mpox, and Candida auris

BACKGROUND

New and emerging infectious diseases continue to represent a public health threat. Emerging infectious disease threats include pathogens increasing in range (eg, Mpox), zoonotic microbes jumping species lines to cause sustained infections in humans via person-to-person transmission (SARS-CoV-2) and multidrug-resistant pathogens (eg, Candida auris).

MATERIALS AND METHODS

We searched the published English literature and reviewed the selected articles on SARS-CoV-2, Mpox, and Candida auris with a focus on environmental survival, contamination of the patient's hospital environment, susceptibility of the pathogen to antiseptics and disinfectants and infection prevention recommendations.

RESULTS

All three pathogens (ie, SARS-CoV-2, Mpox, and Candida auris) can survive on surfaces for minutes to hours and for Mpox and C auris for days. Currently available antiseptics (eg, 70%-90% alcohol hand hygiene products) are active against SARS-CoV-2, Mpox and C auris. The U.S Environmental Protection Agency provides separate lists of surface disinfectants active against SARS-CoV-2, Mpox, and C auris.

DISCUSSION

The risk of environment-to-patient transmission of SARS-CoV-2, Mpox and Candida auris, is very low, low-moderate and high, respectively. In the absence of appropriate patient isolation and use of personal protection equipment, the risk of patient-to-health care provider transmission of SARS-CoV-2, Mpox, and C auris is high, moderate and low, respectively.

CONCLUSIONS

Appropriate patient isolation, use of personal protective equipment by health care personnel, hand hygiene, and surface disinfection can protect patients and health care personnel from acquiring SARS-CoV-2, Mpox, and C auris from infected patients.

Assessing changes in incubation period, serial interval, and generation time of SARS-CoV-2 variants of concern: a systematic review and meta-analysis

BACKGROUND

After the first COVID-19 wave caused by the ancestral lineage, the pandemic has been fueled from the continuous emergence of new SARS-CoV-2 variants. Understanding key time-to-event periods for each emerging variant of concern is critical as it can provide insights into the future trajectory of the virus and help inform outbreak preparedness and response planning. Here, we aim to examine how the incubation period, serial interval, and generation time have changed from the ancestral SARS-CoV-2 lineage to different variants of concern.

METHODS

We conducted a systematic review and meta-analysis that synthesized the estimates of incubation period, serial interval, and generation time (both realized and intrinsic) for the ancestral lineage, Alpha, Beta, and Omicron variants of SARS-CoV-2.

RESULTS

Our study included 280 records obtained from 147 household studies, contact tracing studies, or studies where epidemiological links were known. With each emerging variant, we found a progressive shortening of each of the analyzed key time-to-event periods, although we did not find statistically significant differences between the Omicron subvariants. We found that Omicron BA.1 had the shortest pooled estimates for the incubation period (3.49 days, 95% CI: 3.13-4.86 days), Omicron BA.5 for the serial interval (2.37 days, 95% CI: 1.71-3.04 days), and Omicron BA.1 for the realized generation time (2.99 days, 95% CI: 2.48-3.49 days). Only one estimate for the intrinsic generation time was available for Omicron subvariants: 6.84 days (95% CrI: 5.72-8.60 days) for Omicron BA.1. The ancestral lineage had the highest pooled estimates for each investigated key time-to-event period. We also observed shorter pooled estimates for the serial interval compared to the incubation period across the virus lineages. When pooling the estimates across different virus lineages, we found considerable heterogeneities (I2 > 80%; I2 refers to the percentage of total variation across studies that is due to heterogeneity rather than chance), possibly resulting from heterogeneities between the different study populations (e.g., deployed interventions, social behavior, demographic characteristics).

CONCLUSIONS

Our study supports the importance of conducting contact tracing and epidemiological investigations to monitor changes in SARS-CoV-2 transmission patterns. Our findings highlight a progressive shortening of the incubation period, serial interval, and generation time, which can lead to epidemics that spread faster, with larger peak incidence, and harder to control. We also consistently found a shorter serial interval than incubation period, suggesting that a key feature of SARS-CoV-2 is the potential for pre-symptomatic transmission. These observations are instrumental to plan for future COVID-19 waves.

Mathematical Modeling of SARS-CoV-2 Transmission between Minks and Humans Considering New Variants and Mink Culling

We formulated and studied mathematical models to investigate control strategies for the outbreak of the disease caused by SARS-CoV-2, considering the transmission between humans and minks. Two novel models, namely SEIR and SVEIR, are proposed to incorporate human-to-human, human-to-mink, and mink-to-human transmission. We derive formulas for the reproduction number R0 for both models using the next-generation matrix technique. We fitted our model to the daily number of COVID-19-infected cases among humans in Denmark as an example, and using the best-fit parameters, we calculated the values of R0 to be 1.58432 and 1.71852 for the two-strain and single-strain models, respectively. Numerical simulations are conducted to investigate the impact of control measures, such as mink culling or vaccination strategies, on the number of infected cases in both humans and minks. Additionally, we investigated the possibility of the mutated virus in minks being transmitted to humans. Our results indicate that to control the disease and spread of SARS-CoV-2 mutant strains among humans and minks, we must minimize the transmission and contact rates between mink farmers and other humans by quarantining such individuals. In order to reduce the virus mutation rate in minks, culling or vaccination strategies for infected mink farms must also be implemented. These measures are essential in managing the spread of SARS-CoV-2 and its variants, protecting public health, and mitigating the potential risks associated with human-to-mink transmission.

Real-world effectiveness of mRNA COVID-19 vaccines in the elderly during the Delta and Omicron variants: Systematic review

BACKGROUND

As of 31 December 2022, there were over 6.6 million coronavirus disease 2019 (COVID-19) deaths and over 651 million cases across 200 countries worldwide. Despite the increase in vaccinations and booster shots, COVID-19 cases and deaths continue to remain high. While the effectiveness of these vaccines has already been established by different manufacturers, the fact remains that these vaccines were created quickly for global emergency use, tested under controlled clinical conditions from voluntary subjects and age groups whose general characteristics may differ from the actual general population.

AIM

To conduct a systematic review to determine the real-world effectiveness of mRNA COVID-19 vaccines in the elderly during the predominance of Delta and Omicron variants in preventing COVID-19 related infection, hospital, intensive care unit (ICU) admission and intubation, and death.

METHODS

A combination of Medical Subject Headings and non-Medical Subject Headings was carried out to identify all relevant research articles that meets the inclusion and exclusion criteria from PubMed, Cochrane, CINAHL, Scopus, ProQuest, Embase, Web of Science, and Google Scholar databases, as well as qualified research studies from pre-print servers using medRxiv and Research Square, published from January 1, 2021 - December 31, 2022.

