"Wait and see" vaccinating behaviour during a pandemic: a game theoretic analysis

Effect of homophily on coupled behavior-disease dynamics near a tipping point

Understanding the interplay between social activities and disease dynamics is crucial for effective public health interventions. Recent studies using coupled behavior-disease models assumed homogeneous populations. However, heterogeneity in population, such as different social groups, cannot be ignored. In this study, we divided the population into social media users and non-users, and investigated the impact of homophily (the tendency for individuals to associate with others similar to themselves) and online events on disease dynamics. Our results reveal that homophily hinders the adoption of vaccinating strategies, hastening the approach to a tipping point after which the population converges to an endemic equilibrium with no vaccine uptake. Furthermore, we find that online events can significantly influence disease dynamics, with early discussions on social media platforms serving as an early warning signal of potential disease outbreaks. Our model provides insights into the mechanisms underlying these phenomena and underscores the importance of considering homophily in disease modeling and public health strategies.

Determinants of COVID-19 vaccine uptake: evidence from a vulnerable global South setting

OBJECTIVE

Studies are paying increasing attention to complex social determinants in explaining the variation in the rates COVID-19 vaccine uptake. This study examines the influence of various individual, contextual, and vaccine-related factors on COVID-19 vaccine uptake behaviour in a resource-scarce and vulnerable setting using a quantitative research approach. Using a multi-staged cluster sampling approach, 408 individuals from 204 households in Cape Coast, Ghana's tourism hub, were surveyed. Probit and logistic regression models were estimated to test the vaccine-related factors.

RESULTS

A significant difference is observed between wait time and vaccination status (χ2 = 21.17; p = 0.000). Moreover, age and religion, as controlled variables, equally played significant roles in influencing the adoption of the vaccine. Other factors encompass the perceived risk of contracting COVID-19, the perceived benefits of the vaccine in relation to its side effects, and the level of trust individuals have in the concern of vaccine producers for their health. These findings call for targeted campaigns by the Ministry of Health, health facilities and other institutions promoting the COVID-19 vaccine. These actors should emphasize the benefits of vaccination, prioritize trust-building initiatives, and provide clear guidance on vaccination schedules, and manage waiting time.

Timing of preventive behavior in the case of a new and evolving health risk: the case of COVID-19 vaccination

BACKGROUND

Time preferences for preventive behavior under novel risks and uncertain contexts may differ from timing preferences related to familiar risks. Therefore, it is crucial to examine drivers of preventative health behavior timing in light of new health risks. Using the case of COVID-19, we examine factors affecting vaccination timing plans when vaccines were widely available in the European Union (EU).

METHODS

We use data from the Flash Eurobarometer 494 survey (May 21-26, 2021), which collected information on EU residents' attitudes towards COVID-19 vaccinations. We also use the 'Our World in Data' vaccination database for country-level COVID-19 vaccination rates. Probit regressions were conducted to determine how local vaccination rates, trust in information sources, social norms, vaccine safety beliefs, and risk understanding affected the probability of COVID-19 vaccination delay.

RESULTS

Of total participants (n = 26,106), 9,063 (34.7%) were vaccinated, 7,114 (27.3%) wanted to get vaccinated as soon as possible, 5,168 (19.8%) wanted to delay vaccination and 2,962 (11.4%) resisted vaccination. Participants were more likely to delay COVID-19 vaccination if they lived in a country with lower vaccination prevalence, trusted online social networks, family, friends, and colleagues for vaccination information, were eager to follow vaccination-related social norms, expressed vaccine safety concerns, and understood the risk of catching COVID-19 without a vaccine to be lower.

CONCLUSIONS

Results from the study contribute to understanding important factors that predict timing of vaccination plans. These findings can also contribute to the wider knowledge base about timing of preventive behavior uptake in novel risk contexts.

Impact of voluntary testing on infectious disease epidemiology: A game theoretic approach

The World Health Organization recommends test-and-treat interventions to curb and even eliminate epidemics of HIV, viral hepatitis, and sexually transmitted infections (e.g., chlamydia, gonorrhea, syphilis and trichomoniasis). Epidemic models show these goals are achievable, provided the participation of individuals in test-and-treat interventions is sufficiently high. We combine epidemic models and game theoretic models to describe individual's decisions to get tested for infectious diseases within certain epidemiological contexts, and, implicitly, their voluntary participation to test-and-treat interventions. We develop three hybrid models, to discuss interventions against HIV, HCV, and sexually transmitted infections, and the potential behavioral response from the target population. Our findings are similar across diseases. Particularly, individuals use three distinct behavioral patterns relative to testing, based on their perceived costs for testing, besides the payoff for discovering their disease status. Firstly, if the cost of testing is too high, then individuals refrain from voluntary testing and get tested only if they are symptomatic. Secondly, if the cost is moderate, some individuals will test voluntarily, starting treatment if needed. Hence, the spread of the disease declines and the disease epidemiology is mitigated. Thirdly, the most beneficial testing behavior takes place as individuals perceive a per-test payoff that surpasses a certain threshold, every time they get tested. Consequently, individuals achieve high voluntary testing rates, which may result in the elimination of the epidemic, albeit on temporary basis. Trials and studies have attained different levels of participation and testing rates. To increase testing rates, they should provide each eligible individual with a payoff, above a given threshold, each time the individual tests voluntarily.

