Network-Exposure Severity and Self-Protective Behaviors: The Case of COVID-19

Random forest models of food safety behavior during the COVID-19 pandemic

Machine learning approaches are increasingly being adopted as data analysis tools in scientific behavioral predictions. This paper utilizes a machine learning approach, Random Forest Model, to determine the top prediction variables of food safety behavioral changes during the pandemic. Data was collected among U.S. consumers on risk perception of COVID-19 and foodborne illness (FBI), food safety practice behaviors and demographics through online surveys at ten different time points from April 2020 through to May 2021; and post pandemic in May 2022. Random forest model was used to predict 14 food safety-related behaviors. The models for predicting Handwashing before cooking and Handwashing after eating had a good performance, with F-1 score of 0.93 and 0.88, respectively. Attitudes- related variables were determined to be important in predicting food safety behaviors. The importance ranking of the predicting variables were found to be changing over time.

Motivating Protective Behavior against COVID-19: Fear Versus Hope

OBJECTIVES

Based on protection motivation theory, we investigate how indicators of threat perception (perceived severity, perceived vulnerability, and fear arousal) and coping appraisal (hope) are associated with older people's motivation to engage in protective behavior after the outbreak of COVID-19.

METHODS

We use multivariate regression analyses with a sample of 40,282 individuals from 26 countries participating in the SHARE Corona Survey.

RESULTS

We find that 15% of all respondents stayed home completely-mainly the oldest and vulnerable people with prior health risk conditions. On average, older Europeans responded strongly to the recommended protective behavior measures (6 out of 7 measures adopted). Among the threat perception indicators, fear arousal is the main motivator for protective behavior, whereas the coping appraisal indicator hope shows an equally strong association.

DISCUSSION

Given the negative health effects of fear, our findings may help evaluate and revise governmental policy responses and communication strategies.

Autonomous and policy-induced behavior change during the COVID-19 pandemic: Towards understanding and modeling the interplay of behavioral adaptation

Changes in human behaviors, such as reductions of physical contacts and the adoption of preventive measures, impact the transmission of infectious diseases considerably. Behavioral adaptations may be the result of individuals aiming to protect themselves or mere responses to public containment measures, or a combination of both. What drives autonomous and policy-induced adaptation, how they are related and change over time is insufficiently understood. Here, we develop a framework for more precise analysis of behavioral adaptation, focusing on confluence, interactions and time variance of autonomous and policy-induced adaptation. We carry out an empirical analysis of Germany during the fall of 2020 and beyond. Subsequently, we discuss how behavioral adaptation processes can be better represented in behavioral-epidemiological models. We find that our framework is useful to understand the interplay of autonomous and policy-induced adaptation as a "moving target". Our empirical analysis suggests that mobility patterns in Germany changed significantly due to both autonomous and policy-induced adaption, with potentially weaker effects over time due to decreasing risk signals, diminishing risk perceptions and an erosion of trust in the government. We find that while a number of simulation and prediction models have made great efforts to represent behavioral adaptation, the interplay of autonomous and policy-induced adaption needs to be better understood to construct convincing counterfactual scenarios for policy analysis. The insights presented here are of interest to modelers and policy makers aiming to understand and account for behaviors during a pandemic response more accurately.

Evaluation of vaccine rollout strategies for emerging infectious diseases: A model-based approach including protection attitudes

Vaccine allocation strategies become crucial during vaccine shortages, especially in the face of potential outbreaks of new infectious diseases, as witnessed during the COVID-19 pandemic. To address this, a specialized compartmental model is created, which simulates an emerging infectious disease similar to COVID-19. This model divides the population into different age groups and is used to compare various vaccine prioritisation approaches, aiming to minimize the total number of fatalities. The model is an improvement upon previous ones as it incorporates essential behavioural factors and is adapted to account for the protective effects of vaccination against both disease infection and transmission. It takes into account human behaviors such as mask-wearing and social distancing by utilizing specific parameters related to self-protection, awareness levels, and the frequency of daily person-to-person interactions within each age group. Furthermore, a novel method for dynamic vaccine prioritisation was introduced in this study. This approach is model-independent and relies on the dynamic R number. It is the first time such a method has been developed, offering a decision-making approach that is not tied to any specific model. This innovation provides a flexible and adaptable strategy for determining vaccine priorities based on real-time data and the current state of the outbreak. Our findings reveal crucial insights into vaccine allocation strategies. When the daily rollout rates are fast (0.75% or higher) and children are eligible for vaccination, prioritising groups with high daily person-to-person interactions can lead to substantial reductions in total fatalities (up to approximately 40% lower). On the other hand, if rollout rates are slower and overall vaccination coverage is high, focusing on vaccinating elders emerges as the most effective strategy, resulting in up to approximately 10% fewer fatalities. However, the scenario changes significantly when children are not eligible for vaccination, as they constitute a highly interactive population group. In this case, the differences between priority strategies become smaller. With fast daily rollout rates, prioritisation based on interactions achieves only a 7% reduction in total fatalities, while a slower rollout with vaccination of elders first leads to an approximately 11% reduction in fatalities compared to the scenario where children are eligible for vaccination. The impact of behavioural parameters is equally critical. When the self-protection levels exercised by the population are low, it significantly affects the optimal vaccine prioritisation strategy to be followed, making it essential to consider behavioural factors in decision-making.

