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The COVID-19 pandemic has highlighted the need for broader access to molecular diagnostics. Colorimetric isothermal nucleic acid amplification assays enable simplified instrumentation over more conventional PCR diagnostic assays and, as such, represent a promising approach for addressing this need. In particular, colorimetric LAMP (loop-mediated isothermal amplification) has received a great deal of interest recently. However, there do not currently exist robust instruments for performing these kinds of assays in high throughput with real-time readout of amplification signals. To address this need, we developed LARI, the LAMP Assay Reader Instrument. We have deployed over 50 LARIs for routine use in R&D and production environments, with over 12,000 assays run to date. In this paper, we present the design and construction of LARI along with thermal, optical, and assay performance characteristics. LARI can be produced for under $1500 and has broad applications in R&D, point-of-care diagnostics, and global health. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic is currently one of the biggest public health threats for people's mental health. A particularly endangered group were students, who became highly affected by measures of social distance due to their active lifestyle. Therefore, the aim of this paper is to assess the level of self-reported stress, anxiety and depression of the student population in Serbia, in relation to demographic characteristics, living and studying conditions, students' activities during the epidemic, potential coronavirus infection and general, mental and physical health. Methods: We conducted a cross-sectional study of 580 undergraduate medical students from the University of Belgrade during the 2020/2021 school year. Mental health data were collected using the Depression Anxiety Stress Scales (DASS-21). Both bivariate and multivariate logistic regression analysis were used to examine the association between independent variables with the dependent variable mental health. Results: Women made up the majority of the sample with 80.3%. A total of 64.5%, 66.8% and 66.7% of students between the ages of 21 and 30 had severe depressive symptoms, severe degree of anxiety, and a severe degree of stress, respectively. Women almost twice as often (OR = 1.89) assessed their anxiety as severe and almost two and a half times more (OR = 2.39) perceived stress as severe compared to men. Students who lived with their families during studies two and a half times (OR = 2.57) more often assessed their stress as severe, compared to students who lived alone. Fifth- and sixth-year students were less likely to rate depression and anxiety as serious than the first-year students. Conclusions: Medical students reported their health as severely impaired in terms of depression, anxiety and stress reactions. The results indicate the need to launch a mental health program in the form of counseling and emotional support to students affected by the pandemic. [ABSTRACT FROM AUTHOR]

The success of mass vaccination programs against SARS-CoV-2 hinges on the public's acceptance of the vaccines. During a vaccine roll-out, individuals have limited information about the potential side-effects and benefits. Given the public health concern of the COVID pandemic, providing appropriate information fast matters for the success of the campaign. In this paper, time-trends in vaccine hesitancy were examined using a sample of 35,390 respondents from the Eurofound's Living, Working and COVID-19 (LWC) data collected between 12 February and 28 March 2021 across 28 European countries. The data cover the initial stage of the vaccine roll-out. We exploit the fact that during this period, news about rare cases of blood clots with low blood platelets were potentially linked to the Oxford/AstraZeneca vaccine (or Vaxzeveria). Multivariate regression models were used to analyze i) vaccine hesitancy trends, and whether any trend-change was associated with the link between the AstraZeneca vaccine ii) and blood clots (AstraZeneca controversy), and iii) the suspension among several European countries. Our estimates show that vaccine hesitancy increased over the early stage of the vaccine roll-out (0·002, 95% CI: [0·002 to 0·003]), a positive shift took place in the likelihood of hesitancy following the controversy (0·230, 95% CI: [0·157 to 0·302]), with the trend subsequently turning negative (-0·007, 95% CI: [-0·010 to -0·005]). Countries deciding to suspend the AstraZeneca vaccine experienced an increase in vaccine hesitancy after the suspensions (0·068, 95% CI: [0·04 to 0·095]). Trust in institutions is negatively associated with vaccine hesitancy. The results suggest that SARS-CoV-2 vaccine hesitancy increased steadily since the beginning of the vaccine roll-out and the AstraZeneca controversy and its suspension, made modest (though significant) contributions to increased hesitancy. [ABSTRACT FROM AUTHOR]

Background: To understand the impact of COVID-19 on implementation of the peer education programme of the National Adolescent Health Programme-Rashtriya Kishor Swasthya Karyakram (RKSK); repurposing of the RKSK health workers and Peer Educators (PEs) in COVID-19 response activities and effect on adolescents´ health and development issues. Methods: Virtual in-depth interviews were conducted with stakeholders (n = 31) (aged 15 to 54 years) engaged in the implementation of the RKSK and peer education programme at state, district, block, and village levels in Madhya Pradesh and Maharashtra (India). These interviews were thematically coded and analysed to address the research objectives. Results: Despite most peer education programme activities being stopped, delayed, or disrupted during the pandemic and subsequent lockdown, some communication networks previously established, helped facilitate public health communication regarding COVID-19 and RKSK, between health workers, PEs, and adolescents. There was repurposing of RKSK health workers and PEs' role towards COVID-19 response-related activities. PEs, with support from health workers, were involved in disseminating COVID-19 information, maintaining migrant and quarantine records, conducting household surveys for recording COVID-19 active cases and providing essential items (grocery, sanitary napkins, etc.) to communities and adolescents. Conclusion: PEs with support from community health workers are able to play a crucial role in meeting the needs of the communities during a pandemic. There is a need to further engage, involve and build the skills of PEs to support the health system. PEs can be encouraged by granting more visibility and incorporating their role more formally by paying them within the public health system in India. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has presented a unique opportunity to explore how health systems adapt under rapid and constant change and develop a better understanding of health system transformation. Learning health systems (LHS) have been proposed as an ideal structure to inform a data-driven response to a public health emergency like COVID-19. The aim of this study was to use a LHS framework to identify assets and gaps in health system pandemic planning and response during the initial stages of the COVID-19 pandemic at a single Canadian Health Centre. Methods: This paper reports the data triangulation stage of a concurrent triangulation mixed methods study which aims to map study findings onto the LHS framework. We used a triangulation matrix to map quantitative (textual and administrative sources) and qualitative (semi-structured interviews) data onto the seven characteristics of a LHS and identify assets and gaps related to health-system receptors and research-system supports. Results: We identified several health system assets within the LHS characteristics, including appropriate decision supports and aligned governance. Gaps were identified in the LHS characteristics of engaged patients and timely production and use of research evidence. Conclusion: The LHS provided a useful framework to examine COVID-19 pandemic response measures. We highlighted opportunities to strengthen the LHS infrastructure for rapid integration of evidence and patient experience data into future practice and policy changes. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the influence of corruption perception, experiences of corruptive behavior, and healthcare autonomy on the public trust in Montenegrin healthcare, by surveying the general population before and after the global COVID-19 pandemic. By providing a quasi-replication of a previous empirical study of corruption and trust in the Croatian public healthcare sector, we introduce the COVID-19 pandemic as a new research context. Before the pandemic, we found a consistent and significant negative influence of the corruptive practices and the generally perceived level of corruption (corruption salience) on the trust in public healthcare. The emergence of COVID-19 had mixed effects: while there is a slightly higher effect of corruption salience to the preference of public healthcare, corruptive experiences still matter but are tolerated much higher than before the pandemic. Public assessment of the autonomy of the health system increases preference for public healthcare, both before and after the pandemic, although the emergence of COVID-19 somewhat lowers this effect. The obtained results point to the most significant challenges of the 'post-COVID-19' social context to public health policymaking and management of public healthcare institutions. These include focusing the public healthcare reforms on corruption, reducing waiting times for different diagnostics and medical procedures in the public healthcare system, and regulating the 'dual practice' (simultaneous work in public and private healthcare institutions). [ABSTRACT FROM AUTHOR]

