The level and trend of road traffic injuries attributable mortality rate in Iran, 1990-2015: a story of successful regulations and a roadmap to design future policies.

BACKGROUND: Road-Traffic-Injuries (RTIs) are predicted to rise up to the fifth leading cause of worldwide death by 2030 and Iran has the third highest RTIs mortality among higher-middle income countries. Although the high mortality of RTI in Iran is a warning, it provides the opportunity to indirectly assess the implemented RTI-related regulations' effectiveness via high-resolution relevant statistics and, hence, Iran could serve as a guide for countries with similar context. In order to do so, we utilized this study to report the time and spatial trends of RTIs-related mortality in different age and sex groups and road user classes in Iran. METHODS: Based on the national death-registration-system (DRS), cemeteries data, and the demographic characteristics, and after addressing incompleteness, we estimated mortality rates using spatiotemporal and Gaussian process regression models. We assessed Pearson seatbelt and helmet use and RTIs-attributable Age-Standardized-Morality-Rate (ASMR) associations. We also predicted RTIs-death-numbers, 2012-2020, by fitting a Generalized Additive Model to assess the status of achieving relevant sustainable development goal (SDG), namely reducing the number of RTIs-related deaths by half. RESULTS: Overall RTIs-attributable death and ASMR at the national level increased from 12.64 [95% UI, 9.52-16.86] to 29.1 [22.76-37.14] per 100,000 people in the time period of 1990-2015. The trend consisted of an increasing segment in 1990-2003 followed by a decreasing part till 2015. The highest percentage of death belonged to the three-or-more-wheels motorized vehicles. Pedestrian injuries percentage increased significantly and the highest mortality rate occurred in 85 years and older individuals. Low prevalence of seatbelt and helmet use were observed in provinces with higher than the median ASMR due to the relevant cause of each. RTIs-attributable death number is expected to reduce by 15.99% till 2020 which is lower than the established SDG goal. CONCLUSIONS: Despite the observed substantial moderation in the RTI-ASMR, Iran is till among the leading countries in terms of the highest mortality rates in the world. The enforced regulations including speed limitations (particularly for elder pedestrians) and mandatory use of seatbelt and helmet (for young adult and male drivers) had a considerable effect on ASMR, nevertheless, the RTI burden reduction needs to be sustained and enhanced.

Do the chaotic features of gait change in Parkinson's disease?

Some previous studies have focused on chaotic properties of Parkinson's disease (PD). It seems that considering PD from dynamical systems perspective is a relevant method that may lead to better understanding of the disease. There is some ambiguity about chaotic nature in PD symptoms and normal behaviour. Some studies claim that normal gait has somehow a chaotic behaviour and disturbed gait in PD has decreased chaotic nature. However, it is worth noting that the basis of this idea is the difference of fractal behaviour in gait of normal and PD patients, which is concluded from Long Range Correlation (LRC) indices. Our primary calculations show that a large number of normal persons and patients have similar LRC. It seems that chaotic studies on PD need a different view. Because of short time recording of symptoms, accurate calculation of chaotic features is tough. On the other hand, long time recording of symptoms is experimentally difficult. In this research, we have first designed a physiologically plausible model for normal and PD gait. Then, after validating the model with neural network classifier, we used the model for extracting long time simulation of stride in normal and PD persons. These long time simulations were then used for calculating the chaotic features of gait. According to change of phase space behaviour and alteration of three largest lyapunov exponents, it was observed that simulated normal persons act as chaotic systems in stride production, but simulated PD does not have chaotic dynamics and is stochastic. Based on our results, it may be claimed that normal gait has chaotic nature which is disturbed in PD state. Surely, long time real recordings from gait signal in normal persons and PD patients are necessary to warranty this hypothesis.

The effect of non-punitive peer comparison and performance feedback on drivers' behavior using the telematics: The first randomized trial in Iran.

