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BackgroundTelemedicine provides remote health care services to overcome constraints of time and space in accessing medical care. Similarly, internet hospitals in China support and provide remote health care services. Due to the COVID-19 pandemic, there has been a proliferation of internet hospitals. Many new services, including online consultations and regular online follow-up visit services, can now be accessed via internet hospitals in China. However, the accessibility, cost, and quality advantages of regular online follow-up visit services remain unclear. ObjectiveThis study aimed to evaluate the accessibility, costs, and quality of an online regular follow-up visit service provided by an internet hospital in China. By analyzing the accessibility, costs, and quality of this service from the supply and demand sides, we can summarize the practical and theoretical experiences. MethodsA mixed methods study was conducted using clinical records from 18,473 patients receiving 39,239 online regular follow-up visit services at an internet hospital in 2021, as well as interviews with 7 physicians, 2 head nurses, and 3 administrative staff members. The quantitative analysis examined patient demographics, diagnoses, prescriptions, geographic distribution, physician characteristics, accessibility (travel time and costs), and service hours. The qualitative analysis elucidated physician perspectives on ensuring the quality of online health care. ResultsPatients were predominantly middle-aged men with chronic diseases like viral hepatitis who were located near the hospital. The vast majority were from Guangdong province where the hospital is based, especially concentrated in Guangzhou city. The online regular follow-up visit service reduced travel time by 1 hour to 9 hours and costs by ¥6 to ¥991 (US $0.86-$141.32) depending on proximity, with greater savings for patients farther from the hospital. Consultation times were roughly equivalent between online and in-person visits. Physicians provided most online services during lunch breaks (12 PM to 2 PM) or after work hours (7 PM to 11 PM), indicating increased workload. The top departments providing online regular follow-up visit services were Infectious Diseases, Rheumatology, and Dermatology. The most commonly prescribed medications aligned with the prevalent chronic diagnoses. To ensure quality, physicians conducted initial in-person consultations to fully evaluate patients before allowing online regular follow-up visits, during which they communicated with patients to assess conditions and determine if in-person care was warranted. They also periodically reminded patients to come in person for more comprehensive evaluations. However, they acknowledged online visits cannot fully replace face-to-face care. ConclusionsTelemedicine services such as online regular follow-up visit services provided by internet hospitals must strictly adhere to fundamental medical principles of diagnosis, prescription, and treatment. For patients with chronic diseases, online regular follow-up visit services improve accessibility and reduce cost but cannot fully replace in-person evaluations. Physicians leverage various strategies to ensure the quality of online care.

Abstract Background In Guangdong Province, China, there is lack of information on the HIV epidemic among high-risk groups and the general population, particularly in relation to sexual transmission, which is a predominant route. The new HIV infections each year is also uncertain owing to HIV transmission from men who have sex with men (MSM) to women, as a substantial proportion of MSM also have female sexual partnerships to comply with social demands in China. Methods A deterministic compartmental model was developed to predict new HIV infections in four risk groups, including heterosexual men and women and low- and high-risk MSM, in Guangdong Province from 2016 to 2050, considering HIV transmission from MSM to women. The new HIV infections and its 95% credible interval (CrI) were predicted. An adaptive sequential Monte Carlo method for approximate Bayesian computation (ABC-SMC) was used to estimate the unknown parameter, a mixing index. We calibrated our results based on new HIV diagnoses and proportions of late diagnoses. The Morris and Sobol methods were applied in the sensitivity analysis. Results New HIV infections increased during and 2 years after the COVID-19 pandemic, then declined until 2050. New infections rose from 8,828 [95% credible interval (CrI): 6,435–10,451] in 2016 to 9,652 (95% CrI: 7,027–11,434) in 2019, peaking at 11,152 (95% CrI: 8,337–13,062) in 2024 before declining to 7,084 (95% CrI: 5,165–8,385) in 2035 and 4,849 (95% CrI: 3,524–5,747) in 2050. Women accounted for approximately 25.0% of new HIV infections, MSM accounted for 40.0% (approximately 55.0% of men), and high-risk MSM accounted for approximately 25.0% of the total. The ABC-SMC mixing index was 0.504 (95% CrI: 0.239–0.894). Conclusions Given that new HIV infections and the proportion of women were relatively high in our calibrated model, to some extent, the HIV epidemic in Guangdong Province remains serious, and services for HIV prevention and control are urgently needed to return to the levels before the COVID-19 epidemic, especially in promoting condom-based safe sex and increasing awareness of HIV prevention to general population.

