Search

Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020.

Vaccines against the SARS-CoV-2 virus were developed in record time, but their distribution has been highly unequal. With demand saturating in high-income countries, many low- and middle-income countries (LMIC) finally have an opportunity to acquire COVID-19 vaccines. But the pandemic has taken its toll, and a majority of LMIC populations have partial immunity to COVID-19 disease due primarily to viral infection. This existing immunity, combined with resource limitations, raises the question of how LMICs should prioritize COVID-19 vaccines relative to other competing health priorities. We modify an established computational model, Covasim, to address these questions in four diverse country-like settings under a variety of viral evolution, vaccine delivery, and novel immunity scenarios. Under continued Omicron-like viral evolution and mid-level immunity assumptions, results show that COVID-19 vaccines could avert up to 2 deaths per 1,000 doses if administered to high-risk (60+) populations as prime+boost or annual boosting campaigns. Similar immunization efforts reaching healthy children and adults would avert less than 0.1 deaths per 1,000 doses. Together, these modeling results can help to support normative guidelines and programmatic decision making towards objectively maximizing population health.

Antiretroviral therapy inhibits HIV-1 replication but is not curative due to establishment of a persistent reservoir after virus integration into the host genome. Reservoir reduction is therefore an important HIV-1 cure strategy. Some HIV-1 nonnucleoside reverse transcriptase inhibitors induce HIV-1 selective cytotoxicity in vitro but require concentrations far exceeding approved dosages. Focusing on this secondary activity, we found bifunctional compounds with HIV-1–infected cell kill potency at clinically achievable concentrations. These targeted activator of cell kill (TACK) molecules bind the reverse transcriptase–p66 domain of monomeric Gag-Pol and act as allosteric modulators to accelerate dimerization, resulting in HIV-1 + cell death through premature intracellular viral protease activation. TACK molecules retain potent antiviral activity and selectively eliminate infected CD4 + T cells isolated from people living with HIV-1, supporting an immune-independent clearance strategy.

In 2020, the WHO launched its first Global Strategy to Accelerate the Elimination of Cervical Cancer, outlining an ambitious set of targets for countries to achieve over the next decade. At the same time, new tools, technologies, and strategies are in the pipeline that may improve screening performance, expand the reach of prophylactic vaccines, and prevent the acquisition, persistence and progression of oncogenic HPV. Detailed mechanistic modeling can help identify the combinations of current and future strategies to combat cervical cancer. Open-source modeling tools are needed to shift the capacity for such evaluations in-country. Here, we introduce the Human papillomavirus simulator (HPVsim), a new, flexible agent-based model that can be parameterized with country-specific vital dynamics, structured sexual networks, co-transmitting HPV genotypes, B- and T-cell mediated immunity, and high-resolution disease natural history. HPVsim is designed with a user-first lens: it is implemented in Python, has built-in tools for simulating commonly-used interventions, includes a comprehensive set of tests and documentation, and runs quickly (seconds to minutes) on a laptop. Useful complexity was not sacrificed: the platform is flexible, allowing bespoke scenario modeling.Author summaryMathematical models have been integral in setting ambitious goals for cervical cancer elimination, along with determining intermediate targets for vaccination, screening, and treatment. However, given that elimination strategies encompass decade-long timelines, these targets will inevitably need updating over time as the landscape of available technologies for combating cervical cancer evolves. In this work, we introduce a new model, HPVsim, which can rapidly evaluate pathways toward elimination under complex combinations of new and existing interventions. HPVsim is a flexible agent-based model with country-specific vital dynamics, structured sexual networks, co-transmitting HPV genotypes, B- and T-cell mediated immunity, and high-resolution disease natural history. Written in Python, with easy installation and full testing and documentation, the model is designed so that analysis pipelines can be created with very little effort. By improving access to cervical cancer modeling tools, we aim to enable real-time updates and nimble adaptation of cervical cancer elimination targets in response to changing technologies providing realistic targets on the path to cervical cancer elimination.

