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TY - JOUR AU - Aasia Rajput , AU - Naeem Ahmed Qureshi* , AU - Riaz Ali Buriro , AU - Zeeshan Shabbir Soomro , AU - Kainat Rajput , PY - 2025/09/01 Y2 - 2026/09/19 TI - A data driven approach for forecasting the COVID-19 cases in Pakistan: https://doi.org/10.5281/zenodo.17024984 JF - ` JA - ASSAJ VL - 4 IS - 01 SE - Articles DO - UR - https://www.assajournal.com/index.php/36/article/view/816 SP - 3332-3344 AB - <p><em>Aimed at forecasting the COVID-19 cases in Pakistan using probability distribution modelling approach, the present study used daily data from 1^st July to 30^th September 2021 were used for estimation purpose whereas the data from 1^st October to 31^st December 2021 were used for forecasting. Based on the two modes and positively skewed behaviour of data, Bi-model lognormal distribution was fitted. The results showed that maximum number of daily new cases and recovered cases were recorded during the first wave while the maximum of daily deaths was observed during the third wave.&nbsp; A retrospective analysis for evaluation of forecasts showed that the fitted model performed well leaving out-of-sample forecast error within the limit of 5% except for total recovered cases. Forecasted values for total cases and total deaths showed the decreasing pattern while increasing trend was observed for the total recovered cases. </em></p><p><strong><em>Keywords:</em></strong><em> COVID-19; SARS-CoV-2; coronavirus; fifth wave; phenomenological epidemiologic model; bimodal distribution; lognormal distribution </em></p> ER -