RESULTS

As per the inclusion and exclusion criteria, the effectiveness of Pfizer-BioNTech and Moderna vaccines were evaluated from an estimated total study population of 26,535,692 using infection, hospital, ICU admission and intubation, and death as outcome measures from studies published between 2021 and 2022, conducted in New York, Finland, Canada, Costa Rica, Qatar, Greece, and Brazil. The risk of bias was evaluated using risk of bias in nonrandomized studies of interventions (ROBINS-I) tool for cohort, case-control, and cross-sectional studies. While clinical trial data on Pfizer-BioNTech and Moderna vaccines demonstrated 94% vaccine effectiveness in the elderly, the results in this study showed that vaccine effectiveness in real-world settings is marginally lower against infection (40%-89%), hospitalization (92%), ICU admission and intubation (98%-85%), and death (77%-87%) with an indication of diminished effectiveness of vaccine over time. Furthermore, 2 doses of mRNA vaccines are inadequate and only provides interim protection.

CONCLUSION

Because of the natural diminishing effectiveness of the vaccine, the need for booster dose to restore its efficacy is vital. From a research perspective, the use of highly heterogeneous outcome measures inhibits the comparison, contrast, and integration of the results which makes data pooling across different studies problematic. While pharmaceutical intervention like vaccination is important to fight an epidemic, utilizing common outcome measurements or carrying out studies with minimal heterogeneity in outcome measurements, is equally crucial to better understand and respond to an international health crisis.

SARS-CoV-2 viral load and shedding kinetics

SARS-CoV-2 viral load and detection of infectious virus in the respiratory tract are the two key parameters for estimating infectiousness. As shedding of infectious virus is required for onward transmission, understanding shedding characteristics is relevant for public health interventions. Viral shedding is influenced by biological characteristics of the virus, host factors and pre-existing immunity (previous infection or vaccination) of the infected individual. Although the process of human-to-human transmission is multifactorial, viral load substantially contributed to human-to-human transmission, with higher viral load posing a greater risk for onward transmission. Emerging SARS-CoV-2 variants of concern have further complicated the picture of virus shedding. As underlying immunity in the population through previous infection, vaccination or a combination of both has rapidly increased on a global scale after almost 3 years of the pandemic, viral shedding patterns have become more distinct from those of ancestral SARS-CoV-2. Understanding the factors and mechanisms that influence infectious virus shedding and the period during which individuals infected with SARS-CoV-2 are contagious is crucial to guide public health measures and limit transmission. Furthermore, diagnostic tools to demonstrate the presence of infectious virus from routine diagnostic specimens are needed.

The Skagit County choir COVID-19 outbreak - have we got it wrong?

OBJECTIVES

Over time, papers or reports may come to be taken for granted as evidence for some phenomenon. Researchers cite them without critically re-examining findings in the light of subsequent work. This can give rise to misleading or erroneous results and conclusions. We explore whether this has occurred in the widely reported outbreak of SARS-CoV-2 at a rehearsal of the Skagit Valley Chorale in March 2020, where it was assumed, and subsequently asserted uncritically, that the outbreak was due to a single infected person.

STUDY DESIGN

Review of original report and subsequent modelling and interpretations.

METHODS

We reviewed and analysed original outbreak data in relation to published data on incubation period, subsequent modelling drawing on the data, and interpretations of transmission characteristics of this incident.

RESULTS

We show it is vanishingly unlikely that this was a single point source outbreak as has been widely claimed and on which modelling has been based.

CONCLUSION

An unexamined assumption has led to erroneous policy conclusions about the risks of singing, and indoor spaces more generally, and the benefits of increased levels of ventilation. Although never publicly identified, one individual bears the moral burden of knowing what health outcomes have been attributed to their actions. We call for these claims to be re-examined and for greater ethical responsibility in the assumption of a point source in outbreak investigations.

Replacement dynamics and the pathogenesis of the Alpha, Delta and Omicron variants of SARS-CoV-2

New SARS-CoV-2 variants causing COVID-19 are a major risk to public health worldwide due to the potential for phenotypic change and increases in pathogenicity, transmissibility and/or vaccine escape. Recognising signatures of new variants in terms of replacing growth and severity are key to informing the public health response. To assess this, we aimed to investigate key time periods in the course of infection, hospitalisation and death, by variant. We linked datasets on contact tracing (Contact Tracing Advisory Service), testing (the Second-Generation Surveillance System) and hospitalisation (the Admitted Patient Care dataset) for the entire length of contact tracing in the England - from March 2020 to March 2022. We modelled, for England, time delay distributions using a Bayesian doubly interval censored modelling approach for the SARS-CoV-2 variants Alpha, Delta, Delta Plus (AY.4.2), Omicron BA.1 and Omicron BA.2. This was conducted for the incubation period, the time from infection to hospitalisation and hospitalisation to death. We further modelled the growth of novel variant replacement using a generalised additive model with a negative binomial error structure and the relationship between incubation period length and the risk of a fatality using a Bernoulli generalised linear model with a logit link. The mean incubation periods for each variant were: Alpha 4.19 (95% credible interval (CrI) 4.13-4.26) days; Delta 3.87 (95% CrI 3.82-3.93) days; Delta Plus 3.92 (95% CrI 3.87-3.98) days; Omicron BA.1 3.67 (95% CrI 3.61-3.72) days and Omicron BA.2 3.48 (95% CrI 3.43-3.53) days. The mean time from infection to hospitalisation was for Alpha 11.31 (95% CrI 11.20-11.41) days, Delta 10.36 (95% CrI 10.26-10.45) days and Omicron BA.1 11.54 (95% CrI 11.38-11.70) days. The mean time from hospitalisation to death was, for Alpha 14.31 (95% CrI 14.00-14.62) days; Delta 12.81 (95% CrI 12.62-13.00) days and Omicron BA.2 16.02 (95% CrI 15.46-16.60) days. The 95th percentile of the incubation periods were: Alpha 11.19 (95% CrI 10.92-11.48) days; Delta 9.97 (95% CrI 9.73-10.21) days; Delta Plus 9.99 (95% CrI 9.78-10.24) days; Omicron BA.1 9.45 (95% CrI 9.23-9.67) days and Omicron BA.2 8.83 (95% CrI 8.62-9.05) days. Shorter incubation periods were associated with greater fatality risk when adjusted for age, sex, variant, vaccination status, vaccination manufacturer and time since last dose with an odds ratio of 0.83 (95% confidence interval 0.82-0.83) (P value < 0.05). Variants of SARS-CoV-2 that have replaced previously dominant variants have had shorter incubation periods. Conversely co-existing variants have had very similar and non-distinct incubation period distributions. Shorter incubation periods reflect generation time advantage, with a reduction in the time to the peak infectious period, and may be a significant factor in novel variant replacing growth. Shorter times for admission to hospital and death were associated with variant severity - the most severe variant, Delta, led to significantly earlier hospitalisation, and death. These measures are likely important for future risk assessment of new variants, and their potential impact on population health.

