Geographical Environment Factors and Risk Mapping of Human Cystic Echinococcosis in Western China

A regressive analysis of the main environmental risk factors of human echinococcosis in 370 counties in China

BACKGROUND

Echinococcosis is a natural focal, highly prevalent disease in China. Factors influencing the spread of echinococcosis are not only related to personal exposure but also closely related to the environment itself. The purpose of this study was to explore the influence of environmental factors on the prevalence of human echinococcosis and to provide a reference for prevention and control of echinococcosis in the future.

METHODS

Data were collected from 370 endemic counties in China in 2018. By downloading Modis, DEM and other remote-sensing images in 2018. Data on environmental factors, i.e., elevation, land surface temperature (LST) and normalized difference vegetation index (NDVI) were collected. Rank correlation analysis was conducted between each environmental factor and the prevalence of echinococcosis at the county level. Negative binomial regression was used to analyze the impact of environmental factors on the prevalence of human echinococcosis at the county level.

RESULTS

According to rank correlation analysis, the prevalence of human echinococcosis in each county was positively correlated with elevation, negatively correlated with LST, and negatively correlated with NDVI in May, June and July. Negative binomial regression showed that the prevalence of human echinococcosis was negatively correlated with annual LST and summer NDVI, and positively correlated with average elevation and dog infection rate. The prevalence of human cystic echinococcosis was inversely correlated with the annual average LST, and positively correlated with both the average elevation and the prevalence rate of domestic animals. The prevalence of human alveolar echinococcosis was positively correlated with both NDVI in autumn and average elevation, and negatively correlated with NDVI in winter.

CONCLUSION

The prevalence of echinococcosis in the population is affected by environmental factors. Environmental risk assessment and prediction can be conducted in order to rationally allocate health resources and improve both prevention and control efficiency of echinococcosis.

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.

A 35-Year-Old Man With Fever and Pulmonary Cavity

CASE PRESENTATION

A 35-year-old man was hospitalized with fever, chest pain, and cough of 2 weeks' duration. These symptoms persisted despite 4 days of antibiotic treatment with IV ceftriaxone sodium 2 g/d. The patient was a nonsmoker with an unremarkable medical history who worked as a herdsman and lived in the Shigate region of Tibet, China.

How climate, landscape, and economic changes increase the exposure of Echinococcus Spp

BACKGROUND

Echinococcosis is a global enzootic disease influenced by different biological and environmental factors and causes a heavy financial burden on sick families and governments. Currently, government subsidies for the treatment of patients with echinococcosis are only a fixed number despite patients' finical income or cost of treatment, and health authorities are demanded to supply an annual summary of only endemic data. The risk to people in urban areas or non-endemic is increasing with climate, landscape, and lifestyle changes.

METHODS

We conducted retrospective descriptive research on inpatients with human echinococcosis (HE) in Lanzhou hospitals and analyzed the healthcare expenditure on inpatient treatment and examined the financial inequalities relating to different levels of gross domestic product. The livestock losses were also estimated by infection ratio. The occurrence records of Echinococcus spp. composed of hospitalized patients and dogs infected in the Gansu province were collected for Ecological niche modeling (ENM) to estimate the current suitable spatial distribution for the parasite in Gansu province. Then, we imported the resulting current niche model into future global Shared Socioeconomic Pathways scenarios for estimation of future suitable habitat areas.

RESULTS

Between 2000 to 2020, 625 hospitalized HE patients (51% men and 49% women) were identified, and 48.32 ± 15.62 years old. The average cost of hospitalization expenses per case of HE in Gansu Province was ￥24,370.2 with an increasing trend during the study period and was negative with different counties' corresponding gross domestic product (GDP). The trend of livestock losses was similar to the average cost of hospitalization expenses from 2015 to 2017. The three factors with the strongest correlation to echinococcosis infection probability were (1) global land cover (GLC, 56.6%), (2) annual precipitation (Bio12, 21.2%), and (3) mean temperature of the Wettest Quarter (Bio12, 8.5% of variations). We obtained a robust model that provides detail on the distribution of suitable areas for Echinococcus spp. including areas that have not been reported for the parasite. An increasing tendency was observed in the highly suitable areas of Echinococcus spp. indicating that environmental changes would affect the distributions.

