Intracounty modeling of COVID-19 infection with human mobility: Assessing spatial heterogeneity with business traffic, age, and race.

The COVID-19 pandemic is a global threat presenting health, economic, and social challenges that continue to escalate. Metapopulation epidemic modeling studies in the susceptible-exposed-infectious-removed (SEIR) style have played important roles in informing public health policy making to mitigate the spread of COVID-19. These models typically rely on a key assumption on the homogeneity of the population. This assumption certainly cannot be expected to hold true in real situations; various geographic, socioeconomic, and cultural environments affect the behaviors that drive the spread of COVID-19 in different communities. What's more, variation of intracounty environments creates spatial heterogeneity of transmission in different regions. To address this issue, we develop a human mobility flow-augmented stochastic SEIR-style epidemic modeling framework with the ability to distinguish different regions and their corresponding behaviors. This modeling framework is then combined with data assimilation and machine learning techniques to reconstruct the historical growth trajectories of COVID-19 confirmed cases in two counties in Wisconsin. The associations between the spread of COVID-19 and business foot traffic, race and ethnicity, and age structure are then investigated. The results reveal that, in a college town (Dane County), the most important heterogeneity is age structure, while, in a large city area (Milwaukee County), racial and ethnic heterogeneity becomes more apparent. Scenario studies further indicate a strong response of the spread rate to various reopening policies, which suggests that policy makers may need to take these heterogeneities into account very carefully when designing policies for mitigating the ongoing spread of COVID-19 and reopening.

How National Culture Influences the Speed of COVID-19 Spread: Three Cross-Cultural Studies.

The COVID-19 pandemic has affected 222 countries and territories around the globe. Notably, the speed of COVID-19 spread varies significantly across countries. This cross-cultural research proposes and empirically examines how national culture influences the speed of COVID-19 spread in three studies. Study 1 examines the effects of Hofstede's national cultural dimensions on the speed of COVID-19 spread in 60 countries. Drawing on the GLOBE study (House et al., 2004), Study 2 investigates how GLOBE cultural dimensions relate to the speed of the pandemic's spread in 55 countries. Study 3 examines the effect of cultural tightness in 31 countries. We find that five national cultural dimensions - power distance, uncertainty avoidance, humane orientation, in-group collectivism, and cultural tightness - are significantly related to the speed of COVID-19 spread in the initial stages, but not in the later stages, of the pandemic. Study 1 shows that the coronavirus spreads faster in countries with small power distance and strong uncertainty avoidance. Study 2 supports these findings and further reveals that countries with low humane orientation and high in-group collectivism report a faster spread of the disease. Lastly, Study 3 shows that COVID-19 spreads slower in countries with high cultural tightness.

A global assessment of COVID-19 diffusion based on a single indicator: Some considerations about air pollution and COVID-19 spread.

The extraordinariness of COVID-19 occurred in a world that was completely unprepared to face it. To justify this, sometimes literature proposes positive associations between concentrations of some air pollutants and SARS-CoV-2 mortality and infectivity. However, several of these studies are affected by incomplete data analysis and/or incorrect accounts of spread dynamics that can be attributed to respiratory viruses. Based on separate analyses involving all the USA states and globally all the world countries suffering from the pandemic, this communication shows that commercial trade seems to be a good indicator of virus spread, being proposed as a surrogate of human-to-human interactions. The results of this study strongly support the conclusion that this new indicator could result fundamental to model (and avoid) possible future pandemics, strongly suggesting dedicated studies devoted to better investigate its significance.

A meta-analysis result: Uneven influences of season, geo-spatial scale and latitude on relationship between meteorological factors and the COVID-19 transmission.