COVID-19 in one region of New Zealand: a descriptive epidemiological study

OBJECTIVE

To describe the epidemiology of COVID-19 in one region of New Zealand in the context of the national lockdown and provide a reference for comparing infection dynamics and control measures between SARS-Cov-2 strains.  Methods: Epidemiological linking and analysis of COVID-19 cases and their close contacts residing in the geographical area served by the Southern District Health Board (SDHB).  Results: From 13 March to 5 April 5 2020, 186 cases were laboratory-confirmed with wild-type Sars-Cov-2 in SDHB. Overall, 35·1% of cases were attributable to household transmission, 27·0% to non-household, 25·4% to overseas travel and 12·4% had no known epidemiological links. The highest secondary attack rate was observed in households during lockdown (15·3%, 95%CI 10·4-21·5). The mean serial interval in 50 exclusive infector-infectee pairs was 4·0 days (95%CI 3·2-4·7days), and the mean incubation period was 3.4 days (95%CI 2·7-4·2).

CONCLUSIONS

The SARS-CoV-2 incubation period may be shorter than early estimates that were limited by uncertainties in exposure history or small sample sizes.

IMPLICATIONS FOR PUBLIC HEALTH

The continuation of household transmission during lockdown highlights the need for effective home-based quarantine guidance. Our findings of a short incubation period highlight the need to contact trace and isolate as rapidly as possible.

Assessing the Impact of Contact Tracing, Quarantine and Red Zone on the Dynamical Evolution of the Covid-19 Pandemic using the Cellular Automata Approach and the Resulting Mean Field System: A Case study in Mauritius

A cellular automaton (CA) depicting the dynamics of the Covid-19 pandemic, is set up. Unlike the classic CA models, the present CA is an enhanced version, embodied with contact tracing, quarantine and red zones to model the spread of the Covid-19 pandemic. The incubation and illness periods are assimilated in the CA system. An algorithm is provided to showcase the rules governing the CA, with and without the enactment of red zones. By means of mean field approximation, a nonlinear system of delay differential equations (DDE) illustrating the dynamics of the CA is emanated. The concept of red zones is incorporated in the resulting DDE system, forming a DDE model with red zone. The stability analysis of both systems are performed and their respective reproduction numbers are derived. The effect of contact tracing and vaccination on both reproduction numbers is also investigated. Numerical simulations of both systems are conducted and real time Covid-19 data in Mauritius for the period ranged from 5 March 2021 to 2 September 2021, is employed to validate the model. Our findings reveal that a combination of both contact tracing and vaccination is indispensable to attenuate the reproductive ratio to less than 1. Effective contact tracing, quarantine and red zones have been the key strategies to contain the Covid-19 virus in Mauritius. The present study furnishes valuable perspectives to assist the health authorities in addressing the unprecedented rise of Covid-19 cases.

Automatic Detection of Cases of COVID-19 Pneumonia from Chest X-ray Images and Deep Learning Approaches

Machine learning has already been used as a resource for disease detection and health care as a complementary tool to help with various daily health challenges. The advancement of deep learning techniques and a large amount of data-enabled algorithms to outperform medical teams in certain imaging tasks, such as pneumonia detection, skin cancer classification, hemorrhage detection, and arrhythmia detection. Automated diagnostics, which are enabled by images extracted from patient examinations, allow for interesting experiments to be conducted. This research differs from the related studies that were investigated in the experiment. These works are capable of binary categorization into two categories. COVID-Net, for example, was able to identify a positive case of COVID-19 or a healthy person with 93.3% accuracy. Another example is CHeXNet, which has a 95% accuracy rate in detecting cases of pneumonia or a healthy state in a patient. Experiments revealed that the current study was more effective than the previous studies in detecting a greater number of categories and with a higher percentage of accuracy. The results obtained during the model's development were not only viable but also excellent, with an accuracy of nearly 96% when analyzing a chest X-ray with three possible diagnoses in the two experiments conducted.

A comparative overview of SARS-CoV-2 and its variants of concern

In December 2019, the severe acute respiratory syndrome 2 (SARS-CoV-2) coronavirus outbreak began in Wuhan, China, and quickly spread to practically every corner of the globe, killing millions of people. SARS-CoV-2 produced numerous variants, five of which have been identified as variants of concern (VOC) by the World Health Organization (WHO) (Alpha, Beta, Gamma, Delta, and Omicron). We conducted a comparative epidemiological analysis of SARS-CoV-2 and its VOC in this paper. We compared the effects of various spike (S) protein mutations in SARS-CoV-2 and its VOC on transmissibility, illness severity, hospitalization risk, fatality rate, immunological evasion, and vaccine efficacy in this review. We also looked into the clinical characteristics of patients infected with SARS-CoV-2 and its VOC.

Modeling the spread of COVID-19 as a consequence of undocumented immigration toward the reduction of daily hospitalization: Case reports from Thailand

At present, a large number of people worldwide have been infected by coronavirus 2019 (COVID-19). When the outbreak of the COVID-19 pandemic begins in a country, its impact is disastrous to both the country and its neighbors. In early 2020, the spread of COVID-19 was associated with global aviation. More recently, COVID-19 infections due to illegal or undocumented immigration have played a significant role in spreading the disease in Southeast Asia countries. Therefore, the spread of COVID-19 of all countries’ border should be curbed. Many countries closed their borders to all nations, causing an unprecedented decline in global travel, especially cross-border travel. This restriction affects social and economic trade-offs. Therefore, immigration policies are essential to control the COVID-19 pandemic. To understand and simulate the spread of the disease under different immigration conditions, we developed a novel mathematical model called the Legal immigration and Undocumented immigration from natural borders for Susceptible-Infected-Hospitalized and Recovered people (LUSIHR). The purpose of the model was to simulate the number of infected people under various policies, including uncontrolled, fully controlled, and partially controlled countries. The infection rate was parameterized using the collected data from the Department of Disease Control, Ministry of Public Health, Thailand. We demonstrated that the model possesses nonnegative solutions for favorable initial conditions. The analysis of numerical experiments showed that we could control the virus spread and maintain the number of infected people by increasing the control rate of undocumented immigration across the unprotected natural borders. Next, the obtained parameters were used to visualize the effect of the control rate on immigration at the natural border. Overall, the model was well-suited to explaining and building the simulation. The parameters were used to simulate the trends in the number of people infected from COVID-19.

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.

Possibility of the COVID-19 third wave in India: mapping from second wave to third wave

After a consistent drop in daily new coronavirus cases during the second wave of COVID-19 in India, there is speculation about the possibility of a future third wave of the virus. The pandemic is returning in different waves; therefore, it is necessary to determine the factors or conditions at the initial stage under which a severe third wave could occur. Therefore, first, we examine the effect of related multi-source data, including social mobility patterns, meteorological indicators, and air pollutants, on the COVID-19 cases during the initial phase of the second wave so as to predict the plausibility of the third wave. Next, based on the multi-source data, we proposed a simple short-term fixed-effect multiple regression model to predict daily confirmed cases. The study area findings suggest that the coronavirus dissemination can be well explained by social mobility. Furthermore, compared with benchmark models, the proposed model improves prediction R 2 by 33.6%, 10.8%, 27.4%, and 19.8% for Maharashtra, Kerala, Karnataka, and Tamil Nadu, respectively. Thus, the simplicity and interpretability of the model are a meaningful contribution to determining the possibility of upcoming waves and direct pandemic prevention and control decisions at a local level in India.

