Sarah Kramer is a postdoctoral research scientist at the Max Planck Institute for Infection Biology, using mathematical models to understand seasonal drivers of vaccine response and infectious disease transmission. She recently received her PhD in Environmental Health Sciences from Columbia University’s Mailman School of Public Health, where her work focused on the generation and evaluation of retrospective and real-time forecasts of influenza. Her interests include drivers of spatial and temporal patterns in infectious disease transmission, zoonotic and other emerging infectious diseases, and the use of mathematical modeling methods to inform public health practice.
She/her/hers
Germany
Wong A, Kramer SC, Weinberger DM, Domenech de Cellès M. (2025). Assessing the effect of social contact structure on the impact of pneumococcal conjugate vaccines. Scientific reports, 15(1)
Kramer SC, Barrero Guevara LA, An der Heiden M, Wachtler B, Domenech de Cellès M. (2025). Changing socioeconomic inequalities in the incidence and case fatality rates of COVID-19 in Germany, March 2020 through May 2022: an ecological study. BMC public health, 25(1)
Barrero Guevara LA, Kramer SC, Kurth T, Domenech de Cellès M. (2024). Causal inference concepts can guide research into the effects of climate on infectious diseases. Nature ecology & evolution
Kramer SC, Pirikahu S, Casalegno JS, Domenech de Cellès M. (2024). Characterizing the interactions between influenza and respiratory syncytial viruses and their implications for epidemic control. Nature communications, 15(1)
Pearson T, Kramer S, Panisello Yagüe D, Nangkuu E, Medina-Rodriguez S, Wood C, Hepp C, Camplain R, Mihaljevic J, Milner T. (2024). Staphylococcus aureus infection disparities among Hispanics and non-Hispanics in Yuma, Arizona. Antimicrobial stewardship & healthcare epidemiology : ASHE, 4(1)
Wong A, Barrero Guevara LA, Goult E, Briga M, Kramer SC, Kovacevic A, Opatowski L, Domenech de Cellès M. (2023). The interactions of SARS-CoV-2 with cocirculating pathogens: Epidemiological implications and current knowledge gaps. PLoS pathogens, 19(3)
Domenech de Cellès M, Goult E, Casalegno JS, Kramer SC. (2022). The pitfalls of inferring virus-virus interactions from co-detection prevalence data: application to influenza and SARS-CoV-2. Proceedings. Biological sciences, 289(1966)
Yuan H, Kramer SC, Lau EHY, Cowling BJ, Yang W. (2021). Modeling influenza seasonality in the tropics and subtropics. PLoS computational biology, 17(6)
Kramer SC, Pei S, Shaman J. (2020). Forecasting influenza in Europe using a metapopulation model incorporating cross-border commuting and air travel. PLoS computational biology, 16(10)
Biggerstaff M, Dahlgren FS, Fitzner J, George D, Hammond A, Hall I, Haw D, Imai N, Johansson MA, Kramer S, McCaw JM, Moss R, Pebody R, Read JM, Reed C, Reich NG, Riley S, Vandemaele K, Viboud C, Wu JT. (2020). Coordinating the real-time use of global influenza activity data for better public health planning. Influenza and other respiratory viruses, 14(2)
Kramer SC, Shaman J. (2019). Development and validation of influenza forecasting for 64 temperate and tropical countries. PLoS computational biology, 15(2)
Morita H, Kramer S, Heaney A, Gil H, Shaman J. (2018). Influenza forecast optimization when using different surveillance data types and geographic scale. Influenza and other respiratory viruses, 12(6)
Doms C, Kramer SC, Shaman J. (2018). Assessing the Use of Influenza Forecasts and Epidemiological Modeling in Public Health Decision Making in the United States. Scientific reports, 8(1)
Kramer SC, Bansal S. (2015). Assessing the use of antiviral treatment to control influenza. Epidemiology and Infection, 143(8)
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