scholarly journals Prediction of confinement effects on the number of Covid-19 outbreak in Algeria

2020 ◽  
Vol 15 ◽  
pp. 37 ◽  
Author(s):  
Ali Moussaoui ◽  
Pierre Auger
Keyword(s):  
Reproduction Number ◽  
Control Measures ◽  
Cumulative Number ◽  
Time Data ◽  
Final Size ◽  
First Case ◽  
Algerian Population ◽  
Fast Change ◽  
Real Time Data ◽  
The Basic Reproduction Number

The first case of coronavirus disease 2019 (COVID-19) in Algeria was reported on 25 February 2020. Since then, it has progressed rapidly and the number of cases grow exponentially each day. In this article, we utilize SEIR modelling to forecast COVID-19 outbreak in Algeria under two scenarios by using the real-time data from March 01 to April 10, 2020. In the first scenario: no control measures are put into place, we estimate that the basic reproduction number for the epidemic in Algeria is 2.1, the number of new cases in Algeria will peak from around late May to early June and up to 82% of the Algerian population will likely contract the coronavirus. In the second scenario, at a certain date T, drastic control measures are taken, people are being advised to self-isolate or to quarantine and will be able to leave their homes only if necessary. We use SEIR model with fast change between fully protected and risky states. We prove that the final size of the epidemic depends strongly on the cumulative number of cases at the date when we implement intervention and on the fraction of the population in confinement. Our analysis shows that the longer we wait, the worse the situation will be and this very quickly produces.

scholarly journals A first study on the impact of containment measure on COVID-19 spread in Morocco

2020 ◽  
Author(s):  
Aayah Hammoumi ◽  
Redouane Qesmi
Keyword(s):  
Basic Reproduction Number ◽  
High Speed ◽  
Social Economic ◽  
Reproduction Number ◽  
Cumulative Number ◽  
First Case ◽  
Containment Measure ◽  
The Impact ◽  
The Basic Reproduction Number ◽  
Economic Damages

AbstractBackgroundSince the appearance of the first case of COVID-19 in Morocco, the cumulative number of reported infectious cases continues to increase and, consequently, the government imposed the containment measure within the country. Our aim is to predict the impact of the compulsory containment on COVID-19 spread. Earlier knowledge of the epidemic characteristics of COVID-19 transmission related to Morocco will be of great interest to establish an optimal plan-of-action to control the epidemic.MethodUsing a Susceptible-Asymptomatic-Infectious model and the data of reported cumulative confirmed cases in Morocco from March 2nd to April 9, 2020, we determined the basic and control reproduction numbers and we estimated the model parameter values. Furthermore, simulations of different scenarios of containment are performed.ResultsEpidemic characteristics are predicted according to different rates of containment. The basic reproduction number is estimated to be 2.9949, with CI(2.6729–3.1485). Furthermore, a threshold value of containment rate, below which the epidemic duration is postponed, is determined.ConclusionOur findings show that the basic reproduction number reflects a high speed of spread of the epidemic. Furthermore, the compulsory containment can be efficient if more than 73% of population are confined. However, even with 90% of containment, the end-time is estimated to happen on July 4th which can be harmful and lead to consequent social-economic damages. Thus, containment need to be accompanied by other measures such as mass testing to reduce the size of asymptomatic population. Indeed, our sensitivity analysis investigation shows that the COVID-19 dynamics depends strongly on the asymptomatic duration as well as the contact and containment rates. Our results can help the Moroccan government to anticipate the spread of COVID-19 and avoid human loses and consequent social-economic damages as well.

scholarly journals Analysis and prediction of the coronavirus disease epidemic in China based on an individual-based model

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Zuiyuan Guo ◽  
Dan Xiao
Keyword(s):  
Reproduction Number ◽  
Control Measures ◽  
Cumulative Number ◽  
Individual Based Model ◽  
Whole Process ◽  
Coordinate Descent Algorithm ◽  
Initial Stage ◽  
The Government ◽  
Prevention And Control Measures ◽  
And Control

AbstractWe established a stochastic individual-based model and simulated the whole process of occurrence, development, and control of the coronavirus disease epidemic and the infectors and patients leaving Hubei Province before the traffic was closed in China. Additionally, the basic reproduction number (R0) and number of infectors and patients who left Hubei were estimated using the coordinate descent algorithm. The median R0 at the initial stage of the epidemic was 4.97 (95% confidence interval [CI] 4.82–5.17). Before the traffic lockdown was implemented in Hubei, 2000 (95% CI 1982–2030) infectors and patients had left Hubei and traveled throughout the country. The model estimated that if the government had taken prevention and control measures 1 day later, the cumulative number of laboratory-confirmed patients in the whole country would have increased by 32.1%. If the lockdown of Hubei was imposed 1 day in advance, the cumulative number of laboratory-confirmed patients in other provinces would have decreased by 7.7%. The stochastic model could fit the officially issued data well and simulate the evolution process of the epidemic. The intervention measurements nationwide have effectively curbed the human-to-human transmission of severe acute respiratory syndrome coronavirus 2.

