The incubation period of COVID-19: A meta-analysis

Detection of Common Respiratory Infections, Including COVID-19, Using Consumer Wearable Devices in Health Care Workers: Prospective Model Validation Study

BACKGROUND

The early detection of respiratory infections could improve responses against outbreaks. Wearable devices can provide insights into health and well-being using longitudinal physiological signals.

OBJECTIVE

The purpose of this study was to prospectively evaluate the performance of a consumer wearable physiology-based respiratory infection detection algorithm in health care workers.

METHODS

In this study, we evaluated the performance of a previously developed system to predict the presence of COVID-19 or other upper respiratory infections. The system generates real-time alerts using physiological signals recorded from a smartwatch. Resting heart rate, respiratory rate, and heart rate variability measured during the sleeping period were used for prediction. After baseline recordings, when participants received a notification from the system, they were required to undergo testing at a Northwell Health System site. Participants were asked to self-report any positive tests during the study. The accuracy of model prediction was evaluated using respiratory infection results (laboratory results or self-reports), and postnotification surveys were used to evaluate potential confounding factors.

RESULTS

A total of 577 participants from Northwell Health in New York were enrolled in the study between January 6, 2022, and July 20, 2022. Of these, 470 successfully completed the study, 89 did not provide sufficient physiological data to receive any prediction from the model, and 18 dropped out. Out of the 470 participants who completed the study and wore the smartwatch as required for the 16-week study duration, the algorithm generated 665 positive alerts, of which 153 (23.0%) were not acted upon to undergo testing for respiratory viruses. Across the 512 instances of positive alerts that involved a respiratory viral panel test, 63 had confirmed respiratory infection results (ie, COVID-19 or other respiratory infections detected using a polymerase chain reaction or home test) and the remaining 449 had negative upper respiratory infection test results. Across all cases, the estimated false-positive rate based on predictions per day was 2%, and the positive-predictive value ranged from 4% to 10% in this specific population, with an observed incidence rate of 198 cases per week per 100,000. Detailed examination of questionnaires filled out after receiving a positive alert revealed that physical or emotional stress events, such as intense exercise, poor sleep, stress, and excessive alcohol consumption, could cause a false-positive result.

CONCLUSIONS

The real-time alerting system provides advance warning on respiratory viral infections as well as other physical or emotional stress events that could lead to physiological signal changes. This study showed the potential of wearables with embedded alerting systems to provide information on wellness measures.

Exploring factors shaping antibiotic resistance patterns in Streptococcus pneumoniae during the 2020 COVID-19 pandemic

Non-pharmaceutical interventions implemented to block SARS-CoV-2 transmission in early 2020 led to global reductions in the incidence of invasive pneumococcal disease (IPD). By contrast, most European countries reported an increase in antibiotic resistance among invasive Streptococcus pneumoniae isolates from 2019 to 2020, while an increasing number of studies reported stable pneumococcal carriage prevalence over the same period. To disentangle the impacts of the COVID-19 pandemic on pneumococcal epidemiology in the community setting, we propose a mathematical model formalizing simultaneous transmission of SARS-CoV-2 and antibiotic-sensitive and -resistant strains of S. pneumoniae. To test hypotheses underlying these trends five mechanisms were built into the model and examined: (1) a population-wide reduction of antibiotic prescriptions in the community, (2) lockdown effect on pneumococcal transmission, (3) a reduced risk of developing an IPD due to the absence of common respiratory viruses, (4) community azithromycin use in COVID-19 infected individuals, (5) and a longer carriage duration of antibiotic-resistant pneumococcal strains. Among 31 possible pandemic scenarios involving mechanisms individually or in combination, model simulations surprisingly identified only two scenarios that reproduced the reported trends in the general population. They included factors (1), (3), and (4). These scenarios replicated a nearly 50% reduction in annual IPD, and an increase in antibiotic resistance from 20% to 22%, all while maintaining a relatively stable pneumococcal carriage. Exploring further, higher SARS-CoV-2 R0 values and synergistic within-host virus-bacteria interaction mechanisms could have additionally contributed to the observed antibiotic resistance increase. Our work demonstrates the utility of the mathematical modeling approach in unraveling the complex effects of the COVID-19 pandemic responses on AMR dynamics.

Estimating the Epidemic Size of Superspreading Coronavirus Outbreaks in Real Time: Quantitative Study

BACKGROUND

Novel coronaviruses have emerged and caused major epidemics and pandemics in the past 2 decades, including SARS-CoV-1, MERS-CoV, and SARS-CoV-2, which led to the current COVID-19 pandemic. These coronaviruses are marked by their potential to produce disproportionally large transmission clusters from superspreading events (SSEs). As prompt action is crucial to contain and mitigate SSEs, real-time epidemic size estimation could characterize the transmission heterogeneity and inform timely implementation of control measures.

OBJECTIVE

This study aimed to estimate the epidemic size of SSEs to inform effective surveillance and rapid mitigation responses.

METHODS

We developed a statistical framework based on back-calculation to estimate the epidemic size of ongoing coronavirus SSEs. We first validated the framework in simulated scenarios with the epidemiological characteristics of SARS, MERS, and COVID-19 SSEs. As case studies, we retrospectively applied the framework to the Amoy Gardens SARS outbreak in Hong Kong in 2003, a series of nosocomial MERS outbreaks in South Korea in 2015, and 2 COVID-19 outbreaks originating from restaurants in Hong Kong in 2020.

RESULTS

The accuracy and precision of the estimation of epidemic size of SSEs improved with longer observation time; larger SSE size; and more accurate prior information about the epidemiological characteristics, such as the distribution of the incubation period and the distribution of the onset-to-confirmation delay. By retrospectively applying the framework, we found that the 95% credible interval of the estimates contained the true epidemic size after 37% of cases were reported in the Amoy Garden SARS SSE in Hong Kong, 41% to 62% of cases were observed in the 3 nosocomial MERS SSEs in South Korea, and 76% to 86% of cases were confirmed in the 2 COVID-19 SSEs in Hong Kong.

CONCLUSIONS

Our framework can be readily integrated into coronavirus surveillance systems to enhance situation awareness of ongoing SSEs.

A Brighton Collaboration standardized template with key considerations for a benefit/risk assessment for the Novavax COVID-19 Vaccine (NVX-CoV2373), a recombinant spike protein vaccine with Matrix-M adjuvant to prevent disease caused by SARS-CoV-2 viruses

Novavax, a global vaccine company, began evaluating NVX-CoV2373 in human studies in May 2020 and the pivotal placebo-controlled phase 3 studies started in November 2020; five clinical studies provided adult and adolescent clinical data for over 31,000 participants who were administered NVX-CoV2373. This extensive data has demonstrated a well-tolerated response to NVX-CoV2373 and high vaccine efficacy against mild, moderate, or severe COVID-19 using a two-dose series (Dunkle et al., 2022) [1], (Heath et al., 2021) [2], (Keech et al., 2020) [3], (Mallory et al., 2022) [4]. The most common adverse events seen after administration with NVX-CoV2373 were injection site tenderness, injection site pain, fatigue, myalgia, headache, malaise, arthralgia, nausea, or vomiting. In addition, immunogenicity against variants of interest (VOI) and variants of concern (VOC) was established with high titers of ACE2 receptor-inhibiting and neutralizing antibodies in these studies (EMA, 2022) [5], (FDA, 2023) [6]. Further studies on correlates of protection determined that titers of anti-Spike IgG and neutralizing antibodies correlated with efficacy against symptomatic COVID-19 established in clinical trials (p < 0.001 for recombinant protein vaccine and p = 0.005 for mRNA vaccines for IgG levels) (Fong et al., 2022) [7]. Administration of a booster dose of the recombinant protein vaccine approximately 6 months following the primary two-dose series resulted in substantial increases in humoral antibodies against both the prototype strain and all evaluated variants, similar to or higher than the antibody levels observed in phase 3 studies that were associated with high vaccine efficacy (Dunkle et al., 2022) [1], (Mallory et al., 2022) [4]. These findings, together with the well tolerated safety profile, support use of the recombinant protein vaccine as primary series and booster regimens.

