scholarly journals Mathematical Modeling of COVID-19 Pandemic in the African Continent

2020 ◽  
Author(s):  
Nawel Aries ◽  
Houdayfa Ounis
Keyword(s):  
Public Health ◽  
Mathematical Modeling ◽  
Preventive Measures ◽  
Sir Model ◽  
African Continent ◽  
Mathematical Epidemiology ◽  
Short Term ◽  
Health Measures ◽  
Realistic Assessment ◽  
Official Data

AbstractThe present work aims to give a contribution to the understanding of the highly infectious pandemic caused by the COVID-19 in the African continent. The study focuses on the modelling and the forecasting of COVID-19 spread in the most affected African continent, namely: Morocco, Algeria, Tunisia, Egypt and South Africa and for the sake of comparison two of the most affected European country are also considered, namely: France and Italy. To this end, an epidemiological SEIQRDP model is presented, which is an adaptation of the classic SIR model widely used in mathematical epidemiology. In order to better coincide with the preventive measures taken by the governments to deal with the spread of COVID-19, this model considers the quarantine. For the identification of the model’s parameters, official data of the pandemic up to August 1st, 2020 are considered. The results show that the number of infections due to the use of quarantine is expected to be very low provided the isolation is effective. However, it is increasing in some countries with the early lifting of containment. Finally, the information provided by the SEIQRDP model could help to establish a realistic assessment of the short-term pandemic situation. Moreover, this will help maintain the most appropriate and necessary public health measures after the lockdown lifting.

scholarly journals Spread of Epidemic Disease on Edge-Weighted Graphs from a Database: A Case Study of COVID-19

2021 ◽  
Vol 18 (9) ◽  
pp. 4432
Author(s):  
Ronald Manríquez ◽  
Camilo Guerrero-Nancuante ◽  
Felipe Martínez ◽  
Carla Taramasco
Keyword(s):  
Public Health ◽  
Infectious Diseases ◽  
Preventive Measures ◽  
Weighted Graph ◽  
Real Data ◽  
Sir Model ◽  
Weighted Graphs ◽  
Epidemic Disease ◽  
The Real

The understanding of infectious diseases is a priority in the field of public health. This has generated the inclusion of several disciplines and tools that allow for analyzing the dissemination of infectious diseases. The aim of this manuscript is to model the spreading of a disease in a population that is registered in a database. From this database, we obtain an edge-weighted graph. The spreading was modeled with the classic SIR model. The model proposed with edge-weighted graph allows for identifying the most important variables in the dissemination of epidemics. Moreover, a deterministic approximation is provided. With database COVID-19 from a city in Chile, we analyzed our model with relationship variables between people. We obtained a graph with 3866 vertices and 6,841,470 edges. We fitted the curve of the real data and we have done some simulations on the obtained graph. Our model is adjusted to the spread of the disease. The model proposed with edge-weighted graph allows for identifying the most important variables in the dissemination of epidemics, in this case with real data of COVID-19. This valuable information allows us to also include/understand the networks of dissemination of epidemics diseases as well as the implementation of preventive measures of public health. These findings are important in COVID-19’s pandemic context.

scholarly journals Prediction of the propagation of SARS-CoV-2 in Amapá State, Amazon Region, Brazil, by mathematical modeling

2020 ◽  
pp. 73-95
Author(s):  
Neylan Leal Dias ◽  
Edcarlos Vasconcelos da Silva ◽  
Marcelo Amanajas Pires ◽  
Daniel Chaves ◽  
Katsumi Letra Sanada ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Temporal Evolution ◽  
Sir Model ◽  
Amazon Region ◽  
The Other ◽  
Short Term ◽  
Exponential Behavior ◽  
Linear Projection ◽  
The Third ◽  
The One

This article presents an analysis of the spread of SARS-CoV-2 in Amapá using three approaches. In the first, the ICL model for the pandemic applied to Brazil was used to implement a comparative linear projection for the Amapá population. The second approach was developed with the short-term solution of the standard SIR model where it was shown that the typical exponential behavior satisfactorily describes the data for the first weeks of the epidemic, but soon after there are early discrepancies due to a sudden slowdown in the temporal evolution number of cases due to isolation measures. This new regime is appropriately described with the third approach which is based on the vSIR model which is a variant of the SIR model. The results presented enable, on the one hand, a better understanding of the scenarios already faced by the population and on the other hand provide short-term projections that will be constantly updated on the link[11].

