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Open Access Highly Accessed Research

Environmental determinant of malaria cases among travellers

Gaëtan Texier12, Vanessa Machault34, Meili Barragti35, Jean-Paul Boutin1 and Christophe Rogier36*

Author Affiliations

1 Public Health and Epidemiology Centre of the French Army (CESPA) & SESSTIM UMR912, Allée du Médecin Colonel Jamot, Parc du Pharo, BP60109, 13262 Marseille cedex 07, France

2 Centre Pasteur du Cameroun BP 1274, Yaoundé, Cameroun, France

3 Institute for Biomedical Research of the French Army (IRBA) & URMITE UMR6236, Allée du Médecin Colonel Jamot, Parc du Pharo, BP60109, Marseille cedex 07, 13262, France

4 Observatoire Midi-Pyrénées - Laboratoire d’Aérologie, Centre National de la Recherche Scientifique - Université Paul Sabatier, 14 avenue Edouard, Belin, Toulouse, 31400, France

5 SUPAGRO, INRA, UMR729 MISTEA, Montpellier, F-34060, France

6 Institut Pasteur de Madagascar, B.P. 1274, 101, Antananarivo, Madagascar

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Malaria Journal 2013, 12:87  doi:10.1186/1475-2875-12-87

Published: 4 March 2013

Abstract

Background

Approximately 125 million travellers visit malaria-endemic countries annually and about 10,000 cases of malaria are reported after returning home. Due to the fact that malaria is insect vector transmitted, the environment is a key determinant of the spread of infection. Geo-climatic factors (such as temperature, moisture, water quality) determine the presence of Anopheles breeding sites, vector densities, adult mosquito survival rate, longevity and vector capacity. Several studies have shown the association between environmental factors and malaria incidence in autochthonous population. The association between the incidence of clinical malaria cases among non-immune travellers and environmental factors is yet to be evaluated. The objective of the present study was to identify, at a country scale (Ivory Coast), the environmental factors that are associated with clinical malaria among non-immune travellers, opening the way for a remote sensing-based counselling for malaria risk prevention among travellers.

Methods

The study sample consisted in 87 cohorts, including 4,531 French soldiers who travelled to Ivory Coast, during approximately four months, between September 2002 and December 2006. Their daily locations were recorded during the entire trip. The association between the incidence of clinical malaria and other factors (including individual, collective and environmental factors evaluated by remote sensing methods) was analysed in a random effect mixed Poisson regression model to take into account the sampling design.

Results

One hundred and forty clinical malaria cases were recorded during 572,363 person-days of survey, corresponding to an incidence density of 7.4 clinical malaria episodes per 1,000 person-months under survey. The risk of clinical malaria was significantly associated with the cumulative time spent in areas with NDVI > 0.35 (RR = 2,42), a mean temperature higher than 27°C (RR = 2,4), a longer period of dryness during the preceding month (RR = 0,275) and the cumulative time spent in urban areas (RR = 0,52).

Conclusions

The present results suggest that remotely-sensed environmental data could be used as good predictors of the risk of clinical malaria among vulnerable individuals travelling through African endemic areas.

Keywords:
Malaria; Environment; Remote sensing technology; Forecasting; Travel