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.

Tuberculosis Prevalence Trends from a Predictive Modelling Study - 10 High-Burden Countries, 1980-2035.

What is already known about this topic?: Given the challenges presented by drug-resistant strains of tuberculosis (TB) and the rising mobility of the population, achieving the objective of eradicating TB appears uncertain. What is added by this report?: The examination of TB incidence trends in 10 high-burden countries (HBCs) indicated a steady rise in cases, with India and China jointly accounting for nearly 70% of the burden. Projections for the future show diverse trajectories in these countries, with potential difficulties in reaching the TB elimination target, especially in Nigeria, Congo, and South Africa. What are the implications for public health practice?: The number of TB cases is on the rise. It is crucial to learn from successful strategies to improve TB prevention and control worldwide through collaborative efforts.

Assessment of transmissibility and measures effectiveness of SARS in 8 regions, China, 2002-2003.

Background: Severe acute respiratory syndrome (SARS) is a form of atypical pneumonia which took hundreds of lives when it swept the world two decades ago. The pathogen of SARS was identified as SARS-coronavirus (SARS-CoV) and it was mainly transmitted in China during the SARS epidemic in 2002-2003. SARS-CoV and SARS-CoV-2 have emerged from the SARS metapopulation of viruses. However, they gave rise to two different disease dynamics, a limited epidemic, and an uncontrolled pandemic, respectively. The characteristics of its spread in China are particularly noteworthy. In this paper, the unique characteristics of time, space, population distribution and transmissibility of SARS for the epidemic were discussed in detail. Methods: We adopted sliding average method to process the number of reported cases per day. An SEIAR transmission dynamics model, which was the first to take asymptomatic group into consideration and applied indicators of R 0, Reff, Rt to evaluate the transmissibility of SARS, and further illustrated the control effectiveness of interventions for SARS in 8 Chinese cities. Results: The R 0 for SARS in descending order was: Tianjin city (R 0 = 8.249), Inner Mongolia Autonomous Region, Shanxi Province, Hebei Province, Beijing City, Guangdong Province, Taiwan Province, and Hong Kong. R 0 of the SARS epidemic was generally higher in Mainland China than in Hong Kong and Taiwan Province (Mainland China: R 0 = 6.058 ± 1.703, Hong Kong: R 0 = 2.159, Taiwan: R 0 = 3.223). All cities included in this study controlled the epidemic successfully (Reff<1) with differences in duration. Rt in all regions showed a downward trend, but there were significant fluctuations in Guangdong Province, Hong Kong and Taiwan Province compared to other areas. Conclusion: The SARS epidemic in China showed a trend of spreading from south to north, i.e., Guangdong Province and Beijing City being the central regions, respectively, and from there to the surrounding areas. In contrast, the SARS epidemic in the central region did not stir a large-scale transmission. There were also significant differences in transmissibility among eight regions, with R0 significantly higher in the northern region than that in the southern region. Different regions were able to control the outbreak successfully in differences time.

Environmental spillover of emerging viruses: Is it true?

The concept of environmental "spillover" of pathogens to humans is widely used in the scientific literature about emerging diseases with the idea that it is scientifically proven. However, the exact characterization of the mechanism of spillover is simply lacking. A systematic review retrieved 688 articles using this term. The systematic analysis revealed an irreducible polysemy covering ten different definitions. It also demonstrated the absence of explicit definition in most of the articles, and even antinomies. A modeling analysis of the various processes described by these ten definitions showed that none of them corresponded to the complete trajectory leading to the emergence of a disease. There is no article demonstrating a mechanism of spillover. There are only ten articles proposing ideas on how a putative spillover could work but they merely are intellectual constructions. All other articles only reuse the term with no demonstration. It is essential to understand that since there is no scientific concept behind the "spillover", it might be dangerous to base public health and public protection against future pandemics on it.

Investigation on the Management for Patients with Echinococcosis Treated with Albendazole - Three PLADs, China, 2019.

What is already known about this topic?: In China, patients with echinococcosis receive complimentary healthcare services, such as medical treatment, diagnostic examinations, and follow-up care. Despite this, no studies have been conducted to assess the quality of patient management to date. What is added by this report?: This study reviewed the medical records of 899 patients who underwent albendazole treatment across 10 endemic counties. Out of 634 evaluable patient files, the proportion of patients with a ratio of actual follow-up and reexamination times to theoretical follow-up and reexamination times ≥0.8 were both low (21.92% and 23.19%, respectively). What are the implications for public health practices?: This study identified weaknesses and specific issues in patient management and proposed feasible recommendations to enhance patient file documentation, follow-up, and reexamination.

