District prediction of cholera risk in China based on environmental factors

Non-serogroup O1/O139 agglutinable Vibrio cholerae: a phylogenetically and genealogically neglected yet emerging potential pathogen of clinical relevance

Somatic antigen agglutinable type-1/139 Vibrio cholerae (SAAT-1/139-Vc) members or O1/O139 V. cholerae have been described by various investigators as pathogenic due to their increasing virulence potential and production of choleragen. Reported cholera outbreak cases around the world have been associated with these choleragenic V. cholerae with high case fatality affecting various human and animals. These virulent Vibrio members have shown genealogical and phylogenetic relationship with the avirulent somatic antigen non-agglutinable strains of 1/139 V. cholerae (SANAS-1/139- Vc) or O1/O139 non-agglutinating V. cholerae (O1/O139-NAG-Vc). Reports on implication of O1/O139-NAGVc members in most sporadic cholera/cholera-like cases of diarrhea, production of cholera toxin and transmission via consumption and/or contact with contaminated water/seafood are currently on the rise. Some reported sporadic cases of cholera outbreaks and observed change in nature has also been tracable to these non-agglutinable Vibrio members (O1/O139-NAGVc) yet there is a sustained paucity of research interest on the non-agglutinable V. cholerae members. The emergence of fulminating extraintestinal and systemic vibriosis is another aspect of SANAS-1/139- Vc implication which has received low attention in terms of research driven interest. This review addresses the need to appraise and continually expand research based studies on the somatic antigen non-serogroup agglutinable type-1/139 V.cholerae members which are currently prevalent in studies of water bodies, fruits/vegetables, foods and terrestrial environment. Our opinion is amassed from interest in integrated surveillance studies, management/control of cholera outbreaks as well as diarrhea and other disease-related cases both in the rural, suburban and urban metropolis.

Mapping climate change's impact on cholera infection risk in Bangladesh

Several studies have investigated how Vibrio cholerae infection risk changes with increased rainfall, temperature, and water pH levels for coastal Bangladesh, which experiences seasonal surges in cholera infections associated with heavy rainfall events. While coastal environmental conditions are understood to influence V. cholerae propagation within brackish waters and transmission to and within human populations, it remains unknown how changing climate regimes impact the risk for cholera infection throughout Bangladesh. To address this, we developed a random forest species distribution model to predict the occurrence probability of cholera incidence within Bangladesh for 2015 and 2050. We developed a random forest model trained on cholera incidence data and spatial environmental raster data to be predicted to environmental data for the year of training (2015) and 2050. From our model's predictions, we generated risk maps for cholera occurrence for 2015 and 2050. Our best-fitting model predicted cholera occurrence given elevation and distance to water. Generally, we find that regions within every district in Bangladesh experience an increase in infection risk from 2015 to 2050. We also find that although cells of high risk cluster along the coastline predominantly in 2015, by 2050 high-risk areas expand from the coast inland, conglomerating around surface waters across Bangladesh, reaching all but the northwestern-most district. Mapping the geographic distribution of cholera infections given projected environmental conditions provides a valuable tool for guiding proactive public health policy tailored to areas most at risk of future disease outbreaks.

Complete Genome Sequences of Seven Vibrio cholerae Phages Isolated in China

The complete genome sequences of seven closely related Vibrio cholerae phages isolated from environmental sites in southeastern China are reported here. Phages QH, CJY, H1, H2, H3, J2, and J3 are members of the Podoviridae family and are highly similar to the previously sequenced Vibrio phages VP2, VP5, and phiVC8.

Ecological Niche Modeling of Risk Factors for H7N9 Human Infection in China

China was attacked by a serious influenza A (H7N9) virus in 2013. The first human infection case was confirmed in Shanghai City and soon spread across most of eastern China. Using the methods of Geographic Information Systems (GIS) and ecological niche modeling (ENM), this research quantitatively analyzed the relationships between the H7N9 occurrence and the main environmental factors, including meteorological variables, human population density, bird migratory routes, wetland distribution, and live poultry farms, markets, and processing factories. Based on these relationships the probability of the presence of H7N9 was predicted. Results indicated that the distribution of live poultry processing factories, farms, and human population density were the top three most important determinants of the H7N9 human infection. The relative contributions to the model of live poultry processing factories, farms and human population density were 39.9%, 17.7% and 17.7%, respectively, while the maximum temperature of the warmest month and mean relative humidity had nearly no contribution to the model. The paper has developed an ecological niche model (ENM) that predicts the spatial distribution of H7N9 cases in China using environmental variables. The area under the curve (AUC) values of the model were greater than 0.9 (0.992 for the training samples and 0.961 for the test data). The findings indicated that most of the high risk areas were distributed in the Yangtze River Delta. These findings have important significance for the Chinese government to enhance the environmental surveillance at multiple human poultry interfaces in the high risk area.

Environmental factor analysis of cholera in China using remote sensing and geographical information systems

Cholera is one of a number of infectious diseases that appears to be influenced by climate, geography and other natural environments. This study analysed the environmental factors of the spatial distribution of cholera in China. It shows that temperature, precipitation, elevation, and distance to the coastline have significant impact on the distribution of cholera. It also reveals the oceanic environmental factors associated with cholera in Zhejiang, which is a coastal province of China, using both remote sensing (RS) and geographical information systems (GIS). The analysis has validated the correlation between indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local number of cholera cases based on 8-year monthly data from 2001 to 2008. The results show the number of cholera cases has been strongly affected by the variables of SST, SSH and OCC. Utilizing this information, a cholera prediction model has been established based on the oceanic and climatic environmental factors. The model indicates that RS and GIS have great potential for designing an early warning system for cholera.