Amidst other factors, the effectiveness and efficiency of any surveillance system are first graded by its capacity to provide early warning signals. Currently, the infectious disease surveillance programs around the globe are far below the bar in identifying symptomatic patients in a good time. There is still a lot of dependence on community care workers and health facility reports. This creates a time lag in identifying symptomatic persons for confirmatory tests and puts an unnecessary burden on health care workers. In most cases, infected persons are enrolled in the surveillance system late.
At the early stage of symptoms, most persons resort to self-treatment. A large percentage of infected persons are enrolled in the surveillance programs when their immune systems have been battered and they have no choice but to reach out to health care service providers at the community or health facility level for treatment. Most times, this is not an intentional act of negligence on the part of the infected persons but an act out of ignorance. They are unsure of their status and have no standardized means of ascertaining their status based on persisting symptoms. They never know for sure until it’s too late.
Most systems that pride to be infectious disease surveillance systems are at their best a patient tracking or monitoring system that relies on the effort of community or facility healthcare workers to identify infected persons for enrollment. These systems rely on rumors, hearsay, close relative reporting and self-reporting to identify infectious disease suspect cases for enrollment into the surveillance program.
Infectious disease is as personal as anything can get hence its early detection has to be personal as well. Any infectious disease surveillance program without a robust self-checking and self-reporting system is doomed to fail at a large scale and even struggle to perform at a small scale.
While there have been very little and uncoordinated efforts on self-checking solutions for infectious disease control, self-reporting has been a common practice during outbreaks. However, the self-reporting process is largely handled in a non-evidence-based and non-automated manner, leading to a waste of financial and time resources due to several cases of false alarm. At the common best, toll-free lines are set up for suspect cases to be reported.
Though there has been great progress in the development of self-check systems for numerous health concerns like mental health and menstrual cycle monitoring, infectious disease is still trying to catch up. I mean Google Play Store and Apple Store has hundreds of health and well-being applications with conditional statement programming at basic and machine learning algorithm for the advanced ones. The current self-check systems for infectious diseases leave the public guessing suspect cases based on widely disseminated symptoms. Many times, no thanks to unverified posts on social media and uneducated gossips, disseminated symptoms can be an endless list of fabricated hunches.
Having a robust self-checking and self-reporting system is key to fighting the current spread of COVID-19 and every other infectious disease. Governments need to develop a robust self-checking and self-reporting system and aggressively promote public use. By robust, I mean an all-inclusive and yet technologically advanced system to detect infectious disease symptoms before individuals suffer immune system breakdown. With many successfully deployed reporting channels and tested machine learning models, a lot can be done to fight the spread of any virus.
There is a need for Medical Scientists, Public Health Specialists, Data Scientists, Data Engineers, Telecommunication Engineers, and other experts to work together in deploying scientifically sound, AI and data-driven daily self-check and self-reporting channels for early detection. In my opinion, the following reporting channels are currently not being fully leveraged and explored to ensure inclusion and promote participation in the daily self-check and self-reporting initiatives.
Apps: A standardized and government endorsed app for daily self-check and self-reporting should be developed and made available for free via mobile app stores and web browsers. The app should be AI and data-driven to provide users with updates on their well-being based on responses. The app should also provide users with the option of notifying necessary government officials when symptoms persist.
USSD Reporting System: To accommodate non-smartphone users, Unstructured Supplementary Service Data (USSD) reporting system should be setup. USSD code(s) for all mobile service operators should be widely disseminated for daily self-check and self-reporting.
SMS Reporting System: An AI-driven and toll-free text messaging service with dialogue reporting should also be set up for daily self-check and self-reporting.
Toll-free Call Center: Setup an AI and data-driven call center in widely spoken languages for daily self-check and self-reporting. Most infectious disease call centers are still being managed by human operators. This increases the waiting time of callers and discourages the use of the toll-free lines.
Paper-based Reporting System: While this can be contended because of its potential to further spread the virus if in contact with a positive patient, it remains an option worth considering for remote areas and it is close enough to what is currently being done. A booklet or scorecards for daily self-check and self-reporting should be given to residents of remote rural areas. This will help in early detection if community health workers are able to help residents analyze their data.
During an infectious disease outbreak, it’s safer to assume that the entire population of the affected area are suspects until the outbreak ceases. Hence, providing the entire population with means for daily self-check and self-reporting is important.
The essence of this article is not to discredit the current systems put in place but to open discussions on how to make the systems more effective and efficient. While the current system needs a proper re-evaluation, many current practices will remain valid no matter what. Using any of the reporting channels stated above requires some level of literacy and in some cases technology understanding. This is a good pointer to the fact that the current non-evidence-based self-check system will remain relevant in some places and for some people.
In my next article, I will articulate interesting solutions for other aspects of infectious disease control like contact tracing. Also, I intend to do an in-depth review of applicable machine learning and deep learning models for infectious disease control. I hope you enjoyed reading this piece.