Explore daily and monthly temperature, precipitation, and humidity data for your DHIS2 organization units, and import weather and climate data into DHIS2 data elements to facilitate analysis of climate-sensitive health outcomes
The DHIS2 Climate Data App is a pilot application that is intended to help public health programs identify causal relationships between climate factors and health outcomes — which can then be used to design early warning systems for a variety of health use cases — by providing a means to easily import and explore historical and current weather data in DHIS2. This app has been developed as part of our ongoing project: DHIS2 for Climate & Health. You can watch a webinar about this app on the DHIS2 YouTube channel.
The app allows DHIS2 users to explore daily and monthly temperature, precipitation, and humidity data for your organization units, and to import weather and climate data into DHIS2 data elements, which can then be analyzed and visualized in combination with health data, directly in DHIS2. The app is now available on the DHIS2 App Hub.
The data source used in this app is ERA5-Land, which is considered to be the most accurate and complete climate dataset available with worldwide coveragae. This video shows you how this dataset was created by combining local weather observations with a weather model to fill the missing gaps (climate reanalysis). The data is calculated for DHIS2 organisation units by the Google Earth Engine. DHIS2 instances must have the Google Earth Engine enabled in order to use the Climate Data App.
Temperature, precipitation, and humidity data can be explored for your organization units directly in the app. When you select an organisation unit the following charts will be available:
The period can be adjusted for all the chart types.
Temperature, precipitation, and humidity data can easily be imported into DHIS2 data elements through this app. This will allow you to combine weather and climate data with your health data across all DHIS2 analytics apps. The app includes a setup guide for how to configure the data elements.
Importing daily temperature, precipitation, and humidity values allows you to aggregate data into other period types (e.g. weekly or monthly) in DHIS2. In this way, it is possible to easily match the periodicity of the existing health data in a DHIS2 system.
In many health programs – such as infectious disease surveillance, maternal and child health, and nutrition and food security – health outcomes can be directly and indirectly influenced by local climate variation, extreme weather events, and changes in human behavior linked to weather factors and climate change. Understanding the relationship between climate data and health outcomes is essential for developing effective public health interventions and adaptation strategies.
For instance, malaria research often emphasizes the relationship between temperature and the spread of the disease. Climate data, such as temperature, rainfall and humidity, and vector presence or density could be useful to predict outbreaks and minimize their health effects. Such data integration could help infectious disease programs understand where vector populations may be changing, which geographies and populations may be at the highest risk for increased transmission, the length of seasonal periods of high transmission, and which catchment areas may need to prepare for future health demands.
Warmer temperatures, altered precipitation patterns, and extreme weather events, such as droughts, floods, and storms, pose immediate threats to food production and supply chains. These events can damage or alter the geographical distribution and cultivation conditions of crops, disrupt transportation networks, compromise access to food, and ultimately influence dietary patterns and nutritional outcomes, particularly in vulnerable communities. Combining climate data with routine health data on human malnutrition can show the impact of agricultural adaptation measures on human health, and assist in planning nutrition interventions of extreme weather events.
Extreme weather events, intensified by climate change, pose immediate risks to human health through injuries, displacement, and mental health issues, and changes in temperature, humidity, air quality, and the frequency of extreme weather events all have implications for respiratory health such as asthma and chronic obstructive pulmonary disease (COPD). Moreover, climate change exacerbates existing health disparities, disproportionately affecting vulnerable populations such as the elderly, children, and low-income communities. These groups often have limited access to healthcare and resources to adapt to changing environmental conditions. Incorporating climate data into health surveillance systems can help identify vulnerable populations and anticipate changes in disease burden associated with climate variability and change.
Recognizing the interconnected nature of climate change and health, it is crucial to adopt an effective approach to address these challenges. Climate & Health data integration provides a holistic view of how climate factors contribute to health risks, enabling a deeper understanding of the relationship between environmental conditions associated with climate and disease occurrences.
This app is developed by the University of Oslo and has gone through initial testing with the HISP network. The app is not currently a DHIS2 core app, but useful parts of this app may be incorporated into the DHIS2 core in the future based on your feedback. You can ask questions and share your comments on the app on the DHIS2 Community of Practice, or by sending us an email at: climate-app@dhis2.org
The app will continue to develop as the DHIS2 for Climate & Health project progresses, so if you decide to install it, we encourage you to regularly check for updates and ensure you are using the latest version from the DHIS2 App Hub.
