scholarly journals Short-Term Forecasting of Daily Confirmed COVID-19 Cases in Malaysia Using RF-SSA Model

2021 ◽  
Vol 9 ◽  
Author(s):  
Shazlyn Milleana Shaharudin ◽  
Shuhaida Ismail ◽  
Noor Artika Hassan ◽  
Mou Leong Tan ◽  
Nurul Ainina Filza Sulaiman
Keyword(s):  
Time Series ◽  
Singular Spectrum Analysis ◽  
Daily Basis ◽  
World Health ◽  
Forecasting Model ◽  
Model Assessment ◽  
Short Term Forecasting ◽  
Novel Coronavirus ◽  
Health Organization ◽  
Short Time

Novel coronavirus (COVID-19) was discovered in Wuhan, China in December 2019, and has affected millions of lives worldwide. On 29th April 2020, Malaysia reported more than 5,000 COVID-19 cases; the second highest in the Southeast Asian region after Singapore. Recently, a forecasting model was developed to measure and predict COVID-19 cases in Malaysia on daily basis for the next 10 days using previously-confirmed cases. A Recurrent Forecasting-Singular Spectrum Analysis (RF-SSA) is proposed by establishing L and ET parameters via several tests. The advantage of using this forecasting model is it would discriminate noise in a time series trend and produce significant forecasting results. The RF-SSA model assessment was based on the official COVID-19 data released by the World Health Organization (WHO) to predict daily confirmed cases between 30th April and 31st May, 2020. These results revealed that parameter L = 5 (T/20) for the RF-SSA model was indeed suitable for short-time series outbreak data, while the appropriate number of eigentriples was integral as it influenced the forecasting results. Evidently, the RF-SSA had over-forecasted the cases by 0.36%. This signifies the competence of RF-SSA in predicting the impending number of COVID-19 cases. Nonetheless, an enhanced RF-SSA algorithm should be developed for higher effectivity of capturing any extreme data changes.

scholarly journals Prediction of Epidemic Trends in COVID-19 with Mann-Kendall and Recurrent Forecasting-Singular Spectrum Analysis

2021 ◽  
Vol 50 (4) ◽  
pp. 1131-1142
Author(s):  
Shazlyn Milleana Shaharudin ◽  
Shuhaida Ismail ◽  
Mohd Saiful Samsudin ◽  
Azman Azid ◽  
Mou Leong Tan ◽  
...  
Keyword(s):  
Spectrum Analysis ◽  
Singular Spectrum Analysis ◽  
Kendall Test ◽  
World Health ◽  
Model Assessment ◽  
Single Digit ◽  
Singular Spectrum ◽  
Mann Kendall Test ◽  
Novel Coronavirus ◽  
Health Organization

Novel coronavirus also known as COVID-19 was first discovered in Wuhan, China by end of 2019. Since then, the virus has claimed millions of lives worldwide. In 29th April 2020, there were more than 5,000 outbreak cases in Malaysia as reported by the Ministry of Health Malaysia (MOHE). This study aims to evaluate the trend analysis of the COVID-19 outbreak using Mann-Kendall test, and predict the future cases of COVID-19 in Malaysia using Recurrent Forecasting-Singular Spectrum Analysis (RF-SSA) model. The RF-SSA model was developed to measure and predict daily COVID-19 cases in Malaysia for the coming 10 days using previously-confirmed cases. A Singular Spectrum Analysis-based forecasting model that discriminates noise in a time series trend is introduced. The RF-SSA model assessment is based on the World Health Organization (WHO) official COVID-19 data to predict the daily confirmed cases after 29th April until 9th May, 2020. The preliminary results of Mann-Kendall test showed a declining trend pattern for new cases during Restricted Movement Order (RMO) 3 compared to RMO1, RMO2 and RMO4, with a dramatic increase in the COVID-19 outbreak during RMO1. Overall, the RF-SSA has over-forecasted the cases by 0.36%. This indicates RF-SSA’s competence to predict the impending number of COVID-19 cases. The proposed model predicted that Malaysia would hit single digit in daily confirmed cased of COVID-19 by early-June 2020. These findings have proven the capability of RF-SSA model in apprehending the trend and predict the cases of COVID-19 with high accuracy. Nevertheless, enhanced RF-SSA algorithm should to be developed for higher effectivity in capturing any extreme data changes.

scholarly journals Using curvature to infer COVID-19 fractal epidemic network fragility and systemic risk