Background: COVID-19 has rapidly emerged as a global public health threat with infections recorded in nearly every country. Responses to COVID-19 have varied in intensity and breadth, but generally have included domestic and international travel limitations, closure of non-essential businesses, and repurposing of health services. While these interventions have focused on testing, treatment, and mitigation of COVID-19, there have been reports of interruptions to diagnostic, prevention, and treatment services for other public health threats. Objectives: We conducted a scoping review to characterize the early impact of COVID-19 on HIV, tuberculosis, malaria, sexual and reproductive health, and malnutrition. Methods: A scoping literature review was completed using searches of PubMed and preprint servers (medRxiv/bioRxiv) from November 1st, 2019 to October 31st, 2020, using Medical Subject Headings (MeSH) terms related to SARS-CoV-2 or COVID-19 and HIV, tuberculosis, malaria, sexual and reproductive health, and malnutrition. Empiric studies reporting original data collection or mathematical models were included, and available data synthesized by region. Studies were excluded if they were not written in English. Results: A total of 1604 published papers and 205 preprints were retrieved in the search. Overall, 8.0% (129/1604) of published studies and 10.2% (21/205) of preprints met the inclusion criteria and were included in this review: 7.3% (68/931) on HIV, 7.1% (24/339) on tuberculosis, 11.6% (26/224) on malaria, 7.8% (19/183) on sexual and reproductive health, and 9.8% (13/132) on malnutrition. Thematic results were similar across competing health risks, with substantial indirect effects of the COVID-19 pandemic and response on diagnostic, prevention, and treatment services for HIV, tuberculosis, malaria, sexual and reproductive health, and malnutrition. Discussion: COVID-19 emerged in the context of existing public health threats that result in millions of deaths every year. Thus, effectively responding to COVID-19 while minimizing the negative impacts of COVID-19 necessitates innovation and integration of existing programs that are often siloed across health systems. Inequities have been a consistent driver of existing health threats; COVID-19 has worsened disparities, reinforcing the need for programs that address structural risks. The data reviewed here suggest that effective strengthening of health systems should include investment and planning focused on ensuring the continuity of care for both rapidly emergent and existing public health threats. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had a devastating impact on the global economy. In this paper, we use the Phillips curve to compare and analyze the macroeconomics of three different countries with distinct income levels, namely, lower-middle (Nigeria), upper-middle (South Africa), and high (Canada) income. We aim to (1) find macroeconomic changes in the three countries during the pandemic compared to pre-pandemic time, (2) compare the countries in terms of response to the COVID-19 economic crisis, and (3) compare their expected economic reaction to the COVID-19 pandemic in the near future. An advantage to our work is that we analyze macroeconomics on a monthly basis to capture the shocks and rapid changes caused by on and off rounds of lockdowns. We use the volume and social sentiments of the Twitter data to approximate the macroeconomic statistics. We apply four different machine learning algorithms to estimate the unemployment rate of South Africa and Nigeria on monthly basis. The results show that at the beginning of the pandemic the unemployment rate increased for all the three countries. However, Canada was able to control and reduce the unemployment rate during the COVID-19 pandemic. Nonetheless, in line with the Phillips curve short-run, the inflation rate of Canada increased to a level that has never occurred in more than fifteen years. Nigeria and South Africa have not been able to control the unemployment rate and did not return to the pre-COVID-19 level. Yet, the inflation rate has increased in both countries. The inflation rate is still comparable to the pre-COVID-19 level in South Africa, but based on the Phillips curve short-run, it will increase further, if the unemployment rate decreases. Unfortunately, Nigeria is experiencing a horrible stagflation and a wild increase in both unemployment and inflation rates. This shows how vulnerable lower-middle-income countries could be to lockdowns and economic restrictions. In the near future, the main concern for all the countries is the high inflation rate. This work can potentially lead to more targeted and publicly acceptable policies based on social media content. [ABSTRACT FROM AUTHOR]

The propensity to have children, which, according to the view accepted in the literature, is a good predictor of actual childbearing, is of particular importance in countries with low fertility rates and economic prosperity. In this paper, we report the results of a representative survey of 15,700 respondents in 2021 of university students in an emerging market economy in Central Europe, mapping their intentions to have children. The PLS-SEM data analysis method was used to test our hypotheses on the relationships between social, economic, and environmental variables of childbearing. Our results confirm the dominant role of socio-cultural inclusiveness in childbearing, over socio-economic and environmental-economic factors. The novelty of our research lies in the impact analysis of family policy incentives; however, our results are consistent with those documented in the literature, namely, the primacy of socio-cultural factors in the willingness of childbearing. [ABSTRACT FROM AUTHOR]

When the threat of COVID-19 became widely acknowledged, many hoped that this pandemic would squash "the anti-vaccine movement". However, when vaccines started arriving in rich countries at the end of 2020, it appeared that vaccine hesitancy might be an issue even in the context of this major pandemic. Does it mean that the mobilization of vaccine-critical activists on social media is one of the main causes of this reticence to vaccinate against COVID-19? In this paper, we wish to contribute to current work on vaccine hesitancy during the COVID-19 pandemic by looking at one of the many mechanisms which can cause reticence towards vaccines: the capacity of vaccine-critical activists to influence a wider public on social media. We analyze the evolution of debates over the COVID-19 vaccine on the French Twittosphere, during two first years of the pandemic, with a particular attention to the spreading capacity of vaccine-critical websites. We address two main questions: 1) Did vaccine-critical contents gain ground during this period? 2) Who were the main actors in the diffusion of these contents? While debates over vaccines experienced a tremendous surge during this period, the share of vaccine-critical contents in these debates remains stable except for a limited number of short periods associated with specific events. Secondly, analyzing the community structure of the re-tweets hyper-graph, we reconstruct the mesoscale structure of the information flows, identifying and characterizing the major communities of users. We analyze their role in the information ecosystem: the largest right-wing community has a typical echo-chamber behavior collecting all the vaccine-critical tweets from outside and recirculating it inside the community. The smaller left-wing community is less permeable to vaccine-critical contents but, has a large capacity to spread it once adopted. [ABSTRACT FROM AUTHOR]

Medical facility equality is a critical metric for determining equal access to medical care. Their spatial distribution is important for effective pandemic treatment and daily prevention in cities. This paper used the Kernel Density Two-Step Floating Catchment Area (KD2SFCA) and shortest distance methods to calculate the accessibility of designated COVID-19 Fangcang hospitals and fever clinics in the Wuhan Metropolitan Development Zone. Their equality was evaluated by the Gini coefficient and Lorentz curve. Several results were obtained: (1) The facilities' accessibility declines radial from the central to peripheral areas. (2) Most of the demand points in the study area can reach the medical facilities for COVID-19 pandemic treatment within 60 minutes. (3) For the spatial distribution of these facilities, the equality evaluated for different time thresholds differed significantly, with long time thresholds having better equality than for short time thresholds. (4) While the distances distribution of fever clinics is balanced, the equality gap in various areas remains enormous when considering population distribution. Suggestions for optimizing the spatial distribution of pandemic treatment medical facilities in Wuhan are proposed, and which will serve as references for the planning of Wuhan's pandemic medical facilities in the future. [ABSTRACT FROM AUTHOR]

