Reproductive number of coronavirus: A systematic review and meta-analysis based on global level evidence

A novel comparison framework for epidemiological strategies applied to age-based restrictions versus horizontal lockdowns

During an epidemic, such as the COVID-19 pandemic, policy-makers are faced with the decision of implementing effective, yet socioeconomically costly intervention strategies, such as school and workplace closure, physical distancing, etc. In this study, we propose a rigorous definition of epidemiological strategies. In addition, we develop a scheme for comparing certain epidemiological strategies, with the goal of providing policy-makers with a tool for their systematic comparison. Then, we put the suggested scheme to the test by employing an age-based epidemiological compartment model introduced in Bitsouni et al. (2024), coupled with data from the literature, in order to compare the effectiveness of age-based and horizontal interventions. In general, our findings suggest that these two are comparable, mainly at a low or medium level of intensity.

Estimating population infection rates from non-random testing data: Evidence from the COVID-19 pandemic

To effectively respond to an emerging infectious disease outbreak, policymakers need timely and accurate measures of disease prevalence in the general population. This paper presents a new methodology to estimate real-time population infection rates from non-random testing data. The approach compares how the observed positivity rate varies with the size of the tested population and applies this gradient to infer total population infections. Applying this methodology to daily testing data across U.S. states during the first wave of the COVID-19 pandemic, we estimated widespread undiagnosed COVID-19 infections. Nationwide, we found that for every identified case, there were 12 population infections. Our prevalence estimates align with results from seroprevalence surveys, alternate approaches to measuring COVID-19 infections, and total excess mortality during the first wave of the pandemic.

The descriptive epidemiology of adverse events following two doses of mRNA COVID-19 vaccination in Curaçao, the Caribbean

BACKGROUND

BNT162b2 and mRNA-1273 COVID-19 vaccines have been used for mass vaccinations in Curaçao, the Caribbean but information on adverse events (AEs)in this population is unavailable. This study describes the characteristics of vaccinees that incurred AEs, explores the associations between AEs by vaccine and doses, and estimates the rate of AEs.

METHODS

Vaccination and AEs data for all persons of age 5 years (range 5-105 years) and older who received two doses of COVID-19 vaccine at 71 centres in Curaçao between February 24, 2021, and April 5, 2023, were included in this retrospective observational study.

RESULTS

The vaccines differed significantly in the frequency distribution of vaccinees by age, age groups, sex, AEs, and prior COVID-19 infection. Occurrence of AEs was strongly associated with mRNA vaccine brand, sex, number of doses, but not with age, age group, and prior COVID-19 infection. Of 209,720 doses, 84 persons (0.04%) incurred AEs following two doses of mRNA vaccines (overall rate of 40.1 per 100,000 persons (95% CI 32.4-49.6). AEs were also significantly higher in females compared to males.AE rates associated with BNT162b2, and mRNA-1273 vaccines were low, but BNT162b2 vaccinees incurred substantially significantly higher AE rates (58.3 per 100,000 persons, 95% CI 45.4-74.9) than mRNA-1273 vaccinees (21.9 per 100,000 persons, 95% CI 14.6-32.8). mRNA-1273 vaccine was associated with a significantly lower risk of AEs.

CONCLUSIONS

AE reporting varied by age, sex, and vaccine used as well as the number of doses. Future studies with follow-up and longer-term reporting of AEs should be conducted.

Data-driven mathematical modeling approaches for COVID-19: A survey

In this review, we successively present the methods for phenomenological modeling of the evolution of reported and unreported cases of COVID-19, both in the exponential phase of growth and then in a complete epidemic wave. After the case of an isolated wave, we present the modeling of several successive waves separated by endemic stationary periods. Then, we treat the case of multi-compartmental models without or with age structure. Eventually, we review the literature, based on 260 articles selected in 11 sections, ranging from the medical survey of hospital cases to forecasting the dynamics of new cases in the general population. This review favors the phenomenological approach over the mechanistic approach in the choice of references and provides simulations of the evolution of the number of observed cases of COVID-19 for 10 states (California, China, France, India, Israel, Japan, New York, Peru, Spain and United Kingdom).

Activities of psychiatrists in specialized coronavirus disease 2019 wards at Juntendo Hospital

Since the onset of the coronavirus disease 2019 (COVID-19) pandemic in 2020, specialized COVID-19 wards have been established in general hospitals across Japan. Juntendo Hospital also established a dedicated COVID-19 ward; however, many hospitalized patients were found to have psychiatric symptoms, such as delirium and depression. Juntendo Hospital's COVID-19 specialist beds were staffed mainly by internists, who specialized in physical illnesses and were unfamiliar with psychiatric symptoms, making it difficult for them to provide adequate treatment. Some staff members were also found to be suffering from mental illness, compounding these issues. In 2021, to address these challenges, Juntendo Hospital's psychiatry department began having psychiatrists make rounds once a week in specialized COVID-19 wards. The number of consultations varied depending on the status of the COVID-19 epidemic; however, in the peak month, 45 consultations were made per month. Most consultations involved delirium and neurotic conditions, and there had been over 200 consultations for both by August 2023. We addressed not only the mental symptoms of the patients, but also the health status of the staff at the hospital beds, and took measures to maintain the mental health of the staff. Consequently, the hospital has not experienced any large-scale medical breakdowns due to excessive staff fatigue. New pandemics of emerging infectious diseases will likely occur in the future, and we believe that we need to learn from this pandemic and prepare for future pandemics.

A novel, scenario-based approach to comparing non-pharmaceutical intervention strategies across nations

Comparing COVID-19 response strategies across nations is a key step in preparing for future pandemics. Conventional comparisons, which rank individual non-pharmaceutical intervention (NPI) effects, are limited by: (i) a focus on epidemiological outcomes; (ii) NPIs typically being applied as packages of interventions; and (iii) different political, economic and social conditions among nations. Here, we develop a coupled epidemiological-behavioural-macroeconomic model that can transfer NPI effects from a reference nation to a focal nation. This approach quantifies epidemiological, behavioural and economic outcomes while accounting for both packaged NPIs and differing conditions among nations. As a first proof of concept, we take Germany as our focal nation during Spring 2020, and New Zealand and Switzerland as reference nations with contrasting NPI strategies. Our results suggest that, while New Zealand's more aggressive strategy would have yielded modest epidemiological gains in Germany, it would have resulted in substantially higher economic costs while dramatically reducing social contacts. In contrast, Switzerland's more lenient strategy would have prolonged the first wave in Germany, but would also have increased relative costs. More generally, these findings indicate that our approach can provide novel, multifaceted insights on the efficacy of pandemic response strategies, and therefore merits further exploration and development.

The effect of mobility reductions on infection growth is quadratic in many cases

Stay-at-home orders were introduced in many countries during the COVID-19 pandemic, limiting the time people spent outside their home and the attendance of gatherings. In this study, we argue from a theoretical model that in many cases the effect of such stay-at-home orders on incidence growth should be quadratic, and that this statement should also hold beyond COVID-19. That is, a reduction of the out-of-home duration to, say, 70% of its original value should reduce incidence growth and thus the effective R-value to 70 % · 70 % = 49 % of its original value. We then show that this hypothesis can be substantiated from data acquired during the COVID-19 pandemic by using a multiple regression model to fit a combination of the quadratic out-of-home duration and temperature to the COVID-19 growth multiplier. We finally demonstrate that many other models, when brought to the same scale, give similar reductions of the effective R-value, but that none of these models extend plausibly to an out-of-home duration of zero.

