TY - JOUR
T1 - Structured models of infectious disease
T2 - Inference with discrete data
AU - Metcalf, C. J.E.
AU - Lessler, J.
AU - Klepac, P.
AU - Morice, A.
AU - Grenfell, B. T.
AU - Bjørnstad, O. N.
N1 - Funding Information:
We thank the people of the Costa Rica national network of epidemiology for all their hard work in conducting surveillance activities and providing the rubella data used in this study, and the POLYMOD project. This work was funded by the Royal Society (CJEM) , the Bill and Melinda Gates Foundation (CJEM, BTG, JL, PK) , the RAPIDD program of the Science & Technology Directorate of the Department of Homeland Security , and the Fogarty International Center National Institute of Health (BTG) and NIH grant NIH/GM R01-GM083983-01 (CJEM, BTG) .
PY - 2012/12
Y1 - 2012/12
N2 - The usage of structured population models can make substantial contributions to public health, particularly for infections where clinical outcomes vary over age. There are three theoretical challenges in implementing such analyses: (i) developing an appropriate framework that models both demographic and epidemiological transitions; (ii) parameterizing the framework, where parameters may be based on data ranging from the biological course of infection, basic patterns of human demography, specific characteristics of population growth, and details of vaccination regimes implemented; (iii) evaluating public health strategies in the face of changing human demography. We illustrate the general approach by developing a model of rubella in Costa Rica. The demographic profile of this infection is a crucial aspect of its public health impact, and we use a transient perturbation analysis to explore the impact of changing human demography on immunization strategies implemented.
AB - The usage of structured population models can make substantial contributions to public health, particularly for infections where clinical outcomes vary over age. There are three theoretical challenges in implementing such analyses: (i) developing an appropriate framework that models both demographic and epidemiological transitions; (ii) parameterizing the framework, where parameters may be based on data ranging from the biological course of infection, basic patterns of human demography, specific characteristics of population growth, and details of vaccination regimes implemented; (iii) evaluating public health strategies in the face of changing human demography. We illustrate the general approach by developing a model of rubella in Costa Rica. The demographic profile of this infection is a crucial aspect of its public health impact, and we use a transient perturbation analysis to explore the impact of changing human demography on immunization strategies implemented.
UR - http://www.scopus.com/inward/record.url?scp=84869750211&partnerID=8YFLogxK
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U2 - 10.1016/j.tpb.2011.12.001
DO - 10.1016/j.tpb.2011.12.001
M3 - Article
C2 - 22178687
AN - SCOPUS:84869750211
VL - 82
SP - 275
EP - 282
JO - Theoretical Population Biology
JF - Theoretical Population Biology
SN - 0040-5809
IS - 4
ER -
