scholarly journals FORECASTING COVID-19 PANDEMIC: A DATA-DRIVEN ANALYSIS

2020 ◽  
Author(s):  
Khondoker Nazmoon Nabi
Keyword(s):  
United Kingdom ◽  
Rank Correlation ◽  
Trust Region ◽  
Latin Hypercube Sampling ◽  
Epidemiological Data ◽  
Transmission Dynamics ◽  
Model Parameters ◽  
The Novel ◽  
The United Kingdom ◽  
Novel Coronavirus

In this paper, a new Susceptible-Exposed-Symptomatic Infectious-Asymptomatic Infectious-Quarantined-Hospitalized-Recovered-Dead (SEIDIUQHRD) deterministic compartmental model has been proposed and calibrated for describing the transmission dynamics of the novel coronavirus disease (COVID-19). A calibration process is executed through the solution of an inverse problem with the help of a Trust-Region-Reflective algorithm, used to determine the best parameter values that would fit the model response. The purpose of this study is to give a tentative prediction of the epidemic peak for Russia, Brazil, India and Bangladesh which could become the next COVID-19 hotspots in no time. Based on the publicly available epidemiological data from late January until 10 May, it has been estimated that the number of daily new symptomatic infectious cases for the above mentioned countries could reach the peak around the beginning of June with the peak size of ≈15,774 symptomatic infectious cases in Russia, ≈26,449 cases in Brazil, ≈9,504 cases in India and ≈2,209 cases in Bangladesh. Based on our analysis, the estimated value of the basic reproduction number (R0) as of May 11, 2020 was found to be ≈4.234 in Russia, ≈5.347 in Brazil, ≈5.218 in India, ≈4.649 in the United Kingdom and ≈3.5 in Bangladesh. Moreover, with an aim to quantify the uncertainty of our model parameters, Latin hypercube sampling-partial rank correlation coefficient (LHS-PRCC) which is a global sensitivity analysis (GSA) method is applied which elucidates that, for Russia, the recovery rate of undetected asymptomatic carriers, the rate of getting home-quarantined or self-quarantined and the transition rate from quarantined class to susceptible class are the most influential parameters, whereas the rate of getting home-quarantined or self-quarantined and the inverse of the COVID-19 incubation period are highly sensitive parameters in Brazil, India, Bangladesh and the United Kingdom which could significantly affect the transmission dynamics of the novel coronavirus. Our analysis also suggests that relaxing social distancing restrictions too quickly could exacerbate the epidemic outbreak in the above mentioned countries.

scholarly journals Forecasting COVID-19 Pandemic: A Data-Driven Analysis

2020 ◽  
Author(s):  
Khondoker Nazmoon Nabi
Keyword(s):  
United Kingdom ◽  
Rank Correlation ◽  
Trust Region ◽  
Latin Hypercube Sampling ◽  
Epidemiological Data ◽  
Transmission Dynamics ◽  
The Novel ◽  
Asymptomatic Carriers ◽  
The United Kingdom ◽  
Novel Coronavirus

Abstract In this paper, a new Susceptible-Exposed-Symptomatic Infectious-Asymptomatic Infectious-Quarantined-Hospitalized-Recovered-Dead (SEIDIUQHRD) deterministic compartmental model has been proposed and calibrated for interpreting the transmission dynamics of the novel coronavirus disease (COVID-19). The purpose of this study is to give a tentative prediction of the epidemic peak for Russia, Brazil, India and Bangladesh which could become the next COVID-19 hotspots in no time by using a Trust-region-reflective (TRR) algorithm which one of the well-known real data fitting techniques. Based on the publicly available epidemiological data from late January until 10 May, it has been estimated that the number of daily new symptomatic infectious cases for the above mentioned countries could reach the peak around the beginning of June with the peak size of 15, 774 (95% CI, 13,814-17,734) symptomatic infectious cases in Russia, 26, 449 (95% CI, 23,489-29,409) cases in Brazil, 9, 504 (95% CI, 8,378-10,630) cases in India and 2,209 (95% CI, 1,878-2,540) cases in Bangladesh. As of May 11, 2020, incorporating the infectiousness capability of asymptomatic carriers, our analysis estimates the value of the basic reproduction number (R0) as of May 11, 2020 was found to be 4.234 (95% CI, 3.764-4.7) in Russia, 5.347 (95% CI, 4.737-5.95) in Brazil, 5.218 (95% CI, 4.56-5.81)in India, 4.649 (95% CI, 4.17-5.12) in the United Kingdom and 3.53 (95% CI, 3.12-3.94) in Bangladesh. Moreover, Latin hypercube sampling-partial rank correlation coeffcient (LHS-PRCC) which is a global sensitivity analysis (GSA) method is applied to quantify the uncertainty of our model mechanisms, which elucidates that for Russia, the recovery rate of undetected asymptomatic carriers, the rate of getting home-quarantined or self-quarantined and the transition rate from quarantined class to susceptible class are the most influential parameters, whereas the rate of getting home-quarantined or self-quarantined and the inverse of the COVID-19 incubation period are highly sensitive parameters in Brazil, India, Bangladesh and the United Kingdom which could signicantly affect the transmission dynamics of the novel coronavirus. Our analysis also suggests that relaxing social distancing restrictions too quickly could exacerbate the epidemic outbreak in the above-mentioned countries.

