The Visualize No Malaria initiative has been running since 2015 as a collaboration between non-profit health organisation, PATH, the Zambian Ministry of Health and four tech companies – including data analytics provider Exasol. PATH’s involvement with the Ministry of Health began in 2007.
Jeff Bernson, the chief data officer and VP for technology analytics and market innovations at PATH, said that initially, the partnership involved rolling out the interventions that could prevent the spread of malaria including the use of bed nets, then later on increasing access to diagnostics and drugs to treat malaria.
In addition, he said that PATH helped the Zambian Ministry of Health to adopt increasingly digitised processes. Bernson explained that before 2007, the Ministry of Health was capturing case data but it was being logged in a register and hand-written and it takes a lot to correlate that and report it up and nothing was harmonised.
At the same time, PATH was also going through a transition, moving from capturing hand-written data, which took a lot of time to collate and analyse through spreadsheets and Excel tools, to creating more stabilised repositories.
Then the Ministry of Health with the help of PATH introduced a tool called DHIS2, District Health Information System, which Bernson described as a great open source tool.
A new data store was needed as PATH was taking into account not just surveillance data – routine data captured from a health facility or at a community level – but also environmental data such as vegetation and rainfall which are good indicators of mosquito habitats.
“As we digitised it, the quality of that data was also improving and we started to think about which better tools we could be using,” said Bernson. With the digitised system, PATH and the Ministry of Health were able to begin to ask tougher questions of the data such as where does the disease emerge and what effect are the available resources having on it.
At this level, PATH and the Zambian Ministry of Health needed to use high-speed databases with in-memory computing like Exasol. “It allows us to not only store that data but also serve it up much faster in low resource settings,” said Bernson.
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