Geographical Detector-based influence factors analysis for Echinococcosis prevalence in Tibet, China

Exploring the influencing factors of scrub typhus in Gannan region, China, based on spatial regression modelling and geographical detector

Scrub typhus is a significant public health issue with a wide distribution and is influenced by various determinants. However, in order to effectively eradicate scrub typhus, it is crucial to identify the specific factors that contribute to its incidence at a detailed level. Therefore, the objective of our study is to identify these influencing factors, examine the spatial variations in incidence, and analyze the interplay of two factors on scrub typhus incidence, so as to provide valuable experience for the prevention and treatment of scrub typhus in Gannan and to alleviate the economic burden of the local population.This study employed spatial autocorrelation analyses to examine the dependent variable and ordinary least squares model residuals. Additionally, spatial regression modelling and geographical detector were used to analyze the factors influencing the annual mean 14-year incidence of scrub typhus in the streets/townships of Gannan region from 2008 to 2021. The results of spatial1 autocorrelation analyses indicated the presence of spatial correlation. Among the global spatial regression models, the spatial lag model was found to be the best fitting model (log likelihood ratio = -319.3029, AIC = 666.6059). The results from the SLM analysis indicated that DEM, mean temperature, and mean wind speed were the primary factors influencing the occurrence of scrub typhus. For the local spatial regression models, the multiscale geographically weighted regression was determined to be the best fitting model (adjusted R2 = 0.443, AICc = 726.489). Further analysis using the MGWR model revealed that DEM had a greater impact in Xinfeng and Longnan, while the southern region was found to be more susceptible to scrub typhus due to mean wind speed. The geographical detector results revealed that the incidence of scrub typhus was primarily influenced by annual average normalized difference vegetation index. Additionally, the interaction between GDP and the percentage of grassland area had a significant impact on the incidence of scrub typhus (q = 0.357). This study illustrated the individual and interactive effects of natural environmental factors and socio-economic factors on the incidence of scrub typhus; and elucidated the specific factors affecting the incidence of scrub typhus in various streets/townships. The findings of this study can be used to develop effective interventions for the prevention and control of scrub typhus.

Pictorial review of hepatic echinococcosis: Ultrasound imaging and differential diagnosis

Echinococcosis is a zoonotic disease caused by parasites belonging to the genus Echinococcus that primarily affect the liver. The western plateau and pastoral areas of China are high-risk regions for hepatic cystic echinococcosis and hepatic alveolar echinococcosis (HAE). The high late mortality rate associated with HAE underscores the critical need for early diagnosis to improve cure rates and mitigate the disease burden in endemic areas. Currently, the World Health Organization recommends ultrasonography as the preferred initial screening method for hepatic echinococcosis. However, distinguishing between specific types of lesions, such as those of hepatic cystic echinococcosis and HAE, and other focal liver lesions is challenging. To address this issue, contrast-enhanced ultrasound is recommended as a tool to differentiate solid and cysto-solid hepatic echinococcosis from other focal liver lesions, significantly enhancing diagnostic accuracy. In this comprehensive review, we discuss the progression of hepatic echinococcosis and detail the imaging features of various types of echinococcosis using conventional, contrast-enhanced, and intraoperative ultrasound techniques. Our objective is to provide robust imaging evidence and guidance for early diagnosis, clinical decision making, and postoperative follow-up in regions with high disease prevalence.

Rapid Discriminative Identification of the Two Predominant Echinococcus Species from Canine Fecal Samples in the Tibetan Region of China by Loop-Mediated Isothermal Amplification-Lateral Flow Dipstick Assay

