Model Development and Prediction of Covid-19 Pandemic in Bangladesh with Nonlinear Incident

We introduce a SEIRD compartmental model to analyze the dynamics of the pandemic in Bangladesh. The multi-wave patterns of the new infective in Bangladesh from the day of the official confirmation to August 15, 2021, are simulated in the proposed SEIRD model. To solve the model equations numerically, we use the RK-45 method. Primarily, we establish some theorems including local and global stability for the proposed model. The analysis shows that the death curve simulated by the model provides a very good agreement with the officially confirmed death data for the Covid-19 pandemic in Bangladesh. Furthermore, the proposed model estimates the duration and peaks of Covid-19 in Bangladesh which are compared with the real data.

Impact of vaccination on the entire population and dose-response relation of COVID-19.

Objective: The objective of this study is to develop a mathematical model for the COVID-19 pandemic including vaccination, the transmissibility of the virus-pathogen dose-response relationship, vaccine efficiency, and vaccination rate. Methods: The Runge-Kutta (RK-45) method was applied to solve the proposed model with MATLAB code and the calculated results show the dynamics of the individuals in each compartment. The data of total death due to the COVID-19 pandemic in the case of the USA were collected from GitHub and the re-use of this data needs no ethical clearance. The control reproduction number was used to assess the dose-response relationship and critical vaccination coverage. Results: We have calculated the probability of infection and the infection risk against the different exposure doses and the virus copies, respectively. The results show that the probability of infection increases with the increasing exposure dose for certain virus copies and the risk of infection decreases with the increasing of virus copies for a certain exposure dose. The results also show that the critical vaccination coverage demands increase with an increase in transmission rate and decrease with increasing vaccine efficacy. Conclusions: It was seen that the critical vaccination coverage corresponding to an increased transmission rate rise sharply in the beginning and then reached a threshold. Moreover, the real data of the total death cases in the USA were compared with the fitted curved of the model which validated the proposed model. Vaccination against COVID-19 is essential to control the pandemic, and achieving high vaccine uptake in the population can reduce the pandemic as fast as possible.

Objetivo: El objetivo de este estudio es desarrollar un modelo matemático para la pandemia de COVID-19 que incluya la vacunación, la transmisibilidad de la relación dosis-respuesta virus-patógeno, la eficacia de la vacuna y la tasa de vacunación. Métodos: Se aplicó el método de Runge-Kutta (RK-45) para resolver el modelo propuesto con código MATLAB y los resultados calculados muestran la dinámica de los individuos en cada compartimento. Los datos de muerte total por la pandemia de COVID-19 en el caso de EE. UU. se recopilaron de GitHub y la reutilización de estos datos no necesita autorización ética. El número de reproducción de control se utilizó para evaluar la relación dosis-respuesta y la cobertura de vacunación crítica. Resultados: Hemos calculado la probabilidad de infección y el riesgo de infección frente a las diferentes dosis de exposición y las copias del virus, respectivamente. Los resultados muestran que la probabilidad de infección aumenta con el aumento de la dosis de exposición para ciertas copias del virus y el riesgo de infección disminuye con el aumento de las copias del virus para una determinada dosis de exposición. Los resultados también muestran que las demandas críticas de cobertura de vacunación aumentan con el aumento de la tasa de transmisión y disminuyen con el aumento de la eficacia de la vacuna. Conclusiones: Se observó que las coberturas críticas de vacunación correspondientes a una mayor tasa de transmisión aumentaron bruscamente al principio y luego alcanzaron un umbral. Además, se compararon los datos reales del total de casos de muerte en EE. UU. con la curva ajustada del modelo que validó el modelo propuesto. La vacunación contra el COVID-19 es fundamental para controlar la pandemia, y lograr una alta captación de vacunas en la población puede reducir la pandemia lo más rápido posible.

Model Development and Prediction of Covid-19 Pandemic in Bangladesh with Nonlinear Incident

We introduce a SEIRD compartmental model to analyze the dynamics of the pandemic in Bangladesh. The multi-wave patterns of the new infective in Bangladesh from the day of the official confirmation to August 15, 2021, are simulated in the proposed SEIRD model. To solve the model equations numerically, we use the RK-45 method. Primarily, we establish some theorems including local and global stability for the proposed model. The analysis shows that the death curve simulated by the model provides a very good agreement with the officially confirmed death data for the Covid-19 pandemic in Bangladesh. Furthermore, the proposed model estimates the duration and peaks of Covid-19 in Bangladesh which are compared with the real data.

