scholarly journals Analysis of the COVID-19 epidemic in french overseas department Mayotte based on a modified deterministic and stochastic SEIR model

2020 ◽  
Author(s):  
Solym Mawaki Manou-Abi ◽  
Julien Balicchi
Keyword(s):  
Transmission Rate ◽  
Control Measure ◽  
Exponential Growth Phase ◽  
The Novel ◽  
Rate Parameter ◽  
Seir Model ◽  
Stochastic Epidemic ◽  
Access To Water ◽  
Novel Coronavirus ◽  
Death Cases

AbstractIn order to anticipate a future trends in the development of the novel coronavirus COVID-19 epidemic started early at march 13, in the french overseas department Mayotte, we consider in this paper a modified deterministic and stochastic epidemic model. The model divides the total population into several possible states or compartment: susceptible (S), exposed (E) infected and being under an incubation period, infected (I) being infectious, simple or mild removed RM, severe removed (including hospitalized) RS and death cases (D). The adding of the two new compartment RM and RS are driven by data which together replace the original R compartment in the classical SEIR model.We first fit the constant transmission rate parameter to the epidemic data in Mayotte during an early exponential growth phase using an algorithm with a package of the software R and based on a Maximum Likewood estimator. This allows us to predict the epidemic without any control in order to understand how the control measure and public policies designed are having the desired impact of controlling the epidemic. To do this, we introduce a temporally varying decreasing transmission rate parameter with a control or quarantine parameter q. Then we pointed out some values of q to maintain control which is critical in Mayotte given the fragility of its health infrastructure and the significant fraction of the population without access to water.

Volatility transmission across international markets amid COVID 19 pandemic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hechem Ajmi ◽  
Nadia Arfaoui ◽  
Karima Saci
Keyword(s):  
Crude Oil ◽  
International Markets ◽  
The Novel ◽  
Data Set ◽  
Health Crisis ◽  
Content Type ◽  
Volatility Transmission ◽  
Oil Markets ◽  
Novel Coronavirus ◽  
Death Cases

Purpose This paper aims to investigate the volatility transmission across stocks, gold and crude oil markets before and during the novel coronavirus (COVID-19) crisis. Design/methodology/approach A multivariate vector autoregression (VAR)-Baba, Engle, Kraft and Kroner generalized autoregressive conditional heteroskedasticity model (BEKK-GARCH) is used to assess volatility transmission across the examined markets. The sample is divided as follows. The first period ranging from 02/01/2019 to 10/03/2020 defines the pre-COVID-19 crisis. The second period is from 11/03/2020 to 05/10/2020, representing the COVID-19 crisis period. Then, a robustness test is used using exponential GARCH models after including an exogenous variable capturing the growth of COVID-19 confirmed death cases worldwide with the aim to test the accuracy of the VAR-BEKK-GARCH estimated results. Findings Results indicate that the interconnectedness among the examined market has been intensified during the COVID-19 crisis, proving the lack of hedging opportunities. It is also found that stocks and Gold markets lead the crude oil market especially during the COVID-19 crisis, which explains the freefall of the crude oil price during the health crisis. Similarly, results show that Gold is most likely to act as a diversifier rather than a hedging tool during the current health crisis. Originality/value Although the recent studies in the field focused on analyzing the relationships between different markets during the first quarter of 2020, this study considers a larger data set with the aim to assess the volatility transmission across the examined international markets Amid the COVID-19 crisis, while it shows the most significant impact on various financial markets compared to other diseases.

scholarly journals A Simulation on Potential Secondary Spread of Novel Coronavirus in an Exported Country Using a Stochastic Epidemic SEIR Model

2020 ◽  
Vol 9 (4) ◽  
pp. 944 ◽  
Author(s):  
Kentaro Iwata ◽  
Chisato Miyakoshi
Keyword(s):  
Healthcare Professionals ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Asian Countries ◽  
Hospital Visit ◽  
Seir Model ◽  
Stochastic Epidemic ◽  
Novel Coronavirus ◽  
The Impact ◽  
Multiple Scenarios

