Performing arts as a non-pharmacological intervention for people with dementia and care-partners: a community case study.

Participation in psychosocial enrichment activities, such as music and arts programming, have shown potential to delay or reduce functional decline - without adverse effects that can be associated with pharmaceuticals. The performing-arts programming described in this community case study was inspired by a community music program called B-Sharp Music Wellness, located in Phoenix, Arizona, which involved small groups of musicians who provided symphony performances for people with dementia. Our community programming sought to engage people with dementia and their informal care partner (typically a spouse) in existing performing-arts programs in their local community, providing social hours and season tickets for either symphony, dance (ballet), or non-musical theater performances. This case study describes the program history and design, including outcomes and lessons learned from the program evaluation of the last full season (2018-19) and partial season (2019-20), when the program was halted due to the COVID-19 pandemic. Program outcomes suggest strategies for, and benefits of, design for performing-arts programs as psychosocial interventions in other communities.

Evolving Drivers of Brazilian SARS-CoV-2 Transmission: A Spatiotemporally Disaggregated Time Series Analysis of Meteorology, Policy, and Human Mobility.

Brazil has been severely affected by the COVID-19 pandemic. Temperature and humidity have been purported as drivers of SARS-CoV-2 transmission, but no consensus has been reached in the literature regarding the relative roles of meteorology, governmental policy, and mobility on transmission in Brazil. We compiled data on meteorology, governmental policy, and mobility in Brazil's 26 states and one federal district from June 2020 to August 2021. Associations between these variables and the time-varying reproductive number (R t ) of SARS-CoV-2 were examined using generalized additive models fit to data from the entire 15-month period and several shorter, 3-month periods. Accumulated local effects and variable importance metrics were calculated to analyze the relationship between input variables and R t . We found that transmission is strongly influenced by unmeasured sources of between-state heterogeneity and the near-recent trajectory of the pandemic. Increased temperature generally was associated with decreased transmission and increased specific humidity with increased transmission. However, the impacts of meteorology, policy, and mobility on R t varied in direction, magnitude, and significance across our study period. This time variance could explain inconsistencies in the published literature to date. While meteorology weakly modulates SARS-CoV-2 transmission, daily or seasonal weather variations alone will not stave off future surges in COVID-19 cases in Brazil. Investigating how the roles of environmental factors and disease control interventions may vary with time should be a deliberate consideration of future research on the drivers of SARS-CoV-2 transmission.

Public health and social measures during health emergencies such as the COVID-19 pandemic: An initial framework to conceptualize and classify measures.

Background: Public health and social measures (PHSM) intend to reduce the transmission of infectious diseases and to reduce the burden on health systems, economies and societies. During the COVID-19 pandemic, PHSM have been selected, combined and implemented in a variable manner and inconsistently categorized in policy trackers. This paper presents an initial conceptual framework depicting how PHSM operate in a complex system, enabling a wide-reaching description of these measures and their intended and unintended outcomes. Methods: In a multi-stage development process, we combined (i) a complexity perspective and systems thinking; (ii) literature on existing COVID-19 PHSM frameworks, taxonomies and policy trackers; (iii) expert input and (iv) application to school and international travel measures. Results: The initial framework reflects our current understanding of how PHSM are intended to achieve transmission-related outcomes in a complex system, offering visualizations, definitions and worked examples. First, PHSM operate through two basic mechanisms, that is, reducing contacts and/or making contacts safer. Second, PHSM are defined not only by the measures themselves but by their stringency and application to specific populations and settings. Third, PHSM are critically influenced by contextual factors. The framework provides a tool for structured thinking and further development, rather than a ready-to-use tool for practice. Conclusions: This conceptual framework seeks to facilitate coordinated, interdisciplinary research on PHSM effectiveness, impact and implementation; enable consistent, coherent PHSM monitoring and evaluation; and contribute to evidence-informed decision-making on PHSM implementation, adaptation and de-implementation. We expect this framework to be modified and refined over time.

Uncovering COVID-19 infection determinants in Portugal: towards an evidence-based spatial susceptibility index to support epidemiological containment policies.

