Poorly known aspects of flattening the curve of COVID-19

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Latin America and the Caribbean: Longitudinal Trend Analysis

BACKGROUND

In May 2020, the World Health Organization (WHO) declared Latin America and the Caribbean (LAC) the epicenter of the COVID-19 pandemic, with over 40% of worldwide COVID-19-related deaths at the time. This high disease burden was a result of the unique circumstances in LAC.

OBJECTIVE

This study aimed to (1) measure whether the pandemic was expanding or contracting in LAC when the WHO declared the end of COVID-19 as a public health emergency of international concern on May 5, 2023; (2) use dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history; and (3) provide, with a focus on prevention policies, a historical context for the course of the pandemic in the region.

METHODS

In addition to updates of traditional surveillance data and dynamic panel estimates from the original study, we used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern (VOCs). We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Additionally, we conducted a 1-sided t test for whether the regional weekly speed (rate of novel COVID-19 transmission) was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data across the period from August 2020 to May 2023.

RESULTS

The speed of pandemic spread for the region had remained below the outbreak threshold for 6 months by the time of the WHO declaration. Acceleration and jerk were also low and stable. Although the 1- and 7-day persistence coefficients remained statistically significant for the 120-day period ending on the week of May 5, 2023, the coefficients were relatively modest in magnitude (0.457 and 0.491, respectively). Furthermore, the shift parameters for either of the 2 most recent weeks around May 5, 2023, did not indicate any change in this clustering effect of cases on future cases. From December 2021 onward, Omicron was the predominant VOC in sequenced viral samples. The rolling t test of speed=10 became entirely insignificant from January 2023 onward.

CONCLUSIONS

Although COVID-19 continues to circulate in LAC, surveillance data suggest COVID-19 is endemic in the region and no longer reaches the threshold of the pandemic definition. However, the region experienced a high COVID-19 burden in the early stages of the pandemic, and prevention policies should be an immediate focus in future pandemics. Ahead of vaccination development, these policies can include widespread testing of individuals and an epidemiological task force with a contact-tracing system.

Linkage role of ICT and Big Data in COVID-19: a case of Korea’s digital and social communication practices

Purpose

This paper aims to discuss characteristics of Korea’s system responses with a research framework of the structure, conduct and performance theory and explain the role of information, communication technologies (ICT) and Big Data from a technology-mediated control (TMC) perspective.

Design/methodology/approach

This study examines the contextual nature of Korea’s diagnostic, preventive and treatment efforts. Particular attention is paid to issues related to the effective use of Big Data analytics and its applications, reporting mechanisms and public safety measures. The research model defines key factors in assessing the effectiveness of Korea’s responses.

Findings

Findings of this research suggest: effective strategic planning and operational execution use well-tested and designed crisis-responsive manuals; linkage role of ICT/Big Data is prominent in trace, test and treat and participation (3T + P); and aggressive epidemic investigations require synergistic efforts of national and local government units, broad societal support and participation and contribution of global firms offering their domestic and global supply chain network capabilities.

Research limitations/implications

The Korean Government's effective response experiences suggest the synergy of political, social, cultural and technological factors. Future studies may explore how personal privacy and public safety are both achieved in different social–cultural–political contexts (Ahn et al., 2020; Delgado et al., 2020; Sharma and Bashir, 2020). Other emerging organizational issues and international comparative studies are worth further investigation in future studies.

Practical implications

This case study suggests how to apply ICT capabilities for organizing a national response to the coronavirus pandemic (COVID-19) pandemic. Public and private partnership in the framework of sociotechnological synergy (i.e. integration of ICT and social orchestration) is essential for the 3T process. In support of public policy initiatives, global firms share their IT infrastructure and supply chain integration experiences to accommodate global-level crises like the COVID-19 pandemic.

Social implications

This study extends the TMC framework to a national level. In the adapted TMC framework, the control source, control target and linkage mechanism are specified. Using TMC, this shows the dynamic roles of ICT/Big Data in Korea’s COVID-19 response experiences.

Originality/value

The impacts of the COVID-19 are rapid and enormous. Despite the controversial early policy decisions and the rapid rise of confirmed patients, the world has recognized Korea’s effective responses to the COVID-19 pandemic.