The impact of school closure intervention during the third wave of the COVID-19 pandemic in Italy: Evidence from the Milan area

Background

In February 2021, the spread of a new variant of SARS-CoV-2 in the Lombardy Region, Italy caused concerns about school-aged children as a source of contagion, leading local authorities to adopt an extraordinary school closure measure. This generated a debate about the usefulness of such an intervention in light of the trade-off between its related benefits and costs (e.g. delays in educational attainment, impact on children and families’ psycho-physical well-being). This article analyses the epidemiological impact of the school closure intervention in the Milan metropolitan area.

Methods

Data from the Agency for Health Protection of the Metropolitan City of Milan allowed analysing the trend of contagion in different age classes before and after the intervention, adopting an interrupted times series design, providing a quasi-experimental counterfactual scenario. Segmented Poisson regression models of daily incident cases were performed separately for the 3–11-year-old, the 12–19-year-old, and the 20+-year-old age groups, examining the change in the contagion curves after the intervention, adjusting for time-varying confounders. Kaplan-Meier survival curves and Cox regression were used to assess the equality of survival curves in the three age groups before and after the intervention.

Results

Net of time-varying confounders, the intervention produced a daily reduction of the risk of contagion by 4% in those aged 3–11 and 12–19 (IRR = 0·96) and by 3% in those aged 20 or more (IRR = 0·97). More importantly, there were differences in the temporal order of contagion decrease between the age groups, with the epidemic curve lowering first in the school-aged children directly affected by the intervention, and only subsequently in the adult population, which presumably indirectly benefitted from the reduction of contagion among children.

Conclusion

Though it was not possible to completely discern the effect of school closures from concurrent policy measures, a substantial decrease in the contagion curves was clearly detected after the intervention. The extent to which the slowdown of infections counterbalanced the social costs of the policy remains unclear.

A 14+7 day quarantine period and a dual nucleic acid testing reagent strategy detect potentially indiscoverable Coronavirus disease 2019 infections in Xiamen, China

Background

Determining what quarantine period and detection strategy are more effective and sustainable remains a challenge for further prevention and social stability.

Methods

From October 2020 to December 2021, 290,547 inbound overseas travelers were subject to government quarantine in Xiamen, China. The detection rate of COVID-19 during different quarantine periods using dual or single nucleic acid testing reagents.

Results

The COVID-19 positive rate was 1.79% (519/290,547). The detection rates during the 7-day, 14-day and 14+7-day quarantine periods using the dual reagents were 78.4%, 91.7%, and 100%, respectively. The detection rate of the 7-day, 14-day and 14+7-day quarantine periods were 73.99%, 86.51%, and 94.22%, respectively, using the Liferiver reagent and 72.25%, 84.59%, and 91.91%, respectively, using the Daan reagent. Based on the 14+7 day strategy, dual nucleic acid testing reagent strategy detected all imported cases, but 30 cases (5.78%) were not detected via Liferiver reagent and 42 (8.09%) cases not detected via Daan reagent.

Conclusion

A 14+7-day quarantine period and dual nucleic acid testing reagent strategy are effective screening methods for COVID-19 among inbound overseas travelers. The superior detection rate of these strategies reduce the risk of secondary transmission of the SARS-CoV-2 virus.

SARS-CoV-2 Risk Quantification Model and Validation Based on Large-Scale Dutch Test Events

In response to the outbreak of SARS-CoV-2, many governments decided in 2020 to impose lockdowns on societies. Although the package of measures that constitute such lockdowns differs between countries, it is a general rule that contact between people, especially in large groups of people, is avoided or prohibited. The main reasoning behind these measures is to prevent healthcare systems from becoming overloaded. As of 2021 vaccines against SARS-CoV-2 are available, but these do not guarantee 100% risk reduction and it will take a while for the world to reach a sufficient immune status. This raises the question of whether and under which conditions events like theater shows, conferences, professional sports events, concerts, and festivals can be organized. The current paper presents a COVID-19 risk quantification method for (large-scale) events. This method can be applied to events to define an alternative package of measures replacing generic social distancing.

COVID-19 presenting after Elective Off-pump Coronary Artery Bypass Grafting and Lessons Learned

Background

Cases of COVID-19 presenting after elective cardiac surgery are rare. Published literature suggests that such cases have a high morbidity and mortality rate. Here, we report a case of COVID-19 presenting after an elective, isolated off-pump coronary artery bypass (OPCAB).

Case presentation

A 65-year-old obese, hypertensive, hypothyroid lady, with moderate left ventricular dysfunction, presenting with unstable angina, tested negative for COVID-19 at admission, having undergone thrombolysis for a recent inferior wall myocardial infarction, at an outside centre, and coronary angiography revealing left main triple vessel disease, developed signs and symptoms of COVID-19, four days after OPCAB. She was diagnosed with moderate COVID-19 infection. Subsequent contact tracing revealed that her husband was suffering from mild COVID-19 infection and was managed in home isolation. Isolation and early supportive management with moist oxygen, steroids, intravenous antibiotics, zinc and vitamin C helped the patient recover. She was followed up at one month, six months, one year and at eighteen months and has been doing well.

Conclusions

A strong clinical suspicion and repeat testing for COVID-19 is required as the diagnosis may often be missed with COVID-19 mimicking the signs and symptoms of post-cardiotomy syndrome. Preferentially dealing with such cases off-pump, thereby avoiding cardio pulmonary bypass-related complications, may improve outcomes. Isolation and early supportive management help. Adequate follow-up is required in all such cases as cardiovascular complications are common, alongside known long-term sequelae, like anxiety, depression, cardio-respiratory complications, venous thromboembolism and even postural orthostatic tachycardia syndrome.

A Longer Quarantine Period May Be Needed for Effective Control of COVID-19 Transmission: Experience From Odisha, India

Background

The novel coronavirus disease (COVID-19) has become pandemic. For effective disease control, quarantine of the infected and exposed cases for an optimal period is critical. Currently, infected individuals are quarantined for 14 days. We tried to check if the quarantine period practiced is optimal in the Indian context.

Methods

This cross-sectional study was conducted in Odisha, India. We compiled and analyzed the information of 152 laboratory-confirmed SARS-CoV-2 positive cases. Descriptive analysis was conducted.

