scholarly journals Assessment of the Impacts of Pharmaceutical and Non-pharmaceutical Intervention on COVID-19 in South Africa Using Mathematical Model

2020 ◽  
Author(s):  
Rabiu Musa ◽  
Absalom E. Ezugwu ◽  
Godwin C. E. Mbah
Keyword(s):  
South Africa ◽  
Mathematical Model ◽  
Health Hazard ◽  
Control Measures ◽  
World Health ◽  
The Novel ◽  
Pharmaceutical Intervention ◽  
Social Distancing ◽  
The Impact ◽  
Different Levels

AbstractThe novel coronal virus has spread across more than 213 countries within the space of six months causing devastating public health hazard and monumental economic loss. In the absence of clinically approved pharmaceutical intervention, attentions are shifted to non-pharmaceutical controls to mitigate the burden of the novel pandemic. In this regard, a ten mutually exclusive compartmental mathematical model is developed to investigate possible effects of both pharmaceutical and non-pharmaceutical controls incorporating both private and government’s quarantine and treatments. Several reproduction numbers were calculated and used to determine the impact of both control measures as well as projected benefits of social distancing, treatments and vaccination. We investigate and compare the possible impact of social distancing incorporating different levels of vaccination, with vaccination programme incorporating different levels of treatment. Using the officially published South African COVID-19 data, the numerical simulation shows that the community reproduction threshold will be 30 when there is no social distancing but will drastically reduced to 5 (about 83% reduction) when social distancing is enforced. Furthermore, when there is vaccination with perfect efficacy, the community reproduction threshold will be 4 which increases to 12 (about 67% increment) with-out vaccination. We also established that the implementation of both interventions is enough to curtail the spread of COVID-19 pandemic in South Africa which is in confirmation with the recommendation of the world health organization.

scholarly journals Investigating the effectiveness of re-opening policies before vaccination during a pandemic: SD modelling research based on COVID-19 in Wuhan

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ying Qian ◽  
Wei Xie ◽  
Jidi Zhao ◽  
Ming Xue ◽  
Shiyong Liu ◽  
...  
Keyword(s):  
Model Simulation ◽  
Control Measures ◽  
World Health ◽  
Contact Tracing ◽  
Infection Prevention And Control ◽  
Real World Data ◽  
Medical Resources ◽  
Health Organization ◽  
The Impact ◽  
Different Levels

Abstract Background Lockdown policies were widely adopted during the coronavirus disease 2019 (COVID-19) pandemic to control the spread of the virus before vaccines became available. These policies had significant economic impacts and caused social disruptions. Early re-opening is preferable, but it introduces the risk of a resurgence of the epidemic. Although the World Health Organization has outlined criteria for re-opening, decisions on re-opening are mainly based on epidemiologic criteria. To date, the effectiveness of re-opening policies remains unclear. Methods A system dynamics COVID-19 model, SEIHR(Q), was constructed by integrating infection prevention and control measures implemented in Wuhan into the classic SEIR epidemiological model and was validated with real-world data. The input data were obtained from official websites and the published literature. Results The simulation results showed that track-and-trace measures had significant effects on the level of risk associated with re-opening. In the case of Wuhan, where comprehensive contact tracing was implemented, there would have been almost no risk associated with re-opening. With partial contact tracing, re-opening would have led to a minor second wave of the epidemic. However, if only limited contact tracing had been implemented, a more severe second outbreak of the epidemic would have occurred, overwhelming the available medical resources. If the ability to implement a track-trace-quarantine policy is fixed, the epidemiological criteria need to be further taken into account. The model simulation revealed different levels of risk associated with re-opening under different levels of track-and-trace ability and various epidemiological criteria. A matrix was developed to evaluate the effectiveness of the re-opening policies. Conclusions The SEIHR(Q) model designed in this study can quantify the impact of various re-opening policies on the spread of COVID-19. Integrating epidemiologic criteria, the contact tracing policy, and medical resources, the model simulation predicts whether the re-opening policy is likely to lead to a further outbreak of the epidemic and provides evidence-based support for decisions regarding safe re-opening during an ongoing epidemic. Keyords COVID-19; Risk of re-opening; Effectiveness of re-opening policies; IPC measures; SD modelling.

scholarly journals Modelling the Potential Impact of Social Distancing on the COVID-19 Epidemic in South Africa

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
F. Nyabadza ◽  
F. Chirove ◽  
C. W. Chukwu ◽  
M. V. Visaya
Keyword(s):  
South Africa ◽  
Deterministic Model ◽  
Cumulative Number ◽  
The Novel ◽  
Social Distancing ◽  
The Social ◽  
Potential Impact ◽  
Policy Direction ◽  
Novel Coronavirus ◽  
The Impact