Summary: Background: Dementia poses great health and social challenges in China. Dementia prevalence may vary across geographic areas, while comparable estimations on provincial level is lacking. This study aims to estimate dementia prevalence by provinces across China, taking into account risk factors of individual level and potential spatial correlation of provinces. Methods: In this study, 17,176 adults aged 50 years or older were included from the fourth wave of the China Health and Retirement Longitudinal Study (CHARLS 2018), covering 28 provinces, autonomous regions and municipalities. To improve provincial representativeness, we constructed provincial survey weights based on China 7th census (2020). The prevalence of dementia and 95% Bayesian credible intervals (BCIs) were estimated using a Bayesian conditional autoregressive (CAR) model with spatially varying coefficients of covariates. Findings: The weighted prevalence of dementia at provincial level in China in 2018 ranged from 2.62% (95%BCI: 1.70%, 3.91%) to 13.53% (95%BCI: 8.82%, 20.93%). High dementia prevalence was concentrated in North China, with a prominent high–high cluster, while provinces of low prevalence were concentrated on East and South China, characterized by a low–low cluster. Ordered by the median estimation of prevalence, the top 10% of provinces, include Xinjiang, Jilin, and Beijing. Meanwhile, Fujian, Zhejiang, and Guangdong rank among the last. The association between dementia prevalence and drinking, smoking, social isolation, physical inactivity, hearing impairment, hypertension, and diabetes exhibits provincial variation. Interpretation: Our study identifies a geospatial disparity in dementia prevalence and risk factor effects across China’s provinces, with high–high and low–low clusters in some northern and southern provinces, respectively. The findings emphasize the need for targeted strategies, such as addressing hypertension and hearing impairment, in specific regions for more effective dementia prevention and treatment. Funding: National Science Foundation of China/the Economic and Social Research Council, UK Research and Innovation joint call: Understanding and Addressing Health and Social Challenges for Ageing in the UK and China. UK-China Health And Social Challenges Ageing Project (UKCHASCAP): present and future burden of dementia, and policy responses (grant number 72061137003, ES/T014377/1).

BackgroundHIV self-testing (HIVST) holds great promise for expanding HIV testing. Nonetheless, large-scale data on HIVST behavior are scant. Millions of HIVST kits are sold through e-commerce platforms each year. ObjectiveThis study aims to analyze the spatiotemporal distribution of the HIVST kit–purchasing population (HIVSTKPP) in China. MethodsDeidentified transaction data were retrieved from a leading e-commerce platform in China. A joinpoint regression model was used to examine annual trends of the HIVSTKPP rates by calculating average annual percentage change. Bayesian spatiotemporal analysis was performed to locate hot spots with HIVSTKPP rates. Spatial autocorrelation analysis and space-time cluster analysis were conducted to identify clusters of HIVSTKPP. High-high clusters of HIVSTKPP can be identified by spatial autocorrelation analysis, and high-high clusters indicate that a region and its surrounding region jointly had a higher-than-average HIVSTKPP rate. Spatial regression analysis was used to elucidate the association between the number of HIV testing facilities, urbanization ratio (the proportion of urban population in the total population), and gross domestic product per capita and the HIVSTKPP. ResultsBetween January 1, 2016, and December 31, 2019, a total of 2.18 million anonymous persons in China placed 4.15 million orders and purchased 4.51 million HIVST kits on the web. In each of these 4 years, the observed monthly size of the HIVSTKPP peaked in December, the month of World AIDS Day. HIVSTKPP rates per 100,000 population significantly increased from 20.62 in 2016 to 64.82 in 2019 (average annual percentage change=48.2%; P

