TY - JOUR
T1 - Modeling the human infectious reservoir for malaria control
T2 - Does heterogeneity matter?
AU - Hansen, Elsa
AU - Buckee, Caroline O.
PY - 2013/6
Y1 - 2013/6
N2 - The complex biological relationships underlying malaria transmission make it difficult to predict the impact of interventions. Mathematical models simplify these relationships and capture essential components of malaria transmission and epidemiology. Models designed to predict the impact of control programs generally infer a relationship between transmission intensity and human infectiousness to the mosquito, requiring assumptions about how infectiousness varies between individuals. A lack of understanding of human infectiousness precludes a standard approach to this inference, however, and field data reveal no obvious correlation between transmission intensity and human population infectiousness. We argue that model assumptions will have important consequences for predicting the impact of control programs.
AB - The complex biological relationships underlying malaria transmission make it difficult to predict the impact of interventions. Mathematical models simplify these relationships and capture essential components of malaria transmission and epidemiology. Models designed to predict the impact of control programs generally infer a relationship between transmission intensity and human infectiousness to the mosquito, requiring assumptions about how infectiousness varies between individuals. A lack of understanding of human infectiousness precludes a standard approach to this inference, however, and field data reveal no obvious correlation between transmission intensity and human population infectiousness. We argue that model assumptions will have important consequences for predicting the impact of control programs.
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U2 - 10.1016/j.pt.2013.03.009
DO - 10.1016/j.pt.2013.03.009
M3 - Review article
C2 - 23597499
AN - SCOPUS:84878173306
VL - 29
SP - 270
EP - 275
JO - Trends in Parasitology
JF - Trends in Parasitology
SN - 1471-4922
IS - 6
ER -