Table 1.

Bias required in reported COVID-19 deaths to reproduce local seroprevalence estimates

Country	Seroprevalence estimate	Scaling model estimate	B (bias required)
USA (Santa Clara)	3%	0.4%	0.15
Italy (Robbio)	10%	1.7%	0.20
Germany (Gangelt)	14%	0.2%	0.01

Central COVID-19 prevalence estimates for middle of April 2020, percent, according to local seroprevalence studies and our demographic scaling model, for the USA, Italy and Germany. Also shown is the amount of bias (B; here: under-reporting) that would be required to explain their discrepancy. For example, a bias of 0.2 for Italy could suggest that only one in five COVID-19 deaths would have been reported in order to explain the seroprevalence estimate with our scaling model estimate. Data source for seroprevalence estimates: Bendavid et al.³ Own calculations using estimates of Bendavid et al.,³ Verity et al.,²¹ United Nations World Population Prospects²³ and Johns Hopkins University Center for Systems Science and Engineering as of 17 April 2020.¹⁶