Assessing discrepancies in estimates of road traffic deaths in Brazil.

INTRODUCTION: The First UN Decade of Action for Road Safety (2011-2020) ended with most low/middle-income countries (LMICs) failing to reduce road traffic deaths. In contrast, Brazil reported a strong decline starting in 2012. However, comparisons with global health statistical estimates suggest that official statistics from Brazil under-report traffic deaths and overestimate declines. Therefore, we sought to assess the quality of official reporting in Brazil and explain discrepancies. METHODS: We obtained national death registration data and classified deaths to road traffic deaths and partially specified causes that could include traffic deaths. We adjusted data for completeness and reattributed partially specified causes proportionately over specified causes. We compared our estimates with reported statistics and estimates from the Global Burden of Disease (GBD)-2019 study and other sources. RESULTS: We estimate that road traffic deaths in 2019 exceeded the official figure by 31%, similar to traffic insurance claims (27.5%) but less than GBD-2019 estimates (46%). We estimate that traffic deaths have declined by 25% since 2012, close to the decline estimated by official statistics (27%) but much more than estimated by GBD-2019 (10%). We show that GBD-2019 underestimates the extent of recent improvements because GBD models do not track the trends evident in the underlying data. CONCLUSION: Brazil has made remarkable progress in reducing road traffic deaths in the last decade. A high-level evaluation of what has worked in Brazil could provide important guidance to other LMICs.

Addressing discrepancies in estimates of road traffic deaths and injuries in Ethiopia.

BACKGROUND: There are large discrepancies between official statistics of traffic injuries in African countries and estimates from the Global Burden of Disease (GBD) study and WHO's Global Status Reports on Road Safety (GSRRS). We sought to assess the magnitude of the discrepancy in Ethiopia, its implications and how it can be addressed. METHODS: We systematically searched for nationally representative epidemiological data sources for road traffic injuries and vehicle ownership in Ethiopia and compared estimates with those from GBD and GSRRS. FINDINGS: GBD and GSRRS estimates vary substantially across revisions and across projects. GSRRS-2018 estimates of deaths (27 326 in 2016) are more than three times GBD-2019 estimates (8718), and these estimates have non-overlapping uncertainty ranges. GSRRS estimates align well with the 2016 Demographic and Health Survey (DHS-2016; 27 838 deaths, 95th CI: 15 938 to 39 738). Official statistics are much lower (5118 deaths in 2018) than all estimates. GBD-2019 estimates of serious non-fatal injuries are consistent with DHS-2016 estimates (106 050 injuries, 95th CI: 81 728 to 130 372) and older estimates from the 2003 World Health Survey. Data from five surveys confirm that vehicle ownership levels in Ethiopia are much lower than in other countries in the region. INTERPRETATION: Inclusion of data from national health surveys in GBD and GSRRS can help reduce discrepancies in estimates of deaths and support their use in highlighting under-reporting in official statistics and advocating for better prioritisation of road safety in the national policy agenda. GBD methods for estimating serious non-fatal injuries should be strengthened to allow monitoring progress towards Sustainable Development Goal target 3.6.

Estimates of road traffic deaths in Tanzania.

INTRODUCTION: There is considerable uncertainty in estimates of traffic deaths in many sub-Saharan African countries, with the Global Burden of Disease (GBD) and the Global Status Report on Road Safety (GSRRS) reporting widely differing estimates. As a case study, we reviewed and compared estimates for Tanzania. METHODS: We estimated the incidence of traffic deaths and vehicle ownership in Tanzania from nationally representative surveys. We compared findings with GBD and GSRRS estimates. RESULTS: Traffic death estimates based on the 2012 census (9382 deaths; 95% CI: 7565 to 11 199) and the 2011-2014 Sample Vital Registration with Verbal Autopsy (8778; 95% CI: 7631 to 9925) were consistent with each other and were about halfway between GBD (5 608; 95% UI: 4506 to 7014) and WHO (16 252; 95% CI: 13 130 to 19 374) estimates and more than twice official statistics (3885 deaths in 2013). Surveys and vehicle registrations data show that motorcycles have increased rapidly since 2007 and now comprise 66% of vehicles. However, these trends are not reflected in GBD estimates of motorcycles in the country, likely resulting in an underestimation of motorcyclist deaths. CONCLUSION: Reducing discrepancies between GBD and GSRRS estimates and demonstrating consistency with local epidemiological data will increase the legitimacy of such estimates among national stakeholders. GBD, which is the only project that models the road-user distribution of traffic deaths in all countries, likely severely underestimates motorcycle deaths in countries where there has been a recent increase in motorcycles. Addressing police under-reporting and strengthening surveillance capacity in Tanzania will allow a better understanding of the road safety problem and better targeting of interventions.