Transmissibility of tuberculosis among students and non-students: an occupational-specific mathematical modelling.

BACKGROUND: Recently, despite the steady decline in the tuberculosis (TB) epidemic globally, school TB outbreaks have been frequently reported in China. This study aimed to quantify the transmissibility of Mycobacterium tuberculosis (MTB) among students and non-students using a mathematical model to determine characteristics of TB transmission. METHODS: We constructed a dataset of reported TB cases from four regions (Jilin Province, Xiamen City, Chuxiong Prefecture, and Wuhan City) in China from 2005 to 2019. We classified the population and the reported cases under student and non-student groups, and developed two mathematical models [nonseasonal model (Model A) and seasonal model (Model B)] based on the natural history and transmission features of TB. The effective reproduction number (Reff) of TB between groups were calculated using the collected data. RESULTS: During the study period, data on 456,423 TB cases were collected from four regions: students accounted for 6.1% of cases. The goodness-of-fit analysis showed that Model A had a better fitting effect (P < 0.001). The average Reff of TB estimated from Model A was 1.68 [interquartile range (IQR): 1.20-1.96] in Chuxiong Prefecture, 1.67 (IQR: 1.40-1.93) in Xiamen City, 1.75 (IQR: 1.37-2.02) in Jilin Province, and 1.79 (IQR: 1.56-2.02) in Wuhan City. The average Reff of TB in the non-student population was 23.30 times (1.65/0.07) higher than that in the student population. CONCLUSIONS: The transmissibility of MTB remains high in the non-student population of the areas studied, which is still dominant in the spread of TB. TB transmissibility from the non-student-to-student-population had a strong influence on students. Specific interventions, such as TB screening, should be applied rigorously to control and to prevent TB transmission among students.

Societal drivers of human echinococcosis in China.

BACKGROUND: Echinococcosis is a parasitic zoonotic disease that threatens human health and economic development. In China, 370 counties are endemic for echinococcosis. Qinghai-Tibet Plateau has the most patients and people at risk. Therefore, analyzing the societal factors related to susceptibility to the disease is critical for efficient prevention and control of echinococcosis. METHODS: The demographic characteristics and lifestyle of echinococcosis cases were clustered using K-means cluster analysis to determine the main factors of risk of echinococcosis. RESULTS: Middle-aged and young people as well as those with a low education level and herdsmen are at risk of contracting echinococcosis. Nomadism, domestic and feral dogs in the surrounding environment, and drinking heavily polluted natural surface water are the main behavioral risk factors. The cystic echinococcosis (CE) and alveolar echinococcosis (AE) cluster analysis focused on female, middle-aged, and young people, winter settlement and summer nomadism, and domestic and feral dogs in the surrounding environment. There were significant differences in lifestyle between Qinghai-Tibet Plateau cases and non-Qinghai-Tibet-Plateau cases. CONCLUSION: According to the distribution of cases and CE and AE, this study identified the factors of risk of echinococcosis in the Qinghai-Tibet Plateau and non-Qinghai-Tibet Plateau. Adapted control techniques appropriate for the various epidemic areas should be established to serve as a reference for echinococcosis prevention.

Role of spike compensatory mutations in the interspecies transmission of SARS-CoV-2.

SARS-CoV-2, the virus responsible for COVID-19 in humans, can efficiently infect a large number of animal species. Like any virus, and particularly RNA viruses, SARS-CoV-2 undergoes mutations during its life cycle some of which bring a selective advantage, leading to the selection of a given lineage. Minks are very susceptible to SARS-CoV-2 and owing to their presence in mass rearing, they make a good model for studying the relative importance of mutations in viral adaptation to host species. Variants, such as the mink-selected SARS-CoV-2 Y453F and D614G or H69del/V70del, Y453F, I692V and M1229I were identified in humans after spreading through densely caged minks. However, not all mink-specific mutations are conserved when the virus infects human populations back. Many questions remain regarding the interspecies evolution of SARS-CoV-2 and the dynamics of transmission leading to the emergence of new variant strains. We compared the human and mink ACE2 receptor structures and their interactions with SARS-CVoV-2 variants. In minks, ACE2 presents a Y34 amino acid instead of the H34 amino acid found in the human ACE2. H34 is essential for the interaction with the Y453 residue of the SARS-CoV-2 Spike protein. The Y453F mink mutation abolishes this conflict. A series of 18 mutations not involved in the direct ACE2 interaction was observed in addition to the Y453F and D614G in 16 different SARS-CoV-2 strains following bidirectional infections between humans and minks. These mutations were not random and were distributed into five different functional groups having an effect on the kinetics of ACE2-RD interaction. The interspecies transmission of SARS-CoV-2 from humans to minks and back to humans, generated specific mutations in each species which improved the affinity for the ACE2 receptor either by direct mutation of the core 453 residue or by associated compensatory mutations.