Results

Out of the 152 cases, 80% were males, 9.8% were symptomatic, 66.4% had travel history, and 53.9% had contact with COVID-19 cases. The incubation period ranged from 1-50 days with a median of 19.5 days (IQR: 17-27 days). The median periods were similar according to gender, history of contact, and presence of symptoms. Interestingly, 84.7% of the cases had an incubation period of more than 14 days. To cover 95% and 90% of the individuals, the quarantine period may have to be extended to 38 days and 35 days, respectively.

Conclusion

A longer observed incubation period (minimum 28 days) suggests the extension of the quarantine period for adults beyond the presently practiced 14 days. Considering the fast-spreading outbreak, an extended quarantine period for 28 days or active periodic follow-up could be more effective.

Novel mobility index tracks COVID-19 transmission following stay-at-home orders

Considering the emergence of SARS-CoV-2 variants and low vaccine access and uptake, minimizing human interactions remains an effective strategy to mitigate the spread of SARS-CoV-2. Using a functional principal component analysis, we created a multidimensional mobility index (MI) using six metrics compiled by SafeGraph from all counties in Illinois, Ohio, Michigan and Indiana between January 1 to December 8, 2020. Changes in mobility were defined as a time-updated 7-day rolling average. Associations between our MI and COVID-19 cases were estimated using a quasi-Poisson hierarchical generalized additive model adjusted for population density and the COVID-19 Community Vulnerability Index. Individual mobility metrics varied significantly by counties and by calendar time. More than 50% of the variability in the data was explained by the first principal component by each state, indicating good dimension reduction. While an individual metric of mobility was not associated with surges of COVID-19, our MI was independently associated with COVID-19 cases in all four states given varying time-lags. Following the expiration of stay-at-home orders, a single metric of mobility was not sensitive enough to capture the complexity of human interactions. Monitoring mobility can be an important public health tool, however, it should be modelled as a multidimensional construct.

Analysis of continuous-time Markovian ɛ-SIS epidemics on networks

We analyze continuous-time Markovian ɛ-SIS epidemics with self-infections on the complete graph. The majority of the graphs are analytically intractable, but many physical features of the ɛ-SIS process observed in the complete graph can occur in any other graph. In this work, we illustrate that the timescales of the ɛ-SIS process are related to the eigenvalues of the tridiagonal matrix of the SIS Markov chain. We provide a detailed analysis of all eigenvalues and illustrate that the eigenvalues show staircases, which are caused by the nearly degenerate (but strictly distinct) pairs of eigenvalues. We also illustrate that the ratio between the second-largest and third-largest eigenvalue is a good indicator of metastability in the ɛ-SIS process. Additionally, we show that the epidemic threshold of the Markovian ɛ-SIS process can be accurately approximated by the effective infection rate for which the third-largest eigenvalue of the transition matrix is the smallest. Finally, we derive the exact mean-field solution for the ɛ-SIS process on the complete graph, and we show that the mean-field approximation does not correctly represent the metastable behavior of Markovian ɛ-SIS epidemics.

COVID-19 outbreak response at a nursing hospital in South Korea in the post-vaccination era, including an estimation of the effectiveness of the first shot of the Oxford-AstraZeneca COVID-19 vaccine (ChAdOx1-S)

Objectives

We descriptively reviewed a coronavirus disease 2019 (COVID-19) outbreak at a nursing hospital in Gyeonggi Province (South Korea) and assessed the effectiveness of the first dose of the Oxford-AstraZeneca vaccine in a real-world population.

Methods

The general process of the epidemiological investigation included a public health intervention. The relative risk (RR) of vaccinated and unvaccinated groups was calculated and compared to confirm the risk of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, and vaccine effectiveness was evaluated based on the calculated RR.

Results

The population at risk was confined to ward E among 8 wards of Hospital X, where the outbreak occurred. This population comprised 55 people, including 39 patients, 12 nurses, and 4 caregivers, and 19 cases were identified. The RR between the vaccinated and unvaccinated groups was 0.04, resulting in a vaccine effectiveness of 95.3%. The vaccination rate of the non-patients in ward E was the lowest in the entire hospital, whereas the overall vaccination rate of the combined patient and non-patient groups in ward E was the third lowest.

Conclusion

The first dose of the Oxford-AstraZeneca vaccine (ChAdOx1-S) was effective in preventing SARS-CoV-2 infection. To prevent COVID-19 outbreaks in medical facilities, it is important to prioritize the vaccination of healthcare providers.

Modelling the Effect of the Interaction between Vaccination and Nonpharmaceutical Measures on COVID-19 Incidence

Since December 2019, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly from Wuhan (China) across the globe, affecting more than 200 countries by mid-2021, with over 190 M reported cases and around 4 M fatalities. During the first year of the pandemic, affected countries implemented a variety of nonpharmaceutical interventions to control virus transmission. In December 2020, countries started administering several authorised vaccines under a limited supply scenario. In this context, the aim of this study was to develop a SEIR-type continuous-time deterministic disease model, to determine the impact of interaction between different vaccination scenarios and levels of protection measures on disease incidence. For this, the model incorporates (i) a protection measure including low (self-protection), medium (mobility limitation), high (closure of indoor facilities), and very high (lockdown) protection levels, (ii) quarantine for confirmed cases, and (iii) vaccination rate and efficacy of four types of vaccines (Pfizer, Moderna, Astra Zeneca, and Janssen). The model was verified and evaluated using the response timeline and vaccination strategies and rates in the Basque Country (N. Spain). Once the model performance was validated, different initial phase (when 30% of the population is vaccinated) vaccination scenarios were simulated, including (i) a realistic vaccine limited supply scenario and (ii) four potential full vaccine supply scenarios where a unique vaccine type is administered. Significant differences in disease prevalence and cumulative mortality were found between vaccination scenarios for low and medium-level protection measures. For high-level protection measures, any vaccine scenario is effective at limiting the virus transmission and disease mortality. The results obtained here may vary in further studies since there may be some unpredictable factors/covariates. With this in mind, the model here could be easily applied to other regions or countries, modifying the strategies implemented and initial conditions.

A review of epidemiology and public health control measures of COVID-19 variants in Hong Kong, December 2020 to June 2021

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Hong Kong reported 393 COVID-19 variant cases between December 2020 and June 2021

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h vast majority of variant cases reported in Hong Kong were imported cases

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Only 3 clusters involving local transmission of COVID-19 variants were identified

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Hong Kong's control strategy could have limited community spread of COVID-19 variants

Background

The emergence of coronavirus disease 2019 (COVID-19) variants posed considerable threats to the global public health. We reviewed the epidemiology of variant cases and control measures implemented in Hong Kong.

Methods

The epidemiological characteristics and the temporal trend of the COVID-19 variant cases and local clusters in Hong Kong, and the corresponding public health control measures were reviewed.