Global disparities in COVID-19 vaccine booster dose (VBD) acceptance and hesitancy: An updated narrative review

The global deployment of COVID-19 vaccine booster dose (VBD) has been recognized as a promising therapeutic alliance to provide repeated immunity against the arrival of new variants. Despite scientific evidence supports the effectiveness of periodic doses, COVID-19 vaccine booster reluctance continues to thrive. This narrative review aimed to examine global COVID-19 vaccine booster dose (VBD) acceptance and summarize an up-to-date assessment of potential antecedents associated with VBD acceptance. A comprehensive search was performed in several reputable databases such as Medline (via PubMed), Scopus, Google scholar, and Web of Science from June 10th, 2023, to August 1st, 2023. All relevant descriptive and observational studies on COVID-19 VBD acceptance and hesitancy were included in this review. A total of fifty-eight (58) studies were included, with Asia representing the highest count with thirty-one (53%) studies, Europe with eleven (19 %), the United States with nine (16 %), and other regions (Africa and multi-ethnic) with seven (12 %). Worldwide, the pooled COVID-19 VBD acceptance rate was 77.09 % (95 % CI: 76.28-78.18), VBD willingness (n) = 164189, and the total sample (N) = 212,990. The highest and the lowest VBD acceptance rate was reported in Europe and American regions, respectively, 85.38 % (95 % CI: 85.02-85.73, (n) = 32,047, (N = 37,533) vs. 66.92 % (95 % CI: 66.56-67.4), (n) = 29335, (N) = 43,832. However, Asia and multi-ethnic areas reported moderately high VBD acceptance rate 79.13 % (95 % CI: 78.77-79.23, (n) = 93,994, (N) = 11,8779) and 72.16 % (95 % CI: 71.13-72.93, (n) = 9276, (N) = 12,853), respectively. The most common and key antecedents of COVID-19 VBD acceptance and hesitancy across the countries were "equal safety", "efficacy", "effectiveness", "post-vaccination side effects", "community protection" "family protection", "risk-benefit ratio", "booster necessity", "trust", and "variants control". Disparities in the uptake of COVID-19 VBD were observed globally, with the highest rates found in Europe, and the lowest rates in American regions. Multiple potential antecedents including safety, efficacy, and post-vaccination side effects were associated with VBD acceptance and hesitancy.

The Limitations of a Hypothetical All-Variant COVID-19 Vaccine: A Simulation Study

This paper simulates a hypothetical pan-coronavirus vaccine that confers immediate sterilizing immunity against all SARS-CoV-2 variants. Simulations used a SEIIS (susceptible, exposed, infective, immune, susceptible) spreadsheet model that ran two parallel subpopulations: one that accepted vaccination and another that refused it. The two subpopulations could transmit infections to one another. Using data from the United States (US), the simulated vaccine was tested against limiting factors such as vaccine hesitancy, slow vaccination distribution, and the development of high-transmission variants. The vaccine was often successful at reducing cases, but high-transmission variants and discontinuation of non-pharmaceutical interventions (NPIs) such as masking greatly elevated cases. A puzzling outcome was that if NPIs were discontinued and high-transmission variants became common, the model predicted consistently higher rates of disease than are actually observed in the US in 2024. However, if cumulative exposure to virus antigens increased the duration of immunity or decreased the infectivity of the virus, the model predictions were brought back into a more realistic range. The major finding was that even when a COVID-19 vaccine always produces sterilizing immunity against every SARS-CoV-2 variant, its ability to control the epidemic can be compromised by multiple common conditions.

COVSIM: A stochastic agent-based COVID-19 SIMulation model for North Carolina

We document the evolution and use of the stochastic agent-based COVID-19 simulation model (COVSIM) to study the impact of population behaviors and public health policy on disease spread within age, race/ethnicity, and urbanicity subpopulations in North Carolina. We detail the methodologies used to model the complexities of COVID-19, including multiple agent attributes (i.e., age, race/ethnicity, high-risk medical status), census tract-level interaction network, disease state network, agent behavior (i.e., masking, pharmaceutical intervention (PI) uptake, quarantine, mobility), and variants. We describe its uses outside of the COVID-19 Scenario Modeling Hub (CSMH), which has focused on the interplay of nonpharmaceutical and pharmaceutical interventions, equitability of vaccine distribution, and supporting local county decision-makers in North Carolina. This work has led to multiple publications and meetings with a variety of local stakeholders. When COVSIM joined the CSMH in January 2022, we found it was a sustainable way to support new COVID-19 challenges and allowed the group to focus on broader scientific questions. The CSMH has informed adaptions to our modeling approach, including redesigning our high-performance computing implementation.

Mathematical Optimization Strategy for Effectiveness Profile Estimation in Two-Dose Vaccines and Its Use in Designing Improved Vaccination Strategies Focused on Pandemic Containment

Since late 2019, most efforts to control the COVID-19 pandemic have focused on developing vaccines. By mid-2020, some vaccines fulfilled international regulations for their application. However, these vaccines have shown a decline in effectiveness several weeks after the last dose, highlighting the need to optimize vaccine administration due to supply chain limitations. While methods exist to prioritize population groups for vaccination, there is a lack of research on how to optimally define the time between doses when two-dose vaccines are administrated to such groups. Under such conditions, modeling the real effect of each vaccine on the population is critical. Even though several efforts have been made to characterize vaccine effectiveness profiles, none of these initiatives enable characterization of the individual effect of each dose. Thus, this paper presents a novel methodology for estimating the vaccine effectiveness profile. It addresses the vaccine characterization problem by considering a deconvolution of relevant data profiles, treating them as an optimization process. The results of this approach enabled the independent estimation of the effectiveness profiles for the first and second vaccine doses and their use to find sweet spots for designing efficient vaccination strategies. Our methodology can enable a more effective and efficient contemporary response against the COVID-19 pandemic, as well as for any other disease in the future.

Susceptible-Infected-Susceptible type COVID-19 spread with collective effects

Many models developed to forecast and attempt to understand the COVID-19 pandemic are highly complex, and few take collective behavior into account. As the pandemic progressed individual recurrent infection was observed and simpler susceptible-infected type models were introduced. However, these do not include mechanisms to model collective behavior. Here, we introduce an extension of the SIS model that accounts for collective behavior and show that it has four equilibria. Two of the equilibria are the standard SIS model equilibria, a third is always unstable, and a fourth where collective behavior and infection prevalence interact to produce either node-like or oscillatory dynamics. We then parameterized the model using estimates of the transmission and recovery rates for COVID-19 and present phase diagrams for fixed recovery rate and free transmission rate, and both rates fixed. We observe that regions of oscillatory dynamics exist in both cases and that the collective behavior parameter regulates their extent. Finally, we show that the system exhibits hysteresis when the collective behavior parameter varies over time. This model provides a minimal framework for explaining oscillatory phenomena such as recurring waves of infection and hysteresis effects observed in COVID-19, and other SIS-type epidemics, in terms of collective behavior.

