scholarly journals Spatio-temporal variations of emerging sites infested with schistosome-transmitting Oncomelania hupensis in Hunan Province, China, 1949–2016

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Shengming Li ◽  
Ying Shi ◽  
Weicheng Deng ◽  
Guanghui Ren ◽  
Hongbin He ◽  
...  

Abstract Background Constant emerging sites infested with Oncomelania hupensis (O. hupensis) impede the goal realization of eliminating schistosomiasis. The study assessed the spatial and temporal distributions of new Oncomelania snail habitats in Hunan Province from 1949 to 2016. Methods We used the data from annual snail surveys throughout Hunan Province for the period from 1949 to 2016. Global Moran’s I, Anselin local Moran’s I statistics (LISA) and a retrospective space-time permutation model were applied to determine the spatial and temporal distributions of emerging snail-infested sites. Results There were newly discovered snail-infested sites almost every year in 1949–2016, except for the years of 1993, 2009 and 2012. The number of emerging sites varied significantly in the five time periods (1949–1954, 1955–1976, 1977–1986, 1986–2003 and 2004–2016) (H = 25.35, p < 0.05). The emerging sites lasted 37.52 years in marshlands, 30.04 years in hills and 24.63 at inner embankments on average, with the values of Global Moran’s I being 0.52, 0.49 and 0.44, respectively. High-value spatial clusters (HH) were mainly concentrated along the Lishui River and in Xiangyin County. There were four marshland clusters, two hill clusters and three inner embankment clusters after 1976. Conclusions Lower reaches of the Lishui River and the Dongting Lake estuary were the high-risk regions for new Oncomelania snail habitats with long durations. Snail surveillance should be strengthened at stubborn snail-infested sites at the inner embankments. Grazing prohibition in snail-infested grasslands should be a focus in marshlands. The management of bovines in Xiangyin County is of great importance.

2021 ◽  
Author(s):  
Yan-Feng Gong ◽  
Jia-Xin Feng ◽  
Zhuo-Wei Luo ◽  
Jing-Bo Xue ◽  
Zhao-Yu Guo ◽  
...  

Abstract Background: There is a continuous decline in the prevalence of schistosomiasis and the number of Schistosoma japonicum infections in humans and livestock in China. However, there are a large number of factors that have not been resolved and which may contribute to future transmission of schistosomiasis. These include a range of sources for S. japonicum infection, difficulty in management of S. japonicum sources of infection, frequent emergence and re-emergence of Oncomelania hupensis snail habitats, and the problematic elimination of snail habitats. These factors challenge progress towards the elimination of schistosomiasis in China.Methods: Based on multi-stage continuous downscaling of sentinel monitoring, county-based schistosomiasis surveillance data were captured from the national schistosomiasis surveillance sites of China from 2005 to 2019. The data included S. japonicum infections in humans, livestock, and O. hupensis. The spatio-temporal trends for schistosomiasis were detected using a Joinpoint regression model, with a standard deviational ellipse (SDE) tool, which determined the central tendency and dispersion in spatial distribution of schistosomiasis. Further, spatio-temporal clusters of S. japonicum infections in humans, livestock, and O. hupensis were evaluated by Poisson model. Results: The prevalence of S. japonicum human infections was reduced from 2.06% to zero based on the national schistosomiasis surveillance sites of China during the period from 2005 to 2019, with a reduction from 9.42% to zero for the prevalence of S. japonicum infections in livestock, and from 0.26% to zero for the prevalence of S. japonicum infections in O. hupensis. The decline in prevalence of S. japonicum infections in humans, livestock, and O. hupensis was statistically significant from 2005 to 2019 (P < 0.01). There was an exception to the decline in S. japonicum infections in livestock during the period from 2008 to 2012. Using an SDE tool, schistosomiasis-affected regions were reduced yearly from 2005 to 2014 in the endemic provinces of Hunan, Hubei, Jiangxi, and Anhui, as well as in the Poyang and Dongting Lake regions. Poisson model revealed 11 clusters of S. japonicum human infections, six clusters of S. japonicum infections in livestock, and nine clusters of S. japonicum infections in O. hupensis. The clusters of human infection were found to be highly consistent with clusters of S. japonicum infections in livestock and O. hupensis. These clusters were in the five provinces of Hunan, Hubei, Jiangxi, Anhui, and Jiangsu, as well as along the middle and lower reaches of the Yangtze River. Humans, livestock, and O. hupensis infections with S. japonicum were mainly concentrated in the north of the Hunan Province, south of the Hubei Province, north of the Jiangxi Province, and southwestern portion of Anhui Province. In the two mountainous provinces of Sichuan and Yunnan; human, livestock, and O. hupensis infections with S. japonicum were mainly concentrated in the northwestern portion of the Yunnan Province, the Daliangshan area in the south of Sichuan Province, and the hilly regions in the middle of Sichuan Province. Conclusions: This study demonstrate a significant spatio-temporal heterogeneity of schistosomiasis in China. A remarkable decline in endemic schistosomiasis was observed between 2005 and 2019. However, there continues to be a long-term risk of schistosomiasis transmission in local areas, with high-risk areas primarily located in the Poyang Lake and Dongting Lake regions, with frequent acute S. japonicum infections. Using a One Health approach, further reinforcement of an integrated schistosomiasis control strategy, with an emphasis on the sources of S. japonicum infection, is required to facilitate the elimination of schistosomiasis in China by 2030.


