The prediction of clinical cases of infectious diseases using variant information obtained from wastewater
The COVID-19 pandemic has shown the importance of tracking the spread of pathogens throughout the community before symptoms appear, so that appropriate measures can be taken to limit the spread of disease. During the initial stages of an epidemic, there are multiple pathogenic variants present with varying levels of traits such as infection rate, reproductive rate, and lethality. It is important to incorporate this information when predicting which future dominant strain will affect the population, particularly with viruses due to their rapid spread and mutation within a community. Our goal is to create a model that can correlate trends between the information from wastewater with potential changes in case number so that future epidemics can be predicted before the first clinical cases appear within a city.
Tohoku University – Present
Disaster Risk Management in International Course in Civil and Environmental Engineering (DRM in I-CEEC)
California State University, Long Beach – 2022
Chemical Engineering, B.S.
Research Topic: Improvements in methanol and syngas production using artificial photosynthesis techniques.
University of California, Davis – 2016
Biochemistry and Molecular Biology, B.S.
Research Topic: Comparison of vegetable crop growth rates in hydroponic and aquaponic systems
Licenses & Certifications
- Engineer-in-Training – California Board of Professional Engineers, Land Surveyors, and Geologists
- Water Treatment Plant Operator, Grade II – California State Water Board
- Water Distribution Plant Operator, Grade II – California State Water Board
- Luhur Akbar DEVIANTO
- Sewwandi BANDARA
- Aken Puti WANGUYUN
- Katayoun AMIRFARD
- Mohammadreza VESALINASEH
- 三浦 耀平
- 飯塚 勇仁
- 小山 寛貴
- Yu-bing LI
- 高山 峻
- Marcus SANCHEZ
- Jarin TASNIM
- Lucas MARIJANOVIC
- 澤田 杏樹
- 鈴木 蓮
- YiLei WANG
- 渡部 寛生