BACKGROUND: COVID-19 caused the largest pandemic of the twenty-first century forcing the adoption of containment policies all over the world. Many studies on COVID-19 health determinants have been conducted, mainly using multivariate methods and geographic information systems (GIS), but few attempted to demonstrate how knowing social, economic, mobility, behavioural, and other spatial determinants and their effects can help to contain the disease. For example, in mainland Portugal, non-pharmacological interventions (NPI) were primarily dependent on epidemiological indicators and ignored the spatial variation of susceptibility to infection. METHODS: We present a data-driven GIS-multicriteria analysis to derive a spatial-based susceptibility index to COVID-19 infection in Portugal. The cumulative incidence over 14 days was used in a stepwise multiple linear regression as the target variable along potential determinants at the municipal scale. To infer the existence of thresholds in the relationships between determinants and incidence the most relevant factors were examined using a bivariate Bayesian change point analysis. The susceptibility index was mapped based on these thresholds using a weighted linear combination. RESULTS: Regression results support that COVID-19 spread in mainland Portugal had strong associations with factors related to socio-territorial specificities, namely sociodemographic, economic and mobility. Change point analysis revealed evidence of nonlinearity, and the susceptibility classes reflect spatial dependency. The spatial index of susceptibility to infection explains with accuracy previous and posterior infections. Assessing the NPI levels in relation to the susceptibility map points towards a disagreement between the severity of restrictions and the actual propensity for transmission, highlighting the need for more tailored interventions. CONCLUSIONS: This article argues that NPI to contain COVID-19 spread should consider the spatial variation of the susceptibility to infection. The findings highlight the importance of customising interventions to specific geographical contexts due to the uneven distribution of COVID-19 infection determinants. The methodology has the potential for replication at other geographical scales and regions to better understand the role of health determinants in explaining spatiotemporal patterns of diseases and promoting evidence-based public health policies.

Two years of COVID-19 pandemic: Framework of health interventions in a Brazilian city.

The COVID-19 pandemic and its effects on public health have urgently demanded effective health policies to avoid the spread of COVID-19. Thus, public administrators have implemented non-pharmacological and pharmacological interventions to mitigate the pandemic's impacts and strengthen health services. The aim of this ecological study is to describe the scenario of COVID-19 pandemic in a Brazilian city, during 2 years. This ecological study was carried out in Nova Friburgo, a Brazilian city, for 105 weeks (two years), from March 29, 2020 (week 1) to April 02, 2022 (week 105). Data on COVID-19 cases and COVID-19 deaths, occupation of COVID-19 exclusive beds in hospitals, community mobility, vaccination, government regulation on the opening of city establishments and city risk assessment were collected from public datasets. Four waves of COVID-19 cases and deaths were observed during this period. The first case occurred in week 1 and first death in week 3 of this study. The highest peaks of cases and deaths were observed during the third wave with 1,131 cases (week 54) and 47 deaths (week 55) and where the highest occupation of COVID-19 exclusive beds in local hospitals occurred. Interventions from more restrictive to more flexible, were implemented throughout this study, including lockdown and gradual return in economic and social strata levels. Vaccination began on week 43 and at the end of this study 89.91% of the total population was vaccinated with at least one dose, being 83.22% fully vaccinated. A deep description of several interventions used to avoid COVID-19 spread in a Brazilian city during 2 years of this pandemic can help promote better decision-making in the future while it exposes the challenges of conducting public health policies in a pandemic scenario.

Non-adherence to COVID-19 lockdown: who are they? A cross-sectional study in Portugal.

