Informing Rift Valley Fever preparedness by mapping seasonally varying environmental suitability.


Journal

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
ISSN: 1878-3511
Titre abrégé: Int J Infect Dis
Pays: Canada
ID NLM: 9610933

Informations de publication

Date de publication:
Oct 2020
Historique:
received: 13 04 2020
revised: 09 07 2020
accepted: 24 07 2020
pubmed: 2 8 2020
medline: 15 12 2020
entrez: 2 8 2020
Statut: ppublish

Résumé

Rift Valley Fever (RVF) poses a threat to human and animal health throughout much of Africa and the Middle East and has been recognized as a global health security priority and a key preparedness target. We combined RVF occurrence data from a systematic literature review with animal notification data from an online database. Using boosted regression trees, we made monthly environmental suitability predictions from January 1995 to December 2016 at a 5 × 5-km resolution throughout regions of Africa, Europe, and the Middle East. We calculated the average number of months per year suitable for transmission, the mean suitability for each calendar month, and the "spillover potential," a measure incorporating suitability with human and livestock populations. Several countries where cases have not yet been reported are suitable for RVF. Areas across the region of interest are suitable for transmission at different times of the year, and some areas are suitable for multiple seasons each year. Spillover potential results show areas within countries where high populations of humans and livestock are at risk for much of the year. The widespread environmental suitability of RVF highlights the need for increased preparedness, even in countries that have not previously experienced cases. These maps can aid in prioritizing long-term RVF preparedness activities and determining optimal times for recurring preparedness activities. Given an outbreak, our results can highlight areas often at risk for subsequent transmission that month, enabling decision-makers to target responses effectively.

Sections du résumé

BACKGROUND BACKGROUND
Rift Valley Fever (RVF) poses a threat to human and animal health throughout much of Africa and the Middle East and has been recognized as a global health security priority and a key preparedness target.
METHODS METHODS
We combined RVF occurrence data from a systematic literature review with animal notification data from an online database. Using boosted regression trees, we made monthly environmental suitability predictions from January 1995 to December 2016 at a 5 × 5-km resolution throughout regions of Africa, Europe, and the Middle East. We calculated the average number of months per year suitable for transmission, the mean suitability for each calendar month, and the "spillover potential," a measure incorporating suitability with human and livestock populations.
RESULTS RESULTS
Several countries where cases have not yet been reported are suitable for RVF. Areas across the region of interest are suitable for transmission at different times of the year, and some areas are suitable for multiple seasons each year. Spillover potential results show areas within countries where high populations of humans and livestock are at risk for much of the year.
CONCLUSIONS CONCLUSIONS
The widespread environmental suitability of RVF highlights the need for increased preparedness, even in countries that have not previously experienced cases. These maps can aid in prioritizing long-term RVF preparedness activities and determining optimal times for recurring preparedness activities. Given an outbreak, our results can highlight areas often at risk for subsequent transmission that month, enabling decision-makers to target responses effectively.

Identifiants

pubmed: 32738486
pii: S1201-9712(20)30587-7
doi: 10.1016/j.ijid.2020.07.043
pmc: PMC7562817
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

362-372

Informations de copyright

Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.

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Auteurs

Austin N Hardcastle (AN)

Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.

Joshua C P Osborne (JCP)

Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.

Rebecca E Ramshaw (RE)

Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.

Erin N Hulland (EN)

Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.

Julia D Morgan (JD)

Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.

Molly K Miller-Petrie (MK)

Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.

Julia Hon (J)

Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.

Lucas Earl (L)

Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.

Peter Rabinowitz (P)

Department of Global Health, University of Washington, Seattle, WA, USA.

Judith N Wasserheit (JN)

Department of Global Health, University of Washington, Seattle, WA, USA.

Marius Gilbert (M)

Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium; Fonds National de la Recherche Scientifique (FNRS), Brussels, Belgium.

Timothy P Robinson (TP)

Animal Production and Health Division (AGA), Food and Agriculture Organization of the United Nations, Italy.

G R William Wint (GRW)

Environmental Research Group Oxford (ERGO), c/o Department of Zoology, Oxford, UK.

Shreya Shirude (S)

Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.

Simon I Hay (SI)

Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.

David M Pigott (DM)

Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA. Electronic address: pigottdm@uw.edu.

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Classifications MeSH