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With the implementation processes of strategies such as Guangdong-Hong Kong-Macau Greater Bay Area's coordinated development and "Belt and Road Initiative" initiative, the planning policies had produced a significant influence on land use distributions in Guangzhou. In this paper, we employ nighttime light (NTL) information as a proxy indicator of gross domestic product(GDP), and a future land use simulation model (FLUS) to simulate the land use patterns in Guangzhou from 2015 to 2018 and 2018 to 2035 by incorporating planning policies. The results show that: (1) the accuracy of simulation result from 2015 to 2018 based on National Polar-orbiting Partnership, Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) is higher than that based on GDP; (2) by incorporating planning policies into the model can better identify the potential spatial distribution of urban land and make the simulated results more consistent with the actual urban land development trajectory. This study demonstrates that NTL is a suitable and feasible proxy indicator of GDP for the land use simulations, providing a scientific basis for the development of urban planning and construction policy. [ABSTRACT FROM AUTHOR]

Human immunodeficiency virus (HIV) and sexually transmitted diseases (STDs) cause substantial morbidity and mortality both in African and China. However, there is limited data available on the prevalence of HIV/STDs and the uptake of testing experience ever during in China among African migrants. A venue-based survey was conducted at a tertiary hospital in Guangzhou to investigate the prevalence of HIV/STDs through laboratory testing and identify the associated factors. A total of 200 eligible participants completed the survey and bring into the analysis from April to October 2019, and the temporary visitors were excluded. The prevalence rates of HIV, syphilis, NG, CT, and HBsAg among the participants were 1.0%, 2.5%, 1.0%, 1.5%, and 5.5%, respectively. The overall reported rate of HIV/STD testing was 37.0%, with rates of 23.0% for HIV, 16.5% for syphilis, 12.5% for NG, 6.5% for genital herpes, 5.0% for condyloma acuminata, and 2.5% for CT. HIV/STD testing was associated with living environment in Guangzhou, having medical insurance in China, and utilizing health services in China in the past year. HIV/STDs are prevalent among Africans in Guangzhou, and the epidemic is likely to spread due to a significant proportion of unprotected sexual behaviors and low rates of HIV/STD testing. Urgent interventions, including targeted health education, promotion of health service utilization, and active surveillance of HIV/STDs, are needed to reduce the risk of HIV/STD transmission. [ABSTRACT FROM AUTHOR]

Background: Previous studies exploring the factors associated with the incidence of syphilis have mostly focused on individual-level factors. However, recent evidence has indicated that social-level factors, such as sociodemographic and socioeconomic factors, also affect the incidence of syphilis. Studies on the sociodemographic and socioeconomic factors associated with syphilis incidence are scarce, and they have rarely controlled for spatial effects, even though syphilis shows spatial autocorrelation. Methodology/Principal findings: Syphilis data from 21 cities in Guangdong province between 2005 and 2017 were provided by the National Notifiable Infectious Disease Reporting Information System. The incidence time series, incidence map, and space-time scanning data were used to visualize the spatiotemporal distribution. The spatial panel data model was then applied to explore the relationship between sociodemographic factors (population density, net migration rate, male:female ratio, and the number of health institutions per 1,000 residents), socioeconomic factors (gross domestic product per capita, the proportion of secondary/tertiary industry), and the incidence of primary and secondary syphilis after controlling for spatial effects. The incidence of syphilis increased slowly from 2005 (11.91 per 100,000) to 2011 (13.42 per 100,000) and then began to decrease, reaching 6.55 per 100,000 in 2017. High-risk clusters of syphilis tended to shift from developed areas to underdeveloped areas. An inverted U-shaped relationship was found between syphilis incidence and gross domestic product per capita. Moreover, syphilis incidence was significantly associated with population density (β = 2.844, P = 0.006), the number of health institutions per 1,000 residents (β = -0.095, P = 0.007), and the net migration rate (β = -0.219, P = 0.002). Conclusions/Significance: Our findings suggest that the incidence of primary and secondary syphilis first increase before decreasing as economic development increases further. These results emphasize the necessity to prevent syphilis in regions at the early stages of economic growth. Author summary: Syphilis is a sexually transmitted infection that continues to cause morbidity and mortality worldwide. The primary and secondary stages of syphilis are the most transmissive stages in the entire process of the disease. We analyzed primary and secondary (P&S) syphilis data from 2005 to 2017 in Guangzhou, China, provided by the National Notifiable Infectious Disease Reporting Information System. The results showed that the annual incidence rates of P&S syphilis slightly increased from 2005 to 2011 and then began to decrease in 2017. Cases of P&S syphilis were spatially clustered. The high-risk syphilis clusters tended to shift from developed areas to underdeveloped areas. There may be an inverted U-shaped relationship between the level of economic development and the incidence of P&S syphilis, suggesting that the incidence of P&S syphilis first increased before decreasing as the level of economic development increased further. These results emphasize the necessity of preventing syphilis at locations in the early stage of economic growth. Investments in syphilis prevention education for people in regions at early development stages may mitigate the increasing cost of syphilis to future healthcare systems. [ABSTRACT FROM AUTHOR]

