COVID-19 appears to have pocketed the entirety of the human race as it threatens the whole world on a large scale. The virus emanated from Wuhan and has continuously spread across the world, killing thousands. This no doubt has posed a major threat to many of the underdeveloped health care systems in Africa even as it has stretched the healthcare facilities of developed countries to the limits. Technology may, however, just be the best bet to solving this global crisis.
Data scientists have constantly leveraged various innovations, to bring solutions to global challenges. Using technology, I believe, can enable us plan and mitigate against the present and subsequent pandemics. Leveraging technology, data can be obtained, from areas that appear to be disadvantaged in terms of poor accessibility. You would agree with me that some rural communities in Africa are far from being easily accessible, yet they still get hit by the pandemic.
Using machine learning models, data can be obtained from such localities where data gathering has proven to be difficult to obtain, due to inaccessibility. Data from these areas can supply reliable information on health characteristics, demography and lifestyle, among others.
Little information, at this point, could turn out to be very much of value to the front line workers combating the pandemic. Using the insights gathered from the machine learning model, governments and other private firms can begin to understand different regions and therefore make decisions related to specific localised requirement on the continent.
Responses like improvements in infrastructure, emergency funding allocation and other measures can be guided by some spatial information. As of now, financial systems, health-care professionals, medical equipment, are constrained, so it will be highly critical to swiftly identify countries, states, cities, towns and communities that poses higher risk of emergency.
Considering earlier reports from the most hit countries in Africa, there are maps that have shown the concentration of the population, appearing to be susceptible to COVID-19 complications. Technology can be used to work on related risk factors such as respiratory related diseases, number of people in households and the likes. Insights gathered from this can be used in mapping out risk profiles. Once the number of the at-risk population is identified, there can be proper dissemination of public health information that relates to that population.
Through the combination of data sources and readily available geo-tagged surveys from households, machine learning models can make us determine how local communities consume news on the pandemic.
Data indicating TV viewership, newspaper readers, radio listeners and mobile phone users would be available. These insights can be used, in selecting the best channels for targeting the pandemic awareness campaign and also ensuring optimum delivery of messages. Coming to the reality that this pandemic would pose both short and long term consequences, it is very essential to leverage the power of technology while planning for interventions.
Through the incorporation of data, from the local population into another form of technology called predictive analysis, downstream effects such as food security can be anticipated.
Data generated via machine learning is unique and can be explored to solve challenges around the COVID-19 pandemic. The technology behind machine learning allows learning in real-time, coupled with supplying information, such as risk factors that evolve. Therefore, it is a good technology to deploy in times of evolving crisis like the COVID-19 pandemic.
As the virus continues to take its toll on the continent and other parts of the world, relief packages continue to increase, but amidst this, technology solutions, to combat this pandemic must be given top priority in order to maximise the efficient distribution of the relief packages.
China leveraged big data and analytics to curtail the spread of the coronavirus. Beyond this, the country also deployed robots to assist in transporting medical aids and groceries to its teeming population. Furthermore, China employed drones, normally used for agricultural purposes, to assist in spraying disinfectants to areas that were affected by the virus. Places that were under lockdown were strictly monitored with surveillance camera. Scanners were also used to search out people with potential COVID-19 case or those who have failed to make use of face masks.
The country has also developed a technology that deploys a feature, using colour QR code to detect people with the virus and eventually, have them sent to isolation camps. Aside from machine learning and predictive analysis, artificial Intelligence and blockchain have also proven its usefulness in the fight against the pandemic.
In Saudi Arabia, stores and supermarkets, employ AI to assist in minimising the time for delivery. In the United Arab Emirates, blockchain is used in providing symptom diagnosis to its people.
This is not to say that Africa has not utilised the available technology. Various governments on the continent have swiftly encouraged their respective citizens to embrace mobile transactions for payment for goods and services rather than using cash to mitigate the contagious spread of the virus.
In Kenya, for instance, as of Tuesday, March 17, 2020, mobile operator, Safaricom, increased its daily transaction limits through M-Pesa and further waived charges on transfers up to $10. Some other telecom operators have endeavoured to double Internet speed for their customers, using fibre packages at home.
Governments on the continent have also set up information portals, opened lines that are toll-free as well as WhatsApp channels to pass only authentic information about COVID-19 and also enable their citizens to make reports on suspected cases. It is about time that Africa deploys advanced forms of technologies, beyond increasing the capacity of mobile banking and Internet connectivity. In times like these, if we do not want to be left behind, then, machine learning, predictive analysis, blockchain and artificial intelligence ought to become mainstream.