Relaxation Of Social Distancing Measures Research Articles

Increase of pyogenic bacterial infections after relaxation of social distancing measures linked to COVID-19 pandemic.

After the relaxation of COVID-19 mitigation measures, we observed a dramatic increase in pyogenic infections. Based on this observation, we retrospectively analysed all cases of invasive bacterial infections of brain, lung and complicated ear-nose-throat (ENT) infections, in the period from 1 August to 31 March from the years 2018-2019 to 2022-2023. The study was conducted in two Paediatric Emergency Departments, at IRCCS 'Burlo Garofolo' of Trieste and at Treviso Hospital. Electronic medical records were searched for all cases with a definitive diagnosis at discharge of mastoiditis, suppurative cervical lymphadenitis, retropharyngeal, parapharyngeal and peritonsillar abscess (ENT group), bacterial brain abscesses, epidural empyema, subdural empyema (central nervous system group), thoracic empyema and necrotising pneumonia (lung group). In 2022-2023, we observed an increase in infections compared to the previous years. Total number of cases were 22, 29, 8, 27 and 63 in 2018-2019, 2019-2020, 2020-2021, 2021-2022 and 2022-2023, respectively. The greater increase occurred in thoracic empyema, with a peak incidence of +120% in 2022-2023 in respect of 2021-2022. We reported an important increase in paediatric bacterial complicated infections in two North East Italian regions, possibly correlated with the relaxation of COVID-19 social distancing measures.

Dynamics of endemic human coronavirus and SARS-CoV-2 in a hospital of Madrid, Spain. Retrospective study from June 2020 to July 2023.

An observational and retrospective study was carried out to analyse HCoV positivity from a multiplex PCR respiratory panel and RT-PCR for SARS-CoV-2 in respiratory samples from 1 June 2020 to 31 July 2023 at the Príncipe de Asturias University Hospital (HUPA) in Alcalá de Henares, Madrid, Spain. Out of 2802 respiratory panels, 1258 (44.8%) turned out positive. HCoV was detected in 114 (4%) cases (range 0-23; median 1.5; IQR 0-3.75) with positivity rates ranging from 0% to 14%. All four variants of HCoV circulated, and OC-43 was the most common in 62.3% of cases. After the onset of the pandemic, the HCoV season was delayed 22 weeks, with a peak positivity of 9% in the summer of 2021, showing an inverse relationship with the alpha and delta waves of SARS-CoV-2. In the two subsequent autumn-winter seasons, HCoV positivity increased (11-14%) with a reduction in the summer of 2022 and 2023 following the emergence of the omicron variant and the relaxation of social distancing measures. The seasonal spread pattern of endemic HCoV might be returning to normal in our region and likely in other temperate zones of the northern hemisphere after 3 years of the pandemic.

Mathematical modeling of the dynamics of COVID-19 variants of concern: Asymptotic and finite-time perspectives.

The COVID-19 pandemic has seen multiple waves, in part due to the implementation and relaxation of social distancing measures by the public health authorities around the world, and also caused by the emergence of new variants of concern (VOCs) of the SARS-Cov-2 virus. As the COVID-19 pandemic is expected to transition into an endemic state, how to manage outbreaks caused by newly emerging VOCs has become one of the primary public health issues. Using mathematical modeling tools, we investigated the dynamics of VOCs, both in a general theoretical framework and based on observations from public health data of past COVID-19 waves, with the objective of understanding key factors that determine the dominance and coexistence of VOCs. Our results show that the transmissibility advantage of a new VOC is a main factor for it to become dominant. Additionally, our modeling study indicates that the initial number of people infected with the new VOC plays an important role in determining the size of the epidemic. Our results also support the evidence that public health measures targeting the newly emerging VOC taken in the early phase of its spread can limit the size of the epidemic caused by the new VOC (Wu et al., 2139Wu, Scarabel, Majeed, Bragazzi, & Orbinski, ; Wu et al., 2021).

