Additional file 1: of Mathematical models used to inform study design or surveillance systems in infectious diseases: a systematic review

Study protocol and search strategy. (PDF 74 kb

Eight Years of the Great Influenza Survey to Monitor Influenza-Like Illness in Flanders

<div><p>In 2003, an internet-based monitoring system of influenza-like illness (ILI), the Great Influenza Survey (GIS), was initiated in Belgium. For the Flemish part of Belgium, we investigate the representativeness of the GIS population and assess the validity of the survey in terms of ILI incidence during eight influenza seasons (from 2003 through 2011). The validity is investigated by comparing estimated ILI incidences from the GIS with recorded incidences from two other monitoring systems, (<i>i</i>) the Belgian Sentinel Network and (<i>ii</i>) the Google Flu Trends, and by performing a risk factor analysis to investigate whether the risks on acquiring ILI in the GIS population are comparable with results in the literature. A random walk model of first order is used to estimate ILI incidence trends based on the GIS. Good to excellent correspondence is observed between the estimated ILI trends in the GIS and the recorded trends in the Sentinel Network and the Google Flu Trends. The results of the risk factor analysis are in line with the literature. In conclusion, the GIS is a useful additional surveillance network for ILI monitoring in Flanders. The advantages are the speed at which information is available and the fact that data is gathered directly in the community at an individual level.</p></div

Flow chart representation of the selection process.

<p>Sixteen were excluded because of non-English language: Spanish (8), Portuguese (5) and French (3) in the first step of the selection process.</p

Literature Search Strategy.

<p>Literature Search Strategy.</p

Formulations of antibody cross-reaction hypotheses in host-to-host transmission models.

<p> is the transmission rate, represents the number of individuals infected with serotype and the number of individuals subsequently infected with serotypes and .</p>*<p>In references <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049085#pone.0049085-Aguiar1" target="_blank">[113]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049085#pone.0049085-Aguiar2" target="_blank">[114]</a>, Aguiar <i>et al.</i> assumed that a proportion of secondary infected individuals contribute to a lesser extent to the epidemic process due to hospitalisation or isolation. This assumption is based on the evidence that secondary infections are more likely to produce severe clinical expression of the disease. As the antagonist relationship between previously acquired antibodies and secondary infection with an heterologous serotype is certainly involved in the intra-individual disease evolution, we classified this assumption as depending on the antibody cross-reaction hypotheses.</p

Dengue model parameters in host-to-host transmission approaches.

<p>With these parameter values, the basic reproduction number range is 2–4.</p><p>ADE: antibody-dependent enhancement. Here, with values greater than 1, the secondary infected individuals are assumed to contribute to a greater extent than primary infected individuals to the transmission process (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049085#pone-0049085-t003" target="_blank">Table 3</a>).</p

‘Phylogenetic tree’ of selected articles.

<p>Models are decomposed according to the number of serotypes considered (one (black lines), two (blue full lines) or more than two (red dashed lines) serotypes. Each branch of the tree corresponds to a modification of the initial model owing to additional assumptions. The word “enhancement” refers to the different modelling assumptions to represent the effect of antibody-dependent enhancement (ADE) and CP stands for Cross-Protection. * Extensions of Host-to-Host transmission models <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049085#pone.0049085-Recker1" target="_blank">[106]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049085#pone.0049085-Nagao1" target="_blank">[115]</a> including the vector population.</p

Definitions and ranges of the main parameters in vector-host transmission models.

*<p>The range for the vector recruitment rate was derived from modelling studies considering exclusively the adult mosquito population with a constant recruitment rate (<i>i.e.</i> a constant vector population) and providing parameters values for numerical simulations <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049085#pone.0049085-Esteva1" target="_blank">[19]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049085#pone.0049085-Newton1" target="_blank">[21]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049085#pone.0049085-Garba1" target="_blank">[76]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049085#pone.0049085-Feng1" target="_blank">[88]</a>.</p

Parameters estimates and standard error estimates for the CE-PE model.

<p>Parameters estimates and standard error estimates for the CE-PE model.</p

Comparison of marginal model, and full-shared, partial-shared and partial-equal random effects models, all without or with common intercept and common slope for HIV prevalence and wealth index for the models for <i>π</i>_<i>F</i> and <i>π</i>_<i>M</i>.

<p>The column ‘-2ll’ shows the values of -2×log-likelihood; the column ‘#Par’ shows the number of parameters and the columns ‘Rank’ refers to the ranking of the models according to the AIC and BIC criterion.</p