scholarly journals Continuing Education through COVID-19 Crisis in the United Kingdom: A Swiss Trainee Abroad

2021 ◽  
Vol 10 (01) ◽  
pp. e25-e29
Author(s):  
Alicja Zientara
Keyword(s):  
Cardiac Surgery ◽  
United Kingdom ◽  
Continuing Education ◽  
Personal Perspective ◽  
The Novel ◽  
Swiss Society ◽  
The United Kingdom ◽  
Cardiac Surgeon ◽  
Novel Coronavirus

AbstractThe work has been awarded in July 2020 with the “Special Swiss Young Cardiac Surgeon Award 2020” by the Swiss Society of Cardiac Surgery (Schweizerische Gesellschaft für Herz- und thorakale Gefässchirurgie [SGHC-SSCC]) and reflects a personal perspective from a Swiss trainee experiencing the novel coronavirus disease 2019 (COVID-19) pandemic during her fellowship in London.

scholarly journals Modelling-based evaluation of the effect of quarantine control by the Chinese government in the coronavirus disease 2019 outbreak

2020 ◽  
Author(s):  
Xinkai Zhou ◽  
Zhigui Wu ◽  
Ranran Yu ◽  
Shanni Cao ◽  
Wen Fang ◽  
...  
Keyword(s):  
Government Intervention ◽  
Model Fitting ◽  
Transmission Dynamics ◽  
Transmission Model ◽  
Chinese Government ◽  
Model Parameters ◽  
The Novel ◽  
Government Control ◽  
The World ◽  
Novel Coronavirus

AbstractThe novel coronavirus disease 2019 (COVID-19) epidemic, which was first identified in Wuhan, China in December 2019, has rapidly spread all over China and across the world. By the end of February 2020, the epidemic outside Hubei province in China has been well controlled, yet the next wave of transmission in other countries may have just begun. A retrospective modeling of the transmission dynamics would provide insights into the epidemiological characteristics of the disease and evaluation of the effectiveness of the strict measures that have been taken by central and local governments of China. Using a refined susceptible-exposed-infectious-removed (SEIR) transmission model and a new strategy of model fitting, we were able to estimate model parameters in a dynamic manner. The resulting parameter estimation can well reflect the prevention policy scenarios. Our simulation results with different degrees of government control suggest that the strictly enforced quarantine and travel ban have significantly decreased the otherwise uncontrollable spread of the disease. Our results suggest similar measures should be considered by other countries that are of high risk of COVID-19 outbreak.SummaryBackgroundThe novel coronavirus disease 2019 (COVID-19) epidemic, which was first reported in Wuhan and rapidly spread across the world, has been well controlled in China but is only starting to take off in other countries. Here we provide a retrospective modelling analysis of the transmission dynamics in China and evaluated the effectiveness of the strict government control strategies.MethodsWe considerably refined the original susceptible-exposed-infectious-removed (SEIR) transmission model, and used the publicly available data from Jan 13rd to Feb 29th for model fitting and parameter estimation in a dynamic manner considering effect of prevention policies. We then used the estimated model parameters to simulate the epidemic trend and transmission risk of the disease with various degrees of government control.FindingsThe severity rate and the fatality rate remain unchanged during the whole epidemic. While government intervention had a moderate effect on the incubation rate (σ), the recovered rate (γ) endured several fold increase. Strikingly, a significant decrease in the infectious rate (β) was observed. Without government control, peak infected cases in Wuhan would reach 7.78 million (70% of the whole population) and total deaths could reach 319000 based on the current mortality rate (4.1%).InterpretationOur simulation results with different degrees of government control suggest that the strictly enforced quarantine and travel ban have significantly decreased the otherwise uncontrollable spread of the disease. Our results suggest similar measures should be considered by other countries that are of high risk of COVID-19 outbreak.FundingThe National Natural Science Foundation of China (21877060).Research in contextEvidence before the studyA global outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been posing significant threats to public health worldwide. By the end of February 2020, 87645 confirmed cases are reported around the world, including 7330 severe cases and 2994 fatalities. We searched PubMed and preprint archive for papers published up to Feb 29th, 2020, using keywords “COVID-19”, “SARS-CoV-2”, “2019-nCoV”, and “novel coronavirus.” We found several researches on the transmission dynamics of COVID-19; however, only one preprint predicted the effect of government intervention in China with incomplete epidemiological data.Added value of this studySince the epidemic is already close to its end in China except Wuhan city, we have the opportunity to carry out a relatively complete retrospective analysis. We optimized the SEIR model using a dynamic fitting approach, taking into account the government measures and reached a much more precise fitting of the data comparing to other studies published. We showed that the severity rate and the fatality rate remain unchanged during the whole epidemic, suggesting the only effective way to control the disease is to control the number of infections. While government intervention had a moderate effect on the incubation rate (σ), it is essential for increasing the recovered rate (γ), and for decreasing and stabilizing the infectious rate (β). We also simulated the scenarios with various degrees of government control which could be a useful tool to predict the necessity of government intervention. An interactive online application was made available to the public on Feb 24th, 2020.Implications of all the available evidenceThe COVID-19 outbreak has already been effectively controlled in China; however, the risk of rapid global explosion is extremely high due to the high transmissive rate of the SARS-CoV-2 virus. The quarantine measures adopted by the Chinese government are essential for the control of the COVID-19 epidemic.

