How data analysis helped Mozambique stem a cholera outbreak


Andrew Jack at the Financial Times: “When Mozambique was hit by two cyclones in rapid succession last year — causing death and destruction from a natural disaster on a scale not seen in Africa for a generation — government officials added an unusual recruit to their relief efforts. Apart from the usual humanitarian and health agencies, the National Health Institute also turned to Zenysis, a Silicon Valley start-up.

As the UN and non-governmental organisations helped to rebuild lives and tackle outbreaks of disease including cholera, Zenysis began gathering and analysing large volumes of disparate data. “When we arrived, there were 400 new cases of cholera a day and they were doubling every 24 hours,” says Jonathan Stambolis, the company’s chief executive. “None of the data was shared [between agencies]. Our software harmonised and integrated fragmented sources to produce a coherent picture of the outbreak, the health system’s ability to respond and the resources available.

“Three and a half weeks later, they were able to get infections down to zero in most affected provinces,” he adds. The government attributed that achievement to the availability of high-quality data to brief the public and international partners.

“They co-ordinated the response in a way that drove infections down,” he says. Zenysis formed part of a “virtual control room”, integrating information to help decision makers understand what was happening in the worst hit areas, identify sources of water contamination and where to prioritise cholera vaccinations.

It supported an “mAlert system”, which integrated health surveillance data into a single platform for analysis. The output was daily reports distilled from data issued by health facilities and accommodation centres in affected areas, disease monitoring and surveillance from laboratory testing….(More)”.

Dynamic Networks Improve Remote Decision-Making


Article by Abdullah Almaatouq and Alex “Sandy” Pentland: “The idea of collective intelligence is not new. Research has long shown that in a wide range of settings, groups of people working together outperform individuals toiling alone. But how do drastic shifts in circumstances, such as people working mostly at a distance during the COVID-19 pandemic, affect the quality of collective decision-making? After all, public health decisions can be a matter of life and death, and business decisions in crisis periods can have lasting effects on the economy.

During a crisis, it’s crucial to manage the flow of ideas deliberatively and strategically so that communication pathways and decision-making are optimized. Our recently published research shows that optimal communication networks can emerge from within an organization when decision makers interact dynamically and receive frequent performance feedback. The results have practical implications for effective decision-making in times of dramatic change….

Our experiments illustrate the importance of dynamically configuring network structures and enabling decision makers to obtain useful, recurring feedback. But how do you apply such findings to real-world decision-making, whether remote or face to face, when constrained by a worldwide pandemic? In such an environment, connections among individuals, teams, and networks of teams must be continually reorganized in response to shifting circumstances and challenges. No single network structure is optimal for every decision, a fact that is clear in a variety of organizational contexts.

Public sector. Consider the teams of advisers working with governments in creating guidelines to flatten the curve and help restart national economies. The teams are frequently reconfigured to leverage pertinent expertise and integrate data from many domains. They get timely feedback on how decisions affect daily realities (rates of infection, hospitalization, death) — and then adjust recommended public health protocols accordingly. Some team members move between levels, perhaps being part of a state-level team for a while, then federal, and then back to state. This flexibility ensures that people making big-picture decisions have input from those closer to the front lines.

Witness how Germany considered putting a brake on some of its reopening measures in response to a substantial, unexpected uptick in COVID-19 infections. Such time-sensitive decisions are not made effectively without a dynamic exchange of ideas and data. Decision makers must quickly adapt to facts reported by subject-area experts and regional officials who have the relevant information and analyses at a given moment….(More)“.

Using Data for COVID-19 Requires New and Innovative Governance Approaches


Stefaan G. Verhulst and Andrew Zahuranec at Data & Policy blog: “There has been a rapid increase in the number of data-driven projects and tools released to contain the spread of COVID-19. Over the last three months, governments, tech companies, civic groups, and international agencies have launched hundreds of initiatives. These efforts range from simple visualizations of public health data to complex analyses of travel patterns.

When designed responsibly, data-driven initiatives could provide the public and their leaders the ability to be more effective in addressing the virus. The Atlantic andNew York Times have both published work that relies on innovative data use. These and other examples, detailed in our #Data4COVID19 repository, can fill vital gaps in our understanding and allow us to better respond and recover to the crisis.

But data is not without risk. Collecting, processing, analyzing and using any type of data, no matter how good intention of its users, can lead to harmful ends. Vulnerable groups can be excluded. Analysis can be biased. Data use can reveal sensitive information about people and locations. In addressing all these hazards, organizations need to be intentional in how they work throughout the data lifecycle.