Fundamental bound on epidemic overshoot in the SIR model

We derive an exact upper bound on the epidemic overshoot for the Kermack-McKendrick SIR model. This maximal overshoot value of 0.2984 · · · occurs at [Formula: see text]. In considering the utility of the notion of overshoot, a rudimentary analysis of data from the first wave of the COVID-19 pandemic in Manaus, Brazil highlights the public health hazard posed by overshoot for epidemics with R0 near 2. Using the general analysis framework presented within, we then consider more complex SIR models that incorporate vaccination.

If Long-Term Suppression is not Possible, how do we Minimize Mortality for Infectious Disease Outbreaks?

OBJECTIVE

For any emerging pathogen, the preferred approach is to drive it to extinction with non-pharmaceutical interventions (NPI) or suppress its spread until effective drugs or vaccines are available. However, this might not always be possible. If containment is infeasible, the best people can hope for is pathogen transmission until population level immunity is achieved, with as little morbidity and mortality as possible.

METHODS

A simple computational model was used to explore how people should choose NPI in a non-containment scenario to minimize mortality if mortality risk differs by age.

RESULTS

Results show that strong NPI might be worse overall if they cannot be sustained compared to weaker NPI of the same duration. It was also shown that targeting NPI at different age groups can lead to similar reductions in the total number of infected, but can have strong differences regarding the reduction in mortality.

CONCLUSIONS

Strong NPI that can be sustained until drugs or vaccines become available are always preferred for preventing infection and mortality. However, if people encounter a worst-case scenario where interventions cannot be sustained, allowing some infections to occur in lower-risk groups might lead to an overall greater reduction in mortality than trying to protect everyone equally.

COVID-19 vaccine hesitancy worldwide and its associated factors: a systematic review and meta-analysis

Introduction

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has taken a toll on humans, and the development of effective vaccines has been a promising tool to end the pandemic. However, for a vaccination program to be successful, a considerable proportion of the community must be vaccinated. Hence, public acceptance of coronavirus disease 2019 (COVID-19) vaccines has become the key to controlling the pandemic. Recent studies have shown vaccine hesitancy increasing over time. This systematic review aims to evaluate the COVID-19 vaccine hesitancy rate and related factors in different communities.

Method

A comprehensive search was performed in MEDLINE (via PubMed), Scopus, and Web of Science from January 1, 2019 to January 31, 2022. All relevant descriptive and observational studies (cross-sectional and longitudinal) on vaccine hesitancy and acceptance were included in this systematic review. In the meta-analysis, odds ratio (OR) was used to assess the effects of population characteristics on vaccine hesitancy, and event rate (acceptance rate) was the effect measure for overall acceptance. Publication bias was assessed using the funnel plot, Egger's test, and trim-and-fill methods.

Result

A total of 135 out of 6,417 studies were included after screening. A meta-analysis of 114 studies, including 849,911 participants, showed an overall acceptance rate of 63.1%. In addition, men, married individuals, educated people, those with a history of flu vaccination, those with higher income levels, those with comorbidities, and people living in urban areas were less hesitant.

Conclusion

Increasing public awareness of the importance of COVID-19 vaccines in overcoming the pandemic is crucial. Being men, living in an urban region, being married or educated, having a history of influenza vaccination, having a higher level of income status, and having a history of comorbidities are associated with higher COVID-19 vaccine acceptance.

Genomic epidemiology of the main SARS-CoV-2 variants in Italy between summer 2020 and winter 2021

Since the beginning of the pandemic, SARS-CoV-2 has shown a great genomic variability, resulting in the continuous emergence of new variants that has made their global monitoring and study a priority. This work aimed to study the genomic heterogeneity, the temporal origin, the rate of viral evolution and the population dynamics of the main circulating variants (20E.EU1, Alpha and Delta) in Italy, in August 2020-January 2022 period. For phylogenetic analyses, three datasets were set up, each for a different main lineage/variant circulating in Italy in that time including other Italian and International sequences of the same lineage/variant, available in GISAID sampled in the same times. The international dataset showed 26 (23% Italians, 23% singleton, 54% mixed), 40 (60% mixed, 37.5% Italians, 1 singleton) and 42 (85.7% mixed, 9.5% singleton, 4.8% Italians) clusters with at least one Italian sequence, in 20E.EU1  clade, Alpha and Delta variants, respectively. The estimation of tMRCAs in the Italian clusters (including >70% of genomes from Italy) showed that in all the lineage/variant, the earliest clusters were the largest in size and the most persistent in time and frequently mixed. Isolates from the major Italian Islands tended to segregate in clusters more frequently than those from other part of Italy. The study of infection dynamics showed a positive correlation between the trend in the effective number of infections estimated by BSP model and the Re curves estimated by birth-death skyline plot. The present work highlighted different evolutionary dynamics of studied lineages with high concordance between epidemiological parameters estimation and phylodynamic trends suggesting that the mechanism of replacement of the SARS-CoV-2 variants must be related to a complex of factors involving the transmissibility, as well as the implementation of control measures, and the level of cross-immunization within the population.

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.

Bridging the Gap: Can COVID-19 Research Help Combat African Swine Fever?

African swine fever (ASF) is a highly contagious and economically devastating disease affecting domestic pigs and wild boar, caused by African swine fever virus (ASFV). Despite being harmless to humans, ASF poses significant challenges to the swine industry, due to sudden losses and trade restrictions. The ongoing COVID-19 pandemic has spurred an unparalleled global research effort, yielding remarkable advancements across scientific disciplines. In this review, we explore the potential technological spillover from COVID-19 research into ASF. Specifically, we assess the applicability of the diagnostic tools, vaccine development strategies, and biosecurity measures developed for COVID-19 for combating ASF. Additionally, we discuss the lessons learned from the pandemic in terms of surveillance systems and their implications for managing ASF. By bridging the gap between COVID-19 and ASF research, we highlight the potential for interdisciplinary collaboration and technological spillovers in the battle against ASF.

Inactivation of HCoV-NL63 and SARS-CoV-2 in aqueous solution by 254 nm UV-C

Ultraviolet germicidal irradiation (UVGI) is a highly effective means of inactivating many bacteria, viruses, and fungi. UVGI is an attractive viral mitigation strategy against coronaviruses, including the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of the coronavirus disease-2019 (COVID-19) pandemic. This investigation measures the susceptibility of two human coronaviruses to inactivation by 254 nm UV-C radiation. Human coronavirus NL63 and SARS-CoV-2 were irradiated in a collimated, dual-beam, aqueous UV reactor. By measuring fluence and integrating it in real-time, this reactor accounts for the lamp output transients during UVGI exposures. The inactivation rate constants of a one-stage exponential decay model were determined to be 2.050 cm²/mJ and 2.098 cm²/mJ for the NL63 and SARS-CoV-2 viruses, respectively. The inactivation rate constant for SARS-CoV-2 is within 2% of that of NL63, indicating that in identical inactivation environments, very similar UV 254 nm deactivation susceptibilities for these two coronaviruses would be achieved. Given the inactivation rate constant obtained in this study, doses of 1.1 mJ/cm², 2.2 mJ/cm², and 3.3 mJ/cm² would result in a 90%, 99%, and 99.9% inactivation of the SARS-CoV-2 virus, respectively. The inactivation rate constant obtained in this study is significantly higher than values reported from many 254 nm studies, which suggests greater UV susceptibility to the UV-C than what was believed. Overall, results from this study indicate that 254 nm UV-C is effective for inactivation of human coronaviruses, including SARS-CoV-2.