The geographical distribution and socioeconomic risk factors of COVID-19, tuberculosis and leprosy in Fortaleza, Brazil

BACKGROUND

Fortaleza (Brazil) is high endemic for coronavirus disease 2019 (COVID-19), tuberculosis (TB) and leprosy. These three diseases share respiratory droplets through coughing or sneezing as the main mode of transmission but differ in incubation time, with COVID-19 having a short and leprosy a long incubation time. Consequently, contacts of a patient are at higher risk of infection and developing these diseases. There might be scope for combined preventive measures, but a better understanding of the geographical distribution and relevant socioeconomic risk factors of the three diseases is needed first. This study aims to describe the geographic distribution of COVID-19, TB and leprosy incidence and to identify common socioeconomic risk factors.

METHODS

The total number of new cases of COVID-19, TB and leprosy, as well as socioeconomic and demographic variables, were retrieved from official registers. The geographical distribution of COVID-19, TB and leprosy rates per neighbourhood was visualised in Quantum GIS, and spatial autocorrelation was measured with Moran's I in GeoDa. A spatial regression model was applied to understand the association between COVID-19, TB, leprosy rates, and socioeconomic factors.

RESULTS

COVID-19 and TB showed a more homogenous distribution, whereas leprosy is located more in the south and west of Fortaleza. One neighbourhood (Pedras) in the southeast was identified as high endemic for all three diseases. Literacy was a socioeconomic risk factor for all three diseases: a high literacy rate increases the risk of COVID-19, and a low literacy rate (i.e., illiteracy) increases the risk of TB and leprosy. In addition, high income was associated with COVID-19, while low income with TB.

CONCLUSIONS

Despite the similar mode of transmission, COVID-19, TB and leprosy show a different distribution of cases in Fortaleza. In addition, associated risk factors are related to wealth in COVID-19 and to poverty in TB and leprosy. These findings may support policymakers in developing (partially combined) primary and secondary prevention considering the efficient use of resources.

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.

Exercise Effect on Mental Health in Isolating or Quarantining Adults

INTRODUCTION: In response to coronavirus disease 2019 (COVID-19), travelers are typically subject to quarantine, which is often associated with poorer mental health (MH). While the protective benefits of community-based exercise are widely recognized, the degree to which this extends to the confined setting is unknown. This systematic review aims to evaluate the effect of exercise on MH in isolating or quarantining adults.METHODS: A literature search of Ovid MEDLINE, APA PsycInfo, and the Cochrane Database of Systematic Reviews limited to January 2019-September 2021 inclusive yielded five eligible studies.RESULTS: Data comprised a total of 2755 college and university students, most of whom were confined. Depending on the scale used, 24.9-76.7% of respondents demonstrated impaired MH, which improved with physical activity (PA), especially when regular and moderate or vigorous. The frequency, duration, and participants of exercise increased as lockdown progressed. One study showed that while sleep, diet, and PA all have an impact on MH, PA was the factor most strongly correlated with MH.DISCUSSION: Physical fitness should be optimized before and maintained during quarantine while exercise space and equipment should be accessible. Importantly, the sustainability of persistent quarantine must be considered given the pervasiveness of COVID-19.Chu V, Newman DG. Exercise effect on mental health in isolating or quarantining adults. Aerosp Med Hum Perform. 2023; 94(9):686-695.

Evaluation of the EsteR Toolkit for COVID-19 Decision Support: Sensitivity Analysis and Usability Study

BACKGROUND

During the COVID-19 pandemic, local health authorities were responsible for managing and reporting current cases in Germany. Since March 2020, employees had to contain the spread of COVID-19 by monitoring and contacting infected persons as well as tracing their contacts. In the EsteR project, we implemented existing and newly developed statistical models as decision support tools to assist in the work of the local health authorities.

OBJECTIVE

The main goal of this study was to validate the EsteR toolkit in two complementary ways: first, investigating the stability of the answers provided by our statistical tools regarding model parameters in the back end and, second, evaluating the usability and applicability of our web application in the front end by test users.

METHODS

For model stability assessment, a sensitivity analysis was carried out for all 5 developed statistical models. The default parameters of our models as well as the test ranges of the model parameters were based on a previous literature review on COVID-19 properties. The obtained answers resulting from different parameters were compared using dissimilarity metrics and visualized using contour plots. In addition, the parameter ranges of general model stability were identified. For the usability evaluation of the web application, cognitive walk-throughs and focus group interviews were conducted with 6 containment scouts located at 2 different local health authorities. They were first asked to complete small tasks with the tools and then express their general impressions of the web application.

RESULTS

The simulation results showed that some statistical models were more sensitive to changes in their parameters than others. For each of the single-person use cases, we determined an area where the respective model could be rated as stable. In contrast, the results of the group use cases highly depended on the user inputs, and thus, no area of parameters with general model stability could be identified. We have also provided a detailed simulation report of the sensitivity analysis. In the user evaluation, the cognitive walk-throughs and focus group interviews revealed that the user interface needed to be simplified and more information was necessary as guidance. In general, the testers rated the web application as helpful, especially for new employees.

CONCLUSIONS

This evaluation study allowed us to refine the EsteR toolkit. Using the sensitivity analysis, we identified suitable model parameters and analyzed how stable the statistical models were in terms of changes in their parameters. Furthermore, the front end of the web application was improved with the results of the conducted cognitive walk-throughs and focus group interviews regarding its user-friendliness.

Diagnostics and analysis of SARS-CoV-2: current status, recent advances, challenges and perspectives

The disastrous spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has induced severe public healthcare issues and weakened the global economy significantly. Although SARS-CoV-2 infection is not as fatal as the initial outbreak, many infected victims suffer from long COVID. Therefore, rapid and large-scale testing is critical in managing patients and alleviating its transmission. Herein, we review the recent advances in techniques to detect SARS-CoV-2. The sensing principles are detailed together with their application domains and analytical performances. In addition, the advantages and limits of each method are discussed and analyzed. Besides molecular diagnostics and antigen and antibody tests, we also review neutralizing antibodies and emerging SARS-CoV-2 variants. Further, the characteristics of the mutational locations in the different variants with epidemiological features are summarized. Finally, the challenges and possible strategies are prospected to develop new assays to meet different diagnostic needs. Thus, this comprehensive and systematic review of SARS-CoV-2 detection technologies may provide insightful guidance and direction for developing tools for the diagnosis and analysis of SARS-CoV-2 to support public healthcare and effective long-term pandemic management and control.

Retrospective, Observational Studies for Estimating Vaccine Effects on the Secondary Attack Rate of SARS-CoV-2

Coronavirus disease 2019 (COVID-19) vaccines are highly efficacious at preventing symptomatic infection, severe disease, and death. Most of the evidence that COVID-19 vaccines also reduce transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is based on retrospective, observational studies. Specifically, an increasing number of studies are evaluating vaccine effectiveness against the secondary attack rate of SARS-CoV-2 using data available in existing health-care databases or contact-tracing databases. Since these types of databases were designed for clinical diagnosis or management of COVID-19, they are limited in their ability to provide accurate information on infection, infection timing, and transmission events. We highlight challenges with using existing databases to identify transmission units and confirm potential SARS-CoV-2 transmission events. We discuss the impact of common diagnostic testing strategies, including event-prompted and infrequent testing, and illustrate their potential biases in estimating vaccine effectiveness against the secondary attack rate of SARS-CoV-2. We articulate the need for prospective observational studies of vaccine effectiveness against the SARS-CoV-2 secondary attack rate, and we provide design and reporting considerations for studies using retrospective databases.

SARS-CoV-2 incubation period across variants of concern, individual factors, and circumstances of infection in France: a case series analysis from the ComCor study

BACKGROUND

The incubation period of SARS-CoV-2 has been estimated for the known variants of concern. However, differences in study designs and settings make comparing variants difficult. We aimed to estimate the incubation period for each variant of concern compared with the historical strain within a unique and large study to identify individual factors and circumstances associated with its duration.

