COVID-19 Curve Research Articles

COVID-19 as a National Security Issue in Malaysia: A Comparison with the Italian and Australian Perspectives

COVID-19 pandemic affects variations of countries’ national strategies, policies, and plans of actions while at the same time these arrangements afflicting their residents by implementing a variety of health and legal measures to flatten the COVID-19 curve. This stretches from prohibiting overseas travel, forbidding interstate travel, encouraging work from home closings of some public areas, compulsory wearing of marks and hand sanitisers, quarantine, social distancing, and a mixture of various actions. Malaysia in implementing its laws and regulations on COVID-19 is empowered mainly by the Prevention and Control of Infectious Diseases Act 1988 (Act 342) together with its newly imposed COVID-19 regulations and the old Police Act 1967 (Act 344). The movement control order coupled with the social distancing measures has appeared to be the effective actions in flattening the COVID-19 curve. The study attempts to map COVID-19 as a national security matter for the benefit of public health and national security concurrently within the scope and limits of Malaysia’s public health measures and prevention of diseases, in the protection of security and public order. This paper then proposed for COVID-19 and other future health crises or pandemics as national security issues. This in turn legitimising the health, security, or emergency measures, either developing on the existing laws or moving towards a more practical form of law in line with future unforeseeable threat and intervention. The Australian and Italian laws relating to COVID-19 are analysed to provide better insight and suggest solutions enabling countries facing a future emergency or crisis issues.
 
 Received: 4 March 2021 / Accepted: 6 May 2021 / Published: 8 July 2021

From Contact Prevention to Social Distancing: The Co-Evolution of Bilingual Neologisms and Public Health Campaigns in Two Cities in the Time of COVID-19

This article investigates the evolution of social distancing terms in Chinese and English in two geographically close yet culturally distinct metropolitan cities: Hong Kong and Guangzhou. This study of bilingual public health campaign posters during the COVID-19 pandemic focuses on how the evolution of neologisms and linguistic strategies in public health campaigns adapts to different societal contexts. A baseline meaning of the re-purposed linguistic expressions was established according to the BNC corpus for English and the Chinese Gigaword Corpus for Chinese. To establish the link between linguistic expressions and public health events, we converted them to eventive structures using the Module-Attribute Representation of Verbs and added interpersonal meaning interpretations based on Systemic Functional Linguistics. The two cities are found to have taken divergent approaches. Guangzhou prefers “contact prevention” with behavior-inhibiting imperatives and high value modality. Conversely, the original use of “contact prevention” in Hong Kong was gradually replaced by the neologism social distancing in English, triggering competing loan translations in Chinese. In Hong Kong, behavior-encouraging expressions are predominantly used with positive polarity and varying modality and mood devices, which fluctuate to track the epidemic curve of COVID-19. We conclude that lexical evolution interacts with social realities. Different speech acts, prohibition in Guangzhou but advice and warning in Hong Kong, are constructed with a careful bilingual reconfiguration of eventive information, mood, modality, and polarity to tactfully address the social dynamics in the two cities.

Post covid-19 public space adaption: a case study of building entrances in Jakarta

Recently, all public facilities in Jakarta have been affected by the Covid-19 pandemic; offices and retailers are closing their stores since the beginning of the outbreak, but the other facilities such as airports, train stations, and hospitals are still open while following the new normal protocols. Additionally, to help flatten the curve of Covid-19, buildings are taking transmission caution towards their facilities and interior spaces during the pandemic. This study’s main objective is to provide a review of the concepts of adaption within a building to the occurring issue of Covid-19. An entrance is the first gate or door to welcome customers, but unfortunately, buildings’ entrance areas are undergoing several adjustments of space and functions. In this research, the design thinking method is combined with qualitative analysis using tools such as benefits maps to help build competitive advantage and communication strategy, what kind of activities that give height, low benefit and how easy or difficult it might be to implement the strategy. This study concludes objectives in delivering new normal protocols within the building facility with a recommendation for entrance areas to provide several tools. Fulfilling the customer’s expectation is one way to increase the trust and a feeling of safety in customers’ perceptions. Entrance space adaption will also give customers a positive perception of the buildings when they enter the facility. Additionally, it will also give a long-term solution for the new normal protocols taking place. Finally, the eight concept activities could be utilized as a guideline and strategy for facility and building maintenance proposals to add value to facilities’ long-term solution.

