Výsledky vyhledávání - "Terlouw, Dianne"

Dissertation/ Thesis

Community-based studies on the epidemiology, treatment and prevention of malaria in an area of intense malaria transmission in western Kenya

Autor: Terlouw, Dianne Janette

Proefschrift Universiteit van Amsterdam.
Met lit. opg., bibliogr. - Met samenvatting in het Nederlands.

Externí odkaz: http://dare.uva.nl/document/67732

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Unfolding selection to infer individual risk heterogeneity for optimising disease forecasts and policy development

Autor: Gomes, M. Gabriela M., Feasey, Nicholas A., Ferreira, Marcelo U., LaCourse, E. James, Langwig, Kate E., Reimer, Lisa, Ringwald, Beate, Rylance, Jamie, Stothard, J. Russell, Taegtmeyer, Miriam, Terlouw, Dianne J., Tolhurst, Rachel, Wingfield, Tom, Gordon, Stephen B.

Mathematical models are increasing adopted for setting targets for disease prevention and control. As model-informed policies are implemented, however, the inaccuracies of some forecasts become apparent, for example overprediction of infection burden

Externí odkaz: http://arxiv.org/abs/2009.01354

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Inhibitory geostatistical designs for spatial prediction taking account of uncertain covariance structure

Autor: Chipeta, Michael G., Terlouw, Dianne J., Phiri, Kamija S., Diggle, Peter J.

The problem of choosing spatial sampling designs for investigating unobserved spatial phenomenon S arises in many contexts, for example in identifying households to select for a prevalence survey to study disease burden and heterogeneity in a study r

Externí odkaz: http://arxiv.org/abs/1605.00104

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Adaptive Geostatistical Design and Analysis for Sequential Prevalence Surveys

Autor: Chipeta, Michael G., Terlouw, Dianne J., Phiri, Kamija, Diggle, Peter J.

Non-adaptive geostatistical designs (NAGD) offer standard ways of collecting and analysing geostatistical data in which sampling locations are fixed in advance of any data collection. In contrast, adaptive geostatistical designs (AGD) allow collectio

Externí odkaz: http://arxiv.org/abs/1509.04448

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Combining data from multiple spatially referenced prevalence surveys using generalized linear geostatistical models

Autor: Giorgi, Emanuele, Sesay, Sanie S. S., Terlouw, Dianne J., Diggle, Peter J.

Data from multiple prevalence surveys can provide information on common parameters of interest, which can therefore be estimated more precisely in a joint analysis than by separate analyses of the data from each survey. However, fitting a single mode

Externí odkaz: http://arxiv.org/abs/1308.2790

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