[en] Background: Malaria in Loreto department remains a public health problem, accounting for more than 90% of reported cases in Peru. This is the first study in the Peruvian Amazon aimed at assessing the risk of malaria transmission using satellite imagery and Boosted Regression
Trees (BRT).
Methods: Villages with at least one malaria case between 2010 and 2015 from the routine surveillance data in Loreto were georeferenced and their cases aggregated by year and species. Social and environmental variables were derived from Landsat satellite imagery and other spatial data, then included as explanatory variables into a crossvalidated Poisson BRT model for malaria incidence at the local level.
Time-dependent explanatory variables included forest coverage (FC, %), annual forest loss (FL,%), cumulative annual rainfall (CAR, mm), annual-mean land surface temperature (LST, oC), normalised difference vegetation index (NDVI), and normalised difference water index (NDWI).
Other variables were Euclidean shortest distance to rivers (SDR, meters), time to major populated villages/towns (TPV, minutes), and night-time lights (NTL, mean value 2010-2013) as proxy of population density. BRT accounts for nonlinearities and interactions between factors with high
predictive accuracy for disease risk mapping.
Results: A total of 1524 villages were included in the analysis (70% of total Loreto’s villages). More than 90% of relative influence in the overall malaria incidence was explained by five variables: NTL (67.8%), TPV (8.1%), FC (6.5%), CAR (5%) and SDR (4.6%). The analysis
by species showed a higher influence of environmental variables (CAR, LST, NDVI and NDWI) for P. falciparum (18.4%) than for P. vivax incidence (9.7%). Malaria risk maps were generated based on model predictions taking into account the relative influence of variables.
Conclusions: Remotely sensed data analysed using BRT allowed for maps delimiting areas of high malaria risk in Loreto. These maps will help malaria stakeholders to prioritise areas for control interventions.
Disciplines :
Immunology & infectious disease
Author, co-author :
Solano-Villarreal, Elisa
Valdivia, Walter
Linard, Catherine ; Université de Liège - ULiège > Dpt. de gestion vétérinaire des Ressources Animales (DRA) > Dpt. de gestion vétérinaire des Ressources Animales (DRA)
Pasapera-Gonzales, Jose
Lejeune, Philippe ; Université de Liège - ULiège > Ingénierie des biosystèmes (Biose) > Gestion des ressources forestières et des milieux naturels
Llanos-Cuentas, Alejandro
Speybroeck, Niko
HAYETTE, Marie-Pierre ; Centre Hospitalier Universitaire de Liège - CHU > Unilab > Laboratoire parasitologie
Rosas-Aguirre, Angel
Language :
English
Title :
Malaria risk assessment at local level using satellite imagery and BRT in the Peruvian Amazon
Alternative titles :
[fr] Evaluation du risque malarique au plan local en utilisant l'imagerie satellite et le BRT dans la région de l'Amazone péruvienne
scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.
This website uses cookies to improve user experience. Read more
Save & Close
Accept all
Decline all
Show detailsHide details
Cookie declaration
About cookies
Strictly necessary
Performance
Strictly necessary cookies allow core website functionality such as user login and account management. The website cannot be used properly without strictly necessary cookies.
This cookie is used by Cookie-Script.com service to remember visitor cookie consent preferences. It is necessary for Cookie-Script.com cookie banner to work properly.
Performance cookies are used to see how visitors use the website, eg. analytics cookies. Those cookies cannot be used to directly identify a certain visitor.
Used to store the attribution information, the referrer initially used to visit the website
Cookies are small text files that are placed on your computer by websites that you visit. Websites use cookies to help users navigate efficiently and perform certain functions. Cookies that are required for the website to operate properly are allowed to be set without your permission. All other cookies need to be approved before they can be set in the browser.
You can change your consent to cookie usage at any time on our Privacy Policy page.