As such, the purpose of this study is to evaluate a survey of high road utilizer users and determine whether this survey method is comparable to police data. We hypothesized that surveying vulnerable road users who are high road user utilizers could identify and locate RTC hotspots at least as well as police data.
Vulnerable road users were chosen as they have a unique perspective and suffer the largest burden of injury. We secondarily calculate the marginal cost of conducting such surveys. In both Rwanda and Sri Lanka, we obtained permission and fostered collaborations with the local police in order to conduct the project.
In Sri Lanka in , there were , total registered vehicles of which 44, were three-wheelers; in Galle specifically, there were 28, total vehicles of which were three-wheelers and 20, are motorcycles. The two study countries were specifically chosen to represent different continents, different populations dense urban versus urban , and different police reporting infrastructures; Sri Lanka has a legal non-reporting mechanism where crashes can be not reported and road side agreements made between parties legally for non-fatal injuries whereas Rwanda does not [ 3 ].
Given that police data in these two locations is not formally analyzed or distributed, we anticipated that our surveyed population did not have any familiarity with the retrospective police data. Retrospective data was collected from the police datasets from each setting. Information available included the crash logistics, locations of the crash, involved persons, and severity of injury.
Geolocation coordinates were determined based on addresses and description in police data, or the latitude and longitude if available. These were entered for each description of RTC location for further spatial analysis. The severity of injury in Sri Lanka was labeled as no injuries, non-grievous injury, grievous injury, and fatality while in Rwanda injuries were listed as fatal, grievous, and non-grievous. These categorizations were determined by police according to their police investigation with input from any treating practitioner, if available, but validity and inter-rater agreement amongst these categorizations are untested.
Trained research assistants conducted pilot surveys amongst the high road utilizer population in each country. They utilized electronic data entry and tablet computers for direct data entry into an online database. Questionnaires included respondent demographics such as work history and amount of time spent on roads. Respondents were questioned on their knowledge of the research area in question to ensure they were high road utilizers of the research area.
They were asked to identify dangerous locations and label the severity of danger of each location on a 0— scale. The survey in its electronic form was pilot-tested in each location to ensure appropriate translation, comprehension of questions, and electronic data management capacity. Based on pilot testing, question wording, and translation were improved upon to improve the questionnaire understandability and improve responses. The research team in Sri Lanka identified tuk-tuk three wheel drivers total from each sector of Galle to ensure spatial representation of the municipality.
A tuk-tuk stand located in each sector was chosen at random and visited at a random time during the day by a trained Sri Lankan research assistant. In Rwanda, the national moto motorcycle taxi driver association formally designates stands to provide service in the most populated locations across Kigali. These stands were chosen across Kigali to ensure spatial representation of the city. At each of these stands the first ten moto drivers encountered were offered survey participation by trained, native-Kinyarwanda speaking research assistants who conducted the surveys in Kinyarwanda after informed consent.
REDCap Research Electronic Data Capture is a secure, web-based application designed to support data capture for research studies, providing 1 an intuitive interface for validated data entry; 2 audit trails for tracking data manipulation and export procedures; 3 automated export procedures for seamless data downloads to common statistical packages; 4 procedures for importing data from external sources and 5 secure storage.
To assess the data collected through the surveys, we used RTC data from police as the criterion standard. While police data is known to have extensive underreporting, most LMIC do not have prehospital care nor extensive hospital-based datasets that include RTC location information [ 6 , 16 — 21 ]. Thus, police data remain the best available sources for RTC location. A hotspot, for this project, is an area of high density of road crash locations.
Our analysis plan was comprised of four steps. First, RTC locations were mapped into polygons; then, each polygon was classified by risk low, medium, high based on the density of occurrences within that polygon.
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Using these classifications, we then conducted an agreement and association analysis between methods. Spatial analysis was used to geographically localize RTC locations and identify specific distribution patterns through cartographic visualization [ 22 , 23 ]. We applied a kernel density estimator to verify these spatial patterns.
This function performs a count of all locations within a region of influence, weighting them by the distance of each point to the location of interest. To provide the same metric for comparison for both police data and survey data spatial distribution points, we applied a vectoral grid disposition of polygons to maps QGIS after KDE, building a map based on the same number of polygon for both methods of data collection.
Based on the average KDE, we then classified each polygon into a Low, Medium and High risk for RTC considering previously explained spatial distribution cutoff points for hotspots analysis. To calculate the confidence intervals for Kappa values we used a bootstrapping method based on a randomized samples. Values above 0. Sensitivity and specificity were calculated for survey data hotspots relative to police dataset-determined hotspots. All analyses were performed using R Language [ 26 ]. A cost comparison was conducted for the data collection method in each country.
