Abstract
When pharmaceutical interventions are unavailable to deal with an epidemic outbreak, adequate management of communication strategies can be key to reduce the contagion risks. On the one hand, accessibility to trustworthy and timely information, whilst on the other, the adoption of preventive behaviors may be both crucial. However, despite the abundance of communication strategies, their effectiveness has been scarcely evaluated or merely circumscribed to the scrutiny of public affairs. To study the influence of communication strategies on the spreading dynamics of an infectious disease, we implemented a susceptible-exposed-infected-removed-dead (SEIRD) epidemiological model, using an agent-based approach. Agents in our systems can obtain information modulating their behavior from two sources: (i) through the local interaction with other neighboring agents and, (ii) from a central entity delivering information with a certain periodicity. In doing so, we highlight how global information delivered from a central entity can reduce the impact of an infectious disease and how informing even a small fraction of the population has a remarkable impact, when compared to not informing the population at all. Moreover, having a scheme of delivering daily messages makes a stark difference on the reduction of cases, compared to the other evaluated strategies, denoting that daily delivery of information produces the largest decrease in the number of cases. Furthermore, when the information spreading relies only on local interactions between agents, and no central entity takes actions along the dynamics, then the epidemic spreading is virtually independent of the initial amount of informed agents. On top of that, we found that local communication plays an important role in an intermediate regime where information coming from a central entity is scarce. As a whole, our results highlight the importance of proper communication strategies, both accurate and daily, to tackle epidemic outbreaks.
Highlights
The spread of infectious diseases is nowadays an important health issue worldwide, killing about 8.5 million people yearly [1]
Main conclusions from this research area are summarized as follow: (i) human response depends on the specific disease being dispersed together with social, cultural, political, and economic factors characterizing the population in which the disease spread; (ii) appropriate data is required to identify human behaviours that are key to regulate the spread of the disease; (iii) agent models are suitable tools to study the effect of behavioral changes on a population under an epidemic situation; and (iv), social media and massive data strategies should be both considered at the moment of fitting and feeding models with real data [28]
Several authors have discussed this issue suggesting that including heterogeneity is desirable when modeling the dynamics of epidemic outbreaks [32, 69,70,71]
Summary
The spread of infectious diseases is nowadays an important health issue worldwide, killing about 8.5 million people yearly [1]. The broad and diverse impact of the COVID-19 pandemic around the world has demonstrated that human behavior [2,3,4] and communication [5,6,7] are both key components in the propagation, control [8, 9], and mitigation of epidemics [10], specially in the absence of pharmaceutical interventions. Despite this certainty, the actual relationship between communication and human behavior still remains unclear. While vaccine coverage to deal with the COVID-19 pandemic remains low, for developing countries, the existence of an actual Behavioral Immune System in the population is one of the best protective front lines we can rely on
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