Naffeti Bechir

Dr. Bechir Naffeti is a bio-mathematicians in laboratory of Bio-Informatics, Bio-Mathematics and Bio-Statistics of Pasteur Institute of Tunis. Detail-oriented, accurate and analytical mathematician with a solid understanding of the modeling of infectious diseases, mono and multi-objective optimization algorithms. He is currently a postdoctoral researcher at the Pasteur Institute of Tunis. Passionate about coding with excellent knowledge of Python, MATLAB, SPSS, R coding as well as all office software. Able to propose a model or a simulation of the situation on which the whole team is working by bringing my own perspective to a problem which is approached from various angles by specialized people.

EDUCATION

National Diploma of Doctorate in Mathematics

RESEARCH INTERESTS

Modeling of infectious diseases.
mono and multi-objective optimization algorithms.
Modeling of covid-19

Scopus Publications

Quantifying population-level sexual risk behavior through HSV-2 transmission dynamics in the United States, 1950–2020
Bechir S. Naffeti, Houssein H. Ayoub, Laith J. Abu-Raddad
Scientific Reports, 2025
The risk of acquiring a sexually transmitted infection, such as herpes simplex virus type 2 (HSV-2), is shaped by sexual risk behavior-an aggregate measure influenced not only by an individual's sexual behavior but also by the broader sexual network. This study quantified the temporal and age-specific variations in sexual risk behavior for HSV-2 infection in the United States population between 1950 and 2020. A population-level mathematical model was used to describe HSV-2 transmission and was calibrated with ten rounds of nationally representative, population-based data from the National Health and Nutrition Examination Survey (NHANES). The model produced robust fits to the age-specific, sex-specific, and temporal HSV-2 seroprevalence data across the NHANES rounds. Sexual risk behavior gradually increased starting in the early 1960s, peaked in the early 1980s, and then steadily declined through 2020. The decline was particularly pronounced in the 1990s, when sexual risk behavior dropped sharply compared to the elevated levels of the early 1980s. Sexual risk behavior was highest among individuals aged 15-24 years and steadily declined with increasing age. The analysis identified a distinct wave of sexual risk behavior that began in the early 1960s, peaked in the early 1980s, and subsequently declined.
Modeling COVID-19 dynamics in the Basque Country: characterizing population immunity profile from 2020 to 2022
Bechir Naffeti, Zeineb Ounissi, A. K. Srivastav, N. Stollenwerk, Joseba Bidaurrazaga Van-Dierdonck, M. Aguiar
BMC Infectious Diseases, 2025
COVID-19, caused by SARS-CoV-2, has spread globally, presenting a significant public health challenge. Vaccination has played a critical role in reducing severe disease and deaths. However, the waning of immunity after vaccination and the emergence of immune-escape variants require the continuation of vaccination efforts, including booster doses, to maintain population immunity. This study models the dynamics of COVID-19 in the Basque Country, Spain, aiming to characterize the population’s immunity profile and assess its impact on the severity of outbreaks from 2020 to 2022. A SIR/DS model was developed to analyze the interplay of virus-specific and vaccine-induced immunity. The model includes three levels of immunity, with boosting effects from reinfection and/or vaccination. It was validated using empirical daily case data from the Basque Country. The model tracks shifts in immunity status and their effects on disease dynamics over time. The COVID-19 epidemic in the Basque Country progressed through three distinct phases, each shaped by dynamic interactions between virus transmission, public health interventions, and vaccination efforts. The initial phase was marked by a rapid surge in cases, followed by a decline due to strict public health measures, with a seroprevalence of $$1.3\%$$ . In the intermediate phase, multiple smaller outbreaks emerged as restrictions were relaxed and new variants, such as Alpha and Delta, appeared. During this period, reinfection rates reached $$20\%$$ , and seroprevalence increased to $$32\%$$ . The final phase, dominated by the Omicron variant, saw a significant rise in cases driven by waning immunity and the variant’s high transmissibility. Notably, $$34\%$$ of infections during this phase occurred in the naive population, with seroprevalence peaking at $$43\%$$ . Across all phases, the infection of naive and unvaccinated individuals contributed significantly to the severity of outbreaks, emphasizing the critical role of vaccination in mitigating disease impact. The findings underscore the importance of continuous monitoring and adaptive public health strategies to mitigate the evolving epidemiological and immunological landscape of COVID-19. Dynamic interactions between immunity levels, reinfections, and vaccinations are critical in shaping outbreak severity and guiding evidence-based interventions.
A Branch and Bound algorithm for multidimensional Holder optimization: Estimation of the age-dependent viral hepatitis A infection force
Bechir Naffeti, Hamadi Ammar, Walid Ben Aribi
Mathematics and Computers in Simulation, 2024
Comparative reconstruction of SARS-CoV-2 transmission in three African countries using a mathematical model integrating immunity data
Bechir Naffeti, Walid BenAribi, Amira Kebir, Maryam Diarra, Matthieu Schoenhals, Inès Vigan-Womas, Koussay Dellagi, Slimane BenMiled
IJID Regions, 2024
