The unexpected dynamics of COVID-19 in Manaus, Brazil: Herd immunity versus interventions
He, D.; Artzy-Randrup, Y.; Musa, S. S.; Stone, L.
Show abstract
In late March 2020, SARS-CoV-2 arrived in Manaus, Brazil, and rapidly developed into a large-scale epidemic that collapsed the local health system, and resulted in extreme death rates. Several key studies reported that [~]76% of residents of Manaus were infected (attack rate AR[~=]76%) by October 2020, suggesting protective herd immunity had been reached. Despite this, in November an unexpected second wave of COVID-19 struck again, and proved to be larger than the first creating a catastrophe for the unprepared population. It has been suggested that this could only be possible if the second wave was driven by reinfections. Here we use novel methods to model the epidemic from mortality data, evaluate the impact of interventions, in order to provide an alternative explanation as to why the second wave appeared. The method fits a "flexible" reproductive number R0(t) that changes over the epidemic, and found AR[~=]30-34% by October 2020, for the first wave, which is far less than required for herd immunity, yet in-line with recent seroprevalence estimates. The two-strain model provides an accurate fit to observed epidemic datasets, and finds AR[~=]70% by March 2021. Using genomic data, the model estimates transmissibility of the new P.1 virus lineage, as 1.9 times as transmissible as the non-P1. The model thus provides a reasonable explanation for the two-wave dynamics in Manaus, without the need to rely on reinfections which until now have only been found in small numbers in recent surveillance efforts. SignificanceThis paper explores the concept of herd immunity and approaches for assessing attack rate during the explosive outbreak of COVID-19 in the city of Manaus, Brazil. The event has been repeatedly used to exemplify the epidemiological dynamics of the disease and the phenomenon of herd immunity, as claimed to be achieved by the end of the first wave in October 2020. A novel modelling approach reconstructs these events, specifically in the presence of interventions. The analysis finds herd immunity was far from being attained, and thus a second wave was readily possible, as tragically occurred in reality. Based on genomic data, the multi-strain model gives insights on the new highly transmissible variant of concern P.1 and role of reinfection.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Modelling COVID-19 in the North American region with a metapopulation network and Kalman filter 95%
- Impact of vaccination and non-pharmaceutical interventions on SARS-CoV-2 dynamics in Switzerland 94%
- Gaps in mobility data and implications for modelling epidemic spread: a scoping review and simulation study 93%
Similar papers in this journal
Similar papers in this journal
- Examining face-mask usage as an effective strategy to control COVID-19 spread 95%
- Identifying likely transmission pairs with pathogen sequence data using Kolmogorov Forward Equations; an application to M.bovis in cattle and badgers 94%
- Genetic determination of regional connectivity in modelling the spread of COVID-19 outbreak for improved mitigation strategies 94%
Similar papers in this journal
- Estimating the transmissibility of SARS-CoV-2 during periods of high, low and zero case incidence 94%
- Estimation and worldwide monitoring of the effective reproductive number of SARS-CoV-2 94%
- SARS-CoV-2 transmission dynamics in South Africa and epidemiological characteristics of the Omicron variant 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.