Ensemble Modeling in Epidemiology

Mathematical models are being used increasingly to inform policy on infectious disease outbreak preparedness and response. Selecting a single model for use in policy can be difficult because there are often multiple quality models for any given disease system. Ensemble modeling is a method that uses independent output from multiple models (or multiple parameterizations of one model) to create a single, interpretable prediction, and, therefore, makes choosing a single model unnecessary. This method has been shown to increase the accuracy of forecasts in areas such as weather forecasting and hydrology. The development of ensemble modeling for use in epidemiology is in its infancy but holds tremendous promise for increasing our ability to create accurate and robust predictions and forecasts. As part of a large international collaborative project, I am working on exploring and further developing the use of ensemble modeling methods to create robust predictions and forecasts for foot and mouth disease. The longer-term goal of this project is to develop the ensemble modeling methodology for infectious disease, so that it can be used in many disease systems to improve our ability to identify effective control actions against potential outbreaks and to accurately forecast ongoing outbreaks.

Cattle Movement Patterns and Disease Spread

Livestock movement patterns and spatial distributions can influence the spread of disease. If a foreign animal disease is introduced into the United States, the results could have widespread impacts on livestock health and have negative economic consequences. As part of a large collaborative project, I am exploring the effects of cattle movement patterns in the United States and how these patterns can influence disease spread. This work can help inform predictions about the extent of a disease outbreak, and can be useful in creating response and surveillance plans.

For more information on this topic, see:

Beck-Johnson, Lindsay M, Erin E. Gorsich, Clayton Hallman, Michael J. Tildesley, Ryan S. Miller, Colleen T. Webb. An exploration of within-herd dynamics of a transboundary livestock disease: a foot and mouth disease case study. 2023. Epidemics 42: 100668. https://doi.org/10.1016/j.epidem.2023.100668.

Sellman, Stefan, Lindsay M Beck-Johnson, Clayton Hallman, Ryan Miller, Katharine A. Owers Bonner, Katie Portacci, Colleen Webb, Tom Lindström. Modeling U.S. cattle movements until the cows come home: who ships to whom and how many. 2022. Computers and Electronics in Agriculture 203:107483. https://doi.org/10.1016/j.compag.2022.107483

Gilbertson, Kendra, Peter Brommesson, Amanda Minter, Clayton Hallman, Ryan S. Miller, Katie Portacci, Stefan Sellman, Michael J. Tildesley, Colleen T. Webb, Tom Lindström, and Lindsay M. Beck-Johnson. The importance of livestock demography and infrastructure in driving foot and mouth disease dynamics. 2022. Life 12(10), 1604. 10.3390/life12101604

Sellman, Stefan, Lindsay M. Beck-Johnson, Clayton Hallman, Ryan S. Miller, Katharine A. Owers Bonner, Katie Portacci, Colleen T. Webb, Tom Lindström. Modeling nation-wide U.S. swine movement networks at the resolution of the individual premises. 2022. Epidemics 41: 100636. https://doi.org/10.1016/j.epidem.2022.100636

Brommesson, Peter, Stefan Sellman, Lindsay Beck-Johnson, Clayton Hallman, Deedra Murrieta, Colleen T. Webb, Ryan S. Miller, Katie Portacci, Tom Lindström. Assessing intrastate shipments from interstate data and expert opinion. 2021. R. Soc. open sci. 8:192042. 10.1098/rsos.192042

Tsao, Kimberly, Stefan Sellman, Lindsay M. Beck-Johnson, Deedra J. Murrieta, Clayton Hallman, Tom Lindström, Ryan S. Miller, Katie Portacci, Michael J. Tildesley, Colleen T. Webb. Effects of regional differences and demography in modelling foot-and-mouth disease in cattle at the national scale. 2019. Interface Focus 10: 2019005. http://dx.doi.org/10.1098/rsfs.2019.0054

Beck-Johnson, L.M., Hallman, C., Miller, R.S., Portacci, K., Gorsich, E.E., Grear, D.A., Hartmann, K., Webb, C.T., 2019. Estimating and exploring the proportions of inter- and intrastate cattle shipments in the United States. Prev. Vet. Med. 162, 56–66. doi:10.1016/j.prevetmed.2018.11.002

Vector Population Dynamics

I am also interested in the dynamics of vector borne diseases, particularly the influence that vector populations have on transmission of disease. My research focuses on the mosquito populations that vector malaria parasites and their response to temperature, which is a complex and highly important driver of mosquito populations. Environmental conditions affect the ability of vectors to transmit pathogens successfully, so understanding the effects of the environment on vectors is essential to understanding the dynamics of disease transmission both now and in the future. To that end, I developed a theoretical approach to explore the influence of temperature dependencies and juvenile stage dynamics on adult population structure and malaria transmission potential.

For more information on this topic, see:

Beck-Johnson, Lindsay M., William A. Nelson, Krijn P. Paaijmans, Matthew B. Thomas, Andrew F. Read and Ottar N. Bjørnstad. 2017. The importance of temperature fluctuations in understanding mosquito population dynamics and malaria risk. R. Soc. Open Sci. 4: 160969. http://dx.doi.org/10.1098/rsos.160969

Beck-Johnson, Lindsay M., William A. Nelson, Krijn P. Paaijmans, Matthew B. Thomas, Andrew F. Read and Ottar N. Bjørnstad. 2013. The effect of temperature on Anopheles mosquito population dynamics and the potential for malaria transmission. PLoS ONE 8(11): e79276. doi:10.1371/journal.pone.0079276