# An age-structured extension to the vectorial capacity model.

### Abstract

**BACKGROUND**

Vectorial capacity and the basic reproductive number (R(0)) have been instrumental
in structuring thinking about vector-borne pathogen transmission and how best to prevent
the diseases they cause. One of the more important simplifying assumptions of these
models is age-independent vector mortality. A growing body of evidence indicates that
insect vectors exhibit age-dependent mortality, which can have strong and varied affects
on pathogen transmission dynamics and strategies for disease prevention.**METHODOLOGY/PRINCIPAL FINDINGS**

Based on survival analysis we derived new equations for vectorial capacity and R(0)
that are valid for any pattern of age-dependent (or age-independent) vector mortality
and explore the behavior of the models across various mortality patterns. The framework
we present (1) lays the groundwork for an extension and refinement of the vectorial
capacity paradigm by introducing an age-structured extension to the model, (2) encourages
further research on the actuarial dynamics of vectors in particular and the relationship
of vector mortality to pathogen transmission in general, and (3) provides a detailed
quantitative basis for understanding the relative impact of reductions in vector longevity
compared to other vector-borne disease prevention strategies.**CONCLUSIONS/SIGNIFICANCE**

Accounting for age-dependent vector mortality in estimates of vectorial capacity and
R(0) was most important when (1) vector densities are relatively low and the pattern
of mortality can determine whether pathogen transmission will persist; i.e., determines
whether R(0) is above or below 1, (2) vector population growth rate is relatively
low and there are complex interactions between birth and death that differ fundamentally
from birth-death relationships with age-independent mortality, and (3) the vector
exhibits complex patterns of age-dependent mortality and R(0) ∼ 1. A limiting factor
in the construction and evaluation of new age-dependent mortality models is the paucity
of data characterizing vector mortality patterns, particularly for free ranging vectors
in the field.

### Links

### Authors

Novoseltsev VN, Michalski AI, Novoseltseva JA, Yashin AI, Carey JR, Ellis AM

### Source

### MeSH

Age FactorsAlgorithms

Animals

Basic Reproduction Number

Communicable Diseases

Disease Vectors

Humans

Longevity

Models, Statistical

Population Dynamics

### Pub Type(s)

Journal ArticleResearch Support, N.I.H., Extramural

Research Support, Non-U.S. Gov't

### Language

eng

### PubMed ID

22724022