Background The vastly increasing number of reported HIV and AIDS cases in Luzhou, China, in recent years, coupled with the city’s unique geographical location at the intersection of 4 provinces, makes it particularly important to conduct a spatiotemporal analysis of HIV and AIDS cases. Objective The aim of this study is to understand the spatiotemporal distribution of HIV and the factors influencing this distribution in Luzhou, China, from 2011 to 2020. Methods Data on the incidence of HIV and AIDS in Luzhou from 2011 to 2020 were obtained from the AIDS Information Management System of the Luzhou Center for Disease Control and Prevention. ArcGIS was used to visualize the spatiotemporal distribution of HIV and AIDS cases. The Bayesian spatiotemporal model was used to investigate factors affecting the spatiotemporal distribution of HIV and AIDS, including the gross domestic product (GDP) per capita, urbanization rate, number of hospital beds, population density, and road mileage. Results The reported incidence of HIV and AIDS rose from 8.50 cases per 100,000 population in 2011 to 49.25 cases per 100,000 population in 2020—an increase of 578.87%. In the first 5 years, hotspots were concentrated in Jiangyang district, Longmatan district, and Luxian county. After 2016, Luzhou’s high HIV incidence areas gradually shifted eastward, with Hejiang county having the highest average prevalence rate (41.68 cases per 100,000 population) from 2011 to 2020, being 2.28 times higher than that in Gulin county (18.30 cases per 100,000), where cold spots were concentrated. The risk for the incidence of HIV and AIDS was associated with the urbanization rate, population density, and GDP per capita. For every 1% increase in the urbanization rate, the relative risk (RR) increases by 1.3%, while an increase of 100 people per square kilometer would increase the RR by 8.7%; for every 1000 Yuan (US $148.12) increase in GDP per capita, the RR decreases by 1.5%. Conclusions In Luzhou, current HIV and AIDS prevention and control efforts must be focused on the location of each district or county government; we suggest the region balance urban development and HIV and AIDS prevention. Moreover, more attention should be paid to economically disadvantaged areas.

Background: Recent data have shown divergent trends in gastric cancer (GC) incidence between China and Japan; however, the cause for has not been explored. Methods:We retrieved GC incidence data from 1990 to 2019 from the Global Burden of Disease study, stratified by sex for both countries. We analyzed annual average percentage change (AAPC) via a joinpoint regression model and estimated the effects of age, period, and cohort via the age-period-cohort model. Results:The age-standardized incidence rate trends for GC decreased in both countries and both sexes, but the reduction was more pronounced in Japan because the AAPC for Japanese males (AAPC = −2.65%; 95% CI, −2.98 to −2.32) was eight times greater than that of Chinese males (AAPC = −0.30%; 95% CI, −0.5 to −0.09).The age and cohort effects on the trend are similar in both countries: the risk of GC incidence increased with age among the Chinese and the Japanese but was lower among younger birth cohorts. The two countries showed contrasting trends over the study period; although the risk of GC rapidly decreased for Japanese males and females, it increased by twofold among Chinese males. Conclusions:The period effect is the main reason for the divergent trends in agestandardized incidence rate for GC in China and Japan. By comparing national cancer control programs in both countries, we concluded that countries with a high prevalence of GC, such as China, can learn from Japan's experience in controlling GC by actively conducting national population screening, which is expected to facilitate both prevention and treatment of GC. Lay summary:� More than one-half of all new gastric cancer (GC) worldwide occur in China and Japan, but the reasons for the different incidence trends have not been thoroughly analyzed.� Analysis using the age-period-cohort model confirmed that the cohort effect was the main reason for the decline in age-standardized incidence rate (ASIR) for GCThe first two authors contributed equally to this article.

Background With the increasing effectiveness of antiretroviral therapy and shifting demographics, the problem of older people with HIV or AIDS is increasingly grim in China, and neglecting infection among them may cause more serious social problems, exacerbate the difficulty of controlling HIV or AIDS transmission, and increase the risk of death. Objective We investigated the variations in the trends of Chinese mortality by age, period, and cohort, from 1990 to 2019, to reveal the relationship between age, period, cohort, and HIV burden, as well as providing guidance for resource allocation to prevent HIV-related deaths in vulnerable target populations. Methods We extracted the HIV or AIDS mortality data from the Global Burden of Disease. The joinpoint regression model was applied to detect changes in HIV or AIDS trends. The age-period-cohort model was used to explore the age, period, and cohort effects. Results The trends in age-standardized mortality rates in HIV or AIDS were increased in both genders, from 0.50 to 4.54/105 individuals for males, and from 0.19 to 1.43/105 individuals for females. Joinpoint regression model showed the average annual percentage change of age-standardized mortality rates was 7.0 for male and 6.4 for female individuals, showing an increasing trend. The age effect of male HIV or AIDS mortality showed a net increase of 0.59 (–0.21 to 0.38) from the ages 50-79 years. There is a gradual upward trend in the change in risk of death from HIV or AIDS for the period effect among the older population, lowest at ages 50-54 years (–0.80 for male and –0.78 for female individuals) and highest at ages 75-79 years (0.86 for male and 0.69 for female individuals). The variation of cohort effects was complex, but both genders had a nearly consistent tendency; people born in 1920-1929 had the lowest cohort effect, and those born in 1950-1954 had the highest values. Conclusions Our study showed a marked rise in HIV mortality for both genders in China from 1990 to 2019. Aging is an important issue in current HIV prevention and control. There is an urgent need to promote HIV testing and health education. Our findings will help predict future HIV or AIDS mortality changes and identify age-specific priority populations for intervention.

BACKGROUND The vastly increasing number of reported HIV and AIDS cases in Luzhou, China, in recent years, coupled with the city’s unique geographical location at the intersection of 4 provinces, makes it particularly important to conduct a spatiotemporal analysis of HIV and AIDS cases. OBJECTIVE The aim of this study is to understand the spatiotemporal distribution of HIV and the factors influencing this distribution in Luzhou, China, from 2011 to 2020. METHODS Data on the incidence of HIV and AIDS in Luzhou from 2011 to 2020 were obtained from the AIDS Information Management System of the Luzhou Center for Disease Control and Prevention. ArcGIS was used to visualize the spatiotemporal distribution of HIV and AIDS cases. The Bayesian spatiotemporal model was used to investigate factors affecting the spatiotemporal distribution of HIV and AIDS, including the gross domestic product (GDP) per capita, urbanization rate, number of hospital beds, population density, and road mileage. RESULTS The reported incidence of HIV and AIDS rose from 8.50 cases per 100,000 population in 2011 to 49.25 cases per 100,000 population in 2020—an increase of 578.87%. In the first 5 years, hotspots were concentrated in Jiangyang district, Longmatan district, and Luxian county. After 2016, Luzhou’s high HIV incidence areas gradually shifted eastward, with Hejiang county having the highest average prevalence rate (41.68 cases per 100,000 population) from 2011 to 2020, being 2.28 times higher than that in Gulin county (18.30 cases per 100,000), where cold spots were concentrated. The risk for the incidence of HIV and AIDS was associated with the urbanization rate, population density, and GDP per capita. For every 1% increase in the urbanization rate, the relative risk (RR) increases by 1.3%, while an increase of 100 people per square kilometer would increase the RR by 8.7%; for every 1000 Yuan (US $148.12) increase in GDP per capita, the RR decreases by 1.5%. CONCLUSIONS In Luzhou, current HIV and AIDS prevention and control efforts must be focused on the location of each district or county government; we suggest the region balance urban development and HIV and AIDS prevention. Moreover, more attention should be paid to economically disadvantaged areas.