Forecasting daily new infections, deaths and recovery cases due to COVID-19 in Pakistan by using Bayesian Dynamic Linear Models

Khan, Firdos; Ali, Shaukat; Saeed, Alia; Kumar, Ramesh; Khan, Abdul Wali

doi:10.1371/journal.pone.0253367

Cited by 12 publications

(13 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are various studies about COVID-19 forecasting in different region and countries of the world [ 9 , 15 , 16 , 19 , 26 – 28 ] including Pakistan, Canada, Germany, UK, France, Italy, Russia, Japan and Turkey. The studies of Aslam et al, [ 9 ], Khan et al [ 19 , 27 ] used time series models to forecast future’s scenario of COVID-19 in Pakistan. The results of Aslam et al [ 9 ] show increasing trend and suggested eightfold increase in recoveries and an increase of 2.7 times in new cases in the end of May 2020.…”

Section: Discussionmentioning

confidence: 99%

Short-term forecasting of daily infections, fatalities and recoveries about COVID-19 in Algeria using statistical models

Khan

Lounis

2021

Beni-Suef Univ J Basic Appl Sci

Self Cite

View full text Add to dashboard Cite

Background A viral disease due to a virus called SARS-Cov-2 spreads globally with a total of 34,627,141 infected people and 1,029,815 deaths. Algeria is an African country where 51,690, 1,741 and 36,282 are currently reported as infected, dead and recovered. A multivariate time series model has been used to model these variables and forecast their future scenarios for the next 20 days. Results The results show that there will be a minimum of 63 and a maximum of 147 new infections in the next 20 days with their corresponding 95% confidence intervals of − 89 to 214 and 108–186, respectively. Deaths’ forecast shows that there will be 8 and 12 minimum and maximum numbers of deaths in the upcoming 20 days with their 95% confidence intervals of 1–17 and 4–20, respectively. Minimum and maximum numbers of recovered cases will be 40 and 142 with their corresponding 95% confidence intervals of − 106 to 185 and 44–239, respectively. The total number of infections, fatalities and recoveries in the next 20 days will be 1850, 186 and 1680, respectively. Conclusion The results of this study suggest that the new infections are higher in number than recover cases, and therefore, the number of infected people may increase in future. This study can provide valuable information for policy makers including health and education departments.

show abstract

Section: Discussionmentioning

confidence: 99%

Short-term forecasting of daily infections, fatalities and recoveries about COVID-19 in Algeria using statistical models

Khan

Lounis

2021

Beni-Suef Univ J Basic Appl Sci

Self Cite

View full text Add to dashboard Cite

show abstract

“…Based on observed river flow, the future’s forecast has been made by using BDLM. For further details about BDLM, I refer to 32 , 76 , 77 .…”

Section: Methodsmentioning

confidence: 99%

Water availability and response of Tarbela Reservoir under the changing climate in the Upper Indus Basin, Pakistan

Khan

2022

Sci Rep

Self Cite

View full text Add to dashboard Cite

Agriculture is one of the major contributors to the Gross Domestic Product (GDP) of Pakistan which relies on the availability of water. Hydropower contributes approximately 35% to the national electricity gid of Pakistan. Indus River is the main river of the Indus River System (IRS) which provides water for agriculture, hydropower and other purposes. The outputs of the Conformal-Cubic Atmospheric Model (CCAM) are used to force the University of British Columbia Watershed Model (UBCWM) in the Upper Indus Basin (UIB), to investigate future water availability under the two IPCC emission scenarios (RCP4.5 and RCP8.5). Tarbela Reservoir which is the outlet of UIB is used as a measurement tool to assess water availability and response of the reservoir to climate change. The results show that maximum and minimum temperature are increasing in the future in comparison to the reference period. The largest increases in maximum temperature are projected for MAM (March–April–May) and JJA (June–July–August), with increases up to 2 °C in MAM and increases up to 6.4 °C in JJA under the RCP4.5 and RCP8.5, respectively, in the future. Minimum temperature has maximum increase (6.7 °C) in DJF (December–January–February) during 2071–2100 under RCP8.5. Precipitation shows a 5.1% decrease in DJF during 2011–2040 under RCP4.5. The statistics about water availability suggest that there is consistent increase in most of the months in the future, however, under the RCP4.5, there is decline in the river flow during 2071–2100 as compared to the 2041–2070. The findings of this study show that most of the time there will be more water available but in some months, there may be water scarcity under the RCP4.5, however, proper management and optimal utilization can reduce the water scarcity.

show abstract

“…Khan et al [15] proposed that a flexible framework will help relevant departments formulate policies by predicting new infections of COVID-19 after 5 and 10 days. To observe the forecasting capability of our proposed β-Sutte indicator and βSA ensemble model further, the five days ahead prediction of the cumulative number of confirmed cases is also evaluated.…”

Section: Five Days Ahead Forecasting Of the Cumulative Number Of Conf...mentioning

confidence: 99%

A Novel βSA Ensemble Model for Forecasting the Number of Confirmed COVID-19 Cases in the US

Shih

et al. 2022

Mathematics

View full text Add to dashboard Cite

In December 2019, Severe Special Infectious Pneumonia (SARS-CoV-2)–the novel coronavirus (COVID-19)– appeared for the first time, breaking out in Wuhan, China, and the epidemic spread quickly to the world in a very short period time. According to WHO data, ten million people have been infected, and more than one million people have died; moreover, the economy has also been severely hit. In an outbreak of an epidemic, people are concerned about the final number of infections. Therefore, effectively predicting the number of confirmed cases in the future can provide a reference for decision-makers to make decisions and avoid the spread of deadly epidemics. In recent years, the α-Sutte indicator method is an excellent predictor in short-term forecasting; however, the α-Sutte indicator uses fixed static weights. In this study, by adding an error-based dynamic weighting method, a novel β-Sutte indicator is proposed. Combined with ARIMA as an ensemble model (βSA), the forecasting of the future COVID-19 daily cumulative number of cases and the number of new cases in the US are evaluated from the experiment. The experimental results show that the forecasting accuracy of βSA proposed in this study is better than other methods in forecasting with metrics MAPE and RMSE. It proves the feasibility of adding error-based dynamic weights in the β-Sutte indicator in the area of forecasting.

show abstract

Forecasting daily new infections, deaths and recovery cases due to COVID-19 in Pakistan by using Bayesian Dynamic Linear Models

Cited by 12 publications

References 41 publications

Short-term forecasting of daily infections, fatalities and recoveries about COVID-19 in Algeria using statistical models

Short-term forecasting of daily infections, fatalities and recoveries about COVID-19 in Algeria using statistical models

Water availability and response of Tarbela Reservoir under the changing climate in the Upper Indus Basin, Pakistan

A Novel βSA Ensemble Model for Forecasting the Number of Confirmed COVID-19 Cases in the US

Contact Info

Product

Resources

About