Decision Provenance: Documenting decisions and decision makers across the Data Life Cycle

Unfortunately the individuals and teams responsible for making these design decisions at each critical point of the data lifecycle are rarely identified or recognized by all those interacting with these data systems.

The lack of visibility into the origins of these decisions can impact professional accountability negatively as well as limit the ability of actors to identify the optimal intervention points for mitigating data risks and to avoid missed use of potentially impactful data. Tracking decision provenance is essential.

As Jatinder Singh, Jennifer Cobbe, and Chris Norval of the University of Cambridge explain, decision provenance refers to tracking and recording decisions about the collection, processing, sharing, analyzing, and use of data. It involves instituting mechanisms to force individuals to explain how and why they acted. It is about using documentation to provide transparency and oversight in the decision-making process for everyone inside and outside an organization.

Toward that end, The GovLab at NYU Tandon developed the Decision Provenance Mapping. We designed this tool for designated data stewards tasked with coordinating the responsible use of data across organizational priorities and departments….(More)”

Digital Contact Tracing for Pandemic Response: Ethics and Governance Guidance


Book edited by Jeffrey Kahn and Johns Hopkins Project on Ethics and Governance of Digital Contact Tracing Technologies: “As public health professionals around the world work tirelessly to respond to the COVID-19 pandemic, it is clear that traditional methods of contact tracing need to be augmented in order to help address a public health crisis of unprecedented scope. Innovators worldwide are racing to develop and implement novel public-facing technology solutions, including digital contact tracing technology. These technological products may aid public health surveillance and containment strategies for this pandemic and become part of the larger toolbox for future infectious outbreak prevention and control.

As technology evolves in an effort to meet our current moment, Johns Hopkins Project on Ethics and Governance of Digital Contact Tracing Technologies—a rapid research and expert consensus group effort led by Dr. Jeffrey Kahn of the Johns Hopkins Berman Institute of Bioethics in collaboration with the university’s Center for Health Security—carried out an in-depth analysis of the technology and the issues it raises. Drawing on this analysis, they produced a report that includes detailed recommendations for technology companies, policymakers, institutions, employers, and the public. The project brings together perspectives from bioethics, health security, public health, technology development, engineering, public policy, and law to wrestle with the complex interactions of the many facets of the technology and its applications. This team of experts from Johns Hopkins University and other world-renowned institutions has crafted clear and detailed guidelines to help manage the creation, implementation, and application of digital contact tracing. Digital Contact Tracing Technology for Pandemic Response is the essential resource for this fast-moving crisis…(More)”.

BiblioVid


About: “The project BiblioVid was born out the observation that, when confronted to a serious global crisis, like during the COVID-19 pandemics, it is very hard for health professionals to keep in touch with the latest development, results and recommendations on how to manage the situation. Moreover, it is very hard to quickly make the distinction between valid and doubtful information, high- and low-quality data, as these get thrown around into the mediatic maelstrom.

In this context, four friends working at the Grenoble Alpes University Hospital Center, we decided to join forces on two projects, the first one on monitoring and analyzing the most recent literature on COVID-19 and the second one aimed at providing support for health students during the COVID-19 health crisis…

Now this project breached the French boundaries, reaching health professionals in many countries with teams from Belgium and Canada joining-in to help with the development and dissemination of this tool…(More)”.

Removing the pump handle: Stewarding data at times of public health emergency


Reema Patel at Significance: “There is a saying, incorrectly attributed to Mark Twain, that states: “History never repeat itself but it rhymes”. Seeking to understand the implications of the current crisis for the effective use of data, I’ve drawn on the nineteenth-century cholera outbreak in London’s Soho to identify some “rhyming patterns” that might inform our approaches to data use and governance at this time of public health crisis.

Where better to begin than with the work of Victorian pioneer John Snow? In 1854, Snow’s use of a dot map to illustrate clusters of cholera cases around public water pumps, and of statistics to establish the connection between the quality of water sources and cholera outbreaks, led to a breakthrough in public health interventions – and, famously, the removal of the handle of a water pump in Broad Street.

Data is vital

We owe a lot to Snow, especially now. His examples teaches us that data has a central role to play in saving lives, and that the effective use of (and access to) data is critical for enabling timely responses to public health emergencies.

Take, for instance, transport app CityMapper’s rapid redeployment of its aggregated transport data. In the early days of the Covid-19 pandemic, this formed part of an analysis of compliance with social distancing restrictions across a range of European cities. There is also the US-based health weather map, which uses anonymised and aggregated data to visualise fever, specifically influenza-like illnesses. This data helped model early indications of where, and how quickly, Covid-19 was spreading….

