TY - CHAP
T1 - Searching for Superspreaders
T2 - Identifying Epidemic Patterns Associated with Superspreading Events in Stochastic Models
AU - Edholm, Christina J.
AU - Emerenini, Blessing O.
AU - Murillo, Anarina L.
AU - Saucedo, Omar
AU - Shakiba, Nika
AU - Wang, Xueying
AU - Allen, Linda J.S.
AU - Peace, Angela
N1 - Funding Information:
Acknowledgements The work described in this chapter was initiated during the Association for Women in Mathematics collaborative workshop Women Advancing Mathematical Biology (WAMB) hosted by the Mathematical Biosciences Institute (MBI) at Ohio State University in April 2017. Funding for the workshop was provided by MBI, NSF ADVANCE “Career Advancement for Women Through Research-Focused Networks” (NSF-HRD 1500481), Society for Mathematical Biology, and Microsoft Research. We give special thanks to the WAMB organizers: Ami Radunskaya, Rebecca Segal, and Blerta Shtylla. Anarina L. Murillo acknowledges that this work has been supported in part by the grant T32DK062710 from the National Institute of Diabetes and Digestive and Kidney Diseases and grant T32HL072757 from the National Heart, Lung, and Blood Institute. Omar Saucedo acknowledges that this research has been supported in part by the MBI and the grant NSF-DMS 1440386. Nika Shakiba is the recipient of the NSERC Vanier Canada Graduate Scholarship. This work was partially supported by a grant from the Simons Foundation (#317047 to Xueying Wang). In addition, we thank Texas Tech University for hosting our second WAMB group meeting and the Paul Whitfield Horn Professorship of Linda JS Allen for providing financial support. We thank the two anonymous reviewers for their helpful suggestions on the original manuscript.
Publisher Copyright:
© 2018, The Author(s) and the Association for Women in Mathematics.
PY - 2018
Y1 - 2018
N2 - The importance of host transmissibility in disease emergence has been demonstrated in historical and recent pandemics that involve infectious individuals, known as superspreaders, who are capable of transmitting the infection to a large number of susceptible individuals. To investigate the impact of superspreaders on epidemic dynamics, we formulate deterministic and stochastic models that incorporate differences in superspreaders versus nonsuperspreaders. In particular, continuous-time Markov chain models are used to investigate epidemic features associated with the presence of superspreaders in a population. We parameterize the models for two case studies, Middle East respiratory syndrome (MERS) and Ebola. Through mathematical analysis and numerical simulations, we find that the probability of outbreaks increases and time to outbreaks decreases as the prevalence of superspreaders increases in the population. In particular, as disease outbreaks occur more rapidly and more frequently when initiated by superspreaders, our results emphasize the need for expeditious public health interventions.
AB - The importance of host transmissibility in disease emergence has been demonstrated in historical and recent pandemics that involve infectious individuals, known as superspreaders, who are capable of transmitting the infection to a large number of susceptible individuals. To investigate the impact of superspreaders on epidemic dynamics, we formulate deterministic and stochastic models that incorporate differences in superspreaders versus nonsuperspreaders. In particular, continuous-time Markov chain models are used to investigate epidemic features associated with the presence of superspreaders in a population. We parameterize the models for two case studies, Middle East respiratory syndrome (MERS) and Ebola. Through mathematical analysis and numerical simulations, we find that the probability of outbreaks increases and time to outbreaks decreases as the prevalence of superspreaders increases in the population. In particular, as disease outbreaks occur more rapidly and more frequently when initiated by superspreaders, our results emphasize the need for expeditious public health interventions.
KW - Deterministic model
KW - Ebola
KW - Host heterogeneity
KW - Middle East respiratory syndrome
KW - Stochastic model
KW - Superspreader
UR - http://www.scopus.com/inward/record.url?scp=85055750870&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-98083-6_1
DO - 10.1007/978-3-319-98083-6_1
M3 - Chapter
AN - SCOPUS:85055750870
T3 - Association for Women in Mathematics Series
SP - 1
EP - 29
BT - Association for Women in Mathematics Series
PB - Springer
ER -