## Hémaho Beaugard Taboe

Doctorant

Research interests: Biomathematics and mathematical modeling, Model fitting, identifiability, and sensitivity analysis.

PhD Student

LABEF

### Background

I have a Master of Science in Biostatistics with two defining research experiences on infectious diseases modeling. The first was during my MSc research. At that time, I developed and analyzed a mathematical model for the dynamics of Lassa fever virus (LFV) in West Africa. My other experience is on COVID-19 pandemic modeling. Currently I have two Scientific publications on that pandemic. In the first paper published in Mathematical Biosciences, we have investigated the impact of non-pharmaceutical interventions on COVID-19 in West Africa. In the second, we have modelled the trend of COVID-19 and calculated some key parameters of the pandemic spreading in each of the 16 countries in West Africa.

socio-economic survey conducting; data collection with smartphones; data management; statistical analysis/modeling. In addition, I have used and become familiar with several statistical software’s including:  R, Matlab, Maple, Stata, SPSS, CSPro, ODK-collect, Eviews, Arcview etc.

### Research project

• Title: Coupled economic-disease network models for existing and emerging infectious diseases in West Africa.
• Aim: Develop and use mathematical modeling approach to explain the burden of Infectious diseases in West Africa (measured in terms of the reported number of cases, hospitalizations, deaths, socio-economic impacts). Our applications are on COVID-19 pandemic and Lassa Fever in West Africa.

• Articles: 02

### Publications

• Hémaho B. Taboe, Kolawolé V. Salako, James M. Tison, Calistus N. Ngonghala, Romain Glèlè Kakaï. Predicting COVID-19 spread in the face of control measures in West Africa, Mathematical Biosciences, 328, 108431, 2020, https://doi.org/10.1016/j.mbs.2020.108431
• Sewanou H. Honfo, Hémaho B. Taboe, Romain Glèlè Kakaï. Modeling COVID-19 dynamics in the sixteen West African countries, 2020. (under review in African Journal of Applied Statistics)  https://doi.org/10.1101/2020.09.04.20188532