Spatio-Temporal Dynamics of Plasmodium falciparum and Plasmodium vivax in French Guiana
2005–2019
Bibliographic Data
| ID | 15464176 |
|---|---|
| Authors | Jenna Scully (Columbia University, corresponding author), Émilie Mosnier (0000-0002-6004-3323, Inserm), Aurel Carbunar (0000-0002-4314-152X, University of French Guiana), Emmanuel Roux (0000-0003-2266-8207, Université de Montpellier), Félix Djossou (0000-0002-6761-0511, University of French Guiana), Nicolas Garçeran (University of French Guiana), L Musset (0000-0003-0215-4110), Alice Sanna (0000-0003-2426-2315, University of French Guiana), Magalie Demar (0000-0003-3414-0821, University of French Guiana), Mathieu Nacher (0000-0001-9397-3204, University of French Guiana), Jean Gaudart (0000-0001-9006-5729, Inserm) |
| Year | 2021 |
| Volume | 18 |
| Issue | 3 |
| Pages | 1077-1077 |
| Publication date | 2021-01-26 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph18031077 |
| PMID | 33530386 |
| OpenAlex | W3122214702 |
| Language | EN |
| Citations received | 1 |
| References cited | 27 |
Aims: This study examines the dynamics of malaria as influenced by meteorological factors in French Guiana from 2005 to 2019. It explores spatial hotspots of malaria transmission and aims to determine the factors associated with variation of hotspots with time. Methods : Data for individual malaria cases came from the surveillance system of the Delocalized Centers for Prevention and Care (CDPS) ( n = 17) from 2005-2019. Meteorological data was acquired from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) database. The Box-Jenkins autoregressive integrated moving average (ARIMA) model tested stationarity of the time series, and the impact of meteorological indices (issued from principal component analysis-PCA) on malaria incidence was determined with a general additive model. Hotspot characterization was performed using spatial scan statistics. Results : The current sample includes 7050 eligible Plasmodium vivax ( n = 4111) and Plasmodium falciparum ( n = 2939) cases from health centers across French Guiana. The first and second PCA-derived meteorological components (maximum/minimum temperature/minimum humidity and maximum humidity, respectively) were significantly negatively correlated with total malaria incidence with a lag of one week and 10 days, respectively. Overall malaria incidence decreased across the time series until 2017 when incidence began to trend upwards. Hotspot characterization revealed a few health centers that exhibited spatial stability across the entire time series: Saint Georges de l'Oyapock and Antecume Pata for P. falciparum , and Saint Georges de l'Oyapock, Antecume Pata, Régina and Camopi for P. vivax. Conclusions : This study highlighted changing malaria incidence in French Guiana and the influences of meteorological factors on transmission. Many health centers showed spatial stability in transmission, albeit not temporal. Knowledge of the areas of high transmission as well as how and why transmission has changed over time can inform strategies to reduce the transmission of malaria in French Guiana. Hotspots should be further investigated to understand other influences on local transmission, which will help to facilitate elimination
Autoregressive integrated moving average · Biology · Cartography · Geography · Incidence (geometry · Malaria · Plasmodium falciparum · Plasmodium vivax · Statistics · Time series · Data-Driven Disease Surveillance · Demography · Malaria Research and Control · Mathematics · Mosquito-borne diseases and control · Immunology
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2025 - 2025 (1) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 1 |