Dynamics And Control Of Foot-And-Mouth Disease In Endemic Countries: A Pair Approximation Model

The final publication is available at Elsevier via http://dx.doi.org/10.1016/j.jtbi.2014.05.010 © 2014. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/Previous mathematical models of spatial farm-to-farm transmission of foot and mouth disease (FMD) have explored the impacts of control measures such as culling and vaccination during a single outbreak in a country normally free of FMD. As a result, these models do not include factors that are relevant to countries where FMD is endemic in some regions, like long-term waning natural and vaccine immunity, use of prophylactic vaccination and disease re-importations. These factors may have implications for disease dynamics and control, yet few models have been developed for FMD-endemic settings. Here we develop and study an SEIRV (susceptible-exposed-infectious-recovered-vaccinated) pair approximation model of FMD. We focus on long term dynamics by exploring characteristics of repeated outbreaks of FMD and their dependence on disease re-importation, loss of natural immunity, and vaccine waning. We find that the effectiveness of ring and prophylactic vaccination strongly depends on duration of natural immunity, rate of vaccine waning, and disease re-introduction rate. However, the number and magnitude of FMD outbreaks are generally more sensitive to the duration of natural immunity than the duration of vaccine immunity. If loss of natural immunity and/or vaccine waning happen rapidly, then multiple epidemic outbreaks result, making it difficult to eliminate the disease. Prophylactic vaccination is more effective than ring vaccination, at the same per capita vaccination rate. Finally, more frequent disease re-importation causes a higher cumulative number of infections, although a lower average epidemic peak. Our analysis demonstrates significant differences between dynamics in FMD-free settings versus FMD-endemic settings, and that dynamics in FMD-endemic settings can vary widely depending on factors such as the duration of natural and vaccine immunity and the rate of disease re-importations. We conclude that more mathematical models tailored to FMD-endemic countries should be developed that include these factors

Bounded rationality alters the dynamics of paediatric immunization acceptance

Interactions between disease dynamics and vaccinating behavior have been explored in many coupled behavior-disease models. Cognitive effects such as risk perception, framing, and subjective probabilities of adverse events can be important determinants of the vaccinating behaviour, and represent departures from the pure “rational” decision model that are often described as “bounded rationality”. However, the impact of such cognitive effects in the context of paediatric infectious disease vaccines has received relatively little attention. Here, we develop a disease-behavior model that accounts for bounded rationality through prospect theory. We analyze the model and compare its predictions to a reduced model that lacks bounded rationality. We find that, in general, introducing bounded rationality increases the dynamical richness of the model and makes it harder to eliminate a paediatric infectious disease. In contrast, in other cases, a low cost, highly efficacious vaccine can be refused, even when the rational decision model predicts acceptance. Injunctive social norms can prevent vaccine refusal, if vaccine acceptance is sufficiently high in the beginning of the vaccination campaign. Cognitive processes can have major impacts on the predictions of behaviourdisease models, and further study of such processes in the context of vaccination is thus warranted

Coupling Fishery Dynamics, Human Health And Social Learning In A Model Of Fish-Borne Pollution Exposure

The final publication is available at Springer via http://dx.doi.org/10.1007/s11625-015-0317-5Pollution-induced illnesses are caused by toxicants that result from human activity and are often entirely preventable. However, where industrial priorities have undermined responsible governance, exposed populations must reduce their exposure by resorting to voluntary protective measures and demanding emissions abatement. This paper presents a coupled human-environment system model that represents the effects of water pollution on the health and livelihood of a fishing community. The model is motivated by an incident from 1949 to 1968 in Minamata, Japan, where methylmercury effluent from a local factory poisoned fish populations and humans who ate them. We model the critical role of risk perception in driving both social learning and the protective feedbacks against pollution exposure. These feedbacks are undermined in the presence of social misperceptions such as stigmatization of the injured. Through numerical simulation and scenario analysis, we compare our model results with historical datasets from Minamata, and find that the conditions for an ongoing pollution epidemic are highly unlikely without social misperception. We also find trade-offs between human health outcomes, the viability of the polluting industry and the survival of the fishery. We conclude that an understanding of human-environment interactions and misperception effects is highly relevant to the resolution of contemporary pollution problems, and merits further study.Ontario Graduate Scholarship progra

The Influence Of Social Norms On The Dynamics Of Vaccinating Behaviour For Paediatric Infectious Diseases

