Spatial analysis of county-based gonorrhoea incidence in mainland China, from 2004 to 2009

The Effects of Online Health Information-Seeking Behavior on Sexually Transmitted Disease in China: Infodemiology Study of the Internet Search Queries

BACKGROUND

Sexually transmitted diseases (STDs) are a serious issue worldwide. With the popularity of the internet, online health information-seeking behavior (OHISB) has been widely adopted to improve health and prevent disease.

OBJECTIVE

This study aimed to investigate the short-term and long-term effects of different types of OHISBs on STDs, including syphilis, gonorrhea, and AIDS due to HIV, based on the Baidu index.

METHODS

Multisource big data were collected, including case numbers of STDs, search queries based on the Baidu index, provincial total population, male-female ratio, the proportion of the population older than 65 years, gross regional domestic product (GRDP), and health institution number data in 2011-2018 in mainland China. We categorized OHISBs into 4 types: concept, symptoms, treatment, and prevention. Before and after controlling for socioeconomic and medical conditions, we applied multiple linear regression to analyze associations between the Baidu search index (BSI) and Baidu search rate (BSR) and STD case numbers. In addition, we compared the effects of 4 types of OHISBs and performed time lag cross-correlation analyses to investigate the long-term effect of OHISB.

RESULTS

The distributions of both STD case numbers and OHISBs presented variability. For case number, syphilis, and gonorrhea, cases were mainly distributed in southeastern and northwestern areas of China, while HIV/AIDS cases were mostly distributed in southwestern areas. For the search query, the eastern region had the highest BSI and BSR, while the western region had the lowest ones. For 4 types of OHISB for 3 diseases, the BSI was positively related to the case number, while the BSR was significantly negatively related to the case number (P<.05). Different categories of OHISB have different effects on STD case numbers. Searches for prevention tended to have a larger impact, while searches for treatment tended to have a smaller impact. Besides, due to the time lag effect, those impacts would increase over time.

CONCLUSIONS

Our study validated the significant associations between 4 types of OHISBs and STD case numbers, and the impact of OHISBs on STDs became stronger over time. It may provide insights into how to use internet big data to better achieve disease surveillance and prevention goals.

Trends in the Epidemiology of Sexually Transmitted Disease, Acquired Immune Deficiency Syndrome (AIDS), Gonorrhea, and Syphilis, in the 31 Provinces of Mainland China

BACKGROUND This study aimed to investigate trends in the epidemiology of the leading sexually transmitted diseases (STDs), acquired immune deficiency syndrome (AIDS), gonorrhea, and syphilis, in the 31 provinces of mainland China. MATERIAL AND METHODS This retrospective study analyzed the incidence data of STDs from official reports in China between 2004 and 2016. The grey model first order one variable, or GM (1,1), time series forecasting model for epidemiological studies predicted the incidence of STDs based on the annual incidence reports from 31 Chinese mainland provinces. Hierarchical cluster analysis was used to group the prevalence of STDs within each province. RESULTS The prediction accuracy of the GM (1,1) model was high, based on data during the 13 years between 2004 and 2016. The model predicted that the incidence rates of AIDS and syphilis would continue to increase over the next two years. Cluster analysis showed that 31 provinces could be classified into four clusters according to similarities in the incidence of STDs. Group A (Sinkiang Province) had the highest reported prevalence of syphilis. Group B included provinces with a higher incidence of gonorrhea, mainly in the southeast coast of China. Group C consisted of southwest provinces with a higher incidence of AIDS. CONCLUSIONS The GM (1,1) model was predictive for the incidence of STDs in 31 provinces in China. The predicted incidence rates of AIDS and syphilis showed an upward trend. Regional distribution of the major STDs highlights the need for targeted prevention and control programs.

Spatiotemporal distribution and determinants of gonorrhea infections in mainland China: a panel data analysis

OBJECTIVES

Gonorrhea remains a major public health concern worldwide. This study aims to explore the spatiotemporal distribution and sociodemographic determinants of gonorrhea rates during 2004-2014 in mainland China.

STUDY DESIGN

Space-time scan statistics and spatial panel regression model.

METHODS

The gonorrhea infection data and sociodemographic data during 2004-2014 at the provincial level in mainland China were extracted from the China Public Health Science Data Center and China Statistical Yearbooks, respectively. The space-time scan statistics were used to identify the high-risk clusters of gonorrhea, and the spatial panel regression model was adopted to examine the sociodemographic determinants.

RESULTS

One most likely and five secondary high-risk clusters of gonorrhea rates were identified, which were mainly located in southern and eastern China. The regions with higher GDP per capita, larger floating population, less access to healthcare, higher male-female ratio, and higher divorce rate were more likely to become high-risk areas of gonorrhea.

CONCLUSIONS

Gonorrhea rates were distributed unevenly through space and time and affected by various sociodemographic variables. The space-time scan statistics and spatial panel regression are viable tools for identifying clusters and examining determinants of gonorrhea rates. The findings provide valuable implications for developing targeted prevention and control programs in public health practice.

Space-time clustering characteristics of tuberculosis in China, 2005-2011

OBJECTIVES

China is one of the 22 tuberculosis (TB) high-burden countries in the world. As TB is a major public health problem in China, spatial analysis could be applied to detect geographic distribution of TB clusters for targeted intervention on TB epidemics.

METHODS

Spatial analysis was applied for detecting TB clusters on county-based TB notification data in the national notifiable infectious disease case reporting surveillance system from 2005 to 2011. Two indicators of TB epidemic were used including new sputum smear-positive (SS+) notification rate and total TB notification rate. Global Moran's I by ArcGIS was used to assess whether TB clustering and its trend were significant. SaTScan software that used the retrospective space-time analysis and Possion probability model was utilized to identify geographic areas and time period of potential clusters with notification rates on county-level from 2005 to 2011.

RESULTS

Two indicators of TB notification had presented significant spatial autocorrelation globally each year (p<0.01). Global Moran's I of total TB notification rate had positive trend as time went by (t=6.87, p<0.01). The most likely clusters of two indicators had similar spatial distribution and size in the south-central regions of China from 2006 to 2008, and the secondary clusters in two regions: northeastern China and western China. Besides, the secondary clusters of total TB notification rate had two more large clustering centers in Inner Mongolia, Gansu and Qinghai provinces and several smaller clusters in Shanxi, Henan, Hebei and Jiangsu provinces.

CONCLUSION

The total TB notification cases clustered significantly in some special areas each year and the clusters trended to aggregate with time. The most-likely and secondary clusters that overlapped among two TB indicators had higher TB burden and risks of TB transmission. These were the focused geographic areas where TB control efforts should be prioritized.