The effectiveness of COVID-19 testing and contact tracing in a US city

Although testing, contact tracing, and case isolation programs can mitigate COVID-19 transmission and allow the relaxation of social distancing measures, few countries worldwide have succeeded in scaling such efforts to levels that suppress spread. The efficacy of test-trace-isolate likely depends on the speed and extent of follow-up and the prevalence of SARS-CoV-2 in the community. Here, we use a granular model of COVID-19 transmission to estimate the public health impacts of test-trace-isolate programs across a range of programmatic and epidemiological scenarios, based on testing and contact tracing data collected on a university campus and surrounding community in Austin, TX, between October 1, 2020, and January 1, 2021. The median time between specimen collection from a symptomatic case and quarantine of a traced contact was 2 days (interquartile range [IQR]: 2 to 3) on campus and 5 days (IQR: 3 to 8) in the community. Assuming a reproduction number of 1.2, we found that detection of 40% of all symptomatic cases followed by isolation is expected to avert 39% (IQR: 30% to 45%) of COVID-19 cases. Contact tracing is expected to increase the cases averted to 53% (IQR: 42% to 58%) or 40% (32% to 47%), assuming the 2- and 5-day delays estimated on campus and in the community, respectively. In a tracing-accelerated scenario, in which 75% of contacts are notified the day after specimen collection, cases averted increase to 68% (IQR: 55% to 72%). An accelerated contact tracing program leveraging rapid testing and electronic reporting of test results can significantly curtail local COVID-19 transmission.

SARS-CoV-2 Infection Evolution Among Nephrologists During the Pandemic: Clinical Features and Impact of Vaccination

SARS-CoV-2 Infection Evolution Among Nephrologists During the Pandemic: Clinical Features and Impact of Vaccination

How social distancing, mobility, and preventive policies affect COVID-19 outcomes: Big data-driven evidence from the District of Columbia-Maryland-Virginia (DMV) megaregion.

Many factors play a role in outcomes of an emerging highly contagious disease such as COVID-19. Identification and better understanding of these factors are critical in planning and implementation of effective response strategies during such public health crises. The objective of this study is to examine the impact of factors related to social distancing, human mobility, enforcement strategies, hospital capacity, and testing capacity on COVID-19 outcomes within counties located in District of Columbia as well as the states of Maryland and Virginia. Longitudinal data have been used in the analysis to model county-level COVID-19 infection and mortality rates. These data include big location-based service data, which were collected from anonymized mobile devices and characterize various social distancing and human mobility measures within the study area during the pandemic. The results provide empirical evidence that lower rates of COVID-19 infection and mortality are linked with increased levels of social distancing and reduced levels of travel-particularly by public transit modes. Other preventive strategies and polices also prove to be influential in COVID-19 outcomes. Most notably, lower COVID-19 infection and mortality rates are linked with stricter enforcement policies and more severe penalties for violating stay-at-home orders. Further, policies that allow gradual relaxation of social distancing measures and travel restrictions as well as those requiring usage of a face mask are related to lower rates of COVID-19 infections and deaths. Additionally, increased access to ventilators and Intensive Care Unit (ICU) beds, which represent hospital capacity, are linked with lower COVID-19 mortality rates. On the other hand, gaps in testing capacity are related to higher rates of COVID-19 infection. The results also provide empirical evidence for reports suggesting that certain minority groups such as African Americans and Hispanics are disproportionately affected by the COVID-19 pandemic.