CONCLUSION

This study may help in the development of policies for at-risk populations in geographically defined areas and monitor improvements in HE control strategies by allowing targeted allocation of resources, including spatial analyses of expenditure and the identification of non-endemic areas or risk for these parasites, and a better comprehension of the role of the environment in clarifying the transmission dynamics of Echinococcus spp. Raising healthcare workers' and travelers' disease awareness and preventive health habits is an urgent agenda. Due to unpredictable future land cover types, prediction of the future with only climatic variables involved needs to be treated cautiously.

Risk Factors Associated With Echinococcosis in the General Chinese Population: A Meta-Analysis and Systematic Review

Background

Echinococcosis is a severe zoonotic disease that imposes a substantial burden on human life. This meta-analysis aimed to summarize available data on the prevalence of human echinococcosis and identify the key risk factors for echinococcosis in the Chinese general population.

Methods

Relevant studies were comprehensively searched in the PubMed, EMBASE, Web of Science, Cochrane, Chinese National Knowledge Infrastructure (CNKI), Chongqing VIP Information (VIP), Wanfang and SinoMed databases until August 22, 2020. A random-effects model was used to estimate the pooled odds ratio (OR) and 95% confidence interval (95% CI). The I² and Q statistics were calculated to evaluate the heterogeneity, and potential sources of heterogeneity were identified using sensitivity analysis and subgroup analysis. Publication bias was estimated by funnel plots and Egger's test.

Results

A total of 1026 studies were identified through the database search, of which 26 were eligible for this meta-analysis. The pooled prevalence of AE and CE were 2.88% and 5.66%, respectively. Ethnicity (OR = 2.93, 95% CI: 1.81–4.75; I² = 0), herdsman occupation (OR = 2.66, 95% CI: 2.25–3.14; I² = 8.0%), not washing hands before meals (OR = 2.40, 95% CI: 1.34–4.28; I² = 82.8%) and being female (OR = 1.45, 95% CI: 1.26–1.66; I² = 33.9%) were risk factors for AE. The top five risk factors for CE were ethnicity (OR = 3.18, 95% CI: 1.55–6.52; I² = 79.2%), nomadism (OR = 2.71, 95% CI: 1.65–4.47; I² = 55.8%), drinking nonboiled water (OR = 2.47, 95% CI: 1.36–4.47; I² = 85.7), feeding viscera to dogs (OR = 2.35, 95% CI: 1.89–2.91; I² = 21.5%), and herdsman occupation (OR = 2.19, 95% CI: 1.67–2.86; I² = 85.1%).

Conclusions

This study generalized articles that have contributed to our current understanding of the epidemic of human echinococcosis (AE and CE) in China over the years. The results support that the ethnicity and dog-related factors are major risk factors for both CE and AE. The identification of echinococcosis risk factors may aid researchers and policymakers in improving surveillance and preventive measures aimed at reducing Echinococcus granulosus and Echinococcus multilocularis infection in humans.

Seroprevalence of Cystic Echinococcosis in Yaks and Sheep During 2017 on the Qinghai–Tibet Plateau, China

