The Science of Social Distancing and Total Lock Down: Does it Work? Whom does it Benefit?

The impact of COVID-19 lockdowns on mental health patient populations in the United States

During the start of the COVID-19 pandemic in 2020, lockdowns and movement restrictions were thought to negatively impact population mental health, since depression and anxiety symptoms were frequently reported. This study investigates the effect of COVID-19 mitigation measures on mental health across the United States, at county and state levels using difference-in-differences analysis. It examines the effect on mental health facility usage and the prevalence of mental illnesses, drawing on large-scale medical claims data for mental health patients joined with publicly available state- and county-specific COVID-19 cases and lockdown information. For consistency, the main focus is on two types of social distancing policies, stay-at-home and school closure orders. Results show that lockdown has significantly and causally increased the usage of mental health facilities in regions with lockdowns in comparison to regions without such lockdowns. Particularly, resource usage increased by 18% in regions with a lockdown compared to 1% decline in regions without a lockdown. Also, female populations have been exposed to a larger lockdown effect on their mental health. Diagnosis of panic disorders and reaction to severe stress significantly increased by the lockdown. Mental health was more sensitive to lockdowns than to the presence of the pandemic itself. The effects of the lockdown increased over an extended time to the end of December 2020.

Extending the theory of planned behavior to envisage social distancing behavior in containing the COVID-19 outbreak

The study investigates the antecedents that influence social distancing behavior during the COVID-19 outbreak and develops a hypothetical model integrating additional pertinent variables into the classic theory of planned behavior (TPB) to grasp the social distancing behavior accurately. The extended model was investigated employing structural equation modeling using the data collected through Snowball Technology from 331 respondents. The results unearth significant influences of all the predictor variables on their outcome variables. Surprisingly, the supportive government strategy has no crucial impact on perceived behavioral control toward social distancing. Furthermore, the study reports no trivial difference between young and old and high-low income groups on the intention-actual social distancing. The study outlines policy interventions to prevent mass transmission of the COVID-19 catastrophe. Lastly, limitations are specified to open up novel insights for future researchers.

Spatial analysis and optimization of self-pickup points of a new retail model in the Post-Epidemic Era: the case of Community-Group-Buying in Xi’an City

The Community-Group-Buying Points (CGBPs) flourished during COVID-19, safeguarding the daily lives of community residents in community lockdowns, and continuing to serve as a popular daily shopping channel in the Post-Epidemic Era with its advantages of low price, convenience and neighborhood trust. These CGBPs are allocated on location preferences however spatial distribution is not equal. Therefore, in this study, we used point of interest (POI) data of 2,433 CGBPs to analyze spatial distribution, operation mode and accessibility of CGBPs in Xi’an city, China as well as proposed the location optimization model. The results showed that the CGBPs were spatially distributed as clusters at α = 0.01 (Moran’s I = 0.44). The CGBPs operation mode was divided into preparation, marketing, transportation, and self-pickup. Further CGBPs were mainly operating in the form of joint ventures, and the relying targets presented the characteristic of ‘convenience store-based and multi-type coexistence’. Influenced by urban planning, land use, and cultural relics protection regulations, they showed an elliptic distribution pattern with a small oblateness, and the density showed a low–high-low circular distribution pattern from the Palace of Tang Dynasty outwards. Furthermore, the number of communities, population density, GDP, and housing type were important driving factors of the spatial pattern of CGBPs. Finally, to maximize attendance, it was suggested to add 248 new CGBPs, retain 394 existing CGBPs, and replace the remaining CGBPs with farmers’ markets, mobile vendors, and supermarkets. The findings of this study would be beneficial to CGB companies in increasing the efficiency of self-pick-up facilities, to city planners in improving urban community-life cycle planning, and to policymakers in formulating relevant policies to balance the interests of stakeholders: CGB enterprises, residents, and vendors.

The impact of lockdown in Wuhan on residents confidence in controlling COVID-19 outbreak at the destination cities

Objective

From January 23rd, 2020, lock-down measures were adopted in Wuhan, China to stop the spread of COVID-19. However, due to the approach of the Spring Festival and the nature of COVID-19, more than 6 million permanent and temporary residents of Wuhan (who were potential carriers or spreaders of the virus), left the city before the lock-down measures were implemented. This study aims to explore whether and how the population inflow from Wuhan city impacted residents' confidence in controlling COVID-19 outbreaks at the destination cities.

