Spatial Markov matrices for measuring the spatial dependencies of an epidemiological spread
Case Covid’19 Madagascar
Bibliographic Data
| ID | 15358122 |
|---|---|
| Authors | Stefana Tabera Tsilefa (Université de Fianarantsoa, corresponding author), Angelo Raherinirina (0000-0002-3426-5520, Université de Fianarantsoa) |
| Year | 2024 |
| Volume | 24 |
| Issue | 1 |
| Pages | 2243-2243 |
| Publication date | 2024-08-19 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | BMC Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1471-2458 • E-ISSN: 1471-2458 |
| Publisher | BioMed Central (PUBLISHER • GB) |
| DOI | 10.1186/s12889-024-19654-9 |
| PMID | 39160542 |
| OpenAlex | W4401694626 |
| Language | EN |
| Citations received | 1 |
| References cited | 18 |
After analysis, we can say that there is spatial dependency according to these spatial transition matrices
2019-20 coronavirus outbreak · Biostatistics · Coronavirus disease 2019 (COVID-19 · Disease · Environmental health · Infectious disease (medical specialty · Markov chain · Pandemic · Pathology · Public health · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 · Spatial epidemiology · Statistics · COVID-19 epidemiological studies · Data-Driven Disease Surveillance · Mathematics · Medicine · Spatial and Panel Data Analysis · Epidemiology · Virology
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| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |