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Risk classification of spread of Oncomelania hupensis. The NDVI values of suitable snail habitats were calculated based on snail density data, and the risk was classified as high-density, medium-density and low-density snail habitats with reference to the NDIV values
Source publication
Background
Flooding is considered to be one of the most important factors contributing to the rebound of Oncomelania hupensis , a small tropical freshwater snail and the only intermediate host of Schistosoma japonicum , in endemic foci. The aim of this study was to assess the risk of intestinal schistosomiasis transmission impacted by flooding in t...
Citations
... This refers to water levels rising from May to October (wet season), submerging the whole substratum where snails reside, rendering the area unsuitable for snail activity. This bottomland area has shown a close correlation with the distribution of snails; however, information on bottomland distribution has been used only to test whether an area is suitable for snail habitation and has not been introduced as a continuous variable in the model [11,12]. Therefore, this study hypothesized that harnessing texture information and quantifying the distance from snail habitats to these bottomlands can signi cantly improve precision in identifying snail habitats. ...
Background
Schistosomiasis japonica poses a significant health issue in China, largely due to the spatial distribution of Oncomelania hupensis, the only intermediate host of Schistosoma, which directly affects schistosomiasis incidence. This study therefore aimed to address the limitations in existing remote sensing studies, particularly the oversight of spatial scale and seasonal variations in snail habitats by introducing a multi-source data-driven Random Forest approach.
Methods
This method effectively integrates bottomland and ground-surface texture data with traditional environmental variables for a more comprehensive and accurate snail habitat analysis. Four distinct models focusing on lakes and marshlands in Guichi, China, were developed: the baseline model, including ground-surface texture, bottomland variables, and environmental variables; Model 1, including only environmental variables; Model 2, including ground-surface texture and environmental variables; and Model 3, including bottomland and environmental variables.
Results
The baseline model outperformed the others, achieving a true skill statistic of 0.93, accuracy of 0.97, kappa statistic of 0.94, and area under the curve of 0.98. The findings identified key high-risk snail habitats, particularly along major rivers and lakes in a belt-like distribution, particularly near the Yangtze River, Qiu Pu River, and surrounding areas of Shengjin Lake, Jiuhua River, and Qingtong River.
Conclusions
This study providing vital data for effective snail monitoring, control strategies, and schistosomiasis prevention. This approach may also be applicable in locating other epidemic hosts with similar survival and ecological characteristics.
... Lagrangian methods have been widely applied in studies of the surface water environment, such as the transport of soluble pollutants (Xue et al., 2021), fish eggs Sun et al., 2017), and oil substances (Hata et al., 2017;Moendeg et al., 2017); water exchange (Song et al., 2016);and vegetated flows (Yang et al., 2018). However, considering the current understanding of Oncomelania snails and the professional backgrounds of schistosomiasis researchers, to the authors knowledge, no study has been conducted using Lagrangian methods to simulate the migration of Oncomelania snails in natural environments. ...
The long-distance migration of Oncomelania snails mainly occurs by attaching to floating objects during floods. However, the processes, characteristics and effects of migration are not fully understood. Here, a motion equation for floating objects with attached Oncomelania snails was constructed using the Lagrangian method. The equation can be numerically solved to simulate the movement of floating objects after parameter calibration. Then, the calibrated parameters were used to simulate the migration of Oncomelania snails in the lower Jingjiang River, where they had spread over a large area. The effects of flood conditions on the migration and spread of Oncomelania snails have been studied to a certain extent, but the impact of wind conditions on snail migration has rarely been reported. Therefore, based on the distribution of Oncomelania snails in China, the difficulties and key areas for the control of schistosomiasis and Oncomelania snails, and the morphological characteristics of the river reach, the Lower Jingjiang River section was selected as a practical application case. A theoretical model of the migration and spread of Oncomelania snails was established, and the characteristics of the Oncomelania snail migration were simulated and analyzed based on flood and distribution patterns under different wind conditions. The results indicate that wind conditions have little influence on the longitudinal spreading of Oncomelania snails but have a relatively large influence on the lateral spreading of snails. Compared with calm wind conditions, both northeasterly and southerly wind conditions can lead to longer longitudinal migration distances of snails, thereby increasing the risk of snail spreading and schistosomiasis transmission.
