mbkoltai/covid_lmic_model: Model fitting excess mortality data in Mogadishu v1.0
Koltai, M
(2021).
mbkoltai/covid_lmic_model: Model fitting excess mortality data in Mogadishu v1.0.
[Dataset].
Zenodo.
https://doi.org/10.5281/zenodo.5534762
First release of source code for "Date of introduction and epidemiologic patterns of SARS-CoV-2 in Mogadishu, Somalia: estimates from transmission modelling of satellite-based excess mortality data in 2020".
Alternative Title
Fitting satellite-based excess mortality data from Mogadishu (Somalia) Feb-Sept/2020
Keywords
COVID-19; SARS-CoV-2; Coronavirus| Item Type | Dataset |
|---|---|
| Resource Type |
Resource Type Resource Description Software R script |
| Capture method | Aggregation |
| Date | 28 September 2021 |
| Language(s) of written materials | English |
| Creator(s) |
Koltai, M |
| LSHTM Faculty/Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology (-2023) |
| Research Centre | Centre for the Mathematical Modelling of Infectious Diseases |
| Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom |
| Date Deposited | 22 Jun 2021 10:42 |
| Last Modified | 30 Sep 2021 15:09 |
| Publisher | Zenodo |
Explore Further
- Github (Data)
- Preprint: Model fitting of early 2020 increase in burials in Mogadishu (Somalia) suggests possible early introduction of SARS-CoV-2 (Paper)
- Zenodo (Online Data Resource)
No files available. Please consult associated links.
- Github (Data)
- Preprint: Model fitting of early 2020 increase in burials in Mogadishu (Somalia) suggests possible early introduction of SARS-CoV-2 (Paper)
- Zenodo (Online Data Resource)
ORCID: https://orcid.org/0000-0002-7341-5114