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Tuberculosis is a respiratory disease that is treatable with antibiotics. An increasing prevalence of resistance means that to ensure a good treatment outcome it is desirable to test the susceptibility of each infection to different antibiotics. Conventionally, this is done by culturing a clinical sample and then exposing aliquots to a panel of antibiotics, each being present at a pre-determined concentration, thereby determining if the sample isresistant or susceptible to each sample. The minimum inhibitory concentration (MIC) of a drug is the lowestconcentration that inhibits growth and is a more useful quantity but requires each sample to be tested at a range ofconcentrations for each drug. Using 96-well broth micro dilution plates with each well containing a lyophilised pre-determined amount of an antibiotic is a convenient and cost-effective way to measure the MICs of several drugs at once for a clinical sample. Although accurate, this is still an expensive and slow process that requires highly-skilled and experienced laboratory scientists. Here we show that, through the BashTheBug project hosted on the Zooniverse citizen science platform, a crowd of volunteers can reproducibly and accurately determine the MICs for 13 drugs and that simply taking the median or mode of 11-17 independent classifications is sufficient. There is therefore a potential role for crowds to support (but not supplant) the role of experts in antibiotic susceptibility testing.

In 2020, the World Health Organization estimated that in Madagascar there were 238 cases of Mycobacterium tuberculosis complex infection per 100,000 persons, but fewer than half of infected persons were [...]

Cough assessment is central to the clinical management of respiratory diseases, including tuberculosis (TB), but strategies to objectively and unobtrusively measure cough are lacking. Acoustic epidemiology is an emerging field that uses technology to detect cough sounds and analyze cough patterns to improve health outcomes among people with respiratory conditions linked to cough. This field is increasingly exploring the potential of artificial intelligence (AI) for more advanced applications, such as analyzing cough sounds as a biomarker for disease screening. While much of the data are preliminary, objective cough assessment could potentially transform disease control programs, including TB, and support individual patient management. Here, we present an overview of recent advances in this field and describe how cough assessment, if validated, could support public health programs at various stages of the TB care cascade.

Objective: This study aimed to examine the link between friendship instability during emerging adulthood and depressive symptoms. The moderating role of gender and the pursuit (or not) of postsecondary education was also tested. Participants: A total of 268 participants (60.7% women) was interviewed annually between the ages of 22 and 26. Methods: Friendship instability was measured by asking the participants to name their three best friends each year and depressive symptoms were assessed at ages 22 and 26. Results: A multiple hierarchical regression analysis predicting depressive symptoms at age 26 (while controlling for symptoms at age 22) revealed a triple interaction between friendship instability, gender and the pursuit of postsecondary education. Specifically, friendship instability predicted depressive symptoms at age 26, but only among women pursuing postsecondary education. Conclusions: These results highlight the importance of maintaining friendships for these individuals.