The second wave of SARS-CoV-2 infections and COVID-19 deaths in Germany – driven by values, social status and migration background? A county-scale explainable machine learning approach

ABSTRACTThere is a general consensus that SARS-CoV-2 infections and COVID-19 deaths have hit lower social groups the hardest, however, for Germany individual level information on socioeconomic characteristics of infections and deaths does not exist. The aim of this study was to identify the key features explaining SARS-CoV-2 infections and COVID-19 deaths during the upswing of the second wave in Germany.We considered information on COVID-19 diagnoses and deaths from 1. October to 15. December 2020 on the county-level, differentiating five two-week time periods. We used 155 indicators to characterize counties in nine geographic, social, demographic, and health domains. For each period, we calculated directly age-standardized COVID-19 incidence and death rates on the county level. We trained gradient boosting models to predict the incidence and death rates with the 155 characteristics of the counties for each period. To explore the importance and the direction of the correlation of the regional indicators we used the SHAP procedure. We categorized the top 20 associations identified by the Shapley values into twelve categories depicting the correlation between the feature and the outcome.We found that counties with low SES were important drivers in the second wave, as were those with high international migration and a high proportion of foreigners and a large nursing home population. During the period of intense exponential increase in infections, the proportion of the population that voted for the Alternative for Germany (AfD) party in the last federal election was among the top characteristics correlated with high incidence and death rates.We concluded that risky working conditions with reduced opportunities for social distancing and a high chronic disease burden put populations in low-SES counties at higher risk of SARS-CoV-2 infections and COVID-19 deaths. In addition, noncompliance with Corona measures and spill-over effects from neighbouring counties increased the spread of the virus. To further substantiate this finding, we urgently need more data at the individual level.

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Regional Characteristics of the Second Wave of SARS-CoV-2 Infections and COVID-19 Deaths in Germany

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph182010663 ◽

2021 ◽

Vol 18 (20) ◽

pp. 10663

Author(s):

Gabriele Doblhammer ◽

Daniel Kreft ◽

Constantin Reinke

Keyword(s):

Low Socioeconomic Status ◽

Gradient Boosting ◽

County Level ◽

Learning Approaches ◽

Nursing Home Population ◽

Death Rates ◽

Individual Level ◽

Regional Characteristics ◽

Level Information ◽

Second Wave

(1) Background: In the absence of individual level information, the aim of this study was to identify the regional key features explaining SARS-CoV-2 infections and COVID-19 deaths during the upswing of the second wave in Germany. (2) Methods: We used COVID-19 diagnoses and deaths from 1 October to 15 December 2020, on the county-level, differentiating five two-week time periods. For each period, we calculated the age-standardized COVID-19 incidence and death rates on the county level. We trained gradient boosting models to predict the incidence and death rates by 155 indicators and identified the top 20 associations using Shap values. (3) Results: Counties with low socioeconomic status (SES) had higher infection and death rates, as had those with high international migration, a high proportion of foreigners, and a large nursing home population. The importance of these characteristics changed over time. During the period of intense exponential increase in infections, the proportion of the population that voted for the Alternative for Germany (AfD) party in the last federal election was among the top characteristics correlated with high incidence and death rates. (4) Machine learning approaches can reveal regional characteristics that are associated with high rates of infection and mortality.

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Migration, acculturation, and the maintenance of between-group cultural variation

10.1101/234807 ◽

2017 ◽

Cited By ~ 1

Author(s):

Alex Mesoudi

Keyword(s):