Covid-19 vaccination in 2021 and future challenges

The year 2021 was marked by the beginning of the vaccination campaign against Covid-19 in Brazil. On January 17, 2021, the National Health Surveillance Agency (Anvisa) approved the emergency use of the Coronavac (Sinovac/Butantan) and Oxford/Astrazeneca vaccines in Brazil. On the same day, a health professional in the city of São Paulo already received the first dose of the immunization Coronavac, just over a month after the first dose in the world was administered in the United Kingdom with the Pfizer/BioNTech vaccine. Since then, thousands of people around the world have been immunized, which has contributed to the significant reduction in the number of deaths around the globe and the relief of health systems. Despite the great advances in the vaccination campaign against Covid-19 in Brazil in 2021, ending the year with 67.5% of the population fully vaccinated (1), the year 2022 begins with an increase in the number of cases and hospitalizations for severe acute respiratory syndrome (SARS) caused by the expansion of the Omicron variant of the new coronavirus and the influenza virus H3N2 (Darwin) in national territory. In 2021 Brazil faced its worst moment of the pandemic, reaching a peak of 4,000 deaths and more than 90,000 daily cases between April and June (2). The increase in cases coincided with the relaxation of social distancing measures and the circulation of the Gamma variant, with greater transmission capacity and possible association with more severe forms of the disease (3). With the advance of vaccination, the country registered less than 100 deaths and 3,000 cases per day in December (2). Meanwhile, Europe and the United States suffer from another wave of cases and hospitalizations, now caused by the Delta variant and the recently discovered Omicron variant, which has a high transmission capacity even in vaccinated individuals (4).The spread of the Omicron variant in Brazil, associated to the relaxation of social distancing measures and end of year festivities, in addition to the co-circulation of the H3N2 influenza virus, leads us to believe that the year 2022 will be another challenging year for the Brazilian health system. The moving average of cases in the first weeks of the year already records an increase of more than 600% of new cases of Covid-19, when compared to the last weeks of December 2021. A recent African study showed that efficacy against hospitalisation was reduced from 93% in the pre-Omicron period to 70% in the Omicron period (5). Furthermore, the decrease in vaccine efficacy 6 months after the second dose reinforces the need for booster administration to curb the number of new cases in the country.Therefore, the loss of effectiveness of the vaccines over time, associated with the emergence of new variants of the virus, leads us to believe that the pandemic is still far from over, and that booster doses of the vaccine with the presence of new variants in its composition will be needed regularly, as happens in vaccination campaigns against influenza virus. For the coming months it is of fundamental importance to monitor the behavior of Covid-19 in the national territory, reinforcing the testing of suspected cases, adopting restrictive measures for agglomerations, and accelerating the application of the booster dose of the vaccine to contain the spread of the virus and avoid a collapse in the health system.

Introductory Models of COVID-19 in the United States

ABSTRACT Students develop and test simple kinetic models of the spread of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Microsoft Excel is used as the modeling platform because it is nonthreatening to students and it is widely available. Students develop finite difference models and implement them in the cells of preformatted spreadsheets following a guided inquiry pedagogy that introduces new model parameters in a scaffolded step-by-step manner. That approach allows students to investigate the implications of new model parameters in a systematic way. Students fit the resulting models to reported cases per day data for the United States using least squares techniques with Excel's Solver. Using their own spreadsheets, students discover for themselves that the initial exponential growth of COVID-19 can be explained by a simplified unlimited growth model and by the susceptible-infected-recovered (SIR) model. They also discover that the effects of social distancing can be modeled using a Gaussian transition function for the infection rate coefficient and that the summer surge was caused by prematurely relaxing social distancing and then reimposing stricter social distancing. Students then model the effect of vaccinations and validate the resulting susceptible-infected-recovered-vaccinated (SIRV) model by showing that it successfully predicts the reported cases per day data from Thanksgiving through the holiday period up to 14 February 2021. The same SIRV model is then extended and successfully fits the fourth peak up to 1 June 2021, caused by further relaxation of social distancing measures. Finally, students extend the model up to the present day (27 August 2021) and successfully account for the appearance of the delta variant of the SARS-CoV-2 virus. The fitted model also predicts that the delta variant peak will be comparatively short, and the cases per day data should begin to fall off in early September 2021, counter to current expectations. This case study makes an excellent capstone experience for students interested in scientific modeling.

COVID-19 Importation Risk From Olympic Athletes Prior to the Tokyo 2020 Olympics

The COVID-19 pandemic delayed the Tokyo 2020 Olympics for 1 year and sparked an unprecedented outbreak in Japan in early July 2021 due to the relaxation of social distancing measures for foreign arrivals. Approximately 11,000 athletes from 205 countries would gather at the Tokyo Olympics held from July 23 through August 8, 2021. Based on the prevalence of infection in different source locations and athlete numbers, we estimated that seven countries would introduce least one infection of COVID-19 to Tokyo and at most eleven unidentified infections after the three requested COVID-19 tests.