... However, in contrast to previous studies showing that snail density trended downwards between 2003 and 2015 after the TGD became operational [9,10], we detected an obvious fluctuating and small increasing trend for snail density between 2015 and 2019 (Fig. 3). The volatility of snail density may be associated with frequent flooding disasters that are considered to be responsible for the spread of snails and the variation in snail density [41]. The implementation of massive molluscicide and environmental modification projects became unrealistic, affected by the rigorous policy of the Yangtze River Protection and Ecological Restoration Project [24,42]. ...
... Serious flooding events result in snails being submerged underwater for a long time, which is not conducive to the survival of adult snails [19]. It is possible that snails migrate passively in floodwaters and spread to the snail-free surroundings, forming emerging habitats [6,41]. Therefore, the density of snails generally decreased briefly in the year following the flood, then rebounded due to compensation by new young snails [45,47]. ...
... Attention should be paid to the fluctuation and slight increase in snail density reported in this study. Environmental changes (such as those due to floods and water conservancy projects) may contribute to the diffusion of snail habitats and the rebound of snail density [41,45,47]. The Yangtze River Economic Belt prohibits largescale use of molluscicides and environmental modification measures [24,42]. ...
Background
Snail abundance varies spatially and temporally. Few studies have elucidated the different effects of the determinants affecting snail density between upstream and downstream areas of the Three Gorges Dam (TGD). We therefore investigated the differential drivers of changes in snail density in these areas, as well as the spatial–temporal effects of these changes.
Methods
A snail survey was conducted at 200 sites over a 5-year period to monitor dynamic changes in snail abundance within the Yangtze River basin. Data on corresponding variables that might affect snail abundance, such as meteorology, vegetation, terrain and economy, were collected from multiple data sources. A Bayesian spatial–temporal modeling framework was constructed to explore the differential determinants driving the change in snail density and the spatial–temporal effects of the change.
Results
Volatility in snail density was unambiguously detected in the downstream area of the TGD, while a small increment in volatility was detected in the upstream area. Regarding the downstream area of the TGD, snail density was positively associated with the average minimum temperature in January of the same year, the annual Normalized Difference Vegetation Index (NDVI) of the previous year and the second, third and fourth quartile, respectively, of average annual relative humidity of the previous year. Snail density was negatively associated with the average maximum temperature in July of the previous year and annual nighttime light of the previous year. An approximately inverted “U” curve of relative risk was detected among sites with a greater average annual ground surface temperature in the previous year. Regarding the upstream area, snail density was positively associated with NDVI and with the second, third and fourth quartile, respectively, of total precipitation of the previous year. Snail density was negatively associated with slope.
Conclusions
This study demonstrated a rebound in snail density between 2015 and 2019. In particular, temperature, humidity, vegetation and human activity were the main drivers affecting snail abundance in the downstream area of the TGD, while precipitation, slope and vegetation were the main drivers affecting snail abundance in the upstream area. These findings can assist authorities to develop and perform more precise strategies for surveys and control of snail populations.
Graphical Abstract
... "The Outline of the Healthy China 2030 Plan" also specifies that all endemic counties in China will meet the standards for schistosomiasis elimination by 2030. At present, schistosomiasis control in China has reached transmission interruption, but the prevalence of schistosomiasis may be underestimated due to the wide distribution of snails and insufficient sensitivity of existing detection techniques [23][24][25]. In order to achieve the goal of eliminating schistosomiasis by 2030, the task of interrupting schistosomiasis transmission in China remains daunting, and the intervention strategies after schistosomiasis blocking still need to be improved and optimized [26]. ...
Objectives:
Schistosomiasis is a zoonotic infectious disease that seriously harms people's physical and mental health. As early as 1985, the WHO suggested that health education and health promotion should be the focus of schistosomiasis prevention work. This study aimed to explore the effect of health education on controlling the risk of schistosomiasis transmission after schistosomiasis blocking and to provide a scientific basis for the further improvement of intervention strategies after schistosomiasis interruption in China and other endemic countries.
Methods:
In Jiangling County, Hubei Province, China, one severe, one moderate, and one mildly endemic village were selected as the intervention group; two severe, two moderate, and two mildly endemic villages were selected as the control group. In towns with different epidemic types, a primary school was randomly selected for intervention. In September 2020, a baseline survey was carried out through a questionnaire survey to understand the knowledge, attitudes, and practices (KAP) of adults and students concerning schistosomiasis control. Next, two rounds of health education interventions for schistosomiasis control were carried out. The evaluation survey was conducted in September 2021 and the follow-up survey conducted in September 2022.
