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HIV incidence declines in a rural South African population: a G-imputation approach for inference

Ad hoc assumptions about the unobserved infection event, which is known only to occur between the latest-negative and earliest-positive test dates, can lead to biased HIV incidence rate estimates. Using a G-imputation approach, we infer the infection dates from covariate data to estimate the HIV inc...

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Hauptverfasser: Vandormael, Alain (VerfasserIn) , Cuadros, Diego (VerfasserIn) , Dobra, Adrian (VerfasserIn) , Bärnighausen, Till (VerfasserIn) , Tanser, Frank (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 06 August 2020
In: BMC public health
Year: 2020, Jahrgang: 20, Pages: 1-9
ISSN:1471-2458
DOI:10.1186/s12889-020-09193-4
Online-Zugang:Verlag, kostenfrei, Volltext: https://doi.org/10.1186/s12889-020-09193-4
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Verfasserangaben:Alain Vandormael, Diego Cuadros, Adrian Dobra, Till Bärnighausen and Frank Tanser
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Zusammenfassung:Ad hoc assumptions about the unobserved infection event, which is known only to occur between the latest-negative and earliest-positive test dates, can lead to biased HIV incidence rate estimates. Using a G-imputation approach, we infer the infection dates from covariate data to estimate the HIV incidence rate in a hyper-endemic South African setting.
Beschreibung:Gesehen am 18.09.2020
Beschreibung:Online Resource
ISSN:1471-2458
DOI:10.1186/s12889-020-09193-4

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