Bio

My research focus is infectious disease modeling and optimal control theory. Besides, I am interested in machine learning algorithms and statistical modeling. In my research, I am using mathematical tools to understand the behavior of the diseases and manage the control strategies for the diseases. I’ve been involved in a couple of research projects for building new mathematical models for Leptospirosis infectious disease and I am currently working on schistosomiasis infectious disease to predict future projection of the disease propagation under climate change.

Boards, Advisory Committees, Professional Organizations

  • Officer, Student chapter of Society for Industrial and Applied Mathematics (2017 - 2019)
  • President, University of Tennessee Turkish Student Association (2016 - 2019)

Professional Education

  • Doctor of Philosophy, University of Tennessee Knoxville (2019)
  • MS, University of Tennessee Knoxville, Mathematics with Concentration in Mathematical Ecology/Evolution (2016)
  • MS, Gaziantep University, Applied Mathematics (2011)
  • BSc, Mersin University, Mathematics (2009)

Stanford Advisors

Community and International Work

  • Integrated risk mapping and targeted snail control to support schistosomiasis elimination in Brazil and Cote d’Ivoire under future climate change

    Ongoing Project

    No

    Opportunities for Student Involvement

    No

  • Researcher

    Topic

    Leptospirosis Modeling

    Populations Served

    20

    Location

    US

    Ongoing Project

    No

    Opportunities for Student Involvement

    No

Contact

  • Academic
    iaslan@stanford.edu
    University - Scholar Department: Biology Position: Postdoctoral Scholar

Additional Info

Links

Research Interests

  • Data Sciences

Current Research and Scholarly Interests

Integrated risk mapping and targeted snail control to support schistosomiasis elimination in Brazil and Cote d’Ivoire under future climate change.

Projects

  • Leptospirosis Modeling, NIMBioS/University of Tennessee, Knoxville (August 25, 2015 - June 24, 2016)

    Mathematical modeling of Leptospira transmission and intervention strategies

    Location

    Knoxville

All Publications

  • Analyzing the effect of restrictions on the COVID-19 outbreak for some US states. Theoretical ecology Demir, M., Aslan, I. H., Lenhart, S. 2023; 16 (2): 117-129

    Abstract

    The ongoing pandemic disease COVID‑19 has caused worldwide social and financial disruption. As many countries are engaged in designing vaccines, the harmful second and third waves of COVID‑19 have already appeared in many countries. To investigate changes in transmission rates and the effect of social distancing in the USA, we formulate a system of ordinary differential equations using data of confirmed cases and deaths in these states: California, Texas, Florida, Georgia, Illinois, Louisiana, Michigan, and Missouri. Our models and their parameter estimations show social distancing can reduce the transmission of COVID‑19 by 60% to 90%. Thus, obeying the movement restriction rules is crucial in reducing the magnitude of the outbreak waves. This study also estimates the percentage of people who were not social distancing ranges between 10% and 18% in these states. Our analysis shows the management restrictions taken by these states do not slow the disease progression enough to contain the outbreak.

    View details for DOI 10.1007/s12080-023-00557-1

    View details for PubMedID 37284010

    View details for PubMedCentralID PMC10126528

  • Analyzing the effect of restrictions on the COVID-19 outbreak for some US states THEORETICAL ECOLOGY Demir, M., Aslan, I. H., Lenhart, S. 2023

    View details for DOI 10.1007/s12080-023-00557-1

    View details for Web of Science ID 000976541100001

  • The effect of changing COVID-19 restrictions on the transmission rate in a veterinary clinic. Infectious Disease Modelling Spence, L., Anderson, D. E., Aslan, I. H., Demir, M., Okafor, C. C., Souza, M., Lenhart, S. 2023; 8 (1): 294-308

    Abstract

    With the declaration of the COVID-19 pandemic by the World Health Organization on March 11, 2020, the University of Tennessee College of Veterinary Medicine (UTCVM), like other institutions, restructured their services to reduce the potential spread of the COVID-19 virus while simultaneously providing critical and essential veterinary services. A mathematical model was developed to predict the change in the level of possible COVID-19 infections due to the increased number of potential contacts within the UTCVM hospital. A system of ordinary differential equations with different compartments for UTCVM individuals and the Knox county population was formulated to show the dynamics of transmission and the number of confirmed cases. Key transmission rates in the model were estimated using COVID-19 case data from the surrounding county and UTCVM personnel. Simulations from this model show the increasing number of COVID-19 cases among UTCVM personnel as the number of daily clients and the number of veterinary staff in the clinic are increased. We also investigate how changes within the Knox county community impact the UTCVM hospital. These scenarios show the importance of understanding the effects of re-opening scenarios in veterinary teaching hospitals.

    View details for DOI 10.1016/j.idm.2023.01.005

    View details for PubMedID 36819739

  • Modeling COVID-19: Forecasting and analyzing the dynamics of the outbreaks in Hubei and Turkey MATHEMATICAL METHODS IN THE APPLIED SCIENCES Aslan, I., Demir, M., Wise, M., Lenhart, S. 2022

    View details for DOI 10.1002/mma.8181

    View details for Web of Science ID 000768554000001

  • AN AGE STRUCTURE MODEL WITH IMPULSE ACTIONS FOR LEPTOSPIROSIS IN LIVESTOCK CATTLE JOURNAL OF BIOLOGICAL SYSTEMS Aslan, I., Baca-Carrasco, D., Lenhart, S., Velasco-Hernandez, J. X. 2021; 29 (01): 75-105

    View details for DOI 10.1142/S0218339021500042

    View details for Web of Science ID 000653683900004

https://orcid.org/0000-0002-9188-167X