Results:
Compared with the baseline survey, the qualified rate of the KAP on schistosomiasis prevention of the control group in the follow-up survey increased from 79.1% (584/738) to 81.0% (493/609) (p > 0.05); in the intervention group, the qualified rate of the KAP on schistosomiasis control increased from 74.9% (286/382) to 88.1% (260/295) (p < 0.001). In the baseline survey, the qualified rate of the KAP of the intervention group was lower than that of the control group, and in the follow-up survey, the qualified rate of the KAP of the intervention group was 7.2% higher than that of the control group (p < 0.05). Compared with the baseline survey, the accuracy rates of the KAP of the intervention group's adults were higher than those of the control group, with statistical significance (p < 0.001). Compared with the baseline survey, the qualified rate of the students' KAP in the follow-up survey increased from 83.8% (253/302) to 97.8% (304/311) (p < 0.001). In the follow-up survey, the accuracy rate of the knowledge, attitudes, and practices of the students was significantly different from the baseline accuracy (p < 0.001).
Conclusion:
a health education-led risk control model of schistosomiasis can significantly improve schistosomiasis control knowledge among adults and students, establishing correct attitudes and leading to the development of correct hygiene habits.
... The impact of environmental change on snail distribution has invoked heated attention. Numerous studies have been conducted to explore the impact of environmental changes on the snail distribution and the spread of schistosomiasis [12][13][14][15][16][17][18][19][20]. However, little is known about their impact on the dynamics of snail density [12][13][14][15][16][17][18][19][20]. ...
... Numerous studies have been conducted to explore the impact of environmental changes on the snail distribution and the spread of schistosomiasis [12][13][14][15][16][17][18][19][20]. However, little is known about their impact on the dynamics of snail density [12][13][14][15][16][17][18][19][20]. ...
Background
The area of Oncomelania hupensis snail remains around 3.6 billion m ² , with newly emerging and reemergent habitats continuing to appear in recent years. This study aimed to explore the long-term dynamics of snail density before and after the operation of Three Gorges Dam (TGD).
Methods
Data of snail survey between 1990 and 2019 were collected from electronic databases and national schistosomiasis surveillance. Meta-analysis was conducted to estimate the snail density. Joinpoint model was used to identify the changing trend and inflection point. Inverse distance weighted interpolation (IDW) was used to determine the spatial distribution of recent snail density.
Results
A total of 3777 snail survey sites with a precise location of village or beach were identified. For the downstream area, snail density peaked in 1998 (1.635/0.11 m ² , 95% CI: 1.220, 2.189) and fluctuated at a relatively high level before 2003, then declined steadily from 2003 to 2012. Snail density maintained lower than 0.150/0.11 m ² between 2012 and 2019. Joinpoint model identified the inflection of 2003, and a significant decreasing trend from 2003 to 2012 with an annual percentage change (APC) being − 20.56% (95% CI: − 24.15, − 16.80). For the upstream area, snail density peaked in 2005 (0.760/0.11 m ² , 95% CI: 0.479, 1.207) and was generally greater than 0.300/0.11 m ² before 2005. Snail density was generally lower than 0.150/0.11 m ² after 2011. Snail density showed a significant decreasing trend from 1990 to 2019 with an APC being − 6.05% (95% CI: − 7.97, − 7.09), and no inflection was identified. IDW showed the areas with a high snail density existed in Poyang Lake, Dongting Lake, Jianghan Plain, and the Anhui branch of the Yangtze River between 2015 and 2019.
Conclusions
Snail density exhibited a fluctuating downward trend in the Yangtze River basin. In the downstream area, the operation of TGD accelerated the decline of snail density during the first decade period, then snail density fluctuated at a relatively low level. There still exists local areas with a high snail density. Long-term control and monitoring of snails need to be insisted on and strengthened.
Graphical Abstract
... However, different from previous studies that snail density showed a downward trend between 2003 and 2015 after the operation of TGD [14,15], an obvious uctuating and small rising trend for snail density was detected between 2015 and 2019 (Fig. 3). The volatility of snail density may be associated with frequent ooding disasters that are considered to be responsible for the spread of snail and the variation of snail density [44]. The implementation of massive molluscicide and environmental modi cation projects became unrealistic affected by the rigorous policy of the Yangtze River protection and ecological restoration project [45,46]. ...
