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ObjectivesTo analyze the spatial and temporal clustering characteristics and related influencing factors of late diagnosis of HIV/AIDS in Lanzhou， to identify its high-risk areas and time trends in Lanzhou， and to provide a theoretical basis for developing targeted HIV/AIDS prevention and control strategies in Lanzhou. MethodsThe subjects of this study were adult HIV/AIDS cases reported in Lanzhou City between 2011 and 2018. Data used in the study were sourced from the Lanzhou Center for Disease Control and Prevention and the Lanzhou Statistical Yearbook. To analyze the spatial distribution characteristics and influencing factors of the relative risk （RR） of late HIV/AIDS diagnosis， Bayes spatial-temporal model was used. ResultsA total of 1984 new HIV/AIDS cases were reported in Lanzhou from 2011 to 2018， with an mean age of 37.51 years and predominantly male （91.8%）. The number of late diagnosis cases was 982， with an mean age of 39.67 years and a predominance of males （91.8%）. Late diagnosis was more common in older individuals and women with HIV/AIDS. Chengguan District （51.1%）， Anning District （50.3%） and Yuzhong County （51.9%） had an above-average proportion of late diagnosis of HIV/AIDS. The proportion of late diagnosis cases in Lanzhou showed a fluctuating upward trend from 2011 to 2018. The results of Bayes spatial-temporal model showed that the risk of late HIV/AIDS diagnosis in Lanzhou had fluctuated from 2011 to 2015， and then increased rapidly after 2015 ［RR （95% credibility interval， 95%CI） increased from 1.01 （0.84， 1.23） to 1.11 （0.77， 1.97）］； the trends of risk of late diagnosis in Honggu district and three counties were similar to the overall trend in Lanzhou city， while the risk of late diagnosis in Chengguan District and Qilihe District showed a decreasing trend. The regions with the RR for late diagnosis greater than 1 included Yongdeng County （RR=1.07， 95% CI： 0.55， 1.96）， Xigu District （RR=1.04， 95% CI： 0.67， 1.49）， Chengguan District （RR=2.41， 95% CI： 0.85， 6.16）， and Qilihe District （RR=2.03， 95% CI： 1.10， 3.27）. Besides， the heatmap analysis showed that Chengguan District and Qilihe District were the hot spots. The influencing factors analysis showed that the higher GDP per capita （RR=0.65， 95% CI： 0.35， 0.90） and the larger proportion of males with HIV/AIDS cases （RR=0.53， 95% CI： 0.19， 0.92） could lead to the lower the relative risk of late HIV/AIDS diagnosis. However， the higher the population density （RR=1.35， 95% CI： 1.01， 1.81） caused the higher the risk of late diagnosis. ConclusionOur study shows the risk of late diagnosis of HIV/AIDS in Lanzhou was on the rise， and there are significant regional differences. GDP per capita， the proportion of males in HIV/AIDS cases and population density are influencing factors in the late diagnosis of HIV/AIDS. Therefore， for regions with a high risk of late diagnosis or related risk factors， targeted HIV screening and prevention services should be given priority in order to reduce the proportion and risk of late diagnosis of HIV/AIDS.
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With the development of computer technology and the abundance of spatio-temporal data, Bayesian spatio-temporal model (BSTM) has been developed rapidly, and wildly used by academics to investigate the spatial epidemiological feature of infectious diseases. Hydatid disease is a global natural focus disease that seriously endangers human health. Its epidemic process is complex and affected by many factors. BSTM provides a new method for study of hydatid disease. By modeling, we can not only analyze the influencing factors of hydatid disease, but also can predict the epidemic trend and make the disease distribution map, which is of great significance to public health decisionmaking. Based on a comprehensive review of the literatures, this paper expounds the principles, types and application status of BSTM in hydatid disease.
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Background Stroke has become a main cause of death in China. With global warming, the studies on temperature and stroke have attracted much attention. Objective To analyze he relationships between heatwave and the years of life lost (YLL) by different subtypes of stroke by controlling temporal and spatial effects with Bayesian spatio-temporal model, and to study the modifiers of the health effect of heatwave. Methods The daily information of stroke deaths, meteorological data, and air pollutant data in 40 districts and counties of Guangdong Province were collected during the warm seasons (from May to October) in the years from 2014 to 2017. The individual YLL was first calculated by matching age and gender according to the life table, and then the daily YLL rate (person-years/100 000 people) was obtained by summarizing the daily YLL and correcting it with the population of each district or county. Bayesian spatio-temporal model was used to fit a proposed exposure-response relationship between heatwave and the YLL rates of different subtypes of stroke. Finally, stratified analyses were conducted by age (<65 years, ≥65 years), gender (male, female), and region (Pearl River Delta and non-Pearl River Delta regions) to identify the major modifiers for the association between heatwave and stroke mortality. Results During the warm seasons from 2014 to 2017, a total of 23 heatwave events occurred in the 40 districts or counties of Guangdong Province, cumulatively lasting for 145 d. A total of 30 852 stroke deaths were recorded in the same time periods. The average daily YLL rate of total stroke was (2.39±3.63) person-years/100 000 people, and those for hemorrhagic stroke and ischemic stroke were (1.54±2.99) person-years/100 000 people and (0.84±1.85) person-years/100 000 people, respectively. Heatwave was associated with increased YLL rate of stroke in residents, and it had a greater impact on ischemic stroke with a lag effect. The largest cumulative effect of heatwave was at lag 0-1 day, which was associated with an increased YLL rate of total stroke and ischemic stroke by 0.17 (95%CI: 0.03-0.29) person-years/100 000 people and 0.13 (95%CI: 0.06-0.20) person-years/100 000 people, respectively. The results of stratified analyses showed that heatwave had a larger effect on ischemic stroke in residents of aged 65 years or older, male, and non-Pearl River Delta regions, and the rates of YLL increased by 1.11 (95%CI: 0.58-1.55), 0.13 (95%CI: 0.03-0.23), and 0.20 (95%CI: 0.07-0.32) person-years/100 000 people, respectively; Heatwave only had an effect on hemorrhagic stroke in residents aged 65 years or older with an increased YLL rate of 0.79 (95%CI: 0.26-1.31) person-years/100 000 people. Conclusion Heatwave could elevate the level of years of life lost associated with stroke in Guangdong residents, with greater impacts on ischemic stroke of the aged, men, and residents in non-Pearl River Delta regions, and on hemorrhagic stroke in the elderly.
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Objective To analyze the pilot results of both temporal and temporal-spatial models in outbreaks detection in China Infectious Diseases Automated-alert and Response System (CIDARS)to further improve the system. Methods The amount of signal, sensitivity, false alarm rate and time to detection regarding these two models of CIDARS, were analyzed from December 6,2009 to December 5,2010 in 221 pilot counties of 20 provinces. Results The sensitivity of these two models was equal(both 98.15%). However, when comparing to the temporal model, the temporal-spatial model had a 59.86% reduction on the signals(15 702)while the false alarm rate of the temporal-spatial model(0.73%)was lower than the temporal model(1.79%), and the time to detection of the temporal-spatial model(0 day)was also 1 day shorter than the temporal model.Conclusion Comparing to the temporal model, the temporal-spatial model of CIDARS seemed to be better performed on outbreak detection.