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Background: This paper uses a SEIR(D) model to analyse the time-varying transmission dynamics of the COVID-19 epidemic in Korea throughout its multiple stages of development. This multi-stage estimation of the model parameters offers a better model fit compared to the whole period analysis and shows how the COVID-19's infection patterns change over time, primarily depending on the effectiveness of the public health authority's non-pharmaceutical interventions (NPIs). Methods: This paper uses the SEIR(D) compartment model to simulate and estimate the parameters for three distinctive stages of the COVID-19 epidemic in Korea, using a manually compiled COVID-19 epidemic dataset for the period between 18 February 2020 and 08 February 2021. The paper identifies three major stages of the COVID-19 epidemic, conducts multi-stage estimations of the SEIR(D) model parameters, and carefully infers context-dependent meaning of the estimation results to help better understand the unique patterns of the transmission of the novel coronavirus (SARS-CoV-2) in each stage. Results: The original SIR compartment model may produce a poor and even misleading estimation result if it is used to cover the entire period of the epidemic. However, if we use the model carefully in distinctive stages of the COVID-19 epidemic, we can find useful insights into the nature of the transmission of the novel coronavirus and the relative effectiveness of the government's non-pharmaceutical interventions over time. [ABSTRACT FROM AUTHOR]

This paper uses a SEIR(D) model to analyse the time-varying transmission dynamics of the COVID-19 epidemic in Korea throughout its multiple stages of development. This multi-stage estimation of the model parameters offers a better model fit compared to the whole period analysis and shows how the COVID-19's infection patterns change over time, primarily depending on the effectiveness of the public health authority's non-pharmaceutical interventions (NPIs). This paper uses the SEIR(D) compartment model to simulate and estimate the parameters for three distinctive stages of the COVID-19 epidemic in Korea, using a manually compiled COVID-19 epidemic dataset for the period between 18 February 2020 and 08 February 2021. The paper identifies three major stages of the COVID-19 epidemic, conducts multi-stage estimations of the SEIR(D) model parameters, and carefully infers context-dependent meaning of the estimation results to help better understand the unique patterns of the transmission of the novel coronavirus (SARS-CoV-2) in each stage. The original SIR compartment model may produce a poor and even misleading estimation result if it is used to cover the entire period of the epidemic. However, if we use the model carefully in distinctive stages of the COVID-19 epidemic, we can find useful insights into the nature of the transmission of the novel coronavirus and the relative effectiveness of the government's non-pharmaceutical interventions over time. Identifies three distinctive waves of the COVID-19 epidemic in Korea. Conducts multi-stage estimations of the COVID-19 transmission dynamics using SEIR(D) epidemic models. The transmission dynamics of the COVID-19 vary over time, primarily depending on the relative effectiveness of the government's non-pharmaceutical interventions (NPIs). The SEIR(D) epidemic model is useful and informative, but only when it is used carefully to account for the presence of multiple waves and context-dependent infection patterns in each wave. [ABSTRACT FROM AUTHOR]

In this paper, an optimal control model for the transmission dynamics of COVID-19 is investigated. We established important model properties like nonnegativity and boundedness of solutions, and also the region of invariance. Further, an expression for the basic reproduction number is computed and its sensitivity w.r.t model parameters is carried out to identify the most sensitive parameter. Based on sensitivity analysis, optimal control strategies were presented to reduce the disease burden and related costs. It is demonstrated that optimal control does exist and is unique. The characterization of optimal trajectories is analytically studied via Pontryagin's Minimum Principle. Moreover, various simulations were performed to support analytical results. The simulation results showed that the proposed controls significantly influence the disease burden compared to the absence of control cases. Further, it reveals that the applied control strategies are effective throughout the intervention period in reducing COVID-19 diseases in the community. Besides, the simulation results of the optimal control suggested that concurrently applying all controlling strategies outperform in mitigating the spread of COVID-19 compared to any other preventive measures. [ABSTRACT FROM AUTHOR]