Modelling the effects of social distancing, antiviral therapy, and booster shots on mitigating Omicron spread

As the COVID-19 situation changes because of emerging variants and updated vaccines, an elaborate mathematical model is essential in crafting proactive and effective control strategies. We propose a COVID-19 mathematical model considering variants, booster shots, waning, and antiviral drugs. We quantify the effects of social distancing in the Republic of Korea by estimating the reduction in transmission induced by government policies from February 26, 2021 to February 3, 2022. Simulations show that the next epidemic peak can be estimated by investigating the effects of waning immunity. This research emphasizes that booster vaccination should be administered right before the next epidemic wave, which follows the increasing waned population. Policymakers are recommended to monitor the waning population immunity using mathematical models or other predictive methods. Moreover, our simulations considering a new variant's transmissibility, severity, and vaccine evasion suggest intervention measures that can reduce the severity of COVID-19.

Microneedles: An Emerging Vaccine Delivery Tool and a Prospective Solution to the Challenges of SARS-CoV-2 Mass Vaccination

Vaccination is an effective measure to prevent infectious diseases. Protective immunity is induced when the immune system is exposed to a vaccine formulation with appropriate immunogenicity. However, traditional injection vaccination is always accompanied by fear and severe pain. As an emerging vaccine delivery tool, microneedles overcome the problems associated with routine needle vaccination, which can effectively deliver vaccines rich in antigen-presenting cells (APCs) to the epidermis and dermis painlessly, inducing a strong immune response. In addition, microneedles have the advantages of avoiding cold chain storage and have the flexibility of self-operation, which can solve the logistics and delivery obstacles of vaccines, covering the vaccination of the special population more easily and conveniently. Examples include people in rural areas with restricted vaccine storage facilities and medical professionals, elderly and disabled people with limited mobility, infants and young children afraid of pain. Currently, in the late stage of fighting against COVID-19, the main task is to increase the coverage of vaccines, especially for special populations. To address this challenge, microneedle-based vaccines have great potential to increase global vaccination rates and save many lives. This review describes the current progress of microneedles as a vaccine delivery system and its prospects in achieving mass vaccination against SARS-CoV-2.

English tort law and the pandemic: the dog that has not barked

As of February 2023, no case has been reported in the U.K., either in the law reports or in the media, of a victim of COVID-19 suing in tort a person or organisation alleged to have caused the victim to contract the disease. This article considers the reasons this situation might have arisen. It provisionally concludes that the main legal reasons might lie in the applicable doctrines of factual causation and goes on to discuss whether uncertainty in those doctrines should be resolved in the courts.

Effectiveness of sample pooling strategies for diagnosis of SARS-CoV-2: Specimen pooling vs. RNA elutes pooling

PURPOSE

The pandemic of SARS-CoV-2 or COVID-19 has hugely created an economic imbalance worldwide. With the exponential increase in the number of cases and to keep in check on the community transmission, there is high demand and acute shortage of diagnostic kits. The pooled-sample strategy turns out to be the promising strategy intended to determine the optimal testing for specimens with limited resources and without losing the test sensitivity and specificity. The study was performed with standard molecular biology graded lab equipment, FDA-approved COVID-19 RNA extraction, and SARS-CoV-2 tests kits.

MATERIALS AND METHODS

The study aims to comparatively analyze the pooling strategy of the naso-oropharyngeal specimen sample and RNA extracted from the same patient samples in the pool of 3,5, and 8 with no significant loss in test usability. Another primary focus of the study was detection of low or borderline SARS-CoV-2 positives in the pooling strategy. A total of 300 samples (240 positives and 60 negatives) were tested for 3, 5, and 8 pools of specimen samples and RNA elutes.

RESULTS

The comparative analysis determined the sensitivity for three and five pool strategy to be above 98% and eight pool strategy to be 100%.

CONCLUSION

The RNA elutes pooling strategy concordance rate is better than that of specimen pooling with 100% specificity. Thus, in the substantial crisis of resources with the global pandemic, pooling approaches for SARS-CoV-2 can be practical in a low prevalence rate of 5%.

Single-Center Experience in Detecting Influenza Virus, RSV and SARS-CoV-2 at the Emergency Department

Reverse transcription polymerase chain reaction (RT-PCR) on respiratory tract swabs has become the gold standard for sensitive and specific detection of influenza virus, respiratory syncytial virus (RSV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this retrospective analysis, we report on the successive implementation and routine use of multiplex RT-PCR testing for patients admitted to the Internal Medicine Emergency Department (ED) at a tertiary care center in Western Austria, one of the hotspots in the early coronavirus disease 2019 (COVID-19) pandemic in Europe. Our description focuses on the use of the Cepheid^® Xpert^® Xpress closed RT-PCR system in point-of-care testing (POCT). Our indications for RT-PCR testing changed during the observation period: From the cold season 2016/2017 until the cold season 2019/2020, we used RT-PCR to diagnose influenza or RSV infection in patients with fever and/or respiratory symptoms. Starting in March 2020, we used the RT-PCR for SARS-CoV-2 and a multiplex version for the combined detection of all these three respiratory viruses to also screen subjects who did not present with symptoms of infection but needed in-hospital medical treatment for other reasons. Expectedly, the switch to a more liberal RT-PCR test strategy resulted in a substantial increase in the number of tests. Nevertheless, we observed an immediate decline in influenza virus and RSV detections in early 2020 that coincided with public SARS-CoV-2 containment measures. In contrast, the extensive use of the combined RT-PCR test enabled us to monitor the re-emergence of influenza and RSV detections, including asymptomatic cases, at the end of 2022 when COVID-19 containment measures were no longer in place. Our analysis of PCR results for respiratory viruses from a real-life setting at an ED provides valuable information on the epidemiology of those infections over several years, their contribution to morbidity and need for hospital admission, the risk for nosocomial introduction of such infection into hospitals from asymptomatic carriers, and guidance as to how general precautions and prophylactic strategies affect the dynamics of those infections.

