Indications that Stockholm has reached herd immunity, given limited restrictions, against several variants of SARS-CoV-2

Abstract

"When COVID-19 cases go up, public compliance with restrictions is poor, when cases go down, public compliance is good." In this article, we question this explanation and show that relatively low levels of sero-prevalence helps to keep cases down. In other words, the herd-immunity threshold appears to be much lower than previously thought. We construct a mathematical model taking pre-immunity, antibody waning and more infectious variants of concern into consideration, thereby providing a theoretical framework in which the cases in Stockholm county can be fully predicted without relying on neither oscillations in restrictions (and public compliance thereof) nor vaccination roll-out. We also show that it is very difficult to match the data from Stockholm without including pre-immunity, or, which turns out to be equivalent, great variations in susceptibility.

Immunity to SARS-CoV-2 up to 15 months after infection

“…The majority of patients (99) were recruited between February 28 and December 3, 2020 during the first and second wave in Europe when the G614 variant (B.1 lineage) was the predominant circulating strain in both Sweden and Italy. The rest of the patients (37) were recruited between January 28 and June 16, 2021 during the third wave in which Alpha became a dominant variant and accounted for more than 50-60% of the cases at the beginning of March in Italy and Sweden (Carlsson and So ¨derberg-Naucle ´r, 2021;Di Giallonardo et al, 2021).…”

COVID-19 Modeling Outcome versus Reality in Sweden

“…With this in mind, we postulate that 70% of the vaccinated people become immune, and that the vaccination only affects group 6. In the medRxiv preprint of this paper [36] we instead assumed a 90% efficacy after the first shot, and, therefore, also included vaccinations in group 5 in our modeling. We updated this since the way we do it here seems more realistic and also much simpler to describe and code.…”

“…(Since this becomes rather technical, we want to stress that the way the initial conditions are chosen have no major bearing on the model curves or conclusions of the paper. In the medRxiv preprint version of this paper [36], we chose initial conditions by simply running the model, and the corresponding graphs are almost identical).…”

Decoupling between SARS-CoV-2 transmissibility and population mobility associated with increasing immunity from vaccination and infection in South America

“…Despite confidence intervals of estimates of percentage of immune people were very large, mostly due to uncertainties in the IFR estimates, our analyses support that the cHIT for SARS-CoV variants Gamma and Lambda in South America would be lower than , ranging from 29% in Argentina to 45% in Brazil. A recent modeling study conducted in Stockholm, Sweden, also supports that this country reached the cHIT against the original and Alpha variants of SARS-CoV-2 at 23% and 33% of seroprevalence, respectively 27 . The authors conclude that cHIT for SARS-CoV-2, given limited social distancing restrictions, could be lower than initially estimated and that phenomena could be explained by population heterogeneity.…”