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Imperial College COVID-19 Response Team Report / March 16

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  • Imperial College COVID-19 Response Team Report / March 16

    Originally posted by Juvenal View Post
    The estimates for covid-19 are 80 percent, or around 250 million infected, and an IFR around 1 percent.

    That's 2.5 million.

    The ICL study examined a number of NPIs separately and in tandem and estimated that number could be cut in half.
    Originally posted by carpedm9587 View Post
    Do you have a source for this? I'd love to look at it.

    Thanks!
    The primary source that informed public policy on non-pharmaceutical interventions (NPIs) was released on March 16 "On behalf of the Imperial College COVID-19 Response Team." They examined combinations of four NPIs using a standard epidemiological model.
    Abstract

    The global impact of COVID-19 has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 H1N1 influenza pandemic. Here we present the results of epidemiological modelling which has informed policymaking in the UK and other countries in recent weeks. In the absence of a COVID-19 vaccine, we assess the potential role of a number of public health measures – so-called non-pharmaceutical interventions (NPIs) – aimed at reducing contact rates in the population and thereby reducing transmission of the virus. In the results presented here, we apply a previously published microsimulation model to two countries: the UK (Great Britain specifically) and the US. We conclude that the effectiveness of any one intervention in isolation is likely to be limited, requiring multiple interventions to be combined to have a substantial impact on transmission. Two fundamental strategies are possible: (a) mitigation, which focuses on slowing but not necessarily stopping epidemic spread – reducing peak healthcare demand while protecting those most at risk of severe disease from infection, and (b) suppression, which aims to reverse epidemic growth, reducing case numbers to low levels and maintaining that situation indefinitely. Each policy has major challenges. We find that that optimal mitigation policies (combining home isolation of suspect cases, home quarantine of those living in the same household as suspect cases, and social distancing of the elderly and others at most risk of severe disease) might reduce peak healthcare demand by 2/3 and deaths by half. However, the resulting mitigated epidemic would still likely result in hundreds of thousands of deaths and health systems (most notably intensive care units) being overwhelmed many times over. For countries able to achieve it, this leaves suppression as the preferred policy option. We show that in the UK and US context, suppression will minimally require a combination of social distancing of the entire population, home isolation of cases and household quarantine of their family members. This may need to be supplemented by school and university closures, though it should be recognised that such closures may have negative impacts on health systems due to increased absenteeism. The major challenge of suppression is that this type of intensive intervention package – or something equivalently effective at reducing transmission – will need to be maintained until a vaccine becomes available (potentially 18 months or more) – given that we predict that transmission will quickly rebound if interventions are relaxed. We show that intermittent social distancing – triggered by trends in disease surveillance – may allow interventions to be relaxed temporarily in relative short time windows, but measures will need to be reintroduced if or when case numbers rebound. Last, while experience in China and now South Korea show that suppression is possible in the short term, it remains to be seen whether it is possible long-term, and whether the social and economic costs of the interventions adopted thus far can be reduced.

    R is the number of individuals an infected individual will infect. Infection is an exponential function of R. If R is greater than one, the spread will grow exponentially. If R is less than one, the spread will undergo exponential decay. Initially, at time zero, R is called R0.

    The goal of mitigation or suppression policies is to reduce R.

    Mitigation slows the spread by reducing R, but maintains exponential growth.
    Suppression halts the spread by reducing R to less than one.

    Mortality is the product of two factors, the infection ratio, which can be impacted by NPIs, and the infection fatality ratio. To change the infection fatality ratio requires pharmaceutical intervention, a palliative or a cure, both of which are attracting attention and funding, without notable success to date. So, until there's a vaccine, the goal is to reduce the infection ratio. Unmitigated, that ratio models out at 81 percent, or 2.2 million deaths in the US.
    In the (unlikely) absence of any control measures or spontaneous changes in individual behaviour, we would expect a peak in mortality (daily deaths) to occur after approximately 3 months (Figure 1A). In such scenarios, given an estimated R0 of 2.4, we predict 81% of the GB and US populations would be infected over the course of the epidemic.