... Serious ooding caused snails to be submerged underwater for a long time, which was not conducive to the survival of adult snails [19]. Snails could migrate passively with the help of ood and spread to the snail-free surroundings, forming emerging habitats [11,44]. Therefore, the density of snails generally decreased brie y after the year of the ood, then rebounded with the compensation of new young snails [50]. ...
... The uctuation and slight increase in snail density should be paid enough attention. Environmental changes (such as oods, and water conservancy projects) may contribute to the diffusion of snail habitats and the rebound of the density [4,11,44]. The Yangtze River Economic Belt prohibits large-scale use of molluscicides and environmental modi cation [45,46]. ...
BACKGROUND
The abundance of Oncomelania hupensis snail can promote the transmission of schistosomiasis japonica. Snail distribution varies spatially and temporally in different geographical regions. Hence, we investigated differential drivers of snail density between the downstream and upstream areas of Three Gorges Dam (TGD), and spatial-temporal changes in snail abundance.
METHODS
We deployed the snail survey at 200 sites over 5 years to monitor a dynamic change in snail abundance within the Yangtze River basin. Corresponding variables that might affect snail abundance, such as Meteorology, vegetation, terrain, and economy, were collected from multiple data sources. We conducted the Bayesian spatial-temporal modeling framework to investigate the differential determinants and spatial-temporal effects of the change of snail density.
RESULTS
Obvious volatility for snail density was detected in the downstream area of TGD, whilst a small increment in the upstream area. For the downstream area of TGD, Snail density was positively associated with the average minimum temperature in January of the same year, annual normalized difference vegetation index of the previous year (NDVI), the 2nd quartile of average annual relative humidity of the previous year (RH), the 3rd quartile of RH, the 4th quartile of RH. Snail density was negatively associated with the average maximum temperature in July of the previous year, and annual night-time light of the previous year. An approximately inverted “U” curve of relative risk was detected among sites with a greater average annual ground surface temperature of the previous year. For the upstream area, snail density was positively associated with NDVI, the 2nd quartile of total precipitation of the previous year (Pre), the 3rd quartile of Pre, and the 4th quartile of Pre. Snail density was negatively associated with Slope.
CONCLUSIONS
Collectively, our study demonstrated a rebound in snail density between 2015 and 2019. In particular, temperature, humidity, vegetation, and human activity were the main drivers affecting the snail abundance in the downstream area of TGD, while precipitation, slope, and vegetation were the main drivers affecting the upstream snail abundance. This evidence can assist the authorities to execute more precise strategies for snail investigation and control.
... Poyang Lake (28 • 22 ′ -29 • 45 ′ N, 115 • 47 ′ -116 • 45 ′ E), located in the middle and lower reaches of the Yangtze River and in the north of Jiangxi Province, is the largest inland freshwater lake in China (Xue et al., 2021). The ecological, environmental and geographical features of Poyang Lake with a watershed area of 1.62 × 10 5 km 2 are suitable for Oncomelania snail growth and breeding, thereby making it be another highly endemic region for schistosomiasis (Xue et al., 2021;Xia et al., 2019). ...
... Poyang Lake (28 • 22 ′ -29 • 45 ′ N, 115 • 47 ′ -116 • 45 ′ E), located in the middle and lower reaches of the Yangtze River and in the north of Jiangxi Province, is the largest inland freshwater lake in China (Xue et al., 2021). The ecological, environmental and geographical features of Poyang Lake with a watershed area of 1.62 × 10 5 km 2 are suitable for Oncomelania snail growth and breeding, thereby making it be another highly endemic region for schistosomiasis (Xue et al., 2021;Xia et al., 2019). In this study, a field survey in marshlands of Poyang Lake from 2012 to 2016 was conducted to investigate and analysis the prevalence of Exorchis sp. and S. japonicum in O. hupensis and S. asotus. ...