METHODS

In this case series analysis, we included participants (aged ≥18 years) of the ComCor case-control study in France who had a SARS-CoV-2 diagnosis between Oct 27, 2020, and Feb 4, 2022. Eligible participants were those who had the historical strain or a variant of concern during a single encounter with a known index case who was symptomatic and for whom the incubation period could be established, those who reported doing a reverse-transcription-PCR (RT-PCR) test, and those who were symptomatic by study completion. Sociodemographic and clinical characteristics, exposure information, circumstances of infection, and COVID-19 vaccination details were obtained via an online questionnaire, and variants were established through variant typing after RT-PCR testing or by matching the time that a positive test was reported with the predominance of a specific variant. We used multivariable linear regression to identify factors associated with the duration of the incubation period (defined as the number of days from contact with the index case to symptom onset).

FINDINGS

20 413 participants were eligible for inclusion in this study. Mean incubation period varied across variants: 4·96 days (95% CI 4·90-5·02) for alpha (B.1.1.7), 5·18 days (4·93-5·43) for beta (B.1.351) and gamma (P.1), 4·43 days (4·36-4·49) for delta (B.1.617.2), and 3·61 days (3·55-3·68) for omicron (B.1.1.529) compared with 4·61 days (4·56-4·66) for the historical strain. Participants with omicron had a shorter incubation period than participants with the historical strain (-0·9 days, 95% CI -1·0 to -0·7). The incubation period increased with age (participants aged ≥70 years had an incubation period 0·4 days [0·2 to 0·6] longer than participants aged 18-29 years), in female participants (by 0·1 days, 0·0 to 0·2), and in those who wore a mask during contact with the index case (by 0·2 days, 0·1 to 0·4), and was reduced in those for whom the index case was symptomatic (-0·1 days, -0·2 to -0·1). These data were robust to sensitivity analyses correcting for an over-reporting of incubation periods of 7 days.

INTERPRETATION

SARS-CoV-2 incubation period is notably reduced in omicron cases compared with all other variants of concern, in young people, after transmission from a symptomatic index case, after transmission to a maskless secondary case, and (to a lesser extent) in men. These findings can inform future COVID-19 contact-tracing strategies and modelling.

FUNDING

Institut Pasteur, the French National Agency for AIDS Research-Emerging Infectious Diseases, Fondation de France, the INCEPTION project, and the Integrative Biology of Emerging Infectious Diseases project.

Early-phase pandemic in Italy: Covid-19 spread determinant factors

Although the Covid-19 pandemic is still ongoing, the environmental factors beyond virus transmission are only partially known. This statistical study has the aim to identify the key factors that have affected the virus spread during the early phase of pandemic in Italy, among a wide set of potential determinants concerning demographics, environmental pollution and climate. Because of its heterogeneity in pollution levels and climate conditions, Italy provides an ideal scenario for an ecological study. Moreover, the selected period excludes important confounding factors, as different virus variants, restriction policies or vaccines. The short-term relationship between the infection maximum increase and demographic, pollution and meteo-climatic parameters was investigated, including both winter-spring and summer 2020 data, also focusing separately on the two seasonal periods and on North vs Centre-South. Among main results, the importance of population size confirmed social distancing as a key management option. The pollution hazardous role undoubtedly emerged, as NO₂ affected infection increase in all the studied scenarios, PM_2.5 manifested its impact in North of Italy, while O₃ always showed a protective action. Whereas higher temperatures were beneficial, especially in the cold season with also wind and relative humidity, solar irradiance was always relevant, revealing several significant interactions with other co-factors. Presented findings address the importance of the environment in Sars-CoV-2 spread and indicated that special carefulness should be taken in crowded areas, especially if they are highly polluted and weakly exposed to sun. The results suggest that containment of future epidemics similar to Covid-19 could be supported by reducing environmental pollution, achieving safer social habits and promoting preventive health care for better immune system response, as an only comprehensive strategy.

SARS-CoV-2 infection dynamics and genomic surveillance to detect variants in wastewater - a longitudinal study in Bengaluru, India

Background

Environmental surveillance (ES) of a pathogen is crucial for understanding the community load of disease. As an early warning system, ES for SARS-CoV-2 has complemented routine diagnostic surveillance by capturing near real-time virus circulation at a population level.

Methods

In this longitudinal study conducted between January 2022 and June 2022 in 28 sewershed sites in Bengaluru city (∼11 million inhabitants), we quantified weekly SARS-CoV-2 RNA concentrations to track infection dynamics and provide evidence of change in the relative abundance of emerging variants.

Findings

We describe an early warning system using the exponentially weighted moving average control chart and demonstrate how SARS-CoV-2 RNA concentrations in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 8-14 days earlier in wastewater than in clinical data. This was further corroborated by showing that the estimated number of infections is strongly correlated with SARS-CoV-2 RNA copies detected in the wastewater. Using a deconvolution matrix, we detected emerging variants of concern up to two months earlier in wastewater samples. In addition, we found a huge diversity in variants detected in wastewater compared to clinical samples. The findings from this study have been discussed regularly with local authorities to inform policy-making decisions.

Interpretation

Our study highlights that quantifying viral titre, correlating it with a known number of cases in the area, and combined with genomic surveillance helps in tracking variants of concern (VOC) over time and space, enabling timely and making informed policy decisions.

Funding

This work has been supported by funding from the Rockefeller Foundation grant to National Centre for Biological Sciences, TIFR) and the Indian Council of Medical Research grant to (FI) Tata Institute for Genetics and Society and Tata Trusts.

Wastewater Surveillance Can Function as an Early Warning System for COVID-19 in Low-Incidence Settings

Introduction: During the first two years of the COVID-19 pandemic, Australia implemented a series of international and interstate border restrictions. The state of Queensland experienced limited COVID-19 transmission and relied on lockdowns to stem any emerging COVID-19 outbreaks. However, early detection of new outbreaks was difficult. In this paper, we describe the wastewater surveillance program for SARS-CoV-2 in Queensland, Australia, and report two case studies in which we aimed to assess the potential for this program to provide early warning of new community transmission of COVID-19. Both case studies involved clusters of localised transmission, one originating in a Brisbane suburb (Brisbane Inner West) in July–August 2021, and the other originating in Cairns, North Queensland in February–March 2021. Materials and Methods: Publicly available COVID-19 case data derived from the notifiable conditions (NoCs) registry from the Queensland Health data portal were cleaned and merged spatially with the wastewater surveillance data using statistical area 2 (SA2) codes. The positive predictive value and negative predictive value of wastewater detection for predicting the presence of COVID-19 reported cases were calculated for the two case study sites. Results: Early warnings for local transmission of SARS-CoV-2 through wastewater surveillance were noted in both the Brisbane Inner West cluster and the Cairns cluster. The positive predictive value of wastewater detection for the presence of notified cases of COVID-19 in Brisbane Inner West and Cairns were 71.4% and 50%, respectively. The negative predictive value for Brisbane Inner West and Cairns were 94.7% and 100%, respectively. Conclusions: Our findings highlight the utility of wastewater surveillance as an early warning tool in low COVID-19 transmission settings.

Patient and ward related risk factors in a multi-ward nosocomial outbreak of COVID-19: Outbreak investigation and matched case-control study

BACKGROUND

Risk factors for nosocomial COVID-19 outbreaks continue to evolve. The aim of this study was to investigate a multi-ward nosocomial outbreak of COVID-19 between 1st September and 15th November 2020, occurring in a setting without vaccination for any healthcare workers or patients.

METHODS

Outbreak report and retrospective, matched case-control study using incidence density sampling in three cardiac wards in an 1100-bed tertiary teaching hospital in Calgary, Alberta, Canada. Patients were confirmed/probable COVID-19 cases and contemporaneous control patients without COVID-19. COVID-19 outbreak definitions were based on Public Health guidelines. Clinical and environmental specimens were tested by RT-PCR and as applicable quantitative viral cultures and whole genome sequencing were conducted. Controls were inpatients on the cardiac wards during the study period confirmed to be without COVID-19, matched to outbreak cases by time of symptom onset dates, age within ± 15 years and were admitted in hospital for at least 2 days. Demographics, Braden Score, baseline medications, laboratory measures, co-morbidities, and hospitalization characteristics were collected on cases and controls. Univariate and multivariate conditional logistical regression was used to identify independent risk factors for nosocomial COVID-19.

