Road traffic crashes and emergency response optimization: a geo-spatial analysis using closest facility and location-allocation methods

Abstract Increased occurrence of road traffic crashes in Kano metropolis has resulted in a steady loss of lives, injuries, and increased people's risk exposure. This study looked into the emergency response to road traffic crashes in Kano, with a view to improving efficiency by developing linkages and synergy between Emergency Healthcare Facilities (EHCF), ambulances, and crash hotspots. The geographical location and attributes of the major EHCF, crash hotspots along highway intersections, and the two existent ambulances at the Kano State Fire Service (KSFS) and Federal Road Safety Corp head offices (FRSC) were obtained using GPS surveying. Road traffic network data (vector format) was digitized from satellite image, from which two major road classes (highways and minor roads) were identified, as well as their respective speed limits. The length and speed constraints were used to calculate time distances. Nearest Neighbor and Network (closest facility, shortest route, and location-allocation) analyses were carried out. Location-allocation analysis was to determine based on defined criteria the best locations to allocate EHCF or ambulance for optimum coverage. The results demonstrated that EHCF, ambulances, and crash places have different distribution patterns with almost no linkages. Closest ambulance facility analysis revealed the FRSC ambulance takes 9.41 minutes to arrive to crash spot 18 (Maiduguri Road, following NNPC) and 7.52 minutes to arrive at AKTH, the nearest EHCF. Comparatively, getting to Court road incident scene (spot 16) and IRPH as the closest EHCF takes about 3 times the time it takes to get to spot 18 and 4 times the time it takes to get to AKTH. This means that practically almost all victims in the city suffocate before reaching to the hospital. This signifies that, in cases of demand for CPR at the incident scene, there are higher likelihood of dying as it is expected to be provided within the first four minutes after the crash. Based on a maximum of 4 minutes impedance cutoff from all directions towards the occurrences areas, location-allocation analysis found eight new locations to maximize coverage and improve efficiency. It is concluded that current road traffic crash emergency response system has been determined to be ineffective. As a result, more ambulances should be strategically placed to improve emergency response times.

lives, trauma care, and supporting people who are in desperate need of help at the proper time (Li et al. 2015). Although ambulance transportation appears to be straightforward, it is really challenging in practice, particularly during peak hours (Ganeshkumar 2010). The best use of time following a road traffic crash is a crucial indicator of ambulance emergency service efficacy, as well as a determinant of the number of lives lost and casualties (Kassaw and Asefa 2020). According to the World Health Organization, around 3,500 people die every day as a result of poor ambulance transportation, and tens of millions are injured every year. More than 85% of the victims are from low-and middle-income nations (Kassaw and Asefa 2020). The United Nations' Sustainable Development Goals include two specific aims as a result of the global crisis. The first goal is 3.6, which calls for halving the number of global deaths and injuries caused by road traffic crashes by 2020. The second target (11.2) stated that by 2030, everyone should have access to a safe, affordable, accessible, and sustainable transportation system, with a focus on improving road safety, particularly for those in vulnerable situations such as women, children, people with disabilities, and the elderly. Despite considerable progress in some regions of the world, these aims, particularly target 3.6, are still distant from being met.
Rapid reaction to traffic crashes and victim treatment is increasingly being acknowledged as a key contributory element in reducing the severity of long-term injuries and death. According to recent studies, improved medical response and accompanying technology have a key role in reducing the severity of long-term injuries. It is widely acknowledged that when dealing with medical emergencies originating from traffic crashes, time is of the essence. Road crash victims have a better chance of survival and a reduction in the severity of their injuries if they receive competent first assistance (Moore 2002). Many studies have been conducted around the world and in Nigeria, using various approaches and methodologies to solve problems related to the occurrence of road traffic crashes, their causes, consequences, and emergency response in order to achieve the SDG (Table 1).
Because crashes are unavoidable, mitigating their consequences can be accomplished by systematically analyzing them and implementing appropriate solutions such as traffic control equipment, better road design, traffic regulation enforcement, and, most importantly, provisions for efficient emergency response and optimum access to emergency healthcare facilities. The task of developing efficient remedies to the impact of road traffic crashes, on the other hand, necessitates an examination of spatial patterns of traffic crash hotspots, which can be accomplished using geospatial technology (Cheng and Washington 2008). As a result, this research looked at the spatial distribution of road traffic crash hotspots and used network analysis to model ambulance accessibility to incident spots and then to the nearest healthcare facilities in order to reduce fatalities and improve emergency response to road traffic crashes. Crash hotspots, ambulances, and emergency healthcare facilities such as orthopedic, general, specialized, and pediatric hospitals were all mapped to achieve this. Closest facility analysis was then conducted to show the optimum emergency routes for safe and sustainable living within Kano metropolis.