scholarly journals Mass Media and Health Communication During the Pandemic

2021 ◽  
Vol 2 (2) ◽  
pp. 56-57
Author(s):  
Ms. Asfiya Aziz
Keyword(s):  
Public Health ◽  
Mass Media ◽  
Health Communication ◽  
Behaviour Change ◽  
Preventive Measures ◽  
Healthcare Sector ◽  
Media Industry ◽  
Health Measures ◽  
The Media ◽  
Healthy Behaviour

Importance of specialized health communication has been demonstrated fully during the recent COVID 19 pandemic. New variants of the virus continue to emerge, the larger portion of the country’s population remains unvaccinated, and booster doses are becoming essential. Therefore, the need for sustained interest in health communication through mass media is far from over. Health communication helps public understand the threat and make informed choices about the preventive measures and treatment. Done effectively, it can produce behaviour change, prevent panic and ensure the participation of populations in governments’ public health measures. Healthcare sector possesses the necessary knowledge to impart this information to the media industry which is largely unstructured and learning from experiences. Therefore, the healthcare sector needs to communicate effectively with the mass media representatives in order to influence the population in adopting and continuing healthy behaviour to fight the pandemic.

scholarly journals SOME ASPECTS ABOUT MATHEMATICAL MODELING FOR EPIDEMIC MANAGEMENT

2021 ◽  
Vol 13 (2) ◽  
pp. 19-28
Author(s):  
Amelia BUCUR ◽  
Keyword(s):  
Public Health ◽  
Mathematical Modeling ◽  
Mathematical Models ◽  
Health System ◽  
Public Health System ◽  
Sir Model ◽  
Mathematical Study ◽  
The Public ◽  
A Value ◽  
New Models

The mathematical study of epidemics and their management has been performed for many years, however, in the last few years, new models have been published. Public health is considered very important and has to be monitored, as it is permanently under risk due to the appearance of even more types of microorganisms. Compartmental models, such as exponential models, SI, SIS, SIR, SEIRS, SEIAR, MESIR models, other generalized SIR models were and still are remarkable for studying the spread of an epidemic and for their simulations in software such as MATLAB, Maple, GLEAMviz, etc. The paper has two main objectives: a. to present new simulations in Maple and GLEAMviz for the spread of COVID-19; b. to suggest a generalization of the SIR model for analyzing the spread of COVID-19 and a simulation of it in GLEAMviz. The conclusions are that, generally, mathematical models show a value of a reproduction threshold, which can be used to forecast whether the pandemic is the increasing or decreasing phase, and that mathematical models and simulations in various programs facilitate the improvement of methods of analysis of an epidemic situation and the management of the public health system.

scholarly journals Risk Perception of COVID-19 Infection and Adherence to Preventive Measures among Adolescents and Young Adults

Children ◽  
2020 ◽  
Vol 7 (12) ◽  
pp. 311
Author(s):  
Xin Yu Yang ◽  
Rui Ning Gong ◽  
Samuel Sassine ◽  
Maxime Morsa ◽  
Alexandra Sonia Tchogna ◽  
...  
Keyword(s):  
Public Health ◽  
Young Adults ◽  
Risk Perception ◽  
Perceived Risk ◽  
Online Survey ◽  
Preventive Measures ◽  
Adolescents And Young Adults ◽  
Cross Sectional ◽  
Community Partners ◽  
Health Measures

