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Objective: Road traffic injury (RTI) has become one of the leading causes of deaths in China, yet numbers on road traffic deaths are often inconsistent. This study sought to systematically review 4 national-level data sources that can be used to estimate burdens of RTI, including mortality, injury, and crashes in China. Methods: We conducted structured literature reviews in PubMed, using combined key words of injury or fatality or injury surveillance and traffic and China in order to identify relevant studies (in both English and Chinese) and data sources. We also conducted interviews and hosted seminars with key researchers from the Chinese Center for Disease Control and Prevention (Chinese CDC) to identify potential useful data sources for injury surveillance. We then extracted key information from publicly available reports of each data source. Results: Four national-level data sources were reviewed and compared: Ministry of Health-Vital Registration (MOH-VR) System, Chinese CDC-Disease Surveillance Points (DSP), Chinese CDC-National Injury Surveillance System (NISS), and police reports. Together they provide a complementary yet somewhat contradictory epidemiological profile of RTIs in China. Estimates on road traffic fatalities obtained from MOH-VR and police reports are often used by researchers and policymakers, whereas DSP and NISS, both with great merits, have virtually not been used for RTI research. Despite the well-documented problems of underreported deaths with both MOH-VR and DSP, estimated road traffic deaths from both systems were 3 times those reported by the police. Conclusions: As the foundation of injury prevention, national-level data sources and surveillance systems were reviewed in the study. Existing data infrastructures present the Chinese government a great opportunity to strengthen and integrate existing surveillance systems to better track road traffic injury and fatality and identify the population at risk.

National mortality data are obtained routinely by the Disease Surveillance Points system (DSPs) in China and under-reporting is a big challenge in mortality surveillance. We carried out an under-reporting field survey in all 161 DSP sites to collect death cases during 2009–2011, using a multi-stage stratified sampling. To identify under-reporting, death data were matched between field survey system and the routine online surveillance system by an automatic computer checking followed by a thorough manual verification. We used a propensity score (PS) weighting method based on a logistic regression to calculate the under-reporting rate in different groups classified by age, gender, urban/rural residency, geographic locations and other mortality related variables. For comparison purposes, we also calculated the under-reporting rate by using capture-mark-recapture (CMR) method. There were no significant differences between the field survey system and routine online surveillance system in terms of age group, causes of death, highest level of diagnosis and diagnostic basis. The overall under-reporting rate in the DSPs was 12.9 % (95%CI 11.2 %, 14.6 %) based on PS. The under-reporting rate was higher in the west (18.8 %, 95%CI 16.5 %, 21.0 %) than the east (10.1 %, 95%CI 8.6 %, 11.3 %) and central regions (11.2 %, 95%CI 9.6 %, 12.7 %). Among all age groups, the under-reporting rate was highest in the 0–5 year group (23.7 %, 95%CI 16.1 %, 35.5 %) and lowest in the 65 years and above group (12.4 %, 95%CI 10.9 %, 13.6 %). The under-reporting rates in each group by PS were similar to the results calculated by the CMR methods. The mortality data from the DSP system in China needs to be adjusted. Compared to the commonly used CMR method in the estimation of under-reporting rate, the results of propensity score weighting method are similar but more flexible when calculating the under-reporting rates in different groups. Propensity score weighting is suitable to adjust DSP data and can be used to address under-reporting in mortality surveillance in China.

Road traffic injuries (RTI) impose a substantial health burden among children. Globally, 186 300 children (under 18 years) die from RTI each year. It is the fourth leading cause of death among children aged 5–9 years, third among children aged 10–14 years and first among children aged 15–17 years. At the regional level, sub-Saharan Africa accounts for 35.2% of global child deaths caused by RTI; that number is still increasing. Male children are about two times more likely to die due to RTI than female children. RTI are also related to socioeconomic inequalities; low-income and middle-income countries (LMIC) account for 95% of global child RTI deaths, and children from poor households are more likely to fall victims to RTI. Intervention strategies promoted in the five pillars of the Decade of Action for Road Safety 2011–2020 are available to prevent mortality and morbidity caused by RTI, though validation and implementation of such interventions are urgently needed in the LMIC. Through concerted efforts to cultivate strong political will, build action and advocacy capacity, increase global funding and enhance multisectoral collaboration promoted by the Sustainable Development Goals, the world is challenged to do better in saving children from RTI.

The importance of the family planning service environment and community-level factors on contraceptive use has long been studied. Few studies, however, have been able to link individual and health facility data from surveys that are nationally representative, concurrently fielded, and geographically linked. Data from Performance Monitoring and Accountability 2020 address these limitations. To assess the relative influences of the service delivery environment and community, household, and individual factors on a woman’s likelihood of using a modern contraceptive in five geographically and culturally diverse sub-Saharan African countries. Nationally representative, cross-sectional data from PMA2020 were linked at the household and service delivery level. Country-specific and pooled multilevel multinomial logistic models, comparing non-users, short- and long-acting method users were used. The variables elected for inclusion in our multivariate analyses were guided by the conceptual framework to profile the different levels of influences on individual use of modern contraception. Average marginal effects were calculated to improve interpretability. We find that the effect of contextual factors varies widely but that being visited by a health worker who spoke about family planning in the past 12 months was consistently and positively associated with individual use of short-acting and long-acting contraception. Characteristics of the nearest health facility did not generally exercise their own independent influences on a woman’s use of contraception, except in the case of Burkina Faso, where the average distance between individuals and the nearest family planning provider was significantly greater than other countries. Inclusion of country fixed effects in the pooled models and the relevance of covariates at different levels in the country-specific models demonstrate that there is significant variation across countries in how community, individual, and service delivery environment factors influence contraceptive use and method choice. Context must be taken into account when designing family planning programs.