Social Learning ◽

Cultural Values ◽

Cultural Evolution ◽

Population Level ◽

Empirical Literature ◽

Cultural Variation ◽

Individual Level ◽

And Migration ◽

The Individual ◽

Social Learning Processes

AbstractHow do migration and acculturation (i.e. psychological or behavioral change resulting from migration) affect within- and between-group cultural variation? Here I answer this question by drawing analogies between genetic and cultural evolution. Population genetic models show that migration rapidly breaks down between-group genetic structure. In cultural evolution, however, migrants or their descendants can acculturate to local behaviors via social learning processes such as conformity, potentially preventing migration from eliminating between-group cultural variation. An analysis of the empirical literature on migration suggests that acculturation is common, with second and subsequent migrant generations shifting, sometimes substantially, towards the cultural values of the adopted society. Yet there is little understanding of the individual-level dynamics that underlie these population-level shifts. To explore this formally, I present models quantifying the effect of migration and acculturation on between-group cultural variation, for both neutral and costly cooperative traits. In the models, between-group cultural variation, measured using F statistics, is eliminated by migration and maintained by conformist acculturation. The extent of acculturation is determined by the strength of conformist bias and the number of demonstrators from whom individuals learn. Acculturation is countered by assortation, the tendency for individuals to preferentially interact with culturally-similar others. Unlike neutral traits, cooperative traits can additionally be maintained by payoff-biased social learning, but only in the presence of strong sanctioning institutions. Overall, the models show that surprisingly little conformist acculturation is required to maintain realistic amounts of between-group cultural diversity. While these models provide insight into the potential dynamics of acculturation and migration in cultural evolution, they also highlight the need for more empirical research into the individual-level learning biases that underlie migrant acculturation.

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Understanding how Victoria, Australia gained control of its second COVID-19 wave

Nature Communications ◽

10.1038/s41467-021-26558-4 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

James M. Trauer ◽

Michael J. Lydeamore ◽

Gregory W. Dalton ◽

David Pilcher ◽

Michael T. Meehan ◽

...

Keyword(s):

Time Varying ◽

Population Mobility ◽

School Closures ◽

Individual Level ◽

Risk Of Death ◽

Policy Interventions ◽

Australian State ◽

The Individual ◽

Individual Health Services ◽

Second Wave

AbstractDuring 2020, Victoria was the Australian state hardest hit by COVID-19, but was successful in controlling its second wave through aggressive policy interventions. We calibrated a detailed compartmental model of Victoria’s second wave to multiple geographically-structured epidemic time-series indicators. We achieved a good fit overall and for individual health services through a combination of time-varying processes, including case detection, population mobility, school closures, physical distancing and face covering usage. Estimates of the risk of death in those aged ≥75 and of hospitalisation were higher than international estimates, reflecting concentration of cases in high-risk settings. We estimated significant effects for each of the calibrated time-varying processes, with estimates for the individual-level effect of physical distancing of 37.4% (95%CrI 7.2−56.4%) and of face coverings of 45.9% (95%CrI 32.9−55.6%). That the multi-faceted interventions led to the dramatic reversal in the epidemic trajectory is supported by our results, with face coverings likely particularly important.

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Individual error correction drives responsive self-assembly of army ant scaffolds

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2013741118 ◽

2021 ◽

Vol 118 (17) ◽

pp. e2013741118

Author(s):

Matthew J. Lutz ◽

Chris R. Reid ◽

Christopher J. Lustri ◽

Albert B. Kao ◽

Simon Garnier ◽

...

Keyword(s):