scholarly journals Understanding the possible origin and genotyping of first Bangladeshi SARS-CoV-2 strain

2020 ◽  
Author(s):  
A. S. M. Rubayet Ul Alam ◽  
M. Rafiul Islam ◽  
M. Shaminur Rahman ◽  
Ovinu Kibria Islam ◽  
M. Anwar Hossain
Keyword(s):  
Complete Genome ◽  
Epidemiological Data ◽  
The Novel ◽  
Genome Data ◽  
The United Kingdom ◽  
Comprehensive Picture ◽  
History Of ◽  
Probable Origin ◽  
Novel Coronavirus ◽  
The Uk

The novel coronavirus, SARS-CoV-2, causes the unfathomable pandemic in the history of humankind. Bangladesh is also a victim of this critical situation. To investigate the genomic features of the pathogen, the first complete genome of the virus has very recently been published. Therefore, the long awaiting questions regarding the possible origin and typing of the strain(s) can now be answered. Here, we endeavor to mainly discuss the published reports or online-accessed data (results) regarding those issues and presented a comprehensive picture of the typing of the virus alongside the probable origin of the sub-clade containing Bangladeshi strain. Our observation suggested that this strain might have originated from the United Kingdom (UK) or other European countries epidemiologically linked to the UK. According to different genotyping classification schemes, this strain belongs to A2a clade under G major clade, is of B and/or L type, and is a SARS-CoV-2a sub-strain. The complete genome data will surely increase in the forwarding days in Bangladesh. However, a mass regional sequencing approach targeting the partial or complete genome can link the epidemiological data and may help in further clinical interventions.

scholarly journals Analysis and Prediction of COVID-19 Using SIR, SEIQR, and Machine Learning Models: Australia, Italy, and UK Cases

Information ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 109 ◽  
Author(s):  
Iman Rahimi ◽  
Amir H. Gandomi ◽  
Panagiotis G. Asteris ◽  
Fang Chen
Keyword(s):  
Machine Learning ◽  
Logistic Function ◽  
Prediction Performance ◽  
Machine Learning Algorithms ◽  
Model Parameters ◽  
The Novel ◽  
Chinese City ◽  
Limited Memory ◽  
Increasing Trend ◽  
Novel Coronavirus

The novel coronavirus disease, also known as COVID-19, is a disease outbreak that was first identified in Wuhan, a Central Chinese city. In this report, a short analysis focusing on Australia, Italy, and UK is conducted. The analysis includes confirmed and recovered cases and deaths, the growth rate in Australia compared with that in Italy and UK, and the trend of the disease in different Australian regions. Mathematical approaches based on susceptible, infected, and recovered (SIR) cases and susceptible, exposed, infected, quarantined, and recovered (SEIQR) cases models are proposed to predict epidemiology in the above-mentioned countries. Since the performance of the classic forms of SIR and SEIQR depends on parameter settings, some optimization algorithms, namely Broyden–Fletcher–Goldfarb–Shanno (BFGS), conjugate gradients (CG), limited memory bound constrained BFGS (L-BFGS-B), and Nelder–Mead, are proposed to optimize the parameters and the predictive capabilities of the SIR and SEIQR models. The results of the optimized SIR and SEIQR models were compared with those of two well-known machine learning algorithms, i.e., the Prophet algorithm and logistic function. The results demonstrate the different behaviors of these algorithms in different countries as well as the better performance of the improved SIR and SEIQR models. Moreover, the Prophet algorithm was found to provide better prediction performance than the logistic function, as well as better prediction performance for Italy and UK cases than for Australian cases. Therefore, it seems that the Prophet algorithm is suitable for data with an increasing trend in the context of a pandemic. Optimization of SIR and SEIQR model parameters yielded a significant improvement in the prediction accuracy of the models. Despite the availability of several algorithms for trend predictions in this pandemic, there is no single algorithm that would be optimal for all cases.

