Bayesian spatio-temporal modeling and prediction of malaria cases in Tanzania mainland (2016-2023): unveiling associations with climate and intervention factors.

Njotto LL, Senyoni W, Cronie O, Stensgaard AS.

Open source

DOI: 10.1186/s12942-025-00408-8
Published: 2025-08-01
Container: Int J Health Geogr
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1186/s12942-025-00408-8,
  title = {Bayesian spatio-temporal modeling and prediction of malaria cases in Tanzania mainland (2016-2023): unveiling associations with climate and intervention factors.},
  author = {Njotto LL and  Senyoni W and  Cronie O and  Stensgaard AS.},
  year = {2025},
  journal = {Int J Health Geogr},
  doi = {10.1186/s12942-025-00408-8},
  url = {https://doi.org/10.1186/s12942-025-00408-8}
}

RIS

TY  - JOUR
TI  - Bayesian spatio-temporal modeling and prediction of malaria cases in Tanzania mainland (2016-2023): unveiling associations with climate and intervention factors.
AU  - Njotto LL
AU  -  Senyoni W
AU  -  Cronie O
AU  -  Stensgaard AS.
PY  - 2025
JO  - Int J Health Geogr
DO  - 10.1186/s12942-025-00408-8
UR  - https://doi.org/10.1186/s12942-025-00408-8
ER  -

APA

LL, N., W, S., O, C., & AS., S. (2025). Bayesian spatio-temporal modeling and prediction of malaria cases in Tanzania mainland (2016-2023): unveiling associations with climate and intervention factors.. Int J Health Geogr. https://doi.org/10.1186/s12942-025-00408-8

Source records

europe-pmc · retrieved 2026-09-26T10:16:13.094Z
doaj · retrieved 2026-09-26T10:16:13.072Z