Home > Research > Publications & Outputs > Spatio-temporal modelling of weekly malaria inc...

Associated organisational unit

Electronic data

  • 204846_1_merged_1525870881

    Accepted author manuscript, 2.72 MB, PDF document

    Available under license: CC BY: Creative Commons Attribution 4.0 International License

Links

Text available via DOI:

View graph of relations

Spatio-temporal modelling of weekly malaria incidence in children under 5 for early epidemic detection in Mozambique

Research output: Contribution to journalJournal articlepeer-review

Published

Standard

Spatio-temporal modelling of weekly malaria incidence in children under 5 for early epidemic detection in Mozambique. / Colborn, Kathryn L.; Giorgi, Emanuele; Monaghan, Andrew J.; Gudo, Eduardo; Candrinho, Baltazar; Marrufo, Tatiana J.; Colborn, James M.

In: Scientific Reports, Vol. 8, 9238, 18.06.2018.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Colborn, KL, Giorgi, E, Monaghan, AJ, Gudo, E, Candrinho, B, Marrufo, TJ & Colborn, JM 2018, 'Spatio-temporal modelling of weekly malaria incidence in children under 5 for early epidemic detection in Mozambique', Scientific Reports, vol. 8, 9238. https://doi.org/10.1038/s41598-018-27537-4

APA

Colborn, K. L., Giorgi, E., Monaghan, A. J., Gudo, E., Candrinho, B., Marrufo, T. J., & Colborn, J. M. (2018). Spatio-temporal modelling of weekly malaria incidence in children under 5 for early epidemic detection in Mozambique. Scientific Reports, 8, [9238]. https://doi.org/10.1038/s41598-018-27537-4

Vancouver

Author

Colborn, Kathryn L. ; Giorgi, Emanuele ; Monaghan, Andrew J. ; Gudo, Eduardo ; Candrinho, Baltazar ; Marrufo, Tatiana J. ; Colborn, James M. / Spatio-temporal modelling of weekly malaria incidence in children under 5 for early epidemic detection in Mozambique. In: Scientific Reports. 2018 ; Vol. 8.

Bibtex

@article{1ff627014c6b4645b3422ba467c2d371,
title = "Spatio-temporal modelling of weekly malaria incidence in children under 5 for early epidemic detection in Mozambique",
abstract = "Malaria is a major cause of morbidity and mortality in Mozambique. We present a malaria early warning system (MEWS) for Mozambique informed by seven years of weekly case reports of malaria in children under 5 years of age from 142 districts. A spatio-temporal model was developed based on explanatory climatic variables to map exceedance probabilities, defined as the predictive probability that the relative risk of malaria incidence in a given district for a particular week will exceed a predefined threshold. Unlike most spatially discrete models, our approach accounts for the geographical extent of each district in the derivation of the spatial covariance structure to allow for changes in administrative boundaries over time. The MEWS can thus be used to predict areas that may experience increases in malaria transmission beyond expected levels, early enough so that prevention and response measures can be implemented prior to the onset of outbreaks. The framework we present is also applicable to other climate-sensitive diseases.",
author = "Colborn, {Kathryn L.} and Emanuele Giorgi and Monaghan, {Andrew J.} and Eduardo Gudo and Baltazar Candrinho and Marrufo, {Tatiana J.} and Colborn, {James M.}",
year = "2018",
month = jun,
day = "18",
doi = "10.1038/s41598-018-27537-4",
language = "English",
volume = "8",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",

}

RIS

TY - JOUR

T1 - Spatio-temporal modelling of weekly malaria incidence in children under 5 for early epidemic detection in Mozambique

AU - Colborn, Kathryn L.

AU - Giorgi, Emanuele

AU - Monaghan, Andrew J.

AU - Gudo, Eduardo

AU - Candrinho, Baltazar

AU - Marrufo, Tatiana J.

AU - Colborn, James M.

PY - 2018/6/18

Y1 - 2018/6/18

N2 - Malaria is a major cause of morbidity and mortality in Mozambique. We present a malaria early warning system (MEWS) for Mozambique informed by seven years of weekly case reports of malaria in children under 5 years of age from 142 districts. A spatio-temporal model was developed based on explanatory climatic variables to map exceedance probabilities, defined as the predictive probability that the relative risk of malaria incidence in a given district for a particular week will exceed a predefined threshold. Unlike most spatially discrete models, our approach accounts for the geographical extent of each district in the derivation of the spatial covariance structure to allow for changes in administrative boundaries over time. The MEWS can thus be used to predict areas that may experience increases in malaria transmission beyond expected levels, early enough so that prevention and response measures can be implemented prior to the onset of outbreaks. The framework we present is also applicable to other climate-sensitive diseases.

AB - Malaria is a major cause of morbidity and mortality in Mozambique. We present a malaria early warning system (MEWS) for Mozambique informed by seven years of weekly case reports of malaria in children under 5 years of age from 142 districts. A spatio-temporal model was developed based on explanatory climatic variables to map exceedance probabilities, defined as the predictive probability that the relative risk of malaria incidence in a given district for a particular week will exceed a predefined threshold. Unlike most spatially discrete models, our approach accounts for the geographical extent of each district in the derivation of the spatial covariance structure to allow for changes in administrative boundaries over time. The MEWS can thus be used to predict areas that may experience increases in malaria transmission beyond expected levels, early enough so that prevention and response measures can be implemented prior to the onset of outbreaks. The framework we present is also applicable to other climate-sensitive diseases.

U2 - 10.1038/s41598-018-27537-4

DO - 10.1038/s41598-018-27537-4

M3 - Journal article

VL - 8

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

M1 - 9238

ER -