Setting research priorities for global pandemic preparedness: An international consensus and comparison with ChatGPT's output.

Background: In this priority-setting exercise, we sought to identify leading research priorities needed for strengthening future pandemic preparedness and response across countries. Methods: The International Society of Global Health (ISoGH) used the Child Health and Nutrition Research Initiative (CHNRI) method to identify research priorities for future pandemic preparedness. Eighty experts in global health, translational and clinical research identified 163 research ideas, of which 42 experts then scored based on five pre-defined criteria. We calculated intermediate criterion-specific scores and overall research priority scores from the mean of individual scores for each research idea. We used a bootstrap (n = 1000) to compute the 95% confidence intervals. Results: Key priorities included strengthening health systems, rapid vaccine and treatment production, improving international cooperation, and enhancing surveillance efficiency. Other priorities included learning from the coronavirus disease 2019 (COVID-19) pandemic, managing supply chains, identifying planning gaps, and promoting equitable interventions. We compared this CHNRI-based outcome with the 14 research priorities generated and ranked by ChatGPT, encountering both striking similarities and clear differences. Conclusions: Priority setting processes based on human crowdsourcing - such as the CHNRI method - and the output provided by ChatGPT are both valuable, as they complement and strengthen each other. The priorities identified by ChatGPT were more grounded in theory, while those identified by CHNRI were guided by recent practical experiences. Addressing these priorities, along with improvements in health planning, equitable community-based interventions, and the capacity of primary health care, is vital for better pandemic preparedness and response in many settings.

Anxiety and depression level of patients with multidrug-resistant tuberculosis (MDR-TB) in two hospitals in Banten province, Indonesia.

Purpose: Anxiety and depression can be found in patients diagnosed with multidrug-resistant Tuberculosis (MDR-TB). The purpose of this research is to measure the level of anxiety and depression in new patients with MDR-TB. Methods: One hundred two new patients newly diagnosed with MDR TB in two hospitals in Banten province, Indonesia, are measured for depression and anxiety symptoms. The measurements used the Indonesian language version of the Zung Anxiety Self-Assessment Scale Questionnaire and the Indonesian version of Zung Self-Rating Depression Scale Questionnaire for Pulmonary Tuberculosis Patients that have been validated. The results include the demographic data presented descriptively as tables and charts. Results: The mean age of the patients is 39,57+12,48 years. The monthly income of the patients is 54,9% low and 45,1% medium with no high income. Male is 61,8%, and 38,2% are female. The mean score of the anxiety index is 57,32+10,23. The mean score of the depression index is 55,02+12,36. The percentage of patients with no anxiety is 13,7%, minimal to moderate anxiety 46,1%, marked to severe anxiety 33,3%, and most extreme anxiety 6,9%. Conclusions: A significant proportion of patients newly diagnosed with MDR-TB experience anxiety and depression.