Epidemiology is the study of disease patterns in a population. Quantifying transmission through a mixture of laboratory and computational methods can offer powerful tools to the public health community tasked with predicting the “next big thing” or how to react to the “current big thing.” For example, by informing mathematical models with laboratory data, you can explore the assumptions that some models make and determine how impactful those assumptions might be on the model output and predictions. Some examples include the homogeneity of the infectious period (it’s not), that temperature affects how mosquitoes transmit viruses (that’s not the only thing), and predictions about whether vaccines alone can eradicate mosquito-borne viruses (it can’t). Learning objective: Simulation models used to answer biological questions such as disease transmission carry a lot of assumptions that need biological insight to tease apart. Good news: Math is part of the answer to these questions raised by assumptions.
Dr. Rebecca Christofferson is currently an Assistant Professor at the Louisiana State University School of Veterinary Medicine. She researches the factors that alter and potentially mitigate transmission of mosquito-borne viruses. Specifically, she looks at how mosquito-virus (such as the extrinsic incubation period) and vertebrate-virus (such as intensity of viremia) interactions can lead to changes in the potential for transmission of these viruses. She uses mathematical simulation models to test hypotheses regarding the relative importance of these interactions in effort to improve forecasting of transmission and emergence of these viruses.
Louisiana State University, School of Veterinary Medicine, Pathobiological Sciences