Four steps to precision public health

Scott F. DowellDavid Blazes & Susan Desmond-Hellmann at Nature: “When domestic transmission of Zika virus was confirmed in the United States in July 2016, the entire country was not declared at risk — nor even the entire state of Florida. Instead, precise surveillance defined two at-risk areas of Miami-Dade County, neighbourhoods measuring just 2.6 and 3.9 square kilometres. Travel advisories and mosquito control focused on those regions. Six weeks later, ongoing surveillance convinced officials to lift restrictions in one area and expand the other.

By contrast, a campaign against yellow fever launched this year in sub-Saharan Africa defines risk at the level of entire nations, often hundreds of thousands of square kilometres. More granular assessments have been deemed too complex.

The use of data to guide interventions that benefit populations more efficiently is a strategy we call precision public health. It requires robust primary surveillance data, rapid application of sophisticated analytics to track the geographical distribution of disease, and the capacity to act on such information1.

The availability and use of precise data is becoming the norm in wealthy countries. But large swathes of the developing world are not reaping its advantages. In Guinea, it took months to assemble enough data to clearly identify the start of the largest Ebola outbreak in history. This should take days. Sub-Saharan Africa has the highest rates of childhood mortality in the world; it is also where we know the least about causes of death…..

The value of precise disease tracking was baked into epidemiology from the start. In 1854, John Snow famously located cholera cases in London. His mapping of the spread of infection through contaminated water dealt a blow to the idea that the disease was caused by bad air. These days, people and pathogens move across the globe swiftly and in great numbers. In 2009, the H1N1 ‘swine flu’ influenza virus took just 35 days to spread from Mexico and the United States to China, South Korea and 12 other countries…

The public-health community is sharing more data faster; expectations are higher than ever that data will be available from clinical trials and from disease surveillance. In the past two years, the US National Institutes of Health, the Wellcome Trust in London and the Gates Foundation have all instituted open data policies for their grant recipients, and leading journals have declared that sharing data during disease emergencies will not impede later publication.

Meanwhile, improved analysis, data visualization and machine learning have expanded our ability to use disparate data sources to decide what to do. A study published last year4 used precise geospatial modelling to infer that insecticide-treated bed nets were the single most influential intervention in the rapid decline of malaria.

However, in many parts of the developing world, there are still hurdles to the collection, analysis and use of more precise public-health data. Work towards malaria elimination in South Africa, for example, has depended largely on paper reporting forms, which are collected and entered manually each week by dozens of subdistricts, and eventually analysed at the province level. This process would be much faster if field workers filed reports from mobile phones.

Sources: Ref. 8/Bill & Melinda Gates Foundation

…Frontline workers should not find themselves frustrated by global programmes that fail to take into account data on local circumstances. Wherever they live — in a village, city or country, in the global south or north — people have the right to public-health decisions that are based on the best data and science possible, that minimize risk and cost, and maximize health in their communities…(More)”