Time-variant strategies for optimizing the performance of non-pharmaceutical interventions (NPIs) in protecting lives and livelihoods during the COVID-19 pandemic

Wei Aun Yap; Dhesi Baha Raja

Outcome measures for series A, B (a selection of the 71 scenarios), C, D, and E scenarios are tabulated in Table 3 . B-series scenarios are presented primarily as charts ( Figure 3 ). Prevalence charts for all scenarios are available on online. 5 Baseline scenario. The baseline scenario devoid of any NPI simulated has a peak prevalence of 231 per 1,000 on Day 60 and a peak incidence of 16.9 per 1,000 on Day 47. A total of 3.1 deaths per 1,000 are simulated by Day 365, excluding excess deaths resulting from an overwhelmed health system, as 88.5 percent of the initial population is infected in this fast spreading outbreak. The overcapacity factor is 7,757, the highest of all scenarios, reflecting an unmitigated surge in COVID-19 cases overwhelming the health system. However, proxy measures of economic and social activity are not reduced by any NPIs and hence, in reflection of business-as-usual, are the highest of all scenarios at 840 cumulative 'acts' per person over the intervention period from Day 14 to 182. Timing of introduction. The performance of B-series simulations varies by the day the fixedduration lockdown is introduced (Figure 2 and Figure 3 ) and demonstrates clearly how bimodal peaks in prevalence can be created by a once-off lockdown. Very early introduction of the lockdown merely delays the outbreak until after the lockdown but a lockdown introduced a bit later (B24) reduces peak prevalence to 157 per 1,000 compared to the baseline as a substantial number of cases occur around the introduction of and during the lockdown in a relatively moderated manner. Late introduction of the lockdown (B47) performs poorly in outcomes such as reducing or delaying peak prevalence but performs well in reducing the final tally of the infected to just 77.2 percent of the initial population. The best performance in terms of reducing peak prevalence is seen when the lockdown is timed to result in roughly equally high bimodal peaks, at a critical tipping point such that just one day's difference in timing the lockdown results in the highest peak flipping from occurring after the lockdown on Day 122 (B33) to occurring one day after the lockdown is introduced Day 35 (B34). This tipping point is seen most vividly in Figure 3a where the day of peak 5 https://github.com/quanticlear/Optimizing-NPI-performance . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.