#15,282
Researchers at the MRC Centre for Global Infectious Disease Analysis at Imperial College London - a WHO Collaborating Center - have released their 23rd report on COVID-19 (see previous reports here, here, and here); this time taking a mathematical approach to calculating the attack rate, and effective reproduction number, Rt, for each state in the nation.
Ideally, we'd have the results from multiple, large-scale, and validated, seroprevalence studies to go on. But those studies are just ramping up, and the accuracy of antibody testing remains in doubt.In the past, the focus has been on the R0 - or basic reproductive number - of COVID-19. Essentially, the number of new cases in a susceptible population likely to arise from a single infection (assuming no mitigation efforts).
But as we've discussed often (see EID Journal: Complexity of the Basic Reproduction Number (R0)), that number is not only notoriously difficult to quantify, it changes over time.
As community immunity builds, fewer people are susceptible, which impedes transmission. If NPIs (non-pharmaceutical interventions like social distancing, masks, etc.) are used, that can affect this number as well.A more refined way to look at this number is via the Rt - or effective reproductive number (over time). In Public Health Measures and the Reproduction Number of SARS-CoV-2 published earlier this month in JAMA Insights, author Thomas V. Inglesby, MD wrote:
The effective reproduction number, Rt, determines the potential for epidemic spread at a specific time t under the control measures in place (Figure 1). To evaluate the effectiveness of public health interventions, the Rt should be quantified in different settings, ideally at regular and frequent intervals (eg, weekly).This is an excellent explainer, and is well worth your time to review.
The PDF report contains graphs, and data on each individual state's presumed attack rate to date, Rt, and likely number of currently infectious individuals. Based on their analysis, no state is even close to having `herd immunity', with a national average of just over 4% having been infected with the virus.
I've only posted the summary, so you'll want to download the full report.
Report 23 - State-level tracking of COVID-19 in the United States
Date: 21 May 2020
H Juliette T Unwin, Swapnil Mishra2, Valerie C Bradley, Axel Gandy, Michaela Vollmer, Thomas Mellan, Helen Coupland, Kylie Ainslie, Charlie Whittaker, Jonathan Ish-Horowicz, Sarah Filippi, Xiaoyue Xi, Melodie Monod, Oliver Ratmann, Michael Hutchinson, Fabian Valka, Harrison Zhu, Iwona Hawryluk, Philip Milton, Marc Baguelin, Adhiratha Boonyasiri, Nick Brazeau, Lorenzo Cattarino, Giovanni Charles, Laura V Cooper, Zulma Cucunuba, Gina Cuomo-Dannenburg, Bimandra Djaafara, Ilaria Dorigatti, Oliver J Eales, Jeff Eaton, Sabine van Elsland, Richard FitzJohn, Katy Gaythorpe, William Green, Timothy Hallett, Wes Hinsley, Natsuko Imai, Ben Jeffrey, Edward Knock, Daniel Laydon, John Lees, Gemma Nedjati-Gilani, Pierre Nouvellet, Lucy Okell, Alison Ower, Kris V Parag, Igor Siveroni, Hayley A Thompson, Robert Verity, Patrick Walker, Caroline Walters, Yuanrong Wang, Oliver J Watson, Lilith Whittles, Azra Ghani, Neil M Ferguson, Steven Riley, Christl A. Donnelly, Samir Bhatt1, and Seth Flaxman
Correspondence: s.bhatt@imperial.ac.uk Methodological correspondence: mishra@imperial.ac.uk
Download the full PDF for Report 23
Webpage state-level estimates Report 23
See all reports
WHO Collaborating Centre for Infectious Disease Modelling, MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Department of Mathematics, Imperial College London, Department of Statistics, University of Oxford
Summary
As of 20 May 2020, the US Centers for Disease Control and Prevention reported 91,664 confirmed or probable COVID-19-related deaths, more than twice the number of deaths reported in the next most severely impacted country. In order to control the spread of the epidemic and prevent health care systems from being overwhelmed, US states have implemented a suite of non-pharmaceutical interventions (NPIs), including “stay-at-home” orders, bans on gatherings5.7*, and business and school closures.
We model the epidemics in the US at the state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the time-varying reproduction number (the average number of secondary infections caused by an infected person), the number of individuals that have been infected and the number of individuals that are currently infectious. We use changes in mobility as a proxy for the impact that NPIs and other behaviour changes have on the rate of transmission of SARS-CoV-2. We project the impact of future increases in mobility, assuming that the relationship between mobility and disease transmission remains constant. We do not address the potential effect of additional behavioural changes or interventions, such as increased mask-wearing or testing and tracing
strategies.
Nationally, our estimates show that the percentage of individuals that have been infected is 4.1% [3.7%-4.5%], with wide variation between states. For all states, even for the worst affected states, we estimate that less than a quarter of the population has been infected; in New York, for example, we estimate that 16.6% [12.8%-21.6%] of individuals have been infected to date. Our attack rates for New York are in line with those from recent serological studies [1] broadly supporting our modelling choices.
There is variation in the initial reproduction number, which is likely due to a range of factors; we find a strong association between the initial reproduction number with both population density (measured at the state level) and the chronological date when 10 cumulative deaths occurred (a crude estimate of the date of locally sustained transmission).
Our estimates suggest that the epidemic is not under control in much of the US: as of 17 May 2020, the reproduction number is above the critical threshold (1.0) in 24 [95% CI: 20-30] states. Higher reproduction numbers are geographically clustered in the South and Midwest, where epidemics are still developing, while we estimate lower reproduction numbers in states that have already suffered high COVID-19 mortality (such as the Northeast). These estimates suggest that caution must be taken in loosening current restrictions if effective additional measures are not put in place.
We predict that increased mobility following relaxation of social distancing will lead to resurgence of transmission, keeping all else constant. We predict that deaths over the next two-month period could exceed current cumulative deaths by greater than two-fold, if the relationship between mobility and transmission remains unchanged. Our results suggest that factors modulating transmission such as rapid testing, contact tracing and behavioural precautions are crucial to offset the rise of transmission associated with loosening of social distancing.
Overall, we show that while all US states have substantially reduced their reproduction numbers, we find no evidence that any state is approaching herd immunity or that its epidemic is close to over.
(Continue . . . )