2020 ◽  
Author(s):  
Danillo Barros de Souza ◽  
Fernando A. N. Santos ◽  
Everlon Figuerôa dos Santos ◽  
Jailson B. Correia ◽  
Hernande P. da Silva ◽  
...  
Keyword(s):  
Time Series ◽  
Ricci Curvature ◽  
Systemic Risk ◽  
Daily Basis ◽  
Warning Signs ◽  
Data Driven ◽  
World Health ◽  
Parameter Estimations ◽  
Novel Coronavirus ◽  
Health Organization

The damage of the novel Coronavirus disease (COVID-19) is reaching unprecedented scales. There are numerous classical epidemiology models trying to quantify epidemiology metrics. Usually, to forecast the epidemics, these classical approaches need parameter estimations, such as the contagion rate or the basic reproduction number. Here, we propose a data-driven, parameter-free approach to access the fragility and systemic risk of epidemic networks by studying the Forman-Ricci curvature. Network curvature has been used successfully to forecast risk in financial networks and we suggest that those results can be translated for COVID-19 epidemic time series as well. We first show that our hypothesis is true in a toy-model of epidemic time series with delays, which generates epidemic networks. By doing so, we are able to verify that the Forman-Ricci curvature can be a parameter-free estimate for the fragility and risk of the network at each stage of the simulated pandemic. On this basis, we then compute the Forman-Ricci curvature for real epidemic networks built from epidemic time series available from the World Health Organization (WHO). The Forman-Ricci curvature allow us to detect early warning signs of the emergence of the pandemic. The advantage of the method lies in providing an early geometrical data marker for epidemics, without the need of parameter estimation and stochastic modeling. The strategy above, together with other data-driven tools for investigating epidemic network dynamics, can be readily implemented on a daily basis to quickly estimate the growth, risk and fragility of real COVID-19 epidemic networks at different scales.

An App for Understanding the Case Fatality Rate of Novel Coronavirus (COVID -19): Observation Study (Preprint)

2020 ◽  
Author(s):  
Tsair-Wei Chien ◽  
Wei-Chih Kan ◽  
Yu-Tsen Yeh ◽  
Shu-Chun Kuo
Keyword(s):  
Death Rate ◽  
Case Fatality Rate ◽  
Case Fatality ◽  
Daily Basis ◽  
World Health ◽  
Fatality Rate ◽  
Observation Study ◽  
The Mean ◽  
Novel Coronavirus ◽  
Health Organization

BACKGROUND When a new disease starts to spread, one of the commonly asked questions is (1) how deadly it is. World Health Organization (WHO) announced in a press conference on January 29th, 2020 and reported the death rate of COVID-19 was 2% on the case fatality rate(CFR). Whether the claim was underestimated is worthy of clarifications when considering the lag days from symptom onset to death. OBJECTIVE We developed an app for online displaying three types of computations of CFR and verifying the death rate of 2% substantially underestimated. METHODS We downloaded COVID-19 outbreak numbers from January 21 to February 25, 2020, in countries/regions on a daily basis from Github that contains daily information on confirmed cases, deaths, and the recovered in more than 30 Chinese locations and other worldwide countries/regions. Three CFRs on COVID-19 were compared, including (A) deaths/confirmed;(B) deaths/(deaths+recovered); and (C) deaths/(cases x days ago). The coefficients of variance (CV=the ratio of the standard deviation to the mean) were applied to measure the relative variability for each CFR. A dashboard was developed for daily display of the CFR on COVID-19 for each region. RESULTS We observed that the CVs were 0.07, 9.23, and 5.08 and the CFRs were 3.37%, 8.85%, and 3.58% for these three CFR computations, respectively, on Feb. 25, 2020. The death rate of COVID-19(=2%) announced by WHO using the formula of deaths/confirmed was substantially underestimated. A dashboard was created to present the provisional CFRs of COVID-19 on a daily basis. CONCLUSIONS We suggest examining these three CFRs as a reference to the final CFR. An app developed for displaying the provisional CFR with these three CFRs can modify the underestimated CFR reported by WHO and media. CLINICALTRIAL Not available

scholarly journals ARIMA modelling of predicting COVID-19 infections

2020 ◽  
Author(s):  
W.Regis Anne ◽  
S.Carolin Jeeva
Keyword(s):  
Time Series ◽  
Moving Average ◽  
Arima Model ◽  
Information Criterion ◽  
World Health ◽  
Director General ◽  
Global Pandemic ◽  
Novel Coronavirus ◽  
Health Organization ◽  
Short Term Prediction

