Crises social sensing: longitudinal monitoring of social perceptions of systemic risk during public health crisis

Monitoring how different people–as ‘social sensors'–evaluate and respond to crisis such as pandemics, allows tailoring crisis communication to the social perceptions of the situation, at different moments. To gather such evidence, we proposed a index of social perceptions of systemic risk (SPSR), as an indicator of a situational threat compromising risks to physical health, psychological health, the economy, social relations, health system, and others. This indicator was the core of a social sensing approach applied to crisis situations, implemented during the COVID-19 pandemic through a content analysis of more than 130.000 public comments from Facebook™ users, in COVID-19 related publications. This content coding allowed creating a SPSR index monitored during a one-year descriptive longitudinal analysis. This index correlated with co-occurring events within the social system, namely epidemiological indicators across measurement cycles (e.g. new deaths;cumulative number of infection cases;Intensive Care Unit hospitalizations) and tended to reflect the epidemiological situation severity (e.g. with the highest level registered during the worst pandemic wave). However, discrepancies also occurred, with high SPSR registered in a low severity situation, i.e. low number of hospitalizations and deaths (e.g. school year beginning), or low SPSR in a high severity situation (e.g. 2nd pandemic wave during Christmas), showing other factors beyond the epidemiological situation contributing to the social perceptions. After each ‘crisis period' with SPSR peaking, there was a ‘restoration period', consistently decreasing towards average levels of the previous measurement cycle. This can either indicate social resilience (recovery and resources potentiation) or risk attenuation after a high-severity period. This study serves as preliminary proof of concept of a crises social sensing approach, enabling monitoring of social system dynamics for various crisis types, such as health crisis or the climate crisis. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

How can fear impact economic decisions in pandemic contexts at the light of decision-making systems? An approach to the COVID-19 case

Fear is an important emotion in contexts of uncertainty. With the spread of COVID-19 disease, the process of decision making in the day-to-day economic life is studied considering the way in which fear can impact these decisions in the pandemic context. Our study analyses the situation in Brazil, the way fear can emerge through a process of communication, particularly involving the media. It is possible to conclude about the importance of studying the impact of fear in this context of pandemic, by observing that fear is involved when individuals make non-optimal decisions in such a process of decision-making systems. Copyright © 2022 Inderscience Enterprises Ltd.

Striving for crisis resolution or crisis resilience? The crisis layers and thresholds model and Information and Communication Technology-mediated social sensing for evidence-based crisis management and communication

Do crisis evolve linearly through sequential one-directional stages that end with their resolution? Or are crisis, a set of nonlinear events with somewhat a chaotic nature, better represented as multilayer relapse cycles, that is, a series of dynamic processes and templates that evolve at different levels of analysis and can either go forward—achievement—or go back—relapses? Moreover, should crisis always move forward to reach their resolution or should we strive to achieve social systems resilience, grounded on learning and adaptation processes, that is, moving forward and backwards, until achieving it? To argument in favor of achieving crisis resilience, we propose a theoretical model—the crisis layers and thresholds (CLT) model grounded on the following assumptions: (a) individuals' evaluations and responses should be the basis/core of crisis management and crisis communication activities;(b) different concurrent psychosocial and organizational processes occur at different levels of analysis of a crisis, from a microindividual level to a macro organization level;and (c) rather than striving for crisis resolution, we should strive for crisis resilience, preparing the social system for current and future emerging risks and crisis. To implement effective evidence-based crisis management and crisis communication in line with such assumptions, we also propose the CLT-ResiliScence approach, an Information and Communication Technology-mediated crisis sensing approach. This is based on monitoring “social sensors” data, particularly from social media, as an important source of information. Examples of this will be provided based on research on the current COVID-19 pandemic. © 2020 Wiley Periodicals LLC

Covid-19, economy and the ‘drop of honey effect’ metaphor – A note on the Portuguese case. Situation and measures

Covid-19 appeared in Wuhan (China), by December 2019 and rapidly spread to the rest of the world. Many countries adopted measures against its spread to protect people and national healthcare services. However, at the moment, more than 2.5 million people got infected and more than 175 thousand died in the 213 countries, areas and territories reached by the disease (official records at April 23, 2020). Countries began to adopt also measures to protect the economy and to prepare the economic recovery, once the effects are tremendous worldwide. In Portugal, measures allowed a flattered curve for Covid-19 spread. In this paper, we use an analogy to the ‘drop of honey effect’ to show how this curve develops. The ‘drop of honey effect’ is studied in terms of chaos theory and dynamic systems and is used as a framework to the way systems change in social phenomena. Copyright © 2021 Inderscience Enterprises Ltd.

Epidemics and pandemics: Covid-19 and the "The Drop of Honey Effect"

Purpose: The aim of this paper is the use of the "drop of honey effect" to explain the spread of Covid-19. Approach/Methodology/Design: After Covid-19 appearance in Wuhan, in the Chinese province of Hubei, by December, 2019, it spread all over the world. The World Health Organization declared it as pandemic in March 11, 2020. The infection is highly contagious and made thousands of deaths around the world. Timely decisions are key for the control of the dissemination. The "drop of honey effect" results as an important framework to explain the Covid-19 spread. Findings: An opportune decision in a very initial moment could have made all the difference in the virus spread. Practical Implications: The study will contribute positively to the understanding of the importance of well-timed decisions for governments, world organizations, academia, companies and people, each one on a different dimension's level. Consequences in the public health, and in the social, economic and financial dimensions were tremendous worldwide. Originality/Value: This study presents the "drop of honey effect" as an original and very suitable framework to explain the way how the virus spread all over the world after the virus in Wuhan began to infect people. © 2020 International Strategic Management Association. All rights reserved.

Covid-19, Chaos theory and the “drop of honey effect”. Viruses and human behavior

The paper applies the “drop of honey effect” to the Covid-19 disease’s spread and to the timing for acting. The timing and level of the adopted measures are considered crucial in terms of the virus spread and of the health consequences for populations. The study allows to conclude that a small difference in the adoption of the most proper measures in the initial moment, as much as the measures’ level, may make all the difference in the consequences of the disease and in its pandemic effects, what is valid not only for the first moment after the disease appearance in China but also after its arrival to each country. The “drop of honey effect” is perfect to explain the way how this coronavirus spread all over the world after its detection in humans and to explain its effects. The consequences on the public health were devastating, with thousands of deaths. Also the social, economic and financial implications around the world were enormous, particularly with many stock exchanges declining severely as coronavirus spread. © 2020 Ascociacion Internacional de Economia Aplicada. All rights reserved.