RESULTS

The outbreak involved 42 healthcare workers and 39 patients. The strongest independent risk factor for nosocomial COVID-19 (IRR 3.21, 95% CI 1.47-7.02) was exposure in a multi-bedded room. Of 45 strains successfully sequenced, 44 (97.8%) were B.1.128 and differed from the most common circulating community lineages. SARS-CoV-2 positive cultures were detected in 56.7% (34/60) of clinical and environmental specimens. The multidisciplinary outbreak team observed eleven contributing events to transmission during the outbreak.

CONCLUSIONS

Transmission routes of SARS-CoV-2 in hospital outbreaks are complex; however multi-bedded rooms play a significant role in the transmission of SARS-CoV-2.

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.

Associations of Country-Specific and Sociodemographic Factors With Self-Reported COVID-19-Related Symptoms: Multivariable Analysis of Data From the CoronaCheck Mobile Health Platform

BACKGROUND

The COVID-19 symptom-monitoring apps provide direct feedback to users about the suspected risk of infection with SARS-CoV-2 and advice on how to proceed to prevent the spread of the virus. We have developed the CoronaCheck mobile health (mHealth) platform, the first free app that provides easy access to valid information about the risk of infection with SARS-CoV-2 in English and German. Previous studies have suggested that the clinical characteristics of individuals infected with SARS-CoV-2 vary by age, gender, and viral variant; however, potential differences between countries have not been adequately studied.

OBJECTIVE

The aim of this study is to describe the characteristics of the users of the CoronaCheck mHealth platform and to determine country-specific and sociodemographic associations of COVID-19-related symptoms and previous contacts with individuals infected with COVID-19.

METHODS

Between April 8, 2020, and February 3, 2022, data on sociodemographic characteristics, symptoms, and reports of previous close contacts with individuals infected with COVID-19 were collected from CoronaCheck users in different countries. Multivariable logistic regression analyses were performed to examine whether self-reports of COVID-19-related symptoms and recent contact with a person infected with COVID-19 differed between countries (Germany, India, South Africa), gender identities, age groups, education, and calendar year.

RESULTS

Most app users (N=23,179) were from Germany (n=8116, 35.0%), India (n=6622, 28.6%), and South Africa (n=3705, 16.0%). Most data were collected in 2020 (n=19,723, 85.1%). In addition, 64% (n=14,842) of the users were male, 52.1% (n=12,077) were ≥30 years old, and 38.6% (n=8953) had an education level of more than 11 years of schooling. Headache, muscle pain, fever, loss of smell, loss of taste, and previous contacts with individuals infected with COVID-19 were reported more frequently by users in India (adjusted odds ratios [aORs] 1.3-8.3, 95% CI 1.2-9.2) and South Africa (aORs 1.1-2.6, 95% CI 1.0-3.0) than those in Germany. Cough, general weakness, sore throat, and shortness of breath were more frequently reported in India (aORs 1.3-2.6, 95% CI 1.2-2.9) compared to Germany. Gender-diverse users reported symptoms and contacts with confirmed COVID-19 cases more often compared to male users.

CONCLUSIONS

Patterns of self-reported COVID-19-related symptoms and awareness of a previous contact with individuals infected with COVID-19 seemed to differ between India, South Africa, and Germany, as well as by gender identity in these countries. Viral symptom-collecting apps, such as the CoronaCheck mHealth platform, may be promising tools for pandemics to support appropriate assessments. Future mHealth research on country-specific differences during a pandemic should aim to recruit representative samples.

COVID-19 self-protective practices and associated factors among secondary school students in Jimma town, Jimma, Oromia, Southwest Ethiopia

Background

Since there is limited evidence regarding COVID-19 self-protective practices among school students, this study assessed COVID-19 self-protective practices and associated factors among secondary school students.

Methods

A school-based cross-sectional study was conducted in Jimma town, Oromia regional state, Southwest Ethiopia from 25 May 2021 to 10 June 2021. The total sample size was 634, and students were randomly selected from public and private secondary schools. A self-administered questionnaire was used for data collection. The data were entered into Epidata 3.1 and analyzed using SPSS 21.0 software. Descriptive statistics, such as proportion and mean, were computed to describe the findings. The composite index was computed for each dimension. A linear regression analysis was used to identify the predictors of self-protective practice. A local polynomial smoothing graph was done using Stata 12 software to visualize the relationship between a significant variable and an outcome variable.

Results

A total of 576 respondents participated in this study, which made a response rate of 90.85%. The mean score for overall knowledge was 31.40 (SD ±8.65). Knowledge about COVID-19 symptoms and preventive practices had a mean score of 23.93 and 45.96, respectively. The mean scores for perceived vulnerability, severity, benefits, barriers, self-efficacy, and school support were 26.37, 33.21, 43.13, 16.15, 33.38, and 25.45, respectively. The mean score for self-protective practice was 28.38 (SD ±11.04). As perceived benefit (AOR = 0.199, p = 0.000, 95% CI: 0.094-0.304), perceived school support (AOR = 0.125, p = 0.009, 95% CI: 0.032-0.218), and self-efficacy (AOR = 0.186, p = 0.000, 95% CI: 0.102-0.270) increased, COVID-19 self-protective practices also increased and vice versa. However, age (AOR = -0.873, p = 0.006, 95% CI = -1.495, -0.251), perceived vulnerability (AOR = -0.107, p = 0.021; 95% CI = -0.199, -0.016), and maternal educational status (no formal education) (AOR = -5.395, p = 0.000, 95% CI = -7.712 to 3.077) had negatively associated with self-protective practices.

Conclusion

COVID-19 self-protective practice is unsatisfactory. Perceived benefit, perceived school support, and self-efficacy are positively associated with it. However, students' age, perceived vulnerability, and maternal educational status (no formal education) were negatively associated with COVID-19 self-protective measures among secondary school students. The findings underscore that there is a need to conduct risk communications among students. Similarly, awareness creation intervention should target mothers with no formal education.

Parameter identifiability and optimal control of an SARS-CoV-2 model early in the pandemic

We fit an SARS-CoV-2 model to US data of COVID-19 cases and deaths. We conclude that the model is not structurally identifiable. We make the model identifiable by prefixing some of the parameters from external information. Practical identifiability of the model through Monte Carlo simulations reveals that two of the parameters may not be practically identifiable. With thus identified parameters, we set up an optimal control problem with social distancing and isolation as control variables. We investigate two scenarios: the controls are applied for the entire duration and the controls are applied only for the period of time. Our results show that if the controls are applied early in the epidemic, the reduction in the infected classes is at least an order of magnitude higher compared to when controls are applied with 2-week delay. Further, removing the controls before the pandemic ends leads to rebound of the infected classes.

An Executed Plan to Combat COVID-19 in the United States

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in late 2019. To date, this coronavirus is responsible for greater than 90 million cases in the United States and more than 1 million confirmed deaths. When this virus came to the United States, testing was unorganized, no effective treatments were known, and no vaccines had been discovered. A plan to correct these deficiencies through cooperative science and efficient clinical trials was implemented to combat this novel virus. This plan developed efficient and inexpensive tests, highly effective medicines to treat and prevent disease progression, and vaccines to immunize the population.

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.

Modeling optimal reopening strategies for COVID-19 and its variants by keeping infections low and fixing testing capacity

Since early March 2020, government agencies have utilized a wide variety of non-pharmaceutical interventions to mitigate the spread of COVID-19 and have struggled to determine when it is appropriate to return to in-person activities after an outbreak is detected. At many universities, fundamental issues related to understanding the spread of the disease (e.g. the transmission rate), the ability of administrators to respond quickly enough by closing when there is a sudden rise in cases, and how to make a decision on when to reopen remains a concern. Surveillance testing strategies have been implemented in some places, and those test outcomes have dictated whether to reopen, to simultaneously monitor community spread, and/or to isolate discovered cases. However, the question remains as to when it is safe to reopen and how much testing is required to remain safely open while keeping infection numbers low. Here, we propose an extension of the classic SIR model to investigate reopening strategies for a fixed testing strategy, based on feedback from testing results. Specifically, we close when a predefined proportion of the population becomes infected, and later reopen when that infected proportion decreases below a predefined threshold. A valuable outcome of our approach is that our reopening strategies are robust to variation in almost all model parameters, including transmission rates, which can be extremely difficult to determine as they typically differ between variants, location, vaccination status, etc. Thus, these strategies can be, in theory, translated over to new variants in different regions of the world. Examples of robust feedback strategies for high disease transmission and a fixed testing capacity include (1) a single long lock down followed by a single long in-person period, and (2) multiple shorter lock downs followed by multiple shorter in-person periods. The utility of this approach of having multiple strategies is that administrators of universities, schools, business, etc. can use a strategy that is best adapted for their own functionality.

