Definitions, units and categories of the subject- and household-level covariates included in the Plan-EO database.

Definitions, units and categories of the subject- and household-level covariates included in the Plan-EO database.</p

Data and process flow for the Plan-EO project.

BackgroundDiarrhea 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.MethodsThe 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.DiscussionAs 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 registrationPROSPERO protocol #CRD42023384709.</div

Definitions and sources of environmental spatial covariates extracted from global rasters and included in the Plan-EO database.

Definitions and sources of environmental spatial covariates extracted from global rasters and included in the Plan-EO database.</p

Time-varying hydrometeorological variables calculated from estimates extracted from GLDAS [40] and included in the Plan-EO database.

Time-varying hydrometeorological variables calculated from estimates extracted from GLDAS [40] and included in the Plan-EO database.</p

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.</p

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.</p

Number of reads detected for <i>Campylobacter jejuni</i>, <i>C</i>. <i>coli</i>, <i>C</i>. <i>upsaliensis</i>, and <i>C</i>. <i>helveticus</i>, <i>C</i>. <i>concisus</i> and <i>C</i>. <i>infans</i> in human fecal samples, and qPCR status.

Samples highlighted in green show highlight 8 of 11 samples that were negative using cadF primers, positive with new rpsK/rpsD primers, and confirmed as having C jejuni or C. coli infection by metagenomic analysis.</p

Primer and probes used to detect <i>Campylobacter</i> spp. and <i>Campylobacter jejuni</i> / <i>Campylobacter coli</i>.

Primer and probes used to detect Campylobacter spp. and Campylobacter jejuni / Campylobacter coli.</p

Contingency Tables of <i>Campylobacter</i> spp (16S rRNA), and <i>Campylobacter jejuni</i>/ <i>Campylobacter coli</i> using the cadF primer probe set and the <i>rpsK/rpsD</i> primer probe set.

Using the cadF primers, 66% (31/47) Campylobacter infections would be assigned to “other Campylobacter” whereas only 41.3% (19/46) Campylobacter infections would be assigned to this category using newly designed rpsK/rpsD primer set. No specimens that were cadF positive were negative using rpsK/rpsD primers.</p

The other <i>Campylobacters</i>: Not innocent bystanders in endemic diarrhea and dysentery in children in low-income settings

<div><p>Background</p><p><i>Campylobacter</i> is one of the main causes of gastroenteritis worldwide. Most of the current knowledge about the epidemiology of this food-borne infection concerns two species, <i>C</i>. <i>coli</i> and <i>C</i>. <i>jejuni</i>. Recent studies conducted in developing countries and using novel diagnostic techniques have generated evidence of the increasing burden and importance of other <i>Campylobacter</i> species, i.e. non-<i>C</i>. <i>coli/jejuni</i>. We performed a nested case-control study to compare the prevalence of <i>C</i>. <i>coli/jejuni</i> and other <i>Campylobacter</i> in children with clinical dysentery and severe diarrhea as well as without diarrhea to better understand the clinical importance of infections with <i>Campylobacter</i> species other than <i>C</i>. <i>coli/jejuni</i>.</p><p>Methodology/Principal findings</p><p>Our nested case-control study of 439 stool samples included dysenteric stools, stools collected during severe diarrhea episodes, and asymptomatic stools which were systematically selected to be representative of clinical phenotypes from 9,160 stools collected during a birth cohort study of 201 children followed until two years of age. Other <i>Campylobacter</i> accounted for 76.4% of the 216 <i>Campylobacter</i> detections by qPCR and were more prevalent than <i>C</i>. <i>coli/jejuni</i> across all clinical groups. Other <i>Campylobacter</i> were also more prevalent than <i>C</i>. <i>coli/jejuni</i> across all age groups, with older children bearing a higher burden of other <i>Campylobacter</i>. Biomarkers of intestinal inflammation and injury (methylene blue, fecal occult test, myeloperoxidase or MPO) showed a strong association with dysentery, but mixed results with infection. MPO levels were generally higher among children infected with <i>C</i>. <i>coli/jejuni</i>, but <i>Shigella</i>-infected children suffering from dysentery recorded the highest levels (26,224 ng/mL); the lowest levels (10,625 ng/mL) were among asymptomatic children infected with other <i>Campylobacter</i>. Adjusting for age, sex, and <i>Shigella</i> infection, dysentery was significantly associated with <i>C</i>. <i>coli/jejuni</i> but not with other <i>Campylobacter</i>, whereas severe diarrhea was significantly associated with both <i>C</i>. <i>coli/jejuni</i> and other <i>Campylobacter</i>. Compared to asymptomatic children, children suffering from dysentery had a 14.6 odds of <i>C</i>. <i>coli/jejuni</i> infection (p-value < 0.001, 95% CI 5.5–38.7) but were equally likely to have other <i>Campylobacter</i> infections–odds ratio of 1.3 (0.434, 0.7–2.4). Children suffering from severe diarrhea were more likely than asymptomatic children to test positive for both <i>C</i>. <i>coli/jejuni</i> and other <i>Campylobacter</i>–OR of 2.8 (0.034, 1.1–7.1) and 1.9 (0.018, 1.1–3.1), respectively. Compared to the <i>Campylobacter</i>-free group, the odds of all diarrhea given <i>C</i>. <i>coli/jejuni</i> infection and other <i>Campylobacter</i> infection were 8.8 (<0.001, 3.0–25.7) and 2.4 (0.002, 1.4–4.2), respectively. Eliminating other <i>Campylobacter</i> in this population would eliminate 24.9% of the diarrhea cases, which is almost twice the population attributable fraction of 15.1% due to <i>C</i>. <i>coli/jejuni</i>.</p><p>Conclusions/Significance</p><p>Eighty-seven percent of the dysentery and 59.5% of the severe diarrhea samples were positive for <i>Campylobacter</i>, <i>Shigella</i>, or both, emphasizing the importance of targeting these pathogens to limit the impact of dysentery and severe diarrhea in children. Notably, the higher prevalence of other <i>Campylobacter</i> compared to <i>C</i>. <i>coli/jejuni</i>, their increasing burden during early childhood, and their association with severe diarrhea highlight the importance of these non-<i>C</i>. <i>coli/jejuni Campylobacter</i> species and suggest a need to clarify their importance in the etiology of clinical disease across different epidemiological contexts.</p></div