Attack rate of COVID-19 and the onset of herd immunity in Manaus, Brazil (preprint)

Buss et al. (2021) and Faria et al. (2021) reported that ~76% of the residents of the capital city of Manaus, had been infected by SARS-CoV-2 by October 2020 suggesting that herd immunity had been achieved by the end of the first wave. But the announcement of herd immunity, which would imply reasonable protection from future outbreaks, only provided the Manaus population with a false sense of security. Within two months later, a second wave of COVID-19 was initiated with death rates much larger than the first attributed to the appearance of the new P.1 Variant of Concern. Faria et al. (2021) suggest that large scale reinfections played an important role in enabling the huge second epidemic wave. In this Technical Comment we challenge such interpretations, and provide quantitative arguments that suggest the attack rate of the first wave was well below 76%. We then present alternative interpretations of the data.

The unexpected dynamics of COVID-19 in Manaus, Brazil: Herd immunity versus interventions (preprint)

The arrival of SARS-COV-2 in late March 2020 in the state of Amazonas, Brazil, captured worldwide attention and concern. The rapid growth of the epidemic, a health system that had collapsed, and mass gravesites for coping with growing numbers of dead, were broadcast by the media around the world. Moreover, a majority of the local Amazonian indigenous communities were physically distant from appropriate medical services, to the point where warnings of genocide were issued. In a recent Science paper (December 2020), Buss et al. reported that some 76% of the residents of the city of Manaus, the capital of Amazonas, had been infected by October 2020. This estimate of the COVID-19 attack rate was based on a seroprevalence analysis of blood donor data, which despite its shortcomings was thought to be a sufficiently reliable proxy of the larger population. An attack rate of this magnitude (76%) implied that herd immunity had already been reached and the community was relatively protected from further infection. Yet in December 2020, a harsh second wave of COVID-19 struck Manaus, and currently appears to be even larger than the first wave. Here we use mathematical modelling of mortality data in Manaus, and in various states of Brazil, to understand why a second wave appeared against all expectations. Our analysis is based on estimating a "flexible" reproductive number R0(t) from the mortality data, as it changes in time over the epidemic.