... The study was conducted in October from 2012 to 2016 at Shi Li Hu (29 • 25 ′ N, 116 • 01' E) in Xingzi county, Jiangxi Province, which is located on the western bank of the Poyang Lake in southern China (Fig. 1). The lake usually maintains a higher water level between May and September every year, and is with a lower temperature in the winter season, making it difficult to collect O. hupensis snails (Xue et al., 2021;Xia et al., 2019). The ecological and geographical features of Poyang Lake are very suitable for O. hupensis snail growth and breeding, and a total of 13 counties (cities, districts) (Xia et al., 2019) including Xingzi county in the areas around the lake are endemic for schistosomiasis japonica. ...
Oncomelania hupensis is the obligate intermediate host of Schistosoma japonicum, highlighting the medical importance of interrupting this unique and long-standing parasite-host interaction in controlling schistosomiasis transmission. It has been reported that a catfish trematode Exorchis sp. could have the potential to function as an effective anti-schistosomal agent in the snail host. However, the feasibility of this eco-friendly biological control strategy should be comprehensively investigated and evaluated in endemic areas for schistosomiasis. In this study, a field survey was conducted from 2012 to 2016 in the marshlands of Poyang Lake, which is one of the highly endemic regions for schistosomiasis in China. Results showed that more than half of Silurus asotus (65.79%) were infected with Exorchis sp., and the average intensity of infection was 14.21 per fish. And the average infection rate of Exorchis sp. in O. hupensis is 1.11%. These findings indicated that there are abundant biological resources for the implementation of this biology control strategy in the marshlands of Poyang Lake. The data presented here provide solid evidences for the practical application of this biological control strategy, thereby contributing to achieving the goals of the elimination of schistosomiasis.
... The impact of environmental change on snail distribution has invoked heated attention. Numerous studies have been conducted to explored the impact of environmental changes on the snail distribution and the spread of schistosomiasis [12][13][14][15][16][17][18][19][20]; however, little is known for its impact on the dynamics of overall snail density [12][13][14][15][16][17][18][19][20]. ...
... The impact of environmental change on snail distribution has invoked heated attention. Numerous studies have been conducted to explored the impact of environmental changes on the snail distribution and the spread of schistosomiasis [12][13][14][15][16][17][18][19][20]; however, little is known for its impact on the dynamics of overall snail density [12][13][14][15][16][17][18][19][20]. ...
Background
Oncomelania hupensis (O. hupensis) snail is the sole intermediate host of Schistosoma japonicum. Environmental changes caused by Three Gorges Dam (TGD), flood and drought, affect the distribution of snail population, and better understanding the dynamics and spatial distribution of snail density is critical for schistosomiasis risk assessment and control for affected areas.
Methods
Data of O. hupensis snail survey between 1990 and 2019 were collected from previous studies in four electronic databases (CNKI, Wanfang, Pubmed, and SCI) and from the national schistosomiasis surveillance. Meta-analysis was conducted to estimate the overall and annual snail densities and their 95% confidence intervals (CIs). Joinpoint model was used to identify the changing trend and inflection point of snail density between 1990 and 2019. Inverse distance weighted (IDW) interpolation was used to determine the spatial distribution of recent snail density.
Results
A total of 3777 snail survey sites (872 for the upstream area and 2905 for the downstream area of the TGD) with a precise location of village or beach were identified. For the downstream area of the TGD, the snail density peaked in 1998 (1.635/0.11m2, 95% CI: 1.220–2.189) and fluctuated at a relatively high level before 2003, and declined steadily from 2003 (1.143/0.11m², 95% CI: 0.905–1.397) to 2012 (0.127/0.11m², 95% CI: 0.081–0.199). The snail density maintained lower than 0.150/0.11m² between 2012 and 2019. Joinpoint model identified that the inflection point of 2003 was statistically significant and the snail density showed a significant downward trend from 2003 to 2012 with an APC of -20.56% (95% CI: -24.15 to -16.80). For the Upstream area of the TGD, the snail density peaked in 2005 (0.760/0.11m2, 95% CI: 0.479–1.207) and was generally greater than 0.300/0.11m2 before 2005. The snail density steadily declined since 2006 and was generally lower than 0.150/0.11m2 after 2011. No inflection point was identified and the snail density showed a significant downward trend from 1990 to 2019 with an APC of -6.05% (95% CI: -7.97 to -7.09). The areas with a relatively high snail density were mainly distributed in Poyang Lake, Dongting Lake, Jianghan Plain, and the Anhui branch of the Yangtze River.