Study area
Kano is situated between the longitudes of 8 25 0 E and 8 40 0 E, and the latitudes of 11 50 0 N and 12 10 0 N. Eight (8) local government areas (Dala, Fagge, Gwale, Kano Municipal, Nassarawa, Tarauni) and parts of Kumbotso and Ungoggo make up the city (Maigari 2016). The metropolis has a total size of around 499 km 2 , with a 137 km 2 urban area ( Figure 1). Kano metropolis is one of the fastest expanding urban hubs in the West African sub-continent, both economically and in terms of population. It is the most populous region in northern Nigeria (Barau 2005). Kano city, with a projected population of 4,331,790 people by 2018 (NPC 2013), has witnessed significant development and growth in recent decades. The accompanying increase in human activity intensities is approaching intolerable limits, making proper management of the outcomes of such activities impossible, resulting in a degraded environment (Barau et al. 2015), as well as an increased risk of various disasters and road traffic crashes (Yunus and Falola 2022). Trade and manufacturing activities in Kano may be traced all the way back to before 1900, when the Kano empire was subjugated by British colonization and the region was absorbed into the global capitalist economy. During precolonial times, the state was the most important commercial and industrial (cottage, commerce, agriculture, and industries) center in Northern Nigeria, and its influence extended to neighboring countries such as Niger Republic, Chad, and Benin Republic. After 1945, modern enterprises, such as the Bompai industrial park, grew at a rapid pace. Kano, like the rest of the world, is vulnerable to a variety of natural and manmade disasters all of them resulting in the loss of life, property, and environmental destruction. Flooding, diseases, dam failure, building collapse, crashes (road and air crashes), bomb explosions, communal clashes, fire catastrophes (residential, commercial, and industrial landuses), and air crashes are only some of the disasters that occur. Every year, thousands of people are killed and injured in traffic road crashes in the city. The majority of these crashes are caused by human error and other factors such as rapid population growth combined with a rapid increase in the number of vehicles, traffic jams, lack of road signs, bad roads, violations of road regulations, lack of footpaths, and unsafe roads for people to walk or cross, to name a few (Q2 NBS 2018).

Materials and methods
This section covers data types, materials/instruments used, data gathering procedures and methodologies, analysis methods, and results presentation. Figure 2 summarizes and presents the process.

Data types and sources
Quantitative and geospatial data were used in the study, which came from both primary and secondary sources. Through GPS surveying, quantitative data in the form of latitudinal locations of all existing emergency healthcare facilities and major road traffic crash spots (junctions along highways) within the metropolis was obtained. Additionally, similar data from two ambulances (Federal Road Safety Corps HQ and Kano State Fire Service HQ) was obtained using the same method in order to calculate distance and time travel for determining the best (shortest) emergency response routes in relation to the distribution patterns of crash spots and emergency healthcare facilities. The KanGIS department provided a Very High Spatial Resolution Satellite Image (World View 3 data with 30 cm spatial resolution), which was used for visualization and on-screen digitization of road network data (in vector format) based on topological relationships. For network evaluations, more than 10,000 connected road network data of various sorts was digitized, together with variables such as lengths (km), distance traveled (minutes), and speed limits.