Error Correction ◽

Self Assembly ◽

Field Experiments ◽

Group Level ◽

Final Size ◽

Army Ants ◽

Individual Level ◽

Inclined Surfaces ◽

And Migration ◽

The Individual

An inherent strength of evolved collective systems is their ability to rapidly adapt to dynamic environmental conditions, offering resilience in the face of disruption. This is thought to arise when individual sensory inputs are filtered through local interactions, producing an adaptive response at the group level. To understand how simple rules encoded at the individual level can lead to the emergence of robust group-level (or distributed) control, we examined structures we call “scaffolds,” self-assembled by Eciton burchellii army ants on inclined surfaces that aid travel during foraging and migration. We conducted field experiments with wild E. burchellii colonies, manipulating the slope over which ants traversed, to examine the formation of scaffolds and their effects on foraging traffic. Our results show that scaffolds regularly form on inclined surfaces and that they reduce losses of foragers and prey, by reducing slipping and/or falling of ants, thus facilitating traffic flow. We describe the relative effects of environmental geometry and traffic on their growth and present a theoretical model to examine how the individual behaviors underlying scaffold formation drive group-level effects. Our model describes scaffold growth as a control response at the collective level that can emerge from individual error correction, requiring no complex communication among ants. We show that this model captures the dynamics observed in our experiments and is able to predict the growth—and final size—of scaffolds, and we show how the analytical solution allows for estimation of these dynamics.

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The Use of Penalized Regression Analysis to Identify County-Level Demographic and Socioeconomic Variables Predictive of Increased COVID-19 Cumulative Case Rates in the State of Georgia

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17218036 ◽

2020 ◽

Vol 17 (21) ◽

pp. 8036

Author(s):

Holly L. Richmond ◽

Joana Tome ◽

Haresh Rochani ◽

Isaac Chun-Hai Fung ◽

Gulzar H. Shah ◽

...

Keyword(s):

Social Determinants Of Health ◽

Social Determinants ◽

Penalized Regression ◽

Determinants Of Health ◽

County Level ◽

Lasso Regression ◽

Cross Sectional ◽

Individual Level ◽

The Social ◽

The Individual

Systemic inequity concerning the social determinants of health has been known to affect morbidity and mortality for decades. Significant attention has focused on the individual-level demographic and co-morbid factors associated with rates and mortality of COVID-19. However, less attention has been given to the county-level social determinants of health that are the main drivers of health inequities. To identify the degree to which social determinants of health predict COVID-19 cumulative case rates at the county-level in Georgia, we performed a sequential, cross-sectional ecologic analysis using a diverse set of socioeconomic and demographic variables. Lasso regression was used to identify variables from collinear groups. Twelve variables correlated to cumulative case rates (for cases reported by 1 August 2020) with an adjusted r squared of 0.4525. As time progressed in the pandemic, correlation of demographic and socioeconomic factors to cumulative case rates increased, as did number of variables selected. Findings indicate the social determinants of health and demographic factors continue to predict case rates of COVID-19 at the county-level as the pandemic evolves. This research contributes to the growing body of evidence that health disparities continue to widen, disproportionality affecting vulnerable populations.

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Individual- and County-Level Religious Participation, Corporal Punishment, and Physical Abuse of Children: An Exploratory study

Journal of Interpersonal Violence ◽

10.1177/0886260516674197 ◽

2016 ◽

Vol 34 (19) ◽

pp. 3983-3994 ◽

Cited By ~ 3

Author(s):

Jennifer Price Wolf ◽

Nancy Jo Kepple

Keyword(s):

Physical Abuse ◽

Corporal Punishment ◽

Exploratory Study ◽

Religious Attendance ◽

Religious Participation ◽

County Level ◽

Physical Discipline ◽

Religious Groups ◽

Individual Level ◽

The Individual

Parental religiosity has been associated with corporal punishment. However, most of this research has focused exclusively on Christians and has not examined physical abuse. In addition, little is known about how the larger religious environment might be associated with discipline behaviors. In this exploratory study, we examine how individual- and county-level religious attendance are related to corporal punishment and physical abuse. We sampled and surveyed 3,023 parents of children aged 12 and younger from 50 mid-sized California cities. We used weighted Poisson models to calculate the frequency of corporal punishment and physical abuse in the past year. Parents who attend religious groups used corporal punishment more frequently than parents who did not attend religious groups. However, those who lived in counties with greater rates of religious participation used corporal punishment less frequently than those living in counties with lower rates of religious participation. There were no effects for religious participation on physical abuse at the individual or county level. This exploratory study suggests that parents who attend religious groups may be more likely to use some types of physical discipline with children. Religious groups could be imparting parenting norms supporting corporal punishment at the individual level. More research examining specific doctrines and faiths is needed to validate the study findings.