OBJECTIVES: The SARS-CoV-2 virus has spread worldwide, leading governments to implement mitigation measures. Understanding the reluctance to adhere to non-pharmacological interventions might help promote adherence to these measures. This study aimed to identify factors associated with non-adherence to the first lockdown in Portugal. STUDY DESIGN: Cross-sectional study. METHODS: This study used data from a Portuguese community-based survey entitled 'COVID-19 Barometer: Social Opinion'. Data were collected on risk perception, health status and social experiences using a snowball sampling technique. The event of interest corresponded to participants who reported not staying home during the lockdown period, serving as a proxy for non-adherence to lockdown. Logistic regression was used to identify factors associated with non-adherence to the first lockdown. RESULTS: Responses from 133,601 individual questionnaires that were completed during the first week of the first lockdown in 2020 were analysed. A minority of participants (5.6%) reported non-adherence to lockdown (i.e. leaving home for reasons other than essential situations). Working in the workplace was the factor with the strongest association of non-adherence to the lockdown. Several other factors were also associated with non-adherence to the first lockdown; namely, being a man, being a student, having a low level of education, having a low income, living alone or with a high-infection-risk professional (e.g. doctor, nurse, pharmaceutical, health technician, firefighter, police officer, military, essential services worker), perceiving the risk of getting COVID-19 to be high, not having social support in case of infection, feeling agitated, sad or anxious every day, and considering the preventive measures to be unimportant or inadequate. CONCLUSIONS: Non-adherence to lockdown was associated with socio-economic, trust and perception factors. Future research should investigate the mechanisms underlying these associations to help identify the population groups who are most at risk of non-adherence.

Effects of COVID-19 Non-Pharmacological Interventions on Dengue Infection: A Systematic Review and Meta-Analysis.

Non-pharmacological interventions (NPIs) implemented during the coronavirus disease 2019 (COVID-19) pandemic have demonstrated significant positive effects on other communicable diseases. Nevertheless, the response for dengue fever has been mixed. To illustrate the real implications of NPIs on dengue transmission and to determine the effective measures for preventing and controlling dengue, we performed a systematic review and meta-analysis of the available global data to summarize the effects comprehensively. We searched Embase, PubMed, and Web of Science in line with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines from December 31, 2019, to March 30, 2022, for studies of NPI efficacy on dengue infection. We obtained the annual reported dengue cases from highly dengue-endemic countries in 2015-2021 from the European Centre for Disease Prevention and Control to determine the actual change in dengue cases in 2020 and 2021, respectively. A random-effects estimate of the pooled odds was generated with the Mantel-Haenszel method. Between-study heterogeneity was assessed using the inconsistency index (I2 ) and subgroup analysis according to country (dengue-endemic or non-endemic) was conducted. This review was registered with PROSPERO (CRD42021291487). A total of 17 articles covering 32 countries or regions were included in the review. Meta-analysis estimated a pooled relative risk of 0.39 (95% CI: 0.28-0.55), and subgroup revealed 0.06 (95% CI: 0.02-0.25) and 0.55 (95% CI: 0.44-0.68) in dengue non-endemic areas and dengue-endemic countries, respectively, in 2020. The majority of highly dengue-endemic countries in Asia and Americas reported 0-100% reductions in dengue cases in 2020 compared to previous years, while some countries (4/20) reported a dramatic increase, resulting in an overall increase of 11%. In contrast, there was an obvious reduction in dengue cases in 2021 in almost all countries (18/20) studied, with an overall 40% reduction rate. The overall effectiveness of NPIs on dengue varied with region and time due to multiple factors, but most countries reported significant reductions. Travel-related interventions demonstrated great effectiveness for reducing imported cases of dengue fever. Internal movement restrictions of constantly varying intensity and range are more likely to mitigate the entire level of dengue transmission by reducing the spread of dengue fever between regions within a country, which is useful for developing a more comprehensive and sustainable strategy for preventing and controlling dengue fever in the future.

Impact of layered non-pharmacological interventions on COVID-19 transmission dynamics in Yucatan, Mexico.

Background: The pandemic propagation of SARS-CoV-2 led to the adoption of a myriad of non-pharmacological interventions (NPIs, e.g., social distancing, mobility restrictions, gathering restrictions) in the Americas. Using national epidemiological data, here we report the impact of the layered adoption of multiple NPIs aimed at curving SARS-CoV-2 transmission in Yucatan State, Mexico. Methods: Data from suspected and laboratory confirmed COVID-19 cases during 2020 were analyzed by age groups and sex, clinical signs, and symptoms as well as outcome. The impact of NPIs was quantified using time-varying reproduction numbers (R t) estimated as a time-series and by sectors of the city. Findings: A total of 69,602 suspected cases were reported, 39.3% were laboratory-confirmed. Men were hospitalized (60.2%), more severely ill (3% vs 1.9%) and more likely to die (62%) than women. Early in the outbreak, all sectors in Merida had R t estimates above unity. Once all NPÍs were in place, R t values were dramatically reduced below one, and in the last interval transmission estimates of R t remained below one in all sectors. Interpretation: In the absence of a COVID-19 vaccination program, the combination and wide adherence of NPÍs led to a low and stable trend in SARS-CoV-2 transmission that did not overwhelm the health sector. Our study reflects that a controlled and planned ease of restrictions to balance health, social and economic recovery resulted in a single wave of transmission that prolonged at low and stable levels. Funding: GVP received funding from Emory University via the MP3 Initiative.

