Towards a data-driven characterization of behavioral changes induced by the seasonal flu

Are interactive and tailored data visualizations effective in promoting flu vaccination among the elderly? Evidence from a randomized experiment

OBJECTIVE

Although interactive data visualizations are increasingly popular for health communication, it remains to be seen what design features improve psychological and behavioral targets. This study experimentally tested how interactivity and descriptive titles may influence perceived susceptibility to the flu, intention to vaccinate, and information recall, particularly among older adults.

MATERIALS AND METHODS

We created data visualization dashboards on flu vaccinations, tested in a 2 (explanatory text vs none) × 3 (interactive + tailored, static + tailored, static + nontailored) + questionnaire-only control randomized between-participant online experiment (N   = 1378).

RESULTS

The flu dashboards significantly increased perceived susceptibility to the flu compared to the control: static+nontailored dashboard, b = 0.14, P = .049; static-tailored, b = 0.16, P = .028; and interactive+tailored, b = 0.15, P = .039. Interactive dashboards potentially decreased recall particularly among the elderly (moderation by age: b = -0.03, P = .073). The benefits of descriptive text on recall were larger among the elderly (interaction effects: b = 0.03, P = .025).

DISCUSSION

Interactive dashboards with complex statistics and limited textual information are widely used in health and public health but may be suboptimal for older individuals. We experimentally showed that adding explanatory text on visualizations can increase information recall particularly for older populations.

CONCLUSION

We did not find evidence to support the effectiveness of interactivity in data visualizations on flu vaccination intentions or on information recall. Future research should examine what types of explanatory text can best support improved health outcomes and intentions in other contexts. Practitioners should consider whether interactivity is optimal in data visualization dashboards for their populations.

Epidemic Spreading in Metapopulation Networks Coupled With Awareness Propagation

Understanding the feedback loop that links the spatiotemporal spread of infectious diseases and human behavior is an open problem. To study this problem, we develop a multiplex framework that couples epidemic spreading across subpopulations in a metapopulation network (i.e., physical layer) with the spreading of awareness about the epidemic in a communication network (i.e., virtual layer). We explicitly study the interactions between the mobility patterns across subpopulations and the awareness propagation among individuals. We analyze the coupled dynamics using microscopic Markov chains (MMCs) equations and validate the theoretical results via Monte Carlo (MC) simulations. We find that with the spreading of awareness, reducing human mobility becomes more effective in mitigating the large-scale epidemic. We also investigate the influence of varying topological features of the physical and virtual layers and the correlation between the connectivity and local population size per subpopulation. Overall the proposed modeling framework and findings contribute to the growing literature investigating the interplay between the spatiotemporal spread of epidemics and human behavior.

Mobility patterns and COVID growth: Moderating role of country culture

The COVID-19 pandemic has resulted in countries reacting differently to an ongoing crisis situation. Latent to this reaction mechanism is the inherent cultural characteristics of each society resulting in differential responses to epidemic spread. Epidemiological studies have confirmed the positive effect of population mobility on the growth of infection. However, the effect of culture on indigenous mobility patterns during pandemics needs further investigation. This study aims to bridge this gap by exploring the moderating role of country culture on the relationship between population mobility and growth of CoVID-19. Hofstede's cultural factors; power distance, individualism/collectivism, masculinity/femininity, uncertainty avoidance, long-term and short-term orientation are hypothesised to moderate the effect of mobility on the reproduction number (R) of COVID-19. Panel regression model, using mobility data and number of confirmed cases across 95 countries for a period of 170 days has been preferred to test the hypotheses. The results are further substantiated using slope analysis and Johnson-Neyman technique. The findings suggest that as power distance, individualism and long-term orientation scores increase, the impact of mobility on epidemic growth decreases. However, masculinity scores in a society have an opposite moderating impact on epidemic growth rate. These Hofstede factors act as quasi moderators affecting mobility and epidemic growth. Similar conclusions could be not be confirmed for uncertainty avoidance. Cross-cultural impact, as elucidated by this study, forms a crucial element in policy formulation on epidemic control by indigenous Governing bodies.

