Is death from Covid-19 a multistep process?

medRxiv

Abstract

ABSTRACT Covid-19 death has a different relationship with age than is the case for other severe respiratory pathogens. The Covid-19 death rate increases exponentially with age, and the main risk factors are age itself, as well as having underlying conditions such as hypertension, diabetes, cardiovascular disease, severe chronic respiratory disease and cancer. Furthermore, the almost complete lack of deaths in children suggests that infection alone is not sufficient to cause death; rather, one must have gone through a number of changes, either as a result of undefined aspects of aging, or as a result of chronic disease. These characteristics of Covid-19 death are consistent with the multistep model of disease, a model which has primarily been used for cancer, and more recently for amyotrophic lateral sclerosis (ALS). We applied the multi-step model to data on Covid-19 case fatality rates (CFRs) from China, South Korea, Italy, Spain and Japan. In all countries we found that a plot of ln (CFR) against ln (age) was approximately linear with a slope of about 5. As a comparison, we also conducted similar analyses for selected other respiratory diseases. SARS showed a similar log-log age-pattern to that of Covid-19, albeit with a lower slope, whereas seasonal and pandemic influenza showed quite different age-patterns. Thus, death from Covid-19 and SARS appears to follow a distinct age-pattern, consistent with a multistep model of disease that in the case of Covid-19 is probably defined by comorbidities and age producing immune-related susceptibility. Identification of these steps would be potentially important for prevention and therapy for SARS-COV-2 infection.

Authors 10

1. Neil Pearce

   London School of Hygiene & Tropical Medicine

   Affiliation as printed

   London School of Hygiene and Tropical Medicine, London, UK

2. Giovenale Moirano

   University of Turin

   Affiliation as printed

   Unit of Cancer Epidemiology, Department of Medical Sciences, University of Turin

3. Milena Maria Maule

   University of Turin

   Affiliation as printed

   Unit of Cancer Epidemiology, Department of Medical Sciences, University of Turin

4. Manolis Kogevinas

   Municipal Institute for Medical Research · Barcelona Institute for Global Health · Hospital del Mar Research Institute

   Affiliation as printed

   IMIM (Hospital del Mar Research Institute), Barcelona, Spain

   ISGlobal, Barcelona, Spain

5. Xavier Rodó

   Institució Catalana de Recerca i Estudis Avançats · Barcelona Institute for Global Health

   Affiliation as printed

   ICREA, Barcelona, Spain

   ISGlobal, Barcelona, Spain

6. Debbie A. Lawlor

   University of Bristol · MRC Integrative Epidemiology Unit

   Affiliation as printed

   MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK

   Population Health, Bristol Medical School, University of Bristol, Bristol, UK

7. Jan Paul Vandenbroucke Aachen

   Aarhus University · Leiden University Medical Center · London School of Hygiene & Tropical Medicine

   Affiliation as printed

   Aarhus University Denmark

   Leiden University Medical Center, The Netherlands

   London School of Hygiene and Tropical Medicine, London, UK

8. Christina M. J. E. Vandenbroucke‐Grauls

   Amsterdam University Medical Centers

   Affiliation as printed

   Department of Medical Microbiology and Infection Prevention, Amsterdam UMC, The Netherlands

9. Fernando P. Polack

   Vanderbilt University · Infant Foundation

   Affiliation as printed

   Department of Pediatrics, Vanderbilt University, Nashville, TN

   Fundacion INFANT, Buenos Aires, Argentina

10. Adnan Čustović

    Imperial College London

    Affiliation as printed

    National Heart & Lung Institute, Imperial College London, United Kingdom