BACKGROUND: Aggressive driving is the leading behavior resulting in fatal or nonfatal disabling injuries. Therefore, programs with the main focus on driving behavior could reduce the risk of traffic injuries remarkably. We aimed to investigate the role of non-punitive performance feedback on drivers' behavior and evaluate the persistence of the altered behavior by using in-vehicle telematics. METHODS: This study was done as a randomized controlled trial by repeated-measures design to evaluate the non-punitive behavioral intervention's efficacy on the behavioral transition to safer driving for 1,289 bus and 104 taxi drivers. All participants were studied during 17 weeks through three stages: stage 0 (five weeks for collecting the baseline characteristics of the participants), stage 1 (nine weeks for randomizing the participants into intervention group or control group and sending the intervention group feedback via short message service), and stage 2 (three weeks for following-up the participants without sending feedback). The intervention group drivers received weekly text messages about the driving score and drivers' rank within their peer group.The study's primary outcome was the driver score changing pattern throughout the study calculated by a neuro-fuzzy scoring system composed of four factors: speed violation, harsh acceleration, harsh braking, and harsh turning. RESULTS: Among the bus drivers, a significant positive effect of the intervention was found in stage 1 (P<0.0001) and in stage 2 (P<0.0001) regarding the calculated scoring system. Among the taxi drivers, a significant positive effect of the intervention was found in stage 1 (P<0.0001), but the effect was not significant in stage 2 (P=0.15). CONCLUSION: The results of this study were in favor of using telematics and its positive effect on driving performance. The reformed behavior persisted even after the intervention ceased. PRACTICAL APPLICATION: Behavioral interventions could be considered a promising strategy to enhance and promote safe driving performance.

Evaluation of the effect of fixed speed cameras on speeding behavior among Iranian taxi drivers through telematics monitoring.

OBJECTIVE: Installation of speed cameras is a common strategy to reduce over-speeding; however, there is evidence that their efficacy in speed reduction is limited to the proximity of the camera. This study aimed to evaluate driving speeds in relation to the position of cameras among Iranian taxi drivers. METHODS: Speed data were collected from April 2020 to January 2021 via telematics devices (using on-board computer, gyroscope, and GPS) installed on taxis in southern Tehran, Iran. All drivers were males above 20 years of age. Throughout the study, taxi drivers were not changed. Eligible road segments were selected based on: a) not containing any obstacle that would cause speed reduction; b) having ≤5 entry/exit points; c) absence of park and ride or taxi stations; and d) availability of at least 5,000 datapoints. The average speed was compared between the camera- and non-camera zones. Camera zone was defined as the area within 300 meters of the speed cameras. RESULTS: The telematics system included 2,644,846 datapoints gathered from 50 taxis. Two highways' segments with three lanes in each direction were included: Tehran-Varamin (18 taxis, 18,978 datapoints) and Ghadir (17 taxis, 8,203 datapoints). On both highways, speed was significantly lower in the camera zones (Tehran-Varamin: 84.9 ± 12.2 km/h versus 86.7 ± 13.7 km/h; P = 0.005; Kolmogorov-Smirnov test (KS) P < 0.001/Ghadir: 68.7 ± 13.7 versus 73.1 ± 11.3; P = 0.008; KS P < 0.001), indicating a V-shaped distribution of speed near the position of cameras (Presence of Kangaroo effect). Drivers were more likely to exceed speed limits in the non-camera zones compared to camera zones (Tehran-Varamin: 14.6% versus 8.4%/Ghadir: 23.1% versus 17.3%). This effect of the cameras was consistently observed in a subgroup analysis based on time of day (daytime versus nighttime). CONCLUSIONS: Among Iranian taxi drivers in southern Tehran, average speed was significantly lower in the vicinity of speed cameras, suggesting the presence of camera manipulation. Alternative speed control interventions are required to improve the safety of the taxi service.

Statistical modeling of speech Poincaré sections in combination of frequency analysis to improve speech recognition performance.

This paper introduces a combinational feature extraction approach to improve speech recognition systems. The main idea is to simultaneously benefit from some features obtained from Poincaré section applied to speech reconstructed phase space (RPS) and typical Mel frequency cepstral coefficients (MFCCs) which have a proved role in speech recognition field. With an appropriate dimension, the reconstructed phase space of speech signal is assured to be topologically equivalent to the dynamics of the speech production system, and could therefore include information that may be absent in linear analysis approaches. Moreover, complicated systems such as speech production system can present cyclic and oscillatory patterns and Poincaré sections could be used as an effective tool in analysis of such trajectories. In this research, a statistical modeling approach based on Gaussian mixture models (GMMs) is applied to Poincaré sections of speech RPS. A final pruned feature set is obtained by applying an efficient feature selection approach to the combination of the parameters of the GMM model and MFCC-based features. A hidden Markov model-based speech recognition system and TIMIT speech database are used to evaluate the performance of the proposed feature set by conducting isolated and continuous speech recognition experiments. By the proposed feature set, 5.7% absolute isolated phoneme recognition improvement is obtained against only MFCC-based features.

Prevalence of behavioural risk factors for road-traffic injuries among the Iranian population: findings from STEPs 2016.

