An Integrated Approach for Spatio-Temporal Cholera Disease Hotspot Relation Mining for Public Health Management in Punjab, Pakistan

Fatima Khalique, Shoab Ahmed Khan, Wasi Haider Butt and Irum Matloob
Additional contact information
Fatima Khalique: Department of Computer and Software Engineering, National University of Sciences and Technology, Islamabad 44000, Pakistan
Shoab Ahmed Khan: Department of Computer and Software Engineering, National University of Sciences and Technology, Islamabad 44000, Pakistan
Wasi Haider Butt: Department of Computer and Software Engineering, National University of Sciences and Technology, Islamabad 44000, Pakistan
Irum Matloob: Department of Computer and Software Engineering, National University of Sciences and Technology, Islamabad 44000, Pakistan

IJERPH, 2020, vol. 17, issue 11, 1-18

Abstract: Public health management can generate actionable results when diseases are studied in context with other candidate factors contributing to disease dynamics. In order to fully understand the interdependent relationships of multiple geospatial features involved in disease dynamics, it is important to construct an effective representation model that is able to reveal the relationship patterns and trends. The purpose of this work is to combine disease incidence spatio-temporal data with other features of interest in a mutlivariate spatio-temporal model for investigating characteristic disease and feature patterns over identified hotspots. We present an integrated approach in the form of a disease management model for analyzing spatio-temporal dynamics of disease in connection with other determinants. Our approach aligns spatio-temporal profiles of disease with other driving factors in public health context to identify hotspots and patterns of disease and features of interest in the identified locations. We evaluate our model against cholera disease outbreaks from 2015–2019 in Punjab province of Pakistan. The experimental results showed that the presented model effectively address the complex dynamics of disease incidences in the presence of other features of interest over a geographic area representing populations and sub populations during a given time. The presented methodology provides an effective mechanism for identifying disease hotspots in multiple dimensions and relation between the hotspots for cost-effective and optimal resource allocation as well as a sound reference for further predictive and forecasting analysis.

Keywords: cholera dynamics; health data analytic; integrated health modeling framework; public health; spatio-temporal analysis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1660-4601/17/11/3763/pdf (application/pdf)
https://www.mdpi.com/1660-4601/17/11/3763/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:17:y:2020:i:11:p:3763-:d:363115

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().