Dr Rinita Dam
Dr Rinita Dam is currently working as a community engagement researcher on the HumBug project. At every stage of the project, Rinita will interact with the communities of rural Tanzania and the Democratic Republic of Congo (DRC) with the intention of encouraging the mobilisation and adoption of the HumBug sensor.
Prior to her current role, Rinita has worked on a project that was funded by the European Union Horizon 2020 programme that supported structural change in research organisations to promote Responsible Research and Innovation (RRI). She conducted research into RRI within the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC) with a focus on the gender element of RRI.
Rinita has worked on a variety of health management projects as a postdoctoral researcher. At the University of Manchester, within the School of Health Sciences, Rinita has worked as a qualitative researcher on an evaluation programme study that focused on enhancing understanding of the new health care commissioning system in England. Still at the University of Manchester, Rinita conducted a qualitative study that evaluated the effectiveness of a childhood obesity awareness-raising intervention aimed at parents in Manchester.
Rinita has a background in Biomedical Sciences and Global Public Health, with a placement year at Pfizer pharmaceuticals. She has a Master’s degree in Reproductive and Sexual Health Research from the London School of Hygiene and Tropical Medicine and for her dissertation, she carried out quantitative analysis on primary data regarding the risk factors for entering sex work, particularly for women living in poverty in Tanzania. Following this, she studied for a PhD (which was funded by the Economic and Social Research Council) at the University of Birmingham, examining the impact of HIV and AIDS on 59 women and men from Kolkata, India, with regards to their personal coping strategies and accessing treatment and support services for the disease. Data was collected through semi-structured interviews.