Bayesian spatio-temporal distributed lag modeling for delayed climatic effects on sparse malaria incidence data
<strong>Background<br></strong> In many areas of the Greater Mekong Subregion (GMS), malaria endemic regions have shrunk to patches of predominantly low-transmission. With a regional goal of elimination by 2030, it is important to use appropriate methods to analyze and predict tren...
| Huvudupphovsmän: | , , , |
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| Materialtyp: | Journal article |
| Språk: | English |
| Publicerad: |
BioMed Central
2021
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