Adaptive and optimized COVID-19 vaccination strategies across geographical regions and age groups

We evaluate the efficiency of various heuristic strategies for allocating vaccines against COVID-19 and compare them to strategies found using optimal control theory. Our approach is based on a mathematical model which tracks the spread of disease among different age groups and across different geographical regions, and we introduce a method to combine age-specific contact data to geographical movement data. As a case study, we model the epidemic in the population of mainland Finland utilizing mobility data from a major telecom operator. Our approach allows to determine which geographical regions and age groups should be targeted first in order to minimize the number of deaths. In the scenarios that we test, we find that distributing vaccines demographically and in an age-descending order is not optimal for minimizing deaths and the burden of disease. Instead, more lives could be saved by using strategies which emphasize high-incidence regions and distribute vaccines in parallel to multiple age groups. The level of emphasis that high-incidence regions should be given depends on the overall transmission rate in the population. This observation highlights the importance of updating the vaccination strategy when the effective reproduction number changes due to the general contact patterns changing and new virus variants entering.

The COVID-19 vaccines are now available worldwide and many countries follow the practice of distributing them heuristically e.g. in age-descending order and demographically. Here we evaluate the effectiveness of such strategies by comparing them with optimized ones from an age and spatially-structured mathematical model of COVID-19 transmission. We find that vaccinating multiple age groups simultaneously and targeting regions with the the highest incidence can save more lives than heuristic strategies. Our work also reveals the importance of assessing the vaccination strategy at different stages of the epidemic.

Self-initiated behavioral change and disease resurgence on activity-driven networks

We consider a population that experienced a first wave of infections, interrupted by strong, top-down, governmental restrictions and did not develop a significant immunity to prevent a second wave (i.e., resurgence). As restrictions are lifted, individuals adapt their social behavior to minimize the risk of infection. We explore two scenarios. In the first, individuals reduce their overall social activity towards the rest of the population. In the second scenario, they maintain normal social activity within a small community of peers (i.e., social bubble) while reducing social interactions with the rest of the population. In both cases, we investigate possible correlations between social activity and behavior change, reflecting, for example, the social dimension of certain occupations. We model these scenarios considering a susceptible-infected-recovered epidemic model unfolding on activity-driven networks. Extensive analytical and numerical results show that (i) a minority of very active individuals not changing behavior may nullify the efforts of the large majority of the population and (ii) imperfect social bubbles of normal social activity may be less effective than an overall reduction of social interactions.

Simulating human behavioral changes in livestock production systems during an epidemic: The case of the US beef cattle industry

Human behavioral change around biosecurity in response to increased awareness of disease risks is a critical factor in modeling animal disease dynamics. Here, biosecurity is referred to as implementing control measures to decrease the chance of animal disease spreading. However, social dynamics are largely ignored in traditional livestock disease models. Not accounting for these dynamics may lead to substantial bias in the predicted epidemic trajectory. In this research, an agent-based model is developed by integrating the human decision-making process into epidemiological processes. We simulate human behavioral change on biosecurity practices following an increase in the regional disease incidence. We apply the model to beef cattle production systems in southwest Kansas, United States, to examine the impact of human behavior factors on a hypothetical foot-and-mouth disease outbreak. The simulation results indicate that heterogeneity of individuals regarding risk attitudes significantly affects the epidemic dynamics, and human-behavior factors need to be considered for improved epidemic forecasting. With the same initial biosecurity status, increasing the percentage of risk-averse producers in the total population using a targeted strategy can more effectively reduce the number of infected producer locations and cattle losses compared to a random strategy. In addition, the reduction in epidemic size caused by the shifting of producers' risk attitudes towards risk-aversion is heavily dependent on the initial biosecurity level. A comprehensive investigation of the initial biosecurity status is recommended to inform risk communication strategy design.

The role of facial contact in infection control: Renewed import in the age of coronavirus

Background

Decreasing facial contact takes on new urgency as society tries to stem the tide of COVID-19 spread. A better understanding of the pervasiveness of facial contact in social settings is required in order to then take steps to mitigate the action.

