TechNet Webinar: Varo and Pogo in the Field: How Supply Chain and Service Delivery Teams Are Using Cold Chain Data

Dear colleagues,

Due to a scheduling conflict, the webinar: Varo and Pogo in the Field: How Supply Chain and Service Delivery Teams Are Using Cold Chain Data, has been postponed to June 4, 2026, 14:00 CEST (Geneva time).

We look forward to seeing you then.

Please register here: https://who.zoom.us/webinar/register/WN_W5o-OfpjSSWsnlMaFW293A#/registration

In this webinar, you will first hear from Bentley Cook from the Varo Foundation to provide an overview of how to use the Varo and Pogo-LT apps for temperature data collection from FridgeTag. You will then here from the Nigeria team, Tahir Buhari, Senior Research Lead for the EHA Group, and Perewari Preye Otis, the State Cold Chain Officer for the Bayelsa State Primary Health Care Board in Nigeria, providing a practical application of use of the apps for temperature data collection and links to maintenance decisions. Next Sami Tewfik, a public health supply chain professional with JSI, will present the use of Varo and Pogo-LT to bridge the gap between supply chain and service delivery for improved cold chain management in Ethiopia.

I hope you are able to join.

June 4, 2026, 14h CEST (Geneva time)

Please register here: https://who.zoom.us/webinar/register/WN_W5o-OfpjSSWsnlMaFW293A#/registration

Thank you to everyone who joined the recent TechNet webinar, Varo and Pogo in the Field: How Supply Chain and Service Delivery Teams Are Using Cold Chain Data.

In the webinar we heard from four presenters sharing their experiences with Varo and Pogo-LT to collect and analyze temperature monitoring data from 30DTRs.

• Bentley Cook of the Varo Foundation provided an overview of how to use the Varo and Pogo-LT apps for temperature data collection from 30DTRs.
• Mohammed Sani Lawal with EHA Group in Nigeria and Perewari Preye Otis with the Bayelsa State Primary Health Care Board provided a practical application of use of the apps and links to maintenance decisions.
• Sami Tewfik with JSI/Ethiopia presented the use of Varo and Pogo-LT to bridge the gap between supply chain and service delivery for improved cold chain management.

You can watch the video of the webinar, and the slides are attached.

We have summarized the Q&A below, and would love to continue the information sharing and experience exchange on this platform.

Questions 

Question 1 (aggregated): "What I'd love to know if the raw and transformed data ETL. How does it flow, where does it sit, how persistent, data use, etc." / "How are you addressing the integration gap between regional Pogo LT tools and national ELMIS systems to enable consolidated oversight?" / data interoperability between Varo, DHIS2, OpenLMIS, mSupply, and other national decision-making systems.

Response 1: These questions about data compatibility and interoperability are highly relevant— and they apply broadly to cold chain data, whether the data comes from Varo, an RTMD, or the next-generation ("EMS") CCE just starting to appear in countries. To answer these questions, I want to start closer to the beginning.

Varo is a free tool with a few simple functions: it downloads digital data from 30DTRs and next-generation EMS cold chain equipment, captures facility and CCE appliance details from the user, and shares the unified "Varo report" via email. The intent is to make temperature and diagnostic data visible and shareable in ways that are impractical with paper.

Varo reports are not synchronized to a central Varo server: they exist only on the user's mobile device and in the email inbox(es) to which the user sends the report. The choice not to store data on the cloud was intentional: it ensures that Varo does not undermine national data governance and sovereignty policies.

A Varo report ties together data about three things: the logger, the appliance it's monitoring, and the facility where that equipment sits. Knowing the logger alone isn't enough — those three entities and their associations are what make aggregated reports actionable. This "three-legged stool" applies equally to RTMD and next-gen EMS data. At the local level, this supports charting and easy sharing with biomeds and CCOs; at higher levels, it enables aggregated reporting and connection to national and subnational decision-making systems.

Varo reports are already interoperable: the report has a standard, publicly documented structure. Some countries have made big leaps connecting Varo data to eLMIS systems via an "interoperability layer" — an approach consistent with the WHO's Digital transformation handbook for health supply chain architecture. Many countries already run data exchange or system mediation platforms to connect data across country systems; these are examples of an interoperability layer. In this architecture, Varo is simply a data producer with a clearly defined data structure, while DHIS2, OpenLMIS, Open mSupply, and other national I.T. systems are typically data aggregators/consumers, linked through proven, commodity data-exchange approaches.

Pogo LT is a free tool for aggregated CCE monitoring, but it doesn't connect to national systems. Pogo LT fills a gap for teams that need aggregated reporting but don't yet have a data exchange / interoperability layer strategy. If you need CCE reporting data connected to eLMIS or other national systems, using an interoperability layer or manually importing the raw JSON data file produced by Pogo LT are the recommended approaches. (Pogo LT does (briefly) store Varo reports on a cloud server, but only for the purposes of generating an aggregated Pogo LT report; this automatically expires after a short time. Use of Pogo LT is optional.)

How the interoperability layer works in practice:
The interoperability layer fetches Varo reports from a Gmail inbox at regular intervals, queries other systems (Health Facility Registries, DHIS2, etc.) to match the logger/appliance/facility information against authoritative master data, and updates national systems with CCE functional status and other attributes as defined by country requirements. This works today, and it accommodates 30DTR, RTMD, and next-gen EMS appliances from heterogenous devices and suppliers. 

Question 2: Varo is good but we need to be able to use it with iPhones as well - when will this be possible?

Response 2: We’ve explored porting Varo to iOS multiple times. The iOS platform makes it very challenging to easily collect data from loggers. They lockdown the ability for an app to automatically access connected USB devices and so it would require Varo to prompt a user to navigate to the connected device and select the appropriate files.

Question 3: Can VARO correlate temperature data with equipment age, maintenance history, power reliability, and ambient temperature to generate predictive maintenance recommendations?

Response 3: It does not currently do that. Varo doesn’t store any long-lived information about the equipment. Though one could imagine Varo delivering diagnostic information to the user based on the information it has received during the report creation flow.

Question 4: In scenarios where the 30TDR is non-functional across several facilities, what mitigation measures are in place to ensure the continued operation of VARO  POGO-LT?

Response 4: Where 30DTR is non-functional, a manual report can be done and notify your team as a note on the non-functionality of 30DTR.