Estimation of the force of infection and infectious period of skin sores in remote australian communities using interval-censored data
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Lydeamore, M.J.
Campbell, Patricia T.
Price, David J
Wu, Yue
Marcato, Adrian J
Cunningham, Will
Carapetis, Jonathan R
Andrews, Ross
McDonald, Malcolm I
McVernon, Jodie
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Public Library of Science
Abstract
Prevalence of impetigo (skin sores) remains high in remote Australian Aboriginal communities,
Fiji, and other areas of socio-economic disadvantage. Skin sore infections, driven primarily
in these settings by Group A Streptococcus (GAS) contribute substantially to the
disease burden in these areas. Despite this, estimates for the force of infection, infectious
period and basic reproductive ratio—all necessary for the construction of dynamic transmission
models—have not been obtained. By utilising three datasets each containing longitudinal
infection information on individuals, we estimate each of these epidemiologically
important parameters. With an eye to future study design, we also quantify the optimal sampling
intervals for obtaining information about these parameters. We verify the estimation
method through a simulation estimation study, and test each dataset to ensure suitability to
the estimation method. We find that the force of infection differs by population prevalence,
and the infectious period is estimated to be between 12 and 20 days. We also find that optimal
sampling interval depends on setting, with an optimal sampling interval between 9 and
11 days in a high prevalence setting, and 21 and 27 days for a lower prevalence setting.
These estimates unlock future model-based investigations on the transmission dynamics of
skin sores.
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PLOS Computational Biology
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Open Access
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Creative Commons Attribution License
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