scholarly journals Development of novel hybrid models for the prediction of COVID-19 in Kuwait

2021 ◽  
Author(s):  
Ahmad Al-Dousari ◽  
◽  
Maria Qurban ◽  
Ijaz Hussain ◽  
Maha Al-Hajeri ◽  
...  
Keyword(s):  
Real Time ◽  
Prediction Models ◽  
Hybrid Approach ◽  
Absolute Error ◽  
The Novel ◽  
Time Data ◽  
Epidemic Size ◽  
First Case ◽  
Real Time Data ◽  
Better Than

The first case of COVID-19 in Kuwait was reported on February 24, 2020. There is a need to develop a prediction model for estimating this epidemic size. In this study, we aimed to develop and compare several prediction models using real-time data of COVID-19 from February 24 to June 12, 2020. We modeled the uncertainty and non-stationary real-time data of COVID-19 cases using a multilayer model with different decomposition techniques. We applied our proposed hybrid methodology to predict COVID-19 cases in Kuwait. We further evaluated the performance of the novel hybrid model with others using mean relative error, mean absolute error, and mean square error. We found that our proposed hybrid approach performed better than others for predicting COVID-19 cases.

scholarly journals PubliCo. A protocol for a new risk and crisis communication platform to bridge the gap between policy makers and the public in the context of the COVID-19 crisis (Preprint)

2021 ◽  
Author(s):  
Giovanni Spitale ◽  
Sonja Merten ◽  
Kristen Jafflin ◽  
Bettina Schwind ◽  
Andrea Kaiser-Grolimund ◽  
...  
Keyword(s):  
Real Time ◽  
Crisis Communication ◽  
Public Perception ◽  
Online Survey ◽  
Control Measures ◽  
Time Data ◽  
Flexible Tool ◽  
Policy Makers ◽  
Real Time Data ◽  
Restrictive Measures

UNSTRUCTURED Background Since the end of 2019, COVID-19 has had a significant impact on citizens around the globe. As governments institute more restrictive measures, public adherence could decrease and discontent mount. Providing high-quality information and countering fake news is important. But we also need feedback loops so that government officials can refine preventive measures and communication strategies. Policy-makers need information – preferably based on real-time data – on the public’s cognitive, emotional and behavioural reaction to public health messages and restrictive measures. PubliCo aims to foster effective and tailored risk and crisis communication as well as an assessment of the risks and benefits of prevention and control measures, as their effectiveness depends on public trust and cooperation. Objective Our project aims to develop a tool that helps tackle the COVID-19 infodemic, with a focus on enabling a nuanced and in-depth understanding of public perception. The project adopts a trans-disciplinary multi-stakeholder approach, including participatory citizen science. Methods Methodologically, we combine literature and media review and analysis and empirical research using mixed methods, including an online survey and diary-based research, both of which are ongoing and continuously updated. Building on real-time data and continuous data collection, our research results will be highly adaptable to the evolving situation. Strengths and limitations of this study - PubliCo is a new modular and flexible tool to provide bi-directional interaction between citizens and policy-makers for risk and crisis communication - PubliCo relies on quantitative and qualitative data to provide a precise, timely and rich analysis of complex phenomena - PubliCo is open and transparent by design - Although important safeguards are put in place in the code, in a less democratic context it could be used for social control - Communicating complex notions with moral implications (e.g. about health risks, allocation strategies, and community benefits) is a challenge.

scholarly journals Prediction of the Epidemic Peak of Coronavirus Disease in Japan, 2020

2020 ◽  
Vol 9 (3) ◽  
pp. 789 ◽  
Author(s):  
Toshikazu Kuniya
Keyword(s):  
Compartmental Model ◽  
Reproduction Number ◽  
Least Square ◽  
Time Data ◽  
Long Period ◽  
Epidemic Size ◽  
First Case ◽  
Final Epidemic Size ◽  
Positive Effect ◽  
Day By Day

The first case of coronavirus disease 2019 (COVID-19) in Japan was reported on 15 January 2020 and the number of reported cases has increased day by day. The purpose of this study is to give a prediction of the epidemic peak for COVID-19 in Japan by using the real-time data from 15 January to 29 February 2020. Taking into account the uncertainty due to the incomplete identification of infective population, we apply the well-known SEIR compartmental model for the prediction. By using a least-square-based method with Poisson noise, we estimate that the basic reproduction number for the epidemic in Japan is R 0 = 2.6 ( 95 % CI, 2.4 – 2.8 ) and the epidemic peak could possibly reach the early-middle summer. In addition, we obtain the following epidemiological insights: (1) the essential epidemic size is less likely to be affected by the rate of identification of the actual infective population; (2) the intervention has a positive effect on the delay of the epidemic peak; (3) intervention over a relatively long period is needed to effectively reduce the final epidemic size.