Data analysis and prediction of the COVID-19 outbreak in the first and second waves for top 5 affected countries in the world

In this paper, we introduce a SEIATR compartmental model to analyze and predict the COVID-19 outbreak in the Top 5 affected countries in the world, namely the USA, India, Brazil, France, and Russia. The officially confirmed cases and death due to COVID-19 from the day of the official confirmation to June 30, 2021 are considered for each country. Primarily, we use the data to make a comparison between the cumulative cases and deaths due to COVID-19 among these five different countries. This analysis allows us to infer the key parameters associated with the dynamics of the disease for these five different countries. For example, the analysis reveals that the infection rate is much higher in the USA, Brazil, and France compared to that of India and Russia, while the recovery rate is found almost the same for these countries. Further, the death rate is measured higher in Brazil as opposed to India, where it is found much lower among the remaining countries. We then use the SEIART compartmental model to characterize the first and second waves of these countries, as well as to investigate and identify the influential model parameters and nature of the virus transmissibility in respective countries. Besides estimating the time-dependent reproduction number (Rt) for these countries, we also use the model to predict the peak size and the time occurring peak in respective countries. The analysis demonstrates that COVID-19 was observed to be much more infectious in the second wave than the first wave in all countries except France. The results also demonstrate that the epidemic took off very quickly in the USA, India, and Brazil compared to two other countries considered in this study. Furthermore, the prediction of the epidemic peak size and time produced by our model provides a very good agreement with the officially confirmed cases data for all countries expect Brazil.

Multisystem Inflammatory Syndrome of a Neonate From a COVID-19-Infected Mother: A Case Report.

In neonates, the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 - COVID-19) is lower. There is the potential for vertical transmission of SARS-CoV-2. To date, only a few reports suggest this possibility. Neonates usually have mild symptoms, but some develop multisystem involvement, which is a concern. COVID-19 infections have been reported both in pregnant women and their neonates. However, the evidence of vertical or horizontal transmission modes has not been fully established. We recorded a case study where a 33-year-old mother was tested positive for COVID-19 infection by RT-PCR during her 27th week of gestation and needed ventilator support for her respiratory distress at that time for 11 days. Subsequently, she gave birth to a female baby at the 35th week via a lower uterine segment cesarean section. The neonate manifested a severe multisystem inflammatory syndrome associated with her possible COVID-19 infection. Sharing her uncommon clinical presentation, immunological syndrome, and disease outcome are noteworthy for similar unforeseen pediatric case management to help guide future investigations and care.

Management of Children Admitted to Hospitals across Bangladesh with Suspected or Confirmed COVID-19 and the Implications for the Future: A Nationwide Cross-Sectional Study.

There is an increasing focus on researching children admitted to hospital with new variants of COVID-19, combined with concerns with hyperinflammatory syndromes and the overuse of antimicrobials. Paediatric guidelines have been produced in Bangladesh to improve their care. Consequently, the objective is to document the management of children with COVID-19 among 24 hospitals in Bangladesh. Key outcome measures included the percentage prescribed different antimicrobials, adherence to paediatric guidelines and mortality rates using purposely developed report forms. The majority of 146 admitted children were aged 5 years or under (62.3%) and were boys (58.9%). Reasons for admission included fever, respiratory distress and coughing; 86.3% were prescribed antibiotics, typically parenterally, on the WHO 'Watch' list, and empirically (98.4%). There were no differences in antibiotic use whether hospitals followed paediatric guidance or not. There was no prescribing of antimalarials and limited prescribing of antivirals (5.5% of children) and antiparasitic medicines (0.7%). The majority of children (92.5%) made a full recovery. It was encouraging to see the low hospitalisation rates and limited use of antimalarials, antivirals and antiparasitic medicines. However, the high empiric use of antibiotics, alongside limited switching to oral formulations, is a concern that can be addressed by instigating the appropriate programmes.

Trends of 2019-nCoV in South Asian countries and prediction of the epidemic peaks.

A deterministic compartmental model of the corona virus diseases has been introduced to investigate the current outbreak and epidemic peaks of the 2019-nCoV in South Asian countries. We have done details analysis of the above mentioning model and demonstrated its application using publicly reported data. Based on the reported data, we have determined the new infective rate, ß = 0.0017, ß = 0.00069, ß = 0.0011 and ß = 0.00047 for India, Pakistan, Bangladesh and Afghanistan, respectively and these values are not found for other countries due to insufficient data. According to present model, the epidemic under the most restrictive measures was observed of peak on around June 29 in Bangladesh with a peak size of 4100 infectious individuals which was closed to real size of 4014. In the same way, the model results also showed that the epidemic peaks were found on around September 16 in India, June 13 in Pakistan and on June 5 in Afghanistan with the peak sizes of 97,500, 6950 and 935, respectively those were closed to the real values. In addition, we have derived a model-implied basic reproduction number for each day of currently infected cases so that the mitigation and defeat strategies can be imposed to control the size of the epidemic.