SignificanceForecasts routinely provide critical information for dangerous weather events but not yet for epidemics. Researchers develop computational models that can be used for infectious disease forecasting, but forecasts have not been broadly compared or tested. We collaboratively compared forecasts from 16 teams for 8 y of dengue epidemics in Peru and Puerto Rico. The comparison highlighted components that forecasts did well (e.g., situational awareness late in the season) and those that need more work (e.g., early season forecasts). It also identified key facets to improve forecasts, including using multiple model ensemble approaches to improve overall forecast skill. Future infectious disease forecasting work can build on these findings and this framework to improve the skill and utility of forecasts.

The effects of surfactant and temperature on the spreading of a viscous droplet are studied. Lubrication theory is used to develop a model for the evolution of the droplet. The surfactant is assumed to be insoluble and transport onto and off of the droplet interface at the contact line is allowed. A linear temperature gradient plus a gradient in the surface energy are allowed along the substrate. We find that these effects together can increase the speed of the translation of the droplet. We also find that allowing the static contact angle to vary with the surfactant concentration and temperature, as described by Young's law, can speed up droplet motion. When contact angle hysteresis is allowed, it is possible for the droplet to stop moving when surfactant transport is allowed along the interface.

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