Background: The situation of the COVID-19 outbreak in the border areas of China and Vietnam is complex, and its progress may affect the willingness of urban and rural residents to receive the vaccine. Objective: This study aims to understand the influence of the COVID-19 epidemic situation on the willingness of urban and rural residents in China-Vietnam border areas to get vaccinated and the factors that affect the vaccinations. Methods: A cross-sectional survey was conducted in Hani-Yi Autonomous Prefecture of Honghe, a border area between China and Vietnam, using online and paper questionnaires from April 1 to June 4, 2021. A total of 8849 valid questionnaires were surveyed to compare the differences in the willingness of urban and rural residents to receive the COVID-19 vaccine. Single factor analysis and multivariate logistic regression analysis were used to explore the influence of the epidemic situation on the willingness to be vaccinated. Results: In the border areas between China and Vietnam in Yunnan Province, both urban and rural residents had a high willingness (> 90%) to receive the COVID-19 vaccination, with a higher level of willingness in urban than in rural areas and a higher willingness among residents aged ≥ 56 years. Rural residents mainly concerned about the vaccination were different from urban residents (p< 0.05). About 54.8% of urban respondents and 59.2% of rural respondents indicated that their willingness to get COVID-19 vaccine would be affected by new COVID-19 cases. Respondents who were divorced, had an occupation other than farming, had contraindications to vaccination, were concerned about the safety of vaccines and worried about virus mutation, thought that the epidemic situation would not affect their willingness to get vaccinated (p< 0.05). Conclusion: The prevention and control of epidemics in border areas is of considerable importance. It is necessary to conduct targeted health education and vaccine knowledge popularization among urban and rural residents to increase the vaccination rate and consolidate the epidemic prevention and control at the border. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic upended how many Americans acquire foods. In this paper, we analyze eight food acquisition activities at different points in the pandemic, which allows us to evaluate how food acquisition changed as case rates changed and vaccine rollouts occurred. We collected data from three nationally representative online samples in September 2020, December 2020, and March 2021. We evaluate changes across time and across demographics using a multivariate probit model. Across time, we find that in-person grocery shopping remained extremely common (over 90%) throughout the pandemic. Food acquisition activities with less in-person contact (e.g., ordering from a meal kit service, online grocery shopping) peaked in December 2020, likely due to the surge in cases during that period. Ordering take-out from a restaurant remained common throughout the pandemic, but indoor dining increased significantly in March 2021 when vaccines were becoming more widely available. Food acquisition activities also varied across consumer groups, particularly indoor and outdoor restaurant dining. Overall our results offer evidence that in-person grocery shopping is a staple food acquisition activity that is unlikely to be changed; however, there is a segment of consumers who complement their in-person grocery shopping with online grocery shopping options. Further, relative to grocery stores, restaurants may be more vulnerable to surges in COVID-19 case rates. We conclude with implications for grocery retailers and restaurants as they continue to navigate operational challenges associated with the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Covid-19 has impacted the U.S. economy and business organizations in multiple ways, yet its influence on company fundamentals and risk structures have not been fully elucidated. In this paper, we apply LDA, a mainstream topic model, to analyze the risk factor section from SEC filings (10-K and 10-Q), and describe risk structure change over the past two years. The results show that Covid-19 has transformed the risk structures U.S. companies face in the short run, exerting excessive stress on international interactions, operations, and supply chains. However, this shock has been waning since the second quarter of 2020. Our model shows that risk structure change (measured by topic distribution) from Covid-19 is a significant predictor of lower performance, but smaller companies tend to be stricken harder. [ABSTRACT FROM AUTHOR]

Capacity limitations are indispensable measures of social distancing in fighting COVID-19 and other pandemics. The paper at hand analyzes these restrictions from the viewpoint of fairness, understood as the possibility of equal access to the scarce resource. To this end, it employs the so-called El Farol Bar problem in conjunction with an adaptive learning approach. Particular emphasis is given to the distribution of information. Our results show that information is, indeed, central to the situation. Policy recommendations are derived. [ABSTRACT FROM AUTHOR]

COVID-19 has got us to face a new situation where, for the lack of ready-to-use vaccines, it is necessary to support vaccination with complex non-pharmaceutical strategies. In this paper, we provide a novel Mixed Integer Nonlinear Programming formulation for fine-grained optimal intervention planning (i.e., at the level of the single day) against newborn epidemics like COVID-19, where a modified SIR model accounting for heterogeneous population classes, social distancing and several types of vaccines (each with its efficacy and delayed effects), allows us to plan an optimal mixed strategy (both pharmaceutical and non-pharmaceutical) that takes into account both the vaccine availability in limited batches at selected time instants and the need for second doses while keeping hospitalizations and intensive care occupancy below a threshold and requiring that new infections die out at the end of the planning horizon. In order to show the effectiveness of the proposed formulation, we analyze a case study for Italy with realistic parameters. [ABSTRACT FROM AUTHOR]

The outbreak of COVID-19 at the beginning of 2020 had a significant impact on China's economy, society, and citizens; it also had a negative impact on the development of the construction industry. In particular, small and medium-sized construction enterprises with low ability to withstand risk have been strongly impacted, aggravating a crisis of survival among these firms. The focus of this study is to analyze the impact of COVID-19 on the growth of small and medium-sized construction companies. Based on the characteristics of small and medium-sized construction enterprises, this paper establishes a growth evaluation index and builds a growth evaluation model based on factor analysis. Twenty-three construction enterprises listed on small and medium-sized enterprises board are selected as samples, and the quarterly data of 2019 and 2020 are used for empirical analysis. The results show that the epidemic has had a high short-term impact on construction enterprises, and the total output value of the construction industry in the first quarter of 2020 was 16% lower than that in the same period of last year. In the long run, the impact of the epidemic on the growth of small and medium-sized construction enterprises has been limited. In the first quarter of 2020, the growth score of enterprises decreased by only 1.95% year-over-year, and it was essentially flat in the second and third quarters. The epidemic has had little influence on solvency, tangible resources or intangible resources but a high short term influence on profitability, capital expansion and market expectations. The long-term impact is small; It is conducive to the improvement of enterprise operation ability. Finally, to both address the influence of the COVID-19 on small and medium-sized construction enterprises and to realize their transformation and upgrading, targeted suggestions are offered at the policy and enterprise levels. The results will help to understand the impact of the epidemic on the growth of construction enterprises, and provide decision support for the healthy and orderly development of the follow-up construction industry. [ABSTRACT FROM AUTHOR]

In an effort to gauge the global pandemic's impact on social thoughts and behavior, it is important to answer the following questions: (1) What kinds of topics are individuals and groups vocalizing in relation to the pandemic? (2) Are there any noticeable topic trends and if so how do these topics change over time and in response to major events? In this paper, through the advanced Sequential Latent Dirichlet Allocation model, we identified twelve of the most popular topics present in a Twitter dataset collected over the period spanning April 3rd to April 13th, 2020 in the United States and discussed their growth and changes over time. These topics were both robust, in that they covered specific domains, not simply events, and dynamic, in that they were able to change over time in response to rising trends in our dataset. They spanned politics, healthcare, community, and the economy, and experienced macro-level growth over time, while also exhibiting micro-level changes in topic composition. Our approach differentiated itself in both scale and scope to study the emerging topics concerning COVID-19 at a scale that few works have been able to achieve. We contributed to the cross-sectional field of urban studies and big data. Whereas we are optimistic towards the future, we also understand that this is an unprecedented time that will have lasting impacts on individuals and society at large, impacting not only the economy or geo-politics, but human behavior and psychology. Therefore, in more ways than one, this research is just beginning to scratch the surface of what will be a concerted research effort into studying the history and repercussions of COVID-19. [ABSTRACT FROM AUTHOR]

