Intervention strategies against COVID-19 and their estimated impact on Swedish healthcare capacity

Abstract

Objectives: During March 2020, the COVID-19 pandemic has rapidly spread globally, and non-pharmaceutical interventions are being used to reduce both the load on the healthcare system as well as overall mortality. Design: Individual-based transmission modelling using Swedish demographic and Geographical Information System data and conservative COVID-19 epidemiological parameters. Setting: Sweden Participants: A model to simulate all 10.09 million Swedish residents. Interventions: 5 different non-pharmaceutical public-health interventions including the mitigation strategy of the Swedish government as of 10 April; isolation of the entire household of confirmed cases; closure of schools and non-essential businesses with or without strict social distancing; and strict social distancing with closure of schools and non-essential businesses. Main outcome measures: Estimated acute care and intensive care hospitalisations, COVID-19 attributable deaths, and infections among healthcare workers from 10 April until 29 June. Findings: Our model for Sweden shows that, under conservative epidemiological parameter estimates, the current Swedish public-health strategy will result in a peak intensive-care load in May that exceeds pre-pandemic capacity by over 40-fold, with a median mortality of 96,000 (95% CI 52,000 to 183,000). The most stringent public-health measures examined are predicted to reduce mortality by approximately three-fold. Intensive-care load at the peak could be reduced by over two-fold with a shorter period at peak pandemic capacity. Conclusions: Our results predict that, under conservative epidemiological parameter estimates, current measures in Sweden will result in at least 40-fold over-subscription of pre-pandemic Swedish intensive care capacity, with 15.8 percent of Swedish healthcare workers unable to work at the pandemic peak. Modifications to ICU admission criteria from international norms would further increase mortality.

Higher education institutions and the use of online instruction and online tools and resources during the COVID-19 outbreak - An online review of selected U.S. and SA's universities

“…Besides being implemented intermittently, or in a staggered way (debuglies.com, 2020; Gardner et al, 2020;Kissler et al, 2020;Ramsey, 2020), social distancing can have a limited, enhanced or strong form (Ramsey, 2020). With reference to the two sets of universities investigated in the current study, all of them seem to have temporarily opted for a strong form of social distancing (Gardner et al (2020) since they completely shut down their campuses at the outbreak of the COVID-19 pandemic. This move is evinced by their instantaneous and wholesale transitioning to online pedagogy (see Tables 4 and 7).…”

“…As highlighted in the theoretical framework section, the practice of deploying social distancing measures such as closing learning institutions like schools during pandemic outbreaks seems to be common. For example, scholars such as Germann et al 2019 Again, as argued in the theoretical framework, one of the cardinal goals of social distancing that leads to school and university closures during a pandemic is to minimise social interactions between individuals with a view to reducing person-to-person viral infection rates (Amos & Howard, 2020;debuglies.com, 2020;Gardner et al, 2020;Germann et al, 2019;Morris et al, 2020;Sahu, 2020;Uscher-Pines et al, 2018;cf. Viner et al, 2020).…”

“…;Wind et al, 2020, p. 1). Thereafter, on 11 March 2020, the WHO declared COVID-19 a global pandemic (Duong et al, 2020;Gardner et al, 2020;cf. Viner et al, 2020 [1]).…”

“…To this effect, one view, among others, is that permutations of social distancing can be implemented in addition to or as opposed to a prolonged wholesale lockdown option during a given period of time. One such permutation is multiple sporadic (intermittent) social distancing stints -also known as staggered forms of social distancing (debuglies.com, 2020; also see Gardner et al, 2020;Ramsey, 2020) or an on/off approach (Kissler et al, 2020)which ebb and ow in keeping with the decrease and spike of the pandemic (Kissler et al, 2020;Powell, 2020;Valdez, Macri & Braunstein, 2012). In this instance, Valdez et al (2012) point out the effectiveness of an intermittent social distancing strategy on spreading epidemics in theoretical and real-world adaptive complex networks.…”

Modeling quarantine during epidemics and mass-testing using drones

“…Left: SIR curves (Q=0, obtained by setting D to infinity). Right: SIQR with the testing interval D=8 (see Figure 1 for the number of different-capacity drones needed to reach D=8) Figure 4 shows real data (pink crosses) for confirmed COVID-19 cases in Sweden starting from 100 cases on March 06 2020 [ECDE] (see [GWWK+20] for detailed COVID-19 history in Sweden). The basic SIR model (Q=0) fits the data with a modest (for the novel coronavirus) value of R0=2.27, which is reasonable given the general hygiene and cultural distancing in Sweden.…”