Meteorological factors have been confirmed to affect the COVID-19 transmission, but current studied conclusions varied greatly. The underlying causes of the variance remain unclear. Here, we proposed two scientific questions: (1) whether meteorological factors have a consistent influence on virus transmission after combining all the data from the studies; (2) whether the impact of meteorological factors on the COVID-19 transmission can be influenced by season, geospatial scale and latitude. We employed a meta-analysis to address these two questions using results from 2813 published articles. Our results showed that, the influence of meteorological factors on the newly-confirmed COVID-19 cases varied greatly among existing studies, and no consistent conclusion can be drawn. After grouping outbreak time into cold and warm seasons, we found daily maximum and daily minimum temperatures have significant positive influences on the newly-confirmed COVID-19 cases in cold season, while significant negative influences in warm season. After dividing the scope of the outbreak into national and urban scales, relative humidity significantly inhibited the COVID-19 transmission at the national scale, but no effect on the urban scale. The negative impact of relative humidity, and the positive impacts of maximum temperatures and wind speed on the newly-confirmed COVID-19 cases increased with latitude. The relationship of maximum and minimum temperatures with the newly-confirmed COVID-19 cases were more susceptible to season, while relative humidity's relationship was more affected by latitude and geospatial scale. Our results suggested that relationship between meteorological factors and the COVID-19 transmission can be affected by season, geospatial scale and latitude. A rise in temperature would promote virus transmission in cold seasons. We suggested that the formulation and implementation of epidemic prevention and control should mainly refer to studies at the urban scale. The control measures should be developed according to local meteorological properties for individual city.

Addressing COVID-19 contagion through the HVAC systems by reviewing indoor airborne nature of infectious microbes: Will an innovative air recirculation concept provide a practical solution?

As the world continues to grapple with the reality of coronavirus disease, global research communities are racing to develop practical solutions to adjust to the new challenges. One such challenge is the control of indoor air quality in the COVID-19 era and beyond. Since COVID-19 became a global pandemic, the "super spread" of the virus has continued to amaze policymakers despite measures put in place by public health officials to sensitize the general public on the need for social distancing, personal hygiene, etc. In this work, we have reviewed the literature to demonstrate, by investigating the historical and present circumstances, that indoor spread of infectious diseases may be assisted by the conditions of the HVAC systems. While little consideration has been given to the possibility of indoor airborne transmission of the virus, the available reports have demonstrated that the virus, with average aerodynamic diameter up to 80-120 nm, is viable as aerosol in indoor atmosphere for more than 3 h, and its spread may be assisted by the HVAC systems. Having reviewed the vulnerability of the conventional ventilation systems, we recommend innovative air circulation concept supported by the use of UVGI in combination with nanoporous air filter to combat the spread of SARS-CoV-2 and other harmful microbes in enclosed spaces.

A data-driven model of the COVID-19 spread among interconnected populations: epidemiological and mobility aspects following the lockdown in Italy.

An epidemic multi-group model formed by interconnected SEIR-like structures is formulated and used for data fitting to gain insight into the COVID-19 dynamics and into the role of non-pharmaceutical control actions implemented to limit the infection spread since its outbreak in Italy. The single submodels provide a rather accurate description of the COVID-19 evolution in each subpopulation by an extended SEIR model including the class of asymptomatic infectives, which is recognized as a determinant for disease diffusion. The multi-group structure is specifically designed to investigate the effects of the inter-regional mobility restored at the end of the first strong lockdown in Italy (June 3, 2020). In its time-invariant version, the model is shown to enjoy some analytical stability properties which provide significant insights on the efficacy of the implemented control measurements. In order to highlight the impact of human mobility on the disease evolution in Italy between the first and second wave onset, the model is applied to fit real epidemiological data of three geographical macro-areas in the period March-October 2020, including the mass departure for summer holidays. The simulation results are in good agreement with the data, so that the model can represent a useful tool for predicting the effects of the combination of containment measures in triggering future pandemic scenarios. Particularly, the simulation shows that, although the unrestricted mobility alone appears to be insufficient to trigger the second wave, the human transfers were crucial to make uniform the spatial distribution of the infection throughout the country and, combined with the restart of the production, trade, and education activities, determined a time advance of the contagion increase since September 2020.

Understanding the Impact of Walkability, Population Density, and Population Size on COVID-19 Spread: A Pilot Study of the Early Contagion in the United States.