The association of intensity and duration of non-pharmacological interventions and implementation of vaccination with COVID-19 infection, death, and excess mortality: Natural experiment in 22 European countries.

BACKGROUND: Critical questions remain regarding the need for intensity to continue NPIs as the public was vaccinated. We evaluated the association of intensity and duration of non-pharmaceutical interventions (NPIs) and vaccines with COVID-19 infection, death, and excess mortality in Europe. METHODS: Data comes from Our Word in Data. We included 22 European countries from January 20, 2020, to May 30, 2021. The time-varying constrained distribution lag model was used in each country to estimate the impact of different intensities and duration of NPIs on COVID-19 control, considering vaccination coverage. Country-specific effects were pooled through meta-analysis. RESULTS: This study found that high-intensity and long-duration of NPIs showed a positive main effect on reducing infection in the absence of vaccines, especially in the intensity above the 80th percentile and lasted for 7 days (RR = 0.93, 95% CI: 0.89-0.98). However, the adverse effect on excess mortality also increased with the duration and intensity. Specifically, it was associated with an increase of 44.16% (RR = 1.44, 95% CI: 1.27-1.64) in the excess mortality under the strict intervention (the intensity above the 80th percentile and lasted for 21 days). As the vaccine rollouts, the inhibition of the strict intervention on cases growth rate was increased (RR dropped from 0.95 to 0.87). Simultaneously, vaccination also alleviated the negative impact of the strict intervention on excess mortality (RR decreased from 1.44 to 1.25). Besides, maintaining the strict intervention appeared to more reduce the cases, as well as avoids more overall burden of death compared with weak intervention. CONCLUSIONS: Our study highlights the importance of continued high-intensity NPIs in low vaccine coverage. Lifting of NPIs in insufficient vaccination coverage may cause increased infections and death burden. Policymakers should coordinate the intensity and duration of NPIs and allocate medical resources reasonably with widespread vaccination.

Understanding the Effects of Music Care on the Lived Experience of Isolation and Loneliness in Long-Term Care: A Qualitative Study.

This qualitative study aims to understand the lived experience of residents and other stakeholders during the implementation of a comprehensive music program in long-term care. It was conducted using a subset of 15 long-term care homes from the Room 217 Foundation Music Care Partners (MCP) "Grow" study in Ontario, Canada. The MCP program's approach to music delivery uses therapeutic music practices such as "music care" to improve the care experience for caregivers and residents in long-term care homes. Thirty-two participants were interviewed, including staff, volunteers, and residents. Data were transcribed and analyzed using a modified grounded theory approach based on emergent themes. In total, seven themes arose from the data: limited resources, distinct experiences, life enrichment, dynamic relationships, program flexibility, potential continuity, and enhanced socialization. This study provides insight on barriers, enablers, and outcomes of the MCP program and on key considerations for implementing a novel interdisciplinary music program in a healthcare setting.

Inferring global-scale temporal latent topics from news reports to predict public health interventions for COVID-19.

The COVID-19 pandemic has highlighted the importance of non-pharmacological interventions (NPIs) for controlling epidemics of emerging infectious diseases. Despite their importance, NPIs have been monitored mainly through the manual efforts of volunteers. This approach hinders measurement of the NPI effectiveness and development of evidence to guide their use to control the global pandemic. We present EpiTopics, a machine learning approach to support automation of NPI prediction and monitoring at both the document level and country level by mining the vast amount of unlabeled news reports on COVID-19. EpiTopics uses a 3-stage, transfer-learning algorithm to classify documents according to NPI categories, relying on topic modeling to support result interpretation. We identified 25 interpretable topics under 4 distinct and coherent COVID-related themes. Importantly, the use of these topics resulted in significant improvements over alternative automated methods in predicting the NPIs in labeled documents and in predicting country-level NPIs for 42 countries.