Results

Between December 2020 and June 2021, 393 variant cases were reported, including 153, 59 and 79 cases of Alpha, Beta and Delta variants with no Gamma variant. The vast majority (378, 96.2%) were imported cases. Since early June 2021, Delta variant had taken over Alpha as the dominant strain. Public health control measures, including risk-stratified quarantine and testing requirements for inbound travellers, banning of flights from extremely high-risk areas, enhanced contact tracing and quarantine, were implemented. Among the 3 clusters involving local transmissions, 2 were linked to imported cases while the source of the remaining one was unknown.

Discussion

Amid the global surges of COVID-19 variants, Hong Kong had continued to limit and prevent the occurrence of community-wide outbreak. Ongoing control strategies should be constantly reviewed and adjusted in response to the global and local COVID-19 situation.

Heat inactivation of clinical COVID-19 samples on an industrial scale for low risk and efficient high-throughput qRT-PCR diagnostic testing

We report the development of a large scale process for heat inactivation of clinical COVID-19 samples prior to laboratory processing for detection of SARS-CoV-2 by RT-qPCR. With more than 266 million confirmed cases, over 5.26 million deaths already recorded at the time of writing, COVID-19 continues to spread in many parts of the world. Consequently, mass testing for SARS-CoV-2 will remain at the forefront of the COVID-19 response and prevention for the near future. Due to biosafety considerations the standard testing process requires a significant amount of manual handling of patient samples within calibrated microbiological safety cabinets. This makes the process expensive, effects operator ergonomics and restricts testing to higher containment level laboratories. We have successfully modified the process by using industrial catering ovens for bulk heat inactivation of oropharyngeal/nasopharyngeal swab samples within their secondary containment packaging before processing in the lab to enable all subsequent activities to be performed in the open laboratory. As part of a validation process, we tested greater than 1200 clinical COVID-19 samples and showed less than 1 Cq loss in RT-qPCR test sensitivity. We also demonstrate the bulk heat inactivation protocol inactivates a murine surrogate of human SARS-CoV-2. Using bulk heat inactivation, the assay is no longer reliant on containment level 2 facilities and practices, which reduces cost, improves operator safety and ergonomics and makes the process scalable. In addition, heating as the sole method of virus inactivation is ideally suited to streamlined and more rapid workflows such as ‘direct to PCR’ assays that do not involve RNA extraction or chemical neutralisation methods.

Prevalence of SARS-CoV-2 Positivity in Pediatric Surgical Patients Amid the First Wave of the COVID-19 Pandemic in New York City

INTRODUCTION

New York State implemented an 11-week elective surgery ban in response to the coronavirus disease-2019 (COVID-19) pandemic, during which pediatric patients from the 10 New York Presbyterian network hospitals requiring urgent or emergent surgical procedures were cared for at Morgan Stanley Children's Hospital (MSCH).

MATERIALS AND METHODS

Data was abstracted from the electronic medical record of all patients aged 0 to 20 years who had surgery at MSCH from March 23, 2020 to June 7, 2020. Comparative analysis of demographic and clinical data elements between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-positive and negative cohorts was conducted using the Fisher exact tests.

RESULTS

A total of 505 surgical procedures were performed in 451 patients, with 32 procedures (6.3%) performed in 21 SARS-CoV-2-positive children. The prevalence of SARS-CoV-2 positivity in Medicaid beneficiaries was more than twice the prevalence in commercially insured (6.8% vs. 2.6%, P=0.04) children. SARS-CoV-2-positive patients were more likely to undergo multiple surgical procedures (23.8% vs. 7.2%, P=0.02), and to have higher American Society of Anesthesiologists (ASA) class designations (69.8% III to V vs. 47.4% I to II, P=0.03). There was no significant difference in the prevalence of SARS-CoV-2 positivity across sex, age, race, or ethnicity groups, or in emergent case status or surgical procedure type. Thirty-day mortality rate was <0.1% overall, with no deaths in the SARS-CoV-2-positive group.

CONCLUSIONS

During the first wave of the COVID-19 pandemic in New York City, we found a higher prevalence of SARS-CoV-2 positivity in urgent/emergent pediatric surgical patients compared with other institutions in the United States. SARS-CoV-2-positive patients were more likely to be Medicaid beneficiaries, were clinically more complex, and had more surgical procedures.

Epidemiological features of COVID-19 patients with prolonged incubation period and its implications for controlling the epidemics in China

BACKGROUND

COVID-19 patients with long incubation period were reported in clinical practice and tracing of close contacts, but their epidemiological or clinical features remained vague.

METHODS

We analyzed 11,425 COVID-19 cases reported between January-August, 2020 in China. The accelerated failure time model, Logistic and modified Poisson regression models were used to investigate the determinants of prolonged incubation period, as well as their association with clinical severity and transmissibility, respectively.

RESULT

Among local cases, 268 (10.2%) had a prolonged incubation period of > 14 days, which was more frequently seen among elderly patients, those residing in South China, with disease onset after Level I response measures administration, or being exposed in public places. Patients with prolonged incubation period had lower risk of severe illness (OR_adjusted = 0.386, 95% CI: 0.203-0.677). A reduced transmissibility was observed for the primary patients with prolonged incubation period (50.4, 95% CI: 32.3-78.6%) than those with an incubation period of ≤14 days.

CONCLUSIONS

The study provides evidence supporting a prolonged incubation period that exceeded 2 weeks in over 10% for COVID-19. Longer monitoring periods than 14 days for quarantine or persons potentially exposed to SARS-CoV-2 should be justified in extreme cases, especially for those elderly.

Coronavirus Disease (COVID-19) Control between Drug Repurposing and Vaccination: A Comprehensive Overview

Respiratory viruses represent a major public health concern, as they are highly mutated, resulting in new strains emerging with high pathogenicity. Currently, the world is suffering from the newly evolving severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This virus is the cause of coronavirus disease 2019 (COVID-19), a mild-to-severe respiratory tract infection with frequent ability to give rise to fatal pneumonia in humans. The overwhelming outbreak of SARS-CoV-2 continues to unfold all over the world, urging scientists to put an end to this global pandemic through biological and pharmaceutical interventions. Currently, there is no specific treatment option that is capable of COVID-19 pandemic eradication, so several repurposed drugs and newly conditionally approved vaccines are in use and heavily applied to control the COVID-19 pandemic. The emergence of new variants of the virus that partially or totally escape from the immune response elicited by the approved vaccines requires continuous monitoring of the emerging variants to update the content of the developed vaccines or modify them totally to match the new variants. Herein, we discuss the potential therapeutic and prophylactic interventions including repurposed drugs and the newly developed/approved vaccines, highlighting the impact of virus evolution on the immune evasion of the virus from currently licensed vaccines for COVID-19.

Increased risk of death in COVID-19 hospital admissions during the second wave as compared to the first epidemic wave: a prospective, single-centre cohort study in London, UK

BACKGROUND

The second coronavirus disease (COVID-19) epidemic wave in the UK progressed aggressively and was characterised by the emergence and circulation of variant of concern alpha (VOC 202012/01). The impact of this variant on in-hospital COVID-19-specific mortality has not been widely studied. We aimed to compare mortality, clinical characteristics, and management of COVID-19 patients across epidemic waves to better understand the progression of the epidemic at a hospital level and support resource planning.