The biological and behavioral underpinnings of family planning (FP) unfold on an individual level, across a full reproductive life course, and within a complex system of social and structural constraints. Yet, much of the existing FP modeling landscape has focused solely on macro- or population-level dynamics of family planning. There is a need for an individual-based approach to provide a deeper understanding of how family planning is intertwined with individuals’ lives and health at the micro-level, which can contribute to more effective, person-centered design of both contraceptive technologies and programmatic interventions. This article introduces the Family Planning Simulator (FPsim), a data-driven, agent-based model of family planning, which explicitly models individual heterogeneity in biology and behavior over the life course. Agents in FPsim can experience a wide range of life-course events, such as increases in fecundability (and primary infertility), sexual debut, contraceptive choice, postpartum family planning, abortion, miscarriage, stillbirth, infant mortality, and maternal mortality. The core components of the model – fecundability and contraceptive choice, are represented individually and probabilistically, following age-specific patterns observed in demographic data and prospective cohort studies. Once calibrated to a setting leveraging multiple sources of data, FPsim can be used to build hypothetical scenarios and interrogate counterfactual research questions about the use, non-use, and/or efficacy of family planning programs and contraceptive methods. To our knowledge, FPsim is the first open-source, individual-level, woman-centered model of family planning.Author SummaryAlthough the causes and consequences of family planning unfold on an individual level, few models of family planning consider individual heterogeneity over the life course. To that end, we introduce the methodology, parameters, and use-case(s) of the family planning simulator (FPsim). FPsim is a data-driven agent-based model of family planning, which explicitly models individual heterogeneity in biology and behaviors over a woman’s full life course to better understand the micro-level dynamics leading to more or less successful family planning programs and policies. FPsim is a data-driven model that leverages multiple sources of data to simulate realistic populations in settings that reflect real-life contexts. It is designed to be flexible and user-friendly, allowing for custom calibrations and providing integrated functions for straightforward use. This manuscript describes the model design, including its parameters, potential data sources, and limitations. We illustrate the functionality of FPsim using hypothetical scenarios that improve upon existing injectable contraceptives and introduce new injectable contraceptives into a Senegal-like setting.

Summary Background Vietnam has emerged as one of the world's leading success stories in responding to COVID-19. After a prolonged period of little to no transmission, there was an outbreak of unknown source in July, 2020, in the Da Nang region, but the outbreak was quickly suppressed. We aimed to use epidemiological, behavioural, demographic, and policy data from the COVID-19 outbreak in Da Nang to calibrate an agent-based model of COVID-19 transmission for Vietnam, and to estimate the risk of future outbreaks associated with reopening of international borders in the country. Methods For this modelling study, we used comprehensive data from June 15 to Oct 15, 2020, on testing, COVID-19 cases, and quarantine breaches within an agent-based model of SARS-CoV-2 transmission to model a COVID-19 outbreak in Da Nang in July, 2020. We applied this model to quantify the risk of future outbreaks in Vietnam in the 3 months after the reopening of international borders, under different behavioural scenarios, policy responses (ie, closure of workplaces and schools), and ongoing testing. Findings We estimated that the outbreak in Da Nang between July and August, 2020, resulted in substantial community transmission, and that higher levels of symptomatic testing could have mitigated this transmission. We estimated that the outbreak peaked on Aug 2, 2020, with an estimated 1060 active infections (95% projection interval 890–1280). If the population of Vietnam remains highly compliant with mask-wearing policies, our projections indicate that the epidemic would remain under control even if a small but steady flow of imported infections escaped quarantine into the community. However, if complacency increases and testing rates are relatively low (10% of symptomatic individuals are tested), the epidemic could rebound again, resulting in an estimated 2100 infections (95% projected interval 1050–3610) in 3 months. These outcomes could be mitigated if the behaviour of the general population responds dynamically to increases in locally acquired cases that exceed specific thresholds, but only if testing of symptomatic individuals is also increased. Interpretation The successful response to COVID-19 in Vietnam could be improved even further with higher levels of symptomatic testing. If the previous approaches are used in response to new COVID-19 outbreaks, epidemic control is possible even in the presence of low levels of imported cases. Funding Ministry of Science and Technology (Vietnam). Translation For the Vietnamese translation of the abstract see Supplementary Materials section.

Sportforderunterricht und Psychomotorik sind in Deutschland koexistent. Dabei eint sie, uber Bewegung, Spiel und Wahrnehmungsforderung Kinder ganzheitlich fordern zu wollen. Im vorliegenden Beitrag werden zunachst beide Konzepte kurz vorgestellt, um im Anschluss Gemeinsamkeiten sowie Unterschiede herauszuarbeiten und Anknupfungspunkte zu diskutieren.