The novel coronavirus disease 2019 (COVID-19) pandemic is an unprecedented global event that has been challenging governments, health systems, and communities worldwide. Available data from the first months indicated varying patterns of the spread of COVID-19 within American cities, when the spread was faster in high-density and walkable cities such as New York than in low-density and car-oriented cities such as Los Angeles. Subsequent containment efforts, underlying population characteristics, variants, and other factors likely affected the spread significantly. However, this work investigates the hypothesis that urban configuration and associated spatial use patterns directly impact how the disease spreads and infects a population. It follows work that has shown how the spatial configuration of urban spaces impacts the social behavior of people moving through those spaces. It addresses the first 60 days of contagion (before containment measures were widely adopted and had time to affect spread) in 93 urban counties in the United States, considering population size, population density, walkability, here evaluated through walkscore, an indicator that measures the density of amenities, and, therefore, opportunities for population mixing, and the number of confirmed cases and deaths. Our findings indicate correlations between walkability, population density, and COVID-19 spreading patterns but no clear correlation between population size and the number of cases or deaths per 100 k habitants. Although virus spread beyond these initial cases may provide additional data for analysis, this study is an initial step in understanding the relationship between COVID-19 and urban configuration.

[TRANSFORMATION OF THE ACTIVITIES OF CHILDREN'S PUBLIC ORGANIZATIONS AND NEW OPPORTUNITIES TO WORK IN THE FACE OF THE COVID-19 THREAT].

The article is devoted to the study of the process of transformation of the activities of Russian children's public organizations in the face of the threat of the spread of coronavirus infection COVID-19 and the opening of new opportunities for non-profit organizations to work in this situation. The paper uses the results of a survey conducted from March 18 to 23, 2020 by experts of the Charitable Foundation for the Development of Philanthropy, which covered 232 organizations operating in the non-profit sector. The results of the study allowed us to conclude that the period of self-isolation contributed to the stimulation of children's public organizations to actively implement information technologies in their activities, find new opportunities for remote interaction in their work, and develop online projects.

[INSTABILITY OF SOCIAL AND LABOR RELATIONS AND EMPLOYMENT PROBLEMS DURING THE COVID-19 PANDEMIC].

The article is devoted to the analysis of the consequences in the social and labor sphere, which were caused by the outbreak of the coronavirus infection COVID-19. The changes in labor relations during the pandemic and the benefits of the new regulation norms of the remote work are investigated. The impact of working remotely on the social and labor sphere and the prospects for the development and implementation of effective remote mechanisms over the next ten years are analyzed. In a pandemic situation, remote work has proven to be an important factor for business ongoing activity, with benefits in the form of reduced commuting time, the ability to focus on work tasks away from distracting office aspects, and finding an optimal work-life balance. The study concluded that creating decent job opportunities is only possible with the appropriate socio-economic policies.

[PUBLIC MANAGEMENT DURING THE THREAT OF THE SPREAD OF COVID-19].

The article is devoted to the research of problems and tasks of state management under the conditions of threat of spread of coronavirus infection COVID-19 and consideration of approaches to optimization of processes in the system of state management. The social and economic risks of the pandemic are identified and the directions of anti-crisis measures are considered. Public administration is a system consisting of citizens, business structures and government employees. State authorities, while implementing the directions of public policy, must take into account the interests of all participants of the system, building the channels of interaction between them in the most effective way. The pandemic is a serious challenge to the state administration system of any country, the prevention of the consequences of which requires timely and effective measures to be taken. Under the conditions of the pandemic in Russia, as well as all over the world, the role of the state has significantly increased, both in terms of prevention of pandemic spread, and in the form of measures aimed at supporting citizens and businesses, the most affected spheres of the economy. The purpose of this work is to consider new approaches to optimize the processes in the system of public administration, caused by the need to revise the directions of state policy under the threat of the spread of COVID-19.

Deep learning models for forecasting and analyzing the implications of COVID-19 spread on some commodities markets volatilities.

