We propose to use mathematical modeling to better understand the emergence/re-emergence of dengue fever and similar mosquito-borne diseases and to evaluate the effectiveness of intervention strategies on stopping them. The long term goal of this proposal is to reduce the burden of dengue fever and similar diseases by characterizing transmission to inform models of and response efforts to outbreaks. We intend to deliver a product to these public health officials and policy makers which not only is accurate and predictive, but which utilizes data that is readily available and/or routinely collected (e.g. clinical data, and that from mosquito surveillance programs), as well as a model that is both accessible in use and produces understandable and interpretable outputs. Further, we anticipate our model and outputs to be expandable to other existing vector borne viruses as well as to newly emerging threats not yet identified. Currently existing mathematical models of dengue virus transmission, though add to our understanding of transmission dynamics, are not primarily designed to account for detailed epidemiological prediction and evaluation. Predictive models need to span multiple scales, from house to the community to the international level. Accordingly, we propose the following specific aims: 1) Develop mathematical models of the infection dynamics of DENV in the mosquito and human, 2) Formulate models of the contact dynamics that drive transmission of DENV and 3) Integrate these component models into detailed agent-based simulation models of mosquito-borne transmission. By addressing these aims, we will confront the urgent public health problem of the emergence/re-emergence of dengue and similar viruses, such as chikungunya virus, in the continental US.
As no vaccine or treatment is available for dengue virus, mitigating transmission is the first and only line of defense of public health. Adding precision and thus accuracy to known and accepted measures of transmission and ultimately informing a transmission model will allow for quicker, more directed and actionable responses to prevent and/or respond to an outbreak of a vector-borne virus such as dengue.
|Christofferson, Rebecca C; Mores, Christopher N; Wearing, Helen J (2016) Bridging the Gap Between Experimental Data and Model Parameterization for Chikungunya Virus Transmission Predictions. J Infect Dis 214:S466-S470|
|Forshey, Brett M; Reiner, Robert C; Olkowski, Sandra et al. (2016) Incomplete Protection against Dengue Virus Type 2 Re-infection in Peru. PLoS Negl Trop Dis 10:e0004398|
|Manore, C A; Beechler, B R (2015) Inter-epidemic and between-season persistence of rift valley fever: vertical transmission or cryptic cycling? Transbound Emerg Dis 62:13-23|
|Christofferson, Rebecca C; Mores, Christopher N (2015) A role for vector control in dengue vaccine programs. Vaccine 33:7069-74|
|Brown, Lisa D; Christofferson, Rebecca C; Banajee, Kaikhushroo H et al. (2015) Cofeeding intra- and interspecific transmission of an emerging insect-borne rickettsial pathogen. Mol Ecol 24:5475-89|
|Manore, Carrie A; Hickmann, Kyle S; Hyman, James M et al. (2015) A network-patch methodology for adapting agent-based models for directly transmitted disease to mosquito-borne disease. J Biol Dyn 9:52-72|
|Christofferson, Rebecca C (2015) A Reevaluation of the Role of Aedes albopictus in Dengue Transmission. J Infect Dis 212:1177-9|
|Beechler, B R; Manore, C A; Reininghaus, B et al. (2015) Enemies and turncoats: bovine tuberculosis exposes pathogenic potential of Rift Valley fever virus in a common host, African buffalo (Syncerus caffer). Proc Biol Sci 282:|
|Robert, Michael A; Okamoto, Kenichi W; Gould, Fred et al. (2014) Antipathogen genes and the replacement of disease-vectoring mosquito populations: a model-based evaluation. Evol Appl 7:1238-51|
|Christofferson, Rebecca C; Chisenhall, Daniel M; Wearing, Helen J et al. (2014) Chikungunya viral fitness measures within the vector and subsequent transmission potential. PLoS One 9:e110538|
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