Cystic echinococcosis (CE) is a livestock disease caused by a parasite known as Echinococcus granulosus. It is one of the primary cause for illness and poverty especially for herders on the Qinghai–Tibet plateau, China. Meanwhile, the Qinghai–Tibet plateau has been a key area for echinococcosis control in China. Here in current study, we determined the seroprevalence of E. granulosus in ruminants on this region. A total of 2,730 serum samples (1,638 samples from yaks and 1,092 samples from sheep) were collected on the plateau during the period of 2017. The samples were assayed for E. granulosus antibodies by commercial enzyme-linked immunosorbent assay kits. Our results exhibited a prevalence percentage of 52.2% in Tibetan yaks and 38.2% in Tibetan sheep. Moreover, there was more chance of being infected with E. granulosus infection in old animals due to more exposure to contaminated sources of infection. However, no significant difference was observed. Furthermore, we observed that the rainfall and presence of several lakes has increased the risk of CE infection in yaks and sheep in the Qinghai, Qinglong, and Baingoin areas. Hence, with this investigation, it was possible to determine the frequency and distribution of CE in yaks and Tibetan sheep on the Qinghai-Tibet plateau, that laying the groundwork for its prevention and management.

A two-stage multiresolution neural network for automatic diagnosis of hepatic echinococcosis from ultrasound images: A multicenter study

PURPOSE

Hepatic echinococcosis is a parasitic disease. Ultrasound imaging is a crucially important tool for the diagnosis of this disease. Based on ultrasonic manifestations, hepatic echinococcosis can be classified into many subtypes. However, the subtyping is non-trivial due to the challenges of complex sonographic textures and the large intra-class and small inter-class differences. The purpose of this study is to develop a computer aided diagnosis system for hepatic echinococcosis based on ultrasound images.

METHODS

We collected a multicenter ultrasound dataset containing 9112 images from 5028 patients who were diagnosed with hepatic echinococcosis (the largest cohort to date) and developed a two-stage multiresolution neural network for the automatic diagnosis of hepatic echinococcosis into nine subtypes as suggested by WHO. Our method was based on YOLO3 with two additional strategies to improve its performance: coarse grouping and multiresolution sampling. Considering that some subtypes are inherently very similar and difficult to be differentiated, in the first stage we detected and classified lesions into four coarse groups, instead of making a direct classification into nine classes. In the second stage, we performed fine-grained classification within each coarse group. Multiple views with different resolutions were sampled from the detected lesions and were input into Darknet53. The softmax outputs for the multiresolution views were averaged to generate the final output.

RESULTS

Both the proposed coarse grouping and multiresolution sampling strategies proved to be effective and improved the classification performance by a large margin compared with the setting without using the two strategies. Using five-fold cross validation, our method achieved 87.1%, 86.2%, and 86.5% in the average recall, precision and F1-score, respectively, and outperformed other state-of-the-art methods remarkably.

CONCLUSIONS

The experimental results demonstrate the great promise of our method for classifying hepatic echinococcosis. Our method can be used as an effective tool to facilitate large-scale screening for hepatic echinococcosis in high-risk, resource-poor areas, thus contributing to early diagnosis of this disease and resulting in more successful treatment. This article is protected by copyright. All rights reserved.

The impact of environmental factors on human echinococcosis epidemics: spatial modelling and risk prediction

Background

Human echinococcosis is affected by natural environmental factors, and its prevalence shows a distinct geographical distribution. Western China has the highest endemicity of human echinococcosis worldwide, but the spatial pattern and environmental determinants of echinococcosis are still unclear.

Methods

Hot/cold spot analysis was used to investigate the spatial distribution of human echinococcosis prevalence. Geodetector was used to identify key natural factors, and a structured additive regression model was used to analyse the relationship between natural factors and human echinococcosis prevalence and spatially predict echinococcosis epidemics.

Results

Hot spots for human echinococcosis prevalence include western and southeastern parts of Tibet Autonomous Region (henceforth Tibet) and the border areas between Tibet and the provinces of Qinghai and Sichuan. Spatial effects are crucial when modelling epidemics, and relative humidity, altitude and grassland area ratio were found to have the most evident effects on echinococcosis epidemics. The relationship between these three factors and echinococcosis prevalence was non-linear, and echinococcosis risk was higher in areas with high relative humidity, high altitude, and a high ratio of grassland to other land use types. The prevalence that was predicted from the investigated environmental factors was generally higher than the actual prevalence, and more epidemic hot spots were predicted for the Qinghai-Tibet Plateau, Inner Mongolia Autonomous Region, and the provinces of Yunnan and Sichuan than the rest of western China. These results indicate that prevention and control measures may effectively reduce echinococcosis prevalence.