The appearance of a novel coronavirus in late 2019 radically changed the community of researchers working on coronaviruses since the 2002 SARS epidemic. In 2020, coronavirus-related publications grew by 20 times over the previous two years, with 130,000 more researchers publishing on related topics. The United States, the United Kingdom and China led dozens of nations working on coronavirus prior to the pandemic, but leadership consolidated among these three nations in 2020, which collectively accounted for 50% of all papers, garnering well more than 60% of citations. China took an early lead on COVID-19 research, but dropped rapidly in production and international participation through the year. Europe showed an opposite pattern, beginning slowly in publications but growing in contributions during the year. The share of internationally collaborative publications dropped from pre-pandemic rates; single-authored publications grew. For all nations, including China, the number of publications about COVID track closely with the outbreak of COVID-19 cases. Lower-income nations participate very little in COVID-19 research in 2020. Topic maps of internationally collaborative work show the rise of patient care and public health clusters—two topics that were largely absent from coronavirus research in the two years prior to 2020. Findings are consistent with global science as a self-organizing system operating on a reputation-based dynamic. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has been characterized by a social media "infodemic": an overabundance of information whose authenticity may not always be guaranteed. With the potential to lead individuals to harmful decisions for the society, this infodemic represents a severe threat to information security, public health and democracy. In this paper, we assess the interplay between the infodemic and specific aspects of the pandemic, such as the number of cases, the strictness of containment measures, and the news media coverage. We perform a comparative study on three countries that employed different managements of the COVID-19 pandemic in 2020—namely Italy, the United Kingdom, and New Zealand. We first analyze the three countries from an epidemiological perspective to characterize the impact of the pandemic and the strictness of the restrictions adopted. Then, we collect a total of 6 million posts from Facebook to describe user news consumption behaviors with respect to the reliability of such posts. Finally, we quantify the relationship between the number of posts published in each of the three countries and the number of confirmed cases, the strictness of the restrictions adopted, and the online news media coverage about the pandemic. Our results show that posts referring to reliable sources are consistently predominant in the news circulation, and that users engage more with reliable posts rather than with posts referring to questionable sources. Furthermore, our modelling results suggest that factors related to the epidemiological and informational ecosystems can serve as proxies to assess the evolution of the infodemic. [ABSTRACT FROM AUTHOR]

Physical activity is essential to maintain physical and mental well-being. During the COVID-19 pandemic, in-person physical activity opportunities were limited. This paper describes a telephone-based physical activity support strategy among racially/ethnically diverse patients during the COVID-19 pandemic. Adult patients at a large, Federally Qualified Health Center with an on-site exercise facility referral were eligible to transition to telephone support with personal fitness advisors during the pandemic stay-at-home orders. Baseline surveys assessed physical activity and environmental characteristics; follow-up phone calls used motivational interviewing and physical activity goal setting strategies. From March 23-July 23, 2020, 72 patients participated in 270 phone calls, or 3.8 (±2.1) calls per participant. Participants were, on average, aged 51.3 (±11.6) years, 87.5% female, 31.9% Hispanic/Latino, and 47.2% non-Hispanic Black. Patients meeting physical activity guidelines pre-pandemic reported more planned exercise (100.0% vs. 55.3%; p<0.001), exercise days at home (5.0 vs. 1.7; p<0.001), and accomplishment of personal physical activity goals (57.0% vs. 39.7%; p = 0.11) than patients not meeting guidelines pre-pandemic. Patients with a home treadmill participated in twice the rate of calls compared to those without (RR = 2.22; 95%CI:1.35,3.64), but no other home environmental characteristics predicted participation rate. Pre-pandemic physical activity behavior appeared to predict pandemic physical activity and telephone-based physical activity support was effective for maintaining physical activity for some participants. Long term applications of this work will support continuity of clinic-community partnerships for health behavior change and provide a model for patient physical activity support by community health centers without on-site exercise facilities. [ABSTRACT FROM AUTHOR]

Background: It is critical to capture data and modeling from the COVID-19 pandemic to understand as much as possible and prepare for future epidemics and possible pandemics. The Hawaiian Islands provide a unique opportunity to study heterogeneity and demographics in a controlled environment due to the geographically closed borders and mostly uniform pandemic-induced governmental controls and restrictions. Objective: The goal of the paper is to quantify the differences and similarities in the spread of COVID-19 among different Hawaiian islands as well as several other archipelago and islands, which could potentially help us better understand the effect of differences in social behavior and various mitigation measures. The approach should be robust with respect to the unavoidable differences in time, as the arrival of the virus and promptness of mitigation measures may vary significantly among the chosen locations. At the same time, the comparison should be able to capture differences in the overall pandemic experience. Methods: We examine available data on the daily cases, positivity rates, mobility, and employ a compartmentalized model fitted to the daily cases to develop appropriate comparison approaches. In particular, we focus on merge trees for the daily cases, normalized positivity rates, and baseline transmission rates of the models. Results: We observe noticeable differences among different Hawaiian counties and interesting similarities between some Hawaiian counties and other geographic locations. The results suggest that mitigation measures should be more localized, that is, targeting the county level rather than the state level if the counties are reasonably insulated from one another. We also notice that the spread of the disease is very sensitive to unexpected events and certain changes in mitigation measures. Conclusions: Despite being a part of the same archipelago and having similar protocols for mitigation measures, different Hawaiian counties exhibit quantifiably different dynamics of the spread of the disease. One potential explanation is that not sufficiently targeted mitigation measures are incapable of handling unexpected, localized outbreak events. At a larger-scale view of the general spread of the disease on the Hawaiian island counties, we find very interesting similarities between individual Hawaiian islands and other archipelago and islands. [ABSTRACT FROM AUTHOR]

The outbreak of COVID-19 has led to there being a worldwide socio-economic crisis, with major impacts on developing countries. Understanding the dynamics of the disease and its driving factors, on a small spatial scale, might support strategies to control infections. This paper explores the impact of the COVID-19 on neighborhoods of Recife, Brazil, for which we examine a set of drivers that combines socio-economic factors and the presence of non-stop services. A three-stage methodology was conducted by conducting a statistical and spatial analysis, including clusters and regression models. COVID-19 data were investigated concerning ten dates between April and July 2020. Hotspots of the most affected regions and their determinant effects were highlighted. We have identified that clusters of confirmed cases were carried from a well-developed neighborhood to socially deprived areas, along with the emergence of hotspots of the case-fatality rate. The influence of age-groups, income, level of education, and the access to essential services on the spread of COVID-19 was also verified. The recognition of variables that influence the spatial spread of the disease becomes vital for pinpointing the most vulnerable areas. Consequently, specific prevention actions can be developed for these places, especially in heterogeneous cities. [ABSTRACT FROM AUTHOR]

Estimating the basic reproduction number of a pandemic and the changes that appear on this value over time provide a good understanding of the contagious nature of the virus and efficiency of the controlling strategies. In this paper, we focus on studying the basic reproduction number (R0) for two important variants of COVID-19 pandemic in Iran: Alpha and Delta variants. We use four different methods, three statistical models and one mathematical model, to compute R0: Exponential Growth Rate (EGR), Maximum Likelihood (ML), Sequential Bayesian (SB), and time-dependent SIR model. Alpha variant of COVID-19 was active in Iran from March 10, 2021 until June 10, 2021. Our computations indicate that total R0 of this variant according to EGR, ML, SB, and SIR model is respectively 0.9999 (95% CI: 0.9994-1), 1.046 (95% CI: 1.044-1.049), 1.06 (95% CI: 1.03-1.08), and 2.79 (95% CI: 2.77-2.81) in the whole active time interval. Moreover, during the time interval from April 3, 2021 to April 9, 2021 in which this variant was in its exponential growth in Iran, R0 of Alpha variant in Iran according to SB, EGR, ML, and SIR model is respectively 2.26 (95% CI: 2.04-2.49), 2.64 (95% CI: 2.58-2.7), 11.38 (95% CI: 11.28-11.48), and 12.13 (95% CI: 12.12-12.14). Delta variant was active in Iran during the time interval from June 22, 2021 until September 22, 2021. Our computations show that during the time interval from July 3, 2021 to July 8, 2021 in which this variant was in its exponential growth in Iran, R0 of Delta variant in Iran according to SB, EGR, ML, and SIR model is respectively 3 (95% CI: 2.34-3.66), 3.1 (95% CI: 3.02-3.17), 12 (95% CI: 11.89-12.12), and 23.3 (95% CI: 23.19-23.41). Further, total R0 of Delta variant in Iran in the whole active time interval according to EGR, ML, SB, and SIR model is respectively 1.042 (95% CI: 1.04-1.043), 1.053 (95% CI: 1.051-1.055), 0.79 (95% CI: 0.63-0.95), and 5.65 (95% CI: 5.6-5.7). As the results show Delta variant was more severe than Alpha variant in Iran. Chasing the changes in R0 during each variant shows that the controlling strategies applied were effective in controlling the virus spread. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak has impacted urban transportation mobility throughout the world. In this paper, we investigate the impact of COVID-19 on the urban mobility network's structural characteristics. We contribute to the literature by discussing how various community areas in the city traffic network are impacted by the pandemic. We analyze a large dataset on urban mobility from the city of Chicago and derive various insights. Our analysis of the mobility network structure is important because a better understanding of such networks can help control the spread of the disease by reducing interactions among individuals. We find that the pandemic significantly impacted the structure of the mobility network of taxis in Chicago. Our study reveals some important pointers for policymakers that could potentially aid in developing urban transportation policies during the pandemic. [ABSTRACT FROM AUTHOR]

