President Ramaphosa announced the beginning of a large-scale campaign to counteract the spread of the Covid-19 virus by sending 10 000 field workers to visit homes in villages, towns and cities to screen residents for symptoms. The difficulty in screening vast numbers of people in rural and urban areas can be overcome by deploying a technological solution that can significantly accelerate data gathering.

Though no time frame has been set for the screening, testing, tracing and medical management programme, the challenges are obvious: 10 000 field workers need to screen as many South Africans as possible as quickly as possible to refer those presenting symptoms of the illness to local or mobile clinics for testing.

While the country struggles with social distancing in informal settlements and many retail situations, changes in symptoms may occur so quickly as to make efficient data gathering problematic. Enter M4Jam, a Gig technology company designed to provide a digital engagement solution that enables organisations to connect, communicate, inform and train people through a customisable mobile application.

Georgie Midgley, M4Jam’s CEO, says a two-day survey undertaken as a trial run, and which paid jobbers (signed up gig workers) to complete the survey from the comfort and safety of their own homes via their mobile devices, allowed the company to compile analytics on symptoms which could help the government and the private sector monitor the spread of the virus and allocate resources accordingly.

“On 29 and 30 March, 1035 participants from the informal market completed the survey using their mobile phones. The data gathered allowed us to create a real-time interactive heat map of responses and symptom reporting in non-urban and informal environments across all provinces,” says Midgley.

Results of the survey showed just how difficult a physical screening and referral exercise would be. “Of the 1035 households surveyed, these covered 6167 people in isolation, at an average of six per household. One household had 32 people in it,” she says.

“While 8% of households included people who were over the age of 65, 44% contained high-risk individuals, with conditions such as lung disease, moderate to severe asthma, cancer, TB, HIV/Aids and others. 73% of respondents reported no symptoms in their households, while 17% reported occupants with one symptom, 6% of households showed two symptoms and 4% showed three key symptoms of Covid-19 infection.”

Symptoms reported were roughly evenly split between fever (15%), dry cough (14%) and sore throat (13%). Midgley says 29% of respondents do not know what to do if they identified such symptoms, and 70% of respondents would prefer to be tested at home if and when symptoms did present themselves.

“While more than half respondents (54%) lived within five kilometres of a hospital, nearly a fifth of all respondents (19%) lived more than 20km from a hospital. Another 19% lived six to ten kilometres from a hospital where they could report themselves for testing,” says Midgley.

The fast, accurate data provided included valuable location, demographic and other information in real-time dashboards which could significantly improve resource allocation in responding to the pandemic.

“As social media and access to the internet allowed us to get up-to-date news on Covid-19, just image what live, real time data would do to inform not only the public sector but also the private sector,” concludes Midgley.