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Regional Personality Differences Predict Variation in COVID-19 Infections, Deaths and Social Distancing Behavior

10.31234/osf.io/sqh98 ◽

2020 ◽

Author(s):

Heinrich Peters ◽

Friedrich Martin Götz ◽

Tobias Ebert ◽

Sandrine Müller ◽

Jason Rentfrow ◽

...

Keyword(s):

Critical Role ◽

Initial Growth ◽

Death Rates ◽

Social Distancing ◽

Individual Level ◽

Personality Differences ◽

The Us ◽

The Individual ◽

Objective Indicators ◽

Insight Into

Social and compliance behaviors play a critical role in the transmission of COVID-19. Consequently, regional variation in personality traits that capture individual differences in these behaviors may offer new insight into the spread of COVID-19. We combine self-reported personality data (3.5M people), COVID-19 prevalence and death rates, and behavioral mobility observations (29M people) to show that regional personality differences in the US and Germany predict COVID-19-related outcomes and behaviors incremental to a conservative set of socio-demographic, economic, and pandemic-related control variables. Earlier onsets of COVID-19 and steeper initial growth rates were related to higher levels of Openness and lower levels of Neuroticism. We also show that (i) regional personality is associated with objective indicators of social distancing, (ii) the effects of regional personality can change over time (Openness), and that (iii) the effects of regional personality do not always converge with those observed at the individual level (Agreeableness and Conscientiousness).

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Psychometric evaluation of dynamic managerial capability scale in the context of early internationalizing firms from an emerging economy

Asia-Pacific Journal of Business Administration ◽

10.1108/apjba-06-2019-0140 ◽

2019 ◽

Vol 11 (4) ◽

pp. 371-386 ◽

Cited By ~ 4

Author(s):

Md Imtiaz Mostafiz ◽

Murali Sambasivan ◽

See Kwong Goh

Keyword(s):

Factor Analysis ◽

Psychometric Evaluation ◽

Emerging Economy ◽

Three Dimension ◽

Measurement Scales ◽

Content Type ◽

Individual Level ◽

Order Construct ◽

The Individual ◽

Second Wave

Purpose The purpose of this paper is to perform a psychometric evaluation of dynamic managerial capability (DMC) scale in the context of early internationalizing firms from an emerging economy. Drawing on DMC theory, this study validates the measurement scales to operationalize DMC of entrepreneurs as managerial human capital (MHC), managerial social capital (MSC) and managerial cognition (MC). Design/methodology/approach Sample firms were drawn from the apparel industry in Bangladesh, an emerging economy. Data were collected from entrepreneurs in two waves through a questionnaire-based survey. In total, 185 firms responded during the first wave and 223 firms responded during the second wave. The first wave of data was used to conduct exploratory factor analysis (EFA) to uncover the underlying dimensions of DMC and the data from the second wave were used to test the validity of the DMC scale through confirmatory factor analysis (CFA). Findings EFA suggested a three-dimension scale which was supported by CFA. The findings of the study demonstrate that DMC is a valid and reliable scale to capture the individual-level capability of entrepreneurs. Originality/value DMC is rooted in three underlying attributes as MHC, MSC and MC. It is advisable to the practitioner and researcher to operationalize DMC as a second-order construct in future studies.

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Influenza Vaccination and COVID-19 Mortality in the USA: An Ecological Study

Vaccines ◽

10.3390/vaccines9050427 ◽

2021 ◽

Vol 9 (5) ◽

pp. 427

Author(s):

Claudio Zanettini ◽

Mohamed Omar ◽

Wikum Dinalankara ◽

Eddie Luidy Imada ◽

Elizabeth Colantuoni ◽

...