Herding behavior in COVID-19 vaccine hesitancy in rural Zimbabwe: The moderating role of health information under heterogeneous household risk perceptions

COVID-19 vaccine hesitancy poses a global health threat by potentially delaying the attainment of herd immunity to attenuate infection and transmission. Most governments across the world are engrossed with formulating strategies to surmount conservative group behavior such as vaccine hesitancy typical under risky and uncertain situations such as in the case of COVID-19. This paper examines herding behavior in vaccine hesitancy with a special focus on the moderating role of household access to health information from village health workers under different risk perceptions. We use the 2021 Zimbabwe Vulnerability Assessment Committee cross-section household national survey consisting of 13, 583 valid observations. Our major findings indicate that herding behavior plays a role in rural households' hesitancy to COVID-19 vaccine inoculation. Furthermore, whilst access to health information from village health workers reduces herding behavior in vaccine hesitancy, it does so more when the household perceives itself to be at high risk of contracting COVID-19. Analysing herding behavior in vaccine hesitancy can help policymakers develop more targeted vaccination strategies, such as promoting access to health information through channels like village health workers, especially for households at high risk of contracting COVID-19.

COVID-19 vaccine incentive scheduling using an optimally controlled reinforcement learning model

We model Covid-19 vaccine uptake as a reinforcement learning dynamic between two populations: the vaccine adopters, and the vaccine hesitant. Using data available from the Center for Disease Control (CDC), we estimate the payoff matrix governing the interaction between these two groups over time and show they are playing a Hawk-Dove evolutionary game with an internal evolutionarily stable Nash equilibrium (the asymptotic percentage of vaccinated in the population). We then ask whether vaccine adoption can be improved by implementing dynamic incentive schedules that reward/punish the vaccine hesitant, and if so, what schedules are optimal and how effective are they likely to be? When is the optimal time to start an incentive program, how large should the incentives be, and is there a point of diminishing returns? By using a tailored replicator dynamic reinforcement learning model together with optimal control theory, we show that well designed and timed incentive programs can improve vaccine uptake by shifting the Nash equilibrium upward in large populations, but only so much, and incentive sizes above a certain threshold show diminishing returns.

Factors Associated With the Vaccination Behavior Among COVID-19 Vaccine Hesitant College Students in Wuhan, China: A Survey Based on Social Psychological Dimension

Background

During the COVID-19 pandemic, vaccine hesitancy (VH) on COVID-19 vaccination still exists in different populations, which has a negative impact on epidemic prevention and control. The objectives were to explore college students' willingness to vaccinate, determine the factors influencing the vaccination behavior of students with COVID-19 vaccine hesitancy, and provide a basis for improving the compliance of college students with COVID-19 vaccination.

Methods

The universities in Wuhan are categorized into three levels according to their comprehensive strength and randomly sampled at each level, of which ten universities were selected. A self-designed anonymous electronic questionnaire was distributed online from May 12 to 31, 2021 to investigate the hesitancy, vaccination status, and influencing factors of COVID-19 vaccination among college students in Wuhan.

Results

Of the 1,617 participants (1,825 students received the electronic questionnaire) surveyed, 19.0% reported COVID-19 vaccine hesitancy. Among the vaccine-hesitant students, 40.1% were vaccinated against COVID-19. The binary logistic regression analysis shows that families' attitudes "Uncertain" (odds ratio (OR) = 0.258 [0.132-0.503]), vaccination risk psychology (OR = 0.242 [0.079-0.747]) and wait-and-see mentality (OR = 0.171 [0.068-0.468]) are negative factors for the vaccination behavior of hesitant students, while herd mentality (OR = 7.512 [2.718-20.767]) and uncertainty of free policy's impact on vaccine trust (OR = 3.412 [1.547-7.527]) are positive factors.

Conclusion

The vaccine hesitancy among college students in Wuhan was relatively high. Family support, herd mentality and free vaccination strategies can help improve vaccination among hesitant students, while vaccination risk psychology and "wait-and-see" psychology reduce the possibility of vaccination. The vaccination strategy of college students should be strengthened from the perspective of social psychological construction.

Coordination and equilibrium selection in games: the role of local effects

We study the role of local effects and finite size effects in reaching coordination and in equilibrium selection in two-player coordination games. We investigate three update rules - the replicator dynamics (RD), the best response (BR), and the unconditional imitation (UI). For the pure coordination game with two equivalent strategies we find a transition from a disordered state to coordination for a critical value of connectivity. The transition is system-size-independent for the BR and RD update rules. For the IU it is system-size-dependent, but coordination can always be reached below the connectivity of a complete graph. We also consider the general coordination game which covers a range of games, such as the stag hunt. For these games there is a payoff-dominant strategy and a risk-dominant strategy with associated states of equilibrium coordination. We analyse equilibrium selection analytically and numerically. For the RD and BR update rules mean-field predictions agree with simulations and the risk-dominant strategy is evolutionary favoured independently of local effects. When players use the unconditional imitation, however, we observe coordination in the payoff-dominant strategy. Surprisingly, the selection of pay-off dominant equilibrium only occurs below a critical value of the network connectivity and disappears in complete graphs. As we show, it is a combination of local effects and update rule that allows for coordination on the payoff-dominant strategy.