Background Men who have sex with men (MSM) are vulnerable risk group for human immunodeficiency virus (HIV)-1 infection. However, some MSM do not disclose their same-sex behavior and could impact the transmission and prevention of HIV-1 infection. Here, we evaluated the role of nondisclosed MSM in HIV-1 transmission in Guangzhou, China. Methods The HIV-1 pol sequences were obtained from HIV-infected subjects from 2008 to 2015. A transmission network was constructed using HIV TRAnsmission Cluster Engine (HIV-TRACE) at a pairwise genetic distance of 0.5%. The position of nondisclosed MSM in the network was determined by centrality analysis. Results Nondisclosed MSM were inferred in 9.92% (61 of 615) of slightly older, self-reported non-MSM (P =.006). They were more likely to be married (P =.002) and less educated (P <.001) than the MSM with whom they clustered. Closeness centrality was bigger for nondisclosed MSM than for MSM (P <.001), indicating the central position of nondisclosed MSM in the networks. The average shortest path length was smaller for nondisclosed MSM than for MSM (P <.001), whereas radiality was bigger for nondisclosed MSM than for MSM, suggesting a relatively greater contribution of nondisclosed MSM in transmitting HIV-1 than MSM. Assortativity analysis indicated that nondisclosed MSM were more likely to link each other with coefficient of 0.025. Conclusions Nondisclosed MSM are a specific group, and they play an important role in HIV-1 transmission. They could be bisexual and might increase the risk of HIV-1 infection to their sex partners. Therefore, specific prevention and intervention targeting nondisclosed MSM are urgently needed. [ABSTRACT FROM AUTHOR]

[Display omitted] • Convolutional neural networks (CNN) can classify acoustic scenes from urban forests. • Acoustic scene activity intensity can be measured using target sound area ratios. • Urban forests have ten times more human disturbed birdsong than pure birdsong. • The acoustic scene composition is largely affected by forest and city land uses. • Changing environmental conditions alter the vocal frequencies of vocal organisms. Monitoring biodiversity and assessing the impact of human activities using acoustics is a promising area in the field of urban ecology. Previous studies on urban biodiversity using acoustics are often limited by data continuity and survey scope, making it difficult to answer questions about relationships between bird population dynamics and environmental factors. To some extent, big data methods such as continuous acoustic monitoring have bridged this gap and provided new research paths to address the problem. In this study, we proposed a machine learning (ML) method that uses convolutional neural networks (CNN) and target sound area ratios (TSAR) to quantify the dominance of seven types of acoustic scenes. Acoustic data was recorded at nine sites in three urban forests in Guangzhou, China. Using the site-related sound data, we trained the convolutional neural network and identified seven target soundscape components with an overall F1 score of 0.97, a precision of 0.96, and a recall of 0.97. Spatial patterns of acoustic scenes in urban forests were examined to understand the effective working radius of monitoring equipment and the impacts of differing land use types on the composition of soundscapes. This study indicates significant interactions between human activities and biodiversity using acoustics, demonstrates that vocal organisms respond to environmental changes primarily by changes in their vocal frequencies, and proposes a novel framework for utilizing acoustics to monitor urban biodiversity. Going forth, these analyses help to promote the conservation of biodiversity and the sustainability of urban development. [ABSTRACT FROM AUTHOR]