We describe the discovery of histone deacetylase (HDACs) 1, 2, and 3 inhibitors with ethyl ketone as the zinc-binding group. These HDACs 1, 2, and 3 inhibitors have good enzymatic and cellular activity. Their serum shift in cellular potency has been minimized, and selectivity against hERG has been improved. They are also highly selective over HDACs 6 and 8. These inhibitors contain a variety of substituted heterocycles on the imidazole or oxazole scaffold. Compounds 31 and 48 stand out due to their good potency, high selectivity over HDACs 6 and 8, reduced hERG activity, optimized serum shift in cellular potency, and good rat and dog PK profiles.

A novel series of histone deacetylase (HDAC) inhibitors lacking a zinc-binding moiety has been developed and described herein. HDAC isozyme profiling and kinetic studies indicate that these inhibitors display a selectivity preference for HDACs 1, 2, 3, 10, and 11 via a rapid equilibrium mechanism, and crystal structures with HDAC2 confirm that these inhibitors do not interact with the catalytic zinc. The compounds are nonmutagenic and devoid of electrophilic and mutagenic structural elements and exhibit off-target profiles that are promising for further optimization. The efficacy of this new class in biochemical and cell-based assays is comparable to the marketed HDAC inhibitors belinostat and vorinostat. These results demonstrate that the long-standing pharmacophore model of HDAC inhibitors requiring a metal binding motif should be revised and offers a distinct class of HDAC inhibitors.

The Omicron wave has left a global imprinting of immunity which changes the COVID landscape. In this study, we simulate six hypothetical variants emerging over the next year and evaluate the impact of existing and improved vaccines. We base our study on South Africa’s infection- and vaccination-derived immunity. Our findings illustrate that variant-chasing vaccines will only add value above existing vaccines in the setting where a variant emerges if we can shorten the window between variant introduction and vaccine deployment to under three weeks, an impossible time-frame without significant NPI use. This strategy may have global utility, depending on the rate of spread from setting to setting. Broadly neutralizing and durable next-generation vaccines could avert over three-times as many deaths from an immune-evading variant compared to existing vaccines. Our results suggest it is crucial to develop next-generation vaccines and redress inequities in vaccine distribution to tackle future emerging variants.

BACKGROUND: As lockdown measures to slow the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection begin to ease in the UK, it is important to assess the impact of any changes in policy, including school reopening and broader relaxation of physical distancing measures. We aimed to use an individual-based model to predict the impact of two possible strategies for reopening schools to all students in the UK from September, 2020, in combination with different assumptions about relaxation of physical distancing measures and the scale-up of testing.METHODS: In this modelling study, we used Covasim, a stochastic individual-based model for transmission of SARS-CoV-2, calibrated to the UK epidemic. The model describes individuals' contact networks stratified into household, school, workplace, and community layers, and uses demographic and epidemiological data from the UK. We simulated six different scenarios, representing the combination of two school reopening strategies (full time and a part-time rota system with 50% of students attending school on alternate weeks) and three testing scenarios (68% contact tracing with no scale-up in testing, 68% contact tracing with sufficient testing to avoid a second COVID-19 wave, and 40% contact tracing with sufficient testing to avoid a second COVID-19 wave). We estimated the number of new infections, cases, and deaths, as well as the effective reproduction number (R) under different strategies. In a sensitivity analysis to account for uncertainties within the stochastic simulation, we also simulated infectiousness of children and young adults aged younger than 20 years at 50% relative to older ages (20 years and older).FINDINGS: With increased levels of testing (between 59% and 87% of symptomatic people tested at some point during an active SARS-CoV-2 infection, depending on the scenario), and effective contact tracing and isolation, an epidemic rebound might be prevented. Assuming 68% of contacts could be traced, we estimate that 75% of individuals with symptomatic infection would need to be tested and positive cases isolated if schools return full-time in September, or 65% if a part-time rota system were used. If only 40% of contacts could be traced, these figures would increase to 87% and 75%, respectively. However, without these levels of testing and contact tracing, reopening of schools together with gradual relaxing of the lockdown measures are likely to induce a second wave that would peak in December, 2020, if schools open full-time in September, and in February, 2021, if a part-time rota system were adopted. In either case, the second wave would result in R rising above 1 and a resulting second wave of infections 2·0-2·3 times the size of the original COVID-19 wave. When infectiousness of children and young adults was varied from 100% to 50% of that of older ages, we still found that a comprehensive and effective test-trace-isolate strategy would be required to avoid a second COVID-19 wave.INTERPRETATION: To prevent a second COVID-19 wave, relaxation of physical distancing, including reopening of schools, in the UK must be accompanied by large-scale, population-wide testing of symptomatic individuals and effective tracing of their contacts, followed by isolation of diagnosed individuals.FUNDING: None.

