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Updated: Dec 12, 2025

Laboratory Techniques Used to Maintain and Differentiate Biotypes of Vibrio cholerae Clinical and Environmental Isolates
Published on: May 30, 2017
Volcanic activity controls cholera outbreaks in the East African Rift
Doudou Batumbo Boloweti1, Patrick Giraudoux1, Catherine Deniel2
1UMR CNRS 6249 Chrono-Environnement, University of Bourgogne Franche Comté, Besançon, France.
Abstract:
We hypothesized that Cholera (Vibrio cholerae) that appeared along Lake Kivu in the African Rift in the seventies, might be controlled by volcano-tectonic activity, which, by increasing surface water and groundwater salinity and temperature, may partly rule the water characteristics of Lake Kivu and promote V. cholerae proliferation. Volcanic activity (assessed weekly by the SO2 flux of Nyiragongo volcano plume over the 2007-2012 period) is highly positively correlated with the water conductivity, salinity and temperature of the Kivu lake. Over the 2007-2012 period, these three parameters were highly positively correlated with the temporal dynamics of cholera cases in the Katana health zone that border the lake. Meteorological variables (air temperature and rainfall), and the other water characteristics (namely pH and dissolved oxygen concentration in lake water) were unrelated to cholera dynamics over the same period. Over the 2016-2018 period, we sampled weekly lake water salinity and conductivity, and twice a month vibrio occurrence in lake water and fish. The abundance of V. cholerae in the lake was positively correlated with lake salinity, temperature, and the number of cholera cases in the population of the Katana health zone. V. cholerae abundance in fishes was positively correlated with V. cholerae abundance in lake water, suggesting that their consumption directly contaminate humans. The activity of the volcano, by controlling the physico-chemical characteristics of Lake Kivu, is therefore a major determinant of the presence of the bacillus in the lake. SO2 fluxes in the volcano plume can be used as a tool to predict epidemic risks.
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