2012 ◽  
Vol 20 (3) ◽  
pp. 356-362 ◽  
Author(s):  
Xiao-Lin YANG ◽  
Zhen-Wei SONG ◽  
Hong WANG ◽  
Quan-Hong SHI ◽  
Fu CHEN ◽  
...  

2018 ◽  
Author(s):  
Hossein Sahour ◽  
◽  
Mohamed Sultan ◽  
Karem Abdelmohsen ◽  
Sita Karki ◽  
...  

Author(s):  
Antonio A. S. Balieiro ◽  
Andre M. Siqueira ◽  
Gisely C. Melo ◽  
Wuelton M. Monteiro ◽  
Vanderson S. Sampaio ◽  
...  

In Brazil, malaria caused by Plasmodium vivax presents control challenges due to several reasons, among them the increasing possibility of failure of P. vivax treatment due to chloroquine-resistance (CQR). Despite limited reports of CQR, more extensive studies on the actual magnitude of resistance are still needed. Short-time recurrences of malaria cases were analyzed in different transmission scenarios over three years (2005, 2010, and 2015), selected according to malaria incidence. Multilevel models (binomial) were used to evaluate association of short-time recurrences with variables such as age. The zero-inflated Poisson scan model (scanZIP) was used to detect spatial clusters of recurrences up to 28 days. Recurrences compose less than 5% of overall infection, being more frequent in the age group under four years. Recurrences slightly increased incidence. No fixed clusters were detected throughout the period, although there are clustering sites, spatially varying over the years. This is the most extensive analysis of short-time recurrences worldwide which addresses the occurrence of P. vivax CQR. As an important step forward in malaria elimination, policymakers should focus their efforts on young children, with an eventual shift in the first line of malaria treatment to P. vivax.


2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Kassim S. Mwitondi ◽  
Isaac Munyakazi ◽  
Barnabas N. Gatsheni

Abstract In the light of the recent technological advances in computing and data explosion, the complex interactions of the Sustainable Development Goals (SDG) present both a challenge and an opportunity to researchers and decision makers across fields and sectors. The deep and wide socio-economic, cultural and technological variations across the globe entail a unified understanding of the SDG project. The complexity of SDGs interactions and the dynamics through their indicators align naturally to technical and application specifics that require interdisciplinary solutions. We present a consilient approach to expounding triggers of SDG indicators. Illustrated through data segmentation, it is designed to unify our understanding of the complex overlap of the SDGs by utilising data from different sources. The paper treats each SDG as a Big Data source node, with the potential to contribute towards a unified understanding of applications across the SDG spectrum. Data for five SDGs was extracted from the United Nations SDG indicators data repository and used to model spatio-temporal variations in search of robust and consilient scientific solutions. Based on a number of pre-determined assumptions on socio-economic and geo-political variations, the data is subjected to sequential analyses, exploring distributional behaviour, component extraction and clustering. All three methods exhibit pronounced variations across samples, with initial distributional and data segmentation patterns isolating South Africa from the remaining five countries. Data randomness is dealt with via a specially developed algorithm for sampling, measuring and assessing, based on repeated samples of different sizes. Results exhibit consistent variations across samples, based on socio-economic, cultural and geo-political variations entailing a unified understanding, across disciplines and sectors. The findings highlight novel paths towards attaining informative patterns for a unified understanding of the triggers of SDG indicators and open new paths to interdisciplinary research.


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