This paper proposes a dynamic infectious disease model for COVID-19 daily counts data and estimate the model using the Langevinized EnKF algorithm, which is scalable for large-scale spatio-temporal data, converges to the right filtering distribution, and is thus suitable for performing statistical inference and quantifying uncertainty for the underlying dynamic system. Under the framework of the proposed dynamic infectious disease model, we tested the impact of temperature, precipitation, state emergency order and stay home order on the spread of COVID-19 based on the United States county-wise daily counts data. Our numerical results show that warm and humid weather can significantly slow the spread of COVID-19, and the state emergency and stay home orders also help to slow it. This finding provides guidance and support to future policies or acts for mitigating the community transmission and lowering the mortality rate of COVID-19. [ABSTRACT FROM AUTHOR]

Coronavirus (COVID-19) has captured the attention of the globe very rapidly. Therefore, predicting the spread of the disease has become an indispensa- ble process, this is being due to its extremely infectious nature and due to the negative effects that some courses of actions, which were taken to minimize the spread of the disease, have on economy and key sectors (e.g., health, pharmaceu- tical and industrial sectors). Therefore, in this research work, the nonlinear autore- gressive exogenous model (NARX) is developed to predict the spread of COVID-19 in Jordan by mapping the related factors (i.e. sociodemographic characteristics and government actions) to the number of confirmed COVID-19 cases in the twelve governorates in Jordan. It has been shown that the developed NARX model can predict the number of confirmed cases with a root mean square error of approxi- mately 28. The NARX model developed in this paper can therefore lead to an efficient management of the available resources, and help decision-makers in selecting the best course of actions to minimize the spread of COVID-19. [ABSTRACT FROM AUTHOR]

In this paper we assess the effectiveness of different non-pharmaceutical interventions (NPIs) against COVID-19 utilizing a compartmental model. The local asymptotic stability of equilibria (disease-free and endemic) in terms of the basic reproduction number have been determined. We find that the system undergoes a backward bifurcation in the case of imperfect quarantine. The parameters of the model have been estimated from the total confirmed cases of COVID-19 in India. Sensitivity analysis of the basic reproduction number has been performed. The findings also suggest that effectiveness of face masks plays a significant role in reducing the COVID-19 prevalence in India. Optimal control problem with several control strategies has been investigated. We find that the intervention strategies including implementation of lockdown, social distancing, and awareness only, has the highest cost-effectiveness in controlling the infection. This combined strategy also has the least value of average cost-effectiveness ratio (ACER) and associated cost. [ABSTRACT FROM AUTHOR]

The novel Coronavirus (COVID-19) infection has become a global public health issue, and it has been a cause for morbidity and mortality of more people throughout the world. In this paper, we investigated the impacts of vaccination, other protection measures, home quarantine with treatment, and hospital quarantine with treatment strategies simultaneously using a deterministic mathematical modelling approach. No one has considered these intervention strategies simultaneously in his/her modelling approach. We examined all the qualitative properties of the model such as the positivity and boundedness of the model solutions, the disease-free and endemic equilibrium points, the effective reproduction number using next-generation matrix method, local stabilities of equilibrium points using the Routh–Hurwitz method. Using the Centre Manifold criteria, we have shown the existence of backward bifurcation whenever the COVID-19 effective reproduction number is less than unity. Moreover, we have analysed both sensitivity and numerical simulation using parameter values taken from published literature. The numerical results show that the transmission rate is the most sensitive parameter we have to control. Also vaccination, other protection measures, home quarantine with treatment, and hospital quarantine with treatment have great effects to minimize the COVID-19 transmission in the community. [ABSTRACT FROM AUTHOR]

COVID-19 is a disease caused by infection with the virus 2019-nCoV, a single-stranded RNA virus. During the infection and transmission processes, the virus evolves and mutates rapidly, though the disease has been quickly controlled in Wuhan by 'Fangcang' hospitals. To model the virulence evolution, in this paper, we formulate a new age structured epidemic model. Under the tradeoff hypothesis, two special scenarios are used to study the virulence evolution by theoretical analysis and numerical simulations. Results show that, before 'Fangcang' hospitals, two scenarios are both consistent with the data. After 'Fangcang' hospitals, Scenario I rather than Scenario II is consistent with the data. It is concluded that the transmission pattern of COVID-19 in Wuhan obey Scenario I rather than Scenario II. Theoretical analysis show that, in Scenario I, shortening the value of L (diagnosis period) can result in an enormous selective pressure on the evolution of 2019-nCoV. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) remains a global pandemic at present. Although the human-to-human transmission route for this disease has been well established, its transmission mechanism is not fully understood. In this paper, we propose a mathematical model for COVID-19 which incorporates multiple transmission pathways and which employs time-dependent transmission rates reflecting the impact of disease prevalence and outbreak control. Applying this model to a retrospective study based on publicly reported data in China, we argue that the environmental reservoirs play an important role in the transmission and spread of the coronavirus. This argument is supported by our data fitting and numerical simulation results for the city of Wuhan, for the provinces of Hubei and Guangdong, and for the entire country of China. [ABSTRACT FROM AUTHOR]