Ethics and human rights still matter

As the current crisis evolves, many have expressed concern that the pandemic will be used to justify the rapid roll out of surveillance technologies that do not meet ethical and human rights standards, and that this will be done in the name of the “public good”. Examples of these technologies include symptom- and contact-tracing applications. Privacy experts are also increasingly concerned that governments will be trading off more personal data than is necessary or proportionate to respond to the public health crisis.

Many ethical and human rights considerations (including those listed at the bottom of this piece) are at risk of being overlooked at this time of emergency, and governments would be wise not to press ahead regardless, ignoring legitimate concerns about rights and standards. Instead, policymakers should begin to address these concerns by asking how we can prepare (now and in future) to establish clear and trusted boundaries for the use of data (personal and non-personal) in such crises.

Democratic states in Europe and the US have not, in recent memory, prioritised infrastructures and systems for a crisis of this scale – and this has contributed to our current predicament. Contrast this with Singapore, which suffered outbreaks of SARS and H1N1, and channelled this experience into implementing pandemic preparedness measures.

We cannot undo the past, but we can begin planning and preparing constructively for the future, and that means strengthening global coordination and finding mechanisms to share learning internationally. Getting the right data infrastructure in place has a central role to play in addressing ethical and human rights concerns around the use of data….(More)”.

Stay alert, infodemic, Black Death: the fascinating origins of pandemic terms


Simon Horobin at The Conversation: “Language always tells a story. As COVID-19 shakes the world, many of the words we’re using to describe it originated during earlier calamities – and have colourful tales behind them.

In the Middle Ages, for example, fast-spreading infectious diseases were known as plagues – as in the Bubonic plague, named for the characteristic swellings (or buboes) that appear in the groin or armpit. With its origins in the Latin word plaga meaning “stroke” or “wound”, plague came to refer to a wider scourge through its use to describe the ten plagues suffered by the Egyptians in the biblical book of Exodus.

An alternative term, pestilence, derives from Latin pestis (“plague”), which is also the origin of French peste, the title of the 1947 novel by Albert Camus (La Peste, or The Plague) which has soared up the bestseller charts in recent weeks. Latin pestis also gives us pest, now used to describe animals that destroy crops, or any general nuisance or irritant. Indeed, the bacterium that causes Bubonic plague is called Yersinia pestis….

The later plagues of the 17th century led to the coining of the word epidemic. This came from a Greek word meaning “prevalent”, from epi “upon” and demos “people”. The more severe pandemic is so called because it affects everyone (from Greek pan “all”).

A more recent coinage, infodemic, a blend of info and epidemic, was introduced in 2003 to refer to the deluge of misinformation and fake news that accompanied the outbreak of SARS (an acronym formed from the initial letters of “severe acute respiratory syndrome”).

The 17th-century equivalent of social distancing was “avoiding someone like the plague”. According to Samuel Pepys’s account of the outbreak that ravaged London in 1665, infected houses were marked with a red cross and had the words “Lord have mercy upon us” inscribed on the doors. Best to avoid properties so marked….(More)”.

Governing Simulations: Intro to Necroeconomics


Bryan Wolff, Yevheniia Berchul, Yu Gong, Andrey Shevlyakov at Strelka Mag: “French philosopher Michel Foucault defined biopower as the power over bodies, or the social and political techniques to control people’s lives. Cameroonian philosopher Achille Mbembe continued this line of thinking to arrive at necropolitics, the politics of death, or as he phrases it: “contemporary forms of subjugation of life, to the power of death.” COVID-19 has put these powers in sharp relief. Most world-changing events of the twenty-first century have been internalized with the question “where were you?” For example, “where were you when the planes hit?” But the pandemic knows no single universal moment to refer to. It’s become as much a question of when, as of where. “When did you take the pandemic seriously?” Most likely, your answer stands in direct relation to your proximity to death. Whether a critical mass or a specific loss, fatality defined COVID-19’s reality.

For many governments, it wasn’t the absolute count of death, but rather its simulations that made them take action. The United States was one of the last countries holding out on a lockdown until the Imperial College report projected the possibility of two million to four million fatalities in the US alone (if no measures were taken). And these weren’t the only simulations being run. A week into the lockdown, it was wondered aloud whether this was all worth the cost. It was a unique public reveal of the deadly economics—or necroeconomics—that we’re usually insulated from, whether through specialist language games or simply because they’re too grim to face. But ignoring the financialization of our demise doesn’t make it go away. If we are to ever reconsider the systems meant to keep us alive, we’d better get familiar. What better place to start than to see the current crisis through the eyes of one of the most widely used models of death: the one that puts a price on life. It’s called the “Value of a Statistical Life” or VSL..(More)”.