METHODS

We conducted an analytical, dynamic cohort study in a large hospital in South London. We included all adults (≥ 18 years) with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) who required hospital admission to COVID-19-specific wards between January 2020 and March 2021 (n = 2701). Outcome was COVID-19-specific in-hospital mortality ascertained through Medical Certificate Cause of Death.

RESULTS

In the second wave, the number of COVID-19 admissions doubled, and the crude mortality rate dropped 25% (1.66 versus 2.23 per 100 person-days in second and first wave, respectively). After accounting for age, sex, dexamethasone, oxygen requirements, symptoms at admission and Charlson Comorbidity Index, mortality hazard ratio associated with COVID-19 admissions was 1.62 (95% CI 1.26, 2.08) times higher in the second wave.

CONCLUSIONS

Although crude mortality rates dropped during the second wave, the multivariable analysis suggests a higher underlying risk of death for COVID-19 admissions in the second wave. These findings are ecologically correlated with an increased circulation of SARS-CoV-2 variant of concern 202012/1 (alpha). Availability of improved management, particularly dexamethasone, was important in reducing risk of death.

A snapshot of a pandemic: The interplay between social isolation and COVID-19 dynamics in Brazil

In response to the coronavirus pandemic, governments implemented social distancing, attempting to block the virus spread within territories. While it is well accepted that social isolation plays a role in epidemic control, the precise connections between mobility data indicators and epidemic dynamics are still a challenge. In this work, we investigate the dependency between a social isolation index and epidemiological metrics for several Brazilian cities. Classic statistical methods are employed to support the findings. As a first, initially surprising, result, we illustrate how there seems to be no apparent functional relationship between social isolation data and later effects on disease incidence. However, further investigations identified two regimes of successful employment of social isolation: as a preventive measure or as a remedy, albeit remedy measures require greater social isolation and bring higher burden to health systems. Additionally, we exhibit cases of successful strategies involving lockdowns and an indicator-based mobility restriction plan.

Effects of COVID-19 protective measures on the ophthalmological patient examination with an emphasis on gender-specific differences

Objective

In response to the COVID-19 pandemic, strict hygiene and containment measures have been instituted in the clinical ophthalmological examination to prevent virus transmission. The aim of this study is to assess the effects of these protective measures on the quality of the examination with an emphasis on gender-specific differences.

Methods and analysis

An online survey was sent to ophthalmologists in 10 countries. The collected data included demographics, place of work, current professional status, COVID-19 protective measures and their impact on the quality of the examination. Descriptive statistics were used to analyse the data. Fisher's exact test was used to analyse gender differences.

Results

A total of 120 responses were collected. 54.0% of the respondents identified as female and 43.4% as male. Over 75% agreed that protective measures made the examination conditions more difficult. The major problems were fogging of the lenses (87.6%) or slit lamp oculars (69.9%), reduced operability of the slit lamp due to protective barriers (60.2%) and time delay due to disinfection measures (68.1%). Significantly more women than men reported that they used filtering face piece (FFP2) instead of surgical masks (p=0.02). More male participants reported that they removed their mask to prevent fogging (p=0.01). 31% of all participants felt that the COVID-19 protective measures reduced the overall quality of slit lamp examination and 43.4% reported a reduced quality of fundoscopic examination.

Conclusion

COVID-19 related safety measures reduce the feasibility of the clinical ophthalmological examination. Practicable solutions are required to maintain good examination quality without compromising personal safety.

COVID-19 Outbreak in a Military Unit in Korea

OBJECTIVES

This study presents the response of a military unit to the COVID-19 outbreak in Gyeonggi Province. As soon as two soldiers were identified as index cases, the infectious disease investigators of the Gyeonggi Provincial Government, Korea Disease Control and Prevention Agency and the Armed Forces Epidemiologic Investigation Center, discussed the investigation and response plan for an imminent massive outbreak.

METHODS

The joint immediate response team (IRT) conducted interviews with confirmed patients with COVID-19, reviewed medical records, performed contact tracing using global positioning system (GPS), and undertook a field investigation. For risk assessment, the joint IRT visited all eight sites of the military units and the army chaplain's church to evaluate the transmission risk of each site. The evaluation items included the size of the site, the use of air conditioning, whether windows were opened, and whether masks were worn. A pooled testing was used for a low-risk population to quickly detect the spread of COVID-19 in the military base.

RESULTS

A day before the symptom onset of the index case, the lecturer and >50% of the attendees were infected with COVID-19 while attending a lecture that lasted 2 h and 30 min. Attendees were not wearing masks and were in a poorly ventilated room.

CONCLUSION

Since the disease can be spread before symptom onset, contact tracing must be performed to investigate potential exposures prior to symptom onset and manage any exposed persons.

Distinct weather conditions and human mobility impacts on the SARS-CoV-2 outbreak in Colombia: Application of an artificial neural network approach

The coronavirus disease 2019 (COVID-19) is still spreading fast in several tropical countries after more than one year of pandemic. In this scenario, the effects of weather conditions that can influence the spread of the virus are not clearly understood. This study aimed to analyse the influence of meteorological (temperature, wind speed, humidity and specific enthalpy) and human mobility variables in six cities (Barranquilla, Bogota, Cali, Cartagena, Leticia and Medellin) from different biomes in Colombia on the coronavirus dissemination from March 25, 2020, to January 15, 2021. Rank correlation tests and a neural network named self-organising map (SOM) were used to investigate similarities in the dynamics of the disease in the cities and check possible relationships among the variables. Two periods were analysed (quarantine and post-quarantine) for all cities together and individually. The data were classified in seven groups based on city, date and biome using SOM. The virus transmission was most affected by mobility variables, especially in the post-quarantine. The meteorological variables presented different behaviours on the virus transmission in different biogeographical regions. The wind speed was one of the factors connected with the highest contamination rate recorded in Leticia. The highest new daily cases were recorded in Bogota where cold/dry conditions (average temperature <14 °C and absolute humidity >9 g/m³) favoured the contagions. In contrast, Barranquilla, Cartagena and Leticia presented an opposite trend, especially with the absolute humidity >22 g/m³. The results support the implementation of better local control measures based on the particularities of tropical regions.

Targeted pandemic containment through identifying local contact network bottlenecks

Decision-making about pandemic mitigation often relies upon simulation modelling. Models of disease transmission through networks of contacts–between individuals or between population centres–are increasingly used for these purposes. Real-world contact networks are rich in structural features that influence infection transmission, such as tightly-knit local communities that are weakly connected to one another. In this paper, we propose a new flow-based edge-betweenness centrality method for detecting bottleneck edges that connect nodes in contact networks. In particular, we utilize convex optimization formulations based on the idea of diffusion with p-norm network flow. Using simulation models of COVID-19 transmission through real network data at both individual and county levels, we demonstrate that targeting bottleneck edges identified by the proposed method reduces the number of infected cases by up to 10% more than state-of-the-art edge-betweenness methods. Furthermore, the proposed method is orders of magnitude faster than existing methods.