Priming with social benefit information of vaccination to increase acceptance of COVID-19 vaccines

Vaccine hesitancy can be heightened due to increasing negative reports about vaccines. Emphasizing the social benefits of vaccination may shift individual attention from individual to social benefit of vaccination and hence promote prosocial vaccination. In six rounds of a population-based survey conducted over one major community epidemic of coronavirus disease 2019 (COVID-19) in Hong Kong from June to November 2020, we manipulated the question asking about acceptance of a COVID-19 vaccine with or without emphasizing the social benefit of vaccination against COVID-19 (prosocial priming) and monitored the changes of vaccine confidence by news media sentiment on vaccines. Population-weighted percentages of accepting COVID-19 vaccines by priming condition and vaccine confidence were compared across survey rounds. Logit regression models assessed the main effect of prosocial priming and the modification effects of vaccine confidence and perceived personal risk from COVID-19 on acceptance of COVID-19 vaccines. We found that prosocial priming significantly increased acceptance of COVID-19 vaccines across all survey rounds except for Round 3 when incidence of COVID-19 reached a peak. Vaccine confidence significantly declined in Round 6 when news media sentiment on vaccines became predominantly negative. The effect of prosocial priming on promoting vaccine acceptance was significantly greater in participants with low vaccine confidence and those perceiving the severity of COVID-19 to be mild/very mild. Our study suggests that packaging vaccination against COVID-19 as a prosocial behaviour can help overcome low vaccine confidence and promote prosocial vaccination particularly when disease incidence temporarily declines and the public perceive low severity of COVID-19.

Necessity of Social Distancing in Pandemic Control: A Dynamic Game Theory Approach

We model a society with two types of citizens: healthy and vulnerable individuals. While both types can be exposed to the virus and contribute to its spread, the vulnerable people tend to be more cautious as being exposed to the virus can be fatal for them due to their conditions, e.g., advanced age or prior medical conditions. We assume that both types would like to participate in in-person social activities as freely as possible and they make this decision based on the total number of infected people in the society. In this model, we assume that a local governmental authority imposes and administers social distancing regulations based on the infection status of the society and revises it accordingly in each time period. We model and solve for the steady state in four scenarios: (i) non-cooperative (Nash), (ii) cooperative, (iii) egoistic, and (iv) altruistic. The results show that the Altruistic scenario is the best among the four, i.e., the healthy citizens put the vulnerable citizens' needs first and self-isolate more strictly which results in more flexibility for the vulnerable citizens. We use a numerical example to illustrate that the Altruistic scenario will assist with pandemic control for both healthy and vulnerable citizens in the long run. The objective of this research is not to find a way to resolve the pandemic but to optimally live in a society which has been impacted by pandemic restrictions, similar to what was experienced in 2020 with the spread of COVID-19.

Vaccination intentions generate racial disparities in the societal persistence of COVID-19

We combined survey, mobility, and infections data in greater Boston, MA to simulate the effects of racial disparities in the inclination to become vaccinated on continued infection rates and the attainment of herd immunity. The simulation projected marked inequities, with communities of color experiencing infection rates 3 times higher than predominantly White communities and reaching herd immunity 45 days later on average. Persuasion of individuals uncertain about vaccination was crucial to preventing the worst inequities but could only narrow them so far because 1/5th of Black and Latinx individuals said that they would never vaccinate. The results point to a need for well-crafted, compassionate messaging that reaches out to those most resistant to the vaccine.

Vaccinated or not? Survey on attitude toward 'approach-avoidance conflict' under uncertainty

Vaccinated or not? This is an attitude survey for ‘approach-avoidance conflict’ under uncertainty. Therefore, measuring people’s attitude toward COVID-19 vaccination is relatively distinctive from an attitude over a general conflict. An online survey of 3123 respondents from 30 provincial-level regions — out of 31 — on the Chinese mainland was conducted from January 22 to 27, 2021 to measure their willingness to be vaccinated. We found that over half of the respondents chose the options ‘not to be vaccinated now’ and ‘wait and see before making a vaccination decision,’ thereby indicating that people’s willingness to be vaccinated is not as optimistic as anticipated in the early stage of vaccination in China. Hence, investigators should carefully select the measuring method to assess the ‘true’ levels of willingness to accept COVID-19 vaccines. Lastly, the relevant departments should fully predict obstacles to achieve immunity coverage and prepare for the ‘vaccine hesitancy’ of people in need.

Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemic

Since the recent introduction of several viable vaccines for SARS-CoV-2, vaccination uptake has become the key factor that will determine our success in containing the COVID-19 pandemic. We argue that game theory and social network models should be used to guide decisions pertaining to vaccination programmes for the best possible results. In the months following the introduction of vaccines, their availability and the human resources needed to run the vaccination programmes have been scarce in many countries. Vaccine hesitancy is also being encountered from some sections of the general public. We emphasize that decision-making under uncertainty and imperfect information, and with only conditionally optimal outcomes, is a unique forte of established game-theoretic modelling. Therefore, we can use this approach to obtain the best framework for modelling and simulating vaccination prioritization and uptake that will be readily available to inform important policy decisions for the optimal control of the COVID-19 pandemic.

Game theoretic modelling of infectious disease dynamics and intervention methods: a review

We review research studies which use game theory to model the decision-making of individuals during an epidemic, attempting to classify the literature and identify the emerging trends in this field. The literature is classified based on (i) type of population modelling (classical or network-based), (ii) frequency of the game (non-repeated or repeated), and (iii) type of strategy adoption (self-learning or imitation). The choice of model is shown to depend on many factors such as the immunity to the disease, the strength of immunity conferred by the vaccine, the size of population and the level of mixing therein. We highlight that while early studies used classical compartmental modelling with self-learning games, in recent years, there is a substantial growth of network-based modelling with imitation games. The review indicates that game theory continues to be an effective tool to model decision-making by individuals with respect to intervention (vaccination or social distancing).