Over the past few years, the application of deep learning models to finance has received much attention from investors and researchers. Our work continues this trend, presenting an application of a Deep learning model, long-term short-term memory (LSTM), for the forecasting of commodity prices. The obtained results predict with great accuracy the prices of commodities including crude oil price (98.2 price(88.2 on the variability of the commodity prices. This involved checking at the correlation and the causality with the Ganger Causality method. Our results reveal that the coronavirus impacts the recent variability of commodity prices through the number of confirmed cases and the total number of deaths. We then investigate a hybrid ARIMA-Wavelet model to forecast the coronavirus spread. This analyses is interesting as a consequence of the strong causal relationship between the coronavirus(number of confirmed cases) and the commodity prices, the prediction of the evolution of COVID-19 can be useful to anticipate the future direction of the commodity prices.

[The impact of the COVID-19 epidemic on the elderly mental health and psychosocial support.]

The spread of the COVID-19 epidemic is accompanied by psychosocial problems that have negative consequences for the mental health (MH) and quality of life (QoL) of the majority of the population. The elderly (65+ individuals) with chronic somatic diseases and reduced adaptation reserves are particularly at risk. In General, the epidemic highlighted the growing problems of psychosocial work with the 65+ cohort in the conditions of progressive aging of the population of many developed and developing countries. These problems are directly related to the preservation of MH and QoL of elderly people, people with disabilities, and others. Additional reserves should be sought to support these categories of individuals. In particular, the use of remote tele-consulting and assistive information technologies that enhance the communication capabilities of older persons is relevant. The article analyzes publications that offer practical recommendations for reducing the negative effects of the COVID-19 pandemic on MH and QoL in a cohort of 65+ individuals. As a starting point of the discussion, the article by A.G.Golubev et al., in which the issues of public support for 65+ persons are considered to be the most relevant in the field of gerontology in the context of emergency response to the spread of the COVID-19 epidemic, is considered.

Influence of indoor environmental conditions on airborne transmission and lifetime of sneeze droplets in a confined space: a way to reduce COVID-19 spread.

Effects of indoor temperature (T∞) and relative humidity (RH∞) on the airborne transmission of sneeze droplets in a confined space were studied over the T∞ range of 15-30 °C and RH∞ of 22-62%. In addition, a theoretical evaporation model was used to estimate the droplet lifetime based on experimental data. The results showed that the body mass index (BMI) of the participants played an important role in the sneezing jet velocity, while the impact of the BMI and gender of participants was insignificant on the size distribution of droplets. At a critical relative humidity RH∞,crit of 46%, the sneezing jet velocity and droplet lifetime were roughly independent of T∞. At RH∞ < RH∞,crit, the sneezing jet velocity decreased by increasing T∞ from 15 to 30 °C, while its trend was reversed at RH∞ > RH∞,crit. The maximum spreading distance of aerosols increased by decreasing the RH∞ and increasing T∞, while the droplet lifetime increased by decreasing T∞ at RH∞ > RH∞,crit. The mean diameter of aerosolized droplets was less affected by T∞ than the large droplets at RH∞ < RH∞,crit, while the mean diameter and number fraction of aerosols were more influenced by RH∞ than the T∞ in the range of 46% ≤ RH∞ ≤ 62%. In summary, this study suggests suitable indoor environmental conditions by considering the transmission rate and lifetime of respiratory droplets to reduce the spread of COVID-19.

Effect of indoor temperature on the velocity fields and airborne transmission of sneeze droplets: An experimental study and transient CFD modeling.

The spread of the COVID-19 pandemic through the airborne transmission of coronavirus-containing droplets emitted during coughing, sneezing, and speaking has now been well recognized. This study presented the effect of indoor temperature (T∞) on the airflow dynamics, velocity fields, size distribution, and airborne transmission of sneeze droplets in a confined space through experimental investigation and computational fluid dynamic (CFD) modeling. The CFD simulations were performed using the renormalization group k-ε turbulence model. The experimental shadowgraph imaging and CFD simulations showed the time evolution of sneeze droplet concentrations into the turbulent expanded puff, droplet cloud, and fully-dispersed droplets. Also, the predicted mean velocity of droplets was compared with the obtained experimental data to assess the accuracy of the results. In addition, the validated computational model was used to study the sneeze complex airflow behavior and airborne transmission of small, medium, and large respiratory droplets in confined spaces at different temperatures. The warm room showed more than ∼14 % increase in airborne aerosols than the room with a mild temperature. The study provides information on the effect of room temperature on the evaporation of respiratory droplets during sneezing. The findings of this fundamental study may be used in developing exposure guidelines by controlling the temperature level in indoor environments to reduce the exposure risk of COVID-19.