Susceptible-Infected-Recovered model study using free particle dynamics

A study on the epidemiologic Susceptible-Infected-Recovered (SIR) model is presented using free particle dynamics. The study is performed using a computational model consisting of randomly allocated particles in a closed domain which are free to move inrandom directions with the ability to collide into each other. The transmission rules for the particle–particle interactions are based on the main viral infection mechanisms, resulting in real–time results of the number of susceptible, infected, and recovered particles within a population of N= 200 particles. The results are qualitatively compared with a differential equation SIR model in terms of the transmission rate β, recovery rate γ, and the basic reproductive number R0, yielding overall good results. The effect of the particle density ρ on R0 is also studied to analyze how an infectious disease spreads over different types of populations. The versatility of the proposed free–particle–dynamics SIR model allows to simulate different scenarios, such as social distancing, commonly referredto as quarantine, no social distancing measures, and a mixture of the former and the latter. It is found that by implementing early relaxation of social distancing measures before the number of infected particles reaches zero, could lead to subsequent outbreaks such as the particular events observed in different countries due to the ongoing COVID–19 health crisis

Covid-19 in the Northeast of Brazil: from lockdown to the relaxation of social distancing measures

Even in the period when the Covid-19 pandemic was on the rise in the Northeast of Brazil, the relaxation of social distancing measures was introduced. The scope of the study is to assess, in the light of the epidemiological-sanitary situation in the region, the suitability of relaxation of social distancing measures. Based on the WHO guidelines for relaxation of social distancing, operational indicators were created and analyzed for each guideline in the context of the Northeast. To analyze the behavior of the epidemic, according to selected indicators, Joinpoint trend analysis techniques, heat maps, rate ratios and time trends between capitals and the state interior were compared. The weekly growth peak of the epidemic occurred in May-July 2020 (epidemiological weeks 19 to 31). In most capitals, there was no simultaneous downward trend in the number of cases and deaths in the 14 days prior to flexibilization. In all states the number of tests performed was insufficient. In epidemiological week 24, the state percentages of ICU/Covid-19 bed occupancy were close to or above 70%. The epidemiological situation of the nine Northeastern state capitals analyzed here did not meet criteria and parameters recommended by the World Health Organization for the relaxation of social distancing measures.

Predictions of COVID-19 dynamics in the UK: Short-term forecasting and analysis of potential exit strategies.

Efforts to suppress transmission of SARS-CoV-2 in the UK have seen non-pharmaceutical interventions being invoked. The most severe measures to date include all restaurants, pubs and cafes being ordered to close on 20th March, followed by a “stay at home” order on the 23rd March and the closure of all non-essential retail outlets for an indefinite period. Government agencies are presently analysing how best to develop an exit strategy from these measures and to determine how the epidemic may progress once measures are lifted. Mathematical models are currently providing short and long term forecasts regarding the future course of the COVID-19 outbreak in the UK to support evidence-based policymaking. We present a deterministic, age-structured transmission model that uses real-time data on confirmed cases requiring hospital care and mortality to provide up-to-date predictions on epidemic spread in ten regions of the UK. The model captures a range of age-dependent heterogeneities, reduced transmission from asymptomatic infections and produces a good fit to the key epidemic features over time. We simulated a suite of scenarios to assess the impact of differing approaches to relaxing social distancing measures from 7th May 2020 on the estimated number of patients requiring inpatient and critical care treatment, and deaths. With regard to future epidemic outcomes, we investigated the impact of reducing compliance, ongoing shielding of elder age groups, reapplying stringent social distancing measures using region based triggers and the role of asymptomatic transmission. We find that significant relaxation of social distancing measures from 7th May onwards can lead to a rapid resurgence of COVID-19 disease and the health system being quickly overwhelmed by a sizeable, second epidemic wave. In all considered age-shielding based strategies, we projected serious demand on critical care resources during the course of the pandemic. The reintroduction and release of strict measures on a regional basis, based on ICU bed occupancy, results in a long epidemic tail, until the second half of 2021, but ensures that the health service is protected by reintroducing social distancing measures for all individuals in a region when required. Our work confirms the effectiveness of stringent non-pharmaceutical measures in March 2020 to suppress the epidemic. It also provides strong evidence to support the need for a cautious, measured approach to relaxation of lockdown measures, to protect the most vulnerable members of society and support the health service through subduing demand on hospital beds, in particular bed occupancy in intensive care units.

Quo Vadis Influenza?

The number of influenza virus detections declined tremendously after the emergence and worldwide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); an effect most likely caused by non-pharmaceutical interventions to slow the spread of SARS-CoV-2. Recent data suggest that influenza virus detection has slightly increased in parts of the world, perhaps owing to the relaxation of social distancing measures.