Background: The coronavirus disease 2019 (COVID-19) pandemic may have a potentially serious effect on mental health and increase the risk of anxiety, depression, and post-traumatic stress disorders in people. In this study, we aimed to determine the prevalence of psychological illness and the impact of the COVID-19 pandemic on the Libyan population's mental health. Method: A cross-sectional survey, conducted in both online and paper modes and consisting of five sections, was completed in more than 30 cities and towns across Libya. The first section consisted of questions on basic demographic characteristics. The second section contained a survey related to the lockdown status, activities, related stress levels, and quarantine. The third section comprised the self-administered 9-item Patient Health Questionnaire (PHQ-9). The fourth section contained the 7-item Generalized Anxiety Disorder Scale (GAD-7), and the fifth section contained the Impact of Event Scale-Revised (IES-R). Result: Of the 31,557 respondents, 4,280 (13.6%) reported severe depressive symptoms, with a mean [standard deviation (SD)] PHQ-9 score of 8.32 (5.44); 1,767 (5.6%) reported severe anxiety symptoms, with a mean (SD) GAD-7 score of 6 (4.6); and 6,245 (19.8%) of the respondents reported post-traumatic stress disorder (PTSD), with a mean (SD) score of 15.3 (18.85). In multivariate analysis, young age, being female, unmarried, educated, or victims of domestic violence or abuse, work suspension during the pandemic, and having increased workload, financial issues, suicidal thoughts, or a family member with or hospitalized due to COVID-19 were significantly associated with a high likelihood of depressive and anxiety symptoms, as well as PTSD. Internal displacement due to civil war was also associated with PTSD. Conclusion: To our knowledge, this is the first study to analyze the psychological impacts of the COVID-19 pandemic and civil war in Libya. Further study on the development of strategies and interventions aimed at reducing the mental disease burden on the Libyan population is warranted. [ABSTRACT FROM AUTHOR]

COVID-19 is a global pandemic threatening the lives and livelihood of millions of people across the world. Due to its novelty and quick spread, scientists have had difficulty in creating accurate forecasts for this disease. In part, this is due to variation in human behavior and environmental factors that impact disease propagation. This is especially true for regionally specific predictive models due to either limited case histories or other unique factors characterizing the region. This paper employs both supervised and unsupervised methods to identify the critical county-level demographic, mobility, weather, medical capacity, and health related county-level factors for studying COVID-19 propagation prior to the widespread availability of a vaccine. We use this feature subspace to aggregate counties into meaningful clusters to support more refined disease analysis efforts. [ABSTRACT FROM AUTHOR]

Due to the COVID-19 pandemic, countries around the world are facing one of the most severe health and economic crises of recent history and human society is called to figure out effective responses. However, as current measures have not produced valuable solutions, a multidisciplinary and open approach, enabling collaborations across private and public organizations, is crucial to unleash successful contributions against the disease. Indeed, the COVID-19 represents a Grand Challenge to which joint forces and extension of disciplinary boundaries have been recognized as main imperatives. As a consequence, Open Innovation represents a promising solution to provide a fast recovery. In this paper we present a practical application of this approach, showing how knowledge sharing constitutes one of the main drivers to tackle pressing social needs. To demonstrate this, we propose a case study regarding a data sharing initiative promoted by Facebook, the Data For Good program. We leverage a large-scale dataset provided by Facebook to the research community to offer a representation of the evolution of the Italian mobility during the lockdown. We show that this repository allows to capture different patterns of movements on the territory with increasing levels of detail. We integrate this information with Open Data provided by the Lombardy region to illustrate how data sharing can also provide insights for private businesses and local authorities. Finally, we show how to interpret Data For Good initiatives in light of the Open Innovation Framework and discuss the barriers to adoption faced by public administrations regarding these practices. [ABSTRACT FROM AUTHOR]

Background: In response to the novel Coronavirus Disease 2019 (COVID-19) pandemic, the Department of Veterans Affairs (VA) Million Veteran Program (MVP) organized efforts to better understand the impact of COVID-19 on Veterans by developing and deploying a self-reported survey. Methods: The MVP COVID-19 Survey was developed to collect COVID-19 specific elements including symptoms, diagnosis, hospitalization, behavioral and psychosocial factors and to augment existing MVP data with longitudinal collection of key domains in physical and mental health. Due to the rapidly evolving nature of the pandemic, a multipronged strategy was implemented to widely disseminate the COVID-19 Survey and capture data using both the online platform and mailings. Results: We limited the findings of this paper to the initial phase of survey dissemination which began in May 2020. A total of 729,625 eligible MVP Veterans were invited to complete version 1 of the COVID-19 Survey. As of October 31, 2020, 58,159 surveys have been returned. The mean and standard deviation (SD) age of responders was 71 (11) years, 8.6% were female, 8.2% were Black, 5.6% were Hispanic, and 446 (0.8%) self-reported a COVID-19 diagnosis. Over 90% of responders reported wearing masks, practicing social distancing, and frequent hand washing. Conclusion: The MVP COVID-19 Survey provides a systematic collection of data regarding COVID-19 behaviors among Veterans and represents one of the first large-scale, national surveillance efforts of COVID-19 in the Veteran population. Continued work will examine the overall response to the survey with comparison to available VA health record data. [ABSTRACT FROM AUTHOR]

Introduction: The emergence of the novel coronavirus disease of 2019 (COVID-19) has led to huge disruptions in the medical field and society. The significance of training and education for experts has been increasingly acknowledged in Japan, where the number of infectious disease (ID) specialists is reportedly insufficient. In this paper, we report the results of a web-based survey that was conducted to reveal the ways in which the COVID-19 pandemic has influenced medical students' awareness of ID specialists and future career choices. Method: This cross-sectional descriptive study was conducted in March 2021 and targeted 717 medical students belonging to Medical School of Okayama University, Japan. The questionnaire consisted of four questions meant to assess students' knowledge and future intentions of becoming ID specialists. Results: We obtained 328 eligible questionnaires (response rate: 45.7%). Of 227 (69.2%) students who were aware of ID specialists, 99 (43.6%) answered that they came to know about them only after the pandemic, 12 (3.7%) answered that their interest in being an ID specialist arose during the pandemic, while 36 (11.0%) responded that they would rather not become ID specialists. At the time of the survey, 5 students (1.5%) were aiming to become ID specialists. Conclusion: We observed a very low rate of interest to be an ID specialist among medical students. The experience of the pandemic does not seem to have influenced Japanese medical students to choose ID as a specialty for their careers. Continuous efforts to increase the number of ID specialists are necessary in Japan as a countermeasure against the coming pandemic. [ABSTRACT FROM AUTHOR]

