PoolTestR: An R package for estimating prevalence and regression modelling with pooled samples

12/10/2020
by   Angus McLure, et al.
0

Pooled testing (also known as group testing), where diagnostic tests are performed on pooled samples, has broad applications in the surveillance of diseases in animals and humans. An increasingly common use case is molecular xenomonitoring (MX), where surveillance of vector-borne diseases is conducted by capturing and testing large numbers of vectors (e.g. mosquitoes). The R package PoolTestR was developed to meet the needs of increasingly large and complex molecular xenomonitoring surveys but can be applied to analyse any data involving pooled testing. PoolTestR includes simple and flexible tools to estimate prevalence and fit fixed- and mixed-effect generalised linear models for pooled data in frequentist and Bayesian frameworks. Mixed-effect models allow users to account for the hierarchical sampling designs that are often employed in surveys, including MX. We demonstrate the utility of PoolTestR by applying it to a large synthetic dataset that emulates a MX survey with a hierarchical sampling design.

READ FULL TEXT

page 11

page 12

page 13

research
08/21/2023

Bayesian Prevalence Estimation from Pooled and Individual Data

Pooled and individual disease testing are common methods for determining...
research
11/11/2021

Pool samples to efficiently estimate pathogen prevalence dynamics

Estimating the prevalence of a disease is necessary for evaluating and m...
research
06/17/2021

Optimum Allocation for Adaptive Multi-Wave Sampling in R: The R Package optimall

The R package optimall offers a collection of functions that efficiently...
research
06/14/2023

Modernising the Design and Analysis of Prevalence Surveys for Neglected Tropical Diseases

Current WHO guidelines set prevalence thresholds below which a Neglected...
research
02/11/2023

Optimal Sampling Design Under Logistical Constraints with Mixed Integer Programming

The goal of survey design is often to minimize the errors associated wit...
research
06/18/2021

Generalized Linear Randomized Response Modeling using GLMMRR

Randomized response (RR) designs are used to collect response data about...
research
11/14/2022

Jittering Impacts Raster- and Distance-based Geostatistical Analyses of DHS Data

Fine-scale covariate rasters are routinely used in geostatistical models...

Please sign up or login with your details

Forgot password? Click here to reset