The SARS-CoV-2 pandemic has heightened the interest in particle-laden turbulent jets generated by breathing, talking, coughing and sneezing, and how these can contribute to disease transmission. We present quantitative measurement methods for such flows, while exploring and offering improvements for common shortcomings. We generate jets consisting of either liquid droplets or solid particles in an isothermal, quiescent and electrically isopotential experimental chamber that was constructed to control the effects of ambient forcing on jet behavior. For liquid droplets, we find promise in surface deposition analysis based on fluorescent tracer use. For particles, we explore the performance of commercially available adhesive sampling strips and develop conductive grounded carbon tape based sampling strips. We explore ways in which the smallest of thermal gradients or electrostatic charge issues can affect particle dispersion, and suggest practical methods to address these issues. The developed methods are applied to study the simultaneous deposition of ≈ 25, 50 and 200 μm solid particles from a particle laden turbulent jet with a mean velocity of 33.2 m/s. The deposition location as a function of particle size was compared to results from a simple numerical RANS model, and illustrates ways in which imprecise initial or boundary conditions can lead to a notable deviation from experimental results. The differences in deposition pattern seen in experimental and numerical results despite a carefully controlled environment and characterized particle ejection indicate the need for a more stringent numerical model validation, especially when studying fate and transport of mid-range (neither purely aerosol or ballistic) sized particles. [ABSTRACT FROM AUTHOR]

Between February and May 2020, New Zealand recorded 1504 cases of COVID-19 before eliminating community transmission of the virus in June 2020. During this period, a series of control measures were used including population-wide interventions implemented via a four-level alert system, border restrictions, and a test, trace, and isolate system. Mathematical modelling played a key role in informing the government response and guiding policy development. In this paper, we describe the development of a stochastic mathematical model for the transmission and control of COVID-19 in New Zealand. This includes features such as superspreading, case under-ascertainment, testing and reporting delays, and population-wide and case-targeted control measures. We show how the model was calibrated to New Zealand and international data. We describe how the model was used to compare the effects of various interventions in reducing spread of the virus and to estimate the probability of elimination. We conclude with a discussion of the policy-modelling interface and preparedness for future epidemic outbreaks. [ABSTRACT FROM AUTHOR]

In response to the outbreak of COVID-19, the Chinese government imposed stringent lockdown measures to minimize the spread of the disease. This paper shows that under these measures, the PM2.5 concentrations were lower in February 2020 than in February 2019. However, after the measures were removed, the PM2.5 concentration returned to the same level as in the previous year, thus implicating that the reduction was temporary. [ABSTRACT FROM AUTHOR]

The COVID-19 epidemic has been spreading around the world for nearly three years, and asymptomatic infections have exacerbated the spread of the epidemic. To analyse and evaluate the role of asymptomatic infections in the spread of the epidemic, we establish an improved COVID-19 infectious disease dynamics model. We fit the epidemic data in the four time periods corresponding to the selected 614G, Alpha, Delta and Omicron variants and obtain the proportion of asymptomatic persons among the infected persons gradually increased and with the increase of the detection ratio, the cumulative number of cases has dropped significantly, but the decline in the proportion of asymptomatic infections is not obvious. Therefore, in view of the hidden transmission of asymptomatic infections, the cooperation between various epidemic prevention and control policies is required to effectively curb the spread of the epidemic. [ABSTRACT FROM AUTHOR]

We examine the impact of economic, demographic, and mobility-related factors have had on the transmission of COVID-19 in 2020. While many models in the academic literature employ linear/generalized linear models, few contributions exist that incorporate spatial analysis, which is useful for understanding factors influencing the proliferation of the disease before the introduction of vaccines. We utilize a Poisson generalized linear model coupled with a spatial autoregressive structure to do so. Our analysis yields a number of insights including that, in some areas of the country, the counterintuitive result that staying at home can lead to increased disease proliferation. Additionally, we find some positive effects from increased gathering at grocery stores, negative effects of visiting retail stores and workplaces, and even small effects on visiting parks highlighting the complexities travel and migration have on the transmission of diseases. [ABSTRACT FROM AUTHOR]

