Literature DB >> 19538818

Episodic outbreaks bias estimates of age-specific force of infection: a corrected method using measles as an example.

M J Ferrari1, A Djibo, R F Grais, B T Grenfell, O N Bjørnstad.   

Abstract

Understanding age-specific differences in infection rates can be important in predicting the magnitude of and mortality in outbreaks and targeting age groups for vaccination programmes. Standard methods to estimate age-specific rates assume that the age-specific force of infection is constant in time. However, this assumption may easily be violated in the face of a highly variable outbreak history, as recently observed for acute immunizing infections like measles, in strongly seasonal settings. Here we investigate the biases that result from ignoring such fluctuations in incidence and present a correction based on the epidemic history. We apply the method to data from a measles outbreak in Niamey, Niger and show that, despite a bimodal age distribution of cases, the estimated age-specific force of infection is unimodal and concentrated in young children (<5 years) consistent with previous analyses of age-specific rates in the region.

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Year:  2009        PMID: 19538818      PMCID: PMC4520443          DOI: 10.1017/S0950268809990173

Source DB:  PubMed          Journal:  Epidemiol Infect        ISSN: 0950-2688            Impact factor:   2.451


  19 in total

1.  A simple model for complex dynamical transitions in epidemics.

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2.  Seroepidemiology of measles in Addis Ababa, Ethiopia: implications for control through vaccination.

Authors:  F Enquselassie; W Ayele; A Dejene; T Messele; A Abebe; F T Cutts; D J Nokes
Journal:  Epidemiol Infect       Date:  2003-06       Impact factor: 2.451

3.  The dynamics of measles in sub-Saharan Africa.

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Journal:  Nature       Date:  2008-02-07       Impact factor: 49.962

4.  Measles epidemic in Harare, Zimbabwe, despite high measles immunization coverage rates.

Authors:  R A Kambarami; K J Nathoo; F K Nkrumah; D J Pirie
Journal:  Bull World Health Organ       Date:  1991       Impact factor: 9.408

5.  Chaos and biological complexity in measles dynamics.

Authors:  B M Bolker; B T Grenfell
Journal:  Proc Biol Sci       Date:  1993-01-22       Impact factor: 5.349

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Authors:  J Remme; M P Mandara; J Leeuwenburg
Journal:  Int J Epidemiol       Date:  1984-09       Impact factor: 7.196

7.  An age-structured model of pre- and post-vaccination measles transmission.

Authors:  D Schenzle
Journal:  IMA J Math Appl Med Biol       Date:  1984

8.  Measles in England and Wales--I: An analysis of factors underlying seasonal patterns.

Authors:  P E Fine; J A Clarkson
Journal:  Int J Epidemiol       Date:  1982-03       Impact factor: 7.196

Review 9.  Measles in infants: a review of studies on incidence, vaccine efficacy and mortality in east Africa.

Authors:  B Burström; P Aaby; D M Mutie
Journal:  East Afr Med J       Date:  1995-03

10.  Unacceptably high mortality related to measles epidemics in Niger, Nigeria, and Chad.

Authors:  R F Grais; C Dubray; S Gerstl; J P Guthmann; A Djibo; K D Nargaye; J Coker; K P Alberti; A Cochet; C Ihekweazu; N Nathan; L Payne; K Porten; D Sauvageot; B Schimmer; F Fermon; M E Burny; B S Hersh; P J Guerin
Journal:  PLoS Med       Date:  2007-01       Impact factor: 11.069

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  17 in total

1.  Rural-urban gradient in seasonal forcing of measles transmission in Niger.

Authors:  Matthew J Ferrari; Ali Djibo; Rebecca F Grais; Nita Bharti; Bryan T Grenfell; Ottar N Bjornstad
Journal:  Proc Biol Sci       Date:  2010-04-28       Impact factor: 5.349

2.  Modelling the first dose of measles vaccination: the role of maternal immunity, demographic factors, and delivery systems.

Authors:  C J E Metcalf; P Klepac; M Ferrari; R F Grais; A Djibo; B T Grenfell
Journal:  Epidemiol Infect       Date:  2010-06-07       Impact factor: 2.451

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Authors:  A S Mahmud; C J E Metcalf; B T Grenfell
Journal:  Epidemiol Infect       Date:  2016-11-22       Impact factor: 2.451

4.  The epidemiology of rubella in Mexico: seasonality, stochasticity and regional variation.

Authors:  C J E Metcalf; O N Bjørnstad; M J Ferrari; P Klepac; N Bharti; H Lopez-Gatell; B T Grenfell
Journal:  Epidemiol Infect       Date:  2010-09-15       Impact factor: 2.451

5.  Heterogeneity in social and epidemiological factors determines the risk of measles outbreaks.

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6.  Impact of birth rate, seasonality and transmission rate on minimum levels of coverage needed for rubella vaccination.

Authors:  C J E Metcalf; J Lessler; P Klepac; F Cutts; B T Grenfell
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7.  Rubella metapopulation dynamics and importance of spatial coupling to the risk of congenital rubella syndrome in Peru.

Authors:  C J E Metcalf; C V Munayco; G Chowell; B T Grenfell; O N Bjørnstad
Journal:  J R Soc Interface       Date:  2010-07-21       Impact factor: 4.118

8.  Characterizing the dynamics of rubella relative to measles: the role of stochasticity.

Authors:  Ganna Rozhnova; C Jessica E Metcalf; Bryan T Grenfell
Journal:  J R Soc Interface       Date:  2013-09-11       Impact factor: 4.118

9.  Multiple estimates of transmissibility for the 2009 influenza pandemic based on influenza-like-illness data from small US military populations.

Authors:  Pete Riley; Michal Ben-Nun; Richard Armenta; Jon A Linker; Angela A Eick; Jose L Sanchez; Dylan George; David P Bacon; Steven Riley
Journal:  PLoS Comput Biol       Date:  2013-05-16       Impact factor: 4.475

10.  Serotype-Specific Transmission and Waning Immunity of Endemic Foot-and-Mouth Disease Virus in Cameroon.

Authors:  Laura W Pomeroy; Ottar N Bjørnstad; Hyeyoung Kim; Simon Dickmu Jumbo; Souley Abdoulkadiri; Rebecca Garabed
Journal:  PLoS One       Date:  2015-09-01       Impact factor: 3.240

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