Study design and setting

Based on questionnaire data and migration big data, a multiple regression model was developed to quantify the impact of the population inflow from Wuhan city on the sense of confidence of residents in controlling the COVID-19 outbreak at the destination cities. Scenarios were considered that varied residents' expected month for controlling COVID-19 outbreak at the destination cities, residents' confidence in controlling COVID-19 outbreak at the destination cities, and the overall indicators for the sense of confidence of residents in controlling COVID-19. A marginal effect analysis was also conducted to calculate the probability of change in residents' confidence in controlling the COVID-19 outbreak with per unit change in the population inflow from Wuhan city.

Results

The impact of population inflow from Wuhan city on residents' expected month for controlling COVID-19 outbreak at the destination cities was positive and significant at the 1% level, while that on residents' confidence in controlling COVID-19 at the destination cities was negative and significant at the 1% level. Robustness checks, which included modifying the sample range and replacing measurement indicators of the population inflow from Wuhan city, demonstrated these findings were robust and credible. When the population inflow from Wuhan city increased by one additional unit, the probabilities of the variables "February" and "March" decreased significantly by 0.1023 and 0.1602, respectively, while the probabilities of "April," "May," "June," "July," "before the end of 2020," and "unknown" significantly increased by 0.0470, 0.0856, 0.0333, 0.0080, 0.0046, and 0.0840, respectively. Similarly, when the population inflow from Wuhan city increased by one additional unit, the probability of the variable "extremely confident" decreased by 0.1973. Furthermore, the probabilities of the variables "confident," "neutral," and "unconfident" significantly increased by 0.1392, 0.0224, and 0.0320, respectively.

Conclusion

The population inflow from Wuhan city played a negative role in the sense of confidence of residents in controlling COVID-19 in the destination cities. The higher the population inflow from Wuhan city, the longer the residents' expected month for controlling COVID-19 outbreak at the destination cities became, and the weaker the residents' confidence in controlling the COVID-19 outbreak at the destination cities.

Human Activity Changes During COVID-19 Lockdown in China-A View From Nighttime Light

Strict lockdowns were implemented in China to fight Coronavirus Disease 2019 (COVID-19). We explored the nighttime light (NTL) of China's four cities in five stages of COVID-19 including case free period, newly appeared period, rising period, outbreak period, and stationary period. Using six categories of points of interest data ("company," "recreation," "healthcare," "residence," "shopping," and "traffic facility") and random forest models, we found that dimming light of four cities is associated with the epidemic development and human activity changes. When confirmed cases appeared, healthcare associated NTL radiance increased rapidly in Wuhan and Guangzhou, but decreased in the fourth and fifth stages. Companies in all cities were resuscitated in the fifth stage, while companies in Guangzhou was resuscitated in the fourth stage. Shopping related NTL radiance in Wuhan increased quickly in the fifth stage which indicated some resuscitation. In addition, compared to gross domestic product, the trend in electric power consumption was consistent with the trend in NTL radiance. The above findings contribute to the making of control policies for COVID-19 as well as other infectious diseases.

Public Compliance Matters in Evidence-Based Public Health Policy: Evidence from Evaluating Social Distancing in the First Wave of COVID-19

When the unprecedented COVID-19 pandemic first spread, governments could implement a wide range of measures to tackle the outbreaks. Conventional wisdom holds that public health policy should be made on the basis of empirical demonstrations, while little research has probed on how to safeguard the expected policy utility in the case of evidence shortage on novel contagious diseases. In particular, the fight against COVID-19 cannot succeed without public compliance as well as the support of people who have not tested positive. Based on the data from the first wave of COVID-19, by using a random effect estimator, fixed effect method, and hierarchical technique, we specified the efficiency of particular social distancing policies by contextualizing multiple factors. We found that adopting gathering restrictions decreased new case growth but were conditional on its interaction with population density, while mitigation effects constantly corresponded to policy magnitude in a given time; for which the effective patterns varied from three days to sixty days. Overall, policies encouraging social distancing exerted a positive effect on mitigating the first wave of COVID-19. Both the enforcing duration and public compliance constrained the expected impact of nonpharmaceutical intervention according to degrees of policy level. These findings suggest that, when evidence is incomplete, the effectiveness of public health crisis management depends on the combination of policy appropriateness and, accordingly, public compliance.