Analysis of the comprehensive non-pharmaceutical interventions and measures in containing the COVID-19 epidemic in Shenzhen: a retrospective study

ObjectiveTo analyse the epidemiological characteristics of family clusters of COVID-19 and the three stages of the comprehensive non-pharmaceutical interventions and measures implemented in Shenzhen.MethodsThe epidemic curve of COVID-19 was drawn...

Optimising SARS-CoV-2 pooled testing strategies on social networks for low-resource settings

Controlling the COVID-19 pandemic is an urgent global challenge. The rapid geographic spread of SARS-CoV-2 directly reflects the social structure. Before effective vaccines and treatments are widely available, we have to rely on alternative, non-pharmaceutical interventions, including frequent testing, contact tracing, social distancing, mask wearing, and hand-washing, as public health practises to slow down the spread of the disease. However, frequent testing is the key in the absence of any alternative. We propose a network approach to determine the optimal low resources setting oriented pool testing strategies that identifies infected individuals in a small number of tests and few rounds of testing, at low prevalence of the virus. We simulate stochastic infection curves on societies under quarantine. Allowing some social interaction is possible to keep the COVID-19 curve flat. However, similar results can be strategically obtained searching and isolating infected persons to preserve a healthier social structure. Here, we analyze which are the best strategies to contain the virus applying an algorithm that combine samples and testing them in groups []. A relevant parameter to keep infection curves flat using this algorithm is the daily frequency of testing at zones where a high infection rate is reported. On the other hand, the algorithm efficiency is low for random search of infected people.

Effectiveness of non-pharmaceutical interventions and vaccine for containing the spread of COVID-19: Three illustrations before and after vaccination periods

BackgroundThere are few studies demonstrating how the effectiveness of various extents of non-pharmaceutical interventions (NPIs) before and after vaccination periods. The study aimed to demonstrate such an effectiveness in the alteration of the epidemic curves from theory to practice.MethodsThe empirical data on the daily reported COVID-19 cases were extracted from open source. A computer simulation design in conjunction with the susceptible-exposed-infected-recovered (SEIR) type model was applied to evaluating confinement measures in Italy with adjustment for underreported cases; isolation and quarantine in Taiwan; and NPIs and vaccination in Israel.ResultsIn Italy scenario, the extents of confinement measures were 34% before the end of March and then scaled up to 70% after then. Both figures were reduced to 22–69% after adjusting for underreported cases. Approximately 44% of confinement measures were implemented in the second surge of pandemic in Italy.Fitting the observational data on Taiwan assuming the initial outbreak similar to Wuhan, China, 44% of isolation and quarantine were estimated before March 23rd, 2020. Isolation and quarantine were scaled up to 90% and at least 60% to contain community-acquired outbreaks from March 24th, 2020 onwards. Given 15% monthly vaccination rate from December 2020 in Israel, the effectiveness estimates of reducing the infected toll were 36%, 56%, and 85% for NPIs alone, vaccination alone, and both combined, respectively.ConclusionWe demonstrated how various NPIs stamp out and delay the epidemic curve of COVID-19. The optimal implementation of these NPIs has to be planned before wide vaccine uptake worldwide.

Response to the Precautionary Measures to Prevent Coronaviruses-19; after Decline of the Pandemic, Taif City, KSA

Introduction: In spite of regression of pandemic curve in the Kingdom of Saudi Arabia there is fears of second wave especially during this winter.Objective: This study aims to explore the public commitment to COVID-19’s precautionary measures after the dropping of the cumulative curve towards regression, and to determine the role of society culture in the compliance with these preventive procedures. Methodology: This is a descriptive cross-section survey conducted in Taif city, Saudi Arabia. Using a convenience sampling method. Results: The score of society compliance with precautionary measures after regression of curve towards flat line was (3.72±0.47/) which considered high. There was a significant relationship between nationality and the precautionary measures to prevent COVID-19 (t=-2.34, p<0.05, = 0.02), the mean score of nonSaudi (3.88±0.36), which exceeded Saudi mean scores (3.70±0.48). Fewparticipants thought that there was overstatement against COVID-19’s precautionary measures. Conclusion: After regression of COVID-19 curve towards flat line, the level of society commitment to the preventive measures was still high. Most responders adhere to kept a distance from a person who has signs of SARS-CoV-2.

