Invisible Killer, The World’s Most Underestimated Disease

Invisible Killer, The World’s Most Underestimated Disease

Organisation: Newsweek (United States)

Publication Date: 04/09/2016


Size of team/newsroom:small


Tuberculosis (TB) is second only to HIV/AIDS as the greatest killer worldwide due to a single infectious agent. In 2013, an estimated 9 million people developed tuberculosis and 1.5 million men, women and children died from the disease, which heavily affects the most poor and marginalized communities in the world. In 2014, tuberculosis surpassed HIV as the most deadly infectious disease, leading to 1.5 millions dead worldwide. Africa carried the greatest proportion of new cases per population with 280 cases per 100 000 population in 2013 and, despite the huge progress made over the years to combat this disease, in South Africa TB is still the leading cause of death. High co-infection with HIV, poor medication adherence and densely populated township communities have led to the dissemination of Multi drugs resistant TB (MDR-TB) and Extensively drug resistant TB (XDR-TB) among the population, that occurs when a strain of TB bacteria becomes resistant to two or more "first-line" antibiotic drugs prescribed to combat standard TB. MDR-TB and XDR-TB can only be cured with the use of very expensive and toxic second line drugs, and mortality is up to one third off all the patients. HIV/AIDS in South Africa, where more than 6 million people live with HIV, continues to help fuel the tuberculosis epidemic, which bears the brunt of the burden with 80 per cent of HIV-associated tuberculosis patients worldwide. The problem of antimicrobial resistance poses a great threat to tuberculosis control and remains a major concern for global health security. We investigate this topic from different point of view. We went in the township of Khayelitsha, one of the biggest in south africa, where local activists are trying to inform the population and fighting the stigma around it. We investigate the poor health conditions of mine workers, one of the most affected by this problem. Indeed some 89% of the mine worker are TB positive. In order to tell this story the project combines photoessay, short video story and data visualizations in a single narrative. The team of this project is formed by: Tomaso Clavarino (IT): Photojournalist Isacco Chiaf (IT): Video reporter and graphic designer Luca Vigliani (IT): Video editing This investigative report was conducted with the support of the "Innovation in Development Reporting Grant" program of the European Journalism Centre (EJC), financed by the Bill and Melinda Gates Foundation.

What makes this project innovative? What was its impact?

For such complex and broad topic we decided to combine on-field reporting together with data analysis and data visualizations. This method of telling the story allowed us to counterbalance the scientific analysis done trough data visualizations, with the emotions and the feelings of the patients, and how they coped with the sickness. This allowed us to offer to the viewer a 360 degree view on the topic, with exhaustive explanation, yet in a compelling visual-based format. Additionally, animated data visualizations has been used also as motion graphics elements inside the short video reportage, in order to offer more insight and hard fact to the issue. The uniqueness of Invisible Killers lise in the fact that data, graphics and images mingle inside one unique product with a strong and personal visual identity.

Technologies used for this project:

The project has been design developed and coded from ground-up. The language used for the web page are javascrtipt, CSS3 and HTML. For the data visualizations, we used the global tuberculosis dataset, collected by the world health organization (WHO). The data has been elaborated, filtered and visualized with NodeBox, a python based software, with node GUI for data refining and data visualizations. The final outputs has than been designed and fine-tuned with Adobe Illustrator. For the video motions graphics we used After Effect and NodeBox again for data extraction.


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