To explore factors influencing adolescents and young adults’ (AYAs) risk perception of COVID-19 and adherence to public health measures, we conducted a cross-sectional online survey of AYAs (14–22 years old) from Quebec (Canada) recruited through school and community partners in April 2020 during the first wave of the COVID-19 pandemic. The study included 3037 participants (mean age = 17.7 years, 74.6% female). AYAs had higher mean (standard deviation (SD)) risk perception of COVID-19 for their relatives (8.2 (1.9)) than for themselves (5.6 (2.6)) (p < 0.001). Factors associated with higher risk perception included higher disease knowledge (adjusted odds ratio (aOR) 1.06, 95% CI 1.01–1.11), presence of chronic disease (aOR 2.31, 95%CI 1.82–2.93) and use of immunosuppressants (aOR 2.53, 95%CI 1.67–3.87). AYAs with a higher risk perception (aOR 1.06, 95%CI 1.02–1.10) those wishing to help flatten the disease curve (aOR 1.18, 95%CI 1.12–1.25) or to protect their family/friends (aOR 1.14, 95%CI 1.05–1.24) were more likely to engage in preventive behaviors. Self-perceived risk and desire to protect others were significantly associated with adherence to preventive measures among youth. These findings may help inform public health messaging to AYAs in the current and future pandemics.

scholarly journals How to remove the testing bias in CoV-2 statistics

2020 ◽  
Author(s):  
Klaus Wälde
Keyword(s):  
Public Health ◽  
Time Series ◽  
Severity Index ◽  
Sir Model ◽  
Health Measures ◽  
Testing Bias ◽  
Positive Rate ◽  
Representative Testing ◽  
Over Time

BACKGROUNDPublic health measures and private behaviour are based on reported numbers of SARS-CoV-2 infections. Some argue that testing influences the confirmed number of infections.OBJECTIVES/METHODSDo time series on reported infections and the number of tests allow one to draw conclusions about actual infection numbers? A SIR model is presented where the true numbers of susceptible, infectious and removed individuals are unobserved. Testing is also modelled.RESULTSOfficial confirmed infection numbers are likely to be biased and cannot be compared over time. The bias occurs because of different reasons for testing (e.g. by symptoms, representative or testing travellers). The paper illustrates the bias and works out the effect of the number of tests on the number of reported cases. The paper also shows that the positive rate (the ratio of positive tests to the total number of tests) is uninformative in the presence of non-representative testing.CONCLUSIONSA severity index for epidemics is proposed that is comparable over time. This index is based on Covid-19 cases and can be obtained if the reason for testing is known.

scholarly journals Socio-cultural challenges in the implementation of COVID-19 public health measures: Results from a qualitative study in Punjab, Pakistan

2020 ◽  
Author(s):  
Rubeena Zakar ◽  
Farhan Yousaf ◽  
Muhammad Zakar ◽  
Florian Fischer
Keyword(s):  
Public Health ◽  
Qualitative Study ◽  
Cultural Context ◽  
Preventive Measures ◽  
Control Program ◽  
Living Environment ◽  
Local Context ◽  
Preventive Strategies ◽  
Framework Analysis ◽  
Health Measures

Abstract Background: Informed public health measures are crucial to curb the COVID-19 pandemic. The socio-cultural context is important to understand the success or failure of implementing public health measures. This study explores the social and behavioral response to COVID-19 and unveils challenges in the implementation of related public health measures in Pakistan. Methods: Within this qualitative study, we conducted 34 telephonic/online in-depth interviews with youths, adults, old-age people, and healthcare professionals in the Punjab province of Pakistan. Framework analysis was used for data analysis. Results: People’s poor understanding about COVID-19 and the need for preventive measures were the major challenge in implementation of public health preventive strategies. Study participants reported that the lockdown strategy increased poverty and unemployment. People’s poor living conditions and living environment compelled them to not follow social distancing and restricting themselves to homes. Additionally, an underdeveloped healthcare system was one of the major challenges for Pakistan. False and misleading information about the disease had significant consequences for the COVID control program. In Pakistan, the culture of denial related to the epidemiology of COVID-19 were important challenges within the implementation of public health preventive measures. Conclusions: It is extremely important that public health experts and social scientists work together to understand the contextual socio-cultural factors which shape behaviors associated with the spread of a pandemic. This knowledge is needed in order to design and implement preventive strategies that could effectively work in the local context.

scholarly journals Evaluating Short-term Forecast among Different Epidemiological Models under a Bayesian Framework