Analysis and Simulation of Epidemic COVID-19 Curves with the Verhulst Model Applied to Statistical Inhomogeneous Age Groups

Pandemic curves, such as COVID-19, often show multiple and unpredictable contamination peaks, often called second, third and fourth waves, which are separated by wide plateaus. Here, by considering the statistical inhomogeneity of age groups, we show a quantitative understanding of the different behaviour rules to flatten a pandemic COVID-19 curve and concomitant multi-peak recurrence. The simulations are based on the Verhulst model with analytical generalized logistic equations for the limited growth. From the log–lin plot, we observe an early exponential growth proportional to et/τgrow. The first peak is often τgrow ≅ 5 d. The exponential growth is followed by a recovery phase with an exponential decay proportional to e−t/τrecov. For the characteristic time holds: τgrow< τrecov. Even with isolation, outbreaks due to returning travellers can result in a recurrence of multi-peaks visible on log–lin scales. The exponential growth for the first wave is faster than for the succeeding waves, with characteristic times, τ of about 10 d. Our analysis ascertains that isolation is an efficient method in preventing contamination and enables an improved strategy for scientists, governments and the general public to timely balance between medical burdens, mental health, socio-economic and educational interests.

The Impact of COVID-19 Management Policies Tailored to Airborne SARS-CoV-2 Transmission: Policy Analysis.

BackgroundDaily new COVID-19 cases from January to April 2020 demonstrate varying patterns of SARS-CoV-2 transmission across different geographical regions. Constant infection rates were observed in some countries, whereas China and South Korea had a very low number of daily new cases. In fact, China and South Korea successfully and quickly flattened their COVID-19 curve. To understand why this was the case, this paper investigated possible aerosol-forming patterns in the atmosphere and their relationship to the policy measures adopted by select countries.ObjectiveThe main research objective was to compare the outcomes of policies adopted by countries between January and April 2020. Policies included physical distancing measures that in some cases were associated with mask use and city disinfection. We investigated whether the type of social distancing framework adopted by some countries (ie, without mask use and city disinfection) led to the continual dissemination of SARS-CoV-2 (daily new cases) in the community during the study period.MethodsWe examined the policies used as a preventive framework for virus community transmission in some countries and compared them to the policies adopted by China and South Korea. Countries that used a policy of social distancing by 1-2 m were divided into two groups. The first group consisted of countries that implemented social distancing (1-2 m) only, and the second comprised China and South Korea, which implemented distancing with additional transmission/isolation measures using masks and city disinfection. Global daily case maps from Johns Hopkins University were used to provide time-series data for the analysis.ResultsThe results showed that virus transmission was reduced due to policies affecting SARS-CoV-2 propagation over time. Remarkably, China and South Korea obtained substantially better results than other countries at the beginning of the epidemic due to their adoption of social distancing (1-2 m) with the additional use of masks and sanitization (city disinfection). These measures proved to be effective due to the atmosphere carrier potential of SARS-CoV-2 transmission.ConclusionsOur findings confirm that social distancing by 1-2 m with mask use and city disinfection yields positive outcomes. These strategies should be incorporated into prevention and control policies and be adopted both globally and by individuals as a method to fight the COVID-19 pandemic.

India Fighting COVID-19: Experiences and Lessons Learned From the Successful Kerala and Bhilwara Models.

The COVID-19 pandemic marks its emergence in China in December 2019. India reported its first case on January 30th 2020 which happened to be epidemiologically linked to China. On March 24, India went into nationwide lockdown. The number of cases increased in the country and a few hotspots were identified. Cluster containment strategy seemed to be effective in containing the disease and breaking the chain of transmission. Two models (Kerala and Bhilwara) emerged as a lesson for other states. Kerala government implemented a "triple-lock containment strategy" and Bhilwara district administration followed "all down curfew" with massive sample testing. The experiences from these successful field models can be implemented in other districts and states to flatten the COVID-19 curve.

Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review.

COVID-19 is one of the greatest challenges humanity has faced recently, forcing a change in the daily lives of billions of people worldwide. Therefore, many efforts have been made by researchers across the globe in the attempt of determining the models of COVID-19 spread. The objectives of this review are to analyze some of the open-access datasets mostly used in research in the field of COVID-19 regression modeling as well as present current literature based on Artificial Intelligence (AI) methods for regression tasks, like disease spread. Moreover, we discuss the applicability of Machine Learning (ML) and Evolutionary Computing (EC) methods that have focused on regressing epidemiology curves of COVID-19, and provide an overview of the usefulness of existing models in specific areas. An electronic literature search of the various databases was conducted to develop a comprehensive review of the latest AI-based approaches for modeling the spread of COVID-19. Finally, a conclusion is drawn from the observation of reviewed papers that AI-based algorithms have a clear application in COVID-19 epidemiological spread modeling and may be a crucial tool in the combat against coming pandemics.

Selective perimeter lockdowns in Madrid: a way to bend the COVID-19 curve?