Optimal Management of Public Perceptions During A Flu Outbreak: A Game-Theoretic Perspective

Public perceptions and sentiments play a crucial role in the success of vaccine uptake in the community. While vaccines have proven to be the best preventive method to combat the flu, the attitude and knowledge about vaccines are a major hindrance to higher uptake in most of the countries. The yearly coverage, especially in the vulnerable groups in the population, often remains below the herd immunity level despite the Flu Awareness Campaign organized by WHO every year worldwide. This brings immense challenges to the nation's public health protection agency for strategic decision-making in controlling the flu outbreak every year. To understand the impact of public perceptions and vaccination decisions while designing optimal immunization policy, we model the individual decision-making as a two-strategy pairwise contest game, where pay-off is considered as a function of public health effort for the campaign. We use Pontryagin's maximum principle to identify the best possible strategy for public health to implement vaccination and reduce infection at a minimum cost. Our optimal analysis shows that the cost of public health initiatives is qualitatively and quantitatively different under different public perceptions and attitudes towards vaccinations. When individual risk perception evolves with vaccine uptake or disease induced death, our model demonstrates a feed-forward mechanism in the dynamics of vaccination and exhibits an increase in vaccine uptake. Using numerical simulation, we also observe that the optimal cost can be minimized by putting the effort in the beginning and later part of the outbreak rather than during the peak. It confers that public health efforts towards disseminating disease severity or actual vaccination risk might accelerate the vaccination coverage and mitigate the infection faster.

Decisions and disease: a mechanism for the evolution of cooperation

In numerous contexts, individuals may decide whether they take actions to mitigate the spread of disease, or not. Mitigating the spread of disease requires an individual to change their routine behaviours to benefit others, resulting in a 'disease dilemma' similar to the seminal prisoner's dilemma. In the classical prisoner's dilemma, evolutionary game dynamics predict that all individuals evolve to 'defect.' We have discovered that when the rate of cooperation within a population is directly linked to the rate of spread of the disease, cooperation evolves under certain conditions. For diseases which do not confer immunity to recovered individuals, if the time scale at which individuals receive accurate information regarding the disease is sufficiently rapid compared to the time scale at which the disease spreads, then cooperation emerges. Moreover, in the limit as mitigation measures become increasingly effective, the disease can be controlled; the number of infections tends to zero. It has been suggested that disease spreading models may also describe social and group dynamics, indicating that this mechanism for the evolution of cooperation may also apply in those contexts.

What influenza vaccination programmes are preferred by healthcare personnel? A discrete choice experiment

OBJECTIVES

This study examined the relative importance of factors relating to vaccine characteristics, social normative influence and convenience in access to vaccine for determining decision making for seasonal influenza vaccination (SIV) among healthcare personnel (HCP), aiming to optimize existing influenza vaccination programmes for HCP.

METHODS

A discrete choice experiment (DCE) was conducted in HCP working in public hospitals in Hong Kong. The DCE was designed to examine the relative importance of vaccine characteristics (vaccine efficacy and safety), social normative influence reflected by the proportion of HCP colleagues intending to take SIV, and convenience in access to vaccine indicated by vaccination programme duration, vaccination location, vaccination arrangement procedure and service hours in determining influenza vaccination choice among HCP. Mixed logit regression modelling was conducted to examine the preference weight (β) of factors included in the DCE for determining vaccination choice.

RESULTS

Vaccination probability increased with increase in vaccine efficacy (β = 0.02 for per 1% increase), vaccination location changing from "designated staff clinic" to "mobile station" (β = 0.37), vaccination arrangement procedure changing from "by appointment" to "by walk-in" (β = 0.99), but decreased with the increase in probability of mild reactions to vaccination (β = -0.05 for per 1% increase).

CONCLUSION

Vaccine safety was judged to be more important than vaccine efficacy for determining vaccination choice. Arranging vaccination service by walk-in and implementing mobile vaccination station should be considered in future SIV programmes to compensate for the effect of perceived low vaccination efficacy and concerns about vaccine safety to promote SIV uptake among HCP.

Using experimental gaming simulations to elicit risk mitigation behavioral strategies for agricultural disease management

Failing to mitigate propagation of disease spread can result in dire economic consequences for agricultural networks. Pathogens like Porcine Epidemic Diarrhea virus, can quickly spread among producers. Biosecurity is designed to prevent infection transmission. When considering biosecurity investments, management must balance the cost of protection versus the consequences of contracting an infection. Thus, an examination of the decision making processes associated with investment in biosecurity is important for enhancing system wide biosecurity. Data gathered from experimental gaming simulations can provide insights into behavioral strategies and inform the development of decision support systems. We created an online digital experiment to simulate outbreak scenarios among swine production supply chains, where participants were tasked with making biosecurity investment decisions. In Experiment One, we quantified the risk associated with each participant's decisions and delineated three dominant categories of risk attitudes: risk averse, risk tolerant, and opportunistic. Each risk class exhibited unique approaches in reaction to risk and disease information. We also tested how information uncertainty affects risk aversion, by varying the amount of visibility of the infection as well as the amount of biosecurity implemented across the system. We found evidence that more visibility in the number of infected sites increases risk averse behaviors, while more visibility in the amount of neighboring biosecurity increased risk taking behaviors. In Experiment Two, we were surprised to find no evidence for differences in behavior of livestock specialists compared to Amazon Mechanical Turk participants. Our findings provide support for using experimental gaming simulations to study how risk communication affects behavior, which can provide insights towards more effective messaging strategies.