Data collection methods, instruments and procedure
GPS surveying, crash record consultation (from FRSC and KSFS), on-screen data capture, and field observation were all employed to acquire data. The locational features of healthcare facilities, ambulance stops, and road traffic crash occurrences were obtained using GPS surveying (Garmin 86i). This is so that spatial analysis can figure out how they are related spatially. Crash frequency within the specified junctions along the metropolis' highways was used to determine major incident areas. Field observation was also used, particularly at most highway intersections, to gain a better understanding of some of the factors that contribute to the high frequency of crashes and the emergency response actions. Onscreen digitization in the ArcGIS 10.8 GIS environment was used to collect vector shapefiles of the metropolis's road network based on topological regulations and properties ( Figure 3). Two types of highways were categorized (highway and residential) based on this study, each with a speed limit of 50-70 km/hr and 30-50 km/hr, respectively. The length of each route was established as well as the time and physical distances in minutes and kilometers respectively. For recording the observed causes of crashes and identifying crash hotspots, field notes and crash data were used.

Data analysis techniques
To better understand the distribution pattern of road traffic crashes, emergency healthcare facilities, and ambulances, various methods of analysis were used, as well as modeling (based on time and physical distance) the emergency response to such crashes. The Nearest Neighbor Analysis (NNA) was used to determine the distribution pattern of emergency healthcare facilities, road traffic crash incident places, and ambulances using ArcGIS 10.2 software. The nearest neighbor index is calculated using the average distance between each emergency healthcare facility and incident spot and the closest neighboring location. On the one hand, the technique entails importing the latitude and longitude properties of all emergency healthcare facilities, and on the other, the incident locations. Network Analysis (shortest and closest route) was used to establish the best and shortest travel distance of ambulances to incident locations and from incident locations to the closest emergency healthcare facilities, as well as the shortest route and closest facility within the metropolis. This is to enable determining the time and physical distances (in minutes and kilometer) from ambulance locations to incident spots and as well from the incident spots to the EHCF. The analysis shows the optimum route (based on requirements) from an ambulance site to an incident scene, and from an incident spot to the nearest healthcare facility, with journey distances in kilometers and minutes reported. There was no set cutoff distance for determining the closest facility; however, the search for the closest facility was conducted across the metropolis. There is only one restriction attribute when describing the restriction attributes during the development of network datasets, which is no infringement of road regulations (i.e. one-way). Finally, after identifying the trip bottlenecks, a location-allocation study was performed to find new places where more ambulances may be stationed, particularly along the highway, to provide optimal coverage. Maximum impedeance cut-off of 4 minutes was assigned to clearly define the extents of coverage of all the ambulances (existing and the proposed).

Emergency healthcare facility and road traffic crash spot distribution pattern
The distribution pattern of emergency Healthcare facilities and that of the crash places considerably vary in that the EHCF inside the metropolis are dispersedly distributed with Nearest Neighbor Ratio (NNR) of 1.42 and z-score value of 2.94. This distribution pattern is determined by the nature of services supplied and the existing service coverage specifically within the population clusters in the area (Figure 4). The crash places were found to be randomly distributed (with NNR 1.0) throughout the city, and the pattern is impacted by the network pattern and distribution of junctions along the highways. The ambulances were found to be dispersedly distributed. Since the distribution patterns of the ambulances, EHCF and those of the crashes sites are not identical, and there is a significant need for interaction between them, there is therefore the necessity to evaluate the synergy (if any) among them or otherwise. This is especially with respect to influencing the ability to deliver efficient emergency response throughout the metropolis.

