TY  - JOUR
PY  - 2022//
TI  - Road traffic fatalities in Tunisia: a multisector sources data linkage [conference abstract #559]
JO  - Injury prevention
A1  - Saidi, Wafa
A1  - Souguir, Mohamed Amine
A1  - Khelil, Mehdi Ben
A1  - Zoghlami, Nada
A1  - Hamdi, Imed
A1  - Saidi, Olfa
A1  - Amira, Hatem
A1  - Aounallah-Skhir, Hajer
A1  - Khefifi, Saber
A1  - Iyach, Kacem
A1  - Chebbi, Henda
SP  - A86
EP  - A86
VL  - 28
IS  - Suppl 2
N2  - Proceedings of the 14th World Conference on Injury Prevention and Safety Promotion (Safety 2022)    Background In Tunisia, road traffic fatalities (RTF) count as the first cause of death from an external cause. To date, The National Road Safety Observatory (NRSO), Ministry of the Interior is recognized as the official data source.This study aimed to set up a linkage project between the five main data sources (including the official one), to analyze the underestimation of RTF, and to study its pattern.     Methods A platform has been developed allowing the implementation of a computer system unifying and combining all the data on RTF from five institutions related to Police authorities, health sector, and private insurances. Data were collected for the year 2019.     Results The official data source (NRSO) reported a total of 1421 road traffic fatalities. The total number of deaths observed after combining the sources moved to 2240 casualties, from which 53% were joint between at least two data sources. Only one casualty was reported by the five data sources. Victims were more likely to be male, in the 26-45 age group. The governorate of Tunis (the capital) has recorded the highest number.    This multisectoral linkage project has improved the information systems of each institution with a variable improvement estimated between 9.5% and 100% for the institutions that created a new information system.     Conclusion The linkage data proved the statistics gap of RTF allowing drawing a more accurate picture of the real figures. The project concluded a better alignment between the declared figures and the approximations needed to adapt preventive measures of RTF.<p />  <p>Language: en</p>
LA  - en
SN  - 1353-8047
UR  - http://dx.doi.org/10.1136/injuryprev-2022-safety2022.255
ID  - ref1
ER  -