[Image: see text] The selectivity of histone deacetylase inhibitors (HDACis) is greatly impacted by the zinc binding groups. In an effort to search for novel zinc binding groups, we applied a parallel medicinal chemistry (PMC) strategy to quickly synthesize substituted benzamide libraries. We discovered a series containing 2-substituted benzamides as the zinc binding group which afforded highly selective and potent HDAC3 inhibitors, exemplified by compound 16 with a 2-methylthiobenzamide. Compound 16 inhibited HDAC3 with an IC(50) of 30 nM and with unprecedented selectivity of >300-fold over all other HDAC isoforms. Interestingly, a subtle change of the 2-methylthio to a 2-hydroxy benzamide in 20 retains HDAC3 potency but loses all selectivity over HDAC 1 and 2. This significant difference in selectivity was rationalized by X-ray crystal structures of HDACis 16 and 20 bound to HDAC2, revealing different binding modes to the catalytic zinc ion. This series of HDAC3 selective inhibitors served as tool compounds for investigating the minimal set of HDAC isoforms that must be inhibited for the HIV latency activation in a Jurkat 2C4 cell model and potentially as leads for selective HDAC3 inhibitors for other indications.

In Waldkindergarten verbringen Kinder einen wesentlichen Teil ihrer Zeit in der Natur; dies wirkt sich potenziell entwicklungsfordernd aus. Die vorliegende Studie zeigt, dass Kinder, die einen Waldkindergarten besuchen, hinsichtlich der Konzentrationsfahigkeit genauso gut auf die Schule vorbereitet werden wie Kinder aus dem Regelkindergarten. Unterschiede in der korperlichen Aktivitat oder im Medienkonsum konnten statistisch nicht nachgewiesen werden, auch wenn sich positive Tendenzen zugunsten der Waldkindergarten zeigten. Auffallig ist, dass wenige Mutter von Kindern aus dem Waldkindergarten voll berufstatig sind. Hier zeigt sich Entwicklungspotenzial im Angebot einer Ganztagsbetreuung.

Two orthogonal approaches for hit identification in drug discovery are large-scale in vitro and in silico screening. In recent years, due to the emergence of new targets and a rapid increase in the...

Although the potential value of RNA as a target for new small molecule therapeutics is becoming increasingly credible, the physicochemical properties required for small molecules to selectively bind to RNA remain relatively unexplored. To investigate the druggability of RNAs with small molecules, we have employed affinity mass spectrometry, using the Automated Ligand Identification System (ALIS), to screen 42 RNAs from a variety of RNA classes, each against an array of chemically diverse drug-like small molecules (~50,000 compounds) and functionally annotated tool compounds (~5100 compounds). The set of RNA-small molecule interactions that was generated was compared with that for protein-small molecule interactions, and naïve Bayesian models were constructed to determine the types of specific chemical properties that bias small molecules toward binding to RNA. This set of RNA-selective chemical features was then used to build an RNA-focused set of ~3800 small molecules that demonstrated increased propensity toward binding the RNA target set. In addition, the data provide an overview of the specific physicochemical properties that help to enable binding to potential RNA targets. This work has increased the understanding of the chemical properties that are involved in small molecule binding to RNA, and the methodology used here is generally applicable to RNA-focused drug discovery efforts.

Qualification and study programmes in sports coaching and physical education are based on concepts from Educational Sciences and, at least in part, Sports Sciences; established standards aim to didactically and methodologically educate best for an intended (e.g. learning objective) as well as setting-oriented (e.g. educational context) coaching or teaching, respectively. However, an often referred to mediating competenceremains to be specified—if not, classified. Against the background of a categorizing approach on underlying terminological characteristics (i.e., skill, competence, literacy) and reviewing German education-related competence models, we suggest a conceptual perspective on an integrative mediating competence to serve sports coaching and physical education contexts.

