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.
Highlights
Infections with impetigo remain highly prevalent in remote Australian Aboriginal communities, as well as Fiji and areas of socio-economic disadvantage [1, 2]
Late sequelae of acute rheumatic fever and rheumatic heart disease, combined with a high prevalence in remote Australian Aboriginal communities, Fiji, and other areas of socio-economic disadvantage, mean that impetigo is a substantial contributor to the burden of disease in these settings
Using a series of computational and statistical methods, we find that the infectious period in remote Australian Aboriginal communities is between 12 and 20 days, and that the force of infection varies by setting
Summary
Infections with impetigo (commonly known as skin sores) remain highly prevalent in remote Australian Aboriginal communities, as well as Fiji and areas of socio-economic disadvantage [1, 2]. Despite a relatively high level of understanding about the specifics of the GAS bacterium [3,4,5,6,7], comparatively little is known about the natural history of skin sore infection. We aim to utilise a dynamic transmission model for skin sores to estimate two key quantities: the force of infection, and the duration of infectiousness. In the absence of information relating to immunity post-infection, we assume skin sore transmission follows the dynamics of the SusceptibleInfectious-Susceptible (SIS) model. Calculation of these two key quantities will contribute to the development and parameterisation of models which will in turn inform the design of intervention strategies aimed at reducing prevalence
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