Curating maternal, neonatal and child health (MNCH) datasets for spatiotemporal data analytics
Moses Effiong Ekpenyong, Patience Usoro Usip, Kommomo Jacob Usang, Nnamso Michael Umoh, Samuel Bisong Oyong, Chukwudi Obinna Nwokoro, Aminu Alhaji Suleiman, Kingsley Attai, Anietie Emmanuel John, Inyang Abraham Clement, Ekemini Anietie Johnson, Temitope Joel Fakiyesi

TL;DR
This paper describes curated maternal, neonatal, and child health datasets from Nigeria, including spatiotemporal data for research and policy.
Contribution
The novel contribution is the curation and detailed documentation of MNCH datasets with GPS data for spatiotemporal analysis.
Findings
The datasets include 538 maternal, 720 neonatal, and 425 child records from 2014 to 2019.
Variables like GPS data were captured to support demographic and spatiotemporal analysis.
Data privacy was maintained by replacing personal identifiers with patient numbers.
Abstract
We provide in this Data Note the details of maternal, neonatal and child health (MNCH) datasets curated directly from patients’ medical records; comprising 538 maternal, 720 neonatal and 425 child records, captured at St Luke’s General Hospital, Anua, Uyo, Nigeria, from 2014 to 2019. Variables included in the datasets are gender, age, class of patient (mother/infant/child), LGA (local government area), diagnosis, symptoms, prescription, blood pressure (mm Hg), temperature (degree centigrade), and weight (Kg). The purpose of this publication is to describe the datasets for researchers who may be interested in its reuse (for analysis, research, quality assurance, policy formulation/decision, patient safety, and more). The curated datasets also involved the capturing of location information (GPS: global positioning system data) from the study area, to aid spatiotemporal and informed…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
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Taxonomy
TopicsData-Driven Disease Surveillance · Mobile Health and mHealth Applications · Data Quality and Management