Modeling impact of vaccination on COVID-19 dynamics in St. Louis.

The region of St. Louis, Missouri, has displayed a high level of heterogeneity in COVID-19 cases, hospitalization, and vaccination coverage. We investigate how human mobility, vaccination, and time-varying transmission rates influenced SARS-CoV-2 transmission in five counties in the St. Louis area. A COVID-19 model with a system of ordinary differential equations was developed to illustrate the dynamics with a fully vaccinated class. Using the weekly number of vaccinations, cases, and hospitalization data from five counties in the greater St. Louis area in 2021, parameter estimation for the model was completed. The transmission coefficients for each county changed four times in that year to fit the model and the changing behaviour. We predicted the changes in disease spread under scenarios with increased vaccination coverage. SafeGraph local movement data were used to connect the forces of infection across various counties.

Political violence, risk aversion, and population health: Evidence from the US Capitol riot.

This study is the first to explore the impact of the January 6, 2021 Capitol riot on risk avoidance behavior and the spread of COVID-19. First, using anonymized smartphone data from SafeGraph, Inc., and an event-study approach, we document a substantial increase on January 6 in non-resident smartphone pings at the sites of the protest: the Ellipse, the National Mall, and the US Capitol Building. Then, using data from the same source and a synthetic control approach, we find that the Capitol riot led to an increase in stay-at-home behavior among District of Columbia residents, consistent with risk avoidance behavior and post-riot policies designed to limit large in-person gatherings. Finally, while we find no evidence that the Capitol riot substantially increased the spread of COVID-19 in the District of Columbia, we do find that counties with the highest inflows of out-of-town protesters experienced a 0.004 to 0.010 increase in the rate of daily cumulative COVID-19 case growth during the month following the event. These findings are exacerbated in counties without COVID-19 mitigation policies in place. Supplementary Information: The online version contains supplementary material available at 10.1007/s00148-022-00914-0.

A city-level analysis of PM2.5 pollution, climate and COVID-19 early spread in Spain.

Purpuse: The COVID-19 outbreak has escalated into the worse pandemic of the present century. The fast spread of the new SARS-CoV-2 coronavirus has caused devastating health and economic crises all over the world, with Spain being one of the worst affected countries in terms of confirmed COVID-19 cases and deaths per inhabitant. In this situation, the Spanish Government declared the lockdown of the country. Methods: The variations of air pollution in terms of fine particulate matter (PM2.5) levels in seven representative cities of Spain are analyzed here considering the effect of meteorology during the national lockdown. The possible associations of PM2.5 pollution and climate with COVID-19 accumulated cases were also analyzed. Results: While the epidemic curve was flattened, the results of the analysis show that the 4-week Spanish lockdown significantly reduced the PM2.5 levels in only one city despite the drastically reduced human activity. Furthermore, no associations between either PM2.5 exposure or environmental conditions and COVID-19 transmission were found during the early spread of the pandemic. Conclusions: A longer period applying human activity restrictions is necessary in order to achieve significant reductions of PM2.5 levels in all the analyzed cities. No effect of PM2.5 pollution or weather on COVID-19 incidence was found for these pollutant levels and period of time. Supplementary Information: The online version contains supplementary material available at 10.1007/s40201-022-00786-2.

Counting Pandemic Statistics Remotely Using Webcams.