Ongoing outbreak of pneumonia caused by novel coronavirus (2019-nCoV) began in December 2019 in Wuhan, China, and the number of new patients continues to increase. Even though it began to spread to many other parts of the world, such as other Asian countries, the Americas, Europe, and the Middle East, the impact of secondary outbreaks caused by exported cases outside China remains unclear. We conducted simulations to estimate the impact of potential secondary outbreaks in a community outside China. Simulations using stochastic SEIR model were conducted, assuming one patient was imported to a community. Among 45 possible scenarios we prepared, the worst scenario resulted in the total number of persons recovered or removed to be 997 (95% CrI 990–1000) at day 100 and a maximum number of symptomatic infectious patients per day of 335 (95% CrI 232–478). Calculated mean basic reproductive number (R0) was 6.5 (Interquartile range, IQR 5.6–7.2). However, better case scenarios with different parameters led to no secondary cases. Altering parameters, especially time to hospital visit. could change the impact of a secondary outbreak. With these multiple scenarios with different parameters, healthcare professionals might be able to better prepare for this viral infection.

scholarly journals Modeling the Novel Coronavirus (SARS-CoV-2) Outbreak in Sicily, Italy

2020 ◽  
Vol 17 (14) ◽  
pp. 4964 ◽  
Author(s):  
Andrea Maugeri ◽  
Martina Barchitta ◽  
Sebastiano Battiato ◽  
Antonella Agodi
Keyword(s):  
Transmission Rate ◽  
Control Measures ◽  
Transmission Dynamics ◽  
The Novel ◽  
Epidemic Spread ◽  
Transmission Rates ◽  
Contact Precautions ◽  
Travel Restrictions ◽  
Novel Coronavirus ◽  
Reported Data

Italy was the first country in Europe which imposed control measures of travel restrictions, quarantine and contact precautions to tackle the epidemic spread of the novel coronavirus (SARS-CoV-2) in all its regions. While such efforts are still ongoing, uncertainties regarding SARS-CoV-2 transmissibility and ascertainment of cases make it difficult to evaluate the effectiveness of restrictions. Here, we employed a Susceptible-Exposed-Infectious-Recovered-Dead (SEIRD) model to assess SARS-CoV-2 transmission dynamics, working on the number of reported patients in intensive care unit (ICU) and deaths in Sicily (Italy), from 24 February to 13 April. Overall, we obtained a good fit between estimated and reported data, with a fraction of unreported SARS-CoV-2 cases (18.4%; 95%CI = 0–34.0%) before 10 March lockdown. Interestingly, we estimated that transmission rate in the community was reduced by 32% (95%CI = 23–42%) after the first set of restrictions, and by 80% (95%CI = 70–89%) after those adopted on 23 March. Thus, our estimates delineated the characteristics of SARS-CoV2 epidemic before restrictions taking into account unreported data. Moreover, our findings suggested that transmission rates were reduced after the adoption of control measures. However, we cannot evaluate whether part of this reduction might be attributable to other unmeasured factors, and hence further research and more accurate data are needed to understand the extent to which restrictions contributed to the epidemic control.

scholarly journals The Buffering Effects of Social Insurance for the Spread of Covid-19

2021 ◽  
Vol 12 (4(I)) ◽  
pp. 19-27
Author(s):  
Moein Mirani Ahangarkolaei ◽  
Eser Demir ◽  
Tolga Constantinou ◽  
Mostafa Toranji ◽  
Tadashi Adino ◽  
...  
Keyword(s):  
Social Insurance ◽  
Transmission Rate ◽  
The Novel ◽  
Negative Consequences ◽  
Welfare Programs ◽  
Monthly Data ◽  
The Social ◽  
Wide Range ◽  
Novel Coronavirus ◽  
Low Educated

Global pandemics are associated with substantial losses of human capital. The best strategy of policymakers in public health before a population-wide vaccination is to reduce the outbreak of the disease and finding ways to alleviate its negative consequences in society. Previous studies show that welfare programs have externalities in unintended areas and for unplanned outcomes including a wide range of health outcomes. In this paper, we show that payments under the Unemployment Insurance (UI) program have the potential to reduce the spread of the novel coronavirus. Applying a difference-in-difference technique on monthly data of all US counties from January 2020 to January 2021, we document that the social insurance under the umbrella of UI payments can reduce the transmission rate of Covid-19. The results show heterogeneity across subsample with the largest effects among blacks, poor, and low educated regions

scholarly journals The effects of the clinical symptoms pneumonia-confirmation strategy of the COVID-19 epidemic in Wuhan, China

2020 ◽  
Author(s):  
Yanjin Wang ◽  
Pei Wang ◽  
Shudao Zhang ◽  
Hao Pan
Keyword(s):  
Turning Point ◽  
Clinical Symptoms ◽  
Transmission Rate ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
The Novel ◽  
Wuhan City ◽  
Start Date ◽  
Rapid Spread ◽  
Novel Coronavirus