Indirect Virus Transmission via Fomites Can Counteract Lock-Down Effectiveness

The spread of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has raised major health policy questions. Direct transmission via respiratory droplets seems to be the dominant route of its transmission. However, indirect transmission via shared contact of contaminated objects may also occur. The contribution of each transmission route to epidemic spread might change during lock-down scenarios. Here, we simulate viral spread of an abstract epidemic considering both routes of transmission by use of a stochastic, agent-based SEIR model. We show that efficient contact tracing (CT) at a high level of incidence can stabilize daily cases independently of the transmission route long before effects of herd immunity become relevant. CT efficacy depends on the fraction of cases that do not show symptoms. Combining CT with lock-down scenarios that reduce agent mobility lowers the incidence for exclusive direct transmission scenarios and can even eradicate the epidemic. However, even for small fractions of indirect transmission, such lockdowns can impede CT efficacy and increase case numbers. These counterproductive effects can be reduced by applying measures that favor distancing over reduced mobility. In summary, we show that the efficacy of lock-downs depends on the transmission route. Our results point to the particular importance of hygiene measures during mobility lock-downs.

Simulation and forecasting models of COVID-19 taking into account spatio-temporal dynamic characteristics: A review

The COVID-19 epidemic has caused more than 6.4 million deaths to date and has become a hot topic of interest in different disciplines. According to bibliometric analysis, more than 340,000 articles have been published on the COVID-19 epidemic from the beginning of the epidemic until recently. Modeling infectious diseases can provide critical planning and analytical tools for outbreak control and public health research, especially from a spatio-temporal perspective. However, there has not been a comprehensive review of the developing process of spatio-temporal dynamic models. Therefore, the aim of this study is to provide a comprehensive review of these spatio-temporal dynamic models for dealing with COVID-19, focusing on the different model scales. We first summarized several data used in the spatio-temporal modeling of the COVID-19, and then, through literature review and summary, we found that the existing COVID-19 spatio-temporal models can be divided into two categories: macro-dynamic models and micro-dynamic models. Typical representatives of these two types of models are compartmental and metapopulation models, cellular automata (CA), and agent-based models (ABM). Our results show that the modeling results are not accurate enough due to the unavailability of the fine-grained dataset of COVID-19. Furthermore, although many models have been developed, many of them focus on short-term prediction of disease outbreaks and lack medium- and long-term predictions. Therefore, future research needs to integrate macroscopic and microscopic models to build adaptive spatio-temporal dynamic simulation models for the medium and long term (from months to years) and to make sound inferences and recommendations about epidemic development in the context of medical discoveries, which will be the next phase of new challenges and trends to be addressed. In addition, there is still a gap in research on collecting fine-grained spatial-temporal big data based on cloud platforms and crowdsourcing technologies to establishing world model to battle the epidemic.

Municipal and neighbourhood level wastewater surveillance and subtyping of an influenza virus outbreak

Recurrent influenza epidemics and pandemic potential are significant risks to global health. Public health authorities use clinical surveillance to locate and monitor influenza and influenza-like cases and outbreaks to mitigate hospitalizations and deaths. Currently, global integration of clinical surveillance is the only reliable method for reporting influenza types and subtypes to warn of emergent pandemic strains. The utility of wastewater surveillance (WWS) during the COVID-19 pandemic as a less resource intensive replacement or complement for clinical surveillance has been predicated on analyzing viral fragments in wastewater. We show here that influenza virus targets are stable in wastewater and partitions favorably to the solids fraction. By quantifying, typing, and subtyping the virus in municipal wastewater and primary sludge during a community outbreak, we forecasted a citywide flu outbreak with a 17-day lead time and provided population-level viral subtyping in near real-time to show the feasibility of influenza virus WWS at the municipal and neighbourhood levels in near real time using minimal resources and infrastructure.

Municipal and neighbourhood level wastewater surveillance and subtyping of an influenza virus outbreak

Recurrent influenza epidemics and pandemic potential are significant risks to global health. Public health authorities use clinical surveillance to locate and monitor influenza and influenza-like cases and outbreaks to mitigate hospitalizations and deaths. Currently, global integration of clinical surveillance is the only reliable method for reporting influenza types and subtypes to warn of emergent pandemic strains. The utility of wastewater surveillance (WWS) during the COVID-19 pandemic as a less resource intensive replacement or complement for clinical surveillance has been predicated on analyzing viral fragments in wastewater. We show here that influenza virus targets are stable in wastewater and partitions favorably to the solids fraction. By quantifying, typing, and subtyping the virus in municipal wastewater and primary sludge during a community outbreak, we forecasted a citywide flu outbreak with a 17-day lead time and provided population-level viral subtyping in near real-time to show the feasibility of influenza virus WWS at the municipal and neighbourhood levels in near real time using minimal resources and infrastructure.

Compellingly high SARS-CoV-2 susceptibility of Golden Syrian hamsters suggests multiple zoonotic infections of pet hamsters during the COVID-19 pandemic

Golden Syrian hamsters (Mesocricetus auratus) are used as a research model for severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2). Millions of Golden Syrian hamsters are also kept as pets in close contact to humans. To determine the minimum infective dose (MID) for assessing the zoonotic transmission risk, and to define the optimal infection dose for experimental studies, we orotracheally inoculated hamsters with SARS-CoV-2 doses from 1 * 10⁵ to 1 * 10⁻⁴ tissue culture infectious dose 50 (TCID₅₀). Body weight and virus shedding were monitored daily. 1 * 10⁻³ TCID₅₀ was defined as the MID, and this was still sufficient to induce virus shedding at levels up to 10^2.75 TCID₅₀/ml, equaling the estimated MID for humans. Virological and histological data revealed 1 * 10² TCID₅₀ as the optimal dose for experimental infections. This compelling high susceptibility leading to productive infections in Golden Syrian hamsters must be considered as a potential source of SARS-CoV-2 infection for humans that come into close contact with pet hamsters.

Incubation Period of COVID-19 Caused by Unique SARS-CoV-2 Strains: A Systematic Review and Meta-analysis

IMPORTANCE

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.

OBJECTIVE

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.

DATA SOURCES

PubMed, EMBASE, and ScienceDirect were searched between December 1, 2019, and February 10, 2022.

STUDY SELECTION

Original studies of the incubation period of COVID-19, defined as the time from infection to the onset of signs and symptoms.

DATA EXTRACTION AND SYNTHESIS

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.

MAIN OUTCOMES AND MEASURES

The mean estimate of the incubation period and different SARS-CoV-2 strains.

RESULTS

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.

CONCLUSIONS AND RELEVANCE

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.

Dengue and COVID-19: two sides of the same coin

BACKGROUND

Many countries in Asia and Latin America are currently facing a double burden of outbreaks due to dengue and COVID-19. Here we discuss the similarities and differences between the two infections so that lessons learnt so far from studying both infections will be helpful in further understanding their immunopathogenesis and to develop therapeutic interventions.

MAIN BODY

Although the entry routes of the SARS-CoV-2 and the dengue virus (DENV) are different, both infections result in a systemic infection, with some similar clinical presentations such as fever, headache, myalgia and gastrointestinal symptoms. However, while dengue is usually associated with a tendency to bleed, development of micro and macrothrombi is a hallmark of severe COVID-19. Apart from the initial similarities in the clinical presentation, there are further similarities between such as risk factors for development of severe illness, cytokine storms, endothelial dysfunction and multi-organ failure. Both infections are characterised by a delayed and impaired type I IFN response and a proinflammatory immune response. Furthermore, while high levels of potent neutralising antibodies are associated with protection, poorly neutralising and cross-reactive antibodies have been proposed to lead to immunopathology by different mechanisms, associated with an exaggerated plasmablast response. The virus specific T cell responses are also shown to be delayed in those who develop severe illness, while varying degrees of endothelial dysfunction leads to increased vascular permeability and coagulation abnormalities.

