Fig 1.
This map depicts the locations of the two hospitals used in the study, Hospital Saludesa and Hospital Pedro Vicente Maldonado, as well as the climate station. Inset, coast of Ecuador, with a square marking the relative position of the larger map. PVM = Pedro Vicente Maldonado, INAMHI = Instituto Nacional de Meteorología e Hidrología. Basemap and inset tiles from Stamen Design, under CC BY 3.0 (maps.stamen.com). Maps were modified by R.S. for this manuscript.
Table 1.
School sessions and holidays.
Fig 2.
Time series plots for dataset.
Monthly averages for Oceanic Niño Index (orange), minimum (blue), mean (black), and maximum (red) temperature, precipitation (green), and diagnoses (purple) are plotted over the time period of the study.
Table 2.
Data characteristics.
Fig 3.
The non-climate seasonality (Model 1) predictions for daily diagnoses exhibit an annual seasonality peaking in mid-March. Case predictions are in black, with confidence intervals in grey. The top panel depicts predictions for Hospital Pedro Vicente Maldonado and the bottom panel depicts predictions for Hospital Saludesa.
Fig 4.
The effect of the day of the week on dengue fever diagnoses is summarized in this graph, comparing each day to the overall average effect of weekday. A null estimate (RR = 1.0) is included as a reference. Effect estimates are derived from Model 1. CI = confidence interval.
Fig 5.
Interactions between monthly precipitation and monthly minimum temperature.
Within individual plot panels, number of days with precipitation increase along the x-axis while monthly predicted number of dengue cases increase along the y-axis. Absolute minimum temperature levels increase along panel columns from left to right, and monthly amounts of precipitation increase along panel rows from bottom to top. Increases in the amount of precipitation leads to increases in the number of dengue diagnoses for all temperature conditions, but the relationship between temperature and number of days with precipitation exhibits an overall U-shaped pattern. As the minimum temperature warms, the relationship between number of days with precipitation and number of dengue diagnoses changes from negative to positive. At lower temperatures (18–19° C), additional days with precipitation lead to decreases in the predicted number of dengue cases. At 20° C, the relationship is flat, and at warmer temperatures (21–22° C), additional days with precipitation lead to increases in the number of dengue cases. Effect estimates were obtained from Model 3. T = monthly minimum temperature, mm = millimeters, C = Celsius.