https://github.com/rbroc/cholera_sd_pilot

https://github.com/rbroc/cholera_sd_pilot

Last synced: 11 days ago
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• Host: GitHub
• URL: https://github.com/rbroc/cholera_sd_pilot
• Owner: rbroc
• Created: 2021-08-02T10:19:29.000Z (over 3 years ago)
• Default Branch: master
• Last Pushed: 2021-08-02T12:11:34.000Z (over 3 years ago)
• Last Synced: 2024-10-24T11:52:08.737Z (about 2 months ago)
• Language: Jupyter Notebook
• Size: 17.4 MB
• Stars: 1
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## Cholera Response Simulator resources

This repository contains some materials relevant for the Cholera Response Simulator pilot recommended as a result of research conducted during the 2021 Predictive Analytics Data Fellowship.

Recommendations are outlined in the **Pilot Recommendation** files. There is also some code and data from preliminary data exploration and analysis conducted during the fellowship. Very much work in progress, but hope this could be useful as a starting point.

Contents:

- ```Pilot Recommendations.ipynb```: 📖 report on recommendations for a Cholera Response Simulator pilot using System Dynamics;

- ```datasets```: :1234: a few useful datasets, on which some viz + exploratory analysis work has been done over the course of the fellowship. This includes:

    - ```acaps_2021.xlsx```: ACAPS Crisis InSight dataset including both data on cholera incidence and a number of other indicators of the humanitarian situation in the country. Only includes 2019-2021;

    - ```IATI_data.csv```: a datasets with IATI data on activities in Yemen for 2017-2018;

    - ```cholera_cases_1718.xslx```: monthly data on cholera cases;

    - ```rainfall.csv```: World Bank data on rainfall volume for Yemen (country-wide);

    - ```temperature.csv```: World Bank data on temperature for Yemen (country-wide);

    - ```yem-administrative-divisions-shapefiles```: geo data, used for plotting

- ```explore_acaps_ds.ipynb```: :chart_with_upwards_trend: Some preliminary exploration of the ACAPS dataset, including both viz on number of cases in Yemen between 2017 and 2020 and some analysis to get a sense of the predictive accuracy of different types of non-dynamic multivariate models in predicting cholera cases and deaths. Code is not tidy at all, but this was just a "proof of concept" to concretely see how poorly non-dynamic models perform, given the data that are currently available;

- ```viz_cases+env.ipynb```: :chart_with_upwards_trend: Some plotting of cases against rainfall and temperature data, showing clear decoupling between environmental variables and cases after 2017. Take-home message: interventions matter, and transition to endemic transmission modalities also matter: we need to add these components to CRM and ESA-like models;

- ```viz_IATI.ipynb```: 💰 data on funding for WASH activities or activities mentioning cholera in Yemen for 2017-2018

**NOTE**: when the report is finalized, reference to the report should be added in the recommendations file.