ColdTrace: Real-Time Data
for Immunization and Beyond
ColdTrace: Real-Time Data
The growth of our programs in 2015 laid the groundwork for the milestones in our 2016 Annual Report.
This assessment follows up on the randomized control trial conducted in 2014-2015 with Village Reach, PATH, and the Ministry of Health in Mozambique which aimed to evaluate the impact of remote temperature monitoring (RTM) on vaccine cold chain equipment performance at the health facility level. That study showed that RTM with SMS alerts increased fridge uptime and reduced freezing, as compared to 30 day temperature loggers and paper charts. (See Appendix I of the report for more details.) However, even some fridges in the RTM experimental group had chronic problems and failed to achieve 95% uptime.
We launched this follow-up investigation to answer the question: Can maintenance + RTM lead to 95% uptime?
A cold chain expert traveled to Mozambique from September 24 until October 14, 2015. He used ColdTrace data to identify 27 fridges that were failing and worked with the Ministry of Health maintenance technician to visit or remotely diagnose and fix as many fridges as possible. The expert remained active in fridge fixes, phone calls and follow-ups through the end of November 2015.
Perhaps the most interesting finding was that distinct patterns in the RTM data (which we call “temperature data signatures”) can be used to remotely diagnose problems and enable remote fixes via phone calls to nurses in clinics. For the improperly adjusted fridges in this investigation, thermostat adjustments increased uptime by 30%. Today, the MOH technician continues to use the dashboard data to diagnose problems, call clinics to address the issues, and verify fixes by monitoring subsequent temperature data. We also learned that, without access to key spare parts/tools, even an expert technician cannot get all fridges to 95%: flat batteries on solar fridges were one such problem that the expert did not have the resources to fix. With RTM data, however, those responsible for cold chain maintenance can identify which fridges need help and determine where to focus resources.
The randomized control trial conducted by Nexleaf with the Mozambique Ministry of Health, VillageReach, PATH, and UNICEF evaluated the “uptimes” of vaccine refrigerators in rural communities. Health facilities using Nexleaf’s remote temperature monitoring (RTM) were evaluated in a controlled trial against facilities using 30 day temperature recorders (30DTR) and facilities using paper charts.
The study was conducted to learn: Do refrigerators with RTM devices capable of sending SMS alerts maintain higher uptimes than refrigerators monitored with 30DTRs or paper charts?
Health facilities were randomly selected and placed into three groups:
- Group 1 consisted of 29 health facilities with RTM + SMS alerts; staff received training on responding to RTM alerts, and Standard Operating Procedures (SOPs) were posted in clinics.
- Group 2 consisted of 28 health facilities monitoring fridges with 30DTR devices; staff received additional training on 30DTR usage.
- Group 3 consisted of 26 health facilities monitoring fridges with stem thermometers; staff recorded temperatures twice daily on paper charts.
Following a ten-month evaluation period, we found that vaccine refrigerators equipped with RTM capable of sending SMS alerts, monitored by trained health care professionals, achieved the highest amount of uptime (90%) and lowest percent of total time spent in WHO freeze alarm state (0.55%). However, Group 2, refrigerators monitored by 30DTR, experienced an average of three hours less in WHO heat alarm state than those with RTM.
Nexleaf and the World Bank collaborated on a project to monitor and evaluate cookstove use and subsequent PM2.5 reductions, to support sensor-enabled climate financing. With support from Berkeley Air Monitoring Group and The Energy and Resources Institute, and in consultation with Scripps Institution of Oceanography, Nexleaf completed the first phase of a three phase project.
StoveTrace sensors were deployed in 79 households in four states in India, yielding unprecedented insight into user preference and behavior and spurring tremendous technological development of the platform. The investigation revealed that the health benefits of cleaner air are less immediate and tangible, and do not hold much sway over women’s preference. In 10 additional households, prototypes of integrated PM2.5 devices were deployed, but further technological development and field testing are required to draw conclusions based on air quality data.
This work aims to scale an integrated sensor and increase the capacity of the open data platform accordingly.