Epidemic and disease mapping
By utilising Artificial Intelligence (AI), EPCON quantifies disease burden in specific regions and population groups. We capture, analyze and combine health records with contextual data to expose current epidemic risks and predict their evolution. We can estimate the effects of potential interventions before they happen.
We can help healthcare partners, NGOs and governments target their resources to those patients and areas that need it the most in the following ways:
Preventing disease breakouts and public health catastrophes
Once the program team is well informed about the epidemic and subnational differences, it is capable of making evidence-based decisions on what regions should be prioritized, what capacity should be deployed and what is the most effective approach. Our platform helps the program team to understand the ‘WHY’ and will further facilitate in the strategy and planning to reach the program targets. Evidence based planning and routine monitoring is key to prevention of public health catastrophes.
Identifying disease hotspots
Identifying hotspots is crucial in controlling the spread of diseases. This information is then presented in a powerful visual and spatial format to aid communication. Agencies are then able to prioritize interventions and allocate resources efficiently.
Finding missing patients
Finding missing or undiagnosed patients is key to beating an epidemic. As more data is generated, our AI engine becomes both smarter and more refined. Consequently, resources can be steered in the right direction for maximum impact.
High resolution disease predictions
High resolution observation of data at smaller geographical units enables you to pinpoint problems that could have gone undetected in usual national level prevalence surveys. Common methods of Incidence estimates are also restricted to usual administrative boundaries. With national level prevalence surveys, many problems go undetected. That’s why we generate highly granular estimates of disease burden, at population cluster level, which can guide screening activities, community outreach programs and many other community based interventions. Pinpointing disease within small geographical units improves workforce planning, allows for better engagement with local stakeholders and permits the comparison of various interventions.
Optimising your health programme
We generate visually appealing real time dashboards where your team can observe the daily progress of your field activities, study trends over time, compare the estimates and actual values, generate evidence based program recommendations and tackle bottlenecks in the way of your program steering. This helps to achieve current and future targets.
Reaching the most remote regions
Remote regions often lose out due to a lack of information and scarce resources. By extrapolating data from reference regions in terms of health records and living environment, we can assess the disease burden in the most remote areas. Costly health programmes with an uncertain outcome can now make way for targeted campaigns.
Take preventive action
With the vast quantity of data that enters our AI engine, we can predict how the disease burden will evolve in time and space. Go from costly reactive campaigns to precise preventive actions.
Epicare is a modular survey app to monitor drug adherence. It serves as a communication channel between healthcare workers and target patients to inform and support patients.
To assist our healthcare partners we created Geocare360, a platform where healthcare workers can log information on patients’ screenings and diagnosis. This data feeds our AI engine making it smarter providing even better insights over time.
A few reference cases
Tracking down TB: A Nigerian Case Study
Better Disease Control with the Covid Prediction Dashboard
EPCON supports the National TB Control Programme in Pakistan to find missing cases