
Full text loading...
Disclaimer: The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Financial support: This study was solicited by the Caribbean Institute for Meteorology and Hydrology (CIMH) through the United States Agency for International Development’s (USAID, Grant ID: AID-538-10-14-00001) Programme for Building Regional Climate Capacity in the Caribbean (BRCCC Programme: rcc.cimh.edu.bb/brccc) with funding made possible by the generous support of the American people. R. L. was funded by a Royal Society Dorothy Hodgkin Fellowship.
Authors’ addresses: Catherine A. Lippi and Sadie J. Ryan, Department of Geography, University of Florida, Gainesville, FL, E-mails: [email protected] and [email protected]. Anna M. Stewart-Ibarra, Department of Montevideo, InterAmerican Institute for Global Change Research (IAI), Montevideo, Uruguay, E-mail: [email protected]. Moory Romero, Department of Environmental Studies, State University of New York College of Environmental Science and Forestry (SUNY ESF), Syracuse, NY, E-mail: [email protected]. Rachel Lowe, Department of Infectious Disease Epidemiology, Centre on Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, London, United Kingdom, E-mail: [email protected]. Roché Mahon, Cedric J. Van Meerbeeck, and Adrian R. Trotman, The Caribbean Institute for Meteorology and Hydrology, St. James, Barbados, E-mails: [email protected], [email protected], and [email protected]. Leslie Rollock, Dale Holligan, and Shane Kirton, Ministry of Health and Wellness, St. Michael, Barbados, E-mails: [email protected], [email protected], and [email protected]. Marquita Gittens-St. Hilaire, Faculty of Medical Sciences, University of the West Indies at Cave Hill, Bridgetown, Barbados, E-mail: [email protected]. Mercy J. Borbor-Cordova, Facultad de Ingeniería Marítima y Ciencias del Mar, Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil, Ecuador, E-mail: [email protected].
Abstract.
Dengue fever and other febrile mosquito-borne diseases place considerable health and economic burdens on small island nations in the Caribbean. Here, we used two methods of cluster detection to find potential hotspots of transmission of dengue and chikungunya in Barbados, and to assess the impact of input surveillance data and methodology on observed patterns of risk. Using Moran’s I and spatial scan statistics, we analyzed the geospatial and temporal distribution of disease cases and rates across Barbados for dengue fever in 2013–2016, and a chikungunya outbreak in 2014. During years with high numbers of dengue cases, hotspots for cases were found with Moran’s I in the south and central regions in 2013 and 2016, respectively. Using smoothed disease rates, clustering was detected in all years for dengue. Hotspots suggesting higher rates were not detected via spatial scan statistics, but coldspots suggesting lower than expected rates of disease activity were found in southwestern Barbados during high case years of dengue. No significant spatiotemporal structure was found in cases during the chikungunya outbreak. Spatial analysis of surveillance data is useful in identifying outbreak hotspots, potentially complementing existing early warning systems. We caution that these methods should be used in a manner appropriate to available data and reflecting explicit public health goals—managing for overall case numbers or targeting anomalous rates for further investigation.