Costs included research personnel, equipment, and transportation costs. Police data personnel costs do not include costs of police personnel who collect, enter, accumulate, or distribute this data to researchers but does include costs for data entry personnel who managed research data.
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Other costs include cost of incentives given to tuk-tuk drivers for participating and cost of food and refreshments for participants and data collectors. The cost per method was calculated per crash location determined as it is this data point which allows for power in our analysis. In Rwanda records were included, with from police data and from surveys.
In Sri Lanka, a total of records were included, with from police and from surveys. By overlapping the survey and police data as seen in Fig. Kernel Density Estimation of survey and police data derived RTC hotspots weighted by severity of injury a , b , c , d , e , f. The police and the survey data showed a high agreement in both countries — The sensitivity and specificity of survey data for Rwanda was Frequencies of polygons classified in each strata Low, Medium, High are listed on top and side.
Black areas illustrate agreement between both methods of data collection while grey areas represent lack of agreement. The objective of this project was to evaluate a survey of high road utilizers to inform RTC hotspots in comparison to the more commonly used, but at times limited, police data. To our knowledge, this is the first project to identify an alternative survey method of RTC hotspot identification.
Our survey utilized crowdsourcing methodolgy and was designed to be reproducible, cost-effective, and generalizable in low and middle income countries. It should be noted that police records serve a primarily legal function; their use for research and policymaking is secondary. While superior quality police records would be optimal, this is not feasible in many LMIC. As such, alternative or adjunct methods are warranted. We further demonstrated that survey data could be collected at low cost.
In contrast to police records, which rely on passive data collection, surveying allows active data collection. Finally, surveys provide a medium for high road utilizers to report dangerous traffic spots. This user engagement can have significant benefits for LMIC policymakers and administration. Overall, our high agreement and high sensitivity results suggest that survey-based data collection of high road utilizers is a feasible low - cost alternative for researchers and policy makers in settings where police data might have quality or completeness limitations.
According to the World Bank, Rwanda had one of the worst road-safety records in In Rwanda, given the large area and dense population, we attempted to include more police and survey records in order to adequately survey this larger population. Unfortunately, but not unexpectedly, police data often did not include latitude or longitude or a description of the location in such detail that the RTC location could be located on a map.
It is common to have these limitations in mortuary, police, and hospital data; while prehospital care records sometimes include this information, they suffer the same quality limitations that can been seen in other datasets [ 4 — 6 , 28 , 29 ]. In contrast, Sri Lanka has had a limited national response to road safety prevention even though there have been multiple calls for action [ 14 , 30 ].
When comparing both Sri Lankan and Rwandan experiences, methodological differences might have accounted for the difference in sensitivity and specificity. The police have a National Police computer network and every police station has PCs connected to this network. Those terminals are only connected to the police network and not to the Internet. The majority of the systems accessible on the network are national. All national police systems can be accessed from every network connected work terminal.
The access is secured with a public key infrastructure PKI , where each officer is given personal authority for access to systems necessary for his or her work. Each police officer has a personal smart card, with information needed to verify the officer's rights of access to the police information systems.
Information from the smart card is read through a card reader and each terminal verifies the right of access. Every action taken by an officer within the police information systems is logged in separate log files, to ensure proof if the information systems have been misused. The information systems, in Table 1, handle electronic record which all must be preserved long-term. Besides those information systems the Swedish police also have an intranet IntraPolis and an e-mail system GroupWise for internal information sharing. Those two systems have contents that need to be preserved for varying time periods.
The police have several information systems supporting different operational tasks. Those systems are not nationally regulated or controlled. At the police county in the studies for this paper, there was one system of interest handling police intelligence. Police officers had to apply for authority to access that system. Police information systems are designed to make information available and to make police work more efficient and not to manage records. All information systems are designed with some database solution, enabling quite advanced search functionality. Electronic records within the police information systems are not automatically public.
Requests for records are always followed by an analysis of whether the record is protected by secrecy. All the systems mentioned above were designed and developed to computerize tasks, which previously were handled manually. It was possible to receive or capture all of the information that these systems can deliver or present previously, when the tasks were managed manually. However, when the records were handled manually access for police officers was limited and it was not easy to search, find and get the information. All police officers involved in these studies agreed on the importance of information in police practice.
Police practice and police work is based on information, which is used to support decision-making both tactically and legally. Police officers retrieve information either from others or by their own active search and the gathering mostly relates to needs that have their origin in police work. The police officers commented that they never know when the information could be needed. They made the selection of the most relevant and necessary information themselves, based upon experience and actual needs.
Several police officers mentioned the connection between information and knowledge and the need always to gather, or try to gather, as much information as possible. One officer noted: Information as well as knowledge is not a burden, it is an easy load to carry. One of the most important sources of information is the police information systems. The majority of police officers in these three studies ranked information systems as the major source for relevant information.
