Modeling shield immunity to reduce COVID-19 epidemic spread

Abstract

The COVID-19 pandemic has precipitated a global crisis, with more than 1,430,000 confirmed cases and more than 85,000 confirmed deaths globally as of 9 April 2020 1-4 . Mitigation and suppression of new infections have emerged as the two predominant public health control strategies 5 . Both strategies focus on reducing new infections by limiting human-to-human interactions, which could be both socially and economically unsustainable in the long term. We have developed and analyzed an epidemiological intervention model that leverages serological tests 6,7 to identify and deploy recovered individuals 8 as focal points for sustaining safer interactions via interaction substitution, developing what we term 'shield immunity' at the population scale. The objective of a shield immunity strategy is to help to sustain the interactions necessary for the functioning of essential goods and services 9 while reducing the probability of transmission. Our shield immunity approach could substantively reduce the length and reduce the overall burden of the current outbreak, and can work synergistically with social distancing. The present model highlights the value of serological testing as part of intervention strategies, in addition to its well-recognized roles in estimating prevalence 10,11 and in the potential development of plasma-based therapies 12-15 .In the absence of reliable pharmaceutical interventions against SARS-CoV-2, multiple public health strategies are being deployed to slow the coronavirus pandemic 1,5,16 . These strategies can be broadly grouped into two approaches: mitigation and suppression. Mitigation includes a combination of social distancing (including school and university closures), case testing and symptomatic case isolation to reduce epidemic spread and burden on hospitals. Mitigation is intended to lessen an outbreak. However, the number of cases might still overwhelm health services 5 . Some jurisdictions have either preemptively or reactively adopted a combination of travel restrictions (shown to be effective in curtailing dispersion if implemented early enough 17,18 ) and suppression, which involves imposing complete shutdowns of the bulk of non-essential services for extended periods. Suppression strategies have led to marked decreases in new case rates in the short term by combining case isolation, quarantine, use of separate facilities for treating COVID-19 patients and large-scale

Quantifying antibody kinetics and RNA detection during early-phase SARS-CoV-2 infection by time since symptom onset

“…The extensive individual variation in antibody patterns, which is a common phenomenon across many viral infections ( Pacis et al, 2014 ), may affect the accuracy of transmission models ( Weitz et al, 2020 ). For example, if seroconversion times reflect the actual end of infectiousness and onset of immunity (i.e.…”

“…Since its emergence in December 2019, the SARS-CoV-2 pandemic has been the subject of intense research assessing all facets of the pathogen and its rapid global spread. Serology – the measurement of serum antibodies – provides crucial data for understanding key aspects of infection and epidemiology ( Weitz et al, 2020 ). At the level of populations, serologic data can provide insights into virus spread by enabling estimation of the overall attack rate, and seroprevalence estimates can elucidate the potential for herd immunity ( Stringhini et al, 2020 ; Bryant et al, 2020 ).…”

Protecting the population with immune individuals

“…The idea is that these recovered people can work at the front line in hospitals, nursing homes, pharmacies, grocery stores and other critical institutions in which the infection spreads easily, to lower the number of interactions between susceptible people and infected people. In a recent study in Nature Medicine, Weitz et al model this strategy and find that the immunity strategy can substantially reduce the impact of COVID-19 on deaths and the need for beds in intensive care units 1 .…”

Fleeing lockdown and its impact on the size of epidemic outbreaks in the source and target regions - a COVID-19 lesson

“…We consider two geographic regions, with the disease being initially confined in region A, where also severe control measures are applied and from where people flee to a previously (ideally) uninfected region B. In contrast to previous studies for the spread of COVID-19, we consider here the geographic distribution of cases, but relax the classification of the individuals into age groups 24,32,33 . Calculating the basic reproduction number (2), we identified its four components that account for transmissions from presymptomatic, undetected infectives, detected but not hospitalized, and hospitalized cases.…”