Shigellosis seasonality and transmission characteristics in different areas of China: A modelling study.

Objective: In China, the burden of shigellosis is unevenly distributed, notably across various ages and geographical areas. Shigellosis temporal trends appear to be seasonal. We should clarify seasonal warnings and regional transmission patterns. Method: This study adopted a Logistic model to assess the seasonality and a dynamics model to compare the transmission in different areas. The next-generation matrix was used to calculate the effective reproduction number (R eff) to quantify the transmissibility. Results: In China, the rate of shigellosis fell from 35.12 cases per 100,000 people in 2005 to 7.85 cases per 100,000 people in 2017, peaking in June and August. After simulation by the Logistic model, the 'peak time' is mainly concentrated from mid-June to mid-July. China's 'early warning time' is primarily focused on from April to May. We predict the 'peak time' of shigellosis is the 6.30th month and the 'early warning time' is 3.87th month in 2021. According to the dynamics model results, the water/food transfer pathway has been mostly blocked off. The transmissibility of different regions varies greatly, such as the mean R eff of Longde County (3.76) is higher than Xiamen City (3.15), higher than Chuxiong City (2.52), and higher than Yichang City (1.70). Conclusion: The 'early warning time' for shigellosis in China is from April to May every year, and it may continue to advance in the future, such as the early warning time in 2021 is in mid-March. Furthermore, we should focus on preventing and controlling the person-to-person route of shigellosis and stratified deploy prevention and control measures according to the regional transmission.

Feasibility of Hepatitis C Elimination in China: From Epidemiology, Natural History, and Intervention Perspectives.

Hepatitis C imposes a heavy burden on many countries, including China, where the number of reported cases and the incidence of hepatitis C virus (HCV) increased yearly from 2005 to 2012, with a stable trend after 2012. The geographical distribution of HCV infections varies widely in China, with the northwest and southwest regions and the Henan Province showing a high disease burden. Elderly, men, sexually active people, drug users, migrants, blood transfusion recipients, and renal dialysis patients have become the target populations for hepatitis C prevention and control. It is important to improve the diagnosis rate in high-risk groups and asymptomatic people. Identifying secondary HCV infections, especially in HCV patients co-infected with the human immunodeficiency virus (HIV) is a priority of hepatitis C prevention and control. Enhancing universal access to direct antiviral agents (DAAs) treatment regimens is an effective way to improve the cure rate of HCV infection. For China to contribute to the WHO 2030 global HCV elimination plan, strategic surveillance, management, and treatment program for HCV are needed.

[SARS-CoV-2 has no origin]. / Le virus SARS-CoV-2 n'a pas « d'origine ¼.

Since the beginning of the COVID-19 pandemic, the question of the origin of this virus has been the subject of a vivid controversy. It is the question of the "origin" itself which is biased. Darwin showed that there is no determined origin to any animal or plant species, simply an evolutionary and selective process. The same is true for viruses, there is no origin, but an evolutionary process. Viruses circulate from host to host, animals or humans. Pandemic viruses are already circulating in humans and evolving before the onset of disease. This evolutionary process then continues and gives rise to successive variants. The solution is not to target the disease or the putative causative agent but rather to address the process of disease emergence.

Title: Le virus SARS-CoV-2 n'a pas « d'origine ¼. Abstract: Depuis le début de la pandémie de COVID-19, la question de l'origine de ce virus fait l'objet d'une vive polémique. C'est la question de « l'origine ¼ qui est biaisée. Darwin a montré qu'il n'y a pas d'origine déterminée à aucune espèce animale ou végétale, simplement un processus évolutif et sélectif. Il en est de même pour les virus, il n'y a pas d'origine, mais un processus évolutif. Les virus circulent d'hôte à hôte, animaux ou humains. Les virus pandémiques circulent déjà chez l'homme et évoluent avant l'apparition d'une maladie. Ce processus évolutif se poursuit et donne naissance à des variants successifs. La solution n'est pas de cibler la maladie ou le possible agent causal, mais plutôt de cibler le processus d'émergence de la maladie lui-même.