Early waves of the SARS-CoV-2 pandemic were driven by importation events and subsequent policy responses. However, epidemic dynamics in 2021 are largely driven by the spread of more transmissible and/or immune-evading variants, which in turn are countered by vaccination programs. Here we describe updates to the methodology of Covasim (COVID-19 Agent-based Simulator) to account for immune trajectories over time, correlates of protection, co-circulation of different variants and the roll-out of multiple vaccines. We have extended recent work on neutralizing antibodies (NAbs) as a correlate of protection to account for protection against infection, symptomatic COVID-19, and severe disease using a joint estimation approach. We find that NAbs are strongly correlated with infection blocking and that natural infection provides stronger protection than vaccination for the same level of NAbs, though vaccines typically produce higher NAbs. We find only relatively weak correlations between NAbs and the probability of developing symptoms given a breakthrough infection, or the probability of severe disease given symptoms. A more refined understanding of breakthrough infections in individuals with natural and vaccine-derived immunity will have implications for timing of booster vaccines, the impact of emerging variants of concern on critical vaccination thresholds, and the need for ongoing non-pharmaceutical interventions.

Schools are an excellent setting for health promotion in children and adolescents. In particular the school subject physical education (PE) offers high potential in this regard. The following paper applies thesalutogenic model of Aaron Antonovsky to PE in schools. This approach focuses on strengthening the sense of coherence with its central factors: comprehensibility, manageability and meaningfulness. A high sense of coherence mobilizes generalized resistance resources, results in positive coping strategies and contributes to well-being and health. The presented modified and adapted salutogenic model of health for PE may serve as one element of a schools’ general concept for health promotion.

All herpesviruses encode a conserved DNA polymerase that is required for viral genome replication and serves as an important therapeutic target. Currently available herpesvirus therapies include nucleoside and non-nucleoside inhibitors (NNI) that target the DNA-bound state of herpesvirus polymerase and block replication. Here we report the ternary complex crystal structure of Herpes Simplex Virus 1 DNA polymerase bound to DNA and a 4-oxo-dihydroquinoline NNI, PNU-183792 (PNU), at 3.5 Å resolution. PNU bound at the polymerase active site, displacing the template strand and inducing a conformational shift of the fingers domain into an open state. These results demonstrate that PNU inhibits replication by blocking association of dNTP and stalling the enzyme in a catalytically incompetent conformation, ultimately acting as a nucleotide competing inhibitor (NCI). Sequence conservation of the NCI binding pocket further explains broad-spectrum activity while a direct interaction between PNU and residue V823 rationalizes why mutations at this position result in loss of inhibition., Various herpesvirus therapeutics target the viral DNA polymerase. Here, the authors present the crystal structure of herpesvirus polymerase in the elongating state with bound primer-template DNA and the broad-spectrum non-nucleoside inhibitor PNU-183792, which is of interest for further drug design.

A series of unique macrocyclic HDACs 1, 2, and 3 selective inhibitors were identified with good enzymatic activity and high selectivity over HDACs 6 and 8. These macrocyclic HDAC inhibitors used an ethyl ketone as the zinc-binding group. Compounds 25 and 26 stood out as leads due to their low double-digit nM EC50s in the 2C4 cell-based HIV latency reactivation assay. The PK profiles of these macrocyclic HDAC inhibitors still needed improvement.

As the UK reopened after the first wave of the COVID-19 epidemic, crucial questions emerged around the role for ongoing interventions, including test-trace-isolate (TTI) strategies and mandatory masks. Here we assess the importance of masks in secondary schools by evaluating their impact over September 1–October 23, 2020. We show that, assuming TTI levels from August 2020 and no fundamental changes in the virus’s transmissibility, adoption of masks in secondary schools would have reduced the predicted size of a second wave, but preventing it would have required 68% or 46% of those with symptoms to seek testing (assuming masks’ effective coverage 15% or 30% respectively). With masks in community settings but not secondary schools, the required testing rates increase to 76% and 57%.

