# Global Geospatial Mapping and Modeling of Household-level Covariates of Infectious Disease Transmission and Child Health

> **NIH NIH R03** · UNIVERSITY OF VIRGINIA · 2021 · $80,294

## Abstract

PROJECT SUMMART/ABSTRACT
Many health outcomes of international public health importance can be mapped at global or continental scale
and high resolution using geostatistical methods combined with publicly available georeferenced data. Several
household-level determinants of enteric infectious disease (EID) transmission are routinely ascertained in
censuses and surveys but have yet to be comprehensively mapped at high resolution for EID-endemic regions:
access to an improved drinking water source and sanitation facility, having a covered floor (as opposed to bare
earth), caregiver education and crowded living conditions. Without high-resolution sub-national estimates of the
distribution of these covariates within at-risk populations, it will not be possible to produce pathogen-specific
estimates of disease burden to inform vaccine development and program priorities. The long-term goal of this
proposed project is to provide reliable estimates of populations at elevated risk of EID transmission to inform the
allocation of public health resources. The overall objective is to provide the research community with
standardized geostatistical model-based maps of the current and near-future distribution of five important
household-level risk factors for EID transmission in a format that can be easily used in a geographic information
system (GIS). The central hypothesis is that prevalence of these factors varies spatiotemporally as a function of
geography, socio-demography and environment and can be modelled using publicly available global datasets
and geostatistical methods. The rationale underlying the proposed research is that high resolution global maps
of the selected covariates will make it possible to identify hotspots of infectious disease transmission risk, further
map the predicted incidence of selected pathogens over large areas and project trends several years into the
future. We plan to objectively test the central hypothesis and thereby attain the objective of this project by
pursuing the following specific aims: Aim 1: Compile a large database of georeferenced data relating to five
selected household-level covariates of infectious disease transmission. Aim 2: Produce and make
publicly available global modeled surfaces of each covariate using standardized geostatistical methods,
environmental covariates. Data relating to these five household-level risk factors will first be compiled from
publicly available census and household survey data. Then project will produce raster files using
spatiotemporally explicit hierarchical generalized linear regression model will be fitted to the point-prevalence
data within a Bayesian model-based geostatistical framework and using a suite of candidate environmental and
socio-demographic predictors selected by generalized additive models. The gridded predictions will be made
available to the public for download through an online repository, so that they can be imported into a GIS and
used in further analyses by...

## Key facts

- **NIH application ID:** 10119239
- **Project number:** 5R03AI151564-02
- **Recipient organization:** UNIVERSITY OF VIRGINIA
- **Principal Investigator:** Margaret N Kosek
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $80,294
- **Award type:** 5
- **Project period:** 2020-03-04 → 2022-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10119239

## Citation

> US National Institutes of Health, RePORTER application 10119239, Global Geospatial Mapping and Modeling of Household-level Covariates of Infectious Disease Transmission and Child Health (5R03AI151564-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10119239. Licensed CC0.

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