BACKGROUND: To achieve Sustainable Development Goal 3.6 in Iran, we need to have a comprehensive understanding of the distribution of risky behaviours regarding road-traffic injuries at national and sub-national levels. Little is known about the road-use vulnerability patterns of road-traffic injuries in Iran. The aim of this study is to describe the prevalence of self-reported human risk factors in road-traffic injuries using the findings from a large-scale cross-sectional study based on the World Health Organization's stepwise approach to surveillance of non-communicable diseases (STEPs). METHODS: A cross-sectional survey study in 2016 assessed the road-use pattern and prevalence of risky behaviours of people more than 18 years old. In this study, we planned to recruit 31 050 individuals as a representative sample at national and provincial levels. In practice, 30 541 individuals (3105 clusters) from urban and rural areas of Iran were selected. Basic socio-demographic data, major behavioural risk factors such as seatbelt and helmet non-compliance, drunk driving and occupant in a car with a drunk driver were assessed through baseline interviews gathered through an Android tablet-based questionnaire. RESULTS: The overall prevalence of seatbelt and helmet compliance was 75.2% (95% confidence interval: 74.7-75.7) and 13.9% (13.4-14.5), respectively, at the national level. The prevalence of risk-taking behaviours such as drink driving was 0.5% (0.4-0.6) and for being an occupant in a car with a drunk driver was 3.5% (3.2-3.8). At the provincial level, the highest age-standardized prevalence of seatbelt compliance (89.6%) was almost 1.5 times higher than the lowest provincial prevalence (58.5%). In 63% of provinces, the lowest prevalence of seatbelt compliance was observed among people aged 18-24 years old. CONCLUSIONS: In Iran, existing disease-prevention and health-promotion programmes should be expanded to target vulnerable subgroups that have more prevalent human risk factors for road-traffic injuries. Further research is required to investigate the context-specific proximal human risk factors and vulnerability patterns in Iran.

An Approach Towards Reducing Road Traffic Injuries and Improving Public Health Through Big Data Telematics: A Randomised Controlled Trial Protocol.

OBJECTIVE: Deaths due to road traffic accidents (RTAs) are a major public health concern around the world. Developing countries are over-represented in these statistics. Punitive measures are traditionally employed to lower RTA related behavioural risk factors. These are, however, resource intensive and require infrastructure development. This is a randomised controlled study to investigate the effect of non-punitive behavioural intervention through peer-comparison feedback based on driver behaviour data gathered by an in-vehicle telematics device. DESIGN, SETTING, AND PARTICIPANTS: A randomised controlled trial using repeated measures design conducted in Iran on the drivers of 112 public transport taxis in Tehran province and 1309 inter-city busses operating nationwide. Driving data is captured by an in-vehicle telematics device and sent to a centrally located data centre using a mobile network. The telematics device is installed in all vehicles. Participants are males aged above 20 who have had the device operating in their vehicles for at least 3 months prior to the start of the trial. INTERVENTION: The study had three stages: 1- Driver performance was monitored for a 4-week period after which they were randomised into intervention and control groups. 2- Their performance was monitored for a 9-week period. At the end of each week, drivers in the intervention group received a scorecard and a note informing them of their weekly behaviour and ranking within their peer group. Drivers in the control group received no feedback via short messaging service (SMS). 3- Drivers did not receive further feedback and their behaviour was monitored for another 4 weeks. PRIMARY AND SECONDARY OUTCOME MEASURE: Primary outcome was changes in weekly driving score in intervention and control groups during stage 2 of intervention. Taxis and busses were analysed separately using generalised estimating equation analysis. FUNDING AND ETHICAL APPROVAL: This project was funded by the National Institute for Medical Research Development (Grant No.940576) and approved by its ethics committee (Code: IR.NIMAD.REC.1394.016). This trial was registered at www.irct.ir as IRCT20180708040391N1.

Modeling the gait of normal and Parkinsonian persons for improving the diagnosis.

In this study, we present a model for the gait of normal and Parkinson's disease (PD) persons. Gait is semi-periodic and has fractal properties. Sine circle map (SCM) relation has a sinusoidal term and can show chaotic behaviour. Therefore, we used SCM as a basis for our model structure. Moreover, some similarities exist between the parameters of this relation and basal ganglia (BG) structure. This relation can explain the complex behaviours and the complex structure of BG. The presented model can simulate the BG behaviour globally. A model parameter, Ω, has a key role in the model response. We showed that when Ω is between 0.6 and 0.8, the model simulates the behaviour of normal persons; the amounts greater or less than this range correspond to PD persons. Our statistical tests show that there is a significant difference between the Ω of normal and PD patients. We conclude that Ω can be introduced as a parameter to distinguish normal and PD persons. Additionally, our results showed that Spearman correlation between the Ω and the severity of PD is 0.586. This parameter may be a good index of PD severity.