The Planetary Child Health & Enterics Observatory (Plan-EO): A protocol for an interdisciplinary research initiative and web-based dashboard for mapping enteric infectious diseases and their risk factors and interventions in LMICs

Abstract

Background: Diarrhea 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 pathogens. 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 has engendered a public appetite for interactive web-based dashboards for infectious diseases. However, enteric infectious diseases have been largely overlooked by these developments.

Methods: The Planetary Child Health & Enterics Observatory (Plan-EO) is a new initiative that builds on existing partnerships between epidemiologists, climatologists, bioinformaticians, and hydrologists as well as investigators in numerous low- and middle-income countries. 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. The initiative will produce, curate, and disseminate spatial data products relating to the distribution of enteric pathogens and their environmental and sociodemographic determinants.

Discussion: 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 key challenges and knowledge gaps by making and disseminating rigorously obtained, generalizable disease burden estimates. Pre-processed environmental and EO-derived spatial data products will be housed, continually updated, and made publicly available for download to the research and stakeholder communities. These can then be used as inputs to identify and target priority populations living in transmission hotspots and for decision-making, scenario-planning, and disease burden projection.

Study registration: PROSPERO protocol #CRD42023384709.

Fig 1. Data and process flow for the Plan-EO project.

Fig 2. Distribution of examples of three categories of covariate in LMICs.

a). Time-varying hydrometeorological—GLDAS soil moisture (annual average, 2018) [40]; b). Time-static environmental–enhanced vegetation index (EVI) [68]; c). Household-level–finished floor coverage; d). Preliminary Shigella prevalence estimates (mean of 2018 daily values for asymptomatic children aged 12–23 months) [36]. Base maps compiled from shapefiles obtained from U.S. Department of State—Humanitarian Information Unit [69] and Natural Earth free vector map data @ naturalearthdata.com that are made available in the public domain with no restrictions.

Fig 3

Illustrative visualizations of how a). observed, and b). predicted pathogen prevalence will be displayed on the dashboard. The data visualized has been described previously [36] and is provided here for illustrative purposes only.