Conclusions

We suggest that the prevention and control of human echinococcosis should be prioritized in the hot spots identified here, through the rational allocation of limited medical resources to where they are most needed. Furthermore, the spatial epidemiological modelling methods used in this study can be employed in future studies on echinococcosis and similar diseases.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05169-y.

Prevalence and spatial distribution characteristics of human echinococcosis in China

Background

Echinococcosis is a zoonotic parasitic disease caused by larval stages of cestodes belonging to the genus Echinococcus. The infection affects people’s health and safety as well as agropastoral sector. In China, human echinococcosis is a major public health burden, especially in western China. Echinococcosis affects people health as well as agricultural and pastoral economy. Therefore, it is important to understand the prevalence status and spatial distribution of human echinococcosis in order to advance our knowledge of basic information for prevention and control measures reinforcement.

Methods

Report data on echinococcosis were collected in 370 counties in China in 2018 and were used to assess prevalence and spatial distribution. SPSS 21.0 was used to obtain the prevalence rate for CE and AE. For statistical analyses and mapping, all data were processed using SPSS 21.0 and ArcGIS 10.4, respectively. Chi-square test and Exact probability method were used to assess spatial autocorrelation and spatial clustering.

Results

A total of 47,278 cases of echinococcosis were recorded in 2018 in 370 endemic counties in China. The prevalence rate of human echinococcosis was 10.57 per 10,000. Analysis of the disease prevalence showed obvious spatial positive autocorrelation in globle spatial autocorrelation with two aggregation modes in local spatial autocorrelation, namely high-high and low-high aggregation areas. The high-high gathering areas were mainly concentrated in northern Tibet, western Qinghai, and Ganzi in the Tibetan Autonomous Region and in Sichuan. The low-high clusters were concentrated in Gamba, Kangma and Yadong counties of Tibet. In addition, spatial scanning analysis revealed two spatial clusters. One type of spatial clusters included 71 counties in Tibet Autonomous Region, 22 counties in Qinghai, 11 counties in Sichuan, three counties in Xinjiang Uygur Autonomous Region, two counties in Yunnan, and one county in Gansu. In the second category, six types of spatial clusters were observed in the counties of Xinjiang Uygur Autonomous Region, and the Qinghai, Gansu, and Sichuan Provinces.

Conclusion

This study showed a serious prevalence of human echinococcosis with obvious spatial aggregation of the disease prevalence in China. The Qinghai-Tibet Plateau is the "hot spot" area of human echinococcosis in China. Findings from this study indicate that there is an urgent need of joint strategies to strengthen efforts for the prevention and control of echinococcosis in China, especially in the Qinghai-Tibet Plateau.

Echinococcosis is a zoonotic parasitic disease caused by larval stages of cestodes belonging to the genus Echinococcus. In China, human echinococcosis is a major public health burden, especially in western China. Therefore, it is important to understand the prevalence status and spatial distribution of human echinococcosis in order to provide basic information for prevention and control measures reinforcement. To describe the distribution and analyze the prevalence and spatial distribution characteristics of human echinococcosis in China, report data of echinococcosis were collected in 370 counties in 2018. For the year 2018, there were 47,278 cases of echinococcosis recorded in 370 endemic counties in China. Analysis of the disease prevalence showed obvious spatial positive autocorrelation in global spatial autocorrelation with two aggregation modes in local spatial autocorrelation, namely high-high and low-high aggregation areas. The high-high gathering areas were mainly concentrated in northern Tibet, western Qinghai, and Ganzi in the Tibetan Autonomous Region and in Sichuan. This study showed obvious spatial aggregation of human echinococcosis prevalence in China. The Qinghai-Tibet Plateau is the "hot spot" area of human echinococcosis in China. Such findings indicate that here is an urgent need of joint strategies to strengthen efforts for the prevention and control of echinococcosis in China, especially in the Qinghai-Tibet Plateau.

