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 - 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 -