AbstractThe World Health Organization (WHO) Director-General, Dr. Tedros Adhanom Ghebreyesus on March 11, 2020 declared the novel coronavirus (COVID-19) outbreak a global pandemic [4] the reason being the number of cases outside China increased 13-fold and the number of countries with cases increased threefold. In this paper a time series model to predict short-term prediction of the transmission of the exponentially growing COVID-19 time series is modelled and studied. Auto Regressive Integrated Moving Average (ARIMA) model prediction is performed on the number of cumulative cases over a time period and is validated over Akaike information criterion (AIC) statistics.

Current updates on COVID-19 - A review

2020 ◽  
Vol 10 (1) ◽  
pp. 1-8
Author(s):  
Ghotekar D S ◽  
Vishal N Kushare ◽  
Sagar V Ghotekar
Keyword(s):  
World Health Organization ◽  
Common Cold ◽  
Respiratory Diseases ◽  
Gastrointestinal Diseases ◽  
Hubei Province ◽  
World Health ◽  
The World ◽  
The Common ◽  
Novel Coronavirus ◽  
Health Organization

Coronaviruses are a family of viruses that cause illness such as respiratory diseases or gastrointestinal diseases. Respiratory diseases can range from the common cold to more severe diseases. A novel coronavirus outbreak was first documented in Wuhan, Hubei Province, China in December 2019. The World Health Organization (WHO) has declared the coronavirus disease 2019 (COVID-19) a pandemic. A global coordinated effort is needed to stop the further spread of the virus. A novel coronavirus (nCoV) is a new strain that has not been identified in humans previously. Once scientists determine exactly what coronavirus it is, they give it a name (as in the case of COVID-19, the virus causing it is SARS-CoV-2).

An approach to the understanding of the clinical-etiopathological aspect of COVID-19 (SARS-CoV-2)

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 862-869
Author(s):  
Meena Kumari ◽  
Monika Agrawal ◽  
Rakesh Kumar Singh ◽  
Parameswarappa S Byadgi
Keyword(s):  
World Health ◽  
Apical Surface ◽  
Therapy Assessment ◽  
Differentiated Cells ◽  
The World ◽  
Polarized Epithelia ◽  
Well Differentiated ◽  
Novel Coronavirus ◽  
Health Organization ◽  
Epidemiological Characteristics

Currently, the world is facing a health and socioeconomic crisis caused by the novel coronavirus disease COVID-19. On 11 March 2020, the World Health Organization (WHO) has declared this disease as a pandemic. The condition (COVID-19) is an infectious disorder triggered by a newly discovered severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2. Most of the COVID-19 infected patients will experience mild to moderate respiratory symptoms and recover without any unique therapy. Assessment of the clinical and epidemiological characteristics of SARS-CoV-2 cases suggests the infected patients will not be contagious until the onset of severe symptoms and affects the other organs. Well-differentiated cells of apical airway epithelia communicating with ACE2 were promptly infected to SARS-CoV-2 virus. But the expression of ACE 2 in poorly differentiated epithelia facilitated SARS spike (S) protein-pseudo typed virus entry and it is replicated in polarized epithelia and especially exited via the apical surface. Limiting the transmission of COVID-19 infection & its prevention can be regarded as a hierarchy of controls. In this article, we briefly discuss the most recent advances in respect to aetiology, pathogenesis and clinical progression of the disease COVID-19.

Treatment Options in COVID-19: The Role of Bioavailable Antiviral Ribonucleoside Analog on NHC in vitro

2020 ◽  
Author(s):  
Lara Bittmann
Keyword(s):  
World Health Organization ◽  
Clinical Picture ◽  
Treatment Options ◽  
World Health ◽  
Wuhan City ◽  
The World ◽  
Novel Coronavirus ◽  
Health Organization

On December 31, 2019, WHO was informed of cases of pneumonia of unknown cause in Wuhan City, China. A novel coronavirus was identified as the cause by Chinese authorities on January 7, 2020 and was provisionally named "2019-nCoV". This new Coronavirus causes a clinical picture which has received now the name COVID-19. The virus has spread subsequently worldwide and was explained on the 11th of March, 2020 by the World Health Organization to the pandemic.

