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Data for Data-driven models to predict the elimination of sleeping sickness in former Equateur province of DRC
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Rock, Kat S., Pandey, A., Ndeffo-Mbah, M. L., Atkins, K. E., Lumbala, C., Galvani, A. and Keeling, Matthew James (2017) Data for Data-driven models to predict the elimination of sleeping sickness in former Equateur province of DRC. [Dataset]
Archive (ZIP) (Matlab file, license)
Archive_86503.zip - Unspecified Version Available under License Special licence conditions apply, please see licence document for more details. Download (21Kb) |
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Microsoft Word (Software License - academic and non-commercial use)
Software Licensing Agreement non commercial2.docx - Unspecified Version Download (17Kb) |
Official URL: http://wrap.warwick.ac.uk/86503
Abstract
Approaching disease elimination, it is crucial to be able to assess progress towards key objectives using quantitative tools. For Gambian human African trypanosomiasis (HAT), the ultimate goal is to stop transmission by 2030, while intermediary targets include elimination as a public health problem − defined as <1 new case per 10,000 inhabitants in 90% of foci, and <2000 reported cases by 2020. Using two independent mathematical models, this study assessed the achievability of these goals in the former Equateur province of the Democratic Republic of Congo, which historically had endemic levels of disease.
The two deterministic models used different assumptions on disease progression, risk of infection and non-participation in screening, reflecting biological uncertainty. To validate the models a censor-fit-uncensor procedure was used to fit to health-zone level data from 2000 to 2012; initially the last six years were censored, then three and the final step utilised all data. The different model projections were used to evaluate the expected transmission and reporting for each health zone within each province under six intervention strategies using currently available tools.
In 2012 there were 197 reported HAT cases in former Equateur reduced from 6828 in 2000, however this reflects lower active testing for HAT (1.3% of the population compared to 7.2%). Modelling results indicate that there are likely to be <300 reported cases in former Equateur in 2020 if screening continues at the mean level for 2000–2012 (6.2%), and <120 cases if vector control is introduced. Some health zones may fail to achieve <1 new case per 10,000 by 2020 without vector control, although most appear on track for this target using medical interventions alone. The full elimination goal will be harder to reach; between 39 and 54% of health zones analysed may have to improve their current medical-only strategy to stop transmission completely by 2030.
Item Type: | Dataset | ||||||
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Subjects: | R Medicine > RC Internal medicine | ||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) | ||||||
Type of Data: | Matlab software code | ||||||
Library of Congress Subject Headings (LCSH): | African trypanosomiasis -- Transmission -- Mathematical models -- Congo (Democratic Republic), Tropical medicine | ||||||
Publisher: | University of Warwick, School of Life Sciences | ||||||
Official Date: | 10 March 2017 | ||||||
Dates: |
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Status: | Not Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Media of Output (format): | .txt .docx | ||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||
Copyright Holders: | University of Warwick | ||||||
Description: | This is the Warwick Model (Model W) used to fit and predict infection in former Equateur province of DRC. It was developed by Kat Rock and Matt Keeling at Warwick University under the NTD Modelling Consortium. There are (assumed to be) several unknown parameters: • R0, This code outputs years, active and passive numbers of cases detected and the "Actual" underlying number of new infections |
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