Intergenerational Ties and COVID-19 Contagion: A Study on European Adults Aged 50 Years and Older Using SHARE Data

OBJECTIVES

Intergenerational coresidence and interdependence among family members are salient forms of family support. However, they can also likely increase social and physical contact and thus potential coronavirus disease 2019 (COVID-19) transmission, especially among older adults. This study makes an original contribution to the literature by investigating which individual and household characteristics are associated with the risk of COVID-19 contagion among community-dwelling adults aged 50 years or older living in 27 European countries. We accounted for multiple indicators of intergenerational relationships and conducted a gendered analysis.

METHODS

The data came from the Survey of Health, Ageing and Retirement in Europe (SHARE), including 2 waves of the SHARE Corona Survey. Using linear probability models, the risk of experiencing COVID-19 outcomes was predicted by different family structures and intergenerational relationship indicators.

RESULTS

While intergenerational coresidence was not associated with the risk of COVID-19, a higher frequency of face-to-face contact with adult children was associated with a lower risk of COVID-19 among mothers. This result stresses the importance of social support from adult children during the COVID-19 pandemic. However, we also showed that grandparents who took care of grandchildren were at a higher risk of COVID-19. Additionally, childless individuals had a lower risk of COVID-19 during the second wave of the pandemic.

DISCUSSION

This study highlights the importance of intergenerational relationships in pandemic studies and underscores the need to examine how intergenerational ties might be a source of social support. Implications for policy interventions are discussed in the final section.

COVID-19 precautionary behaviors and vaccine acceptance among older individuals: The role of close kin

The family plays a central role in shaping health behaviors of its members through social control and support mechanisms. We investigate whether and to what extent close kin (i.e., partner and children) matter for older people in taking on precautionary behaviors (e.g., wearing a mask) and vaccination during the COVID-19 pandemic in Europe. Drawing on data from the Survey of Health, Ageing and Retirement in Europe (SHARE), we combine its Corona Surveys (June to September 2020 and June to August 2021) with pre-COVID information (October 2019 to March 2020). We find that having close kin (especially a partner) is associated with a higher probability of both adopting precautionary behaviors and accepting a COVID-19 vaccine. Results are robust to controlling for other potential drivers of precautionary behaviors and vaccine acceptance and to accounting for coresidence with kin. Our findings suggest that policymakers and practitioners may differently address kinless individuals when promoting public policy measures.

Poverty in old age in times of COVID-19-Empirical results from Austria

Early in the pandemic, researchers were cautioning that COVID-19 and the associated health policy countermeasures would have an increased negative impact on groups that were already vulnerable before the pandemic. One of these groups are older people affected by poverty, who according to official figures make up 13.9% of older population in Austria. Even before the pandemic, their living situation was considered precarious. Not without reason, this group has been identified as a high-risk group of the pandemic, due to their increased likelihood of severe COVID-19 related illness and their limited monetary resources and thus lower chances of coping with the pandemic. Nevertheless, research on this group has remained sparse to date. Therefore, the aim of the study is to focus on older people (60+ years) below the poverty line and to compare them with non-poor individuals. Data from the SHARE (Survey of Health Aging and Retirement in Europe) project is used, combining data from the two SHARE Corona Surveys (summer 2020 and summer 2021) and the SHARE Corona Special Austria Survey (December 2020) to gain the most complete picture of life situation during the pandemic. Results demonstrate that older people in poverty were more likely to report poor subjective health before as well as during the pandemic yet were significantly more likely to refuse vaccination against COVID-19, despite adhering to other measures against the pandemic to the same extent as non-poor people. Restrictions in the health care system affected both groups equally and no significant differences in the frequency of social contacts could be found. However, older people below the poverty line were significantly more likely to rely on social support to obtain necessities during the pandemic and were less likely to use the internet. Together, these results point out that disadvantage exist for the older poor in some but not all areas of life during the pandemic. This paper is aimed at providing first insights into the lives of poor older persons during a taxing time and may perhaps inspire more in-depth study of this particularly understudied population.

National variability in Americans' COVID-19 protective behaviors: Implications for vaccine roll-out

Protective behaviors such as mask wearing and physical distancing are critical to slow the spread of COVID-19, even in the context of vaccine scale-up. Understanding the variation in self-reported COVID-19 protective behaviors is critical to developing public health messaging. The purpose of the study is to provide nationally representative estimates of five self-reported COVID-19 protective behaviors and correlates of such behaviors. In this cross-sectional survey study of US adults, surveys were administered via internet and telephone. Adults were surveyed from April 30-May 4, 2020, a time of peaking COVID-19 incidence within the US. Participants were recruited from the probability-based AmeriSpeak® national panel. Brief surveys were completed by 994 adults, with 73.0% of respondents reported mask wearing, 82.7% reported physical distancing, 75.1% reported crowd avoidance, 89.8% reported increased hand-washing, and 7.7% reported having prior COVID-19 testing. Multivariate analysis (p critical value .05) indicates that women were more likely to report protective behaviors than men, as were those over age 60. Respondents who self-identified as having low incomes, histories of criminal justice involvement, and Republican Party affiliation, were less likely to report four protective behaviors, though Republicans and individuals with criminal justice histories were more likely to report having received COVID-19 testing. The majority of Americans engaged in COVID-19 protective behaviors, with low-income Americans, those with histories of criminal justice involvement, and self-identified Republicans less likely to engage in these preventive behaviors. Culturally competent public health messaging and interventions might focus on these latter groups to prevent future infections. These findings will remain highly relevant even with vaccines widely available, given the complementarities between vaccines and protective behaviors, as well as the many challenges in delivering vaccines.