Without a widely distributed vaccine, controlling human mobility has been identified and promoted as the primary strategy to mitigate the transmission of COVID-19. Many studies have reported the relationship between human mobility and COVID-19 transmission by utilizing the spatial-temporal information of mobility data from various sources. To better understand the role of human mobility in the pandemic, we conducted a systematic review of articles that measure the relationship between human mobility and COVID-19 in terms of their data sources, mathematical models, and key findings. Following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, we selected 47 articles from the Web of Science Core Collection up to September 2020. Restricting human mobility reduced the transmission of COVID-19, although the effectiveness and stringency of policy implementation vary temporally and spatially across different stages of the pandemic. We call for prompt and sustainable measures to control the pandemic. We also recommend researchers 1) to enhance multi-disciplinary collaboration; 2) to adjust the implementation and stringency of mobility-control policies in corresponding to the rapid change of the pandemic; 3) to improve mathematical models used in analysing, simulating, and predicting the transmission of the disease; and 4) to enrich the source of mobility data to ensure data accuracy and suability. [ABSTRACT FROM AUTHOR]

Ethiopia is one of the countries highly affected by the COVID-19 pandemic in Africa. A new study has looked at the transmission dynamics of the outbreak in Ethiopia based on the age categories of the infected individuals. Infected individuals are divided into three age categories (less than 14 years (I 1 ), 15–54 years (I 2 ), and above 54 years I 3 ). Chebyshev polynomial of the fourth kind is used to convert a fractional system into an algebraic system of equations, which is then solved using iterative methods. The fundamental reproduction number (R 0) is calculated using the next-generation matrix technique, and the disease-free and endemic equilibrium points, as well as their stability, are carefully studied. We calculated the parameters and starting conditions provided for our model using data from the Ethiopian Public Health Institute (EPHI) and the Ethiopian Ministry of Health from 29 February 2021, to 7 June 2021. [ABSTRACT FROM AUTHOR]

Objective: This review sought to describe the main trends and findings on the SARS-CoV-2 and the pandemic's effect on reproduction (i.e., effects on fertility, reproductive tissue, pregnancy, vertical and sexual transmission) and sexual function and behaviors. Methods: A review was conducted on studies assessing these variables through the Scopus and PubMed databases between the years 2019–2021. Results: Results showed SARS-CoV-2 pandemic and social distancing measures have affected—and in some cases not—different aspects of people's reproductive function, sexual function and behaviors. Conclusions: Suggestions are offered for researchers and professionals focused on future research and clinical practice. [ABSTRACT FROM AUTHOR]

As the COVID-19 vaccination has been quickly rolling out around the globe, the evaluation of the effects of vaccinating populations for the safe reopening of schools has become a focal point for educators, decision-makers, and the general public. Within this context, we develop a contact network agent-based model (CN-ABM) to simulate on-campus disease transmission scenarios. The CN-ABM establishes contact networks for agents based on their daily activity patterns, evaluates the agents' health status change in different activity environments, and then simulates the epidemic curve. By applying the model to a real-world campus environment, we identify how different community risk levels, teaching modalities, and vaccination rates would shape the epidemic curve. The results show that without vaccination, retaining under 50% of on-campus students can largely flatten the curve, and having 25% on-campus students can achieve the best result (peak value < 1%). With vaccination, having a maximum of 75% on-campus students and at least a 45% vaccination rate can suppress the curve, and a 65% vaccination rate can achieve the best result. The developed CN-ABM can be employed to assist local government and school officials with developing proactive intervention strategies to safely reopen schools. [ABSTRACT FROM AUTHOR]