Original Research: Nurses' Experiences of Caring for Patients and Families During the COVID-19 Pandemic: Communication Challenges

OBJECTIVE

The purpose of this study was to gain a better understanding of the perceptions and experiences of nurses caring for patients and families under the COVID-19 pandemic's socially restrictive practices and policies.

BACKGROUND

The COVID-19 global pandemic has affected the delivery of health care to patients and their families, with many aspects altered because of the need for social distancing, social isolation, and visitation restriction policies. These policies have created communication challenges for interdisciplinary health care teams, patients, and families. As frontline caregivers, nurses have felt strongly the impact of these challenges.

METHODS

A qualitative descriptive study was conducted among 17 RNs who were caring for patients during the COVID-19 pandemic and were recruited via social media posts on Facebook, Twitter, and LinkedIn. Watson's theory of human caring served as the conceptual framework for the study.

RESULTS

Several themes emerged regarding nurses' experiences of communication with patients and families. These include communication challenges and barriers, prioritization, integration of group communication, nurse self-reflection, and acceptance of gratitude.

CONCLUSIONS

The study findings underscore the importance of nurses' communication with patients and families under the pandemic's restricted conditions. They demonstrate the value of nurses' ability to innovate in fostering all parties' participation in the plan of care, and highlight the comfort nurses provide to patients who are isolated from loved ones. Strategies that fostered communication were identified, as were areas for further research.

Risk assessment for COVID-19 transmission at household level in sub-Saharan Africa: evidence from DHS

Household habitat conditions matter for diseases transmission and control, especially in the case of the novel coronavirus (COVID-19). These conditions include availability and adequacy of sanitation facilities, and number of persons per room. Despite this, little attention is being paid to these conditions as a pathway to understanding the transmission and prevention of COVID-19, especially in Africa, where household habitat conditions are largely suboptimal. This study assesses household sanitation and isolation capacities to understand the COVID-19 transmission risk at household level across Africa. We conducted a secondary analysis of the Demographic and Health Surveys of 16 African countries implemented between 2015 and 2018 to understand the status of households for prevention of COVID-19 transmission in home. We assessed handwashing capacity and self-isolation capacity using multiple parameters, and identified households with elderly persons, who are most at risk of the disease. We fitted two-level random intercept logit models to explore independent relationships among the three indicators, while controlling for the selected explanatory variables. Handwashing capacity was highest in Tanzania (48.2%), and lowest in Chad (4.2%), varying by household location (urban or rural), as well as household wealth. Isolation capacity was highest in South Africa (77.4%), and lowest in Ethiopia (30.9%). Senegal had the largest proportion of households with an elderly person (42.1%), while Angola (16.4%) had the lowest. There were strong, independent relationships between handwashing and isolation capacities in a majority of countries. Also, strong associations were found between isolation capacity and presence of older persons in households. Household capacity for COVID-19 prevention varied significantly across countries, with those having elderly household members not necessarily having the best handwashing or isolation capacity. In view of the age risk factors of COVID-19 transmission, and its dependence on handwashing and isolation capacities of households, each country needs to use the extant information on its risk status to shape communication and intervention strategies that will help limit the impact of the disease in its population across Africa.

A new SEAIRD pandemic prediction model with clinical and epidemiological data analysis on COVID-19 outbreak

Measuring the spread of disease during a pandemic is critically important for accurately and promptly applying various lockdown strategies, so to prevent the collapse of the medical system. The latest pandemic of COVID-19 that hits the world death tolls and economy loss very hard, is more complex and contagious than its precedent diseases. The complexity comes mostly from the emergence of asymptomatic patients and relapse of the recovered patients which were not commonly seen during SARS outbreaks. These new characteristics pertaining to COVID-19 were only discovered lately, adding a level of uncertainty to the traditional SEIR models. The contribution of this paper is that for the COVID-19 epidemic, which is infectious in both the incubation period and the onset period, we use neural networks to learn from the actual data of the epidemic to obtain optimal parameters, thereby establishing a nonlinear, self-adaptive dynamic coefficient infectious disease prediction model. On the basis of prediction, we considered control measures and simulated the effects of different control measures and different strengths of the control measures. The epidemic control is predicted as a continuous change process, and the epidemic development and control are integrated to simulate and forecast. Decision-making departments make optimal choices. The improved model is applied to simulate the COVID-19 epidemic in the United States, and by comparing the prediction results with the traditional SEIR model, SEAIRD model and adaptive SEAIRD model, it is found that the adaptive SEAIRD model's prediction results of the U.S. COVID-19 epidemic data are in good agreement with the actual epidemic curve. For example, from the prediction effect of these 3 different models on accumulative confirmed cases, in terms of goodness of fit, adaptive SEAIRD model (0.99997) ≈ SEAIRD model (0.98548) > Classical SEIR model (0.66837); in terms of error value: adaptive SEAIRD model (198.6563) < < SEAIRD model(4739.8577) < < Classical SEIR model (22,652.796); The objective of this contribution is mainly on extending the current spread prediction model. It incorporates extra compartments accounting for the new features of COVID-19, and fine-tunes the new model with neural network, in a bid of achieving a higher level of prediction accuracy. Based on the SEIR model of disease transmission, an adaptive model called SEAIRD with internal source and isolation intervention is proposed. It simulates the effects of the changing behaviour of the SARS-CoV-2 in U.S. Neural network is applied to achieve a better fit in SEAIRD. Unlike the SEIR model, the adaptive SEAIRD model embraces multi-group dynamics which lead to different evolutionary trends during the epidemic. Through the risk assessment indicators of the adaptive SEAIRD model, it is convenient to measure the severity of the epidemic situation for consideration of different preventive measures. Future scenarios are projected from the trends of various indicators by running the adaptive SEAIRD model.