Advances in research on echinococcoses epidemiology in China

Echinococcoses are serious zoonotic diseases in China's vast, western and north-western pastoral areas that has one of the highest prevalence in the world. The two most common forms, cystic echinococcosis (CE) and alveolar echinococcosis (AE), are co-epidemic in some areas causing a grave threat to people's health and economic development. Echinococcus spp. are transmitted through domestic, sylvatic and mixed cycles involving many kinds of host. Successful transmission requires a favourable environment for the growth of the parasites and survival of their eggs, while the unique customs and religious beliefs in the endemic areas pose a challenge to the prevention and control of these parasites. Based on previous epidemiological studies, this paper reviews the particular factors affecting the transmission of Echinococcus parasites in China, with a focus on biological (parasite genotype and the species, age, sex and density of hosts), environmental (landscape and climate) and social (age, gender, ethnicity, education, occupation, life style, cultural customs, living conditions and hygiene practices of humans in the endemic areas). These three factors interact with each other and jointly determine the parasites' transmission intensity, the study of which supports the formulation of the strategies and measures that are significant for control of these infections.

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

Echinococcosis, caused by genus Echinococcus, is the most pathogenic zoonotic parasitic disease in the world. In Tibet of the People's Republic of China, echinococcosis refers principally to two types of severe zoonosis, cystic echinococcosis (CE) and alveolar echinococcosis (AE), which place a serious burden on public health and economy in the local community. However, research on the spatial epidemiology of echinococcosis remains inadequate in Tibet, China. Based on the recorded human echinococcosis data, maps of the spatial distribution of human CE and AE prevalence in Tibet were produced at city level and county level respectively, which show that the prevalence of echinococcosis in northern and western Tibet was much higher than that in other regions. We employ a geographical detector to explore the influencing factors for causing CE and AE while sorting information on the maps of disease prevalence and environment factors (e.g. terrain, population, and yak population). The results of our analysis showed that biological factors have the most impact on the prevalence of echinococcosis, of which the yak population contributes the most for CE, while the dog population contributes the most for AE. In addition, the interaction between various factors, as we found out, might further explain the disease prevalence, which indicated that the echinococcosis prevalence is not simply affected by one single factor, but by multiple factors that are correlated with each other complicatedly. Our results will provide an important reference for the evaluation of the echinococcosis risk, control projects, and prevention programs in Tibet.

Association between environmental and climatic risk factors and the spatial distribution of cystic and alveolar echinococcosis in Kyrgyzstan

Background

Cystic and alveolar echinococcosis (CE and AE) are neglected tropical diseases caused by Echinococcus granulosus sensu lato and E. multilocularis, and are emerging zoonoses in Kyrgyzstan. In this country, the spatial distribution of CE and AE surgical incidence in 2014-2016 showed marked heterogeneity across communities, suggesting the presence of ecological determinants underlying CE and AE distributions.

Methodology/Principal findings

For this reason, in this study we assessed potential associations between community-level confirmed primary CE (no.=2359) or AE (no.=546) cases in 2014-2016 in Kyrgyzstan and environmental and climatic variables derived from satellite-remote sensing datasets using conditional autoregressive models. We also mapped CE and AE relative risk. The number of AE cases was negatively associated with 10-year lag mean annual temperature. Although this time lag should not be considered as an exact measurement but with associated uncertainty, it is consistent with the estimated 10–15-year latency following AE infection. No associations were detected for CE. We also identified several communities at risk for CE or AE where no disease cases were reported in the study period.

