Bayesian joint geostatistical + extreme-value model for high-intensity Loa loa microfilaraemia risk (ivermectin MDA safety), south-eastern Nigeria
# Loa loa high-intensity risk mapping with extreme-value theory
Code for a Bayesian **joint geostatistical and extreme-value** model that predicts
where dangerously high *Loa loa* microfilarial loads (>20,000 mf/mL) are appreciably
common, to support the safety of ivermectin mass drug administration (MDA) for
onchocerciasis and lymphatic filariasis in loiasis co-endemic areas. The analysis is
applied to a survey of south-eastern Nigeria (Abia, Anambra, Delta, Ebonyi, Imo).
The model
1. maps infection **prevalence** (logistic geostatistical regression),
2. maps microfilarial **intensity** among positives (lognormal body), the two fields
linked by a **bivariate Gaussian process** (intrinsic coregionalisation), and
3. characterises the **upper tail** of intensity with a peaks-over-threshold
**generalised Pareto distribution (GPD)** — necessary because the threshold of
concern (20,000 mf/mL) lies beyond the largest observed density.
For each Local Government Area (LGA) it reports `P(q_g [Authors]. *Predicting where few people carry dangerously high Loa loa
> microfilarial loads: a Bayesian joint geostatistical and extreme-value analysis to
> support safe ivermectin mass treatment in south-eastern Nigeria.* (in preparation /
> under review).
> **DOI: _to be added on publication._**
Closely related prior work using geostatistics for loiasis MDA safety assessment:
Johnson O, Giorgi E, Fronterrè C, et al. *Geostatistical modelling enables efficient
safety assessment for mass drug administration with ivermectin in Loa loa endemic
areas...* PLOS Negl Trop Dis. 2022;16(2):e0010189.
## Repository layout
```
code/
NGA_common.R Model definitions: Stan hurdle + ICM GP, GPD tail,
kriging, exact per-LGA prediction, helpers (CFG, load_nga)
NGA_fix_data.R Data-relabelling step (two misgeocoded villages)
NGA_gee_extract.py Google Earth Engine extraction of environmental covariates
NGA_validation.R Adequacy gate: convergence, calibrat …