    The principle benefit of mitigation policies is that they provide more time for infected individuals to recover, enhancing herd immunity, cutting the infection ratio in half and saving a million American lives but still allowing a million of us die. The principal benefit of suppression policies is that they can reduce mortality to levels comparable to the seasonal flu.

  • #2
    NPIs.jpg

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    • #3
      Here are the figures which attracted the greatest attention.
      In total, in an unmitigated epidemic, we would predict approximately 510,000 deaths in GB and 2.2 million in the US, not accounting for the potential negative effects of health systems being overwhelmed on mortality.

      Mitigation can cut those in figures in half.
      Table 3 shows the predicted relative impact on both deaths and ICU capacity of a range of single and combined NPIs interventions applied nationally in GB for a 3-month period based on triggers of between 100 and 3000 critical care cases. Conditional on that duration, the most effective combination of interventions is predicted to be a combination of case isolation, home quarantine and social distancing of those most at risk (the over 70s).

      A combination of CI, HQ and CDOL (CDO-Longer, 4 months) gave the best result, at 49 percent reduction. The best any other combination achieved was a 32 percent reduction.

      Comment


      • #4
        Originally posted by Juvenal View Post
        The principal benefit of suppression policies is that they can reduce mortality to levels comparable to the seasonal flu.
        Unmitigated, the US would see daily body counts peaking above 50,000 toward the end of June, less than the UK, proportionately, but a bit later because we're more spread out.

        body counts.jpg

        The good news is that's not going to happen. We are mitigating, which can cut the figures in half.

        Suppression can cut those figures by 90 percent.

        The good news is that suppression policies can succeed. The not so good news is that they'll have to be maintained until there's a vaccine, or a cure. The good news, again, is that suppression can be achieved with intermittent breaks in social distancing. The not so good news is that the NPIs will have to be in full force for most of the epidemic period to maintain suppression.

        While mass gatherings have attracted special attention in the press, they're not considered in the report.
        Stopping mass gatherings is predicted to have relatively little impact (results not shown) because the contact-time at such events is relatively small compared to the time spent at home, in schools or workplaces and in other community locations such as bars and restaurants.

        The viable combinations are:

        CI, SD, and HQ (coded CI-HQ-SD)
        CI, SD, and PC (coded PC-CI-SD)
        CI, SD, HQ and PC (coded PC-CI-HQ-SD)
        Our projections show that to be able to reduce R to close to 1 or below, a combination of case isolation, social distancing of the entire population and either household quarantine or school and university closure are required (Figure 3, Table 4). Measures are assumed to be in place for a 5-month duration. Not accounting for the potential adverse effect on ICU capacity due to absenteeism, school and university closure is predicted to be more effective in achieving suppression than household quarantine. All four interventions combined are predicted to have the largest effect on transmission (Table 4).

        All of these strategies reduce both mortality and peak ICU needs, but CI-HQ-SD, in orange below, risks taking the need for critical care beds above the red line of what we can make available.

        ICU beds.jpg

        In the event, much of the US has chosen all four, and parts of the country are also imposing lockdowns, an NPI that was not considered in the report.
        Combining all four interventions (social distancing of the entire population, case isolation, household quarantine and school and university closure) is predicted to have the largest impact, short of a complete lockdown which additionally prevents people going to work.

        It will be possible to relax SD from time to time and still maintain suppression.
        Given suppression policies may need to be maintained for many months, we examined the impact of an adaptive policy in which social distancing (plus school and university closure, if used) is only initiated after weekly confirmed case incidence in ICU patients (a group of patients highly likely to be tested) exceeds a certain “on” threshold, and is relaxed when ICU case incidence falls below a certain “off” threshold (Figure 4). Case-based policies of home isolation of symptomatic cases and household quarantine (if adopted) are continued throughout.

        In the UK, total deaths from the epidemic can be cut by 90 percent by choosing to suppress using all four and relaxing SD for up to 30 percent of the period.

        90 percent suppression.jpg

        Similar results are achievable in the US.

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