OBJECTIVE: Lack of mask use during large public events might spread COVID-19. It is now possible to measure this and similar public health information using publicly available webcams. We demonstrate a rapid assessment approach for measuring mask usage at a public event. METHOD: We monitored crowds at public areas in Sturgis, SD using a live, high-definition, town-sponsored video stream to analyze the prevalence of mask wearing. We developed a rapid coding procedure for mask wearing and analyzed brief (5 to 25 min) video segments to assess mask-wearing compliance in outdoor public areas. We calculated compliance estimates and compared reliability among the human coders. RESULTS: We were able to observe and quantify public behavior on the public streets. This approach rapidly estimated public health information (e.g., 512 people observed over 25 minutes with 2.3% mask usage) available on the same day. Coders produced reliable estimates across a sample of videos for counting masked users and mask-wearing proportion. Our video data is stored in Databrary.org. CONCLUSIONS: This approach has implications for disaster responses and public health. The approach is easy to use, can provide same day results, and can provide public health stakeholders with key information on public behavior.

COVID-19 Infection May Not Produce Lasting Immunity in Non-vaccinated Young Adults: A Retrospective Review of COVID-19 Antibody Data.

Background Despite progress in achieving herd immunity through recovery from previous infection and vaccination efforts, the COVID-19 pandemic continues to be an imminent health concern. Exposure to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral antigen through infection or vaccination facilitates immune system efficacy against future infection, but it is currently unclear how long this immunity lasts. Therefore, understanding the necessary exposures to produce adequate antibody levels and the duration of this humoral response to prevent infection is imperative in updating guidelines for vaccination and ultimately ending this public health crisis.  Aims This study aimed to compare the presence of serum antibodies in younger and older age groups to determine how vaccination and previous infection compare as indicators of immunity against COVID-19. We also evaluated age to determine its role in antibody presence. We hope that this information will be helpful to the public to develop the best recommendations for vaccination guidelines concerning distinct demographics. â€‹ Materials and methods In this retrospective data analysis, we evaluated saliva SARS-CoV-2 test results taken from 309 subjects (192F/117M; median age=53.4) during a community fair in Crawford County, PA. We sorted the subjects into groups based on age, reported infection with the COVID-19 virus, and vaccination status. We then performed a Chi-square analysis to compare the frequency of positive SARS-CoV-2 antibody tests within these groups. Results The vaccinated but not previously-infected cohort (n=146, 81.5%) was significantly more likely to have antibodies than the unvaccinated infected cohort (n=55, 65.5%; p<0.0001). In the previously-infected, unvaccinated cohort, individuals who were 55 and older were more likely to have antibodies than younger individuals (p<0.0157), but no age-dependent difference was observed among vaccinated individuals. Conclusions The results suggest that vaccination provides a more durable immune response than recovery from infection, and there is an age-dependent humoral response following previous infection but not vaccination. Practically speaking, this information implies that despite popular misconception, individuals under the age of 55 must receive a COVID-19 vaccine despite the previous infection as they are significantly less likely to have antibodies following infection than their counterparts who are over the age of 55.

Spatial temporal distribution of COVID-19 risk during the early phase of the pandemic in Malawi.

BACKGROUND: COVID-19 has been one of the greatest challenges the world has faced since the second world war. This study aimed at investigating the distribution of COVID-19 in both space and time in Malawi. METHODS: The study used publicly available data of COVID-19 cases for the period from 2 April 2020 to 28 October 2020. Semiparametric spatial temporal models were fitted to the number of monthly confirmed cases as an outcome data, with time and district as independent variables, where district was the spatial unit, while accounting for sociodemographic factors. RESULTS: The study found significant effects of location and time, with the two interacting. The spatial distribution of COVID-19 risk showed major cities being at greater risk than rural areas. Over time, the COVID-19 risk was increasing then decreasing in most districts with the rural districts being consistently at lower risk. High proportion of elderly people was positively associated with COVID-19 risk (ß = 1.272, 95% CI [0.171, 2.370]) than low proportion of elderly people. There was negative association between poverty incidence and COVID-19 risk (ß = -0.100, 95% CI [-0.136, -0.065]). CONCLUSION: Future or present strategies to limit the spread of COVID-19 should target major cities and the focus should be on time periods that had shown high risk. Furthermore, the focus should be on elderly and rich people.