When and How to Adjust Non-Pharmacological Interventions Concurrent with Booster Vaccinations Against COVID-19 - Guangdong, China, 2022.

Introduction: With the large-scale roll-out of the coronavirus disease 2019 (COVID-19) booster vaccination effort (a vaccine dose given 6 months after completing primary vaccination) in China, we explore when and how China could lift non-pharmacological interventions (NPIs) against COVID-19 in 2022. Methods: Using a modified susceptible-infectious-recovered (SIR) mathematical model, we projected the COVID-19 epidemic situation and required medical resources in Guangdong Province, China. Results: If the number of people entering from overseas recovers to 20% of the number in 2019, the epidemic in 2022 could be controlled at a low level by a containment (215 local cases) or suppression strategy (1,397 local cases). A mitigation strategy would lead to 21,722 local cases. A coexistence strategy would lead to a large epidemic with 6,850,083 local cases that would overwhelm Guangdong's medical system. With 50% or 100% recovery of the 2019 level of travelers from overseas, the epidemic could also be controlled with containment or suppression, but enormous resources, including more hotel rooms for border quarantine, will be required. However, coexistence would lead to an uncontrollable epidemic with 12,922,032 local cases. Discussion: With booster vaccinations, the number of travelers from overseas could increase slightly in 2022, but a suppression strategy would need to be maintained to ensure a controllable epidemic.

Healthy Dwelling: Design of Biophilic Interior Environments Fostering Self-Care Practices for People Living with Migraines, Chronic Pain, and Depression.

The benefits of biophilic interior design have been recognized by healthcare facilities, but residential environments receive relatively less attention with respect to improving the health of people living with chronic diseases. Recent "stay-at-home" restrictions due to the COVID-19 pandemic further emphasized the importance of creating interior spaces that directly and indirectly support physical and mental health. In this viewpoint article, we discuss opportunities for combining biophilic interventions with interior design, fostering disease-specific self-care. We provide examples of designing residential spaces integrating biophilic interventions, light therapy, relaxation opportunities, mindfulness meditation, listening to music, physical activities, aromatherapy, and quality sleep. These modalities can provide the clinical benefits of reducing migraine headaches and chronic pain, as well as improving depressive symptoms. The disease-specific interior environment can be incorporated into residential homes, workplaces, assisted-living residences, hospitals and hospital at home programs. This work aims to promote a cross-disciplinary dialogue towards combining biophilic design and advances in lifestyle medicine to create therapeutic interior environments and to improve healthcare outcomes.

COVID-19 and cardiovascular system. Part 3. COVID-19 current treatment approaches: Evidence-based review

Unified management plan and treatment strategy for COVID-19 patients are yet to be discovered. Many trials on COVID-19 interventions have been registered or are ongoing. In this article the results of large-scale clinical trials on COVID-19 treatment are presented, the potential mechanism of action of some drugs is discussed, the features of the main pharmacological and non-pharmacological therapeutic options for COVID-19 patients are described. © 2021 Sklifosovsky Research Institute for Emergency Medicine. All rights reserved.

Fractional-order backstepping strategy for fractional-order model of COVID-19 outbreak.

The coronavirus disease (COVID-19) pandemic has impacted many nations around the world. Recently, new variant of this virus has been identified that have a much higher rate of transmission. Although vaccine production and distribution are currently underway, non-pharmacological interventions are still being implemented as an important and fundamental strategy to control the spread of the virus in countries around the world. To realize and forecast the transmission dynamics of this disease, mathematical models can be very effective. Various mathematical modeling methods have been proposed to investigate the transmission patterns of this new infection. In this paper, we utilized the fractional-order dynamics of COVID-19. The goal is to control the prevalence of the disease using non-pharmacological interventions. In this paper, a novel fractional-order backstepping sliding mode control (FOBSMC) is proposed for non-pharmacological decisions. Recently, new variant of this virus have been identified that have a much higher rate of transmission, so finally the effectiveness of the proposed controller in the presence of new variant of COVID-19 is investigated.

No Change of Pneumocystis jirovecii Pneumonia after the COVID-19 Pandemic: Multicenter Time-Series Analyses.