The impact of rare but severe vaccine adverse events on behaviour-disease dynamics: a network model

The propagation of rumours about rare but severe adverse vaccination or infection events through social networks can strongly impact vaccination uptake. Here we model a coupled behaviour-disease system where individual risk perception regarding vaccines and infection are shaped by their personal experiences and the experiences of others. Information about vaccines and infection either propagates through the network or becomes available through globally available sources. Dynamics are studied on a range of network types. Individuals choose to vaccinate according to their personal perception of risk and information about infection prevalence. We study events ranging from common and mild, to severe and rare. We find that vaccine and infection adverse events have asymmetric impacts. Vaccine (but not infection) adverse events may significantly prolong the tail of an outbreak. Similarly, introducing a small risk of a vaccine adverse event may cause a steep decline in vaccine coverage, especially on scale-free networks. Global dissemination of information about infection prevalence boosts vaccine coverage more than local dissemination. Taken together, these findings highlight the dangers associated with vaccine rumour propagation through scale-free networks such as those exhibited by online social media, as well as the benefits of disseminating public health information through mass media.

Individual decisions to vaccinate one's child or oneself: A discrete choice experiment rejecting free-riding motives

It is essential for public health to understand what drives people's hesitance towards vaccination. Theoretical models of vaccination decisions are ubiquitous, often incorporating herd immunity, perceptions of vaccine-related side-effects (VRSE) and of vaccine-preventable burden of disease, but with little to no empirical exploration. Herd immunity is a (usually) positive externality where vaccinated individuals influence others' risks by their reduced capability to transmit an infectious disease to them. It is often assumed that (rational) individuals incorporate this externality in their strategic vaccination decision, from which free-riding behavior arises. We performed a Bayesian D-efficient discrete choice experiment in February-March 2017 to study vaccination behavior in 1919 Belgian respondents. Choice sets with vaccine profiles were constructed using six attributes: vaccine effectiveness, VRSE, accessibility (in terms of convenience and reimbursement), vaccine-preventable burden of disease, local (respondents' network of contacts) vaccination coverage, and population (the population at large) vaccination coverage. VRSE and accessibility are the most influential attributes, followed by vaccine effectiveness and burden of disease. Both population and local coverage are less important than the other attributes, but show a significant direct linear relationship with vaccine utility. This supports the existence of peer influence (more incentivized as more and more vaccinate), rather than free-riding on herd immunity. These findings were independent of whether respondents made vaccine choices for themselves or for their child. Around 40% of the respondents indicated accepting vaccination with little or no questioning. These 'acceptors' were less sensitive to changes in the vaccine-preventable burden of disease for their child's vaccination choices (but not for themselves). Public health institutions are critical in stimulating vaccine uptake by making vaccines conveniently available at an affordable price and by communicating pro-actively on perceived VRSEs. The free-riding assumption as a driver of individual vaccine decisions, seems inappropriate, but this observation needs confirming in other populations.

Infection prevention behaviour and infectious disease modelling: a review of the literature and recommendations for the future

Background

Given the importance of person to person transmission in the spread of infectious diseases, it is critically important to ensure that human behaviour with respect to infection prevention is appropriately represented within infectious disease models. This paper presents a large scale scoping review regarding the incorporation of infection prevention behaviour in infectious disease models. The outcomes of this review are contextualised within the psychological literature concerning health behaviour and behaviour change, resulting in a series of key recommendations for the incorporation of human behaviour in future infectious disease models.

Methods

The search strategy focused on terms relating to behaviour, infectious disease and mathematical modelling. The selection criteria were developed iteratively to focus on original research articles that present an infectious disease model with human-human spread, in which individuals’ self-protective health behaviour varied endogenously within the model. Data extracted included: the behaviour that is modelled; how this behaviour is modelled; any theoretical background for the modelling of behaviour, and; any behavioural data used to parameterise the models.

Results

Forty-two papers from an initial total of 2987 were retained for inclusion in the final review. All of these papers were published between 2002 and 2015. Many of the included papers employed a multiple, linked models to incorporate infection prevention behaviour. Both cognitive constructs (e.g., perceived risk) and, to a lesser extent, social constructs (e.g., social norms) were identified in the included papers. However, only five papers made explicit reference to psychological health behaviour change theories. Finally, just under half of the included papers incorporated behavioural data in their modelling.

Conclusions

By contextualising the review outcomes within the psychological literature on health behaviour and behaviour change, three key recommendations for future behavioural modelling are made. First, modellers should consult with the psychological literature on health behaviour/ behaviour change when developing new models. Second, modellers interested in exploring the relationship between behaviour and disease spread should draw on social psychological literature to increase the complexity of the social world represented within infectious disease models. Finally, greater use of context-specific behavioural data (e.g., survey data, observational data) is recommended to parameterise models.

Electronic supplementary material

The online version of this article (10.1186/s12889-018-5223-1) contains supplementary material, which is available to authorized users.

Voluntary vaccination dilemma with evolving psychological perceptions

Voluntary vaccination is a universal control protocol for infectious diseases. Yet there exists a social dilemma between individual benefits and public health: non-vaccinators free ride via the herd immunity from adequate vaccinators who bear vaccination cost. This is due to the interplay between disease prevalence and individual vaccinating behavior. To complicate matters further, individual vaccinating behavior depends on the perceived vaccination cost rather than the actual one. The perception of vaccination cost is an individual trait, which varies from person to person, and evolves in response to the disease prevalence and vaccination coverage. To explore how evolving perception shapes individual vaccinating behavior and thus the vaccination dynamics, we provide a model combining epidemic dynamics with evolutionary game theory which captures the voluntary vaccination dilemma. In particular, individuals adjust their perception based on the inertia effect in psychology and then update their vaccinating behavior through imitating the behavior of a more successful peer. We find that i) vaccination is acceptable when the expected vaccination cost considering perception and actual vaccination cost is less than the maximum of the expected non-vaccination cost; ii) the evolution of perception is a "double-edged sword" for vaccination dynamics: it can improve vaccination coverage when most individuals perceive exaggerated vaccination cost, and it inhibits vaccination coverage in the other cases.