2020 ◽  
Author(s):  
Qiwei Li ◽  
Tejasv Bedi ◽  
Guanghua Xiao ◽  
Yang Xie
Keyword(s):  
Public Health ◽  
Predictive Modeling ◽  
Growth Models ◽  
Sir Model ◽  
Global Scale ◽  
Bayesian Framework ◽  
Epidemiological Models ◽  
Short Term ◽  
Predictive Capacity ◽  
Term Forecast

AbstractForecasting of COVID-19 daily confirmed cases has been one of the several challenges posed on the governments and health sectors on a global scale. To facilitate informed public health decisions, the concerned parties rely on short-term daily projections generated via predictive modeling. We calibrate stochastic variants of growth models and the standard SIR model into one Bayesian framework to evaluate their short-term forecasts. In summary, it was noted that none of the models proved to be golden standards across all the regions in their entirety, while all outperformed ARIMA in a predictive capacity as well as in terms of interpretability.

scholarly journals Global predictions of short- to medium-term COVID-19 transmission trends : a retrospective assessment

2021 ◽  
Author(s):  
Sangeeta Bhatia ◽  
Kris Parag ◽  
Jack Wardle ◽  
Natsuko Imai ◽  
Sabine van Elsland ◽  
...  
Keyword(s):  
Public Health ◽  
Coverage Probability ◽  
Credible Interval ◽  
Planning Tool ◽  
Medium Term ◽  
Short Term ◽  
Forecast Horizon ◽  
Health Measures ◽  
Retrospective Assessment ◽  
Relative Errors

Abstract From 8th March to 29th November 2020, we produced weekly estimates of SARS-CoV-2 transmissibility and forecasts of deaths due to COVID-19 for 81 countries with evidence of sustained transmission. We also developed a novel heuristic to combine weekly estimates of transmissibility to produce forecasts over a 4-week horizon. We evaluated the robustness of the forecasts using relative error, coverage probability, and comparisons with null models. During the 39-week period covered by this study, both the short- and medium-term forecasts captured well the epidemic trajectory across different waves of COVID-19 infections with small relative errors over the forecast horizon. The model was well calibrated with 56.3\% and 45.6\% of the observations lying in the 50\% Credible Interval in 1-week and 4-week ahead forecasts respectively. We could accurately characterise the overall phase of the epidemic up to 4-weeks ahead in 84.9\% of country-days. The medium-term forecasts can be used in conjunction with the short-term forecasts of COVID-19 mortality as a useful planning tool as countries continue to relax public health measures.

scholarly journals Sociocultural Challenges in the Implementation of COVID-19 Public Health Measures: Results From a Qualitative Study in Punjab, Pakistan

2021 ◽  
Vol 9 ◽  
Author(s):  
Rubeena Zakar ◽  
Farhan Yousaf ◽  
Muhammad Zakria Zakar ◽  
Florian Fischer
Keyword(s):  
Public Health ◽  
Qualitative Study ◽  
Preventive Measures ◽  
Living Environment ◽  
Sociocultural Factors ◽  
Framework Analysis ◽  
Social Scientists ◽  
Health Measures ◽  
Important Challenge ◽  
Study Participants

Informed public health measures are crucial to curb the COVID-19 pandemic. The sociocultural context is important to understand the success or failure of implementing public health measures. This study explores the social and behavioral response to COVID-19 and unveils challenges in the implementation of related public health measures in Pakistan. Within this qualitative study, we conducted 34 telephonic/online in-depth interviews with youths, adults, elderly people, and healthcare professionals in the Punjab province of Pakistan. Framework analysis was used for data analysis. People's poor understanding about COVID-19 and the need for preventive measures were the major challenge in implementing public health preventive strategies. Study participants reported that the lockdown strategy increased poverty and unemployment. People's poor living conditions and living environment compelled them not to follow social distancing and restricting themselves to home. Additionally, an underdeveloped healthcare system was one of the major challenges for Pakistan. The culture of denial in Pakistan related to the epidemiology of COVID-19 was an important challenge within the implementation of public health preventive measures. It is extremely important that public health experts and social scientists work together to understand the contextual sociocultural factors which shape behaviors associated with the spread of a pandemic.

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