Vijiji Tanzania is working with UTHealth at Houston, Trinity Analytics and UDSM in AI enabled clinical decisions *CARE ACT* that will help in making quick clinical decisions and predicting specific outcomes, expect advances in the direction of predicting the entire temporal evolution of a patient.

CARE ACT uses Techniques such as structured output prediction or latent embedding have been successfully used both in the ICU and elsewhere. This approach for developing personalised patient management and treatment plans, based on the success on previous patients with similar prognosis.

CARE ACT uses AI and machine learning (ML) to the data collected to assist in building Traditional epidemic models and the spreading of a contagious disease in a population using differential equations. AI tool can be used to predict COVID-19 incidence and evaluate the impact of mitigating measures such as population confinement and social distancing. Geolocated critical care demand prediction, optimal hospital resource planning, and intelligent patient flow management with decision support algorithms can also be achieved by integrating real time clinical data with population statistics and health interventions.

Vijiji Tanzania uses Computer-assisted detection systems for early identification, grading, and monitoring of infectious and non-infectious lung diseases. Interestingly, our design can also be used to distinguish viral pneumonia from bacterial pneumonia. It is the ML techniques that focus on detecting critical care needs at the Primary Health Care facilities.