Keyword(s):

Mortality Rate ◽

Influenza Vaccination ◽

Vaccination Coverage ◽

Elderly Population ◽

The Elderly ◽

Outcome Variable ◽

County Level ◽

Individual Level ◽

The Usa ◽

The Individual

The COVID-19 mortality rate is higher in the elderly and in those with pre-existing chronic medical conditions. The elderly also suffer from increased morbidity and mortality from seasonal influenza infections; thus, an annual influenza vaccination is recommended for them. In this study, we explore a possible county-level association between influenza vaccination coverage in people aged 65 years and older and the number of deaths from COVID-19. To this end, we used COVID-19 data up to 14 December 2020 and US population health data at the county level. We fit quasi-Poisson regression models using influenza vaccination coverage in the elderly population as the independent variable and the COVID-19 mortality rate as the outcome variable. We adjusted for an array of potential confounders using different propensity score regression methods. Results show that, on the county level, influenza vaccination coverage in the elderly population is negatively associated with mortality from COVID-19, using different methodologies for confounding adjustment. These findings point to the need for studying the relationship between influenza vaccination and COVID-19 mortality at the individual level to investigate any underlying biological mechanisms.

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Are both individual-level and county-level social capital associated with individual health? A serial cross-sectional analysis in China, 2010–2015

BMJ Open ◽

10.1136/bmjopen-2020-044616 ◽

2021 ◽

Vol 11 (8) ◽

pp. e044616

Author(s):

Yang Han ◽

Roger Yat-Nork Chung

Keyword(s):

Mental Health ◽

Social Capital ◽

High Frequency ◽

County Level ◽

Physical And Mental Health ◽

Cross Sectional ◽

Individual Level ◽

Individual Health ◽

Rapid Economic Growth ◽

The Individual

ObjectivesWe aimed to examine the associations of both individual-level and county-level social capital with individual health in China during a period of rapid economic growth.Design and settingA serial cross-sectional study in China.Participants and methodsThe participants were 42 829 Chinese adults (aged ≥18 years) from the 2010, 2012, 2013 and 2015 Chinese General Social Survey. The outcomes were self-rated physical and mental health in all time points. We assessed social capital by the individual-level and county-level indicators, including frequency of socialising, civic participation and trust. We conducted multilevel binary logistic regression models to examine the associations of individual-level and county-level social capital with self-rated physical and mental health.ResultsAt the individual level, high frequency of socialising (2010—OR: 1.49, 95% CI: 1.33 to 1.66; 2012—OR: 1.39, 95% CI: 1.26 to 1.54; 2013—OR: 1.28, 95% CI: 1.15 to 1.42; 2015—OR: 1.36, 95% CI: 1.23 to 1.50) and high trust (2010—OR: 1.34, 95% CI: 1.22 to 1.47; 2012—OR: 1.30, 95% CI: 1.18 to 1.42; 2013—OR: 1.21, 95% CI: 1.10 to 1.33; 2015—OR: 1.41, 95% CI: 1.28 to 1.55) was significantly associated with good physical health in all years. At the individual level, high frequency of socialising (2010—OR: 1.27, 95% CI: 1.14 to 1.42; 2012—OR: 1.21, 95% CI: 1.09 to 1.34; 2013—OR: 1.30, 95% CI: 1.17 to 1.45; 2015—OR: 1.35, 95% CI: 1.22 to 1.50) and high trust (2010—OR: 1.47, 95% CI: 1.34 to 1.61; 2012—OR: 1.42, 95% CI: 1.30 to 1.56; 2013—OR: 1.36, 95% CI: 1.24 to 1.49; 2015—OR: 1.43, 95% CI: 1.30 to 1.57) was also significantly associated with good mental health in all years. No evidence showed that the associations of individual-level frequency of socialising and trust with physical and mental health changed over time. There were no consistent associations of individual-level civic participation or any county-level social capital indicators with physical or mental health.ConclusionThe positive associations of individual-level social capital in terms of socialising and trust with physical and mental health were robust during a period of rapid economic growth. Improving individual-level socialising and trust for health promotion could be a long-term strategy even within a rapidly developing society.

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