Lot quality assurance sampling to assess coverage and compliance following mass drug administration to eliminate lymphatic filariasis in Fiji: A methodological approach

Background Assessing the quality of mass drug administration (MDA) rounds is a key component of lymphatic filariasis (LF) elimination programs. Routine collection of administrative coverage is unreliable, especially when pockets with low program coverage exist. To address this gap, we used lot quality assurance sampling (LQAS) following the 10th annual LF-MDA round in Fiji to explore whether there was any area in which target coverage was not reached. We also assessed the level of drug compliance and satisfaction with the LF-MDA implementation strategy. Methodology/principal findings We conducted a cross-sectional household survey in 3 divisions of Fiji. For LQAS, we defined 19 lots in 7 medical areas of the Suva sub-division and another 12 sub-divisions in the Central, Northern, and Eastern Divisions. A sample of 16 randomly selected household members was taken un each lot. We defined our decision rule as follows: if more than 1 person in a given lot did not swallow the medication, coverage was considered inadequate, i.e. less than 80%. Of the 7 lots in Suva sub-division and 12 lots in the 3 divisions, five and two lots, respectively, were identified as having inadequate coverage. The overall program coverage estimated from 304 samples was 92%, which was higher than the reported administrative coverage of 82%. About 98% of interviewees were offered the medication and 96% swallowed it. Non-participation arose from insufficient information on how to obtain the drugs. At least 92% were satisfied with the LF-MDA implementation strategy. Conclusions Areas of low program coverage with results discordant with the reported administrative coverage existed in both urban and rural settings. Drug compliance and satisfaction were high, even after repeated rounds. We recommend increasing efforts to deliver the service in those areas with inadequate program coverage, as well as conducting timely coverage assessment through LQAS for corrective actio

Implementation of the mental health Gap Action Programme (mhGAP) within the Fijian Healthcare System: a mixed-methods evaluation

To facilitate decentralisation and scale-up of mental health services, Fiji's Ministry of Health and Medical Services committed to implementing the World Health Organization's mental health Gap Action Programme (mhGAP). mhGAP training has been prolific; however, it remains unclear, beyond this, how successfully Fiji's national mental health program has been implemented. We aim to evaluate Fiji's mental health program to inform Fiji's national mental health program and to develop an evidence-base for best practice.The study design was guided by the National Implementation Research Network and adhered to the Consolidated Framework for Implementation Research. CFIR constructs were selected to reflect the objectives of this study and were adapted where contextually necessary. A mixed-methods design utilised a series of instruments designed to collect data from healthworkers who had undertaken mhGAP training, senior management staff, health facilities and administrative data.A total of 66 participants were included in this study. Positive findings include that mhGAP was considered valuable and easy to use, and that health workers who deliver mental health services had a reasonable level of knowledge and willingness to change. Identified weaknesses and opportunities for implementation and system strengthening included the need for improved planning and leadership.This evaluation has unpacked the various implementation processes associated with mhGAP and has simultaneously identified targets for change within the broader mental health system. Notably, the creation of an enabling context is crucial. If Fiji acts upon the findings of this evaluation, it has the opportunity to not only develop effective mental health services in Fiji but to be a role model for other countries in how to successfully implement mhGAP