Consolidated infection control measures imposed by the government and hospitals during COVID-19 pandemic resulted in a sharp decline of respiratory viruses. Based on the issue of whether Pneumocystis jirovecii could be transmitted by airborne and acquired from the environment, we assessed changes in P. jirovecii pneumonia (PCP) cases in a hospital setting before and after COVID-19. We retrospectively collected data of PCP-confirmed inpatients aged ≥18 years (N = 2922) in four university-affiliated hospitals between January 2015 and June 2021. The index and intervention dates were defined as the first time of P. jirovecii diagnosis and January 2020, respectively. We predicted PCP cases for post-COVID-19 and obtained the difference (residuals) between forecasted and observed cases using the autoregressive integrated moving average (ARIMA) and the Bayesian structural time-series (BSTS) models. Overall, the average of observed PCP cases per month in each year were 36.1 and 47.3 for pre- and post-COVID-19, respectively. The estimate for residuals in the ARIMA model was not significantly different in the total PCP-confirmed inpatients (7.4%, p = 0.765). The forecasted PCP cases by the BSTS model were not significantly different from the observed cases in the post-COVID-19 (-0.6%, 95% credible interval; -9.6~9.1%, p = 0.450). The unprecedented strict non-pharmacological interventions did not affect PCP cases.

The economics of stop-and-go epidemic control.

We analyse 'stop-and-go' containment policies that produce infection cycles as periods of tight lockdowns are followed by periods of falling infection rates. The subsequent relaxation of containment measures allows cases to increase again until another lockdown is imposed and the cycle repeats. The policies followed by several European countries during the Covid-19 pandemic seem to fit this pattern. We show that 'stop-and-go' should lead to lower medical costs than keeping infections at the midpoint between the highs and lows produced by 'stop-and-go'. Increasing the upper and reducing the lower limits of a stop-and-go policy by the same amount would lower the average medical load. But increasing the upper and lowering the lower limit while keeping the geometric average constant would have the opposite effect. We also show that with economic costs proportional to containment, any path that brings infections back to the original level (technically a closed cycle) has the same overall economic cost.

The Interplay between Housing Environmental Attributes and Design Exposures and Psychoneuroimmunology Profile-An Exploratory Review and Analysis Paper in the Cancer Survivors' Mental Health Morbidity Context.

Adult cancer survivors have an increased prevalence of mental health comorbidities and other adverse late-effects interdependent with mental illness outcomes compared with the general population. Coronavirus Disease 2019 (COVID-19) heralds an era of renewed call for actions to identify sustainable modalities to facilitate the constructs of cancer survivorship care and health care delivery through physiological supportive domestic spaces. Building on the concept of therapeutic architecture, psychoneuroimmunology (PNI) indicators-with the central role in low-grade systemic inflammation-are associated with major psychiatric disorders and late effects of post-cancer treatment. Immune disturbances might mediate the effects of environmental determinants on behaviour and mental disorders. Whilst attention is paid to the non-objective measurements for examining the home environmental domains and mental health outcomes, little is gathered about the multidimensional effects on physiological responses. This exploratory review presents a first analysis of how addressing the PNI outcomes serves as a catalyst for therapeutic housing research. We argue the crucial component of housing in supporting the sustainable primary care and public health-based cancer survivorship care model, particularly in the psychopathology context. Ultimately, we illustrate a series of interventions aiming at how housing environmental attributes can trigger PNI profile changes and discuss the potential implications in the non-pharmacological treatment of cancer survivors and patients with mental morbidities.

Impact of mobility restrictions on the dynamics of transmission of COVID-19 in Colombian cities.

BACKGROUND: Our aim was to study the association between case rates and reductions in urban mobility in state capitals of Colombia. METHODS: We designed an ecological time-series study to correlate the Colombian incidence rate with reductions in mobility trends of retail stores. RESULTS: The meta-analysis of ß coefficients describing the association between case rates and reductions in mobility trends of retail stores resulted in a mean estimate of 0.0637 (95% confidence interval 0.027 to 0.101; p<0.001) with nearly 100% heterogeneity. CONCLUSIONS: We recommend continuing to consider mobility restrictions when the number of cases starts to climb in each local jurisdiction.