Prevention of treatable infectious diseases: A game-theoretic approach

We model outcomes of voluntary prevention using an imperfect vaccine, which confers protection only to a fraction of vaccinees for a limited duration. Our mathematical model combines a single-player game for the individual-level decision to get vaccinated, and a compartmental model for the epidemic dynamics. Mathematical analysis yields a characterization for the effective vaccination coverage, as a function of the relative cost of prevention versus treatment; note that cost may involve monetary as well as non-monetary aspects. Three behaviors are possible. First, the relative cost may be too high, so individuals do not get vaccinated. Second, the relative cost may be moderate, such that some individuals get vaccinated and voluntary vaccination alleviates the epidemic. In this case, the vaccination coverage grows steadily with decreasing relative cost of vaccination versus treatment. Unlike previous studies, we find a third case where relative cost is sufficiently low so epidemics may be averted through the use of prevention, even for an imperfect vaccine. However, we also found that disease elimination is only temporary-as no equilibrium exists for the individual strategy in this third case-and, with increasing perceived cost of vaccination versus treatment, the situation may be reversed toward the epidemic edge, where the effective reproductive number is 1. Thus, maintaining relative cost sufficiently low will be the main challenge to maintain disease elimination. Furthermore, our model offers insight on vaccine parameters, which are otherwise difficult to estimate. We apply our findings to the epidemiology of measles.

Global stability of infectious disease models with contact rate as a function of prevalence index

In this paper, we consider a SEIR epidemiological model with information--related changes in contact patterns. One of the main features of the model is that it includes an information variable, a negative feedback on the behavior of susceptible subjects, and a function that describes the role played by the infectious size in the information dynamics. Here we focus in the case of delayed information. By using suitable assumptions, we analyze the global stability of the endemic equilibrium point and disease--free equilibrium point. Our approach is applicable to global stability of the endemic equilibrium of the previously defined SIR and SIS models with feedback on behavior of susceptible subjects.

Dueling biological and social contagions

Numerous models explore how a wide variety of biological and social phenomena spread in social networks. However, these models implicitly assume that the spread of one phenomenon is not affected by the spread of another. Here, we develop a model of “dueling contagions”, with a particular illustration of a situation where one is biological (influenza) and the other is social (flu vaccination). We apply the model to unique time series data collected during the 2009 H1N1 epidemic that includes information about vaccination, flu, and face-to-face social networks. The results show that well-connected individuals are more likely to get vaccinated, as are people who are exposed to friends who get vaccinated or are exposed to friends who get the flu. Our dueling contagion model suggests that other epidemiological models may be dramatically underestimating the R₀ of contagions. It also suggests that the rate of vaccination contagion may be even more important than the biological contagion in determining the course of the disease. These results suggest that real world and online platforms that make it easier to see when friends have been vaccinated (personalized vaccination campaigns) and when they get the flu (personalized flu warnings) could have a large impact on reducing the severity of epidemics. They also suggest possible benefits from understanding the coevolution of many kinds of dueling contagions.

Behavioural change models for infectious disease transmission: a systematic review (2010-2015)

We review behavioural change models (BCMs) for infectious disease transmission in humans. Following the Cochrane collaboration guidelines and the PRISMA statement, our systematic search and selection yielded 178 papers covering the period 2010-2015. We observe an increasing trend in published BCMs, frequently coupled to (re)emergence events, and propose a categorization by distinguishing how information translates into preventive actions. Behaviour is usually captured by introducing information as a dynamic parameter (76/178) or by introducing an economic objective function, either with (26/178) or without (37/178) imitation. Approaches using information thresholds (29/178) and exogenous behaviour formation (16/178) are also popular. We further classify according to disease, prevention measure, transmission model (with 81/178 population, 6/178 metapopulation and 91/178 individual-level models) and the way prevention impacts transmission. We highlight the minority (15%) of studies that use any real-life data for parametrization or validation and note that BCMs increasingly use social media data and generally incorporate multiple sources of information (16/178), multiple types of information (17/178) or both (9/178). We conclude that individual-level models are increasingly used and useful to model behaviour changes. Despite recent advancements, we remain concerned that most models are purely theoretical and lack representative data and a validation process.