Perceptions and experiences of the public regarding the COVID-19 pandemic in Nepal: a qualitative study using phenomenological analysis

OBJECTIVES

Perceptions of people regarding COVID-19 influences their health behaviour in terms of seeking public health services. This helps the government in planning appropriate public health strategies. Therefore, this study intends to explore the perceptions of people towards COVID-19 and their experiences during the pandemic in Nepal.

DESIGN, SETTING AND PARTICIPANTS

This qualitative study was conducted among the public in Kathmandu, Kanchanpur, Bajura and Jhapa districts of Nepal. Eight focus group discussions and 40 in-depth interviews were conducted by using a maximum variation sampling method.

RESULTS

The findings were organised into the following themes: General understanding of COVID-19, Disease prevention, Source of information and misconceptions, Expectation and challenges; and Personal and societal consequences of COVID-19, social distancing and lockdown. There was a good general understanding among respondents about COVID-19, personal preventive measures and population-level strategies. They responded that the use of masks, sanitisers, handwashing and proper lockdown would help to prevent the disease. The respondents acknowledged the vital role of media in increasing awareness. Participants also expressed concerns over the misleading news spread by some media. The lack of social interaction, isolation and loss of income were raised as pertinent issues by the participants as potentially leading to psychological consequences. Health workers and public both raised concerns over inadequate Personal Protective Equipment, under-prepared health system, unorganised public quarantine centres, and public violation of lockdown CONCLUSIONS: This study reports participants' views on disease prevention measures such as maintaining personal hygiene, adhering to physical distancing, and using personal protective equipments. Additionally, it illuminates the confusion among public due to conflicting public health messages from different sources of information which was deemed as misleading by the participants. This research sheds light on people's perspectives and experiences that can inform population-targeted policies in the future.

Alzheimer's Disease and Face Masks in Times of COVID-19

Generalized lockdown caused by COVID-19, necessary yesterday, can no longer be that of tomorrow. It will no longer be possible to cram the humblest into cramped areas, but priority must be given to prevention (certainly with physical barriers, hydro-alcoholic gel, face masks), biological diagnosis, isolation, and also the care of any infected person. COVID-19 has hit the most vulnerable first in terms of biological inequality, such as Alzheimer's disease (AD) patients. Those with AD can have sensorial deficits and perception troubles, including visual difficulties and the inability to recognize faces and emotions. Face masks and physical distancing can disrupt facial familiarity and make it more difficult to recognize emotional facial expressions. It can provoke distress, which the visitor can perceive and feel obligated to take off the face mask. This gesture should not be considered as an act of indiscipline, but an act of empathy. Transparent face masks could improve the suffering of AD patients, distraught in the presence of their loved ones whose masks hide their faces. Wearing a mask should not be due to fear of punishment, but as an understanding of the responsibility of each individual in the control of the current pandemic. It may be necessary to convince more citizens of this civic duty, using clear and attractive messaging in order to standardize the wearing of face masks for the general public and to adapt them to the needs of patients.