Methods

YouTube videos of random individuals were included in a behavioral observation study to document rates of contact to the eyes, nose, and mouth area. Factors including age, sex, the presence of eyewear or facial hair, distraction and fatigue were analyzed as possible contributing factors that increase likelihood of facial contact.

Results

The median rate of facial contact was 22 contacts per hour. Men had a significantly higher rate of facial contact compared to women. Age, glasses, and presence of facial hair were not contributing factors. The mouth was the most frequently observed site of contact. Fatigue and distraction may increase rates of facial contact.

Conclusions

Changing personal behavior is a simple and cost-effective action that can be employed to reduce one's risk of acquiring an infectious disease. This study indicates that there are societal differences that put some individuals at higher risk of contracting infectious disease than others.

Non-pharmaceutical interventions during the COVID-19 pandemic: A review

Infectious diseases and human behavior are intertwined. On one side, our movements and interactions are the engines of transmission. On the other, the unfolding of viruses might induce changes to our daily activities. While intuitive, our understanding of such feedback loop is still limited. Before COVID-19 the literature on the subject was mainly theoretical and largely missed validation. The main issue was the lack of empirical data capturing behavioral change induced by diseases. Things have dramatically changed in 2020. Non-pharmaceutical interventions (NPIs) have been the key weapon against the SARS-CoV-2 virus and affected virtually any societal process. Travel bans, events cancellation, social distancing, curfews, and lockdowns have become unfortunately very familiar. The scale of the emergency, the ease of survey as well as crowdsourcing deployment guaranteed by the latest technology, several Data for Good programs developed by tech giants, major mobile phone providers, and other companies have allowed unprecedented access to data describing behavioral changes induced by the pandemic. Here, I review some of the vast literature written on the subject of NPIs during the COVID-19 pandemic. In doing so, I analyze 348 articles written by more than 2518 authors in the first 12 months of the emergency. While the large majority of the sample was obtained by querying PubMed, it includes also a hand-curated list. Considering the focus, and methodology I have classified the sample into seven main categories: epidemic models, surveys, comments/perspectives, papers aiming to quantify the effects of NPIs, reviews, articles using data proxies to measure NPIs, and publicly available datasets describing NPIs. I summarize the methodology, data used, findings of the articles in each category and provide an outlook highlighting future challenges as well as opportunities.

Behaviours and attitudes in response to the COVID-19 pandemic: insights from a cross-national Facebook survey

BACKGROUND

In the absence of medical treatment and vaccination, individual behaviours are key to curbing the spread of COVID-19. Here we describe efforts to collect attitudinal and behavioural data and disseminate insights to increase situational awareness and inform interventions.

METHODS

We developed a rapid data collection and monitoring system based on a cross-national online survey, the "COVID-19 Health Behavior Survey". Respondent recruitment occurred via targeted Facebook advertisements in Belgium, France, Germany, Italy, the Netherlands, Spain, the United Kingdom, and the United States. We investigated how the threat perceptions of COVID-19, the confidence in the preparedness of organisations to deal with the pandemic, and the adoption of preventive and social distancing behaviours are associated with respondents' demographic characteristics.

RESULTS

We analysed 71,612 questionnaires collected between March 13-April 19, 2020. We found substantial spatio-temporal heterogeneity across countries at different stages of the pandemic and with different control strategies in place. Respondents rapidly adopted the use of face masks when they were not yet mandatory. We observed a clear pattern in threat perceptions, sharply increasing from a personal level to national and global levels. Although personal threat perceptions were comparatively low, all respondents significantly increased hand hygiene. We found gender-specific patterns: women showed higher threat perceptions, lower confidence in the healthcare system, and were more likely to adopt preventive behaviours. Finally, we also found that older people perceived higher threat to themselves, while all respondents were strongly concerned about their family.