At the time of the COVID-19 pandemic, providing access to data (properly optimised regarding personal data protection) plays a crucial role in providing the general public and media with up-to-date information. Open datasets also represent one of the means for evaluation of the pandemic on a global level. The primary aim of this paper is to describe the methodological and technical framework for publishing datasets describing characteristics related to the COVID-19 epidemic in the Czech Republic (epidemiology, hospital-based care, vaccination), including the use of these datasets in practice. Practical aspects and experience with data sharing are discussed. As a reaction to the epidemic situation, a new portal COVID-19: Current Situation in the Czech Republic (https://onemocneni-aktualne.mzcr.cz/covid-19) was developed and launched in March 2020 to provide a fully-fledged and trustworthy source of information for the public and media. The portal also contains a section for the publication of (i) public open datasets available for download in CSV and JSON formats and (ii) authorised-access-only section where the authorised persons can (through an online generated token) safely visualise or download regional datasets with aggregated data at the level of the individual municipalities and regions. The data are also provided to the local open data catalogue (covering only open data on healthcare, provided by the Ministry of Health) and to the National Catalogue of Open Data (covering all open data sets, provided by various authorities/publishers, and harversting all data from local catalogues). The datasets have been published in various authentication regimes and widely used by general public, scientists, public authorities and decision-makers. The total number of API calls since its launch in March 2020 to 15 December 2020 exceeded 13 million. The datasets have been adopted as an official and guaranteed source for outputs of third parties, including public authorities, non-governmental organisations, scientists and online news portals. Datasets currently published as open data meet the 3-star open data requirements, which makes them machine-readable and facilitates their further usage without restrictions. This is essential for making the data more easily understandable and usable for data consumers. In conjunction with the strategy of the MH in the field of data opening, additional datasets meeting the already implemented standards will be also released, both on COVID-19 related and unrelated topics. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic spread rapidly worldwide. On September 15, 2021, a total of 546,251 confirmed cases were recorded in Saudi Arabia alone. Saudi Arabia imposed various levels of lockdown and forced the community to implement social distancing. In this paper, we formulate a mathematical model to study the impact of these measures on COVID-19 spread. The model is analyzed qualitatively, producing two equilibrium points. The existence and stability of the COVID-19 free equilibrium and the endemic equilibrium depend on the control reproduction number, Rc. These results are in good agreement with the numerical experiments. Moreover, the model is fitted with actual data from the COVID-19 dashboard of the Saudi Ministry of Health. We divide the timeline from March 12, 2020, to September 23, 2020, into seven phases according to the varied applications of lockdown and social distancing. We then explore several scenarios to investigate the optimal application of these measures and address whether it is possible to rely solely on social distancing without imposing a lockdown. [ABSTRACT FROM AUTHOR]

People are obtaining more and more information from social media and other online sources, but the spread of misinformation can lead to social disruption. In particular, social networking services (SNSs) can easily spread information of uncertain authenticity and factuality. Although many studies have proposed methods that addressed how to suppress the spread of misinformation on SNSs, few works have examined the impact on society of diffusing both misinformation and its corrective information. This study models the effects of effort to reduce misinformation and the diffusion of corrective information on social disruption, and it clarifies these effects. With the aim of reducing the impact on social disruption, we show that not only misinformation but also corrective information can cause social disruption, and we clarify how to control the spread of the latter to limit its impact. We analyzed the misinformation about a toilet-paper shortage and its correction as well as the social disruption this event caused in Japan during the COVID-19 pandemic in 2020. First, (1) we analyzed the extent to which misinformation and its corrections spread on SNS, and then (2) we created a model to estimate the impact of misinformation and its corrections on the world. Finally, (3) We used our model to analyze the change in this impact when the diffusion of the misinformation and its corrections changed. Based on our analysis results in (1), the corrective information spread much more widely than the misinformation. From the model developed in (2), the corrective information caused excessive purchasing behavior. The analysis results in (3) show that the amount of corrective information required to minimize the societal impact depends on the amount of misinformation diffusion. Most previous studies concentrated on the impact of corrective information on attitudes toward misinformation. On the other hand, the most significant contribution of this study is that it focuses on the impact of corrective information on society and clarifies the appropriate amount of it. [ABSTRACT FROM AUTHOR]

This paper examines whether the COVID-19-induced employment shocks are associated with increases in suicides and safety net use in the second and third quarters of 2020. We exploit plausibly exogenous regional variation in the magnitude of the employment shocks in Japan and adopt a difference-in-differences research design to examine and control for possible confounders. Our preferred point estimates suggest that a one-percentage-point increase in the unemployment rate in the second quarter of 2020 is associated with, approximately, an additional 0.52 suicides, 28 unemployment benefit recipients, 88 recipients of a temporary loan program, and 10 recipients of public assistance per 100,000 population per month. A simple calculation based on these estimates suggests that if a region experienced a one-percentage-point increase in the unemployment rate caused by the COVID-19 crisis in the second quarter of 2020, which is roughly equivalent to the third-highest regional employment shock, this would be associated with 37.4%, 60.5%, and 26.5% increases in the total, female, and male suicide rates respectively in July 2020 compared with July 2019. These results are primarily correlational rather than causal due to the limitation of our data and research design, but our baseline findings are robust to several different model specifications. [ABSTRACT FROM AUTHOR]

Taking place annually in more than 400 cities, European Researchers' Night is a pan- European synchronized event that aims to bring researchers closer to the public. In this paper audience profiles are compared from events in 2019 and 2020. In 2019, face-to-face events reached an estimated 1.6 million attendees, while in 2020, events shifted online due to the COVID-19 pandemic and reached an estimated 2.3 million attendees. Focusing on social inclusion metrics, survey data is analyzed across two national contexts (Ireland and Malta) in 2019 (n = 656) and 2020 (n = 506). The results from this exploratory, descriptive study shed light on how moving public engagement with research online shifted audience profiles. Based on prior research about the digital divide in access and use of online media, hypotheses were proposed that online European Researchers' Night events would attract audiences with higher educational attainment levels and greater self-reported, subjective economic well-being. While changes were observed from 2019 to 2020, results for each hypothesis show a mixed picture. The first hypothesis was upheld for the highest education levels but failed for the lowest levels suggesting that the pivot to online events simultaneously attracted participants with no formal education and those with postgraduate qualifications, while attracting less of those with undergraduate or lower levels of education. The second hypothesis was not upheld, with online European Researchers' Night events attracting audiences with slightly higher levels of economic well-being compared to face-to-face events. The findings of this study indicate that European Researchers' Night events present a clear opportunity to measure the effects of the digital divide in relation to public engagement with research across Europe. [ABSTRACT FROM AUTHOR]

The pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) took the world by surprise. Following the first outbreak of COVID-19 in December 2019, several models have been developed to study and understand its transmission dynamics. Although the spread of COVID-19 is being slowed down by vaccination and other interventions, there is still a need to have a clear understanding of the evolution of the pandemic across countries, states and communities. To this end, there is a need to have a clearer picture of the initial spread of the disease in different regions. In this project, we used a simple SEIR model and a Bayesian inference framework to estimate the basic reproduction number of COVID-19 across Africa. Our estimates vary between 1.98 (Sudan) and 9.66 (Mauritius), with a median of 3.67 (90% CrI: 3.31–4.12). The estimates provided in this paper will help to inform COVID-19 modeling in the respective countries/regions. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic is bringing disruptive effects on the healthcare systems, economy and social life of countries all over the world. Even though the elder portion of the population is the most severely affected by the COVID-19 disease, the counter-measures introduced so far by governments took into little account the age structure, with restrictions that act uniformly on the population irrespectively of age. In this paper, we introduce a SIRD model with age classes for studying the impact on the epidemic evolution of lockdown policies applied heterogeneously on the different age groups of the population. The proposed model is then applied to age-stratified COVID-19 Italian data. The simulation results suggest that control measures focused to specific age groups may bring benefits in terms of reduction of the overall mortality rate. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has been damaging to the lives of people all around the world. Accompanied by the pandemic is an infodemic, an abundant and uncontrolled spread of potentially harmful misinformation. The infodemic may severely change the pandemic's course by interfering with public health interventions such as wearing masks, social distancing, and vaccination. In particular, the impact of the infodemic on vaccination is critical because it holds the key to reverting to pre-pandemic normalcy. This paper presents findings from a global survey on the extent of worldwide exposure to the COVID-19 infodemic, assesses different populations' susceptibility to false claims, and analyzes its association with vaccine acceptance. Based on responses gathered from over 18,400 individuals from 40 countries, we find a strong association between perceived believability of COVID-19 misinformation and vaccination hesitancy. Our study shows that only half of the online users exposed to rumors might have seen corresponding fact-checked information. Moreover, depending on the country, between 6% and 37% of individuals considered these rumors believable. A key finding of this research is that poorer regions were more susceptible to encountering and believing COVID-19 misinformation; countries with lower gross domestic product (GDP) per capita showed a substantially higher prevalence of misinformation. We discuss implications of our findings to public campaigns that proactively spread accurate information to countries that are more susceptible to the infodemic. We also defend that fact-checking platforms should prioritize claims that not only have wide exposure but are also perceived to be believable. Our findings give insights into how to successfully handle risk communication during the initial phase of a future pandemic. [ABSTRACT FROM AUTHOR]