Uncertainty and error in SARS-CoV-2 epidemiological parameters inferred from population-level epidemic models

During the SARS-CoV-2 pandemic, epidemic models have been central to policy-making. Public health responses have been shaped by model-based projections and inferences, especially related to the impact of various non-pharmaceutical interventions. Accompanying this has been increased scrutiny over model performance, model assumptions, and the way that uncertainty is incorporated and presented. Here we consider a population-level model, focusing on how distributions representing host infectiousness and the infection-to-death times are modelled, and particularly on the impact of inferred epidemic characteristics if these distributions are mis-specified. We introduce an SIR-type model with the infected population structured by 'infected age', i.e. the number of days since first being infected, a formulation that enables distributions to be incorporated that are consistent with clinical data. We show that inference based on simpler models without infected age, which implicitly mis-specify these distributions, leads to substantial errors in inferred quantities relevant to policy-making, such as the reproduction number and the impact of interventions. We consider uncertainty quantification via a Bayesian approach, implementing this for both synthetic and real data focusing on UK data in the period 15 Feb-14 Jul 2020, and emphasising circumstances where it is misleading to neglect uncertainty. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

COVID-19 vaccine acceptance in sub-Saharan African countries: A systematic review and meta-analysis

Vaccination is the most effective intervention for the primary prevention of COVID-19. Several studies have been conducted in sub-Saharan African countries on the acceptance and associated factors of COVID-19 vaccine. This review and meta-analysis aimed to recapitulate the pooled magnitude of vaccine acceptance and its favoring factors in sub-Saharan African countries. PUBMED, MEDLINE, Science Direct, Web of Science, and SCOPUS were the main databases searched from 15 March to 5 June 2022; and all the articles written in the English language were included. Also, some articles were retrieved from biomedical peer-reviewed journal sites and Google scholar. The quality of thirty-five selected articles was evaluated using an adapted scale for evaluating cross-sectional studies based on the Newcastle-Ottawa Scale. The result of the review and meta-analysis revealed that COVID-19 vaccine acceptance rate varied across studies. In a pooled analysis, factors such as; higher-level perception of infection risk (OR (95% CI (2.7 (2.1, 3.4))), perceived vaccine safety (13.9 (9.2, 20.9)), virus-related good knowledge (2.7 (2.3, 3.2)) and appropriate attitude (5.9 (4.4, 7.8)), adherence to safety precautions (5.5 (4.8, 6.2)), and infection experience (4.4 (2.8, 6.9)) were positively affected the COVID-19 vaccine acceptance. Also, vaccine acceptance was found to be high among males and chronically ill individuals. Thus, understanding factors that enhance vaccine acceptance would support planners to augment vaccine uptake in the region.

A real-time regional model for COVID-19: Probabilistic situational awareness and forecasting

The COVID-19 pandemic is challenging nations with devastating health and economic consequences. The spread of the disease has revealed major geographical heterogeneity because of regionally varying individual behaviour and mobility patterns, unequal meteorological conditions, diverse viral variants, and locally implemented non-pharmaceutical interventions and vaccination roll-out. To support national and regional authorities in surveilling and controlling the pandemic in real-time as it unfolds, we here develop a new regional mathematical and statistical model. The model, which has been in use in Norway during the first two years of the pandemic, is informed by real-time mobility estimates from mobile phone data and laboratory-confirmed case and hospitalisation incidence. To estimate regional and time-varying transmissibility, case detection probabilities, and missed imported cases, we developed a novel sequential Approximate Bayesian Computation method allowing inference in useful time, despite the high parametric dimension. We test our approach on Norway and find that three-week-ahead predictions are precise and well-calibrated, enabling policy-relevant situational awareness at a local scale. By comparing the reproduction numbers before and after lockdowns, we identify spatially heterogeneous patterns in their effect on the transmissibility, with a stronger effect in the most populated regions compared to the national reduction estimated to be 85% (95% CI 78%-89%). Our approach is the first regional changepoint stochastic metapopulation model capable of real time spatially refined surveillance and forecasting during emergencies.

Gold nanoparticle conjugate-based lateral flow immunoassay (LFIA) for rapid detection of RBD antigen of SARS-CoV-2 in clinical samples using a smartphone-based application

The coronavirus disease 2019 (COVID-19) pandemic has emphasized the need for development of a rapid diagnostic device for the effective treatment and its mitigation. Lateral flow immunoassay (LFIA) belongs to a class of diagnostic devices, which has the benefit of providing quick results, easy to handle, low cost, and on-site applicable. So far, several LFIA has been developed for the detection of infectious severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), however, only a few of them are antigen (Ag)-based. Here, we describe an antibody (Ab)-labeled gold nanoparticles (AuNPs)-based LFIA (AuNPs-LFIA) for the detection of Receptor-Binding Domain (RBD) of SARS-CoV-2. For this, RBD Ab of SARS-CoV-2 was conjugated with the AuNPs, which served as a detecting probe. The fabricated LFIA strip was optimized for different parameters such as membrane pore size, blocking conditions, Ab coating concentration, and conjugate incubation. The optimized LFIA strips were validated in spiked buffer samples and the optimal limit of detection was found to be 1 ng/ml, which was confirmed by a smartphone-based application. Moreover, the developed AuNPs-LFIA strips effectively detected RBD Ag in 100 clinical samples with 94.3% sensitivity and 90.9% specificity in clinical samples when compared with the gold standard (RT-PCR). The fabricated LFIAs are reported to have storage stability of up to 21 days at 4°C and room temperature (RT). Hence, the developed LFIA can be used as a portable, cost-effective diagnostic device for rapid detection of SARS-CoV-2.

COVID-19 vaccine hesitancy in Sri Lanka: A national level survey

Objective

It is important to understand the factors associated with vaccination hesitancy for a given population for successful coronavirus disease-2019 (COVID-19) immunization program. This survey aimed to examine the prevalence of vaccine hesitancy and associated sociodemographic factors.

Methods

A cross-sectional online survey was undertaken by circulating through social media platforms. Survey questions included sociodemographics and vaccination acquisition-related questions.

Results

The study comprised a total of 3621 respondents. Over one-fifth of the unvaccinated population were identified as vaccine hesitancy group. Ethnicity and district indicated significant associations with vaccine hesitancy (P < 0.05). Indian Tamils (Odds Radio [OR] 2.222; 95%Confidence interval [CI], 1.150-4.294; P = 0.018), Sri Lankan Tamils (OR 1.714; 95% CI, 1.181-2.488; P = 0.005), and Sri Lankan Moors (OR 1.913; 95% CI, 1.316-2.781; P = 0.001) had significantly higher odds of vaccine hesitancy when compared to the Sinhalese. People in rural areas also had greater odds of vaccine hesitancy (OR 1.339; 95% CI, 1.000-1.793; P = 0.05) compared to municipal council areas.

Conclusion

Vaccine hesitancy was considerably high in this survey population. Our results emphasize the need of the Sri Lankan government taking appropriate efforts to establish a targeted COVID-19 vaccination campaign plan for rural and Colombo district residents. Attention should also be given to ethnic minority groups.

Using a real-world network to model the trade-off between stay-at-home restriction, vaccination, social distancing and working hours on COVID-19 dynamics

Background

Human behaviour, economic activity, vaccination, and social distancing are inseparably entangled in epidemic management. This study aims to investigate the effects of various parameters such as stay-at-home restrictions, work hours, vaccination, and social distance on the containment of pandemics such as COVID-19.

Methods

To achieve this, we have developed an agent based model based on a time-dynamic graph with stochastic transmission events. The graph is constructed from a real-world social network. The edges of graph have been categorized into three categories: home, workplaces, and social environment. The conditions needed to mitigate the spread of wild-type COVID-19 and the delta variant have been analyzed. Our purposeful agent based model has carefully executed tens of thousands of individual-based simulations. We propose simple relationships for the trade-offs between effective reproduction number (R _e), transmission rate, working hours, vaccination, and stay-at-home restrictions.

Results

We have found that the effect of a 13.6% increase in vaccination for wild-type (WT) COVID-19 is equivalent to reducing four hours of work or a one-day stay-at-home restriction. For the delta, 20.2% vaccination has the same effect. Also, since we can keep track of household and non-household infections, we observed that the change in household transmission rate does not significantly alter the R _e. Household infections are not limited by transmission rate due to the high frequency of connections. For the specifications of COVID-19, the R _e depends on the non-household transmissions rate.

