4 citations · 5 across the 3 of their papers we have counts for
4 papers
Unfolding selection to infer individual risk heterogeneity for optimising disease forecasts and policy development
M. Gabriela M. Gomes, Nicholas A. Feasey, Marcelo U. Ferreira +11
Mathematical models are increasing adopted for setting targets for disease prevention and control. As model-informed policies are implemented, however, the inaccuracies of some for…
Inhibitory geostatistical designs for spatial prediction taking account of uncertain covariance structure
Michael G. Chipeta, Dianne J. Terlouw, Kamija S. Phiri +1
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 pr…
Adaptive Geostatistical Design and Analysis for Sequential Prevalence Surveys
Michael G. Chipeta, Dianne J. Terlouw, Kamija Phiri +1
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 collecti…
Combining data from multiple spatially referenced prevalence surveys using generalized linear geostatistical models
Emanuele Giorgi, Sanie S. S. Sesay, Dianne J. Terlouw +1
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…