scispace - formally typeset
D

David J. D. Earn

Researcher at McMaster University

Publications -  128
Citations -  11162

David J. D. Earn is an academic researcher from McMaster University. The author has contributed to research in topics: Population & Pandemic. The author has an hindex of 43, co-authored 121 publications receiving 9746 citations. Previous affiliations of David J. D. Earn include University of Toronto & University of Cambridge.

Papers
More filters
Journal ArticleDOI

Vaccination and the theory of games.

TL;DR: It is shown that a formal game theoretical analysis of the problem of whether a sufficient proportion of the population is already immune, either naturally or by vaccination, leads to new insights that help to explain human decision-making with respect to vaccination.
Journal ArticleDOI

A simple model for complex dynamical transitions in epidemics.

TL;DR: This work has shown that measles is a natural ecological system that exhibits different dynamical transitions at different times and places, yet all of these transitions can be predicted as bifurcations of a single nonlinear model.
Journal ArticleDOI

A draft genome of Yersinia pestis from victims of the Black Death

TL;DR: A reconstructed ancient genome of Yersinia pestis is reported at 30-fold average coverage from Black Death victims securely dated to episodes of pestilence-associated mortality in London, England, 1348–1350, suggesting that contemporary Y. pestis epidemics have their origins in the medieval era.
Journal ArticleDOI

Surgical mask vs N95 respirator for preventing influenza among health care workers: a randomized trial.

TL;DR: A randomized controlled trial of 446 nurses in emergency departments, medical units, and pediatric units in 8 tertiary care Ontario hospitals showed that the use of a surgical mask compared with an N95 respirator resulted in non-inferior rates of laboratory-confirmed influenza.
Journal ArticleDOI

Interactions Between the Immune System and Cancer: A Brief Review of Non-spatial Mathematical Models

TL;DR: The simplest (single equation) models for tumor growth and greater immunological detail are considered and the necessity for expanding the complexity of models in order to capture the biological mechanisms the authors wish to understand is clarified.