Conclusions

Our findings highlight that decreasing working hours is the least effective among the non-pharmaceutical interventions. Our results suggest that policymakers decrease work-related activities as a last resort and should probably not do so when the effects are minimal, as shown. Furthermore, the enforcement of stay-at-home restrictions is moderately effective and can be used in conjunction with other measures if absolutely necessary.

A comparison of COVID-19 outbreaks across US Combined Statistical Areas using new methods for estimating R0 and social distancing behaviour

We investigated the initial outbreak rates and subsequent social distancing behaviour over the initial phase of the COVID-19 pandemic across 29 Combined Statistical Areas (CSAs) of the United States. We used the Numerus Model Builder Data and Simulation Analysis (NMB-DASA) web application to fit the exponential phase of a SCLAIV+D (Susceptible, Contact, Latent, Asymptomatic infectious, symptomatic Infectious, Vaccinated, Dead) disease classes model to outbreaks, thereby allowing us to obtain an estimate of the basic reproductive number R₀ for each CSA. Values of R₀ ranged from 1.9 to 9.4, with a mean and standard deviation of 4.5±1.8. Fixing the parameters from the exponential fit, we again used NMB-DASA to estimate a set of social distancing behaviour parameters to compute an epidemic flattening index c_flatten. Finally, we applied hierarchical clustering methods using this index to divide CSA outbreaks into two clusters: those presenting a social distancing response that was either weaker or stronger. We found c_flatten to be more influential in the clustering process than R₀. Thus, our results suggest that the behavioural response after a short initial exponential growth phase is likely to be more determinative of the rise of an epidemic than R₀ itself.

Optimal control strategies to combat COVID-19 transmission: A mathematical model with incubation time delay

The coronavirus disease 2019, started spreading around December 2019, still persists in the population all across the globe. Though different countries have been able to cope with the disease to some extent and vaccination for the same has been developed, it cannot be ignored that the disease is still not on the verge of completely eradicating, which in turn creates a need for having deeper insights of the disease in order to understand it well and hence be able to work towards its eradication. Meanwhile, using mitigation strategies like non-pharmaceutical interventions can help in controlling the disease. In this work, our aim is to study the dynamics of COVID-19 using compartmental approach by applying various analytical methods. We obtain formula for important tools like R0 and establish the stability of disease-free equilibrium point for R0<1. Further, based on R0, we discuss the stability and existence of the endemic equilibrium point. We incorporate various control strategies possible and using optimal control theory, study their expected positive impacts on the spread of the disease. Later, using a biologically feasible set of parameters, we numerically analyse the model. We even study the trend of the outbreak in China, for over 120 days, where the active cases rise up to a peak and then the curve flattens.

Testing for COVID-19 during an outbreak within a large UK prison: an evaluation of mass testing to inform outbreak control

OBJECTIVES

The aim of this paper was to describe the results of mass asymptomatic testing for COVID-19 in a male prison in England following the declaration of an outbreak. It provides novel data on the implementation of a mass testing regime within a prison during the pandemic.

METHODS

The paper is an observational evaluation of the mass testing conducted for 6 months following the declaration of a COVID-19 outbreak within a prison. It investigated the incidence of positive cases in both staff and residents using polymerase chain reaction testing.

RESULTS

Data from October 2020 until March 2021 was included. A total of 2170 tests were performed by 851 residents and 182 staff members; uptake was 48.3% for people living in prison and 30.4% for staff. Overall test positivity was 11.6% (14.3% for residents, 3.0% for staff), with around one-quarter of these reporting symptoms. The prison wing handling new admissions reported the second-lowest positivity rate (9.4%) of the eight wings.

CONCLUSION

Mass testing for COVID-19 over a short space of time can lead to rapid identification of additional cases, particularly asymptomatic cases. Testing that relies on residents and staff reporting symptoms will underestimate the true extent of transmission and will likely lead to a prolonged outbreak.

Early estimates of the incidence trend and the reproductive number of the monkeypox epidemic in Brazil

BACKGROUND

We aimed to calculate the weekly growth of the incidence and the effective reproductive number (Rt) of the 2022 Monkeypox epidemic during its introduction in Brazil.

METHOD

We described the case distribution in the country and calculated the incidence trend and the Rt in the four geographical states with the highest case reports. By using two regression approaches, count model and the Prais-Winsten, we calculated the relative incidence increase. Moreover, we estimated the Rt for the period between the 24th and the 50th days after the first official report, using a serial interval reported in another population and two alternative values (± 3 days).

RESULTS

Up to August 22, 3.896 Monkeypox cases were confirmed in Brazil. The weekly incidence increases were between 37.5% (95% CI: 20.7% - 56,6%) and 82.1% (95% CI: 59.5%-107.8%), and all estimates of Rt were significantly higher than 1 in the four states analyzed.

CONCLUSIONS

The Monkeypox outbreak in Brazil is a significant public health emergency that requires coordinated public health strategies such as testing, contact tracing, and vaccination.

Reliability of Early Estimates of the Basic Reproduction Number of COVID-19: A Systematic Review and Meta-Analysis

OBJECTIVE

This systematic review estimated the pooled R0 for early COVID-19 outbreaks and identified the impact of study-related factors such as methods, study location and study period on the estimated R0.

METHODS

We searched electronic databases for human studies published in English between 1 December 2019 and 30 September 2020 with no restriction on country/region. Two investigators independently performed the data extraction of the studies selected for inclusion during full-text screening. The primary outcome, R0, was analysed by random-effects meta-analysis using the restricted maximum likelihood method.

RESULTS

We identified 26,425 studies through our search and included 151 articles in the systematic review, among which 81 were included in the meta-analysis. The estimates of R0 from studies included in the meta-analysis ranged from 0.4 to 12.58. The pooled R0 for COVID-19 was estimated to be 2.66 (95% CI, 2.41-2.94). The results showed heterogeneity among studies and strong evidence of a small-study effect.

CONCLUSIONS

The high heterogeneity in studies makes the use of the R0 for basic epidemic planning difficult and presents a huge problem for risk assessment and data synthesis. Consensus on the use of R0 for outbreak assessment is needed, and its use for assessing epidemic risk is not recommended.

Two Years into the COVID-19 Pandemic: Lessons Learned

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible and virulent human-infecting coronavirus that emerged in late December 2019 in Wuhan, China, causing a respiratory disease called coronavirus disease 2019 (COVID-19), which has massively impacted global public health and caused widespread disruption to daily life. The crisis caused by COVID-19 has mobilized scientists and public health authorities across the world to rapidly improve our knowledge about this devastating disease, shedding light on its management and control, and spawned the development of new countermeasures. Here we provide an overview of the state of the art of knowledge gained in the last 2 years about the virus and COVID-19, including its origin and natural reservoir hosts, viral etiology, epidemiology, modes of transmission, clinical manifestations, pathophysiology, diagnosis, treatment, prevention, emerging variants, and vaccines, highlighting important differences from previously known highly pathogenic coronaviruses. We also discuss selected key discoveries from each topic and underline the gaps of knowledge for future investigations.