Echinococcosis poses a significant concern in the fields of public health and veterinary care as it can be transmitted between animals and humans. The primary endemic subtypes are cystic echinococcosis (CE) and alveolar echinococcosis (AE), which result from infestation by Echinococcus granulosus and Echinococcus multilocularis, respectively. A prominent epidemic of echinococcosis greatly affects the Tibet Autonomous Region (TAR) in China. A new technique called the loop-mediated isothermal amplification-lateral flow dipstick (LAMP-LFD) test is introduced in this research to differentiate between E. granulosus and E. multilocularis using their repetitive genetic sequences. The test is characterized by its portable nature, simple operation, quick result production, high sensitivity, and low susceptibility to aerosol contamination. The LAMP-LFD method demonstrated an exceptional minimal detection limit, reaching levels as low as approximately 1 fg/μL (femtogram per microliter) of genomic DNA. The assay's specificity was assessed, and no cross-reactivity was seen. A total of 982 dog fecal samples were collected from 54 counties in the TAR region between July 2021 and June 2022. The established method underwent validation using a commercially available ELISA kit. The agreement rate between the LAMP-LFD and ELISA methods was 97.25%, with a sensitivity of 96.05% and a specificity of 97.35%. The assay described in this study improves specificity by using a double-labeled probe, and it reduces the risk of false-positive results caused by aerosol contamination through the use of a sealed device. This makes it a suitable choice for quickly and accurately identifying the two main types of Echinococcus in field settings.

Developing a geographical-meteorological indicator system and evaluating prediction models for alveolar echinococcosis in China

BACKGROUND

Geographical and meteorological factors have been reported to influence the prevalence of echinococcosis, but there's a lack of indicator system and model.

OBJECTIVE

To provide further insight into the impact of geographical and meteorological factors on AE prevalence and establish a theoretical basis for prevention and control.

METHODS

Principal component and regression analysis were used to screen and establish a three-level indicator system. Relative weights were examined to determine the impact of each indicator, and five mathematical models were compared to identify the best predictive model for AE epidemic levels.

RESULTS

By analyzing the data downloaded from the China Meteorological Data Service Center and Geospatial Data Cloud, we established the KCBIS, including 50 basic indicators which could be directly obtained online, 15 characteristic indicators which were linear combination of the basic indicators and showed a linear relationship with AE epidemic, and 8 key indicators which were characteristic indicators with a clearer relationships and fewer mixed effects. The relative weight analysis revealed that monthly precipitation, monthly cold days, the difference between negative and positive temperature anomalies, basic air temperature conditions, altitude, the difference between positive and negative atmospheric pressure anomalies, monthy extremely hot days, and monthly fresh breeze days were correlated with the natural logarithm of AE prevalence, with sequential decreases in their relative weights. The multinomial logistic regression model was the best predictor at epidemic levels 1, 3, 5, and 6, whereas the CART model was the best predictor at epidemic levels 2, 4, and 5.

Prevalence and spatial distribution characteristics of human echinococcosis: A county-level modeling study in southern Xinjiang, China

Objectives

Human echinococcosis remains an important public health problem. The aim of this study was to analyze the prevalence and spatial distribution characteristics of human echinococcosis cases in southern Xinjiang, China from 2005 to 2021.

Methods

Human echinococcosis cases were collected from the National Infectious Disease Reporting System. Joinpoint regression analysis was performed to explore the trends. Spatial autocorrelation, hot spot analysis, as well as spatial-temporal clustering analysis were conducted to confirm the distribution and risk factors.

Results

A total of 4580 cases were reported in southern Xinjiang during 2005-2021, with a mean annual incidence of 2.56/100,000. Echinococcosis incidence showed an increasing trend from 2005 to 2017 (APC = 17.939, 95%CI: 13.985 to 22.029) and a decreasing trend from 2017 to 2021 (APC = -18.769, 95%CI: 28.157 to -8.154). Echinococcosis cases had a positive spatial autocorrelation in 2005-2021 (Moran's I = 0.19, P < 0.05). The disease hotspots were located in the east and west in these areas, then returned to the east clusters, including Hejing, Heshuo, Wuqia, Atushi, Aheqi, and Yanqi Hui Autonomous County. Meanwhile, spatial-temporal analysis identified the first cluster comprised of five counties (cities): Yanqi Hui Autonomous County, Korla City, Bohu County, Hejing County, and Heshuo County. And secondary clusters 1-3 are predominantly in Wushi County, Aheqi County, Keping County, Atushi City, Wuqia County and Cele County.