Fitting Susceptible-Infected-Recovered (SIR) models to incidence data is problematic when not all infected individuals are reported. Assuming an underlying SIR model with general but known distribution for the time to recovery, this paper derives the implied differential-integral equations for observed incidence data when a fixed fraction of newly infected individuals are not observed. The parameters of the resulting system of differential equations are identifiable. Using these differential equations, we develop a stochastic model for the conditional distribution of current disease incidence given the entire past history of reported cases. We estimate the model parameters using Bayesian Markov Chain Monte-Carlo sampling of the posterior distribution. We use our model to estimate the transmission rate and fraction of asymptomatic individuals for the current Coronavirus 2019 outbreak in eight American Countries: the United States of America, Brazil, Mexico, Argentina, Chile, Colombia, Peru, and Panama, from January 2020 to May 2021. Our analysis reveals that the fraction of reported cases varies across all countries. For example, the reported incidence fraction for the United States of America varies from 0.3 to 0.6, while for Brazil it varies from 0.2 to 0.4. [ABSTRACT FROM AUTHOR]

This paper proposes some high-ordered integer-valued auto-regressive time series process of order p (INAR(p)) with Zero-Inflated and Poisson-mixtures innovation distributions, wherein the predictor functions in these mentioned distributions allow for covariate specification, in particular, time-dependent covariates. The proposed time series structures are tested suitable to model the SARs-CoV-2 series in Mauritius which demonstrates excess zeros and hence significant over-dispersion with non-stationary trend. In addition, the INAR models allow the assessment of possible causes of COVID-19 in Mauritius. The results illustrate that the event of Vaccination and COVID-19 Stringency index are the most influential factors that can reduce the locally acquired COVID-19 cases and ultimately, the associated death cases. Moreover, the INAR(7) with Zero-inflated Negative Binomial innovations provides the best fitting and reliable Root Mean Square Errors, based on some short term forecasts. Undeniably, these information will hugely be useful to Mauritian authorities for implementation of comprehensive policies. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 epidemic in Italy has severely affected people aged more than 80, especially socially isolated. Aim of this paper is to assess whether a social and health program reduced mortality associated to the epidemic. Methods: An observational retrospective cohort analysis of deaths recorded among >80 years in three Italian cities has been carried out to compare death rate of the general population and "Long Live the Elderly!" (LLE) program. Parametric and non-parametric tests have been performed to assess differences of means between the two populations. A multivariable analysis to assess the impact of covariates on weekly mortality has been carried out by setting up a linear mixed model. Results: The total number of services delivered to the LLE population (including phone calls and home visits) was 34,528, 1 every 20 day per person on average, one every 15 days during March and April. From January to April 2019, the same population received one service every 41 days on average, without differences between January-February and March-April. The January-April 2020 cumulative crude death rate was 34.8‰ (9,718 deaths out of 279,249 individuals; CI95%: 34.1–35.5) and 28.9‰ (166 deaths out of 5,727 individuals; CI95%:24.7–33.7) for the general population and the LLE sample respectively. The general population weekly death rate increased after the 11th calendar week that was not the case among the LLE program participants (p<0.001). The Standardized Mortality Ratio was 0.83; (CI95%: 0.71–0.97). Mortality adjusted for age, gender, COVID-19 weekly incidence and prevalence of people living in nursing homes was lower in the LLE program than in the general population (p<0.001). Conclusions: LLE program is likely to limit mortality associated with COVID-19. Further studies are needed to establish whether it is due to the impact of social care that allows a better clients' adherence to the recommendations of physical distancing or to an improved surveillance of older adults that prevents negative outcomes associated with COVID-19. [ABSTRACT FROM AUTHOR]

Aim/Goal/Purpose: Population surveys underrepresent people with severe mental ill health. This paper aims to use multiple regression analyses to explore perceived social support, loneliness and factor associations from self-report survey data collected during the Covid-19 pandemic in a sample of individuals with severe mental ill health. Design/Methodology/Approach: We sampled an already existing cohort of people with severe mental ill health. Researchers contacted participants by phone or by post to invite them to take part in a survey about how the pandemic restrictions had impacted health, Covid-19 experiences, perceived social support, employment and loneliness. Loneliness was measured by the three item UCLA loneliness scale. Findings: In the pandemic sub-cohort, 367 adults with a severe mental ill health diagnosis completed a remote survey. 29–34% of participants reported being lonely. Loneliness was associated with being younger in age (adjusted OR = -.98, p =.02), living alone (adjusted OR = 2.04, p =.01), high levels of social and economic deprivation (adjusted OR = 2.49, p =.04), and lower perceived social support (B = -5.86, p <.001). Living alone was associated with lower perceived social support. Being lonely was associated with a self-reported deterioration in mental health during the pandemic (adjusted OR = 3.46, 95%CI 2.03–5.91). Practical implications: Intervention strategies to tackle loneliness in the severe mental ill health population are needed. Further research is needed to follow-up the severe mental ill health population after pandemic restrictions are lifted to understand perceived social support and loneliness trends. Originality: Loneliness was a substantial problem for the severe mental ill health population before the Covid-19 pandemic but there is limited evidence to understand perceived social support and loneliness trends during the pandemic. [ABSTRACT FROM AUTHOR]

Higher education students' mental health has been a growing concern in recent years even before the COVID-19 pandemic. The stresses and restrictions associated with the pandemic have put university students at greater risk of developing mental health issues, which may significantly impair their academic success, social interactions and their future career and personal opportunities. This paper aimed to understand the mental health status of University students at an early stage in the pandemic and to investigate factors associated with higher levels of distress. An online survey including demographics, lifestyle/living situations, brief mental well-being history, questions relating to COVID-19 and standardised measures of depression, anxiety, resilience and quality of life was completed by 1173 students at one University in the North of England. We found high levels of anxiety and depression, with more than 50% experiencing levels above the clinical cut offs, and females scoring significantly higher than males. The survey also suggested relatively low levels of resilience which we attribute to restrictions and isolation which reduced the opportunities to engage in helpful coping strategies and activities rather than enduring personality characteristics. Higher levels of distress were associated with lower levels of exercising, higher levels of tobacco use, and a number of life events associated with the pandemic and lockdown, such as cancelled events, worsening in personal relationships and financial concerns. We discuss the importance of longer-term monitoring and mental health support for university students. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, US public land managers faced the challenge of catering to large increases in camping demand, while maintaining social distancing guidelines. In this paper, we use multivariate linear regression to analyze weekly changes in reservations to US Forest Service (USFS) campgrounds between 2019 and 2020. The regression models estimate the impact of local COVID infection rates, public health restrictions, and spatial spillovers from proximity to National Parks (NPs), metropolitan areas and wildfire on camping demand. Our sample includes 1,688 individual USFS campgrounds from across the contiguous US. The results illustrate the dramatic increases in camping on USFS land that occurred in the summer of 2020 and demonstrate that increases in local infection rates led to significant increases in camping nights reserved in the summer. The results also illustrate that the increase in camping nights reserved at USFS campgrounds was particularly dramatic for campgrounds located near large metropolitan areas and near NPs that saw increases in overall recreational visits. These results point to the important role that public lands played during the pandemic and can help guide public land resource allocations for campground maintenance and operation. [ABSTRACT FROM AUTHOR]