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 Reconstructing the origin and transmission dynamics of the 1967–68 foot-and-mouth disease epidemic in the United Kingdom

2013 ◽  
Vol 20 ◽  
pp. 230-238 ◽  
Author(s):  
Caroline F. Wright ◽  
Nick J. Knowles ◽  
Antonello Di Nardo ◽  
David J. Paton ◽  
Daniel T. Haydon ◽  
...  
Keyword(s):  
United Kingdom ◽  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Transmission Dynamics ◽  
The United Kingdom ◽  
Foot And Mouth

scholarly journals How did the COVID-19 pandemic change the practice of Paediatric Endoscopists in Europe?

2020 ◽  
Author(s):  
Ilektra Athiana ◽  
Corinne Légeret ◽  
Patrick Bontems ◽  
Luigi Dall'Oglio ◽  
Paola De Angelis ◽  
...  
Keyword(s):  
At Risk ◽  
United Kingdom ◽  
European Society ◽  
Personal Protective Equipment ◽  
Protective Equipment ◽  
The Novel ◽  
Endoscopic Procedures ◽  
Viral Spread ◽  
Novel Coronavirus ◽  
Time Point

Abstract Background: As endoscopists are at risk to get infected by the novel Coronavirus SARS-CoV-2 during endoscopic procedures, the European Society for Paediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) published recommendations regarding protection for the paediatric endoscopist and endoscopy suite staff. The aim of this survey was to investigate whether European paediatric gastroenterology centres applied the recommendations and how this extraordinary situation was handled by the different centres.Results: Twelve Paediatric European gastroenterology centers (from Belgium, Greece, Italy, Portugal, Slovenia, Spain, Switzerland, and United Kingdom) participated. Nine centres (75%) screened their patients for a possible COVID-19 infection before the procedure, the same amount of hospitals changed their practice based on the ESPGHAN recommendations. 67% of the centres reduced the staff in the endoscopy suite, 83% of the units used FFP2/3 masks and protective goggles during the procedure and 75% wore waterproof gowns.Conclusion: The global situation caused by COVID-19 changed so rapidly, and hospitals had to react immediately to protect staff and patients and could not wait for guidelines to be published. Furthermore, uniform guidelines could not be applied by all European hospitals at a certain time point of the viral spread, as different regions of Europe were not only affected differently by COVID-19, but also had different access to personal protective equipment.

scholarly journals The Early Transmission Dynamics of H1N1pdm Influenza in the United Kingdom

PLoS Currents ◽  
2010 ◽  
Vol 1 ◽  
pp. RRN1130 ◽  
Author(s):  
Azra Ghani ◽  
Marc Baguelin ◽  
Jamie Griffin ◽  
Stefan Flasche ◽  
Albert Jan van Hoek ◽  
...  
Keyword(s):  
United Kingdom ◽  
Transmission Dynamics ◽  
The United Kingdom

scholarly journals Stability and global sensitivity analysis of the transmission dynamics of malaria with relapse and ignorant infected humans

2022 ◽  
Author(s):  
Yves Tinda Mangongo ◽  
Joseph-Désiré Kyemba Bukweli ◽  
Justin Dupar Busili Kampempe ◽  
Rostin Matendo Mabela ◽  
Justin Manango Wazute Munganga
Keyword(s):  
Sensitivity Analysis ◽  
Recovery Rate ◽  
Global Sensitivity Analysis ◽  
Rank Correlation ◽  
Latin Hypercube Sampling ◽  
Transmission Dynamics ◽  
Asymptotically Stable ◽  
Globally Asymptotically Stable ◽  
Global Sensitivity ◽  
Partial Rank Correlation

Abstract In this paper we present a more realistic mathematical model for the transmission dynamics of malaria by extending the classical SEIRS scheme and the model of Hai-Feng Huo and Guang-Ming Qiu [21] by adding the ignorant infected humans compartment. We analyze the global asymptotically stabilities of the model by the use of the basic reproduction number R_0 and we prove that when R_0≦1, the disease-free equilibrium is globally asymptotically stable. That is malaria dies out in the population. When R_0>1, there exists a co-existing unique endemic equilibrium which is globally asymptotically stable. The global sensitivity analysis have been done through the partial rank correlation coefficient using the samples generated by the use of latin hypercube sampling method and shows that the most influence parameters in the spread of malaria are the proportion θ of infectious humans who recover and the recovery rate γ of infectious humans. In order to eradicate malaria, we have to decrease the number of ignorant infected humans by testing peoples and treat them. Numerical simulations show that malaria can be also controlled or eradicated by increasing the recovery rate γ of infectious humans, decreasing the number of ignorant infected humans and decreasing the average number n of mosquito bites.

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