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Details of Grant 

EPSRC Reference: EP/T003197/1
Title: Modelling Emergency Medical Services in Indonesia
Principal Investigator: Harper, Professor PR
Other Investigators:
Knight, Dr V Gartner, Dr D
Researcher Co-Investigators:
Project Partners:
Department: Sch of Mathematics
Organisation: Cardiff University
Scheme: GCRF (EPSRC)
Starts: 01 October 2019 Ends: 30 September 2021 Value (£): 460,765
EPSRC Research Topic Classifications:
Mathematical Aspects of OR
EPSRC Industrial Sector Classifications:
Healthcare
Related Grants:
Panel History:
Panel DatePanel NameOutcome
12 Jun 2019 SI GCRF 4 - Maths Research and GCRF 5 - Maths Capability Announced
Summary on Grant Application Form
Recent events such as the Anak Krakatau eruption and tsunami, and the Lombok and Palu earthquakes and tsunami have once again brought the attention of the world on Indonesia. In 2018 alone, it is estimated that natural disasters claimed the lives of more than 4,000 people and displaced around 3 million people across the country. Natural disasters, manmade conflicts and violence are commonly experienced across the country, alongside a rising demand for emergency services. The lack of emergency medical transportation across Indonesia is a main barrier to the access and availability of medical care for the 264 million population.

Until recently, Indonesia had no public ambulance service but is now moving towards an integrated national emergency response system. There are however many challenges faced including vast geographical areas, severe traffic congestion, and inadequate numbers of ambulances. Making efficient and effective use of such valuable resources is therefore critical and will be the focus of our research, as is helping to empower local services and provide for the poorest in society who cannot afford to take privately run ambulances.

The National 118 Emergency Ambulance Service was established in 2005 by the Indonesian Surgeons' Association, and is the only public ambulance service in the country, operating currently in five cities: Jakarta, Palembang, Yogyakarta, Surabaya and Makasser. Whilst some private ambulance providers are available, these are hugely expensive and thus out of reach of the majority of the Indonesian population who consequently suffer from a lack of timely access to medical care and are at high risk of morbidity and mortality. Traffic accidents account for 70% of the country's trauma deaths, and nearly 1 in 3 of all deaths are caused by strokes and ischemic heart disease/heart attacks, where rapid access to appropriate treatment is absolutely vital. In Jakarta alone, 118 serves a potential population of 11 million people (the 15th most populous city in the World and the largest in Southeast Asia), covering an area of 661 square km, but remarkably with only 15 ambulances currently available based at 5 locations across the city. Not surprisingly response times and outcomes are very poor, because of the lack of vehicles, the sheer volume of traffic on the roads (Jakarta is reported to have the worst traffic jams of any major Asian city), and the large area to cover.

Our research programme will use Operational Research (OR) methods for mathematical modelling of emergency medical services (EMS). We will work directly with the Founder and Director of the Indonesian National 118 Ambulance Service, Professor Aryono Pusponegoro MD, PhD, and his EMS team to help forecast emergency demand and make critical decisions on the optimal types, capacities and geographical locations of vehicles for a sustainable emergency service. Such factors directly impact on the probability of patient survival, ability to respond to major disasters, and the overall quality of care provided. Our ambitious, adventurous and transformative research programme is underpinned by novel scientific methods that will: (i) develop a methodology to forecast spatiotemporal demand without historical call data using census and survey data within a machine-learning framework, and (ii) develop a novel approach to consider EMS capacities and allocations for maximising survival within a heterogeneous population (multiple medical needs) using a heterogeneous fleet with consideration of multiple vehicle types each with differing travel times/speeds. This will be achieved via the creation of an optimisation and simulation decision-support framework that will be deployed by the national 118 emergency ambulance service.
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