ObjectivesThe early stages of the COVID-19 pandemic illustrated that SARS-CoV-2, the virus that causes the disease, has the potential to spread exponentially. Therefore, as long as a substantial proportion of the population remains susceptible to infection, the potential for new epidemic waves persists even in settings with low numbers of active COVID-19 infections, unless sufficient countermeasures are in place. We aim to quantify vulnerability to resurgences in COVID-19 transmission under variations in the levels of testing, tracing and mask usage.SettingThe Australian state of New South Wales (NSW), a setting with prolonged low transmission, high mobility, non-universal mask usage and a well-functioning test-and-trace system.ParticipantsNone (simulation study).ResultsWe find that the relative impact of masks is greatest when testing and tracing rates are lower and vice versa. Scenarios with very high testing rates (90% of people with symptoms, plus 90% of people with a known history of contact with a confirmed case) were estimated to lead to a robustly controlled epidemic. However, across comparable levels of mask uptake and contact tracing, the number of infections over this period was projected to be 2–3 times higher if the testing rate was 80% instead of 90%, 8–12 times higher if the testing rate was 65% or 30–50 times higher with a 50% testing rate. In reality, NSW diagnosed 254 locally acquired cases over this period, an outcome that had a moderate probability in the model (10%–18%) assuming low mask uptake (0%–25%), even in the presence of extremely high testing (90%) and near-perfect community contact tracing (75%–100%), and a considerably higher probability if testing or tracing were at lower levels.ConclusionsOur work suggests that testing, tracing and masks can all be effective means of controlling transmission. A multifaceted strategy that combines all three, alongside continued hygiene and distancing protocols, is likely to be the most robust means of controlling transmission of SARS-CoV-2.

BackgroundFollowing the resurgence of the COVID-19 epidemic in the UK in late 2020 and the emergence of the alpha (also known as B117) variant of the SARS-CoV-2 virus, a third national lockdown was imposed from January 4, 2021. Following the decline of COVID-19 cases over the remainder of January 2021, the question of when and how to reopen schools became an increasingly pressing one in early 2021. This study models the impact of a partial national lockdown with social distancing measures enacted in communities and workplaces under different strategies of reopening schools from March 8, 2021 and compares it to the impact of continual full national lockdown remaining until April 19, 2021.MethodsWe used our previously published agent-based model, Covasim, to model the emergence of the alpha variant over September 1, 2020 to January 31, 2021 in presence of Test, Trace and Isolate (TTI) strategies. We extended the model to incorporate the impacts of the roll-out of a two-dose vaccine against COVID-19, with 200,000 daily vaccine doses prioritised by age starting with people 75 years or older, assuming vaccination offers a 95% reduction in disease acquisition risk and a 30% reduction in transmission risk. We used the model, calibrated until January 25, 2021, to simulate the impact of a full national lockdown (FNL) with schools closed until April 19, 2021 versus four different partial national lockdown (PNL) scenarios with different elements of schooling open: 1) staggered PNL with primary schools and exam-entry years (years 11 and 13) returning on March 8, 2021 and the rest of the schools years on March 15, 2020; 2) full-return PNL with both primary and secondary schools returning on March 8, 2021; 3) primary-only PNL with primary schools and exam critical years (years 11 and 13) going back only on March 8, 2021 with the rest of the secondary schools back on April 19, 2021 and 4) part-rota PNL with both primary and secondary schools returning on March 8, 2021 with primary schools remaining open continuously but secondary schools on a two-weekly rota-system with years alternating between a fortnight of face-to-face and remote learning until April 19, 2021. Across all scenarios, we projected the number of new daily cases, cumulative deaths and effective reproduction number R until April 30, 2021.ResultsOur calibration across different scenarios is consistent with alpha variant being around 60% more transmissible than the wild type. We find that strict social distancing measures, i.e. national lockdowns, were essential in containing the spread of the virus and controlling hospitalisations and deaths during January and February 2021. We estimated that a national lockdown over January and February 2021 would reduce the number of cases by early March to levels similar to those seen in October 2020, with R also falling and remaining below 1 over this period. We estimated that infections would start to increase when schools reopened, but found that if other parts of society remain closed, this resurgence would not be sufficient to bring R above 1. Reopening primary schools and exam critical years only or having primary schools open continuously with secondary schools on rotas was estimated to lead to lower increases in cases and R than if all schools opened. Without an increase in vaccination above the levels seen in January and February, we estimate that R could have increased above 1 following the reopening of society, simulated here from April 19, 2021.FindingsOur findings suggest that stringent measures were integral in mitigating the increase in cases and bringing R below 1 over January and February 2021. We found that it was plausible that a PNL with schools partially open from March 8, 2021 and the rest of the society remaining closed until April 19, 2021 would keep R below 1, with some increase evident in infections compared to continual FNL until April 19, 2021. Reopening society in mid-April, without an increase in vaccination levels, could push R above 1 and induce a surge in infections, but the effect of vaccination may be able to control this in future depending on the transmission blocking properties of the vaccines.

