Democratising forecasting workshop, October 2018, Iraq

The 3rd demcoratising forecasting workshop will take place in Charmo University in October 2018. Democratising forecasting is a part of Forecasting4Change intiaitive lead by Bahman Rostami-Tabar. The aim is to share knownoledge on forecasting and influence relevant practices prioritising the need of population and the society. Register in Eventbrite Registeration is closed on Thursday 20 September 2018 at 02:30 (UK time). Prerequisites Basic knowledge in statistics; No knowledge of forecasting is assumed.

First (mini)conference on Forecasting for Social Good took place at Cardiff Business School on 12-13 July 2018

The first international workshop dedicated to “Forecasting for Social Good” took place at Cardiff Business School , 12-13 July 2018. We had 38 participants from 8 countries( UK, USA, Australia, India, Norway, Switzerland, India, Germany) over two days. In particular, we had practitionaires from organisations such as NHS, International Committee of the Red Cross, United Nation High Commission for Refugees, United Nations Office for Disaster Risk Reduction, Welsh Government, Australian Government, Future Generation Commissioner for Wales.

Flow management in admission and emergency care

This project is funded by Global Challenge Research Fund. The project will focus on the analysis of the flow management practices (information, products, staff and patients) for the A&E and medical admissions in the Charle Nicole hospital in Tunisia

Forecasting for social Good in India

We organize a workshop in India, bringing together academics and practitioners (NGOs, governmental organizations, private companies, etc. with social missions), to provide access to high quality training, share knowledge, and build capacity and relationships for collaborative research on forecasting and data analytics for social good, consistent with the purpose of GCRF on sustainable development.

Impact of special events on Accident and Emergency attendance in NHS Wales

The goals of this study is to explore and evaluate the impact of special events such as holidays, weather, festivals and sport events in using several statistical forecasting methods to predict A&E patient volumes. A new model will be developed considering special events and will be compared to a benchmark and existing time series forecasting methods.