Lockdowns have been widespread used to limit social interaction and bend the epidemic curve. However, their intensity and geographical delimitation have been variable across different countries. Madrid (Spain) implemented perimeter lockdowns in September with the purpose of bending the COVID-19 curve. In this paper we compared, using join point regressions, the evolution of COVID-19 cases in those areas where this intervention was implemented and those where it was not. According to our analysis, the decrease in the epidemic curve started before the impact of the perimeter lockdown could be reflected.

COVID-19 LOCKDOWN RELATED DEPRESSION AND IMMUNE SUPPRESSION: IMPACT ON HUMAN RESOURCE AND INDIAN ECONOMY

Unanimously lockdown is the most scientific way to flatten the curve of COVID-19. But, lockdown has the negative influence on social, psychological, physiological and economical aspects of life as well. Under this health emergency situation, the depression is playing its role as silent killer on immune suppression. Physiologically the immune suppressed people are more prone to any viral infection like COVID-19. Moreover, there are so many adverse effects of depression on our health. Therefore, it is a challenge to minimize the depression related immune suppression caused by the pandemic of Covid-19. The Government of India should admit the truth of physiology in the light of depression related to immune suppression during the lockdown period. Without the sweat of healthy human resources, money cannot reform Indian economy. Therefore, many anti-depressant strategies have to be taken by the Government to minimize the psychological depression linked directly with the health of human resources. Therefore, this is the high time to think positively about the anti-depressant strategies to minimize and flatten the curve of COVID-19 in future.

Kerala’s Innovations and Flexibility for Covid-19 Recovery: Storytelling using Systems Thinking

During the early five months of the first phase of the Covid-19 pandemic, the South Indian state of Kerala regularly appeared in world media, presenting an impactful case of Covid-19 innovations. The purpose of this article is to uniquely present Kerala’s success of flattening the Covid-19 curve during that period, employing storytelling using systems thinking. Contributing to the literature stream linking flexible systems management and systems thinking, this study presents the interconnected whole of Kerala’s Covid-19 innovations for pandemic management. The reference mode that was developed using the systems thinking and modelling methodology confirmed Kerala’s exemplary performance in flattening the Covid-19 curve during the first five months of 2020. The systems model built showed six feedback loops explaining how Covid-19 spreading was controlled in Kerala by different types of innovations and an effective public health system. Overall, with a strong inbuilt social fabric, experienced leadership that withered Nipah-virus outbreak, and robust public health system at its advantage, Kerala flattened the Covid-19 curve using its intertwined social, policing, communication and technological innovations.

An analysis of COVID-19 clusters in India

BackgroundIn this study we cluster the districts of India in terms of the spread of COVID-19 and related variables such as population density and the number of specialty hospitals. Simulation using a compartment model is used to provide insight into differences in response to public health interventions. Two case studies of interest from Nizamuddin and Dharavi provide contrasting pictures of the success in curbing spread.MethodsA cluster analysis of the worst affected districts in India provides insight about the similarities between them. The effects of public health interventions in flattening the curve in their respective states is studied using the individual contact SEIQHRF model, a stochastic individual compartment model which simulates disease prevalence in the susceptible, infected, recovered and fatal compartments.ResultsThe clustering of hotspot districts provide homogeneous groups that can be discriminated in terms of number of cases and related covariates. The cluster analysis reveal that the distribution of number of COVID-19 hospitals in the districts does not correlate with the distribution of confirmed COVID-19 cases. From the SEIQHRF model for Nizamuddin we observe in the second phase the number of infected individuals had seen a multitudinous increase in the states where Nizamuddin attendees returned, increasing the risk of the disease spread. However, the simulations reveal that implementing administrative interventions, flatten the curve. In Dharavi, through tracing, tracking, testing and treating, massive breakout of COVID-19 was brought under control.ConclusionsThe cluster analysis performed on the districts reveal homogeneous groups of districts that can be ranked based on the burden placed on the healthcare system in terms of number of confirmed cases, population density and number of hospitals dedicated to COVID-19 treatment. The study rounds up with two important case studies on Nizamuddin basti and Dharavi to illustrate the growth curve of COVID-19 in two very densely populated regions in India. In the case of Nizamuddin, the study showed that there was a manifold increase in the risk of infection. In contrast it is seen that there was a rapid decline in the number of cases in Dharavi within a span of about one month.