The impacts of simultaneous disease intervention decisions on epidemic outcomes

Mathematical models of the interplay between disease dynamics and human behavioural dynamics can improve our understanding of how diseases spread when individuals adapt their behaviour in response to an epidemic. Accounting for behavioural mechanisms that determine uptake of infectious disease interventions such as vaccination and non-pharmaceutical interventions (NPIs) can significantly alter predicted health outcomes in a population. However, most previous approaches that model interactions between human behaviour and disease dynamics have modelled behaviour of these two interventions separately. Here, we develop and analyze an agent based network model to gain insights into how behaviour toward both interventions interact adaptively with disease dynamics (and therefore, indirectly, with one another) during the course of a single epidemic where an SIRV infection spreads through a contact network. In the model, individuals decide to become vaccinated and/or practice NPIs based on perceived infection prevalence (locally or globally) and on what other individuals in the network are doing. We find that introducing adaptive NPI behaviour lowers vaccine uptake on account of behavioural feedbacks, and also decreases epidemic final size. When transmission rates are low, NPIs alone are as effective in reducing epidemic final size as NPIs and vaccination combined. Also, NPIs can compensate for delays in vaccine availability by hindering early disease spread, decreasing epidemic size significantly compared to the case where NPI behaviour does not adapt to mitigate early surges in infection prevalence. We also find that including adaptive NPI behaviour strongly mitigates the vaccine behavioural feedbacks that would otherwise result in higher vaccine uptake at lower vaccine efficacy as predicted by most previous models, and the same feedbacks cause epidemic final size to remain approximately constant across a broad range of values for vaccine efficacy. Finally, when individuals use local information about others' behaviour and infection prevalence, instead of population-level information, infection is controlled more efficiently through ring vaccination, and this is reflected in the time evolution of pair correlations on the network. This model shows that accounting for both adaptive NPI behaviour and adaptive vaccinating behaviour regarding social effects and infection prevalence can result in qualitatively different predictions than if only one type of adaptive behaviour is modelled.

Individual Vaccination as Nash Equilibrium in a SIR Model with Application to the 2009-2010 Influenza A (H1N1) Epidemic in France

The vaccination against ongoing epidemics is seldom compulsory but remains one of the most classical means to fight epidemic propagation. However, recent debates concerning the innocuity of vaccines and their risk with respect to the risk of the epidemic itself lead to severe vaccination campaign failures, and new mass behaviors appeared driven by individual self-interest. Prompted by this context, we analyze, in a Susceptible-Infected-Recovered model, whether egocentric individuals can reach an equilibrium with the rest of the society. Using techniques from the "Mean Field Games" theory, we extend previous results and show that an equilibrium exists and characterizes completely the individual best vaccination strategy (with or without discounting). We also compare with a strategy based only on overall societal optimization and exhibit a situation with nonnegative price of anarchy. Finally, we apply the theory to the 2009-2010 Influenza A (H1N1) vaccination campaign in France and hint that a group of individuals stopped vaccinating at levels that indicated a pessimistic perception of the risk of the vaccine.

Conflicts of interest during contact investigations: a game-theoretic analysis

The goal of contact tracing is to reduce the likelihood of transmission, particularly to individuals who are at greatest risk for developing complications of infection, as well as identifying individuals who are in need of medical treatment of other interventions. In this paper, we develop a simple mathematical model of contact investigations among a small group of individuals and apply game theory to explore conflicts of interest that may arise in the context of perceived costs of disclosure. Using analytic Kolmogorov equations, we determine whether or not it is possible for individual incentives to drive noncooperation, even though cooperation would yield a better group outcome. We found that if all individuals have a cost of disclosure, then the optimal individual decision is to simply not disclose each other. With further analysis of (1) completely offsetting the costs of disclosure and (2) partially offsetting the costs of disclosure, we found that all individuals disclose all contacts, resulting in a smaller basic reproductive number and an alignment of individual and group optimality. More data are needed to understand decision making during outbreak investigations and what the real and perceived costs are.

Predictors of the timing of vaccination uptake: The 2009 influenza pandemic (H1N1) in Montreal

BACKGROUND

In response to the 2009 H1N1 influenza pandemic, Canada undertook the largest vaccination campaign in its history. The effort mobilized thousands of healthcare workers, cost many hundreds of millions of dollars, and vaccinated more than 40% of the population. Despite the large investment in mass vaccination internationally, little is known about the factors that drive the timing of vaccination uptake.

PURPOSE

Data from 2009 were used to investigate three potential determinants of vaccination uptake in Montreal, Canada.

METHODS

Poisson regression was used to analyze daily vaccination before and after a telephone intervention targeting households in 12 of the city's 29 health neighborhoods. The effect of an eligibility strategy based on risk groups, and of weather, on uptake was then estimated. Data were analyzed in 2013.

RESULTS

Considerable variation in daily mass vaccination was observed, with the peak day (30,204 individuals) accounting for nearly five times the uptake of the slowest day (6298 individuals). No evidence was found that the telephone intervention led to a significant increase in vaccination. Daily vaccination was associated significantly with weather conditions, including mean temperature (relative risk [RR]=1.28, 95% CI=1.12, 1.46) and heavy precipitation (RR=0.63, 95% CI=0.45, 0.89), even after accounting for changes to eligibility, which also were associated with increased vaccination.

CONCLUSIONS

Considerable temporal variation in uptake can occur during mass vaccination efforts. Targeted interventions to increase vaccination should be evaluated further, as a large intervention had no observable effect. Mass vaccination campaigns should, however, attempt to optimize priority sequences and account for weather when estimating vaccine demand.

Conscious consideration of herd immunity in influenza vaccination decisions

BACKGROUND

Influenza vaccination decisions may be influenced by perceived risk reduction related to herd immunity.

PURPOSE

This paper examines how free-riding (i.e., foregoing vaccination because of reduced risk perceptions related to herd immunity) or protective benefits to the community affect vaccination decisions.

METHODS

A survey of a nationally representative panel of U.S. adults (N=442 respondents; data collected and analyzed during 2012) asked about how respondents made vaccination decisions, including whether and how vaccination among the members of respondents' social networks influenced their own vaccination decisions.