Conclusions/Significance

Our findings support the hypothesis that CE is linked to an anthropogenic cycle and is less affected by environmental risk factors compared to AE, which is believed to result from spillover from a wild life cycle. As CE was not affected by factors we investigated, hence control should not have a geographical focus. In contrast, AE risk areas identified in this study without reported AE cases should be targeted for active disease surveillance in humans. This active surveillance would confirm or exclude AE transmission which might not be reported with the present passive surveillance system. These areas should also be targeted for ecological investigations in the animal hosts.

Cystic and alveolar echinococcosis (CE and AE) are parasitic zoonoses that cause a substantial disease burden in Kyrgyzstan. The etiologic agents of these diseases are parasites in the genus Echinococcus. These parasites have complex life cycles which include mammalian definitive and intermediate hosts and a free-living egg stage in the environment. Consequently, environmental and climatic factors can affect the prevalence and geographical distribution of these diseases because such factors influence the parasites’ eggs survival and longevity, and can affect suitable habitats for the intermediate and definitive hosts. In this geographic correlation study, we assessed environmental and climatic determinants of the spatial distributions of CE and AE in Kyrgyzstan. We found that 10-year lag annual temperature plays an important role in AE distribution, whilst none of the variables assessed was found to significantly affect that of CE. Moreover, communities at risk where these diseases are potentially under- or misdiagnosed were identified. Our findings provide vital information for targeted, area-specific interventions in Kyrgyzstan, and add to the body of knowledge on the ecology of these neglected parasitic diseases that are emerging and reemerging in several regions in North America, Europe and Asia.

Temporal and spatial distribution trends of human brucellosis in Liaoning Province, China

Brucellosis is a natural epidemic zoonotic disease. Liaoning province, north-east of China, has been among the top 10 provinces with highest brucellosis incidence. In this study, the spatial and temporal distribution of brucellosis in Liaoning Province from 2006 through 2017 was analysed using the Bayesian theory of space-time modelling. The study found that in Liaoning Province, (a) all regions of the entire study area were stable counties; (b) the risk of brucellosis declined slowly with time without an obvious trend; (c) the declining trend of disease risk in three sub-hot-spot counties was faster than the overall trend, whereas in other counties, the trend was similar to the overall trend. Furthermore, the time and spatial trends of brucellosis incidence in Liaoning Province were calculated and analysed. These results may provide a theoretical and scientific basis for the public health department to develop targeted effective prevention and control measures for the disease.

Analysis of Factors Influencing Cystic Echinococcosis in Northwest Non-Qinghai Tibetan Plateau Regions of China

Cystic echinococcosis (CE) is an important health problem in northwest non-Qinghai Tibetan Plateau regions of China. Understanding CE risk factors may help in formulating effective prevention and control measures. In the current study, negative binomial regression was used to analyze CE-related factors using prevalence data from 147 counties (cities, districts, and banners) in northwest non-Qinghai Tibetan Plateau regions of China gathered from a national survey conducted in 2012, county economic data, and livestock production data for 2012. The negative binomial regression models indicated Echinococcus granulosus infection rate in livestock (odds ratio [OR]: 1.0471, 95% CI: 1.0128-1.0825, P = 0.0067), the mean number of dogs per family (OR: 3.0589, 95% CI: 1.5116-6.1900, P = 0.0019), the mean number of sheep per family (OR: 1.0431, 95% CI: 1.0027-1.0852, P = 0.0365), and the source of drinking water (OR: 0.9808, 95% CI: 0.9627-0.9992, P = 0.0413) were correlated with human CE prevalence, whereas altitude, surface temperature, economy, and mean number of cattle per family had a negative association. We found that the positive rate of dog stool coproantigen of Echinococcus was associated with human CE prevalence using the univariate analysis but not after controlling for covariates including the number of dogs per family. This might be partially due to the deworming campaigns that were carried out in most of the researched areas. Therefore, the positive rate of dog stool coproantigen of Echinococcus could not reflect the dog infection rate under natural conditions. These findings indicate that dogs and livestock play the most important role in CE transmission. Further studies should be carried out at the township or village level.

