DHIS2 Climate & Health work in Rwanda leverages existing DHIS2 infrastructure and capacity, while testing innovative DHIS2 tools for climate data integration and predictive modeling.
Health information systems & capacity
DHIS2 has been used as Rwanda’s national health management information system (HMIS) since 2012, containing routine data on all key public health programs. It now serves as the backbone of Rwanda’s national Health Intelligence Center. Rwanda has often served as a country of “firsts” for DHIS2 and digital health innovation in Africa: achieving a national scale electronic immunization registry, implementing advanced use cases for DHIS2 Tracker programs such as hypertension and cancer screening, establishing cross-sectoral data sharing with DHIS2, and scaling up facility electronic medical records (EMRs).
The MoH has a core DHIS2 team supporting the HMIS as well as a number of complex DHIS2 individual-level systems at national scale. The MOH, alongside the Rwanda Biomedical Center (RBC), have demonstrated a strong capacity for using DHIS2 as an active disease surveillance, outbreak response and health emergency management system, including in response to recent outbreaks of Marburg and Ebola. HISP Rwanda provides DHIS2 technical assistance to the MoH, RBC, and other local partners.
Climate data integration
The DHIS2 Climate App has been installed in Rwanda’s national HMIS system, enabling import and integration of climate data from the globally available ERA-5 Land and CHIRPS data sets. In addition, local climate and weather data from Rwanda’s ENACTS MapRoom has been integrated using the ENACTS Integrator, and HISP Rwanda worked with local stakeholders to digitize and integrate malaria intervention data from a number of sources using DHIS2 Climate Tools. This data has been used to create a prototype climate-malaria dashboard in DHIS2.
Predictive modeling
The Chap Modeling Platform and DHIS2 Modeling App have been installed on a DHIS2 testing instance in Rwanda. A predictive analytics workflow has been defined, testing has been completed on several globally available models, and local development and evaluation of predictive models is ongoing.
There is strong capacity for modeling and advanced statistical analysis through MoH, RBC and partnerships with local universities. The MoH Director of Planning comes from a modeling background and has been actively engaged in contributing this expertise to testing models in DHIS2 and Chap for early warning systems of climate-sensitive diseases. The HISP Rwanda team has also onboarded a local modeler who works closely with the malaria program and the HMIS units on these solutions.