My research primarily focuses on mathematical modeling for infectious diseases, which continue to pose significant threats to global health. I employ mathematical tools to derive crucial insights such as identifying patterns, forecasting pandemic trajectories, and assessing the effectiveness of various interventions, thereby informing public health policies and decision-making at local and global scales.

I am currently a postdoctoral scholar in the De Leo Lab and developing mechanistic models to investigate the impact of climate change on the transmission of the parasitic disease schistosomiasis, a role I have held since 2022. Prior to this, I completed my Ph.D. at the University of Tennessee in the Department of Mathematics, specializing in Mathematical Ecology/Evolution, in 2019. Subsequently, I served as a faculty member at Batman University.

Honors & Awards

  • Summer Research Assistantship, University of Tennessee (2018)
  • Graduate Teaching Assistantships, University of Tennessee (2015)
  • Summer Research Assistantship, University of Tennessee (2015)
  • Ph.D. Fellowship, Turkish Ministry of National Education (2014)
  • Graduate Fellowship, Higher Education Credit and Hostels Institution, Turkiye (2010)
  • Honor Undergraduate Reward, Mersin University (2009)
  • Undergraduate Scholarship, Higher Education Credit and Hostels Institution, Turkiye (2005)

Boards, Advisory Committees, Professional Organizations

  • Councillor, Stanford Doerr School of Sustainability, Postdoc Advisory (2022 - 2024)
  • Liaison, Stanford Doerr School of Sustainability, Diversity Equity Inclusion (2022 - 2022)
  • 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


    Opportunities for Student Involvement


  • Researcher


    Leptospirosis Modeling

    Populations Served




    Ongoing Project


    Opportunities for Student Involvement


Research Interests

  • Data Sciences

Current Research and Scholarly Interests

Currently, I am exploring the complex interplay between temperature and the transmission risk of schistosomiasis, a parasitic disease currently affecting over two hundred million people, predominantly in SSA. I have been developing a novel mechanistic model with system of DE accounting for most of the thermal sensitive stages in the schistosomiasis life cycle and then improving the model with seasonal temperature oscillation and also some dormancy adaptation behaviors of snails like aestivation to explore the impact of seasonal temperature variation on the dynamics of schistosomiasis. In addition to that, I am also exploring the future projection of schistosomiasis under multiple future climate change scenarios in Brazil and Africa. Some of our preliminary results indicate that increasing the magnitude of seasonality, decreases the intensity of schistosomiasis, promotes a shift in the optimal transmission temperature towards lower values, Moreover, we discovered the seasonality extend the thermal breath of schistosomiasis.


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

    Mathematical modeling of Leptospira transmission and intervention strategies



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


    Africa, Europe, North America, South America

Lab Affiliations

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


    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
  • 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


    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