The Planetary Child Health and Enterics Observatory (Plan-EO): An Interdisciplinary Research Initiative and Web-Based Dashboard for Climate-Informed Mapping of Enteric Infectious Diseases and Their Risk Factors and Interventions in Low- and Middle-Income Countries

Diarrheal disease remains a leading cause of childhood illness throughout the world that is increasing due to climate change and is caused by various species of ecologically sensitive enteric pathogens, including viruses, bacteria, and protozoa. The emerging Planetary Health movement emphasizes the interdependence of human health with natural systems, and much of its focus has been on infectious diseases and their interactions with environmental and human processes. Meanwhile, the era of big data coinciding with the COVID-19 pandemic has engendered a public appetite for interactive web-based dashboards for monitoring infectious diseases. However, enteric infectious diseases have been largely overlooked by these developments.

The Planetary Child Health and Enterics Observatory (Plan-EO, pronounced “plan-ei-oh”) is a new initiative that builds on existing partnerships between epidemiologists, climatologists, bioinformaticians, and hydrologists as well as investigators in numerous LMICs. Its objective is to provide the research and stakeholder community with an evidence base for the geographical targeting of enteropathogen-specific child health interventions such as novel vaccines. Specifically, it aims to apply a big data approach to the modeling of EIDs in combination with advanced geostatistical analyses and global Earth Observation (EO)-derived climate datasets, to produce generalizable estimates of the geographical distribution of these outcomes and of their associations with environmental drivers disseminated via an interactive web-based dashboard.

The Plan-EO team is compiling a comprehensive repository of georeferenced epidemiological data based on PCR diagnostics sourced from studies in diverse Low- and Middle-Income Countries (LMICs) that together represent the broadest and most representative range of currently available climate zones and environmental contexts. An initial list of pathogens has been selected based on their being either highly endemic or responsible for high diarrheal disease morbidity in LMICs as well as to be representative of the three major enteropathogen taxa. These include 5 enteric viruses – adenovirus, astrovirus, norovirus, rotavirus and sapovirus – 3 bacteria – Campylobacter, ETEC and Shigella – and two protozoa – Cryptosporidium and Giardia. Disease data from tens of thousands of human subjects in 25 countries are stored and processed in accordance with a HIPAA-compliant data management plan that has received IRB approval, and are then linked spatiotemporally (by data and location) with a suite of covariate variables that fall into three categories:

a). Time-varying hydrometeorological variables: A set of historical daily Earth Observation- and model-based re-analysis-derived estimates of hydrometeorological variables have been selected based on their demonstrated or hypothesized potential to influence enteric pathogen transmission. These are extracted from version 2.1 of the Global Land Data Assimilation System (GLDAS) and include not only variables that are commonly considered as disease transmission drivers such as ambient temperature, precipitation volume, wind speed and solar radiation but also parameters such as soil moisture, specific humidity and surface runoff, which are not routinely reported by ground-based sources.

b). Environmental spatial covariates: A set of time-static environmental and sociodemographic spatial covariates have been compiled in raster file format based on their hypothesized or demonstrated associations with diarrheal disease outcomes. These include Köppen-Geiger climate classification, Enhanced Vegetation Index (EVI), and potential evapotranspiration.

c). Subject- and household-level covariates: These data are supplied by the contributing studies and will be recoded to match as closely as possible standardly used variable definitions, units, and categories. They include factors such as drinking water source (groundwater, piped, surface water), housing construction materials, and livestock husbandry.

Dissemination of and stakeholder engagement with our findings is central to Plan-EO’s mission and will consist of two components:

i). An interactive web-based dashboard: We will establish a data access and visualization system and suite of interactive maps to collate and disseminate the data products (comparable to WorldPop, the Malaria Atlas Project, or the DHS Program’s Spatial Data Repository). It will provide users with an interactive portal to explore the resulting pathogen-specific risk maps and the pre-processed environmental and EO-derived spatial data outputs. This repository of products will be continually updated and made publicly available to the research and stakeholder communities both within the webpage itself and for download in commonly used GIS formats.

ii). An international consortium of investigators: A global network of collaborating researchers (with a majority being early-career and/or from LMICs) will be fostered and coordinated out of the Plan-EO headquarters at the University of Virginia (UVA).

As climate change accelerates there is an urgent need for etiology-specific estimates of diarrheal disease burden at high spatiotemporal resolution. Plan-EO aims to address these challenges and knowledge gaps by making rigorously obtained, generalizable disease burden estimates freely available and accessible to the research and stakeholder communities. Pre-processed environmental and EO-derived spatial data products will be housed, continually updated, and made publicly available to the research and stakeholder communities both within the webpage itself and for download. These inputs can then be used to identify and target priority populations living in transmission hotspots and for decision-making, scenario-planning, and disease burden projection, an evidence base that is urgently needed to underpin a proposed reorientation towards radical, transformative WASH and Planetary Health agendas. Its findings also have the potential to generate novel hypotheses about the drivers of enteropathogen transmission, risk, and seasonality that can be further tested and findings to be replicated in other settings. Results from pathogen-specific infection risk models can be used to assess their relative sensitivity to changes in climate compared to other determinants such as sanitation improvements and to develop a scenario-based framework to support decision-making, resource allocation and identification of priority populations for targeting pathogen-specific interventions such as novel vaccines.