Objectives: Africa has experienced fewer COVID-19 cases and deaths than other regions, with a contrasting epidemiological situation between countries, raising questions regarding the determinants of disease spread in Africa. Methods: We built a susceptible-exposed-infected-recovered model including COVID-19 mortality data where recovery class is structured by specific immunization and modeled by a partial differential equation considering the opposed effects of immunity decline and immunization. This model was applied to Tunisia, Senegal, and Madagascar. Results: Senegal and Tunisia experienced two epidemic phases. Initially, infections emerged in naive individuals and were limited by social distancing. Variants of concern (VOCs) were also introduced. The second phase was characterized by successive epidemic waves driven by new VOCs that escaped host immunity. Meanwhile, Madagascar demonstrated a different profile, characterized by longer intervals between epidemic waves, increasing the pool of susceptible individuals who had lost their protective immunity. The impact of vaccination on model parameters in Tunisia and Senegal was evaluated. Conclusions: Loss of immunity and vaccination-induced immunity have played crucial role in controlling the African pandemic. SARS-CoV-2 has become endemic now and will continue to circulate in African populations. However, previous infections provide significant protection against severe diseases, thus providing a basis for future vaccination strategies.
Complex Network Approaches for Epidemic Modeling: A Case Study of COVID-19
Akhil Kumar Srivastav, Vizda Anam, Rubén Blasco-Aguado, Carlo Delfin S. Estadilla, Bruno V. Guerrero, Amira Kebir, Luís Mateus, Bechir Naffeti, Fernando Saldaña, Vanessa Steindorf, Nico Stollenwerk
Modeling and Simulation in Science Engineering and Technology, 2024
A branch and bound algorithm for Holder bi-objective optimization. Implementation to multidimensional optimization
Hamadi Ammar, Bechir Naffeti
Mathematics and Computers in Simulation, 2023
Spatio-temporal evolution of the COVID-19 across African countries
Bechir Naffeti, Sebastien Bourdin, Walid Ben Aribi, Amira Kebir, Slimane Ben Miled
Frontiers in Public Health, 2022
The aim of this study is to make a comparative study on the reproduction number R0 computed at the beginning of each wave for African countries and to understand the reasons for the disparities between them. The study covers the two first years of the COVID-19 pandemic and for 30 African countries. It links pandemic variables, reproduction number R0, demographic variable, median age of the population, economic variables, GDP and CHE per capita, and climatic variables, mean temperature at the beginning of each waves. The results show that the diffusion of COVID-19 in Africa was heterogeneous even between geographical proximal countries. The difference of the basic reproduction number R0 values is very large between countries and is significantly correlated with economic and climatic variables GDP and temperature and to a less extent with the mean age of the population.
Global Stability and Numerical Analysis of a Compartmental Model of the Transmission of the Hepatitis A Virus (HAV): A Case Study in Tunisia
Walid Ben Aribi, Bechir Naffeti, Kaouther Ayouni, Hamadi Ammar, Henda Triki, Slimane Ben Miled, Amira Kebir
International Journal of Applied and Computational Mathematics, 2022
A new trisection method for solving Lipschitz bi-objective optimization problems
Bechir Naffeti, Hamadi Ammar
Mathematics and Computers in Simulation, 2021
Hepatitis a virus infection in Central-West Tunisia: An age structured model of transmission and vaccination impact
Kaouther Ayouni, Bechir Naffeti, Walid Ben Aribi, Jihène Bettaieb, Walid Hammami, Afif Ben Salah, Hamadi Ammar, Slimane Ben Miled, Henda Triki
BMC Infectious Diseases, 2020
Background The epidemiological pattern of hepatitis A infection has shown dynamic changes in many parts of the world due to improved socio-economic conditions and the accumulation of seronegative subjects, which leads to possible outbreaks and increased morbidity rate. In Tunisia, the epidemiological status of hepatits A virus is currently unknown. However, over the past years higher numbers of symptomatic hepatitis A virus infection in school attendants and several outbreaks were reported to the Ministry of Health, especially from regions with the lowest socio-economic levels in the country. The aim of this study was to investigate the current seroprevalence of hepatitis A virus antibodies in central-west Tunisia and assess the impact of hepatitis A virus vaccination on hepatitis A epidemiology. Methods Serum samples from 1379 individuals, aged 5–75 years, were screened for hepatitis A virus antibodies. Adjusted seroprevalence, incidence and force of infection parameters were estimated by a linear age structured SEIR (Susceptible-Exposed-Infectious-Recovered) compartmental model. A vaccine model was then constructed to assess the impact on hepatitis A virus epidemiology of 3 scenarios of vaccination strategies: one dose at 12-months of age, one dose at 6-years and one dose at 12-months and another at 6-years of age during 6 years. Results A rapid increase in anti-hepatitis A virus seroprevalence was noted during infancy and adolescence: 47% of subjects under 10-years-old are infected; the prevalence increases to 77% at 15-years and reaches 97% in subjects aged 30-years. The force of infection is highest between 10 and 30-years of age and the incidence declines with increasing age. The vaccine model showed that the 3-scenarios lead to a significant reduction of the fraction of susceptibles. The two doses scenario gives the best results. Single-dose vaccination at 6-years of age provides more rapid decrease of disease burden in school-aged children, as compared to single-dose vaccination at 12-months, but keeps with a non-negligible fraction of susceptibles among children < 6-years. Conclusions Our study confirms the epidemiological switch from high to intermediate endemicity of hepatitis A virus in Tunisia and provides models that may help undertake best decisions in terms of vaccinations strategies.
Filled Function Method for Nonlinear Model Predictive Control
Hajer Degachi, Bechir Naffeti, Wassila Chagra, Moufida Ksouri
Mathematical Problems in Engineering, 2018

Publications

Spatio-temporal evolution of the COVID-19 across African countries.
A branch and bound algorithm for Holder bi-objective optimization. Implementation to multidimensional optimization.
Global Stability and Numerical Analysis of a Compartmental Model of the Transmission of the Hepatitis A Virus (HAV): A Case Study in Tunisia.
Hepatitis a virus infection in Central-West Tunisia: an age structured model of transmission and vaccination impact
A new trisection method for solving Lipschitz bi-objective optimization problems.
Filled function method for nonlinear model predictive control.
Non-pharmaceutical interventions and COVID-19 vaccination strategies in Senegal: a modelling study.