Using mobile phone data to predict the spatial spread of cholera
- PMID: 25747871
- PMCID: PMC4352843
- DOI: 10.1038/srep08923
Using mobile phone data to predict the spatial spread of cholera
Abstract
Effective response to infectious disease epidemics requires focused control measures in areas predicted to be at high risk of new outbreaks. We aimed to test whether mobile operator data could predict the early spatial evolution of the 2010 Haiti cholera epidemic. Daily case data were analysed for 78 study areas from October 16 to December 16, 2010. Movements of 2.9 million anonymous mobile phone SIM cards were used to create a national mobility network. Two gravity models of population mobility were implemented for comparison. Both were optimized based on the complete retrospective epidemic data, available only after the end of the epidemic spread. Risk of an area experiencing an outbreak within seven days showed strong dose-response relationship with the mobile phone-based infectious pressure estimates. The mobile phone-based model performed better (AUC 0.79) than the retrospectively optimized gravity models (AUC 0.66 and 0.74, respectively). Infectious pressure at outbreak onset was significantly correlated with reported cholera cases during the first ten days of the epidemic (p < 0.05). Mobile operator data is a highly promising data source for improving preparedness and response efforts during cholera outbreaks. Findings may be particularly important for containment efforts of emerging infectious diseases, including high-mortality influenza strains.
Figures
Similar articles
-
Improved response to disasters and outbreaks by tracking population movements with mobile phone network data: a post-earthquake geospatial study in Haiti.PLoS Med. 2011 Aug;8(8):e1001083. doi: 10.1371/journal.pmed.1001083. Epub 2011 Aug 30. PLoS Med. 2011. PMID: 21918643 Free PMC article.
-
Cholera epidemic in Haiti, 2010: using a transmission model to explain spatial spread of disease and identify optimal control interventions.Ann Intern Med. 2011 May 3;154(9):593-601. doi: 10.7326/0003-4819-154-9-201105030-00334. Epub 2011 Mar 7. Ann Intern Med. 2011. PMID: 21383314
-
High-resolution spatial analysis of cholera patients reported in Artibonite department, Haiti in 2010-2011.Epidemics. 2016 Mar;14:1-10. doi: 10.1016/j.epidem.2015.08.001. Epub 2015 Sep 3. Epidemics. 2016. PMID: 26972509
-
Review of reported cholera outbreaks worldwide, 1995-2005.Am J Trop Med Hyg. 2006 Nov;75(5):973-7. Am J Trop Med Hyg. 2006. PMID: 17123999 Review.
-
Widespread epidemic cholera caused by a restricted subset of Vibrio cholerae clones.Clin Microbiol Infect. 2014 May;20(5):373-9. doi: 10.1111/1469-0691.12610. Epub 2014 Mar 29. Clin Microbiol Infect. 2014. PMID: 24575898 Review.
Cited by
-
Privacy guarantees for personal mobility data in humanitarian response.Sci Rep. 2024 Nov 19;14(1):28565. doi: 10.1038/s41598-024-79561-2. Sci Rep. 2024. PMID: 39557941 Free PMC article.
-
Integrating machine learning and artificial intelligence in life-course epidemiology: pathways to innovative public health solutions.BMC Med. 2024 Sep 2;22(1):354. doi: 10.1186/s12916-024-03566-x. BMC Med. 2024. PMID: 39218895 Free PMC article. Review.
-
Informing policy via dynamic models: Cholera in Haiti.PLoS Comput Biol. 2024 Apr 29;20(4):e1012032. doi: 10.1371/journal.pcbi.1012032. eCollection 2024 Apr. PLoS Comput Biol. 2024. PMID: 38683863 Free PMC article.
-
The new informatics of pandemic response: humanitarian technology, efficiency, and the subtle retreat of national agency.J Int Humanit Action. 2018;3(1):8. doi: 10.1186/s41018-018-0036-5. Epub 2018 May 30. J Int Humanit Action. 2018. PMID: 38624273 Free PMC article.
-
Unconventional data, unprecedented insights: leveraging non-traditional data during a pandemic.Front Public Health. 2024 Mar 7;12:1350743. doi: 10.3389/fpubh.2024.1350743. eCollection 2024. Front Public Health. 2024. PMID: 38566798 Free PMC article.
References
-
- Murray C. J. et al. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. The Lancet 380, 2197–2223 (2013). - PubMed
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