Shortest routes of ambulances for emergency response to crash spots
The role of ambulances in road traffic crashes emergency response cannot be overemphasized. Examining the distribution patterns of the ambulances in relation to crash places and EHCF is very significant in achieving efficiency in the response system. The outcome of study ( Figure 5) illustrates the closest paths from the 2 ambulance locations to all the identified crash hotspots within the metropolis. The result ranked the routes based on time and physical distances (in minutes and km) to the incident spots (Table 2). This to enable determining the travel distances from the ambulance locations to the incident spots before traveling from the spots to the closest EHCF. From Table 2, Facility ID 1 and 2 refers to the Kano State Fire Service (KSFS) and the Federal Road Safety Corps (FRSC) Ambulances respectively.
From Figure 5, it was found that, KSFS ambulance travels for about 15 minutes to reach to incident spot 1 along Gwarzo road, and about 6.54 minutes (Table 3) for transporting the victims to IWGH which is the closest EHCF (excluding the time taken at the scene for possibly first aid and CPR where necessary). Similarly, it takes  FRSC ambulance about 9.41 minutes to reach to crash spot 18 (Maiduguri Road, after NNPC), and 7.52 minutes to travel to AKTH as the closest EHCF. Furthermore, it takes the same ambulance about 3 times the time taken to spot 18 and 4 times the  In comparism to these standards, the result shows that about 90% of the crashes spots within the metropolis are accessed long after the recommended 4 minutes travel distances (if CPR is required). In most cases, it takes up to 3 times or more than the minimum recommended time before emergency personnel reaches to the incident spots. This results into decline in the chances of survival after crashes especially if CPR is required. This therefore warrants the need for redistribution of and location of more ambulances in some strategic locations to enable efficient and optimum coverage throughout the metropolis.

Accessibility to the closest emergency healthcare facilities from crashes spots
Apart from time taken for ambulance travel to incident spot, there is also additional time spent on travelling from the incident spot to the closest healthcare facilities. The results in Figure 6 and Table 2 depict these relationships. Travel distance from event areas to the closest EHCF is also a consideration for survival of victims when crashes occur.
From Table 3, it is obvious that, it takes less than one minute to go from crash places 13, 14 and 15 to IRPH as the closest EHCF. Traveling from incident areas 20 and 23 to Sir Sunusi and MMS hospitals takes about the same amount of time. However, the longest distance traveled from all incident places to the closest EHCF is 8.27 minutes which is from Sharada Junction (spot 12) to IWGH, followed by 7.52 minutes from spot 18 (Maiduguri road, NNPC) to AKTH. However, over 70% of trip routes fall within the recommended 0-4 minute journey distance (if CPR is required).

Accessibility to nearest orthopedic emergency healthcare facilities from all crash locations
In the event of an orthopedic emergency, the best routes from all incident spots to the only National Orthopedic Hospital revealed that the closest incident spot is Kofar Dawanau junction, which is about 1.58 km away and takes 2.48 minutes to travel (Figure 7 and Table 3).
However, the longest distance to the orthopedic hospital in the city is from Maiduguri Road (after NNPC), which takes around 16 minutes to cover a distance of about 13 kilometers (excluding the travel distance from ambulance location to the incident spots). This denotes the casualty's proclivity for suffocating before arriving at the hospital. Only the crash sites at Mandawari and Gidan Sarki crossroads meet the suggested standards, which highlight a higher likelihood of survival if response and CPR (if required) are performed within 4 minutes.

Accessibility to pediatric emergency healthcare facilities from all crash locations
The optimal paths to two famous pediatric hospitals were discovered as a result of pediatric-related casualties (i.e. Asiya Bayero and Isiaka Rabiu Pediatric Hospital). Figure 8 shows that Asiya Bayero Pediatric Hospital is around 85% closer to the crash sites than Isiaka Rabiu Hospital.
However, the shortest distance traveled was between the intersections of Zoo Road Dan Kura Street, Gandun Albasa Street, and Total, which took 0.15, 0.26, and 0.49 minutes, respectively (Table 4). This does not include travel kilometers from the ambulance to the incident site. The shortest distance to Asiya Bayero Pediatric Hospital (in minutes) is from the intersections of Gidan Sarki (0.92), Dan Agundi (2), Kofar Mata (2.48), and Kofar Naisa (2.94). It's worth noting that these distances are within prescribed guidelines, implying that if ambulance travel lengths are likewise within a 2-minute drive, there's a better probability of pediatric survival in the event of an crash. However, the reality on the ground shows that ambulance travel time to incident locations is longer than journey time from incident locations to the next EHCF.
The longest distances to pediatric hospitals are from Danbare junction (opposite BUK, newsite) and Rimin Gata (opposite Hijra filling station), which take approximately 13.29 and 12.09 minutes, respectively, plus ambulance distance travel of approximately 15.06 and 13.87 minutes (Table 2).