Abstract Motivated by the quick control in Wuhan, China, and the rapid spread in other countries of COVID-19, we investigate the questions that what is the turning point in Wuhan by quantifying the variety of basic reproductive number after the lockdown city. The answer may help the world to control the COVID-19 epidemic. A modified SEIR model is used to study the COVID-19 epidemic in Wuhan city. Our model is calibrated by the hospitalized cases. The modeling result gives out that the means of basic reproductive numbers are 1.5517 (95% CI 1.1716-4.4283) for the period from Jan 25 to Feb 11, 2020, and 0.4738(95% CI 0.0997-0.8370) for the period from Feb 12 to Mar 10. The transmission rate fell after Feb 12, 2020 as a result of China’s COVID-19 strategy of keeping society distance and the medical support from all China, but principally because of the clinical symptoms to be used for the novel coronavirus pneumonia (NCP) confirmation in Wuhan since Feb 12, 2020. Clinical diagnosis can quicken up NCP-confirmation such that the COVID-19 patients can be isolated without delay. So the clinical symptoms pneumonia-confirmation is the turning point of the COVID-19 battle of Wuhan. The measure of clinical symptoms pneumonia-confirmation in Wuhan has delayed the growth and reduced size of the COVID-19 epidemic, decreased the peak number of the hospitalized cases by 96% in Wuhan. Our modeling also indicates that the earliest start date of COVID-19 in Wuhan may be Nov 2, 2019.

scholarly journals Dynamics of COVID-19 transmission including indirect transmission mechanisms: a mathematical analysis

2020 ◽  
Vol 148 ◽  
Author(s):  
A. Meiksin
Keyword(s):  
Transmission Rate ◽  
The Novel ◽  
Major Health ◽  
Indirect Transmission ◽  
Transmission Mechanisms ◽  
Novel Coronavirus ◽  
The Uk ◽  
Counterfactual Model ◽  
Respiratory Droplets ◽  
Significant Spread

Abstract The outbreak of the novel coronavirus severe acute respiratory syndrome-coronavirus-2 has raised major health policy questions and dilemmas. Whilst respiratory droplets are believed to be the dominant transmission mechanisms, indirect transmission may also occur through shared contact of contaminated common objects that is not directly curtailed by a lockdown. The conditions under which contaminated common objects may lead to significant spread of coronavirus disease 2019 during lockdown and its easing is examined using the susceptible-exposed-infectious-removed model with a fomite term added. Modelling the weekly death rate in the UK, a maximum-likelihood analysis finds a statistically significant fomite contribution, with 0.009 ± 0.001 (95% CI) infection-inducing fomites introduced into the environment per day per infectious person. Post-lockdown, comparison with the prediction of a corresponding counterfactual model with no fomite transmission suggests fomites, through enhancing the overall transmission rate, may have contributed to as much as 25% of the deaths following lockdown. It is suggested that adding a fomite term to more complex simulations may assist in the understanding of the spread of the illness and in making policy decisions to control it.

scholarly journals A fractional order approach to modeling and simulations of the novel COVID-19

2020 ◽  
Author(s):  
Isaac Owusu-Mensah ◽  
Lanre Akinyemi ◽  
Bismark Oduro ◽  
Olaniyi S. Iyiola
Keyword(s):  
Public Health ◽  
Fractional Order ◽  
Transmission Rate ◽  
The Novel ◽  
Modeling And Simulations ◽  
Modern Times ◽  
Important Benefit ◽  
Proposed Model ◽  
Public Health Challenges ◽  
Novel Coronavirus

Abstract The novel coronavirus (SARS-CoV-2.) has emerged and spread at fast speed globally; the disease has become an unprecedented threat to public health worldwide. It is one of the greatest public health challenges in modern times, with no proven cure or vaccine. In this paper, our focus is on a fractional order approach to modeling and simulations of the novel COVID-19. We introduce a fractional type Susceptible-Exposed-Infected-Recovered (SEIR) model to gain insight into the ongoing pandemic of COVID-19. Our proposed model incorporates transmission rate, testing rates, and transition rate (from asymptomatic to symptomatic population groups) for a holistic study of the coronavirus disease. The impacts of these parameters on the dynamics of the solution proles for the disease are simulated and discussed in detail. Furthermore, across all the different parameters, the effects of the fractional order derivative are also simulated and discussed in detail. Various simulations carried out enable us gain deep insights into the dynamics of the spread of COVID-19. The simulation results confirm that fractional calculus is an appropriate tool in modeling the spread of a complex infectious disease such as the novel COVID-19. In the absence of vaccine and treatment, our analysis strongly supports the significance reduction in the transmission rate as valuable strategy to curb the spread of the virus. Our results suggest that tracing and moving testing up has an important benefit. It reduces the number of infected individuals in the general public and thereby reduce the spread of the pandemic. Once the infected individuals are identified and isolated, the interaction between susceptible and infected individuals diminishes and transmission reduces. Furthermore, aggressive testing is also highly recommended.