The role of religiosity in product and technology acceptance: Evidence from COVID-19 vaccines

Previous research on religion and economic phenomena has suggested that religious attitudes are related to risk aversion. Moreover, risk attitudes play a significant role in the adoption and diffusion of technological innovations. However, the role of religiosity in technology-related phenomena is still relatively unexplored. The present study fills this gap and investigates the impact of religiosity on the acceptance of innovative technologies and products in the context of the COVID-19 pandemic. Specifically, we frame COVID-19 vaccines as new products based on innovative production technologies and show that their acceptance by the general public is negatively associated with country-level religiosity. Furthermore, we investigate the role of religious leaders in endorsing COVID-19 vaccines to their followers. Our hypotheses are empirically tested on 1179 weekly observations of vaccination rates in 22 European countries characterised by different levels of religiosity. The results suggest that religiosity is negatively associated with vaccine rates after controlling for country-level social and economic factors. Conversely, the countries where Roman Catholics are the majority religious group display a positive association between religiosity and vaccine rates, highlighting the role of leaders in endorsing the COVID-19 vaccination campaign.

Five common misconceptions regarding flattening-the-curve of COVID-19

In the fight against COVID-19 pandemic, the phrase "Flattening the curve" (FTC) has become a rallying cry, popularized by government leaders and journalist in the news and on the social media. FTC is a succinct way of communicating an important public health message that physical distancing, mask-wearing and other public health measures will decrease the peak number of cases and prevent the healthcare system from being overwhelmed. However, while the message of FTC is right in the sense that limiting transmission will reduce the peak number of cases, some visualizations used to illustrate its effect are incorrect from an infectious disease modelling point of view. The misconceptions are misinterpretations of flattened curves, the effect of FTC on the duration of the pandemic, the dynamics of the curve to be flattened, and the overestimation of the importance of FTC.

Convex-Concave fitting to successively updated data and its application to covid-19 analysis

Let n measurements of a process be provided sequentially, where the process follows a sigmoid shape, but the data have lost sigmoidicity due to measuring errors. If we smooth the data by making least the sum of squares of errors subject to one sign change in the second divided differences, then we obtain a sigmoid approximation. It is known that the optimal fit of this calculation is composed of two separate sections, one best convex and one best concave. We propose a method that starts at the beginning of the data and proceeds systematically to construct the two sections of the fit for the current data, step by step as n is increased. Although the minimization calculation at each step may have many local minima, it can be solved in about O ( n 2 ) operations, because of properties of the join between the convex and the concave section. We apply this method to data of daily Covid-19 cases and deaths of Greece, the United States of America and the United Kingdom. These data provide substantial differences in the final approximations. Thus, we evaluate the performance of the method in terms of its capabilities as both constructing a sigmoid-type approximant to the data and a trend detector. Our results clarify the optimization calculation both in a systematic manner and to a good extent. At the same time, they reveal some features of the method to be considered in scenaria that may involve predictions, and as a tool to support policy-making. The results also expose some limitations of the method that may be useful to future research on convex-concave data fitting.

COVID-19 Management Missteps

In December 2019, the first case of a novel coronavirus infectious disease, coronavirus disease 2019 (COVID-19), was identified in the province of Wuhan, China. Since the initial identification on March 11, 2020, by the World Health Organization (WHO), COVID-19 had rapidly spread all over the world, leading to the declaration of COVID-19 as a pandemic. In response to the exponential trend of reported confirmed cases, national governments worked quickly to devise plans to combat the spread and to soften the consequences which were to follow. Two primary approaches included limiting the spread of the virus and increasing hospital capacity. The implementation of these strategies, however, varied greatly among different governments and their respective populations.

Countries developed similar guidelines in response to COVID-19, but with a variation. Many of these guidelines were similar in that they fell under the same general topics such as the use of facial masks, social distancing, and online learning. The effect of COVID-19 on public health was more reliant on the implementation of these recommendations rather than the recommendations themselves. 

The medical therapies used to treat the widespread COVID-19 disease are flourishing and evolving rapidly. Ongoing research shows that the spectrum of treatment for COVID-19 varies from pharmacological and non-pharmacological therapeutic interventions. Some of the treatments that are being used in clinical practice include supportive care, antiviral drugs, immunomodulatory agents, convalescent plasma transfusion, and monoclonal antibody treatments. In addition, the most promising approach thus far is the COVID-19 vaccine developed by Pfizer-BioNTech, Moderna, and most recently Johnson & Johnson. Overall, as various treatment approaches are being explored and administered to people globally, it is important to acknowledge that there is currently no definite cure or any evidence-based treatment for COVID-19. 

COVID-19 infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have brought devastating consequences to the lives of millions of people through their health effects and the failure of global initiatives to contain it. A review of many missteps that potentially could have altered the landscape for this virus to affect the lives of many is discussed with hope for a better approach going forward. 