During the COVID-19 pandemic decision makers frequently face questions like where to impose a lockdown, which traffic to close, and whom to quarantine, all required to be carried out at minimal costs. Establishing cost-effective pandemic control policies requires identifying good targets. New computational models from network theory and epidemic simulations over real contact networks provide a valuable tool for finding the right bottlenecks to target upon. Here we study a computationally efficient network centrality measure that enables us to detect local transmission bottlenecks, i.e., contact edges that are especially important for the spread of disease among small communities or local network structures inside large networks. We find that pandemic intervention strategies that target at local network structures significantly outperform interventions that solely focus on the entire network structure as a whole, which are traditionally believed to be the most effective.

covid19.Explorer: a web application and R package to explore United States COVID-19 data

Appearing at the end of 2019, a novel virus (later identified as SARS-CoV-2) was characterized in the city of Wuhan in Hubei Province, China. As of the time of writing, the disease caused by this virus (known as COVID-19) has already resulted in over three million deaths worldwide. SARS-CoV-2 infections and deaths, however, have been highly unevenly distributed among age groups, sexes, countries, and jurisdictions over the course of the pandemic. Herein, I present a tool (the covid19.Explorer R package and web application) that has been designed to explore and analyze publicly available United States COVID-19 infection and death data from the 2020/21 U.S. SARS-CoV-2 pandemic. The analyses and visualizations that this R package and web application facilitate can help users better comprehend the geographic progress of the pandemic, the effectiveness of non-pharmaceutical interventions (such as lockdowns and other measures, which have varied widely among U.S. states), and the relative risks posed by COVID-19 to different age groups within the U.S. population. The end result is an interactive tool that will help its users develop an improved understanding of the temporal and geographic dynamics of the SARS-CoV-2 pandemic, accessible to lay people and scientists alike.

Review of oral ulcerative lesions in COVID-19 patients: A comprehensive study of 51 cases

Numerous oral manifestations of COVID-19 have been reported in the literatures. Common oral lesions in COVID-19 patients included ulcerations, xerostomia, dysgeusia, gingival inflammation, and erythema. Among them, oral ulceration is the most frequent finding and is present as various but distinct patterns. Thus, we conducted a comprehensive review of 51 COVID-19 patients with oral ulcerative lesions to further analyze the various oral ulcerative lesions in COVID-19 patients. There were a median age of 41.4 years and a slight female predilection in these patients. Most oral lesions manifested as an aphtha-like ulceration but lack of an evidence of recurrent aphthous stomatitis. Some of them were present as herpetiform ulcerations without HSV infection. Widespread ulcerations accompanied with necrosis were observed in the more severe and immunosuppressed older patients. Although some reported patients were asymptomatic, most of them had systemic symptoms concurring or slightly preceding the oral ulcerative lesions and the latency from the onset of systemic symptoms to oral ulcerative lesions were under 10 days, suggesting that oral ulceration was one of the early symptoms of COVID-19. Therefore, the oral ulcerative lesions may be considered as oral markers for early diagnosis of the underlying COVID-19 infection in the asymptomatic patients.

Evaluation of COVID-19 Mitigation Policies in Australia Using Generalised Space-Time Autoregressive Intervention Models

In handling the COVID-19 pandemic, various mitigation policies aiming at slowing the spread and protecting all individuals, especially the vulnerable ones, were implemented. A careful evaluation of the effectiveness of these policies is necessary so that policy-makers can implement informed decisions if another wave of COVID-19 or another pandemic happens in the future. This paper reports an assessment of some policies introduced by the Australian governments using a generalised space-time autoregressive model which incorporates multiple exogenous variables and delay effects. Our results show that the number of daily new cases from the states and territories are influenced by both temporal and spatial aspects. Business and border restrictions are found helpful in reducing the number of new cases a few days after implementation while gathering restrictions may not be effective.

A novel index-based decision support toolkit for safe reopening following a generalized lockdown in low and middle-income countries

While the effectiveness of lockdowns to reduce Coronavirus Disease-2019 (COVID-19) transmission is well established, uncertainties remain on the lifting principles of these restrictive interventions. World Health Organization recommends case positive rate of 5% or lower as a threshold for safe reopening. However, inadequate testing capacity limits the applicability of this recommendation, especially in the low-income and middle-income countries (LMICs). To develop a practical reopening strategy for LMICs, in this study, we first identify the optimal timing of safe reopening by exploring accessible epidemiological data of 24 countries during the initial COVID-19 surge. We find that a safe opening can occur two weeks after the crossover of daily infection and recovery rates while maintaining a negative trend in daily new cases. Epidemiologic SIRM model-based example simulation supports our findings. Finally, we develop an easily interpretable large-scale reopening (LSR) index, which is an evidence-based toolkit-to guide/inform reopening decision for LMICs.

Relation of severe COVID-19 in Scotland to transmission-related factors and risk conditions eligible for shielding support: REACT-SCOT case-control study

BACKGROUND

Clinically vulnerable individuals have been advised to shield themselves during the COVID-19 epidemic. The objectives of this study were to investigate (1) the rate ratio of severe COVID-19 associated with eligibility for the shielding programme in Scotland across the first and second waves of the epidemic and (2) the relation of severe COVID-19 to transmission-related factors in those in shielding and the general population.

METHODS

In a matched case-control design, all 178,578 diagnosed cases of COVID-19 in Scotland from 1 March 2020 to 18 February 2021 were matched for age, sex and primary care practice to 1,744,283 controls from the general population. This dataset (REACT-SCOT) was linked to the list of 212,702 individuals identified as eligible for shielding. Severe COVID-19 was defined as cases that entered critical care or were fatal. Rate ratios were estimated by conditional logistic regression.

RESULTS

With those without risk conditions as reference category, the univariate rate ratio for severe COVID-19 was 3.21 (95% CI 3.01 to 3.41) in those with moderate risk conditions and 6.3 (95% CI 5.8 to 6.8) in those eligible for shielding. The highest rate was in solid organ transplant recipients: rate ratio 13.4 (95% CI 9.6 to 18.8). Risk of severe COVID-19 increased with the number of adults but decreased with the number of school-age children in the household. Severe COVID-19 was strongly associated with recent exposure to hospital (defined as 5 to 14 days before presentation date): rate ratio 12.3 (95% CI 11.5 to 13.2) overall. The population attributable risk fraction for recent exposure to hospital peaked at 50% in May 2020 and again at 65% in December 2020.

CONCLUSIONS

The effectiveness of shielding vulnerable individuals was limited by the inability to control transmission in hospital and from other adults in the household. Mitigating the impact of the epidemic requires control of nosocomial transmission.