Evaluating Data-Driven Forecasting Methods for Predicting SARS-CoV2 Cases: Evidence From 173 Countries

Evaluating Data-Driven Forecasting Methods for Predicting SARS-CoV2 Cases: Evidence From 173 Countries

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Being elected as the President of Pakistan Biological Safety Association (PBSA) is a true honour for me. I believe that promoting awareness, knowledge and understanding of biosafety at the regional and national level is responsibility of each member and trainer of the PBSA. This organization is commended in many of the national and international forums for its preventive training for Risk Assessment and management, that was much needed at the time of COVID-19 outbreak. Additionally, it has promoted strong collaborations and affiliations with various Biosafety developmental programs that align with international standards to acknowledge and recognize biosafety as a separate scientific discipline within Pakistan. I strongly agree that “no one is safe until everyone is safe”, and would like to work with the PBSA team to implement this approach as far and wide as possible.

Prof. Dr. Saeed Khan
Prof. Dr. Saeed Khan, President PBSA/ Professor Dow University of Health Sciences Karachi

A pre-print document is available that is titled “Evaluating Data-Driven Forecasting Methods for Predicting SARS-CoV2 Cases: Evidence From 173 Countries”. The authors of the paper includes Dr. Aamer Ikram (Executive Director, NIH), Javed Muhammad (Treasurer, Pakistan Biological Safety Association) and Furqan Ahmed (Lifetime Member PBSA; also 2016-2018 Programme Manager of Pakistan Biological Safety Association).

An abstract from the document is provided below:

The WHO announced the epidemic of SARS-CoV2 as a public health emergency of international concern on 30th January 2020. To date, it has spread to more than 200 countries, and has been declared as a global pandemic. For appropriate preparedness, containment, and mitigation response, the stakeholders and policymakers require prior guidance on the propagation of SARS-CoV2. This study aims to provide such guidance by forecasting the cumulative COVID-19 cases up to 4 weeks ahead for 173 countries, using four data-driven methodologies; autoregressive integrated moving average (ARIMA), exponential smoothing model (ETS), random walk forecasts (RWF) with and without drift. We also evaluate the accuracy of these forecasts using the Mean Absolute Percentage Error (MAPE). The results show that the ARIMA and ETS methods outperform the other two forecasting methods. Additionally, using these forecasts, we generated heat maps to provide a pictorial representation of the countries at risk of having an increase in cases in the coming 4 weeks for June. Due to limited data availability during the ongoing pandemic, less data-hungry forecasting models like ARIMA and ETS can help in anticipating the future burden of SARS-CoV2 on healthcare systems.

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We congratulate the endeavors of Dr. Aamer Ikram, Javed Muhammad and all members of PBSA for making Pakistan biosafe.