TY - JOUR
T1 - Reconstructing susceptible and recruitment dynamics from measles epidemic data
AU - Bobashev, Georgiy V.
AU - Ellner, Stephen P.
AU - Nychka, Douglas W.
AU - Grenfell, Bryan T.
N1 - Funding Information:
Dynamical epidemic studies are often based on the reported number of cases. For various purposes it would be helpful to have information about the numbers ofsus-ceptibles, but these data are rarely available. We show that under general theoretical assumptions itispossible toreconstruct, uptolinear scaling parameters, thedynamicsof the susceptible class, aswell astherate ofrecruitment to thesusceptible class, based only on case report data. Wedemonstrate that susceptible data reconstructed byourmethod improve the performance of forecasting models. Our estimate of susceptible class dynamics also can be used to estimate the age distribution of recruitment into the susceptible class, if the birth rate is known from independent data. Simulation experiments show that thereconstruction isrobust toerrors inthe reporting scheme. Thiswork was motivated by measles in large developed-world cities prior to immunization Acknowledgements: We thank Ben Bolker for numerous valuable discussions and assisting us incollating the data sets.This research waspartially supported by NSF Grant DMS 92-17866 to Nychka, Ellner, and A.R. Gallant, and was a portion of the senior author's Ph.D. thesis in the Biomathematics Graduate Program at North Carolina State University. * Corresponding author. Tel:(919) 541-6167, Fax: (919) 541-5966. E-mail: [email protected]
PY - 2000
Y1 - 2000
N2 - Dynamical epidemic studies are often based on the reported number of cases. For various purposes it would be helpful to have information about the numbers of susceptibles, but these data are rarely available. We show that under general theoretical assumptions it is possible to reconstruct, up to linear scaling parameters, the dynamics of the susceptible class, as well as the rate of recruitment to the susceptible class, based only on case report data. We demonstrate that susceptible data reconstructed by our method improve the performance of forecasting models. Our estimate of susceptible class dynamics also can be used to estimate the age distribution of recruitment into the susceptible class, if the birth rate is known from independent data. Simulation experiments show that the reconstruction is robust to errors in the reporting scheme. This work was motivated by measles in large developed-world cities prior to immunization programs; our theoretical assumptions are empirically justified for measles but should also be applicable to some other diseases with permanent immunity.
AB - Dynamical epidemic studies are often based on the reported number of cases. For various purposes it would be helpful to have information about the numbers of susceptibles, but these data are rarely available. We show that under general theoretical assumptions it is possible to reconstruct, up to linear scaling parameters, the dynamics of the susceptible class, as well as the rate of recruitment to the susceptible class, based only on case report data. We demonstrate that susceptible data reconstructed by our method improve the performance of forecasting models. Our estimate of susceptible class dynamics also can be used to estimate the age distribution of recruitment into the susceptible class, if the birth rate is known from independent data. Simulation experiments show that the reconstruction is robust to errors in the reporting scheme. This work was motivated by measles in large developed-world cities prior to immunization programs; our theoretical assumptions are empirically justified for measles but should also be applicable to some other diseases with permanent immunity.
KW - Forecasting
KW - Mathematical epidemiology
KW - Measles
KW - Modeling
KW - Susceptibility
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U2 - 10.1080/08898480009525471
DO - 10.1080/08898480009525471
M3 - Article
AN - SCOPUS:0033671548
SN - 0889-8480
VL - 8
SP - 1
EP - 29
JO - Mathematical Population Studies
JF - Mathematical Population Studies
IS - 1
ER -