scholarly journals Time from Symptom Onset to Hospitalisation of Coronavirus Disease 2019 (COVID-19) Cases: Implications for the Proportion of Transmissions from Infectors with Few Symptoms

2020 ◽  
Vol 9 (5) ◽  
pp. 1297 ◽  
Author(s):  
Robin N. Thompson ◽  
Francesca A. Lovell-Read ◽  
Uri Obolski
Keyword(s):  
Basic Reproduction Number ◽  
Symptom Onset ◽  
Reproduction Number ◽  
Wide Spectrum ◽  
Control Measures ◽  
Current Evidence ◽  
The Novel ◽  
Novel Coronavirus ◽  
The Basic Reproduction Number

Interventions targeting symptomatic hosts and their contacts were successful in bringing the 2003 SARS pandemic under control. In contrast, the COVID-19 pandemic has been harder to contain, partly because of its wide spectrum of symptoms in infectious hosts. Current evidence suggests that individuals can transmit the novel coronavirus while displaying few symptoms. Here, we show that the proportion of infections arising from hosts with few symptoms at the start of an outbreak can, in combination with the basic reproduction number, indicate whether or not interventions targeting symptomatic hosts are likely to be effective. However, as an outbreak continues, the proportion of infections arising from hosts with few symptoms changes in response to control measures. A high proportion of infections from hosts with few symptoms after the initial stages of an outbreak is only problematic if the rate of new infections remains high. Otherwise, it can simply indicate that symptomatic transmissions are being prevented successfully. This should be considered when interpreting estimates of the extent of transmission from hosts with few COVID-19 symptoms.

OPTIMAL CONTROL ANALYSIS OF THE EFFECT OF TREATMENT, ISOLATION AND VACCINATION ON HEPATITIS B VIRUS

2020 ◽  
Vol 28 (02) ◽  
pp. 351-376 ◽  
Author(s):  
MUHAMMAD ALTAF KHAN ◽  
SYED AZHAR ALI SHAH ◽  
SAIF ULLAH ◽  
KAZEEM OARE OKOSUN ◽  
MUHAMMAD FAROOQ
Keyword(s):  
Optimal Control ◽  
Hepatitis B ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Control Strategies ◽  
Control Measures ◽  
Hepatitis B Infection ◽  
Control Variables ◽  
Effect Of Treatment ◽  
The Basic Reproduction Number

Hepatitis B infection is a serious health issue and a major cause of deaths worldwide. This infection can be overcome by adopting proper treatment and control strategies. In this paper, we develop and use a mathematical model to explore the effect of treatment on the dynamics of hepatitis B infection. First, we formulate and use a model without control variables to calculate the basic reproduction number and to investigate basic properties of the model such as the existence and stability of equilibria. In the absence of control measures, we prove that the disease free equilibrium is locally asymptotically stable when the basic reproduction number is less than unity. Also, using persistent theorem, it is shown that the infection is uniformly persistent, whenever the basic reproduction number is greater than unity. Using optimal control theory, we incorporate into the model three time-dependent control variables and investigate the conditions required to curtail the spread of the disease. Finally, to illustrate the effectiveness of each of the control strategies on disease control and eradication, we perform numerical simulations. Based on the numerical results, we found that the first two strategies (treatment and isolation strategy) and (vaccination and isolation strategy) are not very effective as a long term control or eradication strategy for HBV. Hence, we recommend that in order to effectively control the disease, all the control measures (isolation, vaccination and treatment) must be implemented at the same time.

scholarly journals Global stability analysis and control of leptospirosis

2016 ◽  
Vol 14 (1) ◽  
pp. 567-585 ◽  
Author(s):  
Kazeem Oare Okosun ◽  
M. Mukamuri ◽  
Daniel Oluwole Makinde
Keyword(s):  
Cost Effectiveness ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Cost Effective ◽  
Control Measures ◽  
Basic Reproductive Number ◽  
Control Parameters ◽  
Constant Control ◽  
Preventive Vaccination ◽  
The Basic Reproduction Number