CONCLUSIONS

Rapid population surveys conducted via Facebook allow us to monitor behavioural changes, adoption of protective measures, and compliance with recommended practices. As the pandemic progresses and new waves of infections are a threatening reality, timely insights from behavioural and attitudinal data are crucial to guide the decision-making process.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1140/epjds/s13688-021-00270-1.

Can pollen explain the seasonality of flu-like illnesses in the Netherlands?

Current models for flu-like epidemics insufficiently explain multi-cycle seasonality. Meteorological factors alone, including the associated behavior, do not predict seasonality, given substantial climate differences between countries that are subject to flu-like epidemics or COVID-19. Pollen is documented to be allergenic, it plays a role in immuno-activation and defense against respiratory viruses, and seems to create a bio-aerosol that lowers the reproduction number of flu-like viruses. Therefore, we hypothesize that pollen may explain the seasonality of flu-like epidemics, including COVID-19, in combination with meteorological variables. We have tested the Pollen-Flu Seasonality Theory for 2016-2020 flu-like seasons, including COVID-19, in the Netherlands, with its 17.4 million inhabitants. We combined changes in flu-like incidence per 100 K/Dutch residents (code: ILI) with pollen concentrations and meteorological data. Finally, a predictive model was tested using pollen and meteorological threshold values, inversely correlated to flu-like incidence. We found a highly significant inverse correlation of r(224) = -0.41 (p < 0.001) between pollen and changes in flu-like incidence, corrected for the incubation period. The correlation was stronger after taking into account the incubation time. We found that our predictive model has the highest inverse correlation with changes in flu-like incidence of r(222) = -0.48 (p < 0.001) when average thresholds of 610 total pollen grains/m³, 120 allergenic pollen grains/m³, and a solar radiation of 510 J/cm² are passed. The passing of at least the pollen thresholds, preludes the beginning and end of flu-like seasons. Solar radiation is a co-inhibitor of flu-like incidence, while temperature makes no difference. However, higher relative humidity increases with flu-like incidence. We conclude that pollen is a predictor of the inverse seasonality of flu-like epidemics, including COVID-19, and that solar radiation is a co-inhibitor, in the Netherlands.

[Effects of the Covid-19 Restrictions on Supermarket Visits in Germany]

Hintergrund  Die in Deutschland ab Mitte März verhängten Ausgangsbeschränkungen hinterließen in vielen Bereichen des öffentlichen Lebens deutliche Spuren. Während das Vermeiden sozialer Kontakte in vielen Bereichen durchaus möglich war, blieb die Versorgung mit Lebensmitteln der Verantwortung der privaten Haushalte überlassen.

Ziel der Arbeit  Die vorliegende Arbeit untersucht, ob und inwiefern die Beschränkungen zu Veränderungen hinsichtlich der Besuche von Supermärkten mit Personenkraftwagen geführt haben.

Material und Methoden  Zur Verfügung stehen Daten über die Parkbewegungen von 136 Parkplätzen von Supermärkten in Deutschland zwischen Anfang Februar und Ende Mai. Im Fokus der Analysen stehen Veränderungen der Gesamtzahl an Parkvorgängen pro Tag und Stellplatz sowie deren Dauer.

Ergebnisse  Mit Blick auf die Parkvorgänge zeigt sich eine deutliche Reduktion bis Ende April, unterbrochen durch einen temporären Anstieg um die Osterfeiertage. Nach Einführung der Maskenpflicht erholen sich die Werte wieder bis knapp unter das Vorniveau. Die Parkdauer verändert sich nur vergleichsweise wenig. Sie sinkt mit den Beschränkungen, steigt jedoch später leicht über das Niveau vor den Beschränkungen. Mittelfristig ist eine leichte Reduzierung der Parkvorgänge und eine Verlängerung ihrer Dauer um jeweils gut 5% zu beobachten.

Schlussfolgerung  Trotz ausdrücklicher Ausnahme der Einkäufe von Lebensmitteln von den Ausgangsbeschränkungen zeigt sich auch in diesem Bereich ein dynamisches Anpassungsverhalten der Bevölkerung an die sich verändernden Gegebenheiten. Ein dauerhafter Effekt auf die Einkaufsgewohnheiten scheint gemessen an den Parkbewegungen unwahrscheinlich.

