Search

BackgroundIn China, the cases of newly diagnosed HIV/AIDS in men who have sex with men (MSM) have increased more than tenfold since 2006. However, the MSM population size, geographical distribution, and migration patterns are largely unknown. ObjectiveOur aim is to estimate the number, spatial distribution, and migration of MSM populations in mainland China using big data from social networking. MethodsWe collected 85 days of data on online users of a social networking MSM app in mainland China. Daily online MSM users and their migration across the country were investigated during a holiday period and a nonholiday period. Using the capture-mark-recapture model, we designed an experiment consisting of two independent samples to estimate the total provincial MSM population. ResultsThe estimate of MSM in mainland China was 8,288,536 (95% CI 8,274,931-8,302,141), accounting for 1.732% (95% CI 1.729%-1.734%) of adult men aged 18 to 64 years. The average daily number of MSM social networking online across mainland China was 1,198,682 during the nonholiday period. The five provinces (including municipalities) with the highest average number of daily online MSM numbers were Guangdong (n=141,712), Jiangsu (n=90,710), Zhejiang (n=72,212), Shandong (n=68,065), and Beijing (n=66,057). The proportion of daily online MSM among adult men in different cities varied from 0.04% to 0.96%, with a mean of 0.20% (SD 0.14%). Three migrating centers—Guangdong, Beijing, and the Yangtze River Delta (Shanghai-Zhejiang-Jiangsu)—accounted for 57.23% of MSM migrants in the county. ConclusionsThe percentage of MSM among adult men in mainland China is at the middle level compared with other Asia and Pacific countries. However, the number of MSM is very large, and the distribution is uneven. Both MSM distribution and migration are highly affected by socioeconomic status.

Green space is not always equitably located in cities, and the attractiveness of green space varies, leaving some residents with easy access to high-quality parks and others with little or no access or access to under-maintained parks. To remedy these inequities, this study identified attractive and well-utilized recreational green spaces and developed a model to measure the likelihood of using these recreational green spaces (PSG). The goal was to reduce the travel time and cost of walking or using public transportation to get to green spaces and to design all green spaces to be attractive. The data come from the perspective of the city's public transportation system and residents' personal choices. First, the attractiveness of recreational green spaces was calculated from big data on the geolocation of cell phones, measuring the level of provision of recreational green spaces and the trip rates of urban residents. After that, the travel cost to reach recreational green space in residential areas was calculated according to residents' travel habits. Finally, the probability of all recreational green spaces in the city being used was calculated by combining the population size of residential areas. Taking Pu'er City in China as an example, the attractiveness and utilization rates of recreational green spaces were calculated by PSG, and the results of the study showed that the probability of residents choosing to use the recreational green spaces that are closer to the residential area, with a larger population capacity, and with a higher attractiveness is the highest. The results of the study help promote equitable access to health and socialization opportunities for individuals and communities, thereby promoting environmental justice to help mitigate and respond to climate change. [ABSTRACT FROM AUTHOR]

The occurrence of chickenpox in rapidly developing areas poses substantial seasonal risk to children. However, certain factors influencing local chickenpox outbreaks have not been studied. Here, we examined the relationship between spatial clustering, heterogeneity of chickenpox outbreaks, and socioeconomic factors in Southern China. We assessed chickenpox outbreak data from Southern China between 2006 and 2021, comprising both relatively fast-growing parts and slower sub-regions, and provides a representative sample of many developing regions. We analyzed the spatial clustering attributes associated with chickenpox outbreaks using Moran's I and local indicators of spatial association and quantified their socioeconomic determinants using Geodetector q statistics. There were significant spatial heterogeneity in the risk of chickenpox outbreaks, with strong correlations between chickenpox risk and various factors, particularly demographics and living environment. Furthermore, interactive effects among specific are factors, such as population density and per capita residential building area, percentage of households with toilets, percentage of rental housing, exhibited q statistics of 0.28, 0.25, and 0.24, respectively. This study provides valuable insights into the spatial dynamics of chickenpox outbreaks in rapidly developing regions, revealing the socioeconomic factors affecting disease transmission. These implications extend the formulation of effective public health strategies and interventions to prevent and control chickenpox outbreaks in similar global contexts. [ABSTRACT FROM AUTHOR]