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. 2021 Jun 9;21:548. doi: 10.1186/s12879-021-06256-8

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 1 — Simulation results and effectiveness of targeted pooled household testing (TPHT) on COVID-19. (A) Fitting the model to Oslo hospitalization data. We plot the mean predicted number of hospitalizations (black) and confidence interval (2σ, dashed). Actual Oslo hospitalizations (red) were used as calibration (until May 15th). Hospitalization data May 15th- August 30th (green) were not used to determine model parameters. (B) Effect of TPHT in response to a sudden rise in cases (reaching 1,000 symptomatic individuals), assuming general infectivity parameters similar to those of Oslo in late May 2020 but with 75% increased infectivity of random contacts giving R=1.2. (C) Predicted number of deaths and infections for different TPHT testing fractions corresponding to panel (B), relative to no testing. Panels (D)-(F) use same parameters as panel (B), except with a 113% increased infectivity of random contacts giving R=1.4. (D) Effect of test frequency and fraction on R, for TPHT (left) and random pooled household testing (right). Dashed and solid lines indicate isoclines for R=1 and constant test density, respectively. Optimal point is marked with red circle. (E) Response of weekly TPHT to varying city size. We scale the population of the baseline Oslo model (γ=1) to generate larger (γ>1) or smaller networks with household, school, daycare, workplace and nursing home size-distributions unchanged. (F) Response of weekly TPHT to changes in distribution of household size, relative to the baseline Oslo model (α=0). For α>0, a portion of households are each split into a new pair, yielding a smaller average household size than the baseline. For α<0, a portion of the households are pairwise merged, yielding a larger average household size than the baseline. Household, school, daycare, workplace and nursing home size-distributions are kept unchanged. (G) COVID-19 stopping time (number of days until symptomatic cases are reduced by 75%) in response to changing days between tests (left) and fraction of weekly TPHT tests (right). Stopping times longer than 100 days are truncated