The Big Failure of Small Government


Mariana Mazzucato and Giulio Quaggiotto at Project Syndicate: “Decades of privatization, outsourcing, and budget cuts in the name of “efficiency” have significantly hampered many governments’ responses to the COVID-19 crisis. At the same time, successful responses by other governments have shown that investments in core public-sector capabilities make all the difference in times of emergency. The countries that have handled the crisis well are those where the state maintains a productive relationship with value creators in society, by investing in critical capacities and designing private-sector contracts to serve the public interest.

From the United States and the United Kingdom to Europe, Japan, and South Africa, governments are investing billions – and, in some cases, trillions – of dollars to shore up national economies. Yet, if there is one thing we learned from the 2008 financial crisis, it is that quality matters at least as much as quantity. If the money falls on empty, weak, or poorly managed structures, it will have little effect, and may simply be sucked into the financial sector. Too many lives are at stake to repeat past errors.

Unfortunately, for the last half-century, the prevailing political message in many countries has been that governments cannot – and therefore should not – actually govern. Politicians, business leaders, and pundits have long relied on a management creed that focuses obsessively on static measures of efficiency to justify spending cuts, privatization, and outsourcing.

As a result, governments now have fewer options for responding to the crisis, which may be why some are now desperately clinging to the unrealistic hope of technological panaceas such as artificial intelligence or contact-tracing apps. With less investment in public capacity has come a loss of institutional memory (as the UK’s government has discovered) and increased dependence on private consulting firms, which have raked in billions. Not surprisingly, morale among public-sector employees has plunged in recent years.

Consider two core government responsibilities during the COVID-19 crisis: public health and the digital realm. In 2018 alone, the UK government outsourced health contracts worth £9.2 billion ($11.2 billion), putting 84% of beds in care homes in the hands of private-sector operators (including private equity firms). Making matters worse, since 2015, the UK’s National Health Service has endured £1 billion in budget cuts.

Outsourcing by itself is not the problem. But the outsourcing of critical state capacities clearly is, especially when the resulting public-private “partnerships” are not designed to serve the public interest. Ironically, some governments have outsourced so eagerly that they have undermined their own ability to structure outsourcing contracts. After a 12-year effort to spur the private sector to develop low-cost ventilators, the US government is now learning that outsourcing is not a reliable way to ensure emergency access to medical equipment….(More)”.

The public debate around COVID-19 demonstrates our ongoing and misplaced trust in numbers


Ville Aula at LSE Blogs: “Read the front page of any major newspaper and I guarantee that the latest number of patients who have tested positive for COVID-19 and the number of mortalities will feature heavily. Open your social media accounts and you will quickly encounter graphs that show the mounting numbers of cases in different countries, complemented by modelling projections. These numbers and graphs feed the popular imagination of how well countries are “flattening the curve”, a concept that has brought epidemiological modelling inspired language to everyone’s lips. 

Numbers, graphs, and data are thus playing an essential part in how we experience the pandemic. The endless flows of numbers from different countries are meticulously compared with those from others. These comparisons then form the basis to how individual countries are portrayed and ranked in the global pandemic drama. 

But, there is also doubt in the air. We distrust the existing numbers and call for ever-more accurate information. For example, there has been a lively debate on how widespread the pandemic has been in China, an issue that connects directly to how tests are administered and cases reported. Equally, numbers from Europe do not provide indisputable or uniform information on the pandemic either, because their collection is subject to vastly different policies, practices, and contexts that make comparisons difficult. We also lack the scientific consensus that would allow us to link the number of mortalities to the prevalence of the virus, yet mortalities are still often taken as the most solid form of information on the pandemic.  These doubts have fuelled demands to do systematic population level testing of the virus prevalence, which is just a different way of saying that we need more numbers. 

Numbers are thus both the problem and the solution, and we want more of them. However, what makes numbers useful for developing better treatments and policies, does not necessarily lead to the same outcomes when applied to public debate. In the broader sphere of public debate, such tendencies reveal a longing for the veracity of data during times of uncertainty. Even when such calls are founded on demands for transparency in the name of democracy or healthy skepticism of existing data, they are entangled in a faulty logic of data itself eventually providing a solid standing for public debate….(More)”.