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China's 30-year economic boom has created a unique social and economic market for commercial sex, as well as for a workforce of migrant women from rural China. This qualitative study explores the impact of the rapidly changing social and economic environment on migration patterns, sexually transmitted infection (STI) knowledge, STI risk behaviours, and health beliefs among female streetwalkers in Shanghai. Qualitative data were collected in 2010 through semi-structured in-depth interviews with 16 streetwalkers to characterise their migration passages, sexual health and behaviours, and peer networks. Many streetwalkers reported histories of childhood impoverishment, of family or partner violence or trauma, of migration consistent with the timeline and routes of economic development, and of a scarcity in health, social, or economic support. Their knowledge of the prevention and treatment of HIV and STIs was limited. They had little bargaining power on condom use, and the majority resorted to vaginal douching and self-management with antibiotics as preventative measures. The study identifies streetwalkers’ perspectives on the changing environment, their options and actions, and finally HIV/STI risks that were unique to this hidden population.

Objectives Bicycling and helmet surveillance, research, and programme evaluation depend on accurate measurement by direct observation, but it is unclear whether weather and other exogenous factors introduce bias into observed counts of cyclists and helmet use.

There is a need to develop motorcycle helmet surveillance approaches that are less labour intensive than direct observation (DO), which is the commonly recommended but never formally validated approach, particularly in developing settings. This study sought to assess public traffic camera feeds as an alternative to DO, in addition to the reliability of DO under field conditions. DO had high inter-rater reliability, κ=0.88 and 0.84, respectively, for cycle type and helmet type, which reinforces its use as a gold standard. However, traffic camera-based data collection was found to be unreliable, with κ=0.46 and 0.53 for cycle type and helmet type. When bicycles, motorcycles and scooters were classified based on traffic camera streams, only 68.4% of classifications concurred with those made via DO. Given the current technology, helmet surveillance via traffic camera streams is infeasible, and there remains a need for innovative traffic safety surveillance approaches in low-income urban settings.