Fig. 1.

A demonstration of the model process. A The transmission model simulation of Buliisa sub-district. The entomological inoculation rate in the model is arbitrarily varied so that averaged annual prevalence (blue polygon) matches the empirical trial estimate measured at baseline for children aged 2–10 years (red point). In the Buliisa example, LLINs were distributed in May 2017 (first vertical grey arrow). The model simulated estimate for prevalence in the same age cohort is shown for the simulation distributing nets as originally scheduled (red line) and for the simulation distributing nets given the COVID-19 mitigation efforts (green line). Uncertainty draws, derived from varying model parameters associated with LLIN performance as determined from trial estimated data or statistical analysis of LLIN entomological impact [21], are shown as grey or green lines for the respective simulations. The mass campaign in 2020 for this location was scheduled to take place in December (dark red arrow), but took place earlier, 9th–21st August 2020 (green dot-dashed arrow). B Cross-sectional surveys of prevalence in children aged 2–10 years completed at baseline (red) and at 25-months (black) after the LLIN campaigns are compared to model simulated estimates for all 100 clusters in the LLINEUP trial demonstrating the model’s validity. C An example of the full simulation for Buliisa health sub-district. Here, the simulation is calibrated to baseline prevalence data (red point), and shown to reasonably recover the 6-month (grey), 12-month (light blue), 18-month (dark blue) and 25-month (black) empirical data estimates (Supplementary Fig. 1 shows results for all 100 clusters). Net distribution is then simulated given the scheduled date (dark red) or actual distribution date (dark green). As some distributions, like this example, went out before, and others after (see Supplementary Fig. 1), the 3-years from Jan 1st 2020 onward (blue polygon) are simulated for comparisons