On the global time evolution of the Covid-19 pandemic: Logistic modeling

In this article it is presented a multi-logistic model to describe the time evolution of the Covid-19 pandemics. The model is not intended as paragon for the accurate prediction of the future number of people infected, but instead as a useful phenomenological approach for a comprehensive understanding of the pandemic development, able to uncover some hidden aspects of its unfolding. Our results, using OWID data of total cases and daily cases of Covid-19 from March 12, 2020, up to September 27, 2021, brought to light that the pandemic has unfolded globally as a multi-step logistic, namely six logistic phases, each with its own characteristic duration and intensity. Moreover, it is demonstrated how differently the pandemics spread among different countries and continents. The methodology is tested regarding its ability of forecasting, and is demonstrated that it works well in the range of circa 30 days within a margin of less than 3% error while a given phase is still in development. The case study of Portugal demonstrates the benefit of preventive sanitary measures, as well as shows how disastrous it may be the absence of such measures due to hesitations and/or political positions. Completing the article, a qualitative analysis is presented to scrutinize the possible causes of the asymmetry observed in the diffusion of Covid-19 among the different continents and countries.

Corporate immunity, national culture and stock returns: Startups amid the COVID-19 pandemic

Small and medium-sized firms, particularly startups, are highly vulnerable to the COVID-19 pandemic because of their financial instability. Using a sample of listed startups across four countries, we investigate whether a startup's built-up capacity pre-COVID-19 can stimulate corporate immunity to endure the impact of the COVID-19 pandemic, reflected via stock performance. We find that the increase in the accumulated COVID-19 confirmed cases worsens stock returns and that the negative effect is alleviated if startups are greater in size as well as have low debt, large board size and CEO duality. Moreover, national cultural dimensions significantly moderate the relationship between stock returns and COVID-19. The COVID-19 negative impact is relieved in societies where people are more collectivistic and cooperative, less tolerant towards uncertainty, and more long-term oriented. Overall, our results support the consolidation of corporate capacities and suggest policymakers consider national culture when formulating COVID-19 or similar infectious pandemic strategies.

Decision Making in Health Management during Crisis: A Case Study Based on Epidemiological Curves of China and Italy against COVID-19

In December 2019, a new infectious respiratory disease called COVID-19 was identified in Wuhan, Hubei province, in China and quickly reached pandemic status in March 2020, in uncertain and frightening situation. The objective of this study was to analyze the epidemiological curves from the fight against COVID-19 in China and Italy, establishing parameters that can assist with the decisions of health-planning managers. This study was conducted using the principles of the grounded theory methodology and a practical method of comparison between the real and ideal curves, based on the contamination and death data by SARS-CoV-2 in China and Italy. For this purpose, we built graphs, including parameters, such as, among others, amplitude, height, saturation point, acceleration, lethality, event, risk, and efficiency. The results of our study showed that China exhibited amplitude and height of the active contamination and death curve 2 times smaller than those of Italy which exhibited several saturations. It was investigated that Italy presented a qualitative risk of 5–6, whereas for China it was 4. According to the parameters, China and Italy presented health management that was able to reduce the impact caused by the virus. The implementation of adequate health management with these practical tools can guide perception of the crisis critical levels, avoiding major disasters. We intend to continue to validate the method in the analysis of data from Brazil and the USA.

Comment on "Poorly known aspects of flattening the curve of COVID-19″

This short research note describes and summarizes several recent peer-reviewed and non-peer-reviewed studies on the concept of flattening-the-curve (FTC) in the context of the COVID-19 pandemic. This note also highlights contradictory findings of these studies in terms of the effect of FTC on the total number of infections (the final epidemic size), and poses a research problem for future studies.

Forecasting COVID-19 pandemic: Unknown unknowns and predictive monitoring

During the current COVID-19 pandemic, there have been many efforts to forecast infection cases, deaths, and courses of development, using a variety of mechanistic, statistical, or time-series models. Some forecasts have influenced policies in some countries. However, forecasting future developments in the pandemic is fundamentally challenged by the innate uncertainty rooted in many "unknown unknowns," not just about the contagious virus itself but also about the intertwined human, social, and political factors, which co-evolve and keep the future of the pandemic open-ended. These unknown unknowns make the accuracy-oriented forecasting misleading. To address the extreme uncertainty of the pandemic, a heuristic approach and exploratory mindset is needed. Herein, grounded on our own COVID-19 forecasting experiences, I propose and advocate the "predictive monitoring" paradigm, which synthesizes prediction and monitoring, to make government policies, organization planning, and individual mentality heuristically future-informed despite the extreme uncertainty.