Conclusions

Our findings suggest that echinococcosis is still an important zoonotic parasitic disease in southern Xinjiang, yet it showed a certain degree of spatial clustering. It is crucial to implement comprehensive prevention and control measures to effectively combat the epidemic of echinococcosis.

Changes in the global epidemiological characteristics of cystic echinococcosis over the past 30 years and projections for the next decade: Findings from the Global Burden of Disease Study 2019

Background

Despite ongoing changes in the global epidemiology of cystic echinococcosis (CE), there is a lack of research conducted to date.

Methods

We extracted data on incidence and disability-adjusted life years for 204 countries and territories from 1990 to 2019 to evaluate the epidemiological characteristics and burden of CE through the Global Burden of Diseases, Injuries, and Risk Factors Study 2019. We used locally weighted linear regression to analyse the primary driving factors of the prevalence of CE at the national and regional levels and utilised a Bayesian Age-Period-Cohort model to forecast the global incidence of CE in the next decade.

Results

Globally, the incidence of CE remained constantly high from 1990 (2.65 per 100 000 population) to 2019 (2.60 per 100 000 population), resulting in an estimated 207 368 new cases in 2019. We observed substantial variations in the disease burden regarding its spatiotemporal distribution, population demographics, and Socio-Demographic Index levels. According to established models, factors such as health care capacity, livestock husbandry, agricultural activities, rural populations, and education levels are likely to play significant roles in determining the prevalence of CE across different countries. By 2030, the worldwide number of CE cases could reach as high as 235 628, representing an increase of 13.63% compared to 2019.

Conclusions

Over the past three decades, the global burden of CE has persistently remained high, especially in Central Asia, as well as North Africa and the Middle East. Efforts should focus on more effective prevention and control measures in these key regions and should specifically target vulnerable populations to prevent the escalation of epidemics.

Epidemiological characteristics and risk factors for cystic and alveolar echinococcosis in China: an analysis of a national population-based field survey

BACKGROUND

Human cystic and alveolar echinococcosis are neglected tropical diseases that WHO has prioritized for control in recent years. Both diseases impose substantial burdens on public health and the socio-economy in China. In this study, which is based on the national echinococcosis survey from 2012 to 2016, we aim to describe the spatial prevalence and demographic characteristics of cystic and alveolar echinococcosis infections in humans and assess the impact of environmental, biological and social factors on both types of the disease.

METHODS

We computed the sex-, age group-, occupation- and education level-specific prevalences of cystic and alveolar echinococcosis at national and sub-national levels. We mapped the geographical distribution of echinococcosis prevalence at the province, city and county levels. Finally, by analyzing the county-level echinococcosis cases combined with a range of associated environmental, biological and social factors, we identified and quantified the potential risk factors for echinococcosis using a generalized linear model.

RESULTS

A total of 1,150,723 residents were selected and included in the national echinococcosis survey between 2012 and 2016, of whom 4161 and 1055 tested positive for cystic and alveolar echinococcosis, respectively. Female gender, older age, occupation at herdsman, occupation as religious worker and illiteracy were identified as risk factors for both types of echinococcosis. The prevalence of echinococcosis was found to vary geographically, with areas of high endemicity observed in the Tibetan Plateau region. Cystic echinococcosis prevalence was positively correlated with cattle density, cattle prevalence, dog density, dog prevalence, number of livestock slaughtered, elevation and grass area, and negatively associated with temperature and gross domestic product (GDP). Alveolar echinococcosis prevalence was positively correlated with precipitation, level of awareness, elevation, rodent density and rodent prevalence, and negatively correlated with forest area, temperature and GDP. Our results also implied that drinking water sources are significantly associated with both diseases.

CONCLUSIONS

The results of this study provide a comprehensive understanding of geographical patterns, demographic characteristics and risk factors of cystic and alveolar echinococcosis in China. This important information will contribute towards developing targeted prevention measures and controlling diseases from the public health perspective.