AbstractThe aim of this paper is to investigate the effectiveness and cost-effectiveness of leptospirosis control measures, preventive vaccination and treatment of infective humans that may curtail the disease transmission. For this, a mathematical model for the transmission dynamics of the disease that includes preventive, vaccination, treatment of infective vectors and humans control measures are considered. Firstly, the constant control parameters’ case is analyzed, also calculate the basic reproduction number and investigate the existence and stability of equilibria. The threshold condition for disease-free equilibrium is found to be locally asymptotically stable and can only be achieved when the basic reproduction number is less than unity. The model is found to exhibit the existence of multiple endemic equilibria. Furthermore, to assess the relative impact of each of the constant control parameters measures the sensitivity index of the basic reproductive number to the model’s parameters are calculated. In the time-dependent constant control case, Pontryagin’s Maximum Principle is used to derive necessary conditions for the optimal control of the disease. The cost-effectiveness analysis is carried out by first of all using ANOVA to check on the mean costs. Then followed by Incremental Cost-Effectiveness Ratio (ICER) for all the possible combinations of the disease control measures. Our results revealed that the most cost-effective strategy for the control of leptospirosis is the combination of the vaccination and treatment of infective livestocks. Though the combinations of all control measures is also effective, however, this strategy is not cost-effective and so too costly. Therefore, more efforts from policy makers on vaccination and treatment of infectives livestocks regime would go a long way to combat the disease epidemic.

scholarly journals Assessing the Effectiveness of Mass Testing and Quarantine in the Spread of COVID-19 in Beijing and Xinjiang, 2020

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Feng Li ◽  
Zhen Jin ◽  
Juan Zhang
Keyword(s):  
Reproduction Number ◽  
Vaccination Campaign ◽  
Transmission Mechanism ◽  
Control Measures ◽  
Financial Resources ◽  
Function Technique ◽  
Final Size ◽  
The People ◽  
Mass Vaccination Campaign ◽  
The Government

Coronavirus disease (COVID-19) cases and COVID-19-related deaths have been increasing worldwide since the outbreak in 2019. Before the mass vaccination campaign for COVID-19, the main methods for COVID-19 control in China were mass testing and quarantine. Based on the transmission mechanism of COVID-19, we constructed a dynamic model for COVID-19 transmission in two typical regions: Beijing and Xinjiang. We calculated the basic reproduction number R 0 , proved the global stability of COVID-19 transmission via the Lyapunov function technique, and introduced the final size. We assessed the effectiveness of mass testing and quarantine. Sensitivity analysis indicated that the more the people were tested per day, the larger is the quarantine proportionality coefficient, the earlier the source location was determined, and the better is the controlling effect. In addition, it was more effective to increase the coefficient of quarantine if the population density in the region was low. To eliminate the pandemic, the government has to expand testing and quarantine, requiring a large amount of continuous manpower, material, and financial resources. Therefore, new control measures should be developed.

scholarly journals Estimating the basic reproduction number for the 2015 bubonic plague outbreak in Nyimba district of Eastern Zambia

2020 ◽  
Vol 14 (11) ◽  
pp. e0008811
Author(s):  
Joseph Sichone ◽  
Martin C. Simuunza ◽  
Bernard M. Hang’ombe ◽  
Mervis Kikonko
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Cost Effective ◽  
Control Measures ◽  
Effective Control ◽  
Infectious Period ◽  
Bubonic Plague ◽  
Infectious Individual ◽  
Susceptible Population ◽  
The Basic Reproduction Number

Background Plague is a re-emerging flea-borne infectious disease of global importance and in recent years, Zambia has periodically experienced increased incidence of outbreaks of this disease. However, there are currently no studies in the country that provide a quantitative assessment of the ability of the disease to spread during these outbreaks. This limits our understanding of the epidemiology of the disease especially for planning and implementing quantifiable and cost-effective control measures. To fill this gap, the basic reproduction number, R0, for bubonic plague was estimated in this study, using data from the 2015 Nyimba district outbreak, in the Eastern province of Zambia. R0 is the average number of secondary infections arising from a single infectious individual during their infectious period in an entirely susceptible population. Methodology/Principal findings Secondary epidemic data for the most recent 2015 Nyimba district bubonic plague outbreak in Zambia was analyzed. R0 was estimated as a function of the average epidemic doubling time based on the initial exponential growth rate of the outbreak and the average infectious period for bubonic plague. R0 was estimated to range between 1.5599 [95% CI: 1.382–1.7378] and 1.9332 [95% CI: 1.6366–2.2297], with average of 1.7465 [95% CI: 1.5093–1.9838]. Further, an SIR deterministic mathematical model was derived for this infection and this estimated R0 to be between 1.4 to 1.5, which was within the range estimated above. Conclusions/Significance This estimated R0 for bubonic plague is an indication that each bubonic plague case can typically give rise to almost two new cases during these outbreaks. This R0 estimate can now be used to quantitatively analyze and plan measurable interventions against future plague outbreaks in Zambia.

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