Meteorological parameters, influenza positive proportion and regression output for the study areas.

<p>In the last row, black curves are the observed data; grey shades indicate the 95% confidence interval; red curves are modeled results; and blue curves are the prospectively estimated influenza activity using actual meteorological data and regression models trained with influenza data from previous years. OR is the odds ratio from the regression for the meteorological parameters, and CI is the associated 95% Confidence Interval.</p

Change in influenza positive proportion when the indicated meteorological variable was increased by 1 standard deviation (temperature 2.74°C, specific humidity 2.61 g/kg, rainfall 6.48 mm/day).

<p>Change in influenza positive proportion when the indicated meteorological variable was increased by 1 standard deviation (temperature 2.74°C, specific humidity 2.61 g/kg, rainfall 6.48 mm/day).</p

Multivariable analysis of meteorological factors associated with influenza positivity.

<p>Bold font indicates a statistically significant variable (<i>p-value</i><0.05). RMSE is the Root Mean Squared Error and Corr. Coeff is the correlation coefficient between the observation and estimated influenza positive proportion in 2013.</p><p>The models were adjusted for: potentially confounding variables (RSV, parainfluenza and adeno viruses), previous weeks' influenza positivity, seasonality and other possible nonlinear relationships (modeled as a polynomial function, up to degree of 3, of the week number).</p

Study areas.

<p>Departments or provinces included in the study. Adjacent departments in Guatemala and El Salvador were combined in the analysis: Western departments in Guatemala (1,2), Central departments in Guatemala (3,4) and West-central departments in El Salvador (5–8).</p

Percent change in model deviance.

<p>Change in deviance between the full model (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100659#pone-0100659-t002" target="_blank">Table 2</a>) and the model with the indicated meteorological variable removed.</p

Countries and sub-national regions that were included in the analysis.

<p><b>The Global Influenza B Study, Latin-American countries, 2003–2014</b>. Dark Blue: Central America. Light Blue: Brazil. Yellow: remaining sites in South America.</p

Heat map of monthly influenza virus incidence patterns, 2003–2014, sorted by latitude.

<p>The Global Influenza B Study, Latin-American countries, 2003–2014.</p

Main features of influenza surveillance systems of countries and sub-national regions included in the analysis.

<p>The Global Influenza B Study, Latin-American countries, 2003–2014.</p

Timing and amplitude of primary (circles) and secondary (triangles) peak of influenza detection by site, against their latitudinal position.

<p><b>The size corresponds to the amplitude of influenza seasonality</b>. Dark Blue: Central America. Light Blue: Brazil. Yellow: remaining sites in South America.</p

Timing and amplitude of primary and secondary peaks of seasonal influenza epidemics.

<p>The Global Influenza B Study, Latin-American countries, 2003–2014.</p