With the evolving epidemiological parameters of COVID-19 in Africa, the response actions and lessons learnt during the pandemic's past two years, SARS-COV 2 will certainly continue to circulate in African countries in 2022 and beyond. As countries in the African continent need to be more prepared and plan to 'live with the virus' for the upcoming two years and after and at the same time mitigate risks by protecting the future most vulnerable and those responsible for maintaining essential services, WHO AFRO is anticipating four interim scenarios of the evolution of the pandemic in 2022 and beyond in the region. In preparation for the rollout of response actions given the predicted scenarios, WHO AFRO has identified ten strategic orientations and areas of focus for supporting member states and partners in responding to the COVID-19 pandemic in Africa in 2022 and beyond. WHO analysed trends of the transmissions since the first case in the African continent and reviewed lessons learnt over the past months. Establishing a core and agile team solely dedicated to the COVID-19 response at the WHO AFRO, the emergency hubs, and WCOs will improve the effectiveness of the response and address identified challenges. The team will collaborate with the various clusters of the regional office, and other units and subunits in the WCOs supported with good epidemics intelligence. COVID-19 pandemic has afflicted global humanity at unprecedented levels. Two years later and while starting the third year of the COVID-19 response, we now need to change and adapt our strategies, tools and approaches in responding timely and effectively to the pandemic in Africa and save more lives. [ABSTRACT FROM AUTHOR]

The Kingdom of Bahrain announced its first case of COVID-19 infection on February 24, 2020. Since that time, the government has imposed several restrictions such as closures, banning gatherings, and closing border crossings to limit the spread of the pandemic and relieve pressure on the healthcare system. This article provides an overview of the current trajectory of the pandemic in the Kingdom of Bahrain. In addition, the article introduces and applies a methodology to analyze the impact of the interventions and precautionary measures enforced by the government to limit the COVID-19 disease propagation. The results show that most of the enforced precautionary measures were effective in reducing the spread of the disease by a percentage ranging from 20.2% to 41.8%. A religious occasion in Bahrain—involving large gatherings—had increased the spread of the disease by 28.7%. Not enough evidence is found to conclude that reopening interventions had caused the disease to spread again. [ABSTRACT FROM AUTHOR]

The Coronavirus Disease 2019 (COVID-19) is a pulmonary disease produced by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and has become a global pandemic March 2019. The aim of this research is to study a modelling approach on the spread of the COVID-19 pandemic utilizing analysis that is based on the well-known susceptible-infectious-removed (SIR) model. Since the declaration of the epidemic in Wuhan-city in China and other places around the world, several studies have addressed the development and evolution of the disease in different countries and have shown good stability of the use of such model. The United Arab Emirates is among the countries affected by the spread of the virus. Using collected data from 1 March 2020 to 31 August 2020 collected by John Hopkins University and the Federal Competitiveness and Statistics Authority (FCSA) in the UAE, we apply the SIR model to simulate the evolution of the virus in the United Arab Emirates. Our model predicts a peak in the daily infected cases on 19 May 2020, and the cumulative number of infected individuals to reach 100,000 cases by the end of October 2020. [ABSTRACT FROM AUTHOR]

ASEAN, include Indonesia, Malaysia, Philippines, Singapore, and Thailand, are the countries with ongoing transmission of SARS-COV-2, the virus that causes COVID-19. The confirmed cases in Indonesia and Philippines are the highest ranks among other ASEAN countries such as Malaysia, Thailand, and Singapore. To reduce the spread of the pandemic COVID-19, each country has implemented the lock-down policy differently, depending on its economic situation. Therefore, the study of the impact of lock-down across the world, particularly in ASEAN countries, is still relevant to do. In this study, we developed the lock-down model in ASEAN countries by using hybrid ARIMA-SVR and hybrid SEIR-ANN. The first hybrid is based on the time series model ARIMA, with the revision of the error is by using SVR. The second hybrid is based on the classical model of infectious diseases, SEIR, which we revise on the prediction part by using ANN. The hybrid is intended to revise the individual prediction model. The data collected per country was started from January 20, 2020 to August 5, 2020. The periods of lock-down in this study are divided into three, namely no lock-down, implemented lock-down, and the new normal periods. The strictness levels of lock-down were predicted for 60 days ahead. The results showed that the hybrid ARIMA-SVR had smaller RMSE compared with individual ARIMA, similarly, hybrid SEIR-ANN predicted S, E, I, and R more accurately compared with individual SEIR model. It has been also found that the lock down was most effectively implemented in Thailand, Singapore, and Malaysia, whereas Indonesia and Philippines were inefficient countries to enforce the restriction. It is indicated by the number of cases increased significantly during the restriction periods in both countries. [ABSTRACT FROM AUTHOR]