Parental beliefs and willingness to pay for reduction in their child's asthma symptoms: A joint estimation approach

Many aspects of asthma-in particular the relationship between beliefs, averting behaviors, and symptoms-are not directly observable from market data. An approach that combines observable market data with nonmarket valuation to gather data on unobservable aspects of the illness can improve efforts to quantify the burden of asthma if it accounts for the endogeneity in the system. Such approaches are used in the valuation of recreation but have not been widely used to value the burden of a chronic illness. We estimate parents' willingness to pay (WTP) to reduce their child's asthma symptoms using a three-equation model that combines revealed preference, contingent valuation, and burden of asthma, increasing the efficiency of estimation and correcting for endogeneity. WTP for a device that reduces a child's asthma symptoms by 50% is $125/month (s.d. $20). Parents' valuations are driven by beliefs about asthma and by their degree of worry about asthma between episodes. There is a nonlinear relationship between the number of days with symptoms and WTP per symptom day. The experience of living with asthma affects families' responses to a contingent valuation scenario, because it influences willingness to spend money to manage the illness and their subjective perceptions and beliefs about the illness itself.

Collective Response to Media Coverage of the COVID-19 Pandemic on Reddit and Wikipedia: Mixed-Methods Analysis

BACKGROUND

The exposure and consumption of information during epidemic outbreaks may alter people's risk perception and trigger behavioral changes, which can ultimately affect the evolution of the disease. It is thus of utmost importance to map the dissemination of information by mainstream media outlets and the public response to this information. However, our understanding of this exposure-response dynamic during the COVID-19 pandemic is still limited.

OBJECTIVE

The goal of this study is to characterize the media coverage and collective internet response to the COVID-19 pandemic in four countries: Italy, the United Kingdom, the United States, and Canada.

METHODS

We collected a heterogeneous data set including 227,768 web-based news articles and 13,448 YouTube videos published by mainstream media outlets, 107,898 user posts and 3,829,309 comments on the social media platform Reddit, and 278,456,892 views of COVID-19-related Wikipedia pages. To analyze the relationship between media coverage, epidemic progression, and users' collective web-based response, we considered a linear regression model that predicts the public response for each country given the amount of news exposure. We also applied topic modelling to the data set using nonnegative matrix factorization.

RESULTS

Our results show that public attention, quantified as user activity on Reddit and active searches on Wikipedia pages, is mainly driven by media coverage; meanwhile, this activity declines rapidly while news exposure and COVID-19 incidence remain high. Furthermore, using an unsupervised, dynamic topic modeling approach, we show that while the levels of attention dedicated to different topics by media outlets and internet users are in good accordance, interesting deviations emerge in their temporal patterns.

CONCLUSIONS

Overall, our findings offer an additional key to interpret public perception and response to the current global health emergency and raise questions about the effects of attention saturation on people's collective awareness and risk perception and thus on their tendencies toward behavioral change.

Pollen likely seasonal factor in inhibiting flu-like epidemics. A Dutch study into the inverse relation between pollen counts, hay fever and flu-like incidence 2016-2019

There is uncertainty if current models for the Covid-19 pandemic should already take into account seasonality. That is because current environmental factors do not provide a powerful explanation of such seasonality, especially given climate differences between countries with moderate climates. It is hypothesized that one major factor is overlooked: pollen count. Pollen are documented to invoke strong immune responses and might create an environmental factor that makes it more difficult for flu-like viruses to survive outside a host. This Dutch study confirms that there is a (highly) significant inverse correlation between pollen count and weekly changes in medical flu consults, and that there is a highly significant inverse correlation between hay fever incidence, as measured by prescribed medication revenues, and weekly flu consults. This supports the idea that pollen are a direct or indirect factor in the seasonality of flu-like epidemics. If seasonality will be observed during the covid-19 spread as well, it is not unlikely that pollen play a role.