CARIWIG Case Study Report

Dengue Fever in the Belize District

Presenter: Diana RuizContributors: Clare Goodess, Ottis Joslyn and Colin HarphamAffiliations: Caribbean Community Climate Change Centre, Belize

University of East Anglia, UK

Aim and objectives

The primary aim is to examine the impact of changes in climatic variables on dengue fever occurrence in the Belize District• To determine implications for policy

making and suggest key uncertainties to be considered

• To provide sound information for evidence based decision making

Which tools were used? How & why?• Relevant short-term time series 2020’s (2011-

2040) and 2050’s (2041-2070), preferred for planning • Time periods offer the opportunity for

comparison between those years • Model outputs including rainfall and temperature

are critical for the sustainable transmission of DF

The findings

Source: Ministry of Health, 2014

• DF occurrence is highest in Urban Communities

• Uncertainties: Change in reporting structure, human behaviour and practices

• Rainfall is positively correlated with dengue fever in September-October-Nov (r=.547) and December-January- February (r=.555)• Tmin positively correlated with DF in Sept- Oct-Nov

and Dec-Jan-Feb (r=.723 and .527, respectively)• Tmax negatively associated with DF in all seasons• In 2050s, mean wet-day precipitation remains

relatively unchanged in Mar-Apr-May, decrease in June-July-Aug, high variability (more rainfall) in Sept-Oct-Nov and remains relatively unchanged in Dec-Jan-Feb• Min and Max temperature increases in both

scenarios in the 2050s

Mean wet-day precipitation, ECHAM5 and AENWH 2050

Minimum temperature, ECHAM5 and AENWH 2050

Implications for policy & planning• Consider uncertainties which includes:

• Social conditioning factors• Change in DF reporting structure• The impact of preventative measures (individual

and Gov’t) on incidence• Underreporting and population growth• Differences between climate model results

• High variability (more) rainfall and population growth can increase DF which may strain health sector resources• Consider planning and intervention activities

before or during the onset of the rainy season

Implications for policy & planning

• Tmin increase in 2050s indicates DF increase due to warming

• Some indication of increased drought in the summer; will be further explored in the CARiDRO Tool

• Consider the use of climate modelling tools and scientific studies for proactive planning

Feedback on the tools

• Technical guidance to properly interpret data outputs from the WG and to operate the CARiDRO Tool

• Tool provides output from various variables which can be used in other sectors

• Interpreting and analysing the information required considerable time

What more could be done?•Ground work can verify social conditioning factors contributing to DF incidence

•Conduct a comprehensive policy/ programme evaluation to determine the impact of existing prevention and control measures on the number of dengue fever cases

•Assess DF surveillance system to determine how the information is used

•In addition to ECHAM5 and AENWH models, consider the use of multiple climate scenarios

Thank you for your attention!

Questions and comments

Appendix

Population density by community, Belize 2010

Source: Statistical Institute of Belize, 2014

DF Classification 2007-2014

Source: Ministry of Health, 2014

Seasonal Correlation Tables