Conclusion
The density of O. hupensis snails showed a fluctuating downward trend in the Yangtze River basin between 1990 and 2019. In the downstream area, the decline of snail density was accelerated after the operation of TGD, and then fluctuated at a relatively low level. Infected areas with a higher density of snails were distributed in Dongting Lake, Poyang Lake, Jianhan Plain, and the Anhui branch of the Yangtze River.
... The epidemics of NTDs are sensitive in different ways to environmental and socioeconomic conditions [27][28][29], so the risk evaluation for NTDs requires data from multiple sources and multiple aspects, such as the geographical distributions of the pathogens, vectors, or host populations, as well as their related environmental determinants [30,31]. Ecological niche models integrate these datasets and utilize statistical approaches for predicting the potential distribution of vector species from survey-based observations [32]. ...
Schistosomiasis caused by Schistosoma japonicum is one of the major neglected tropical diseases worldwide. The snail Oncomelania hupensis is the only intermediate host of S. japonicum, which is recognized as an indicator of the schistosomias occurrence. In order to evaluate the risk of schistosomiasis in China, this work investigate the potential geographical distribution of host snail habitus by developing an ensemble ecological niche model with reference to the suitable environmental factors. The historical records of snail habitus were collected form the national schistosomiasis surveillance program from the year of 2005 to 2014. A total of 25 environmental factors in terms of the climate, geographic, and socioeconomic determinants of snail habitats were collected and geographically coded with reference to the snail data. Based on the correlations among snail habitats and the geographically associated environmental factors, an ensemble ecological niche model was developed by integrating ten standard models, aiming for improving the predictive accuracy. Three indexes are used for model performance evaluation, including receiver operating characteristic curves, kappa statistics, and true skill statistics. The model was used for mapping the risk of schistosomiasis in the middle and lower reaches of the Yangtze River. The results have shown that the predicted risk areas were classified into low risk (4.55%), medium risk (2.01%), and high risk areas (4.40%), accounting for 10.96% of the land area of China. This study demonstrated that the developed ensemble ecological niche models was an effective tool for evaluating the risk of schistosomiasis, particularly for the endemic regions, which were not covered by the national schistosomiasis control program.
... Background With the deepening of global integration, under the influence of factors such as increased population mobility and intensified environmental change, global public health emergencies become more frequent [1][2][3]. Human health is closely linked to animals and the ecological environment [4][5][6], for instance, 60% of known human infectious diseases are zoonotic [7][8][9][10], and about 70% of new zoonotic diseases originate in wild animals [11]. Thus, some scholars put forward the concept of One Health, which integrates human, animal, and environmental health to carry out health promotion work [12,13], the American Veterinary Medical Association first established the One Health Action group in 2007. ...
Background
One Health has become a global consensus to deal with complex health problems. However, the progress of One Health implementation in many countries is still relatively slow, and there is a lack of systematic evaluation index. The purpose of this study was to establish an indicator framework for global One Health Intrinsic Drivers index (GOH-IDI) to evaluate human, animal and environmental health development process globally.
Method
First, 82 studies were deeply analyzed by a grounded theory (GT) method, including open coding, axial coding, and selective coding, to establish a three-level indicator framework, which was composed of three selective codes, 19 axial codes, and 79 open codes. Then, through semi-structured interviews with 28 health-related experts, the indicators were further integrated and simplified according to the inclusion criteria of the indicators. Finally, the fuzzy analytical hierarchy process combined with the entropy weight method was used to assign weights to the indicators, thus, forming the evaluation indicator framework of human, animal and environmental health development process.
Results
An indicator framework for GOH-IDI was formed consisting of three selective codes, 15 axial codes and 61 open codes. There were six axial codes for “Human Health”, of which “Infectious Diseases” had the highest weight (19.76%) and “Injuries and Violence” had the lowest weight (11.72%). There were four axial codes for “Animal Health”, of which “Animal Epidemic Disease” had the highest weight (39.28%) and “Animal Nutritional Status” had the lowest weight (11.59%). Five axial codes were set under “Environmental Health”, among which, “Air Quality and Climate Change” had the highest weight (22.63%) and “Hazardous Chemicals” had the lowest weight (17.82%).
Conclusions
An indicator framework for GOH-IDI was established in this study. The framework were universal, balanced, and scientific, which hopefully to be a tool for evaluation of the joint development of human, animal and environmental health in different regions globally.
