Toussaint Mitchodigni
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Toussaint Mitchodigni has a total of 13 co-authors. Here are the top co-authors by number of shared publications:
- Anders Dalsgaard
Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, 1870 Frederiksberg, Denmark
1 shared publication - Anges Yadouleton
Laboratory of Viral Haemorrhagic Fevers and Arboviruses of Benin, Cotonou, Benin
1 shared publication - Arnaud Soha
Research Unit in Applied Microbiology and Pharmacology of Natural Substances, Research Laboratory in Applied Biology, Polytechnic School of Abomey-Calavi, University of Abomey-Calavi, Abomey-Calavi 01 BP 526, Benin
1 shared publication - Casimir Yelognisse Da‐Allada
LaGEA/ENSTP/UNSTIM Abomey Benin
1 shared publication - Cossi Georges Epiphane Degbe
Institut de Recherches Halieutiques et Océanologiques du Benin (IRHOB), Cotonou 03 BP 1665, Benin
1 shared publication - Frédéric Bonou
International Chair in Mathematical Physics and Applications (ICMPA–UNESCO Chair), University of Abomey-Calavi, Abomey-Calavi 01 BP 526, Benin
1 shared publication
Latest Publications
- Open Access
Impact of Weather and Climate Drivers on Waterborne Diseases: A Systematic Review of Mechanisms and Models
Global climate change significantly alters environmental and health dynamics, posing a major 21st-century public health threat. Diseases commonly transmitted through water and/or food (diarrhea, cholera, dysentery) are particularly sensitive to these changes. While numerous studies have investigated the climate impacts on waterborne diseases, a critical assessment of the applied methodologies and the consistencies of their outcomes is lacking. This systematic review synthesizes the impact of climate change on waterborne diseases, focusing on analytical methods and predictive models used to explain disease presence or abundance. We further evaluate the strengths and limitations of each approach, identifying key gaps for future research. We analyzed 78 indexed research articles published between 1996 and 2023. Our findings demonstrate that diverse climate-related extreme events, including precipitation, flooding, and drought, substantially impact waterborne disease incidence. Additionally, temperature, salinity, humidity, sunshine duration, wind patterns, and specific water quality parameters play significant roles, with regional variations observed. Sensitivity analysis methods and mathematical models are employed to assess sensitivities, quantify correlations, examine impacts, and predict risks. Based on these findings, we urge future research to prioritize elucidating mechanisms and developing models that leverage climate data to predict disease presence or abundance accurately and quantitatively.
Open AccessImpact of Weather and Climate Drivers on Waterborne Diseases: A Systematic Review of Mechanisms and Models
Global climate change significantly alters environmental and health dynamics, posing a major 21st-century public health threat. Diseases commonly transmitted through water and/or food (diarrhea, cholera, dysentery) are particularly sensitive to these changes. While numerous studies have investigated the climate impacts on waterborne diseases, a critical assessment of the applied methodologies and the consistencies of their outcomes is lacking. This systematic review synthesizes the impact of climate change on waterborne diseases, focusing on analytical methods and predictive models used to explain disease presence or abundance. We further evaluate the strengths and limitations of each approach, identifying key gaps for future research. We analyzed 78 indexed research articles published between 1996 and 2023. Our findings demonstrate that diverse climate-related extreme events, including precipitation, flooding, and drought, substantially impact waterborne disease incidence. Additionally, temperature, salinity, humidity, sunshine duration, wind patterns, and specific water quality parameters play significant roles, with regional variations observed. Sensitivity analysis methods and mathematical models are employed to assess sensitivities, quantify correlations, examine impacts, and predict risks. Based on these findings, we urge future research to prioritize elucidating mechanisms and developing models that leverage climate data to predict disease presence or abundance accurately and quantitatively.