The COVID Pandemic may affect fertility behaviour and intentions in many ways. Restrictions on service provision reduce access to family planning services and increase fertility in the short term. By contrast, the economic uncertainty brought about by the pandemic and its impact on mental health and well-being may reduce fertility. These various pathways have been explored in the context of high income countries such as the United States and Western Europe, but little is known about middle income countries. In this paper we asses the impact of the COVID pandemic on fertility intentions and behaviour in the Republic of Moldova, a middle income country in Eastern Europe, using the Generations and Gender Survey. This survey was conducted partially before and partially after the onset of the pandemic in 2020, allowing for detailed comparisons of individual circumstances. The results indicate that the pandemic reduced the used of intrauterine devices, and increased the use of male condoms, but with no overall decrease in contraceptive use. Conversely individuals interviewed after the onset of the pandemic were 34.5% less likely to be trying to conceive, although medium term fertility intentions were unchanged. Indicators therefore suggest that in the medium term fertility intentions may not be affected by the pandemic but restricted access to contraception requiring medical consultation and a decrease in short-term fertility intentions could disrupt short term family planning. [ABSTRACT FROM AUTHOR]

Vaccine rejection is a problem severely impacting the global society, especially considering the COVID-19 outbreak. The need to understand the psychological mechanisms underlying the active involvement of the pro-vaccine and anti-vaccine movements is therefore very important both from a theoretical and practical perspective. This paper investigates the group identities of people with positive and negative attitudes towards vaccination, and their attitudes toward general science. A targeted sample study of 192 pro-vaccine and 156 anti-vaccine group members showed that the group identity of pro-vaccine individuals is higher than of anti-vaccine individuals. and that both pro-vaccine and anti-vaccine individuals had a positive attitude toward science. Results are discussed in context of the heterogeneity of motivations causing vaccine rejection and the relation between active involvement in online discussion and group identity. [ABSTRACT FROM AUTHOR]

Introduction: The COVID-19 pandemic has caused widespread disruptions including to health services. In the early response to the pandemic many countries restricted population movements and some health services were suspended or limited. In late 2020 and early 2021 some countries re-imposed restrictions. Health authorities need to balance the potential harms of additional SARS-CoV-2 transmission due to contacts associated with health services against the benefits of those services, including fewer new HIV infections and deaths. This paper examines these trade-offs for select HIV services. Methods: We used four HIV simulation models (Goals, HIV Synthesis, Optima HIV and EMOD) to estimate the benefits of continuing HIV services in terms of fewer new HIV infections and deaths. We used three COVID-19 transmission models (Covasim, Cooper/Smith and a simple contact model) to estimate the additional deaths due to SARS-CoV-2 transmission among health workers and clients. We examined four HIV services: voluntary medical male circumcision, HIV diagnostic testing, viral load testing and programs to prevent mother-to-child transmission. We compared COVID-19 deaths in 2020 and 2021 with HIV deaths occurring now and over the next 50 years discounted to present value. The models were applied to countries with a range of HIV and COVID-19 epidemics. Results: Maintaining these HIV services could lead to additional COVID-19 deaths of 0.002 to 0.15 per 10,000 clients. HIV-related deaths averted are estimated to be much larger, 19–146 discounted deaths per 10,000 clients. Discussion: While there is some additional short-term risk of SARS-CoV-2 transmission associated with providing HIV services, the risk of additional COVID-19 deaths is at least 100 times less than the HIV deaths averted by those services. Ministries of Health need to take into account many factors in deciding when and how to offer essential health services during the COVID-19 pandemic. This work shows that the benefits of continuing key HIV services are far larger than the risks of additional SARS-CoV-2 transmission. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic has highlighted the importance of citizens' behaviors in the containment of the virus. Individuals might change their intention to adhere to public health prescriptions depending on various personal characteristics, including their own emotional status, which has been recognized to be a crucial psychological factor in orienting people's adherence to public health recommendation during emergency settings. In particular, it is crucial to support citizens' alliance with authorities and feeling of trust: public engagement is a concept that refers to the general involvement of citizens into public affairs which is generally considered an effective approach to enhance citizens' understanding of their crucial role in public affairs. However, so far there is no agreement on the metrics and indexes that should be used to measures public engagement during a health crisis. The aim of this paper is to validate a psychometric scale (PHEs-E), which intends to measure the readiness of individuals to adhere to the prescribed behavioral change to contain the emergency. Data were collected throughout the pandemic in Italy: in particular, five independent samples were recruited starting from March 2020 to March 2021. Results showed that the proposed measure has good psychometric characteristics. A general linear model was computed to assess the differences of public engagement across the different data points and among citizens with different sociodemographic characteristics. Correlations with other psychological constructs (i.e. Anxiety, Depression and Self-Efficacy) were also tested, showing that more engaged citizens have a lower level of anxiety and depression, and a higher self-efficacy. This study's findings indicate that individuals' characteristics may differentiate citizens' motivation to engage in public health behavioral recommendation to prevent the COVID-19 contagion. However the scale could be useful to perform a psychological monitoring of psychological readiness to engage in public health strategies to face critical events and settings. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AMR) is a global public health crisis that is now impacted by the COVID-19 pandemic. Little is known how COVID-19 risks influence people to consume antibiotics, particularly in contexts like Bangladesh where these pharmaceuticals can be purchased without a prescription. This paper identifies the social drivers of antibiotics use among home-based patients who have tested positive with SARS-CoV-2 or have COVID-19-like symptoms. Using qualitative telephone interviews, the research was conducted in two Bangladesh cities with 40 participants who reported that they had tested positive for coronavirus (n = 20) or had COVID-19-like symptoms (n = 20). Our analysis identified five themes in antibiotic use narratives: antibiotics as 'big' medicine; managing anxiety; dealing with social repercussions of COVID-19 infection; lack of access to COVID-19 testing and healthcare services; and informal sources of treatment advice. Antibiotics were seen to solve physical and social aspects of COVID-19 infection, with urgent ramifications for AMR in Bangladesh and more general implications for global efforts to mitigate AMR. [ABSTRACT FROM AUTHOR]

In this paper we analyze panel data (N = 400) to investigate the change in attitudes towards the Covid-19 measures and the change in compliance behavior between the first and second lockdowns in a sample of young adults from the University of Bern, Switzerland. We find considerable fatigue. While respondents expressed high acceptance of and compliance with the Covid-19 measures during the first lockdown, both acceptance and compliance behavior decreased substantially during the second lockdown. Moreover, we show via a structural equation model that respondents' compliance behavior is largely driven by the perception of how others behave and by the acceptance of the Covid-19 measures. All other effects scrutinized e.g., individual and social risk perception, trust in politics, and pro-social orientations affect compliance behavior via the acceptance of Covid-19 measures. We also conduct two tests of causality of the estimated relation between attitudes towards the measures and social distancing behavior. The first test incorporates the effect of compliance behavior reported during the first lockdown on attitudes during the second lockdown. The second test involves estimating a first difference panel regression model of attitudes on compliance behavior. The results of both tests suggest that the effect of Covid-19 attitudes on social distancing behavior can be interpreted causally. [ABSTRACT FROM AUTHOR]