Adherence to Self-isolation measures by older adults during coronavirus disease 2019 (COVID-19) epidemic: A phone survey in Iran.

Background: Older adults are at higher risk for severe illness and death associated with coronavirus disease 2019 (COVID-19). As Iran was affected by COVID-19 pandemic, the elderly population soon were told to self-isolate for a very long time. We aimed to identify the coverage, efficacy, and integrity of self-isolation and its predictors in the Iranian older adults (≥60 years) from February 19 to 19 March 2020. Methods: Quota sampling was performed to recruit respondents from 16 cities that were selected based on their population size (4, 7, and 5 cities for localities with ≤500 000, 500 000-1 000 000, and ≥1 000 000 populations) and geographical direction (West = 4 cities; North, East, South, Center = 3 each). At least 30 respondents per locality were selected. Phone interviews of 558 respondents (out of 560; response rate = 99.6%) were performed by local trained interviewers using a validated interview form. Association between age, sex, and living condition (with family vs alone) was assessed with Pearson Chi Square and logistic regression analyses. Results: Complete self-isolation was reported by 61% of the respondents. In 72%, self-isolation led to 80%-100% contact reduction. Self-isolation was broken by 26% of the respondents. Females had better self-isolation behaviors (OR adjusted: 2.3, 95% CI: 1.5, 3.3) and higher contact reduction rates (p: 0.067). They kept the integrity of self-isolation better (OR adjusted: 1.8; 95% CI: 1.2, 2.7). Those aged older than 80 years were 2.3-folds more likely to completely self-isolate than younger elderly (95% CI adjusted: 1.2, 4.3). Living alone did not significantly predict self-isolation features in the elderly. Conclusion: About one third of the interviewed Iranian older adults did not adhere to important self-isolation measures, with males and younger ages showing lower adherence. With the relaxation of social distancing measures, protection measures of the elderly should be strengthened. Given that prolonged self-isolation adversely affects physical and mental health status of the elderly, it is highly recommended to think of creative and gender-specific methods that best tailor the needs of this population in Iran.

Coronavirus Disease 2019 (COVID-19) Transmission in the United States Before Versus After Relaxation of Statewide Social Distancing Measures.

BackgroundWeeks after issuing social distancing orders to suppress severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and reduce growth in cases of severe coronavirus disease 2019 (COVID-19), all US states and the District of Columbia partially or fully relaxed these measures.Methods We identified all statewide social distancing measures that were implemented and/or relaxed in the United States between 10 March and 15 July 2020, triangulating data from state government and third-party sources. Using segmented linear regression, we estimated the extent to which relaxation of social distancing affected epidemic control, as indicated by the time-varying, state-specific effective reproduction number (Rt).ResultsIn the 8 weeks prior to relaxation, mean Rt declined by 0.012 units per day (95% confidence interval [CI], −.013 to −.012), and 46/51 jurisdictions achieved Rt < 1.0 by the date of relaxation. After relaxation of social distancing, Rt reversed course and began increasing by 0.007 units per day (95% CI, .006–.007), reaching a mean Rt of 1.16. Eight weeks later, the mean Rt was 1.16 and only 9/51 jurisdictions were maintaining an Rt < 1.0. Parallel models showed similar reversals in the growth of COVID-19 cases and deaths. Indicators often used to motivate relaxation at the time of relaxation (eg, test positivity rate <5%) predicted greater postrelaxation epidemic growth.ConclusionsWe detected an immediate and significant reversal in SARS-CoV-2 epidemic suppression after relaxation of social distancing measures across the United States. Premature relaxation of social distancing measures undermined the country’s ability to control the disease burden associated with COVID-19.

Roadmap to recovery: Reporting on a research taskforce supporting Indigenous responses to COVID-19 in Australia.

