Some simple rules for estimating reproduction numbers in the presence of reservoir exposure or imported cases

Date

2020

Authors

McLure, Angus
Glass, Katie

Journal Title

Journal ISSN

Volume Title

Publisher

Academic Press

Abstract

For many diseases, the basic reproduction number () is a threshold parameter for disease extinction or survival in isolated populations. However no human population is fully isolated from other human or animal populations. We use compartmental models to derive simple rules for the basic reproduction number in populations where an endemic disease is sustained by a combination of local transmission within the population and exposure from some other source: either a reservoir exposure or imported cases. We introduce the idea of a reservoir-driven or importation-driven disease: diseases that would become extinct in the population of interest without reservoir exposure or imported cases (since ), but nevertheless may be sufficiently transmissible that many or most infections are acquired from humans in that population. We show that in the simplest case, if and only if the proportion of infections acquired from the external source exceeds the disease prevalence and explore how population heterogeneity and the interactions of multiple strains affect this rule. We apply these rules in two case studies of Clostridium difficile infection and colonisation: C. difficile in the hospital setting accounting for imported cases, and C. difficile in the general human population accounting for exposure to animal reservoirs. We demonstrate that even the hospital-adapted, highly-transmissible NAP1/RT027 strain of C. difficile had a reproduction number <1 in a landmark study of hospitalised patients and therefore was sustained by colonised and infected admissions to the study hospital. We argue that C. difficile should be considered reservoir-driven if as little as 13.0% of transmission can be attributed to animal reservoirs

Description

Keywords

Reproduction number, Imported cases, Zoonosis, Infectious disease modelling, Heterogeneity, Clostridium difficile

Citation

Source

Theoretical Population Biology

Type

Journal article

Book Title

Entity type

Access Statement

License Rights

DOI

10.1016/j.tpb.2020.04.002

Restricted until