| 1. |
- Giardina, Federica, et al.
(författare)
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Getting more from heterogeneous HIV-1 surveillance data in a high immigration country : estimation of incidence and undiagnosed population size using multiple biomarkers
- 2019
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Ingår i: International Journal of Epidemiology. - : Oxford University Press (OUP). - 0300-5771 .- 1464-3685. ; 48:6, s. 1795-1803
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Tidskriftsartikel (refereegranskat)abstract
- Background: Most HIV infections originate from individuals who are undiagnosed and unaware of their infection. Estimation of this quantity from surveillance data is hard because there is incomplete knowledge about (i) the time between infection and diagnosis (TI) for the general population, and (ii) the time between immigration and diagnosis for foreign-born persons.Methods: We developed a new statistical method for estimating the incidence of HIV-1 and the number of undiagnosed people living with HIV (PLHIV), based on dynamic modelling of heterogeneous HIV-1 surveillance data. The methods consist of a Bayesian non-linear mixed effects model using multiple biomarkers to estimate TI of HIV-1-positive individuals, and a novel incidence estimator which distinguishes between endogenous and exogenous infections by modelling explicitly the probability that a foreign-born person was infected either before or after immigration. The incidence estimator allows for direct calculation of the number of undiagnosed persons. The new methodology is illustrated combining heterogeneous surveillance data from Sweden between 2003 and 2015.Results: A leave-one-out cross-validation study showed that the multiple-biomarker model was more accurate than single biomarkers (mean absolute error 1.01 vs ≥1.95). We estimate that 816 [95% credible interval (CI) 775-865] PLHIV were undiagnosed in 2015, representing a proportion of 10.8% (95% CI 10.3-11.4%) of all PLHIV.Conclusions: The proposed methodology will enhance the utility of standard surveillance data streams and will be useful to monitor progress towards and compliance with the 90–90-90 UNAIDS target.
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| 2. |
- Nilsson, Anton, et al.
(författare)
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A directed acyclic graph for interactions
- 2021
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Ingår i: International Journal of Epidemiology. - : Oxford University Press (OUP). - 1464-3685 .- 0300-5771. ; 50:2, s. 613-619
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Directed acyclic graphs (DAGs) are of great help when researchers try to understand the nature of causal relationships and the consequences of conditioning on different variables. One fundamental feature of causal relations that has not been incorporated into the standard DAG framework is interaction, i.e. when the effect of one variable (on a chosen scale) depends on the value that another variable is set to. In this paper, we propose a new type of DAG-the interaction DAG (IDAG), which can be used to understand this phenomenon. METHODS: The IDAG works like any DAG but instead of including a node for the outcome, it includes a node for a causal effect. We introduce concepts such as confounded interaction and total, direct and indirect interaction, showing that these can be depicted in ways analogous to how similar concepts are depicted in standard DAGs. This also allows for conclusions on which treatment interactions to account for empirically. Moreover, since generalizability can be compromised in the presence of underlying interactions, the framework can be used to illustrate threats to generalizability and to identify variables to account for in order to make results valid for the target population. CONCLUSIONS: The IDAG allows for a both intuitive and stringent way of illustrating interactions. It helps to distinguish between causal and non-causal mechanisms behind effect variation. Conclusions about how to empirically estimate interactions can be drawn-as well as conclusions about how to achieve generalizability in contexts where interest lies in estimating an overall effect.
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| 3. |
- Holmberg, L, et al.
(författare)
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A search for recall bias in a case-control study of diet and breast cancer
- 1996
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Ingår i: INTERNATIONAL JOURNAL OF EPIDEMIOLOGY. - : OXFORD UNIV PRESS UNITED KINGDOM. - 0300-5771. ; 25:2, s. 235-244
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Tidskriftsartikel (refereegranskat)abstract
- Background. In retrospective studies of dietary habits and breast cancer risk, recall bias is a concern since diet has been publicized as a cause of breast cancer. Methods, In a case-control study of diet and breast cancer risk nested within a cohort of w
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