Prediction of Human Brucellosis in China Based on Temperature and NDVI

Brucellosis occurs periodically and causes great economic and health burdens. Brucellosis prediction plays an important role in its prevention and treatment. This paper establishes relationships between human brucellosis (HB) and land surface temperature (LST), and the normalized difference vegetation index (NDVI). A seasonal autoregressive integrated moving average with exogenous variables (SARIMAX) model is constructed to predict trends in brucellosis rates. The fitted results (Akaike Information Criterion (AIC) = 807.58, Schwarz Bayes Criterion (SBC) = 819.28) showed obvious periodicity and a rate of increase of 138.68% from January 2011 to May 2016. We found a significant effect between HB and NDVI. At the same time, the prediction part showed that the highest monthly incidence per year has a decreasing trend after 2015. This may be because of the brucellosis prevention and control measures taken by the Chinese Government. The proposed model allows the early detection of brucellosis outbreaks, allowing more effective prevention and control.

Correlates of School Children's Handwashing: A Study in Tibetan Primary Schools

Hand hygiene, including handwashing by children, has been reported to contribute to the prevention of various infectious conditions. This study aims to explore the correlates of handwashing behavior among 1690 fourth to sixth grade primary school students in 19 Tibetan primary schools (Golog, Qinghai, China). The theory of reasoned action (TRA) was applied. Data was collected by questionnaire. Structural equation modeling (SEM) analysis showed that students' attitude (β = 0.22, 95% CI 0.13-0.31) and subjective norms in terms of compliance to teachers', parents' and peers' suggestions to wash hands (β = 0.09, 95% CI 0.01-0.18) were directly associated with students' handwashing behavior. Students' knowledge (β = 0.04, 95% CI 0.03-0.07) had an indirect association with handwashing behavior, mediated by students' attitudes and subjective norms. Subjective norms (β = 0.12, 95% CI 0.07-0.17) were also indirectly correlated with handwashing through students' attitudes. Therefore, our study supported the theory of reasoned action through our findings that students' attitude and knowledge, and also attitudes from teachers, parents and peers were correlated with student handwashing behavior. Students reported higher level of compliance to teachers than to their parents and classmates. Based on this information, we recommend teacher-involved participatory hygiene education to promote students' handwashing behaviors in areas at high risk for infectious diseases that can be prevented by handwashing.

Echinococcosis transmission on the Tibetan Plateau

Since the mid-1990s detailed studies and field investigations on the Tibetan Plateau have revealed human echinococcosis to be an under-reported major public health problem, particularly in the dominant pastoral communities in the eastern and central regions. Human prevalence surveys showed that cystic echinococcosis (CE, caused by Echinococcus granulosus) and alveolar echinococcosis (AE, caused by Echinococcus multilocularis) are co-endemic with higher burdens of each disease than other endemic world regions. Epidemiological investigations identified some major risk factors for human CE and AE including dog ownership, husbandry practices and landscape features. Dogs appear to be the major zoonotic reservoir for both E. granulosus and E. multilocularis, but the latter is also transmitted in complex wildlife cycles. Small mammal assemblages especially of vole and pika species thrive on the Plateau and contribute to patterns of E. multilocularis transmission which are influenced by landscape characteristics and anthropogenic factors. Tibetan foxes are a principal definitive host for both E. multilocularis and E. shiquicus. In 2006 a national echinococcosis control programme was initiated in Tibetan communities in northwest Sichuan Province and rolled out to all of western China by 2010, and included improved surveillance (and treatment access) of human disease and regular deworming of dogs with annual copro-testing. Control of echinococcosis in Tibetan pastoral communities poses a difficult challenge for delivery and sustainability.

Spatio-Temporal Analysis of Infectious Diseases

Epidemiological research on the pathogenesis, diagnosis, and treatment of infectious diseases is a broad field of study with renewed validity in the face of social changes and new threats [...].