In April 2020 a Group of Eight Taskforce was convened, consisting of over 100 researchers, to provide independent, research‐based recommendations to the Commonwealth Government on a “Roadmap to Recovery” from COVID‐19. The report covered issues ranging from pandemic control and relaxation of social distancing measures, to well‐being and special considerations for vulnerable populations. Our work focused on the critical needs of Aboriginal and Torres Strait Islander communities; this paper presents an overview of our recommendations to the Roadmap report. In addressing the global challenges posed by pandemics for citizens around the world, Indigenous people are recognised as highly vulnerable. At the time of writing Australia's First Nations Peoples have been largely spared from COVID‐19 in comparison to other Indigenous populations globally. Our recommendations emphasise self‐determination and equitable needs‐based funding to support Indigenous communities to recover from COVID‐19, addressing persistent overcrowded housing, and a focus on workforce, especially for regional and remote communities. These latter two issues have been highlighted as major issues of risk for Indigenous communities in Australia It remains to be seen how governments across Australia take up these recommendations to support Indigenous peoples' health and healing journey through yet another, potentially catastrophic, health crisis.

Haematological cancers and the risk of severe COVID-19: Exploration and critical evaluation of the evidence to date.

SummaryFrom the outset of the COVID‐19 pandemic, patients and healthcare professionals have been concerned that a history of haematological malignancy will lead to an increased risk of severe COVID‐19. This led to the UK government advising patients with blood cancers to shield, massive re‐organisation of NHS haematology and cancer services, and changes in treatment plans for thousands of patients. Given the unknown effects that relaxation of social‐distancing measures will have on the infection rate, we review the evidence to date to see whether a history of haematological malignancy is associated with increased risk of COVID‐19. Multivariable analysis of large population studies, taking other known risk factors into account, do indicate that patients with haematological malignancy, especially those diagnosed recently, are at increased risk of death from COVID‐19 compared to the general population. The evidence that this risk is higher than for those with solid malignancies is conflicting. There is suggestive evidence from smaller cohort studies that those with myeloid malignancy may be at increased risk within the blood cancer population, but this needs to be confirmed on larger studies. Ongoing large collaborative efforts are required to gain further evidence regarding specific risk factors for severe complications of COVID‐19.

Pedagogical foundations to online lectures in health professions education.

Professional and tertiary health professions education (HPE) has been markedly challenged by the current novel coronavirus (COVID-19). Mandates for training organisations to reduce social contact during the global pandemic, and make learning available online, provide an opportunity for regional, rural and remote clinicians and students to more easily access learning and professional development opportunities. Online lectures, while posing an opportunity for regional, rural and remote HPE, entail potential risks. Educators who are familiar with face-to-face pedagogies may find a transition to remote, digital interaction unfamiliar, disarming, and therefore they may not design maximally engaging lectures. The strategies used in a face-to-face lecture cannot be directly transferred into the online environment. This article proposes strategies to ensure the ongoing effectiveness, efficiency and engagement of lectures transitioning from face-to-face to online delivery. Cognitive learning theory, strategies to promote learner engagement and minimise distraction, and examples of software affordances to support active learning during the lecture are proposed. This enables lecturers to navigate the challenges of lecturing in an online environment and plan fruitful online lectures during this disruptive time. These suggestions will therefore enable HPE to better meet the existing and future needs of regional, rural and remote learners who may not be able to easily access face-to-face learning upon the relaxation of social distancing measures. Strategies to provide equitable HPE to learners who cannot access plentiful, fast internet are also discussed.

The dynamics of humoral immune responses following SARS-CoV-2 infection and the potential for reinfection.

SARS-CoV-2 is a novel coronavirus that is the causative agent of coronavirus infectious disease 2019 (COVID-19). As of 17 April 2020, it has infected 2 114 269 people, resulting in 145 144 deaths. The timing, magnitude and longevity of humoral immunity is not yet understood for SARS-CoV-2. Nevertheless, understanding this is urgently required to inform the likely future dynamics of the pandemic, to guide strategies to allow relaxation of social distancing measures and to understand how to deploy limiting vaccine doses when they become available to achieve maximum impact. SARS-CoV-2 is the seventh human coronavirus to be described. Four human coronaviruses circulate seasonally and cause common colds. Two other coronaviruses, SARS and MERS, have crossed from animal sources into humans but have not become endemic. Here we review what is known about the human humoral immune response to epidemic SARS CoV and MERS CoV and to the seasonal, endemic coronaviruses. Then we summarize recent, mostly non-peer reviewed, studies into SARS-CoV-2 serology and reinfection in humans and non-human primates and summarize current pressing research needs.