CONCLUSION

While there are many similarities between dengue and SARS-CoV-2 infection, there are also key differences especially in long-term disease sequelae. Therefore, it would be important to study the parallels between the immunopathogenesis of both infections for development of more effective vaccines and therapeutic interventions.

Seroprevalence in health care workers during the later phase of the second wave: Results of three hospitals in Serbia, prior to vaccine administration

BACKGROUND

Since the COVID-19 pandemic has started, Serbia has faced problems in implementing proper public health measures in the population, including non-pharmaceutical interventions, as well as protecting health care workers (HCWs) from disease, like all other countries. This study aimed to estimate COVID-19 seroprevalence and evaluate the risk perception of COVID-19 among HCWs in three different hospitals in Belgrade, Serbia: non-COVID hospital, Emergency Center (EC), and dedicated COVID hospital.

METHODS

A cross-sectional study was conducted in three hospitals during the second wave of the outbreak in Serbia, from June to early October. All staff in these hospitals were invited to voluntarily participate in blood sampling for IgG antibodies against SARS-CoV-2 and questionnaire testing. The questionnaire included socio-demographic characteristics, known exposure to COVID-19 positive persons, previous signs and symptoms related to COVID-19 infection since the outbreak had started in our country, and SARS-CoV-2 PCR testing.

RESULTS

The overall prevalence of SARS-CoV-2 antibody among 1580 HCWs was 18.3 % [95 % CI 16.4-20.3 %]. Significantly higher prevalence of HCWs with positive results for the serum IgG antibody test was observed in COVID hospital (28.6 %, 95 %CI: 24.0-33.6 %) vs. prevalence in the EC (12.6 %, 95 %CI: 10.1-15.4 %), and in the non-COVID hospital (18.3 %, 95 %CI: 15.2-26.7 %). The prevalence adjusted for declared test sensitivity and specificity would be 16.8 %; that is 27.4 % in COVID-19 hospital, 10.9 % in EC, and 16.8 % in non-COVID hospital. In multivariate logistic regression analysis, the independent predictors for seropositivity were working in COVID-hospital, the profession of physician, and the presence of the following symptoms: fever, shortness of breath, and anosmia/ageusia.

CONCLUSIONS

We found an overall seropositivity rate of 18.3 % and 16.0 % of the adjusted rate that is higher than seroprevalence obtained in similar studies conducted before vaccinations started. The possibility that patients in non-COVID dedicated hospitals might also be infectious, although PCR tested, imposes the need for the use of personal protective equipment also in non-COVID medical institutions.

Protocol for a prospective quasi-experimental study on SARS-CoV-2 transmission during outdoor sports events in France: the COVID-ESO project

INTRODUCTION

The spread of SARS-CoV-2 and its variants in the community remains a major concern despite the application of control measures including the banning of mass sporting events. The circulation of SARS-CoV-2 within the general population, and potentially within the population practicing outdoor sports activities, suggests contexts conducive to the transmission of the virus. We hypothesise that outdoor sports events (OSEs) do not present a higher risk of SARS-CoV-2 contamination. The objective of the COVID-ESO project is to measure if individuals participating in OSE present a similar risk of SARS-CoV-2 transmission compared with individuals not participating in OSE, in France.

METHODS AND ANALYSIS

The COVID-ESO project is a prospective, quasi-experimental study to be conducted in volunteer individuals likely to participate in OSE. Six events are targeted across France to be included. Three sport trials will be eligible for the study: running, cycling and triathlon. Each individual participating in the OSE will choose one of his or her usual training partner to be eligible for the unexposed control group. Individuals will be matched (1:1) on age, sex and the district of residence. Individuals assigned to the exposed group will participate in the OSE, whereas individuals assigned to the unexposed group will not participate in the OSE. All individuals will be asked to perform saliva tests on the day of the event and 7 days after the event. A questionnaire including sociodemographic, clinical and exposure data to SARS-CoV-2 will be sent by email for both groups on the day before the event and 7 days after the event. Differences in SARS-CoV-2 infection rates between the exposed versus the unexposed group will be analysed by fitting a conditional logistic regression model, adjusted for potential confounders. As the sport events unfold, data will be analyzed by performing sequential meta-analyses.

ETHICS AND DISSEMINATION

This protocol has been approved by the ethical committee. Ethical approval has been obtained for the Clinical research and committee of South West of France, 10 June 2021. COMITE DE PROTECTION DES PERSONNES DU SUD-OUEST ET OUTRE-MER 4 under the reference number 21.03.23.71737/CPP2021-04-045 a COVID/2021-A00845-36. Findings generated from this study will be shared to national health and sport authorities.

Two Separate Clusters of SARS-CoV-2 Delta Variant Infections in A Group of 41 Students Travelling from India: An Illustration of the Need for Rigorous Testing and Quarantine

We report two clusters of SARS-CoV-2 B.1.617.2 (Delta variant) infections in a group of 41 Indian nursing students who travelled from New Delhi, India, to Belgium via Paris, France. All students tested negative before departure and had a second negative antigen test upon arrival in Paris. Upon arrival in Belgium, the students were quarantined in eight different houses. Four houses remained COVID-free during the 24 days of follow-up, while all 27 residents of the other four houses developed an infection during quarantine, including the four residents who were fully vaccinated and the two residents who were partially vaccinated. Genome sequencing revealed two distinct clusters affecting one and three houses, respectively. In this group of students, vaccination status did not seem to prevent infection nor decrease the viral load. No severe symptoms were reported. Extensive contact tracing and 3 months of nationwide genomic surveillance confirmed that these outbreaks were successfully contained and did not contribute to secondary community transmission in Belgium. These clusters highlight the importance of repeated testing and quarantine measures among travelers coming from countries experiencing a surge of infections, as all infections were detected 6 days or more after arrival.

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.

Distinct airway epithelial immune responses after infection with SARS-CoV-2 compared to H1N1

Children are less likely than adults to suffer severe symptoms when infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), while influenza A H1N1 severity is comparable across ages except for the very young or elderly. Airway epithelial cells play a vital role in the early defence against viruses via their barrier and immune functions. We investigated viral replication and immune responses in SARS-CoV-2-infected bronchial epithelial cells from healthy paediatric (n = 6; 2.5-5.6 years old) and adult (n = 4; 47-63 years old) subjects and compared cellular responses following infection with SARS-CoV-2 or Influenza A H1N1. While infection with either virus triggered robust transcriptional interferon responses, including induction of type I (IFNB1) and type III (IFNL1) interferons, markedly lower levels of interferons and inflammatory proteins (IL-6, IL-8) were released following SARS-CoV-2 compared to H1N1 infection. Only H1N1 infection caused disruption of the epithelial layer. Interestingly, H1N1 infection resulted in sustained upregulation of SARS-CoV-2 entry factors FURIN and NRP1. We did not find any differences in the epithelial response to SARS-CoV-2 infection between paediatric and adult cells. Overall, SARS-CoV-2 had diminished potential to replicate, affect morphology and evoke immune responses in bronchial epithelial cells compared to H1N1.

The performance of wearable sensors in the detection of SARS-CoV-2 infection: a systematic review

Containing the COVID-19 pandemic requires rapidly identifying infected individuals. Subtle changes in physiological parameters (such as heart rate, respiratory rate, and skin temperature), discernible by wearable devices, could act as early digital biomarkers of infections. Our primary objective was to assess the performance of statistical and algorithmic models using data from wearable devices to detect deviations compatible with a SARS-CoV-2 infection. We searched MEDLINE, Embase, Web of Science, the Cochrane Central Register of Controlled Trials (known as CENTRAL), International Clinical Trials Registry Platform, and ClinicalTrials.gov on July 27, 2021 for publications, preprints, and study protocols describing the use of wearable devices to identify a SARS-CoV-2 infection. Of 3196 records identified and screened, 12 articles and 12 study protocols were analysed. Most included articles had a moderate risk of bias, as per the National Institute of Health Quality Assessment Tool for Observational and Cross-Sectional Studies. The accuracy of algorithmic models to detect SARS-CoV-2 infection varied greatly (area under the curve 0·52-0·92). An algorithm's ability to detect presymptomatic infection varied greatly (from 20% to 88% of cases), from 14 days to 1 day before symptom onset. Increased heart rate was most frequently associated with SARS-CoV-2 infection, along with increased skin temperature and respiratory rate. All 12 protocols described prospective studies that had yet to be completed or to publish their results, including two randomised controlled trials. The evidence surrounding wearable devices in the early detection of SARS-CoV-2 infection is still in an early stage, with a limited overall number of studies identified. However, these studies show promise for the early detection of SARS-CoV-2 infection. Large prospective, and preferably controlled, studies recruiting and retaining larger and more diverse populations are needed to provide further evidence.

