Early Warning and Response System for climate-sensitive diseases (EWARS-csd)

Left: Credit: WHO / TDR/DeCicca; right: Credit: WHO/TDR/Laith Hussain

Overview

Climate-sensitive diseases are illnesses whose incidence, intensity or distribution is impacted by climate and weather conditions. These diseases can be directly or indirectly influenced by variations in temperature, precipitation, humidity and extreme weather events. Examples include vector-borne diseases, such as malaria and dengue fever, transmitted by mosquitoes that thrive in warmer and wetter climates, and water-borne diseases such as cholera, which may increase with flooding and inadequate water sanitation. Climate change has the potential to modify the epidemiology of these diseases, leading to increased prevalence or severity in specific regions.

Our work

In 2012, TDR led the design and testing of the Early Warning and Response System for climate-sensitive diseases (EWARS-csd) in collaboration with the University of Gothenburg, the University of Freiburg, IT experts and stakeholders from endemic partner countries in five WHO regions.

Since then, TDR and WHO’s Climate Change and Health Unit have been supporting countries for piloting and implementing EWARS-csd, which aims to provide timely and accurate information to support locally preventive and adaptive actions that can reduce the morbidity and mortality associated with climate-sensitive diseases such as dengue.

The use of EWARS-csd enables the prediction of dengue outbreaks approximately 12 weeks in advance, and Mexico was the first country to integrate it into its national disease surveillance system. Supported by TDR, many countries are currently testing diverse approaches to operationalize EWARS-csd effectively. These include Burkina Faso, Colombia, Dominican Republic, Ethiopia, India, Senegal and Thailand.  EWARS-csd aligns with Pillars 1 and 2 of the strategy of the WHO Global Arbovirus Initiative (GLAI).

Countries such as Ethiopia and Mozambique are using EWARS-csd to predict the occurrence of climate-sensitive diseases such as malaria and meningitis. Further research is required to fully explore the potential of this predicting tool.