Ambulance location allocation for maximum emergency coverage in Kano metropolis
The service coverage of existing ambulances was determined based on maximum impedeance coverage of 4 minutes in order to propose ideal places for putting more ambulances for optimum coverage (Figure 9). Only crash areas 12, 13, and 15 can be reached within the specified travel distance from FRSC, according to the results. The KSFS ambulance, on the other hand, can go to crash areas 8, 9, 14, 22, 23, and 24. However, the two existing ambulances, on the other hand, are unable to reach all other crash sites within the mandated ravel distance. As a result, a location-allocation study was required to propose new locations for ambulances to be stationed for optimal coverage.
The suggested sites for ambulances along the major routes within the metropolis are depicted in Figure 10. Based on a maximum of four minutes impedance cutoff from all directions towards the occurrences areas, eight new locations were found (Table 5). Only crash places 10 and 11 (both within Sharada) were not reached by any of the ambulances within 4 minutes, according to the results. Table 6 indicates that with the new ambulances, all crash places can be reached in less than the minimum standard of four minutes, allowing for immediate CPR when needed.

Discussion
In most cities around the world, the distribution of ambulances for emergency response and EHCF is usually based on a number of factors, including the city's nature and state, population density and distribution, landuse pattern, emergency response demand, and risk pattern, among others. The most important variables for any city are determined by its unique characteristics. However, in many African    towns, including Kano, these response facilities are placed randomly, regardless of any of the conditions described above. This results into extensive delays before victims reached to the hospital. This supports the findings of Ashiagbor et al. (2020)   and Ouma et al. (2018). The most concerning issue is that most emergency response facilities are insufficient (where they exist) or non-existent in most parts of the metropolis. With a population of 4,331,790 people and at least 50 road traffic incidents per day, Kano metropolitan has only two active emergency response ambulances (KSFS and FRSC ambulances), which is woefully inadequate.
When it comes to emergency response in the event of a crash in the city, the KSFS ambulance, for example, takes about 13-15 minutes to reach crash spots 1, 2, and 3 before transferring to the next EHCF (Table 2). Similarly, the FRSC ambulance takes 7-9 minutes to arrive at crash locations 18, 20, and 21. This clearly reveals that impacted people have a higher likelihood of dying before an ambulance arrives at most event sites, particularly those who will require CPR within the first four minutes following the crash. In addition, the travel distance between incident sites and the nearest EHCF is a major source of worry. This is because the casualty must travel for an extra 4-6 minutes before being transported to the hospital (Table 3). This contradicts the findings of Kassaw and Asefa (2020) in Arada Sub-City, Addis Ababa, Ethiopia, who found that it takes between 1 and 2 minutes to get to hospitals in an emergency. Similar issues exist in the city when it comes to orthopedic and pediatric emergencies. For example, it takes an extra 10-15 minutes to go to NOH or ABP from crash spots 1-4, 12, 17, 18, 20, and 21 in the event of a complicated orthopedic or pediatric emergency (Table 6). This demonstrates the inefficiency of the current emergency response system in Kano. The inadequacy of ambulances, as well as a lack of synergy in terms of distribution and closeness to EHCF and crash hotspots, are all challenges experienced in emergency response. TThis finding is directly opposite that of Oruonye, Dumas and Ahmed who found efficiency and synergy in response system within the city.

Conclusion and recommendation
Road traffic crash, which has resulted in injurying and losing of several lives and properties, is unavoidable in Kano Metropolis, owing to population growth and the density of traffic flow, particularly along the state's highways connecting it to neighboring states. The city's current road traffic crash emergency response system is ineffective due to a number of factors, one of which being a lack of ambulances at various places. Following are some suggestions based on the findings: i. More ambulances should be stationed, particularly along highways and near crash sites, to speed up emergency response and save more lives of those who have been injured.

Data availability statement
The data that support the findings of this study are available from the corresponding author, Sulaiman Yunus, upon reasonable request.

Disclosure statement
No potential conflict of interest was reported by the authors.