The novel coronavirus (COVID-19) pandemic continues to be a global health problem whose impact has been significantly felt in South Africa. With the global spread increasing and infecting millions, containment efforts by countries have largely focused on lockdowns and social distancing to minimise contact between persons. Social distancing has been touted as the best form of response in managing a rapid increase in the number of infected cases. In this paper, we present a deterministic model to describe the impact of social distancing on the transmission dynamics of COVID-19 in South Africa. The model is fitted to data from March 5 to April 13, 2020, on the cumulative number of infected cases, and a scenario analysis on different levels of social distancing is presented. The model shows that with the levels of social distancing under the initial lockdown level between March 26 and April 13, 2020, there would be a projected continued rise in the number of infected cases. The model also looks at the impact of relaxing the social distancing measures after the initial announcement of the lockdown. It is shown that relaxation of social distancing by 2% can result in a 23% rise in the number of cumulative cases whilst an increase in the level of social distancing by 2% would reduce the number of cumulative cases by about 18%. The model results accurately predicted the number of cases after the initial lockdown level was relaxed towards the end of April 2020. These results have implications on the management and policy direction in the early phase of the epidemic.

scholarly journals The challenges of distance learning in countries undergoing transition during the COVID-19 pandemic - case study

2021 ◽  
Vol 24 ◽  
pp. 196-207
Author(s):  
Naser Rugova ◽  
Elmire Nikci – Rexha ◽  
Elmi Berisha ◽  
Fallanza Beka Bajrami
Keyword(s):  
Higher Education ◽  
Online Learning ◽  
Distance Learning ◽  
Learning Process ◽  
Control Measures ◽  
World Health ◽  
Social Distancing ◽  
First Case ◽  
The World ◽  
The Impact

Virtual learning, also known as online learning or distance learning has transformed the face of the education system for quite some time. Now, it is rapidly becoming an integral aspect and a common tool, in the broader aspect of higher education, as a result of the COVID-19 pandemic. In addition to providing an alternative method of learning in the digital age, online learning offers students the opportunity to learn new skills or improve existing ones.  On March 11, 2020, the World Health Organization declared COVID-19 a global pandemic. Following the speed with which COVID-19 spread to all parts of the world and to curb the spread of the disease, most governments around the world, including the Republic of Kosovo, authorized unprecedented social control measures to stop this disease unknown. These measures, among others, required social distancing and temporary physical closure of educational institutions. The first case of COVID 19 in Kosovo was identified on March 13, 2020, social distancing - full closure came into force on March 15, while UBT Higher Education Institution started online learning on March 16, 2020, the first in Kosovo and possibly in the Western Balkans. This teaching-learning process was a novelty for Kosovo and was applied for the first time. Objective: The main objective of the current survey was to study the impact of E-learning on students' academic performance and their evaluations of this form of teaching in general. The purpose of this paper is to reflect as professionally as possible the organization of distance learning, the effects on the teaching and learning process as well as the form and level of communication and teacher-student relations in this process which was a novelty for Kosovo and UBT as one of the largest Private Colleges in the region.

scholarly journals Modelling the potential impact of social distancing on the COVID-19 epidemic in South Africa

2020 ◽  
Author(s):  
F. Nyabadza ◽  
F. Chirove ◽  
W. Chukwu ◽  
M.V. Visaya
Keyword(s):  
South Africa ◽  
Deterministic Model ◽  
Cumulative Number ◽  
The Novel ◽  
Social Distancing ◽  
The Social ◽  
Potential Impact ◽  
Policy Direction ◽  
Novel Coronavirus ◽  
The Impact

AbstractThe novel coronavirus (COVID-19) pandemic continues to be a global health problem whose impact has been significantly felt in South Africa. Social distancing has been touted as the best form of response in managing a rapid increase in the number of infected cases. In this paper, we present a deterministic model to model the impact of social distancing on the transmission dynamics of COVID-19 in South Africa. The model is fitted to the currently available data on the cumulative number of infected cases and a scenario analysis on different levels of social distancing are presented. The results show a continued rise in the number of cases in the lock down period with the current levels of social distancing albeit at a lower rate. The model shows that the number of cases will rise to above 4000 cases by the end of the lockdown. The model also looks at the impact of relaxing the social distancing measures after the initial announcement of the lock down measures. A relaxation of the social distancing by 2% can result in a 23% rise in the number of cumulative cases while on the other hand increasing the levels of social distancing by 2% would reduce the number of cumulative cases by about 18%. These results have implications on the management and policy direction in the early phases of the epidemic.

scholarly journals Role of Mathematical Model in Curbing COVID-19 in Nigeria

2021 ◽  
Vol 3 (2) ◽  
pp. 135-147
Author(s):  
Chinwendu Emilian Madubueze ◽  
Nkiru Maria Akabuike ◽  
Sambo Dachollom
Keyword(s):  
Mathematical Model ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Viral Disease ◽  
Control Measures ◽  
Social Distancing ◽  
Testing Rate ◽  
Intervention Measures ◽  
The Impact ◽  
The Basic Reproduction Number

