ArticleBMC infectious diseases2016
DotMapper: an open source tool for creating interactive disease point maps.
Article in BMC infectious diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review.BMC medicine · 2018Pooled it
- The PHA4GE Microbial Data-Sharing Accord: establishing baseline consensus microbial data-sharing norms to facilitate cross-sectoral collaboration.BMJ global health · 2024Article
- Transmission visualizations of healthcare infection clusters: A scoping review.Antimicrobial stewardship & healthcare epidemiology : ASHE · 2022Article
- Risk characterisation and methods of improving practice for municipal waste management in disaster situations: A case study in Qom Province, Iran.Jamba (Potchefstroom, South Africa) · 2022Article
- To screen or not to screen: an interactive framework for comparing costs of mass malaria treatment interventions.BMC medicine · 2020Article
- Rapid Analysis of Diagnostic and Antimicrobial Patterns in R (RadaR): Interactive Open-Source Software App for Infection Management and Antimicrobial Stewardship.Journal of medical Internet research · 2019Article
- An interactive data visualisation application to investigate nosocomial transmission of infections.Wellcome open research · 2019Article
- EpiViewer: an epidemiological application for exploring time series data.BMC bioinformatics · 2018Article
- Public Health, Population Health, and Epidemiology Informatics: Recent Research and Trends in the United States.Yearbook of medical informatics · 2017Review
- Navigating an outbreak: geospatial methods for STI outbreak investigations.Sexually transmitted infections · 2016Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
backgroundMolecular strain typing of tuberculosis isolates has led to increased understanding of the epidemiological characteristics of the disease and improvements in its control, diagnosis and treatment. However, molecular cluster investigations, which aim to detect previously unidentified cases, remain challenging. Interactive dot mapping is a simple approach which could aid investigations by highlighting cases likely to share epidemiological links. Current tools generally require technical expertise or lack interactivity.
resultsWe designed a flexible application for producing disease dot maps using Shiny, a web application framework for the statistical software, R. The application displays locations of cases on an interactive map colour coded according to levels of categorical variables such as demographics and risk factors. Cases can be filtered by selecting combinations of these characteristics and by notification date. It can be used to rapidly identify geographic patterns amongst cases in molecular clusters of tuberculosis in space and time; generate hypotheses about disease transmission; identify outliers, and guide targeted control measures.
conclusionsDotMapper is a user-friendly application which enables rapid production of maps displaying locations of cases and their epidemiological characteristics without the need for specialist training in geographic information systems. Enhanced understanding of tuberculosis transmission using this application could facilitate improved detection of cases with epidemiological links and therefore lessen the public health impacts of the disease. It is a flexible system and also has broad international potential application to other investigations using geo-coded health information.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.