CSU 122/2011: DATA NEEDED FOR MODELING OF MEASLES IN DEVELOPING COUNTRIES

Wednesday, 6th of April 2011

Szusz and colleagues review existing datasets and look at those needed properly to model measles in developing countries.

'The classic threshold result describing the critical proportion immune (*p*c) required to eradicate an infectious disease, *p*c = 1-1/*R*0, may overestimate the required
proportion immune to eradicate measles in some developing country populations.’

Abstract is below; full text, at http://www.biomedcentral.com/1756-0500/3/75

Good reading.

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A review of data needed to parameterize a dynamic model of measles in developing countries

Emily K Szusz*1, Louis P Garrison*2 and Chris T Bauch*1

1 Department of Mathematics and Statistics, University of Guelph, Guelph,
Canada

2 Department of Pharmacy, University of Washington, Seattle, Washington,
USA

*BMC Research Notes* 2010, *3:*75doi:10.1186/1756-0500-3-75

The electronic version of this article is the complete one and can be found
online at: http://www.biomedcentral.com/1756-0500/3/75

© 2010 Bauch et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any
medium, provided the original work is properly cited.

Abstract

Background

Dynamic models of infection transmission can project future disease burden
within a population. Few dynamic measles models have been developed for
low-income countries, where measles disease burden is highest. Our objective
was to review the literature on measles epidemiology in low-income
countries, with a particular focus on data that are needed to parameterize
dynamic models.

Methods

We included age-stratified case reporting and seroprevalence studies with
fair to good sample sizes for mostly urban African and Indian populations.
We emphasized studies conducted before widespread immunization. We
summarized age-stratified attack rates and seroprevalence profiles across
these populations. Using the study data, we fitted a "representative"
seroprevalence profile for African and Indian settings. We also used a
catalytic model to estimate the age-dependent force of infection for
individual African and Indian studies where seroprevalence was surveyed. We
used these data to quantify the effects of population density on the basic
reproductive number *R*0.

Results

The peak attack rate usually occurred at age 1 year in Africa, and 1 to 2
years in India, which is earlier than in developed countries before mass
vaccination. Approximately 60% of children were seropositive for measles
antibody by age 2 in Africa and India, according to the representative
seroprevalence profiles. A statistically significant decline in the force of
infection with age was found in 4 of 6 Indian seroprevalence studies, but
not in 2 African studies. This implies that the classic threshold result
describing the critical proportion immune (*p*c) required to eradicate an
infectious disease, *p*c = 1-1/*R*0, may overestimate the required
proportion immune to eradicate measles in some developing country
populations. A possible, though not statistically significant, positive
relation between population density and *R*0 for various Indian and African
populations was also found. These populations also showed a similar pattern
of waning of maternal antibodies. Attack rates in rural Indian populations
show little dependence on vaccine coverage or population density compared to
urban Indian populations. Estimated *R*0 values varied widely across
populations which has further implications for measles elimination.

Conclusions

It is possible to develop a broadly informative dynamic model of measles transmission in low-income country settings based on existing literature, though it may be difficult to develop a model that is closely tailored to any given country. Greater efforts to collect data specific to low-income countries would aid in control efforts by allowing highly
population-specific models to be developed.