Evaluation of the effects of meteorological factors on COVID-19 prevalence by the distributed lag nonlinear model

Background

Although numerous studies have explored the impact of meteorological factors on the epidemic of COVID-19, their relationship remains controversial and needs to be clarified.

Methods

We assessed the risk effect of various meteorological factors on COVID-19 infection using the distributed lag nonlinear model, based on related data from July 1, 2020, to June 30, 2021, in eight countries, including Portugal, Greece, Egypt, South Africa, Paraguay, Uruguay, South Korea, and Japan, which are in Europe, Africa, South America, and Asia, respectively. We also explored associations between COVID-19 prevalence and individual meteorological factors by the Spearman’s rank correlation test.

Results

There were significant non-linear relationships between both temperature and relative humidity and COVID-19 prevalence. In the countries located in the Northern Hemisphere with similar latitudes, the risk of COVID-19 infection was the highest at temperature below 5 ℃. In the countries located in the Southern Hemisphere with similar latitudes, their highest infection risk occurred at around 15 ℃. Nevertheless, in most countries, high temperature showed no significant association with reduced risk of COVID-19 infection. The effect pattern of relative humidity on COVID-19 depended on the range of its variation in countries. Overall, low relative humidity was correlated with increased risk of COVID-19 infection, while the high risk of infection at extremely high relative humidity could occur in some countries. In addition, relative humidity had a longer lag effect on COVID-19 than temperature.

Conclusions

The effects of meteorological factors on COVID-19 prevalence are nonlinear and hysteretic. Although low temperature and relative humidity may lower the risk of COVID-19, high temperature or relative humidity could also be associated with a high prevalence of COVID-19 in some regions.

Severe Acute Respiratory Syndrome Coronavirus 2 Infection in Pregnancy. A Non-systematic Review of Clinical Presentation, Potential Effects of Physiological Adaptations in Pregnancy, and Placental Vascular Alterations

In December 2019, the novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) rapidly spread to become a pandemic. To date, increasing evidence has described the potential negative impact of SARS-CoV-2 infection on pregnant women. Although the pathophysiology of coronavirus disease 2019 (COVID-19) is not entirely understood, there is emerging evidence that it causes a severe systemic inflammatory response associated with vascular alterations that could be of special interest considering some physiological changes in pregnancy. Additionally, these alterations may affect the physiology of the placenta and are associated with pregnancy complications and abnormal histologic findings. On the other hand, data about the vaccine against SARS-CoV-2 are limited, but the risks of administering COVID-19 vaccines during pregnancy appear to be minimal. This review summarizes the current literature on SARSCoV2 virus infection, the development of COVID-19 and its relationship with physiological changes, and angiotensin-converting enzyme 2 (ACE2) function during pregnancy. We have particularly emphasized evidence coming from Latin American countries.

Whole-Genome Sequencing of SARS-CoV-2 Infection in a Cluster of Immunocompromised Children in Indonesia

Background

Thus far, Indonesia has recorded over 4,000,000 confirmed COVID-19 cases and 144,000 fatalities; 12.8% of cases have been in children under 18 years. Whole-genome viral sequencing (WGS) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been demonstrated to help differentiate hospital-acquired infection from community-acquired coronavirus disease 2019 (COVID-19) infection. Our study highlighted the use of WGS to investigate the origin of infection among pediatric oncology patients in Jakarta. The aim of our study was to evaluate clinical and laboratory characteristics and also the efficacy of using WGS to confirm hospital-acquired COVID-19 infection in a cluster of immunocompromised children within a single ward of a tertiary hospital in metropolitan Jakarta based on quasispecies, viral load, and admission dates.

Method

Real-time reverse-transcription polymerase chain reaction (RT-PCR) from nasopharyngeal (NP) swabs was used to diagnose the patients and also guardians and healthcare workers (HCWs) in the ward, followed by WGS of RT-PCR positive cases to establish their phylogenetic relationships.

Result

Using WGS, we showed that SARS-CoV-2 transmission in a cluster of children with underlying malignancy was characterized by high similarity of whole virus genome, which suggests nosocomial transmission.

Dynamical regulations on mobility and vaccinations for controlling COVID-19 spread

Using a system of time-dynamical equations, we investigate how daily mobility indices, such as the homestay percentage above the pre-COVID normal ([Formula: see text]; or H-forcing), and the vaccinated percentage ([Formula: see text]; or V-forcing) impact the net reproductive rate (R0) of COVID-19 in ten island nations as a prototype, and then, extending it to 124 countries worldwide. Our H- and V-forcing model of R0 can explain the new trends in 106 countries. The disease transmission can be controlled by forcing down [Formula: see text] with an enforcement of continuous [Formula: see text] in [Formula: see text] of countries with [Formula: see text] vaccinated plus recovered, [Formula: see text]. The required critical [Formula: see text] decreases with increasing [Formula: see text], dropping it down to [Formula: see text] with [Formula: see text], and further down to [Formula: see text] with [Formula: see text]. However, the regulations on [Formula: see text] are context-dependent and country-specific. Our model gives insights into forecasting and controlling the disease's transmission behaviour when the effectiveness of the vaccines is a concern due to new variants, and/or there are delays in vaccination rollout programs.

Novel Evidence Showing the Possible Effect of Environmental Variables on COVID-19 Spread

Coronavirus disease (COVID-19) remains a serious issue, and the role played by meteorological indicators in the process of virus spread has been a topic of academic discussion. Previous studies reached different conclusions due to inconsistent methods, disparate meteorological indicators, and specific time periods or regions. This manuscript is based on seven daily meteorological indicators in the NCEP reanalysis data set and COVID-19 data repository of Johns Hopkins University from 22 January 2020 to 1 June 2021. Results showed that worldwide average temperature and precipitable water (PW) had the strongest correlation (ρ > 0.9, p < 0.001) with the confirmed COVID-19 cases per day from 22 January to 31 August 2020. From 22 January to 31 August 2020, positive correlations were observed between the temperature/PW and confirmed COVID-19 cases/deaths in the northern hemisphere, whereas negative correlations were recorded in the southern hemisphere. From 1 September to 31 December 2020, the opposite results were observed. Correlations were weak throughout the near full year, and weak negative correlations were detected worldwide (|ρ| < 0.4, p ≤ 0.05); the lag time had no obvious effect. As the latitude increased, the temperature and PW of the maximum confirmed COVID-19 cases/deaths per day generally showed a decreasing trend; the 2020-year fitting functions of the response latitude pattern were verified by the 2021 data. Meteorological indicators, although not a decisive factor, may influence the virus spread by affecting the virus survival rates and enthusiasm of human activities. The temperature or PW threshold suitable for the spread of COVID-19 may increase as the latitude decreases.

T and B Cells Immune Response and the importance of vaccines Against SARS-CoV-2

SARS-CoV-2 has become a global pandemic because it is a severe respiratory syndrome that attacks many people worldwide and can lead to death depending on the severity. In recent years, the study of the acquired immune response (T cells) and innate (B cells) has increased to better treat the disease from the quantitative cell count. A picture has begun to emerge revealing that CD4+ T cells, CD8+ T cells, and neutralizing antibodies contribute to the control of SARS-CoV-2 in COVID-19 cases. This work studies the three fundamental components of the adaptive immune system: B cells (the source of antibodies), CD4+T cells, and CD8+T cells and their function against SARS-CoV2. The importance of vaccines and the different types of existing vaccines are discussed. Implications of covid-19 variants on Immunity and vaccine types are also analyzed to understand how the action of the immune system will help treat the disease.