RESULTS

Most individuals (61%) reported that vaccination in the social network would not influence their decision. Among those perceiving being influenced by vaccination in their social network, most stated that an increase in network vaccination coverage would make them more likely to get vaccinated, rather than less. Overall, only 6% (28 of 442) gave a response consistent with the reduced-risk logic of herd immunity, which was more common among those stating that they would be less likely to get vaccinated (emphasizing free-riding) than among those more likely to get vaccinated (emphasizing social protection; 33% vs 11%, two-sided, p=0.0005). The reduced-risk logic of herd immunity, and more specifically free-riding, is consciously considered by relatively few individuals. Far more common are social influences bolstering personal vaccination, such as peer pressure and social learning (6% vs 11%, two-sided, p=0.015).

CONCLUSIONS

Interventionists may be more successful by capitalizing on existing social-influence considerations than by trying to combat the conscious lure of free-riding.

Vaccination, herd behavior, and herd immunity

BACKGROUND

During the 2009 outbreak of novel influenza AH1N1, insufficient data were available to adequately inform decision makers about benefits and risks of vaccination and disease. We hypothesized that individuals would opt to mimic their peers, having no better decision anchor. We used Game Theory, decision analysis, and transmission models to simulate the impact of subjective risks and preference estimates on vaccination behavior.

METHODS

We asked 95 students to provide estimates of risk and health state valuations with regard to AH1N1 infection, complications, and expectations of vaccine benefits and risks. These estimates were included in a sequential chain of models: a dynamic epidemic model, a decision tree, and a population-level model. Additionally, participants' intentions to vaccinate or not at varying vaccination rates were documented.

RESULTS

The model showed that at low vaccination rates, vaccination dominated. When vaccination rates increased above 78%, nonvaccination was the dominant strategy. We found that vaccination intentions did not correspond to the shift in strategy dominance and segregated to 3 types of intentions: regardless of what others do 29/95 (31%) intended to vaccinate while 27/95 (28%) did not; among 39 of 95 (41%) intention was positively associated with putative vaccination rates.

CONCLUSIONS

Some people conform to the majority's choice, either shifting epidemic dynamics toward herd immunity or, conversely, limiting societal goals. Policy leaders should use models carefully, noting their limitations and theoretical assumptions. Behavior drivers were not explicitly explored in this study, and the discrepant results beg further investigation. Models including real subjective perceptions with empiric or subjective probabilities can provide insight into deviations from expected rational behavior and suggest interventions in order to provide better population outcomes.

Understanding the interplay of factors informing vaccination behavior in three Canadian provinces

Arguably, the two most critical components in any response to a pandemic are effective risk communication and the rapid development of a vaccine. Despite the roll-out of a publicly-funded H1N1 vaccine program across the country, less than half of all Canadians were vaccinated during the 2009-10 pandemic. Using focus group data, this study examined vaccinating behaviors, the impact of public health messaging, and the public's attitudes toward H1N1 and the H1N1 vaccine in three Canadian provinces. Drawing on vaccine risk communication literature, a framework was devised to identify and analyze the factors related to vaccine uptake and vaccine refusal. The most predictive factor for H1N1 vaccine uptake was a prior history of vaccinating against seasonal influenza. Other important factors included barriers to immunizing (access issues) and an individual's perception of serious risk from contracting H1N1. Although critical gaps in the public's understanding of influenza infections were identified, together with misinformation about vaccination effectiveness and safety, these factors were less frequently reported to be the core factors influencing an individual's decision to vaccinate.

Outcome inelasticity and outcome variability in behaviour-incidence models: an example from an SEIR infection on a dynamic network

Behavior-incidence models have been used to model phenomena such as free-riding vaccinating behavior, where nonvaccinators free ride on herd immunity generated by vaccinators. Here, we develop and analyze a simulation model of voluntary ring vaccination on an evolving social contact network. Individuals make vaccination decisions by examining their expected payoffs, which are influenced by the infection status of their neighbors. We find that stochasticity can make outcomes extremely variable (near critical thresholds) and thus unpredictable: some stochastic realizations result in rapid control through ring vaccination while others result in widespread transmission. We also explore the phenomenon of outcome inelasticity, wherein behavioral responses result in certain outcome measures remaining relatively unchanged. Finally, we explore examples where ineffective or risky vaccines are more widely adopted than safe, effective vaccines. This occurs when such a vaccine is unattractive to a sufficient number of contacts of an index case to cause failure of ring vaccination. As a result, the infection percolates through the entire network, causing the final epidemic size and vaccine coverage to be higher than would otherwise occur. Effects such as extreme outcome variability and outcome inelasticity have implications for vaccination policies that depend on individual choice for their success and predictability.

Acceptance on the move: public reaction to shifting vaccination realities

This review examines four events related to vaccination that have occurred in recent years: (a) the ongoing recovery from the MMR/Autism scare in the UK, (b) the upgrading of the Varicella vaccine to a universal childhood vaccine, (c) the major effort of authorities to provide a vaccine for A/H1N1 influenza and its rejection by the public, and, d) the current attempts to change the HPV vaccine target from girls only to boys and girls. All of these changes have been met with shifts in the public acceptance of the relevant vaccine. These shifts are characterized not only by the number of people willing to be vaccinated, but also by the attitudes and the motives related to acceptance. Examination of the interrelationship between changes in vaccination realities, and changes in acceptance patterns suggests that today, the public has a better understanding of vaccination, is acting in a more reflexive way, and is capable of changing attitudes and behavior. All together, changes in vaccination enhance debates and dialogues about vaccines, and lead to higher awareness and more conscious acceptance.