The instantaneous reproduction number (R) is estimated using the daily incidence of new cases, while including effects of social distancing, population density, and combined temperature and humidity lagged over the prior 14 days.

This model projects the effect of a theoretical May 15 midway return of normal travel to non-essential businesses. Future cases are estimated from predicted values of R.

Most epidemiological models applied to COVID-19 do not consider heterogeneity in infectiousness and impact of superspreaders, despite the broad viral loading distributions amongst COVID-19 positive people (1-1 000 000 per mL). Also, mass group testing is not used [due] to existing shortage of tests. I propose new strategy for early detection of superspreaders with reasonable number of RT-PCR tests, which can dramatically mitigate development COVID-19 pandemic and even turn it endemic.

Methods

I used stochastic social-epidemiological SEIAR model, where S-suspected, E-exposed, I-infectious, A-admitted (confirmed COVID-19 positive, who are admitted to hospital or completely isolated), R-recovered. The model was applied to real COVID-19 dynamics in London, Moscow and New York City.

Findings

Viral loading data measured by RT-PCR were fitted by broad log-normal distribution, which governed high importance of superspreaders. The proposed full scale model of a metropolis shows that top 10% spreaders (100+ higher viral loading than median infector) transmit 45% of new cases. Rapid isolation of superspreaders leads to 4-8 fold mitigation of pandemic depending on applied quarantine strength and amount of currently infected people. High viral loading allows efficient group matrix pool testing of population focused on detection of the superspreaders requiring remarkably small amount of tests.

Interpretation

The model and new testing strategy may prevent thousand or millions COVID-19 deaths requiring just about 5000 daily RT-PCR test for big 12 million city such as Moscow. Though applied to COVID-19 pandemic the results are universal and can be used for other infectious heterogenous epidemics.

The instantaneous reproduction number (R) is estimated using the daily incidence of new cases, while including effects of social distancing, population density, and combined temperature and humidity lagged over the prior 14 days.

This model projects the effect of a theoretical May 15 midway return of normal travel to non-essential businesses. Future cases are estimated from predicted values of R.

The instantaneous reproduction number (R) is estimated using the daily incidence of new cases, while including effects of social distancing, population density, and combined temperature and humidity lagged over the prior 14 days.

This model projects the effect of a theoretical May 15 midway return of normal travel to non-essential businesses. Future cases are estimated from predicted values of R.

The instantaneous reproduction number (R) is estimated using the daily incidence of new cases, while including effects of social distancing, population density, and combined temperature and humidity lagged over the prior 14 days.

This model projects the effect of a theoretical May 15 midway return of normal travel to non-essential businesses. Future cases are estimated from predicted values of R.

The instantaneous reproduction number (R) is estimated using the daily incidence of new cases, while including effects of social distancing, population density, and combined temperature and humidity lagged over the prior 14 days.

This model projects the effect of a theoretical May 15 midway return of normal travel to non-essential businesses. Future cases are estimated from predicted values of R.

R_{0} is the basic reproduction number of an epidemic. It’s defined as the number of secondary infections produced by a single infection. If R_{0} is greater than one, the epidemic spreads through every susceptible individual in a population. If R_{0} is less than one, the epidemic spreads, but limps along and disappears before everyone becomes infected. The flu has an R_{0}between one and two while measles sits in the high teens. While R_{0} is a useful measure, it is flawed in an important way: it’s static.

We’ve all witnessed that humans are adaptable. Our behavior changes, whether mandated or self-prescribed, and that changes the effectiveR value at any point in time. As we socially distance and isolate, R plummets. Because the value changes so rapidly, Epidemiologists have argued that the only true way to combat COVID19 is to understand and manage by R_{t}.

I agree, and I’d go further: we not only need to know R_{t}, we need to know local R_{t}. New York’s epidemic is vastly different than California’s and using a single number to describe them both is not useful. Knowing the local R_{t} allows us to manage the pandemic effectively.

States have had a variety of lockdown strategies, but there’s very little understanding of which have worked and which need to go further. Some states like California have been locked down for weeks, while others like Iowa and Nebraska continue to balk at taking action as cases rise. Being able to compare local R_{t} between different areas and/or watch how R_{t} changes in one place can help us measure how effective local policies are at slowing the spread of the virus.

Tracking R_{t} also lets us know when we might loosen restrictions. Any suggestion that we loosen restrictions when R_{t} > 1.0 is an explicit decision to let the virus proliferate. At the same time, if we are able to reduce R_{t} to below 1.0, and we can reduce the number of cases overall, the virus becomes manageable. Life can begin to return to ‘normal.’ But without knowing R_{t} we are simply flying blind.

The instantaneous reproduction number (R) is estimated using the daily incidence of new cases, while including effects of social distancing, population density, and combined temperature and humidity lagged over the prior 14 days.

This model projects the effect of a theoretical May 15 midway return of normal travel to non-essential businesses. Future cases are estimated from predicted values of R.

The instantaneous reproduction number (R) is estimated using the daily incidence of new cases, while including effects of social distancing, population density, and combined temperature and humidity lagged over the prior 14 days.

This model projects the effect of a theoretical May 15 midway return of normal travel to non-essential businesses. Future cases are estimated from predicted values of R.

The instantaneous reproduction number (R) is estimated using the daily incidence of new cases, while including effects of social distancing, population density, and combined temperature and humidity lagged over the prior 14 days.

This model projects the effect of a theoretical May 15 midway return of normal travel to non-essential businesses. Future cases are estimated from predicted values of R.