Javier Perez-Saez, Stephen A Lauer, Laurent Kaiser, Simon Regard, Elisabeth Delaporte, Idris Guessous, Silvia Stringhini, Andrew S Azman, Davidovic Alioucha, Isabelle Arm-Vernez, Sultan Bahta, Jonathan Barbolini, Hélène Baysson, Rebecca Butzberger, Sophie Cattani, François Chappuis, Alison Chiovini, Prune Collombet, Delphine Courvoisier, David De Ridder, Eugénie De Weck, Paola D'ippolito, Antoine Daeniker, Odile Desvachez, Yaron Dibner, Céline Dubas, Joséphine Duc, Isabella Eckerle, Céline Eelbode, Nacira El Merjani, Benjamin Emery, Benoit Favre, Antoine Flahault, Natalie Francioli, Laurent Gétaz, Alice Gilson, Acem Gonul, Julie Guérin, Lina Hassar, Aurélia Hepner, Francesca Hovagemyan, Samia Hurst, Olivia Keiser, Melis Kir, Gaëlle Lamour, Pierre Lescuyer, Fanny Lombard, Amélie Mach, Yasmina Malim, Eva Marchetti, Kailing Marcus, Soraya Maret, Chantal Martinez, Kourosh Massiha, Virginie Mathey-Doret, Loan Mattera, Philippe Matute, Jean-Michel Maugey, Benjamin Meyer, Tom Membrez, Natacha Michel, Aleksandra Mitrovic, Emmanuelle Marie Mohbat, Mayssam Nehme, Natacha Noël, Hugo-Ken Oulevey, Febronio Pardo, Francesco Pennacchio, Dusan Petrovic, Attilio Picazio, Giovanni Piumatti, Didier Pittet, Jane Portier, Géraldine Poulain, Klara Posfay-Barbe, Jean-François Pradeau, Caroline Pugin, Rakotomiaramanana Barinjaka Rakotomiaramanana, Aude Richard, Christiane Rocchia Fine, Irine Sakvarelidze, Lilas Salzmann-Bellard, Magdalena Schellongova, Stephanie Schrempft, Mélanie Seixas Miranda, Milena Stimec, Michel Tacchino, Sophie Theurillat, Mélissa Tomasini, Kor-Gael Toruslu, Nawel Tounsi, Didier Trono, Natacha Vincent, Guillemette Violot, Nicolas Vuilleumier, Zoé Waldmann, Sylvie Welker, Manon Will, Ania Wisniak, Sabine Yerly, Maria-Eugenia Zaballa, and Alenka Zeballos Valle
The infection fatality risk (IFR) is the average number of deaths per infection by a pathogen and is key to characterizing the severity of infection across the population and for specific demographic groups. To date, there are few empirical estimates of IFR published due to challenges in measuring infection rates.1,2 Outside of closed, closely surveilled populations where infection rates can be monitored through viral surveillance, we must rely on indirect measures of infection, like specific antibodies. Representative seroprevalence studies provide an important avenue for estimating the number of infections in a community, and when combined with death counts can lead to robust estimates of the IFR. We estimated overall and age-specific IFR for the canton of Geneva, Switzerland using age-stratified daily case and death incidence reports combined with five weekly population-based seroprevalence estimates.3 From February 24th to June 2nd there were 5’039 confirmed cases and 286 reported deaths within Geneva (population of 506’765). We inferred age-stratified (5-9, 10-19, 20-49, 50-65 and 65+) IFRs by linking the observed number of deaths to the estimated number of infected individuals from each serosurvey. We account for the delays between infection and seroconversion as well as between infection and death.4 Inference is drawn in a Bayesian framework that incorporates uncertainty in seroprevalence estimates (supplement).Of the 286 reported deaths caused by SARS-CoV-2, the youngest person to die was 31 years old. Infected individuals younger than 50 years experienced statistically similar IFRs (range 0.00032-0.0016%), which increases to 0.14% (95% CrI 0.096-0.19) for those 50-64 years old to 5.6% (95% CrI 4.3-7.4) for those 65 years and older (supplement). After accounting for demography and age-specific seroprevalence, we estimate a population-wide IFR of 0.64% (95% CrI 0.38-0.98).Our results are subject to two notable limitations. Among the 65+ age group that died of COVID-19 within Geneva, 50% were reported among residents of assisted care facilities, where around 0.8% of the Geneva population resides. While the serosurvey protocol did not explicitly exclude these individuals, they are likely to have been under-represented. This would lead to an overestimation of the IFR in the 65+ age group if seroprevalence in this institutionalized population was higher than in the general population (supplement). Further, our IFR estimates are based on current evidence regarding post-infection antibody kinetics, which may differ between severe and mild infections. If mild infections have significantly lower and short-lived antibody responses, our estimates of IFR may be biased upwards.5Estimates of IFR are key for understanding the true pandemic burden and for weighing different risk reduction strategies. The IFR is not solely determined by host and pathogen biology, but also by the capacity of health systems to treat severe cases. Despite having among the highest per capita incidence in Switzerland, Geneva’s health system accommodated the influx of cases needing intensive care (peak of 80/110 ICU-beds including surge capacity) while maintaining care quality standards. As such, our IFR estimates can be seen as a best-case scenario with respect to health system capacity. Our results reveal that population-wide estimates of IFR mask great heterogeneity by age and point towards the importance of age-targeted interventions to reduce exposures among those at highest risk of death.