ArticleInfluenza and other respiratory viruses2018
Influenza-associated mortality in South Africa, 2009-2013: The importance of choices related to influenza infection proxies.
Article in Influenza and other respiratory viruses, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- The epidemiology of seasonal influenza after the 2009 influenza pandemic in Africa: a systematic review.African health sciences · 2020Pooled it
- Excess Respiratory Hospitalisations Associated with Influenza, Respiratory Syncytial Virus and SARS-CoV-2 in Singapore from 2015 to 2023.Influenza and other respiratory viruses · 2025Article
- Estimates of influenza-associated hospitalisations in tropical Singapore, 2010-2017: Higher burden estimated in more recent years.Influenza and other respiratory viruses · 2019Article
- Influenza-associated mortality in South Africa, 2009-2013: The importance of choices related to influenza infection proxies.Influenza and other respiratory viruses · 2018Article
- Advances in measuring influenza burden of disease.Influenza and other respiratory viruses · 2018Article
- Impact of seasonal influenza on polyclinic attendances for upper respiratory tract infections in Singapore.Western Pacific surveillance and response journal : WPSARArticle
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 3 countries.
Funding
Abstract
backgroundRegression modeling methods are commonly used to estimate influenza-associated mortality using covariates such as laboratory-confirmed influenza activity in the population as a proxy of influenza incidence.
objectiveWe examined the choices of influenza proxies that can be used from influenza laboratory surveillance data and their impact on influenza-associated mortality estimates.
methodSemiparametric generalized additive models with a smoothing spline were applied on national mortality data from South Africa and influenza surveillance data as covariates to obtain influenza-associated mortality estimates from respiratory causes from 2009 to 2013. Proxies examined included alternative ways of expressing influenza laboratory surveillance data such as weekly or yearly proportion or rate of positive samples, using influenza subtypes, or total influenza data and expressing the data as influenza season-specific or across all seasons.
resultBased on model fit, weekly proportion and influenza subtype-specific proxy formulation provided the best fit. The choice of proxies used gave large differences to mortality estimates, but the 95% confidence interval of these estimates overlaps.
conclusionRegardless of proxy chosen, mortality estimates produced may be broadly consistent and not statistically significant for public health practice.
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