Basic reproduction number of the COVID-19 Delta variant: Estimation from multiple transmission datasets

The basic reproduction number, $ R_0 $, plays a central role in measuring the transmissibility of an infectious disease, and it thus acts as the fundamental index for planning control strategies. In the present study, we apply a branching process model to meticulously observed contact tracing data from Wakayama Prefecture, Japan, obtained in early 2020 and mid-2021. This allows us to efficiently estimate $ R_0 $ and the dispersion parameter $ k $ of the wild-type COVID-19, as well as the relative transmissibility of the Delta variant and relative transmissibility among fully vaccinated individuals, from a very limited data. $ R_0 $ for the wild type of COVID-19 is estimated to be 3.78 (95% confidence interval [CI]: 3.72-3.83), with $ k = 0.236 $ (95% CI: 0.233-0.240). For the Delta variant, the relative transmissibility to the wild type is estimated to be 1.42 (95% CI: 0.94-1.90), which gives $ R_0 = 5.37 $ (95% CI: 3.55-7.21). Vaccine effectiveness, determined by the reduction in the number of secondary transmissions among fully vaccinated individuals, is estimated to be 91% (95% CI: 85%-97%). The present study highlights that basic reproduction numbers can be accurately estimated from the distribution of minor outbreak data, and these data can provide further insightful epidemiological estimates including the dispersion parameter and vaccine effectiveness regarding the prevention of transmission.

VGsim: Scalable viral genealogy simulator for global pandemic

Accurate simulation of complex biological processes is an essential component of developing and validating new technologies and inference approaches. As an effort to help contain the COVID-19 pandemic, large numbers of SARS-CoV-2 genomes have been sequenced from most regions in the world. More than 5.5 million viral sequences are publicly available as of November 2021. Many studies estimate viral genealogies from these sequences, as these can provide valuable information about the spread of the pandemic across time and space. Additionally such data are a rich source of information about molecular evolutionary processes including natural selection, for example allowing the identification of new variants with transmissibility and immunity evasion advantages. To our knowledge, there is no framework that is both efficient and flexible enough to simulate the pandemic to approximate world-scale scenarios and generate viral genealogies of millions of samples. Here, we introduce a new fast simulator VGsim which addresses the problem of simulation genealogies under epidemiological models. The simulation process is split into two phases. During the forward run the algorithm generates a chain of population-level events reflecting the dynamics of the pandemic using an hierarchical version of the Gillespie algorithm. During the backward run a coalescent-like approach generates a tree genealogy of samples conditioning on the population-level events chain generated during the forward run. Our software can model complex population structure, epistasis and immunity escape.

We develop a fast and flexible simulation software package VGsim for modeling epidemiological processes and generating genealogies of large pathogen samples. The software takes into account host population structure, pathogen evolution, host immunity and some other epidemiological aspects. The computational efficiency of the package allows to simulate genealogies of tens of millions of samples, which is important, e.g., for SARS-CoV-2 genome studies.

COVID-19 trends, public restrictions policies and vaccination status by economic ranking of countries: a longitudinal study from 110 countries

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has transitioned to a third phase and many variants have been originated. There has been millions of lives loss as well as billions in economic loss. The morbidity and mortality for COVID-19 varies by country. There were different preventive approaches and public restrictions policies have been applied to control the COVID-19 impacts and usually measured by Stringency Index. This study aimed to explore the COVID-19 trend, public restriction policies and vaccination status with economic ranking of countries.

METHODS

We received open access data from Our World in Data. Data from 210 countries were available. Countries (n = 110) data related to testing, which is a key variable in the present study, were included for the analysis and remaining 100 countries were excluded due to incomplete data. The analysis period was set between January 22, 2020 (when COVID-19 was first officially reported) and December 28, 2021. All analyses were stratified by year and the World Bank income group. To analyze the associations among the major variables, we used a longitudinal fixed-effects model.

RESULTS

Out of the 110 countries included in our analysis, there were 9 (8.18%), 25 (22.72%), 31 (28.18%), and 45 (40.90%) countries from low income countries (LIC), low and middle income countries (LMIC), upper middle income countries (UMIC) and high income countries (HIC) respectively. New case per million was similar in LMIC, UMIC and HIC but lower in LIC. The number of new COVID-19 test were reduced in HIC and LMIC but similar in UMIC and LIC. Stringency Index was negligible in LIC and similar in LMIC, UMIC and HIC. New positivity rate increased in LMIC and UMIC. The daily incidence rate was positively correlated with the daily mortality rate in both 2020 and 2021. In 2020, Stringency Index was positive in LIC and HIC but a negative association in LMIC and in 2021 there was a positive association between UMIC and HIC. Vaccination coverage did not appear to change with mortality in 2021.

CONCLUSION

New COVID-19 cases, tests, vaccinations, positivity rates, and Stringency indices were low in LIC and highest in UMIC. Our findings suggest that the available resources of COVID-19 pandemic would be allocated by need of countries; LIC and UMIC.

SAfE transport: wearing face masks significantly reduces the spread of COVID-19 on trains

COVID-19 has had a substantial impact globally. It spreads readily, particularly in enclosed and crowded spaces, such as public transport carriages, yet there are limited studies on how this risk can be reduced. We developed a tool for exploring the potential impacts of mitigation strategies on public transport networks, called the Systems Analytics for Epidemiology in Transport (SAfE Transport). SAfE Transport combines an agent-based transit assignment model, a community-wide transmission model, and a transit disease spread model to support strategic and operational decision-making. For this simulated COVID-19 case study, the transit disease spread model incorporates both direct (person-to-person) and fomite (person-to-surface-to-person) transmission modes. We determine the probable impact of wearing face masks on trains over a seven day simulation horizon, showing substantial and statistically significant reductions in new cases when passenger mask wearing proportions are greater than 80%. The higher the level of mask coverage, the greater the reduction in the number of new infections. Also, the higher levels of mask coverage result in an earlier reduction in disease spread risk. These results can be used by decision makers to guide policy on face mask use for public transport networks.

Diagnostic Tools for Rapid Screening and Detection of SARS-CoV-2 Infection

The novel coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has severely impacted human health and the health management system globally. The ongoing pandemic has required the development of more effective diagnostic strategies for restricting deadly disease. For appropriate disease management, accurate and rapid screening and isolation of the affected population is an efficient means of containment and the decimation of the disease. Therefore, considerable efforts are being directed toward the development of rapid and robust diagnostic techniques for respiratory infections, including SARS-CoV-2. In this article, we have summarized the origin, transmission, and various diagnostic techniques utilized for the detection of the SARS-CoV-2 virus. These higher-end techniques can also detect the virus copy number in asymptomatic samples. Furthermore, emerging rapid, cost-effective, and point-of-care diagnostic devices capable of large-scale population screening for COVID-19 are discussed. Finally, some breakthrough developments based on spectroscopic diagnosis that could revolutionize the field of rapid diagnosis are discussed.

Keeping up with the COVID's-Could siRNA-based antivirals be a part of the answer?