Inkonsistensi Kebijakan Pemerintah Pusat dalam Penanganan Covid-19 Di Indonesia

Until the end of 2020, the Covid-19 curve in Indonesia has not decreased, and even continues to increased. This indicate something wrong with government policy. With the form of the state of Indonesia as a nation state “decentralized”, national policies become the reference policies in local policies. Its be a determining factor in facing this pandemic. This paper discusses the inconsistency of national policies with implications for local governments. The research used a qualitative approach by utilizing descriptive analysis methods. Data sources used are secondary data from journals, books, government websites, electronic media, legislation, and other studies. Data collection techniques using the method of document review. The results of the research identified inconsistencies in national policies, namely unclear direction of regional quarantine policies, rapidly changing transportation policies, and government lack of transparency in health policies. The result of this inconsistency has implications for local governments into deficit budget, an increase in the number of positive patients in the regions, a decrease in public awareness of obeying regulations. Based on this, the pattern of policy relations built by the government in terms of handling Covid-19 in Indonesia is centralized (Top-Down).

Virus spread versus contact tracing: Two competing contagion processes

After the blockade that many nations suffered to stop the growth of the incidence curve of COVID-19 during the first half of 2020, they face the challenge of resuming their social and economic activity. The rapid airborne transmissibility of SARS-CoV-2, and the absence of a vaccine, calls for active containment measures to avoid the propagation of transmission chains. The best strategy up to date, popularly known as Test-Track-Treat (TTT), consist in testing the population for diagnosis, track the contacts of those infected, and treat by quarantine all these cases. The dynamical process that better describes the combined action of the former mechanisms is that of a contagion process that competes with the spread of the pathogen, cutting off potential contagion pathways. Here we propose a compartmental model that couples the dynamics of the infection with the contact tracing and isolation of cases. We develop an analytical expression for the effective case reproduction number $R_c(t)$ that reveals the role of contact tracing in the mitigation and suppression of the epidemics. We show that there is a trade off between the infection propagation and the isolation of cases. If the isolation is limited to symptomatic individuals only, the incidence curve can be flattened but not bended. However, if contact tracing is applied to asymptomatic individuals too, the strategy can bend the curve and suppress the epidemics. Quantitative results are dependent on the network topology. We quantify, the most important indicator of the effectiveness of contact tracing, namely its capacity to reverse the increasing tendency of the epidemic curve, causing its bending.

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.

Flattening the curve is flattening the complexity of covid-19

Since the February 2020 publication of the article ‘Flattening the curve’ in The Economist, political leaders worldwide have used this expression to legitimize the introduction of social distancing measures in fighting Covid-19. In fact, this expression represents a complex combination of three components: the shape of the epidemic curve, the social distancing measures and the reproduction number mathscr{R}_{0}. Each component has its own history, each with a different history of control. Presenting the control of the epidemic as flattening the curve is in fact flattening the underlying natural-social complexity. The curve that needs to be flattened is presented as a bell-shaped curve, implicitly suggesting that the pathogen’s spread is subject only to natural laws. The mathscr{R} value, however, is, fundamentally, a metric of how a pathogen behaves within a social context, namely its numerical value is affected by sociopolitical influences. The jagged and erratic empirical curve of Covid-19 illustrates this. Although the virus has most likely infected only a small portion of the total susceptible population, it is clear its shape has changed drastically. This changing shape is largely due to sociopolitical factors. These include shifting formal laws and policies, shifting individual behaviors as well as shifting various other social norms and practices. This makes the course of Covid-19 curve both erratic and unpredictable.

Assessing the effects of time-dependent restrictions and control actions to flatten the curve of COVID-19 in Kazakhstan.

This article presents the assessment of time-dependent national-level restrictions and control actions and their effects in fighting the COVID-19 pandemic. By analysing the transmission dynamics during the first wave of COVID-19 in the country, the effectiveness of the various levels of control actions taken to flatten the curve can be better quantified and understood. This in turn can help the relevant authorities to better plan for and control the subsequent waves of the pandemic. To achieve this, a deterministic population model for the pandemic is firstly developed to take into consideration the time-dependent characteristics of the model parameters, especially on the ever-evolving value of the reproduction number, which is one of the critical measures used to describe the transmission dynamics of this pandemic. The reproduction number alongside other key parameters of the model can then be estimated by fitting the model to real-world data using numerical optimisation techniques or by inducing ad-hoc control actions as recorded in the news platforms. In this article, the model is verified using a case study based on the data from the first wave of COVID-19 in the Republic of Kazakhstan. The model is fitted to provide estimates for two settings in simulations; time-invariant and time-varying (with bounded constraints) parameters. Finally, some forecasts are made using four scenarios with time-dependent control measures so as to determine which would reflect on the actual situations better.