Epidemiological characteristics and transmission dynamics of dengue fever in China.

China has experienced successive waves of dengue epidemics over the past decade. Nationwide data on 95,339 dengue cases, 89 surveillance sites for mosquito density and population mobility between 337 cities during 2013-20 were extracted. Weekly dengue time series including time trends and harmonic terms were fitted using seasonal regression models, and the amplitude and peak timing of the annual and semiannual cycles were estimated. A data-driven model-inference approach was used to simulate the epidemic at city-scale and estimate time-evolving epidemiological parameters. We found that the geographical distribution of dengue cases was expanding, and the main imported areas as well as external sources of imported cases changed. Dengue cases were predominantly concentrated in southern China and it exhibited an annual peak of activity, typically peaking in September. The annual amplitude of dengue epidemic varied with latitude (F = 19.62, P = 0.0001), mainly characterizing by large in southern cities and small in northern cities. The effective reproduction number Reff across cities is commonly greater than 1 in several specific months from July to November, further confirming the seasonal fluctuations and spatial heterogeneity of dengue epidemics. The results of this national study help to better informing interventions for future dengue epidemics in China.

Critical windows for exposure to chemical composition of ambient particulate matter and human semen quality decline.

BACKGROUND: Critical windows for exposure to chemical components of particulate matter (PM <2.5 µm in diameter [PM2.5]) associated with the human semen quality decline remain unclear. OBJECTIVES: To address this gap, we developed a new analytical framework by integrating a Linear Mixed Model (LMM) with subject- and center-specific intercepts and a Distributed Lag Model (DLM) to fully account for correlations between finely vulnerable exposure windows based on complete profile of the spermatogenesis cycle. METHODS: We constructed a multicenter cohort involving 33,234 sperm donors with 78,952 semen samples covering 6 representative regions across China from 2014 to 2020 to investigate the week-scale critical windows for the exposure. Daily exposure to PM2.5 chemical components of donors was derived from grid data based on 1-km spatial resolution surface measurements. RESULTS: Decreased sperm count was significantly associated with NO3- and SO42- at 9-10 weeks (e.g., ß: -0.05 %, 95%CI: [-0.10 %, -0.00 %] at the 9th week) and 0-2 weeks (e.g., ß: -0.66 %, 95%CI: [-1.24 %, -0.07 %] at the 1st week), respectively. Critical windows of progressive motility decline were 0-10 weeks for BC (e.g., ß: -0.07 %, 95%CI: [-0.11 %, -0.03 %] at the 5th week), Cl- at 1-4 weeks (e.g., ß: -2.21 %, 95%CI: [-3.77 %, -0.66 %] at the 2nd week), 0-6 weeks and 9-10 weeks for NO3- (e.g., ß: -0.05 %, 95%CI: [-0.09 %, -0.01 %] at the 4th week), 1-3 weeks and the 8th week for NH4+ (e.g., ß: -0.06 %, 95%CI: [-0.11 %, -0.01 %] at the 2nd week). Total motility is significantly negatively associated with BC at entire windows, Cl- at 0-3 weeks, the 5th week and 9-10 weeks. CONCLUSIONS: There are week-scale vulnerable windows of exposure to PM2.5 chemical components for human semen quality. This highlights the need for more targeted pollution control strategies addressing PM2.5 and its chemical components.

Beneficial effect of residential greenness on sperm quality and the role of air pollution: A multicenter population-based study.

BACKGROUND: Poor sperm quality is a major cause of male infertility. However, evidence remains scarce on how greenness affects male sperm quality. OBJECTIVES: To assess the associations of residential greenness with male sperm quality and the modification effect of air pollution exposure on the relationship. METHODS: A total of 78,742 samples from 33,184 sperm donors from 6 regions across China during 2014-2020 were included and analyzed. Individual residential greenness exposures of study subjects were estimated using the Normalized Difference Vegetation Index (NDVI) during the entire (0-90 lag days) and two key stages (0-37, and 34-77 lag days) of sperm development. Contemporaneous personal exposure levels to air pollutants were estimated using a spatio-temporal deep learning method. Linear mixed models were employed to assess the impact of greenspace in relation to sperm quality. The modification effect of air pollution on the greenspace-sperm quality relationship was also estimated. RESULTS: Per IQR increment in NDVI exposure throughout spermatogenesis were statistically associated with increasing sperm count by 0.0122 (95 % CI: 0.0007, 0.0237), progressive motility by 0.0162 (95 % CI: 0.0045, 0.0280), and total motility by 0.0147 (95 % CI: 0.0014, 0.0281), respectively. Similar results were observed when the model added air pollutants (PM1, PM2.5 or O3) for adjustment. Additionally, specific air pollutants, including PM1, PM2.5, and O3, were found to modify this association. Notably, the protective effects of greenness exposure were more pronounced at higher concentrations of PM1 and PM2.5 and lower concentrations of O3 (all Pinteraction < 0.05). Statistically significant positive effects of NDVI were observed on sperm motility in early spermatogenesis and sperm count in late spermatogenesis. CONCLUSIONS: Exposure to residential greenness may have beneficial effects on sperm quality and air pollution modifies their relationship. These findings highlight the importance of adopting adaptable urban greenspace planning and policies to safeguard male fertility against environmental factors.