Stopping the COVID-19 Pandemic: A Review on the Advances of Diagnosis, Treatment, and Control Measures

With the continued spread of COVID-19 across the world, rapid diagnostic tools, readily available respurposable drugs, and prompt containment measures to control the SARS-CoV-2 infection are of paramount importance. Examples of recent advances in diagnostic tests are CRISPR technology, IgG assay, spike protein detection, and use of artificial intelligence. The gold standard reverse transcription polymerase chain (RT-PCR) has also been upgraded with point-of-care rapid tests. Supportive treatment, mechanical ventilation, and extracorporeal membrane oxygenation (ECMO) remain the primary choice, while therapeutic options include antivirals, antiparasitics, anti-inflammatories, interferon, convalescent plasma, monoclonal antibody, hyperimmunoglobulin, RNAi, and mesenchymal stem cell therapy. Different types of vaccines such as RNA, DNA, and lentiviral, inactivated, and viral vector are in clinical trials. Moreover, rapidly deployable and easy-to-transport innovative vaccine delivery systems are also in development. As countries have started easing down on the lockdown measures, the chance for a second wave of infection demands strict and rational control policies to keep fatalities minimized. An improved understanding of the advances in diagnostic tools, treatments, vaccines, and control measures for COVID-19 can provide references for further research and aid better containment strategies.

The COVID-19 Contagion–Pandemic Dyad: A View from Social Sciences

The objective of this concept paper focuses on the relevance of the analytical potential of Social Sciences for understanding the multiple implications and challenges posed by the COVID-19 contagion–pandemic dyad. This pandemic is generating a global threat with a high number of deaths and infected individuals, triggering enormous pressure on health systems. Most countries have put in place a set of procedures based on social distancing, as well as (preventive) isolation from possible infected and transmitters of the disease. This crisis has profound implications and raises issues for which the contribution of Social Sciences does not seem to be sufficiently mobilised. The contribution of Social Sciences is paramount, in terms of their knowledge and skills, to the knowledge of these problematic realities and to act in an informed way on these crises. Social Sciences are a scientific project focused on interdisciplinarity, theoretical and methodological plurality. This discussion is developed from the systems of relationships between social phenomena in the coordinates of time and place, and in the socio-historical contexts in which they are integrated. A pandemic is a complex phenomenon as it is always a point of articulation between natural and social determinations. The space of the discourse on the COVID-19 pandemic can be understood as the expression of a coalition of discourses, i.e., the interaction of various discourses, combined in re-interpretative modalities of certain realities and social phenomena. The circumstantial coalitions of interests, which shape the different discursive records and actions produced by different agents of distinct social spaces, enable the acknowledgement and legitimation of this pandemic threat and danger, and the promotion of its public management.

Impacts of COVID-19 on a Transitioning Energy System, Society, and International Cooperation

Short term outcomes of the COVID-19 pandemic have included improved air quality and reduced carbon dioxide (CO2) and other greenhouse gas emissions, while long term repercussions may include a disruption to joint international research efforts, the creation of silos, and the potential for internalizing efforts toward national rather than global goals. In this study, we identified the impacts of reduced mobility on pollutants and emissions, the emergence of nationalist approaches and effects on international cooperation, and how these issues will affect the achievement of global carbon targets and the Sustainable Development Goals (SDGs). COVID-19 presents a global short-term crisis and there is a demonstrated global desire and effort to develop a vaccine and effective treatments. Similarly, climate change is also a near future issue, and as a result we need to reduce CO2 emissions rapidly. This review highlights potential policy interventions, which capitalize on learnings from COVID-19, while identifying SDGs 10, 13 and 17 as critical to engendering a successful, cooperative transition toward sustainability. The recognition of the earth as a closed system, demonstrated by the shared impacts of the COVID-19 crisis, may encourage positive future effects on cooperative approaches toward mitigating climate change, another looming crisis for humanity.

Estimating the impacts of lockdown on Covid-19 cases in Nigeria

The study examines the extent to which lockdown measures impact on COVID-19 confirmed cases in Nigeria. Six indicators of lockdown entailing retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residential, are considered. The empirical evidence is anchored on the negative binomial regression estimator, due to the count nature of the dataset on the daily cases of the virus. The study established the key following findings: First, retail and recreation, grocery and pharmacy, parks, transit stations, and workplaces are statistically significant and negatively signed as relevant predictors of the virus. Second, the impact of residential is positive and statistically significant at the conventional level. Lastly, the results are robust to an alternative estimator of Poisson Regression. The emanated policy message centres on the need to direct efforts toward ensuring total compliance to the lockdown rules as it holds the key to keeping the virus under check.