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1. MODELING CHOLERA TRANSMISSION UNDER DISEASE CONTROL MEASURES

   https://doi.org/10.1142/S0218339021400015  

   BROWN, MARGARET; JIANG, MIKO; YANG, CHAYU; WANG, JIN (June 2021, Journal of Biological Systems)

   null (Ed.)

   We present a new mathematical model to investigate the transmission dynamics of cholera under disease control measures that include education programs and water sanitation. The model incorporates the impact of education programs into the disease transmission rates and that of water sanitation into the environmental pathogen dynamics. We conduct a detailed analysis to the autonomous system of the model and establish the local and global stabilities of its equilibria that characterize the threshold dynamics of cholera. We then perform an optimal control study on the general model with time-dependent controls and explore effective approaches to implement the education programs and water sanitation while balancing their costs. Our analysis and simulation highlight the complex interaction among the direct and indirect transmission pathways of the disease, the intrinsic growth of the environmental pathogen and the impact of multiple control measures, and their roles in collectively shaping the transmission dynamics of cholera. 

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2. Anticipatory decision-making for cholera in Malawi

   https://doi.org/10.1128/mbio.00529-23  

   Jutla, Antarpreet; Usmani, Moiz; Brumfield, Kyle D.; Singh, Komalpreet; McBean, Fergus; Potter, Amy; Gutierrez, Angelica; Gama, Samuel; Huq, Anwar; Colwell, Rita R. (December 2023, mBio)

   Hazen, Terry C. (Ed.)

   Climate change raises an old disease to a new level of public health threat. The causative agent,Vibrio cholerae, native to aquatic ecosystems, is influenced by climate and weather processes. The risk of cholera is elevated in vulnerable populations lacking access to safe water and sanitation infrastructure. Predictive intelligence, employing mathematical algorithms that integrate earth observations and heuristics derived from microbiological, sociological, and weather data, can provide anticipatory decision-making capabilities to reduce the burden of cholera and save human lives. An example offered here is the recent outbreak of cholera in Malawi, predicted in advance by such algorithms. 

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3. El Niño and the shifting geography of cholera in Africa

   https://doi.org/10.1073/pnas.1617218114  

   Moore, Sean M.; Azman, Andrew S.; Zaitchik, Benjamin F.; Mintz, Eric D.; Brunkard, Joan; Legros, Dominique; Hill, Alexandra; McKay, Heather; Luquero, Francisco J.; Olson, David; et al (April 2017, Proceedings of the National Academy of Sciences)
4. Cholera Toxin as a Probe for Membrane Biology

   https://doi.org/10.3390/toxins13080543  

   Kenworthy, Anne K.; Schmieder, Stefanie S.; Raghunathan, Krishnan; Tiwari, Ajit; Wang, Ting; Kelly, Christopher V.; Lencer, Wayne I. (August 2021, Toxins)

   Cholera toxin B-subunit (CTxB) has emerged as one of the most widely utilized tools in membrane biology and biophysics. CTxB is a homopentameric stable protein that binds tightly to up to five GM1 glycosphingolipids. This provides a robust and tractable model for exploring membrane structure and its dynamics including vesicular trafficking and nanodomain assembly. Here, we review important advances in these fields enabled by use of CTxB and its lipid receptor GM1. 

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5. A multi-scale cholera model linking between-host and within-host dynamics

   https://doi.org/10.1142/S1793524518500341  

   Yang, Chayu; Posny, Drew; Bao, Feng; Wang, Jin (April 2018, International Journal of Biomathematics)

   We propose a multi-scale modeling framework to investigate the transmission dynamics of cholera. At the population level, we employ a SIR model for the between-host transmission of the disease. At the individual host level, we describe the evolution of the pathogen within the human body. The between-host and within-host dynamics are connected through an environmental equation that characterizes the growth of the pathogen and its interaction with the hosts outside the human body. We put a special emphasis on the within-host dynamics by making a distinction for each individual host. We conduct both mathematical analysis and numerical simulation for our model in order to explore various scenarios associated with cholera transmission and to better understand the complex, multi-scale disease dynamics. 

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