COVID-19 is a viral disease that is caused by Severe Acute Respiratory Syndrome coronavirus 2 (SARSCoV-2) which has no approved vaccine. Based on the available non-pharmacological interventions like wearing of face masks, observing social distancing, and lockdown, this work assesses the impact of non-pharmaceutical control measures (social distancing and use of face-masks) and mass testing on the transmission of COVID-19 in Nigeria. A mathematical model for COVID-19 is formulated with intervention measures (observing social distancing and wearing of face masks) and mass testing. The basic reproduction number, R_0, is computed using next-generation method while the disease-free equilibrium is found to be locally and globally asymptotically stable when R_0< 1. The model is parameterized using Nigeria data on COVID-19 in Nigeria. The basic reproduction number is found to be less than unity (R_0 < 1) either when the compliance with intervention measures is moderate (50% <= alpha< 70%) and the testing rate per day is moderate (0,5 <=alpha_2 < 0,7) or when the compliance with intervention measures is strict (alpha>=70%) and the testing rate per day is poor (alpha_2 = 0,3). This implies that Nigeria will be able to halt the spread of COVID-19 under these two conditions. However, it will be easier to enforce strict compliance with intervention measures in the presence of poor testing rate due to the limited availability of testing facilities and manpower in Nigeria. Hence, this study advocates that Nigerian governments (Federal and States) should aim at achieving a testing rate of at least 0.3 per day while ensuring that all the citizens strictly comply with wearing face masks and observing social distancing in public.

Characterizing the effectiveness of COVID-19 mitigation measures: A data-centric approach (Preprint)

2020 ◽  
Author(s):  
Lukman Olagoke ◽  
Ahmet E. Topcu
Keyword(s):  
Control Measure ◽  
Control Measures ◽  
World Health ◽  
Mitigation Measures ◽  
Effective Control ◽  
The World ◽  
Decision Making Processes ◽  
And Performance ◽  
Health Organization ◽  
The Impact

BACKGROUND COVID-19 represents a serious threat to both national health and economic systems. To curb this pandemic, the World Health Organization (WHO) issued a series of COVID-19 public safety guidelines. Different countries around the world initiated different measures in line with the WHO guidelines to mitigate and investigate the spread of COVID-19 in their territories. OBJECTIVE The aim of this paper is to quantitatively evaluate the effectiveness of these control measures using a data-centric approach. METHODS We begin with a simple text analysis of coronavirus-related articles and show that reports on similar outbreaks in the past strongly proposed similar control measures. This reaffirms the fact that these control measures are in order. Subsequently, we propose a simple performance statistic that quantifies general performance and performance under the different measures that were initiated. A density based clustering of based on performance statistic was carried out to group countries based on performance. RESULTS The performance statistic helps evaluate quantitatively the impact of COVID-19 control measures. Countries tend show variability in performance under different control measures. The performance statistic has negative correlation with cases of death which is a useful characteristics for COVID-19 control measure performance analysis. A web-based time-line visualization that enables comparison of performances and cases across continents and subregions is presented. CONCLUSIONS The performance metric is relevant for the analysis of the impact of COVID-19 control measures. This can help caregivers and policymakers identify effective control measures and reduce cases of death due to COVID-19. The interactive web visualizer provides easily digested and quick feedback to augment decision-making processes in the COVID-19 response measures evaluation. CLINICALTRIAL Not Applicable

Impact of natural hazards on the evolving COVID-19 pandemic: cases from Greece

2021 ◽  
Author(s):  
Maria Mavrouli ◽  
Spyridon Mavroulis ◽  
Efthymios Lekkas
Keyword(s):  
Built Environment ◽  
Natural Hazards ◽  
Local Population ◽  
World Health ◽  
Economic Losses ◽  
The Novel ◽  
Hydrological Hazards ◽  
Eastern Aegean ◽  
The Impact ◽  
Post Disaster