Der Schulsport mit seinen Saulen Sportunterricht, Sportforderunterricht sowie auserunterrichtlicher Schulsport bietet ein hohes gesundheitsforderndes Potenzial. Ausgestaltet nach den Prinzipien des fachdidaktischen Konzepts des „erziehenden Sportunterrichts“ konnen Schuler zu gesundheitsforderndem (sportlichem) Verhalten befahigt und motiviert werden. Die padagogische Perspektive „Gesundheit fordern, Gesundheitsbewusstsein entwickeln“ legitimiert im Zusammenspiel mit dem Doppelauftrag des Schulsports („Erziehung zum Sport“ und „Erziehung durch Sport“) einen entsprechenden Fokus. Neben den direkten positiven gesundheitlichen Auswirkungen von Bewegung, Spiel und Sport ist korperliche Aktivitat als Ressource und Schutzfaktor anzusehen. In einem salutogenetischen Verstandnis sollte Schulsport das Koharenzgefuhl von Schulern fordern und auch auf diesem Weg zur Gesundheitsforderung beitragen.

In settings with zero community transmission, any new SARS-CoV-2 outbreaks are likely to be the result of random incursions. The level of restrictions in place at the time of the incursion is likely to considerably affect possible outbreak trajectories. We used an agent-based model to investigate the relationship between ongoing restrictions and behavioural factors, and the probability of an incursion causing an outbreak and the resulting growth rate. We applied our model to the state of Victoria, Australia, which has reached zero community transmission as of November 2020.We found that a future incursion has a 45% probability of causing an outbreak (defined as a 7-day average of >5 new cases per day within 60 days) if no restrictions were in place, decreasing to 23% with a mandatory masks policy, density restrictions on venues such as restaurants, and if employees worked from home where possible. A drop in community symptomatic testing rates was associated with up to a 10-percentage point increase in outbreak probability, highlighting the importance of maintaining high testing rates as part of a suppression strategy.Because the chance of an incursion occurring is closely related to border controls, outbreak risk management strategies require an integrated approaching spanning border controls, ongoing restrictions, and plans for response. Each individual restriction or control strategy reduces the risk of an outbreak. They can be traded off against each other, but if too many are removed there is a danger of accumulating an unsafe level of risk. The outbreak probabilities estimated in this study are of particular relevance in assessing the downstream risks associated with increased international travel.

BackgroundVietnam has emerged as one of the world’s leading success stories in responding to COVID-19. After prolonged zero-low transmission, a summer outbreak of unknown source at Da Nang caused the country’s first COVID-19 deaths, but was quickly suppressed. Vietnam recently reopened its borders to international travelers. Understanding the attendant risks and how to minimize them is crucial as Vietnam moves into this new phase.MethodsWe create an agent-based model of COVID-19 in Vietnam, using regional testing data and a detailed linelist of the 1,014 COVID-19 cases, including 35 deaths, identified across Vietnam. We investigate the Da Nang outbreak, and quantify the risk of another outbreak under different assumptions about behavioral/policy responses and ongoing testing.ResultsThe Da Nang outbreak, although rapidly contained once detected, nevertheless caused significant community transmission before it was detected; higher symptomatic testing could have mitigated this. If testing levels do not increase, the adoption of past policies in response to newly-detected cases may reduce the size of potential outbreaks but will not prevent them. Compared to a baseline symptomatic testing rate of 10%, we estimate half as many infections under a 20% testing rate, and a quarter as many with 40-50% testing rates, over the four months following border reopenings.ConclusionsVietnam’s success in controlling COVID-19 is largely attributable to its rapid response to detected outbreaks, but the speed of response could be improved even further with higher levels of symptomatic testing.

Policymakers make decisions about COVID-19 management in the face of considerable uncertainty. We convened multiple modeling teams to evaluate reopening strategies for a mid-sized county in the United States, in a novel process designed to fully express scientific uncertainty while reducing linguistic uncertainty and cognitive biases. For the scenarios considered, the consensus from 17 distinct models was that a second outbreak will occur within 6 months of reopening, unless schools and non-essential workplaces remain closed. Up to half the population could be infected with full workplace reopening; non-essential business closures reduced median cumulative infections by 82%. Intermediate reopening interventions identified no win-win situations; there was a trade-off between public health outcomes and duration of workplace closures. Aggregate results captured twice the uncertainty of individual models, providing a more complete expression of risk for decision-making purposes.