ArticlePloS one2021
Forecasting daily new infections, deaths and recovery cases due to COVID-19 in Pakistan by using Bayesian Dynamic Linear Models.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- Formulation of a spatiotemporal model for the analysis of neonatal mortality amidst SDG interventions: The case of Uganda.PloS one · 2026Article
- Respiratory viral infections: when and where? A scoping review of spatiotemporal methods.Journal of global health · 2025Article
- Time series forecasting of COVID-19 infections and deaths in Alpha and Delta variants using LSTM networks.PloS one · 2023Article
- Water availability and response of Tarbela Reservoir under the changing climate in the Upper Indus Basin, Pakistan.Scientific reports · 2022Article
- Fractional Stochastic Differential Equation Approach for Spreading of Diseases.Entropy (Basel, Switzerland) · 2022Article
- eHealth Engagement on Facebook during COVID-19: Simplistic Computational Data Analysis.International journal of environmental research and public health · 2022Article
- Prediction of COVID-19 Pandemic in Bangladesh: Dual Application of Susceptible-Infective-Recovered (SIR) and Machine Learning Approach.Interdisciplinary perspectives on infectious diseases · 2022Article
- Short-term forecasting of daily infections, fatalities and recoveries about COVID-19 in Algeria using statistical models.Beni-Suef University journal of basic and applied sciences · 2021Article
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Authors and funding
5 authors.
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Abstract
The COVID-19 has caused the deadliest pandemic around the globe, emerged from the city of Wuhan, China by the end of 2019 and affected all continents of the world, with severe health implications and as well as financial-damage. Pakistan is also amongst the top badly effected countries in terms of casualties and financial loss due to COVID-19. By 20th March, 2021, Pakistan reported 623,135 total confirmed cases and 13,799 deaths. A state space model called 'Bayesian Dynamic Linear Model' (BDLM) was used for the forecast of daily new infections, deaths and recover cases regarding COVID-19. For the estimation of states of the models and forecasting new observations, the recursive Kalman filter was used. Twenty days ahead forecast show that the maximum number of new infections are 4,031 per day with 95% prediction interval (3,319-4,743). Death forecast shows that the maximum number of the deaths with 95% prediction interval are 81 and (67-93), respectively. Maximum daily recoveries are 3,464 with 95% prediction interval (2,887-5,423) in the next 20 days. The average number of new infections, deaths and recover cases are 3,282, 52 and 1,840, respectively, in the upcoming 20 days. As the data generation processes based on the latest data has been identified, therefore it can be updated with the availability of new data to provide latest forecast.
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