Prevalences of SARS-CoV-2 RNA and anti-SARS-CoV-2 among at-risk populations in Chiang Mai and Lamphun provinces, Thailand, during November 2020-January 2021

Non-healthcare workers with a high potential for exposure to severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) may contribute to the virus spreading. Data among asymptomatic and high exposure risk populations is still scarce, in particular Chiang Mai and Lamphun provinces, Thailand. We conducted a cross-sectional observational study aiming to assess the prevalence of SARS-CoV-2 RNA positivity, anti-SARS-CoV-2 IgM/IgG, and potential associated factors among asymptomatic/mild symptomatic individuals with a high exposure risk in Chiang Mai and Lamphun provinces, during the second wave of outbreak in Thailand (November 2020–January 2021). Socio-demographic data was collected through an on-line questionnaire prior to collection of nasopharyngeal/throat swab samples and blood samples tested for SARS-CoV-2 RNA (DaAn Gene, China) and anti-SARS-CoV-2 IgM/IgG antibodies (commercial lateral flow immunoassays), respectively. Univariable and multivariable logistic regression analysis were used to analyze associated factors. None of 1,651 participants were found positive for SARS-CoV-2 RNA (0%, 95% confidence intervals, CI: 0–0.2). Fourteen were positive for anti-SARS-CoV-2 IgM/IgG antibodies (0.9%, 95% CI: 0.5–1.4), including 7 positives for IgM and 7 positives for IgG (0.4%, 95% CI: 0.2–0.9). Being over 50 years old was independently associated with virus exposure (OR: 5.8, 95% CI: 1.0–32.1%, p = 0.045). Despite high exposure risk, no current infection was found, and a very high proportion was still susceptible to SARS-CoV-2 infection and would clearly benefit from vaccination. Continuing active surveillance, rolling out of vaccination and monitoring response to vaccine will help better control the COVID-19 spread.

The “Invisible Enemy” SARS-CoV-2: Viral Spread and Drug Treatment

Nowadays, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has become the main subject of the scientific medical world and all World Organizations, causing millions of deaths worldwide. In this review, we have highlighted the context of the Coronavirus disease 2019 (COVID-19) pandemic, how the virus spreads, the symptoms and complications that may occur, and, especially, the drug treatment of viral infection, with emphasis on monoclonal antibodies. While well-known strains such as Alpha, Beta, Gamma, and, especially, Delta have shown an accelerated transmission among the population, the new Omicron variant (discovered on 24 November 2021) indicates more significant infectiousness and the poor efficacy of monoclonal antibody therapy due to mutations on the spike protein receptor-binding domain. With these discoveries, the experiments began, the first being in silico and in vitro, but these are not enough, and in vivo experiments are needed to see exactly the cause of neutralization of the action of these drugs. Following the documentation of the latest medical and scientific research, it has been concluded that there are many chemical molecules that have the potential to treat SARS-CoV-2 infection, but more detailed clinical trials are needed for their use in therapy. In addition, it is important to consider the structure of the viral strain in the administration of treatment.

Investigation of a Limited but Explosive COVID-19 Outbreak in a German Secondary School

The role of schools as a source of infection and driver in the coronavirus-pandemic has been controversial and is still not completely clarified. To prevent harm and disadvantages for children and adolescents, but also adults, detailed data on school outbreaks is needed, especially when talking about open schools employing evidence-based safety concepts. Here, we investigated the first significant COVID-19 school outbreak in Hamburg, Germany, after the re-opening of schools in 2020. Using clinical, laboratory, and contact data and spatial measures for epidemiological and environmental studies combined with whole-genome sequencing (WGS) analysis, we examined the causes and the course of the secondary school outbreak. The potential index case was identified by epidemiological tracking and the lessons in classrooms with presumably high virus spreading rates and further infection chains in the setting. Sequence analysis of samples detected one sample of a different virus lineage and 25 virus genomes with almost identical sequences, of which 21 showed 100% similarity. Most infections occurred in connection with two lesson units of the primary case. Likely, 31 students (12–14 years old), two staff members, and three family members were infected in the school or the typical household. Sequence analysis revealed an outbreak cluster with a single source that was epidemiologically identified as a member of the educational staff. In lesson units, two superspreading events of varying degrees with airborne transmission took place. These were influenced by several parameters including the exposure times, the use of respiratory masks while speaking and spatial or structural conditions at that time.

How Can Hybrid Simulation Support Organizations in Assessing COVID-19 Containment Measures?

Simulation models have always been an aid in epidemiology for understanding the spread of epidemics and evaluating their containment policies. This paper illustrates how hybrid simulation can support companies in assessing COVID-19 containment measures in indoor environments. In particular, a Hybrid Simulation (HS) is presented. The HS model consists of an Agent-Based Simulation (ABS) to simulate the virus contagion model and a Discrete Event Simulation (DES) model to simulate the interactions between flows of people in an indoor environment. Compared with previous works in the field of simulation and COVID-19, this study provides the possibility to model the specific behaviors of individuals moving in time and space and the proposed HS model could be adapted to several epidemiological conditions (just setting different parameters in the agent-based model) and different kinds of facilities. The HS approach has been developed and then successfully tested with a real case study related to a university campus in northern Italy. The case study highlights the potentials of hybrid simulation in assessing the effectiveness of the containment measures adopted during the period under examination in the pandemic context. From a managerial perspective, this study, exploiting the complementarity of the ABM and DES approaches in a HS model, provides a complete and usable tool to support decision-makers in evaluating different contagion containment measures.

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.

IgG Antibodies Develop to Spike but Not to the Nucleocapsid Viral Protein in Many Asymptomatic and Light COVID-19 Cases

Since SARS-CoV-2 appeared in late 2019, many studies on the immune response to COVID-19 have been conducted, but the asymptomatic or light symptom cases were somewhat understudied as respective individuals often did not seek medical help. Here, we analyze the production of the IgG antibodies to viral nucleocapsid (N) protein and receptor-binding domain (RBD) of the spike protein and assess the serum neutralization capabilities in a cohort of patients with different levels of disease severity. In half of light or asymptomatic cases the antibodies to the nucleocapsid protein, which serve as the main target in many modern test systems, were not detected. They were detected in all cases of moderate or severe symptoms, and severe lung lesions correlated with respective higher signals. Antibodies to RBD were present in the absolute majority of samples, with levels being sometimes higher in light symptom cases. We thus suggest that the anti-RBD/anti-N antibody ratio may serve as an indicator of the disease severity. Anti-RBD IgG remained detectable after a year or more since the infection, even with a slight tendency to raise over time, and the respective signal correlated with the serum capacity to inhibit the RBD interaction with the ACE-2 receptor.

Impact of non-pharmaceutical interventions against COVID-19 in Europe in 2020: a quasi-experimental non-equivalent group and time series design study

IntroductionThe current pandemic of coronavirus disease (COVID-19) is unparalleled in recent history as are the social distancing interventions that have led to a considerable halt on the economic and social life of so many countries.AimWe aimed to generate empirical evidence about which social distancing measures had the most impact in reducing case counts and mortality.MethodsWe report a quasi-experimental (observational) study of the impact of various interventions for control of the outbreak through 24 April 2020. Chronological data on case numbers and deaths were taken from the daily published figures by the European Centre for Disease Prevention and Control and dates of initiation of various control strategies from the Institute of Health Metrics and Evaluation website and published sources. Our complementary analyses were modelled in R using Bayesian generalised additive mixed models and in STATA using multilevel mixed-effects regression models.ResultsFrom both sets of modelling, we found that closure of education facilities, prohibiting mass gatherings and closure of some non-essential businesses were associated with reduced incidence whereas stay-at-home orders and closure of additional non-essential businesses was not associated with any independent additional impact.ConclusionsOur findings are that schools and some non-essential businesses operating 'as normal' as well as allowing mass gatherings were incompatible with suppressing disease spread. Closure of all businesses and stay at home orders are less likely to be required to keep disease incidence low. Our results help identify what were the most effective non-pharmaceutical interventions in this period.