64 research outputs found

    Comparison of weighted deming regression of force of infection estimates by country from cumulative incidence data and seroprevalence data.

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    <p>Each point is weighted depending on the error in both serology and incidence estimates, represented by the size of circles (larger circles indicating greater weight, i.e. smaller error).</p

    Posterior median estimates of the total force of infection from the model fitted to incidence data (model 1) and model A (as described in [13]) to age-stratified seroprevalence data (serology) from Thailand where incidence and serology data were available from the same year and location.

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    <p>Posterior median estimates of the total force of infection from the model fitted to incidence data (model 1) and model A (as described in [<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0004833#pntd.0004833.ref013" target="_blank">13</a>]) to age-stratified seroprevalence data (serology) from Thailand where incidence and serology data were available from the same year and location.</p

    Flowchart describing the literature search process for age-stratified incidence data.

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    <p>Flowchart describing the literature search process for age-stratified incidence data.</p

    Flowchart describing the literature search process for dengue seroprevalence surveys.

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    <p>Flowchart describing the literature search process for dengue seroprevalence surveys.</p

    Summary of PRNT surveys identified and associated demographics.

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    <p><i>^Number of serotypes known to have been in circulation</i>.</p><p>Summary of PRNT surveys identified and associated demographics.</p

    Summary of cross-sectional non-serotype specific datasets identified and associated demographics.

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    <p>^ Survey date not given, noted as ‘pre-year of publication’. <sup>+</sup>All assays were IgG or HI ELISAs. <sup>-</sup>Cross-sectional surveys from multiple years (2001–2007).</p><p>Summary of cross-sectional non-serotype specific datasets identified and associated demographics.</p

    Total force of infection and corresponding R<sub>0</sub> estimates from the model fitted to the incidence data grouped by country.

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    <p>Each dot represents the posterior median estimate and the error bars show the 95% CrI for each dataset. The box represents the country-specific central estimate calculated by taking the mean values of the MCMC output for each country (the line and limits of the box represents the posterior median and the 95% CrI respectively). R<sub>0</sub> assumption one: complete protection acquired upon quaternary infection, assumption two: complete protection reached after secondary infection.</p

    Summary of cross-sectional incidence datasets identified and associated demographics.

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    <p>Summary of cross-sectional incidence datasets identified and associated demographics.</p

    Summary of estimated reporting rates showing the baseline reporting rate or probability of detecting a secondary infection (ρ), the probability of detecting a primary infection (γ1) relative to a secondary infection, and the probability of detecting a tertiary/quaternary infection (γ3) relative to a primary infection.

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    <p>Each point represents the posterior median estimate and the error bars show the 95% CrI for each dataset. The box represents the country-specific central estimate calculated by taking the mean values of the MCMC output for each country (the line and limits of the box represents the posterior median and the 95% CrI respectively). A single overall value of γ1 and γ3 were estimated per country.</p
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