Update on the genetic diversity and population structure of Echinococcus granulosus in Gansu Province, Tibet Autonomous Region, and Xinjiang Uygur Autonomous Region, Western China, inferred from mitochondrial cox1, nad1, and nad5 sequences

The identification of additional Echinococcus granulosus sensu lato (s.l.) complex species/genotypes in recent years raises the possibility that there might be more variation among this species in China than is currently understood. The aim of this study was to explore intra- and inter-species variation and population structure of Echinococcus species isolated from sheep in three areas of Western China. Of the isolates, 317, 322, and 326 were successfully amplified and sequenced for cox1, nad1, and nad5 genes, respectively. BLAST analysis revealed that the majority of the isolates were E. granulosus s.s., and using the cox1, nad1, and nad5 genes, respectively, 17, 14, and 11 isolates corresponded to Elodea canadensis (genotype G6/G7). In the three study areas, G1 genotypes were the most prevalent. There were 233 mutation sites along with 129 parsimony informative sites. A transition/transversion ratio of 7.5, 8, and 3.25, respectively, for cox1, nad1, and nad5 genes was obtained. Every mitochondrial gene had intraspecific variations, which were represented in a star-like network with a major haplotype with observable mutations from other distant and minor haplotypes. The Tajima's D value was significantly negative in all populations, indicating a substantial divergence from neutrality and supporting the demographic expansion of E. granulosus s.s. in the study areas. The phylogeny inferred by the maximum likelihood (ML) method using nucleotide sequences of cox1-nad1-nad5 further confirmed their identity. The nodes assigned to the G1, G3, and G6 clades as well as the reference sequences utilized had maximal posterior probability values (1.00). In conclusion, our study confirms the existence of a significant major haplotype of E. granulosus s.s. where G1 is the predominant genotype causing of CE in both livestock and humans in China.

Specific urban units identified in tuberculosis epidemic using a geographical detector in Guangzhou, China

BACKGROUND

A remarkable drop in tuberculosis (TB) incidence has been achieved in China, although in 2019 it was still considered the second most communicable disease. However, TB's spatial features and risk factors in urban areas remain poorly understood. This study aims to identify the spatial differentiations and potential influencing factors of TB in highly urbanized regions on a fine scale.

METHODS

This study included 18 socioeconomic and environmental variables in the four central districts of Guangzhou, China. TB case data obtained from the Guangzhou Institute of Tuberculosis Control and Prevention. Before using Pearson correlation and a geographical detector (GD) to identify potential influencing factors, we conducted a global spatial autocorrelation analysis to select an appropriate spatial scales.

RESULTS

Owing to its strong spatial autocorrelation (Moran's I = 0.33, Z = 4.71), the 2 km × 2 km grid was selected as the spatial scale. At this level, TB incidence was closely associated with most socioeconomic variables (0.31 < r < 0.76, P < 0.01). Of five environmental factors, only the concentration of fine particulate matter displayed significant correlation (r = 0.21, P < 0.05). Similarly, in terms of q values derived from the GD, socioeconomic variables had stronger explanatory abilities (0.08 < q < 0.57) for the spatial differentiation of the 2017 incidence of TB than environmental variables (0.06 < q < 0.27). Moreover, a much larger proportion (0.16 < q < 0.89) of the spatial differentiation was interpreted by pairwise interactions, especially those (0.60 < q < 0.89) related to the 2016 incidence of TB, officially appointed medical institutions, bus stops, and road density.

CONCLUSIONS

The spatial heterogeneity of the 2017 incidence of TB in the study area was considerably influenced by several socioeconomic and environmental factors and their pairwise interactions on a fine scale. We suggest that more attention should be paid to the units with pairwise interacting factors in Guangzhou. Our study provides helpful clues for local authorities implementing more effective intervention measures to reduce TB incidence in China's municipal areas, which are featured by both a high degree of urbanization and a high incidence of TB.