Comparing estimates of road traffic deaths and non-fatal road traffic injuries in Cambodia.

INTRODUCTION: Timely, accurate and detailed information about traffic injuries are essential for managing national road safety programmes. However, there is considerable under-reporting in official statistics of many low and middle-income countries (LMICs) and large discrepancies between estimates from the Global Burden of Disease (GBD) study and WHO's Global Health Estimates (GHE). We compared all sources of epidemiological information on traffic injuries in Cambodia to guide efforts to improve traffic injury statistics. METHODS: We estimated the incidence of traffic deaths and injuries and household ownership of motor vehicles in Cambodia from nationally representative surveys and censuses. We compared findings with GDB and GHE estimates. RESULTS: We identified seven sources for estimating traffic deaths and three for non-fatal injuries that are not included as data sources in GBD and GHE models. These sources and models suggest a fairly consistent estimate of approximately 3100 deaths annually, about 50% higher than official statistics, likely because most hospital deaths are not recorded. Surveys strongly suggest that the vehicle fleet is dominated by motorcycles, which is not consistent with GBD estimates that suggest similar numbers of motorcyclist and vehicle occupant deaths. Estimates of non-fatal injuries from health surveys were about 7.5 times official statistics and 1.5 times GBD estimates. CONCLUSION: Including local epidemiological data sources from LMICs can help reduce uncertainty in estimates from global statistical models and build trust in estimates among local stakeholders. Such analysis should be used as a benchmark to assess and strengthen the completeness of reporting of the national surveillance system.

Availability of population-level data sources for tracking the incidence of deaths and injuries from road traffic crashes in low-income and middle-income countries.

INTRODUCTION: Tracking progress towards Sustainable Development Goal (SDG) 3·6 of reducing traffic deaths and serious injuries poses a measurement challenge in most low-income and middle-income countries (LMICs) due to large discrepancies between reported official statistics and estimates from global health measurement studies. We assess the extent to which national population censuses and health surveys can fill the information gaps. METHODS: We reviewed questionnaires for nationally representative surveys and censuses conducted since 2000 in LMICs. We identified sources that provide estimates of household ownership of vehicles, incidence of traffic deaths and non-fatal injuries, and prevalence of disability. RESULTS: We identified 802 data sources from 132 LMICs. Sub-Saharan African countries accounted for 43% of all measurements. The number of measurements since 2000 was high, with 97% of the current global LMIC population having at least one measurement for vehicle ownership, 77% for deaths, 90% for non-fatal injuries and 50% for disability due to traffic injuries. Recent data (since 2010) on traffic injuries were available from far fewer countries (deaths: 21 countries; non-fatal injuries: 62 and disability: 12). However, there were many more countries with recent data on less-specific questions about unintentional or all injuries (deaths: 41 countries, non-fatal: 87, disability: 32). CONCLUSION: Traffic injuries are substantially underreported in official statistics of most LMICs. National surveys and censuses provide a viable alternative information source, but despite a large increase in their use to monitor SDGs, traffic injury measurements have not increased. We show that relatively small modifications and additions to questions in forthcoming surveys can provide countries with a way to benchmark their existing surveillance systems and result in a substantial increase in data for tracking road traffic injuries globally.