&lt;p&gt;The first confirmed COVID-19 case was reported in December 2019. Over the first months of 2020, the novel SARS-CoV-2 virus was spread worldwide resulting in the declaration on March 11, 2020 of a global COVID-19 pandemic by the World Health Organization. The evolving pandemic has resulted in over 1900000 fatalities worldwide (as of January 8, 2021), while all sectors of the everyday life has been affected in numerous and varied ways. Natural hazards did not stop for the novel coronavirus. When the natural hazards cross the path of an evolving pandemic, compound emergencies emerge and are characterized by various effects and new unprecedented challenges.&lt;/p&gt;&lt;p&gt;Greece was no exception. Geological, hydrological and meteorological hazards took place in several parts of the country and they affected the local population, the natural and the built environment including buildings, infrastructures and lifelines. Among the most destructive effects in terms of human and economic losses was the March 21, 2020, Mw=5.7, Epirus (northwestern Greece) earthquake, the August 9, 2020, Evia (central Greece) flood, the September 17, 2020, Ianos medicane and the October 30, 2020, Mw=7.0, Samos (Eastern Aegean Sea) earthquake.&lt;/p&gt;&lt;p&gt;In order to identify the potential impact of the aforementioned disasters on the evolution of the COVID-19 pandemic in the disaster-affected areas, the officially reported laboratory-confirmed daily COVID-19 cases for the pre- and post- disaster periods from the disaster-affected areas were used. The impact of disasters in the evolution of the pandemic in the studied disaster-affected areas comprises increasing and decreasing trends and stability of the COVID-19 cases during the post-disaster period. More specifically, the geological and the hydrological hazards and the induced disasters negligibly affected the evolution of pandemic in the affected areas, while the hydrometeorological hazards resulted in increasing trends of the post-disaster reported COVID-19 cases in various affected areas.&lt;/p&gt;&lt;p&gt;The detected trends are strongly associated with the pre-existing viral load and infection rate in the disaster-affected areas, to the emergency response actions adapted to adopt provisional measures for the mitigation and elimination of COVID-19 consequences, to demographic features of the affected areas and to the intensity of the induced disasters and their effects on the local population (fatalities and injuries), the natural environment (primary and secondary environmental effects) and the built environment (structural damage to buildings, infrastructures and lifelines).&lt;/p&gt;

scholarly journals Mathematical Modelling, Simulation, and Optimal Control of the 2014 Ebola Outbreak in West Africa

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Amira Rachah ◽  
Delfim F. M. Torres
Keyword(s):  
Mathematical Model ◽  
Optimal Control ◽  
Ebola Virus ◽  
World Health ◽  
Multiple Shooting ◽  
Multiple Shooting Method ◽  
Major Outbreak ◽  
Health Organization ◽  
Spread Of Infection ◽  
The Impact

The Ebola virus is currently one of the most virulent pathogens for humans. The latest major outbreak occurred in Guinea, Sierra Leone, and Liberia in 2014. With the aim of understanding the spread of infection in the affected countries, it is crucial to modelize the virus and simulate it. In this paper, we begin by studying a simple mathematical model that describes the 2014 Ebola outbreak in Liberia. Then, we use numerical simulations and available data provided by the World Health Organization to validate the obtained mathematical model. Moreover, we develop a new mathematical model including vaccination of individuals. We discuss different cases of vaccination in order to predict the effect of vaccination on the infected individuals over time. Finally, we apply optimal control to study the impact of vaccination on the spread of the Ebola virus. The optimal control problem is solved numerically by using a direct multiple shooting method.

scholarly journals The African swine fever control zone in South Africa and its current relevance

2016 ◽  
Vol 83 (1) ◽  
Author(s):  
Noluvuyo R. Magadla ◽  
Wilna Vosloo ◽  
Livio Heath ◽  
Bruce Gummow
Keyword(s):  
South Africa ◽  
Disease Control ◽  
African Swine Fever ◽  
Control Measures ◽  
Maximum Temperature ◽  
Boundary Line ◽  
Control Line ◽  
Control Zone ◽  
Ornithodoros Moubata ◽  
The Impact

African swine fever (ASF) has been reported in South Africa since the early 20th century. The disease has been controlled and confined to northern South Africa over the past 80 years by means of a well-defined boundary line, with strict control measures and movement restrictions north of this line. In 2012, the first outbreak of ASF outside the ASF control zone since 1996 occurred. The objective of this study was to evaluate the current relevance of the ASF control line as a demarcation line between endemic ASF (north) areas and ASF-free (south) area and to determine whether there was a need to realign its trajectory, given the recent outbreaks of ASF, global climate changes and urban development since the line’s inception. A study of ASF determinants was conducted in an area 20 km north and 20 km south of the ASF control line, in Limpopo, Mpumalanga, North West and Gauteng provinces between May 2008 and September 2012. The study confirmed that warthogs, warthog burrows and the soft tick reservoir, Ornithodoros moubata, are present south of the ASF control line, but no virus or viral DNA was detected in these ticks. There appears to be an increasing trend in the diurnal maximum temperature and a decrease in humidity along the line, but the impact of these changes is uncertain. No discernible changes in minimum temperatures and average rainfall along the disease control line were observed between 1992 and 2014. Even though the reservoirs were found south of the ASF boundary line, the study concluded that there was no need to realign the trajectory of the ASF disease control line, with the exception of Limpopo Province. However, the provincial surveillance programmes for the reservoir, vector and ASF virus south of this line needs to be maintained and intensified as changing farming practices may favour the spread of ASF virus beyond the control line.Keywords: African swine fever; warthog burrow; Ornithodoros moubata;control line

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