Abstract Background The two-week illness prevalence rate is an important and comparable indicator of health service needs. High-spatial-resolution, age-specific risk mapping of this indicator can provide valuable information for health resource allocation. The age-prevalence relationships may be different among areas of the study region, but previous geostatistical models usually ignored the spatial-age interaction. Methods We took Guangdong province, the province with the largest population and economy in China, as a study case. We collected two-week illness data and other potential influencing predictors from the fifth National Health Services Survey in 2013 and other open-access databases. Bayesian geostatistical binary regression models were developed with spatial-age structured random effect, based on which, high-resolution, age-specific two-week illness prevalence rates, as well as number of people reporting two-week illness, were estimated. The equality of health resource distribution was further evaluated based on the two-week illness mapping results and the health supply data. Results The map across all age groups revealed that the highest risk was concentrated in the central (i.e., Pearl River Delta) and northern regions of the province. These areas had a two-week illness prevalence > 25.0%, compared with 10.0–20.0% in other areas. Age-specific maps revealed significant differences in prevalence between age groups, and the age-prevalence relationships also differed across locations. In most areas, the prevalence rates decrease from age 0 to age 20, and then increase gradually. Overall, the estimated age- and population-adjusted prevalence was 16.5% [95% Bayesian credible interval (BCI): 14.5–18.6%], and the estimated total number of people reporting illness within the two-week period was 17.5 million (95% BCI: 15.5–19.8 million) in Guangdong Province. The Lorenz curve and the Gini coefficient (resulted in 0.3526) showed a moderate level of inequality in health resource distribution. Conclusions We developed a Bayesian geostatistical modeling framework with spatial-age structured effect to produce age-specific, high-resolution maps of the two-week illness prevalence rate and the numbers of people reporting two-week illness in Guangdong province. The methodology developed in this study can be generalized to other global regions with available relevant survey data. The mapping results will support plans for health resource allocation.

Abstract Background Reproductive tract infections (RTIs) have become major but silent public health problems devastating women’s lives in Bangladesh. Accurately and precisely identifying high-risk areas of RTIs through high-resolution risk maps is meaningful for resource-limited settings. Methods We obtained data reported with RTI symptoms by women of childbearing age in the years 2007, 2011 and 2014 from Bangladesh Demographic and Health Survey. High-spatial Environmental, socio-economic and demographic layers were downloaded from different open-access data sources. We applied Bayesian spatial-temporal models to identify important influencing factors and to estimate the infection risk at 5 km spatial resolution across survey years in Bangladesh. Results We estimated that in Bangladesh, there were approximate 11.1% (95% Bayesian credible interval, BCI: 10.5–11.7%), 13.9% (95% BCI: 13.3–14.5%) and 13.4% (95% BCI: 12.8–14.0%) of women of childbearing age reported with RTI symptoms in 2007, 2011 and 2014, respectively. The risk of most areas shows an obvious increase from 2007 to 2011, then became stable between 2011 and 2014. High risk areas were identified in the southern coastal areas, the western Rajshahi Division, the middle of Khulna Division, and the southwestern Chittagong Division in 2014. The prevalence of Rajshahi and Nawabganj District were increasing during all the survey years. Conclusion The high-resolution risk maps of RTIs we produced can guide the control strategies targeted to priority areas cost-effectively. More than one eighth of women of childbearing age reported symptoms suggesting RTIs and the risk of RTIs varies in different geographical area, urging the government to pay more attention to the worrying situation of female RTIs in the country.

Background: The reproductive health addresses the reproductive processes, functions and system at all stages of life. Enhancing the level of global reproductive health is the goal of sustained attention and struggle by the international community. The social and economic development in Southeast Asia is lagging behind, and its female reproductive health is worrying, while the differences of female reproductive health among different regions are significant.Objective: To obtains the necessity and urgency of strengthening the reproductive health level of Southeast Asian countries, so as to provide the basis for the priorities and target to policy-makers and health administrators to improve reproductive health.Methods: Literature review were searched in PubMed, Web of Science databases, Google Scholar database, and WHO’s webpages. Maternal mortality ratio, contraceptive rates, unmet need for family planning, antenatal and postnatal care coverage, and sexually transmitted disease were the five key indicators and the influence factors for female reproductive health status in Southeast Asian countries.Results: The reproductive health of Southeast Asian women were still at a lower level overall and varied in different regions and conntries. Women’s education and attitude, accessibility of service, socioeconomic and cultural factors, etc. were the potential influencing factors.Conclusion: There is left quite large space for improvement to the reproductive health in Southeast Asian countries and efficient interventions can be achieved for the key and easier-improved risk factors such as education and in high-risk areas.