Assessment of echinococcosis control in Tibet Autonomous Region, China.

BACKGROUND: In China the highest prevalence of echinococcosis is in Tibet Autonomous Region (TAR). The government has issued documents and implemented comprehensive prevention and control measures focusing on controlling the source of infection of echinococcosis. It was very important to understand the implementation and effect of infectious source control measures. The purpose of this study was to examine the implementation of measures to control infectious source (domestic and stray dogs) in TAR and to assess their effectiveness. METHODS: We collected data on domestic dog registration and deworming and stray dog sheltering in 74 counties/districts in the TAR from 2017 to 2019. Fecal samples from domestic dogs were collected from randomly selected towns to determine Echinococcus infection in dogs using coproantigen ELISA. We analyzed the data to compare the canine rate of infection between 2016 and 2019. The data analysis was performed by SPSS statistical to compare dog infection rate in 2016 and 2019 by chi-square test, and ArcGIS was used for mapping. RESULTS: From 2017 to 2019, 84 stray dog shelters were built in TAR, and accumulatively 446,660 stray or infected dogs were arrested, sheltered, or disposed of. The number of domestic dogs went downward, with an increased registration management rate of 78.4% (2017), 88.8% (2018), and 99.0% (2019). Dogs were dewormed 5 times in 2017, 12 times in 2018, and 12 times in 2019. The dog infection rate was 1.7% (252/14,584) in 2019, significantly lower than 7.3% (552/7564) from the survey of echinococcosis prevalence in Tibet in 2016 (P < 0.05). CONCLUSION: Between 2017 and 2019, the number of stray dogs and infection rate of Echinococcus spp. in domestic dogs decreased significantly, indicating that dogs were effectively controlled as a source of infection in TAR and reflecting a significant decrease in the risk of echinococcosis transmission.

Geographic distribution and prevalence of human echinococcosis at the township level in the Tibet Autonomous Region.

BACKGROUND: Echinococcosis, a zoonotic parasitic disease, is caused by larval stages of cestodes in the Echinococcus genus. Echinococcosis is highly prevalent in ten provinces/autonomous regions of western and northern China. In 2016, an epidemiological survey of Tibet Autonomous Region (TAR) revealed that the prevalence of human echinococcosis was 1.66%, which was much higher than the average prevalence in China (0.24%). Therefore, to improve on the current prevention and control measures, it is important to understand the prevalence and spatial distribution characteristics of human echinococcosis at the township level in TAR. METHODS: Data for echinococcosis cases in 2018 were obtained from the annual report system of echinococcosis of Tibet Center for Disease Control and Prevention. Diagnosis had been performed via B-ultrasonography. The epidemic status of echinococcosis in all townships in TAR was classified according to the relevant standards of population prevalence indices as defined in the national technical plan for echinococcosis control. Spatial scan statistics were performed to establish the geographical townships that were most at risk of echinococcosis. RESULTS: In 2018, a total of 16,009 echinococcosis cases, whose prevalence was 0.53%, were recorded in 74 endemic counties in TAR. Based on the order of the epidemic degree, all the 692 townships were classified from high to low degrees. Among them, 127 townships had prevalence rates ≥ 1%. The high prevalence of human echinococcosis in TAR, which is associated with a wide geographic distribution, is a medical concern. Approximately 94.65% of the villages and towns reported echinococcosis cases. According to spatial distribution analysis, the prevalence of human echinococcosis was found to be clustered, with the specific clustering areas being identified. The cystic echinococcosis primary cluster covered 88 townships, while that of alveolar echinococcosis's covered 38 townships. CONCLUSIONS: This study shows spatial distributions of echinococcosis with different epidemic degrees in 692 townships of TAR and high-risk cluster areas at the township level. Our findings indicate that strengthening the echinococcosis prevention and control strategies in TAR should directed at townships with a high prevalence and high-risk clustering areas.

There is no "origin" to SARS-CoV-2.