Definitive version as published available at: Oraby, T., Thampi, V., & Bauch, C. T. (2014). The influence of social norms on the dynamics of vaccinating behaviour for paediatric infectious diseases. Proceedings of the Royal Society B: Biological Sciences, 281(1780), 20133172–20133172., http://dx.doi.org/10.1098/rspb.2013.3172Mathematical models that couple disease dynamics and vaccinating behaviour often assume that the incentive to vaccinate disappears if disease prevalence is zero. Hence, they predict that vaccine refusal should be the rule, and elimination should be difficult or impossible. In reality, countries with non-mandatory vaccination policies have usually been able to maintain elimination or very low incidence of paediatric infectious diseases for long periods of time. Here, we show that including injunctive social norms can reconcile such behaviour-incidence models to observations. Adding social norms to a coupled behaviour-incidence model enables the model to better explain pertussis vaccine uptake and disease dynamics in the UK from 1967 to 2010, in both the vaccine-scare years and the years of high vaccine coverage. The model also illustrates how a vaccine scare can perpetuate suboptimal vaccine coverage long after perceived risk has returned to baseline, pre-vaccine-scare levels. However, at other model parameter values, social norms can perpetuate depressed vaccine coverage during a vaccine scare well beyond the time when the population's baseline vaccine risk perception returns to pre-scare levels. Social norms can strongly suppress vaccine uptake despite frequent outbreaks, as observed in some small communities. Significant portions of the parameter space also exhibit bistability, meaning long-term outcomes depend on the initial conditions. Depending on the context, social norms can either support or hinder immunization goals

Strategic Decision-making about Travel during Disease Outbreaks: a Game Theoretical Approach

This is an accepted manuscript that has been accepted for publication by the Royal Society in the Journal of the Royal Society Interface and is made available under the following terms: https://royalsociety.org/journals/ethics-policies/media-embargo/Visitors can play an important role in the spread of infections. Here, we incorporate an epidemic model into a game theoretical framework to investigate the effects of travel strategies on infection control. Potential visitors must decide whether to travel to a destination that is at risk of infectious disease outbreaks. We compare the individually optimal (Nash equilibrium) strategy to the group optimal strategy that maximizes the overall population utility. Economic epidemiological models often find that individual and group optimal strategies are very different. In contrast, we find perfect agreement between individual and group optimal strategies across a wide parameter regime. For more limited regimes where disagreement does occur, the disagreement is (1) generally very extreme; (2) highly sensitive to small changes in infection transmissibility and visitor costs/benefits; and (3) can manifest either in a higher travel volume for individual optimal than group optimal strategies, or vice versa. The simulations show qualitative agreement with the 2003 Severe Acute Respiratory Syndrome (SARS) outbreak in Beijing, China. We conclude that a conflict between individual and group optimal visitor travel strategies during outbreaks may not generally be a problem, although extreme differences could emerge suddenly under certain changes in economic and epidemiological conditions.Early Career Scheme grant from the Hong Kong Research 343 Grant Council || PolyU 251001/14

Estimating the COVID-19 R number: a bargain with the devil?

The basic reproduction number R0 is the average number of infections produced by a single infectious person in a population with no immunity. R0 has a close relative named the effective reproduction number R: the average number of infections produced by a single infected person in a population with partial immunity. In The Lancet Infectious Diseases2, Li and colleagues estimate how the imposition and lifting of non-pharmaceutical interventions (NPIs) changed the R number for SARS-CoV-2 in 131 countries in the first half of 2020

Coevolution Of Risk Perception, Sexual Behaviour, And Hiv Transmission In An Agent-Based Model

The final publication is available at Elsevier via http://dx.doi.org/10.1016/j.jtbi.2013.08.014 © 2013. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/Risk perception shapes individual behaviour, and is in turn shaped by the consequences of that behaviour. Here we explore this dynamics in the context of human immunodeficiency virus (HIV) spread. We construct a simplified agent-based model based on a partner selection game, where individuals are paired with others in the population, and through a decision tree, agree on unprotected sex, protected sex, or no sex. An individual's choice is conditioned on their HIV status, their perceived population-level HIV prevalence, and the preferences expressed by the individual with whom they are paired. HIV is transmitted during unprotected sex with a certain probability As expected, in model simulations, the perceived population-level HIV prevalence climbs along with actual HIV prevalence. During this time, HIV individuals increasingly switch from unprotected sex to protected sex, HIV+ individuals continue practicing unprotected sex whenever possible, and unprotected sex between HIV+ and HIV individuals eventually becomes rare. We also find that the perceived population-level HIV prevalence diverges according to HIV status: HIV individuals develop a higher perceived HIV prevalence than HIV+ individuals, although this result is sensitive to how much information is derived from global versus local sources. This research illustrates a potential mechanism by which distinct groups, as defined by their sexual behaviour, HIV status, and risk perceptions, can emerge through coevolution of HIV transmission and risk perception dynamics.CIHR Operating GrantNSERC Discovery Gran