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In this month’s episode, Abt experts Jill Berkowitz and Sung-Woo Cho discuss how machine learning can amplify our work combatting malaria—25 million people protected to date—by applying what we’ve learned to other infectious diseases.

Healthcare workers (HCWs) are a pivotal part of controlling the spread of infectious diseases and are at the forefront of the response to emerging pathogens. However, HCWs themselves are at high risk of exposure to these infectious diseases. To protect…

Abt uses machine learning to do things that until recently would have been impossible, such as categorizing a vast amount of unstructured text into main themes or counting mosquito eggs from a smartphone picture using image recognition.

Abt’s Natalie Matthews and Terri Mota connect the dots between homelessness and public health and discuss how we can do more moving forward in this podcast.

Infectious diseases can spread quickly through nursing homes, leading to high morbidity and mortality in this vulnerable population. The COVID-19 pandemic underscored this, causing over 1.7 million SARS-CoV-2 cases and almost 168,000 deaths among nursing…

Be it outbreak, epidemic, or pandemic—human or zoonotic—the goal is to get reliable information on infectious diseases, quickly. Abt experts Laura Edwards and Sung-Woo Cho discuss strategies for harnessing machine learning and data visualization to provide actionable information—at scale—that can help stem a health crisis.

Abt recommended a variety of ways to improve the diagnostic journey for Tasmanians with a rare disease through a rare disease diagnostic care pathway.

People with a substance use disorder are overrepresented in the justice system, from the arrest phase to incarceration to the risk for recidivism. For example, more than 10 times as many people in prison (58 percent) and sentenced to jail (63 percent)…