Net/Health fights pandemic

supports post-lockdown

Enables mobile networks to support outbreak modelling and combat resurgence


Introducing Net/Health, a real-time mobile data platform for epidemic control

Net/Health enables Mobile Network Operators (MNO) to offer analytics and monitoring support to public health authorities and epidemic scientists in their situation assessments and decision-making.


  • “We offer anonymous mobility data to help health authorities predict and prevent the spread of the virus.”

    Sigve Brekke, President & CEO, Telenor Group
  • “The estimates of aggregate flows of people are incredibly valuable. A map that examines the impact of social distancing messaging or policies on population mobility patterns, for example, will help county officials understand what kinds of messaging or policies are most effective….. We will need these estimates, not only now but also when we need to resume life again without risking a major resurgence.”

    Caroline O. Buckee, Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health
  • “Over the course of the COVID-19 crisis so far, the GSMA has been working closely with operators
    and demand-side agencies to understand how mobile big data analytics can support governments.
    We have seen four main types of data aggregates used to build insights to combat the virus and
    improve the response, easing the impact on citizens’ lives.”

    The role of AI for Impact in the fight against COVID-19, GSMA

Net/Health uses Grafana for its interactive dashboard.  With a plethora of visualization options to help users to understand the data, the graphical interface displays real-time metrics, time series comparisons, animated maps, visual histograms, donut charts, analytic maps and space-time cubes to visually explore movements and interaction, correlate it with the transit network at very fine grain.

Crowd Avoidance: Net/Health supports heat map visualization of  places where and when people engage in behaviour which puts them at risk of contracting the disease through human-to-human contact or air inhalation in a relatively closed environment. In addition to the usual health advice like “wash your hands or avoid crowds”, more specific space-time activity recommendations could be made.

Net/Health Geo-analytics visualization will help researchers and decision makers to model and simulate practical solutions (e.g. changing commuting patterns, time-based economic activities, e.g. temporarily cutting off certain geo links between certain major hubs or areas)

During post-lockdown, Net/Health geo-analytics visualization can help decision makers to model and simulate practical solutions for re-opening. For example, by changing certain patterns on commuting or time-based economic activities such as selectively suspending transport links between certain major hubs or areas.



Net/Health can help users to measure and monitor the effectiveness of containment measures

  • Identify locations with high population mixing and assess impact of travel or social gathering restrictions during outbreaks.
  • Estimate of the amount of time people spend away from home, the number of locations people visit in a day, and the volume of people travelling between two regions can be derived from the data. These estimates can be calculated on a daily basis, typically providing timely insights into what happened 24 to 48 hours ago.
  • Measure how much less are people travelling as a result of the restrictions. How much time are people still spending away from home.
  • Measure how much travel is still happening between administrative regions

Using historic data, which can be up to 30 days from the time of the query, Net/Health supports  health authorities to trace a particular individual, suspected or known to be a carrier of a contagious disease. Net/Health tracing is based on the person’s journey, inferred activity from trajectory, social cluster and contact network based on historical co-location and routine regularity analysis with very high temporal resolution.  

Using location situation and encounter probability analysis (e.g. crowdedness, closeness, inferred spatial distance etc.), Net/Health will output a list of anonymized people who might have been in proximity with the suspect.

Net/Health can trace multiple targets simultaneously in different districts of a city within the same time window. This capability can be used to track down the first spreader of an outbreak.




Classical compartmental epidemic models such as SIR model do not take into account the impact of social connectivity and mobility on the spreading of virus.

Net/Health offers a built-in compartmental reference model which incorporate quantitative input of mobility and connectivity at different location granularities. Within each geographical area, infection dynamics can be studied taking into account the latest mobility and social connectivity parameters.   With Net/Health,  epidemiologists can study the current disease dynamics with a more predictiveness.


Why JSpectrum

With over 15 years of experience in building passive monitoring of mobility and location,  JSpectrum is a pragmatic carrier grade platform builder. Unlike data and analytics products, we build our real-time platform from practice. With key competence in actionable analytics based on historical profile, elapsed time events and network signalling, JSpectrum is a carrier-grade platform builders for robust operation and maintainability.  We collaborate with international R&D communities and adapt latest  published findings.


Leave a Reply