If they did not find what they were looking for in those systems, only then did they use other sources. Police officers use the information systems presented in Table 1 as source of information.
The following excerpts from the field study explain how electronic record serves as source of information. This excerpt shows how information systems support information gathering and information retrieval. Before these systems existed the police officers had to read everything in paper form. Some of the systems described above are bringing new access possibilities, e. Search possibilities have increased since the computerized system for making police report were introduced. Before RAR was developed, officers could search for goods in a national goods database, but the database was out of date and rarely gave any hits.
When police officers make a report and use RAR, the police officers are helped by the system to fill in fields, according to which the database can be searched. This excerpt shows how officers use information systems and records for decision-making and to be able to know what to give priority. When these information systems were not available, the amount of data for decision making was limited and there were limitations in the possibilities to search information about persons, addresses and types of crime.
Police officers not only retrieve and gather information actively, they also get information through automated communication processes. This excerpt shows how one of the information systems is used as a source of vital information, which could be basis for decision making. STORM gives police officers possibilities to search information on whether an address, person or vehicle has been of interest to the police previously.
Many police officers are aware of the possibilities of the police information systems and, therefore, are not always satisfied with the help and support they get from the dispatch centre. However, they are aware that without the information systems the support from the dispatch centre would be even more limited. Police officers working in pairs do communicate a lot.
They talk with each other during their working shift. The communication is mainly about work-related topics.
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Police officers find that the informal communication around the coffee table, within the police vehicle, during physical training etc. Much of this information has its origin in the police information systems. Electronic records have been a new source of information, information that may be communicated during such informal meetings.
At every work shift change, police officers traditionally share work-related information with each other. GroupWise is the police e-mail system, which is well used for communication and distribution of information. GroupWise has become an alternative to telephone or internal paper mail. In this example e-mail has been used as a tool both to deliver information and to return information. A memo is one of several official documents produced in police work that has no legal requirement to be signed and, therefore, can be sent by e-mail. The majority of the police officers in these three studies interpreted information and knowledge as being of equal status.
They need reliable and relevant information in order to make correct decisions both tactically and legally. Therefore, it is natural for the officers to gather as much information as possible. When they are standing in the middle of a situation, information and knowledge are their weapons. During assignments there are needs for a specific type of decision support. This is information about addresses, criminals or vehicles that are stored in the police information systems. Information about what has happened earlier at a specific location could be of vital importance for the police officers to choose the right tactical approach.
In police practice the dispatch centre supports police officers with information, when they are out on duty. The above-mentioned active information search performed by police officers also aims to increase knowledge for enabling a decision making support. Police officers are aware of how quickly a situation can appear and, therefore, information can be part of a successful solution. According to Swedish national laws, the police must contact the public prosecutor in some types of serious crimes.
Often the public prosecutor has to decide if the police patrol is going to use means of coercion, or similar tasks. As basis for the decision the public prosecutor is going to take, police officers must be able to present historical information about the suspect of the crime. The historical information can be obtained with help from the dispatch centre. In some cases the information has its origin in electronic records.
These data are used as basis for decisions on a strategic level by the police board and the superior officers in command of the police force in the county. The statistical data are also used to analyse crime trends and to measure police effectiveness. Police officers assume that information delivered from the information systems mentioned above is valid and that the information itself has a legal value. The information systems were developed to replace previous manually-handled tasks, and, therefore, it is natural for police officers not to question the authenticity of the information.
No police officers in these three studies have questioned the reliability and authenticity of information originating from electronic records within information systems. The management of the information systems within the police is strictly regulated and this ensures the trustworthiness of the information. Information derived from police information systems can be used as evidence both for the public prosecutor and in court proceedings.
No doubts are expressed from other parts of the Swedish legal system about the authenticity of the electronic records produced within police information systems. Police officers interviewed in these three studies were all disappointed with the possibility of accessing the police information system during operational work.
They meant the information could be distorted when, for example, the dispatch centre mediated information from information systems. The CDs are processed and information is automatically updated to Identity History Summaries with minimal manual intervention. This means in a matter of hours, several thousand summaries will have updated disposition information. MRD submission results in major savings in personnel resources and faster processing. Currently, only state agencies can submit dispositions via MRD.
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In order to submit dispositions via MRD, the state must meet the following requirements:. For more information, contact the FBI via e-mail at fbi-iii leo. Currently, only state agencies can submit dispositions via III. In order to submit dispositions via III, the state must meet the following requirements:.
Suffixes denoting seniority e. The format is month, day and year e. Enter SID numbers with no more than ten alphanumeric characters, which includes the state abbreviations. No Date of Arrest means there is a summary, but the arrest to which the disposition refers is not on file.