Coronavirus disease 2019 (COVID-19) is a highly contagious viral disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This deadly infection has resulted in more than 5.2 million deaths worldwide. The global rollout of COVID-19 vaccines has without doubt saved countless lives by reducing the severity of symptoms for patients. However, as the virus continues to evolve, there is a risk that the vaccines and antiviral designed to target the infection will no longer be therapeutically viable. Furthermore, there remain fears over both the short and long-term side effects of repeat exposure to currently available vaccines. In this review, we discuss the pros and cons of the vaccine rollout and promote the idea of a COVID medicinal toolbox made up of different antiviral treatment modalities, and present some of the latest therapeutic strategies that are being explored in this respect to try to combat the COVID-19 virus and other COVID viruses that are predicted to follow. Lastly, we review current literature on the use of siRNA therapeutics as a way to remain adaptable and in tune with the ever-evolving mutation rate of the COVID-19 virus.

Lockdowns exert selection pressure on overdispersion of SARS-CoV-2 variants

The SARS-CoV-2 ancestral strain has caused pronounced superspreading events, reflecting a disease characterized by overdispersion, where about 10% of infected people cause 80% of infections. New variants of the disease have different person-to-person variability in viral load, suggesting for example that the Alpha (B.1.1.7) variant is more infectious but relatively less prone to superspreading. Meanwhile, non-pharmaceutical mitigation of the pandemic has focused on limiting social contacts (lockdowns, regulations on gatherings) and decreasing transmission risk through mask wearing and social distancing. Using a mathematical model, we show that the competitive advantage of disease variants may heavily depend on the restrictions imposed. In particular, we find that lockdowns exert an evolutionary pressure which favours variants with lower levels of overdispersion. Our results suggest that overdispersion is an evolutionarily unstable trait, with a tendency for more homogeneously spreading variants to eventually dominate.

•

Novel variants of SARS-CoV-2 appear to be less prone to superspreading.

•

A new model shows that it is advantageous for the pathogen to spread homogeneously.

•

Interventions exert a selective pressure towards developing homogeneous transmission.

•

The results have implications for the assessment of novel variants.

•

Adds to understanding of how behaviour and interventions shape pathogen evolution.

Ventilation strategies and design impacts on indoor airborne transmission: A review

The COVID-19 outbreak has brought the indoor airborne transmission issue to the forefront. Although ventilation systems provide clean air and dilute indoor contaminated air, there is strong evidence that airborne transmission is the main route for contamination spread. This review paper aims to critically investigate ventilation impacts on particle spread and identify efficient ventilation strategies in controlling aerosol distribution in clinical and non-clinical environments. This article also examines influential ventilation design features (i.e., exhaust location) affecting ventilation performance in preventing aerosols spread. This paper shortlisted published documents for a review based on identification (keywords), pre-processing, screening, and eligibility of these articles. The literature review emphasizes the importance of ventilation systems' design and demonstrates all strategies (i.e., mechanical ventilation) could efficiently remove particles if appropriately designed. The study highlights the need for occupant-based ventilation systems, such as personalized ventilation instead of central systems, to reduce cross-infections. The literature underlines critical impacts of design features like ventilation rates and the number and location of exhausts and suggests designing systems considering airborne transmission. This review underpins that a higher ventilation rate should not be regarded as a sole indicator for designing ventilation systems because it cannot guarantee reducing risks. Using filtration and decontamination devices based on building functionalities and particle sizes can also increase ventilation performance. This paper suggests future research on optimizing ventilation systems, particularly in high infection risk spaces such as multi-storey hotel quarantine facilities. This review contributes to adjusting ventilation facilities to control indoor aerosol transmission.

SARS-CoV-2 Transmission and Prevention in the Era of the Delta Variant

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) delta variant transmits much more rapidly than prior SARS-CoV-2 viruses. The primary mode of transmission is via short range aerosols that are emitted from the respiratory tract of an index case. There is marked heterogeneity in the spread of this virus, with 10% to 20% of index cases contributing to 80% of secondary cases, while most index cases have no subsequent transmissions. Vaccination, ventilation, masking, eye protection, and rapid case identification with contact tracing and isolation can all decrease the transmission of this virus.

Epidemiological and genomic findings of the first documented Italian outbreak of SARS-CoV-2 Alpha variant of concern

From 24 December 2020 to 8 February 2021, 163 cases of SARS-CoV-2 Alpha variant of concern (VOC) were identified in Chieti province, Abruzzo region. Epidemiological data allowed the identification of 14 epi-clusters. With one exception, all the epi-clusters were linked to the town of Guardiagrele: 149 contacts formed the network, two-thirds of which were referred to the family/friends context. Real data were then used to estimate transmission parameters. According to our method, the calculated Re(t) was higher than 2 before the 12 December 2020. Similar values were obtained from other studies considering Alpha VOC. Italian sequence data were combined with a random subset of sequences obtained from the GISAID database. Genomic analysis showed close identity between the sequences from Guardiagrele, forming one distinct clade. This would suggest one or limited unspecified viral introductions from outside to Abruzzo region in early December 2020, which led to the diffusion of Alpha VOC in Guardiagrele and in neighbouring municipalities, with very limited inter-regional mixing.

A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data

The transmission dynamics and burden of SARS-CoV-2 in many regions of the world is still largely unknown due to the scarcity of epidemiological analyses and lack of testing to assess the prevalence of disease. In this work, we develop a quantitative framework based on excess mortality data to reconstruct SARS-CoV-2 transmission dynamics and assess the level of underreporting in infections and deaths. Using weekly all-cause mortality data from Iran, we are able to show a strong agreement between our attack rate estimates and seroprevalence measurements in each province and find significant heterogeneity in the level of exposure across the country with 11 provinces reaching near 100% attack rates. Despite having a young population, our analysis reveals that incorporating limited access to medical services in our model, coupled with undercounting of COVID-19-related deaths, leads to estimates of infection fatality rate in most provinces of Iran that are comparable to high-income countries.

Prioritizing COVID-19 vaccination. Part 2: Real-time comparison between single-dose and double-dose in Japan

Japan successfully implemented a mass vaccination program for coronavirus disease 2019 (COVID-19), immunizing more than 1 million persons a day by July 2021. Given the COVID-19 vaccination capacity limitations, an urgent question was raised regarding whether it would be better to (ⅰ) complete double-dose COVID-19 vaccination among healthcare personnel and older adults before beginning double-dose vaccination of younger adults (double-dose strategy) or (ⅱ) allocate a single dose of COVID-19 vaccine to all adults regardless of age before administering the second dose (single-dose-first strategy). We used an age-structured susceptible-infectious-recovered (SIR) compartment model to compare the effectiveness of possible COVID-19 vaccination strategies and the length of public health and social measures (PHSM) to minimize the cumulative COVID-19 disease risk and death toll. Our results indicate that if the single-dose-first strategy was taken, an estimated total of 1,387,078 persons, i.e., 263,315 children, 928,518 young adults, and 195,245 older adults, would develop COVID-19, resulting in 15,442 deaths. In contrast, if the double-dose strategy was taken instead, an estimated total of 1,900,172 persons, i.e., 377,107 children, 1,315,927 young adults, and 207,138 older adults, would develop COVID-19, yielding 17,423 deaths. Real-time investigation favored the disease transmission blocking option, i.e., single-dose vaccination strategy. Applying the single-dose-first strategy should yield a smaller epidemic size than applying the double-dose strategy; however, for both strategies, PHSM will be essential by the time second-dose COVID-19 vaccination is complete among all adults.