Since the beginning of the COVID-19 pandemic in 2020 caused by SARS-CoV-2, the question of the origin of this virus has been a highly debated issue. Debates have been, and are still, very disputed and often violent between the two main hypotheses: a natural origin through the "spillover" model or a laboratory-leak origin. Tenants of these two options are building arguments often based on the discrepancies of the other theory. The main problem is that it is the initial question of the origin itself which is biased. Charles Darwin demonstrated in 1859 that all species are appearing through a process of evolution, adaptation and selection. There is no determined origin to any animal or plant species, simply an evolutionary and selective process in which chance and environment play a key role. The very same is true for viruses. There is no determined origin to viruses, simply also an evolutionary and selective process in which chance and environment play a key role. However, in the case of viruses the process is slightly more complex because the "environment" is another living organism. Pandemic viruses already circulate in humans prior to the emergence of a disease. They are simply not capable of triggering an epidemic yet. They must evolve in-host, i.e. in-humans, for that. The evolutionary process which gave rise to SARS-CoV-2 is still ongoing with regular emergence of novel variants more adapted than the previous ones. The real relevant question is how these viruses can emerge as pandemic viruses and what the society can do to prevent the future emergence of pandemic viruses.

Origin of COVID-19: Dismissing the Mojiang mine theory and the laboratory accident narrative.

The origin of SARS-CoV-2 is still the subject of a controversial debate. The natural origin theory is confronted to the laboratory leak theory. The latter is composite and comprises contradictory theories, one being the leak of a naturally occurring virus and the other the leak of a genetically engineered virus. The laboratory leak theory is essentially based on a publication by Rahalkar and Bahulikar in 2020 linking SARS-CoV-2 to the Mojiang mine incident in 2012 during which six miners fell sick and three died. We analyzed the clinical reports. The diagnosis is not that of COVID-19 or SARS. SARS-CoV-2 was not present in the Mojiang mine. We also bring arguments against the laboratory leak narrative.

A comparative study on the three calculation methods for reproduction numbers of COVID-19.

Objective: This study uses four COVID-19 outbreaks as examples to calculate and compare merits and demerits, as well as applicational scenarios, of three methods for calculating reproduction numbers. Method: The epidemiological characteristics of the COVID-19 outbreaks are described. Through the definition method, the next-generation matrix-based method, and the epidemic curve and serial interval (SI)-based method, corresponding reproduction numbers were obtained and compared. Results: Reproduction numbers (R eff ), obtained by the definition method of the four regions, are 1.20, 1.14, 1.66, and 1.12. Through the next generation matrix method, in region H R eff = 4.30, 0.44; region P R eff = 6.5, 1.39, 0; region X R eff = 6.82, 1.39, 0; and region Z R eff = 2.99, 0.65. Time-varying reproduction numbers (R t ), which are attained by SI of onset dates, are decreasing with time. Region H reached its highest R t = 2.8 on July 29 and decreased to R t < 1 after August 4; region P reached its highest R t = 5.8 on September 9 and dropped to R t < 1 by September 14; region X had a fluctuation in the R t and R t < 1 after September 22; R t in region Z reached a maximum of 1.8 on September 15 and decreased continuously to R t < 1 on September 19. Conclusion: The reproduction number obtained by the definition method is optimal in the early stage of epidemics with a small number of cases that have clear transmission chains to predict the trend of epidemics accurately. The effective reproduction number R eff , calculated by the next generation matrix, could assess the scale of the epidemic and be used to evaluate the effectiveness of prevention and control measures used in epidemics with a large number of cases. Time-varying reproduction number R t , obtained via epidemic curve and SI, can give a clear picture of the change in transmissibility over time, but the conditions of use are more rigorous, requiring a greater sample size and clear transmission chains to perform the calculation. The rational use of the three methods for reproduction numbers plays a role in the further study of the transmissibility of COVID-19.

The stochastic world of emerging viruses.

The acquisition of new hosts is a fundamental mechanism by which parasitic organisms expand their host range and perpetuate themselves on an evolutionary scale. Among pathogens, viruses, due to their speed of evolution, are particularly efficient in producing new emergence events. However, even though these phenomena are particularly important to the human species and therefore specifically studied, the processes of virus emergence in a new host species are very complex and difficult to comprehend in their entirety. In order to provide a structured framework for understanding emergence in a species (including humans), a comprehensive qualitative model is an indispensable cornerstone. This model explicitly describes all the stages necessary for a virus circulating in the wild to come to the crossing of the epidemic threshold. We have therefore developed a complete descriptive model explaining all the steps necessary for a virus circulating in host populations to emerge in a new species. This description of the parameters presiding over the emergence of a new virus allows us to understand their nature and importance in the emergence process.

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.