scholarly journals Impacts of Social and Economic Factors on the Transmission of Coronavirus Disease 2019 (COVID-19) in China

2020 ◽  
Author(s):  
Yun Qiu ◽  
Xi Chen ◽  
Wei Shi
Keyword(s):  
Socioeconomic Factors ◽  
Transmission Rate ◽  
Virus Transmission ◽  
The Novel ◽  
Virus Spread ◽  
Government Response ◽  
Machine Learning Approach ◽  
The Rich ◽  
Novel Coronavirus

AbstractThis paper examines the role of various socioeconomic factors in mediating the local and cross-city transmissions of the novel coronavirus 2019 (COVID-19) in China. We implement a machine learning approach to select instrumental variables that strongly predict virus transmission among the rich exogenous weather characteristics. Our 2SLS estimates show that the stringent quarantine, massive lockdown and other public health measures imposed in late January significantly reduced the transmission rate of COVID-19. By early February, the virus spread had been contained. While many socioeconomic factors mediate the virus spread, a robust government response since late January played a determinant role in the containment of the virus. We also demonstrate that the actual population flow from the outbreak source poses a higher risk to the destination than other factors such as geographic proximity and similarity in economic conditions. The results have rich implications for ongoing global efforts in containment of COVID-19.

scholarly journals A Simulation on Potential Secondary Spread of Novel Coronavirus in an Exported Country Using a Stochastic Epidemic SEIR Model

2020 ◽  
Author(s):  
Kentaro Iwata ◽  
Chisato Miyakoshi
Keyword(s):  
Healthcare Professionals ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Secondary Case ◽  
Hospital Visit ◽  
Seir Model ◽  
Stochastic Epidemic ◽  
Novel Coronavirus ◽  
The Impact ◽  
Multiple Scenarios

Ongoing outbreak of pneumonia caused by novel coronavirus (2019-nCoV) began in December 2019 in Wuhan, China, and the number of new patients continues to increase. On the contrary to ongoing outbreak in China, however, there are limited secondary outbreaks caused by exported case outside the country. We here conducted simulations to estimate the impact of potential secondary outbreaks at a community outside China. Simulations using stochastic SEIR model was conducted, assuming one patient was imported to a community. Among 45 possible scenarios we prepared, the worst scenario resulted in total number of persons recovered or removed to be 997 (95% CrI 990-1,000) at day 100 and maximum number of symptomatic infectious patients per day of 335 (95% CrI 232-478). Calculated mean basic reproductive number (R0) was 6.5 (Interquartile range, IQR 5.6-7.2). However, with good case scenarios with different parameter led to no secondary case. Altering parameters, especially time to hospital visit could change the impact of secondary outbreak. With this multiple scenarios with different parameters, healthcare professionals might be able to prepare for this viral infection better.

scholarly journals The New Pandemic Covid-19: Treatment Options and Developments

2020 ◽  
pp. 1-13 ◽  
Author(s):  
R. Gayatri ◽  
S. Lavanya ◽  
Meeran Hussain ◽  
John Veslin
Keyword(s):  
Immune System ◽  
Treatment Options ◽  
Clinical Status ◽  
Causative Factor ◽  
The Novel ◽  
Treatment Combination ◽  
Plasma Therapy ◽  
Ayurvedic Treatment ◽  
Novel Coronavirus ◽  
Death Cases

SARS-CoV-2, the novel infectious causative factor of the new pandemic COVID-19 produced 5934936 total infected cases and 367166 death cases across multiple continents as of May 31, 2020. Majority of the world’s population are still vulnerable to COVID-19. As of now, there are no clear scientific proven treatment or drug to combat covid-19, but prevention and management can reduce the spread of virus. In this crisis, a vaccine, that can train the immune system to fight against this novel coronavirus becomes essential to control the further dissemination of the new pandemic COVID-19. This review provides insights into the on- going treatment options available for COVID-19 including antiviral drugs, Ayurvedic treatment, combination of drugs and plasma therapy. This review also aims to highlight on the development of vaccines and its clinical status.

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