Novel Coronavirus 2019 Outbreak: A Global Epidemic

2020 ◽  
Vol 17 (12) ◽  
pp. 1458-1464
Author(s):  
Sweta Kamboj ◽  
Rohit Kamboj ◽  
Shikha Kamboj ◽  
Kumar Guarve ◽  
Rohit Dutt
Keyword(s):  
World Health ◽  
Upper Respiratory Tract ◽  
Global Epidemic ◽  
The Public ◽  
The Government ◽  
Tract Disease ◽  
The 1960S ◽  
Novel Coronavirus ◽  
Health Organization ◽  
The Impact

Background: In the 1960s, the human coronavirus was designated, which is responsible for the upper respiratory tract disease in children. Back in 2003, mainly 5 new coronaviruses were recognized. This study directly pursues to govern knowledge, attitude and practice of viral and droplet infection isolation safeguard among the researchers during the outbreak of the COVID-19. Introduction: Coronavirus is a proteinaceous and infectious pathogen. It is an etiological agent of severe acute respiratory syndrome (SARS) and the Middle East respiratory syndrome (MERS). Coronavirus, appeared in China from the seafood and poultry market last year, which has spread in various countries, and has caused several deaths. Methods: The literature data has been taken from different search platforms like PubMed, Science Direct, Embase, Web of Science, who.int portal and complied. Results: Corona virology study will be more advanced and outstanding in recent years. COVID-19 epidemic is a threatening reminder not solely for one country but all over the universe. Conclusion: In this review article, we encapsulated the pathogenesis, geographical spread of coronavirus worldwide, also discussed the perspective of diagnosis, effective treatment, and primary recommendations by the World Health Organization, and guidelines of the government to slow down the impact of the virus are also optimistic, efficacious and obliging for the public health. However, it will take a prolonged time in the future to overcome this epidemic.

An Efficient Approach for Detection and Verification of Infected Cases of Covid-19 Virus through Block Chain: A Survey

2020 ◽  
Vol 10 ◽  
Author(s):  
Kanika Gupta ◽  
Aatif Jamshed
Keyword(s):  
Data Storage ◽  
Operations Management ◽  
World Health ◽  
Chain Model ◽  
Human Beings ◽  
Healthcare Applications ◽  
Food Market ◽  
Block Chain ◽  
Novel Coronavirus ◽  
Health Organization

: Some unknown cases of pneumonia were communicated to World Health Organization (WHO) on 31 December,2019 in China’s Wuhan state. The higher authorities of China informed novel coronavirus as the root cause and labelled as “nCov-2019”. This virus is lying into the virus’s family which propagates the diseases like cold flu, lungs infection and more serious diseases. It is not detected earlier in human beings as it is considered to be a new patch on life. Many countries have increased their surveillance forces around the globe to detect any new novel coronavirus cases. An efficient and safe network for secure data storage i.e. Block chain is used in several applications such as food market, healthcare applications, finance, operations management, Internet of Things (IoT). In this paper, with the use of this emerging technology, are able to track useful information and accelerate the treatment process of patients. It also preserves the person’s identity. Correct implementation of block chain model has the chances to restrict the coronavirus transmissions and its related mortality rate where there are inadequate facilities of testing. Other infectious diseases will also be curbed by this model. The advantages of this model can reach to various stakeholders who are involved in the healthcare field which helps us to restrict the transmission of various diseases.

Critical Insight into the Attributes of Emerging Novel Coronavirus (COVID-19) in India and Across the World

Coronaviruses ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 49-56
Author(s):  
Gaurav M. Doshi ◽  
Hemen S. Ved ◽  
Ami P. Thakkar
Keyword(s):  
Review Article ◽  
World Health ◽  
Effective Vaccine ◽  
Human Contact ◽  
The World ◽  
Critical Insight ◽  
Novel Coronavirus ◽  
Health Organization ◽  
Insight Into ◽  
Old Drugs

The World Health Organization (WHO) has recently announced the spread of novel coronavirus (nCoV) globally and has declared it a pandemic. The probable source of transmission of the virus, which is from animal to human and human to human contact, has been established. As per the statistics reported by the WHO on 11th April 2020, data has shown that more than sixteen lakh confirmed cases have been identified globally. The reported cases related to nCoV in India have been rising substantially. The review article discusses the characteristics of nCoV in detail with the probability of potentially effective old drugs that may inhibit the virus. The research may further emphasize and draw the attention of the world towards the development of an effective vaccine as well as alternative therapies. Moreover, the article will help to bridge the gap between the new researchers since it’s the current thrust area of research.

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