Recommendations for an Optimal Model of integrated case detection, referral, and confirmation of Neglected Tropical Diseases: A case study in Bong County, Liberia
Godwin-Akpan, T. G.; Chowdhury, S.; Rogers, E. J.; Kollie, K. K.; Zaizay, F. Z.; Wickenden, A.; Zawolo, G. V. K.; Parker, C. B. M. C.; Dean, L.
Show abstract
BackgroundPeople affected by Neglected Tropical Diseases (NTDs), specifically leprosy, Buruli ulcer (BU), yaws, and lymphatic filariasis, experience significant delays in accessing health services, often leading to catastrophic physical, psychosocial, and economic consequences. Global health actors have recognized that Sustainable Development Goal 3:3 is only achievable through an integrated inter and intra-sectoral response. This study evaluated existing case detection and referral approaches in Liberia, utilizing the findings to develop and test an Optimal Model for integrated community-based case detection, referral, and confirmation. Finally, this study evaluates the efficacy of implementing the Optimal Model in improving the early diagnosis of NTDs. Methodology/Principal FindingsThe study used mixed methods, including key informant interviews, focus group discussions, participant observation, quantitative analysis, and reflexive sessions to evaluate the implementation of an Optimal Model developed through this study. The quantitative results from the testing of the optimal model are of limited utility. The annual number of cases detected increased in the twelve months of implementation in 2020 compared to 2019 (pre-intervention) but will require observation over a more extended period to be of significance. Qualitative data revealed essential factors that impact the effectiveness of integrated case detection. Data emphasized the gendered dynamics in communities that shape the case identification process, such as men and women preferring to see health workers of the same gender. Furthermore, the qualitative data showed an increase in knowledge of the transmission, signs, symptoms, and management options amongst CHW, which enabled them to dispel misconceptions and stigma associated with NTDs. Conclusion/SignificanceThis study demonstrates the opportunity for greater integration in training, case detection, rereferral, and confirmations. However, the effectiveness of this approach depends on a high level of collaboration, joint planning, and implementation embedded within existing health systems infrastructure. Together, these approaches improve access to health services for NTDs. Author SummaryGlobal health professionals and stakeholders have advocated for integration across diseases and sectors to improve the success of public health interventions. This advocacy has also impacted NTDs programs globally. NTDs interventions are becoming more integrated than disease-specific activities to maximize limited resources, improve coverage and access to healthcare services. However, documentation on the effectiveness of integrated approaches to improve access to healthcare services is minimal. This study evaluated existing case detection and referral approaches in Liberia, utilizing the findings to develop and test an Optimal Model for integrated community-based case detection, referral, and confirmation. Finally, this study evaluates the efficacy of implementing the Optimal Model in improving the early diagnosis of NTDs. The results provide evidence of the benefits of an integrated approach and the programmatic challenges to achieve the goal of improving access to health services for persons affected by NTDs.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- “We are their eyes and ears here on the ground, yet they do not appreciate us” - Factors influencing the performance of Kenyan community health volunteers working in urban informal settlements 97%
- Community-orientated primary health care: exploring the interface between community health worker programmes, the health system and communities in South Africa 97%
- Exploring variations in the implementation of a health system level policy intervention to improve maternal and child health outcomes in resource limited settings: A qualitative multiple case study from Uganda 97%
Similar papers in this journal
- COVID-19 self-testing in Nigeria: Stakeholders’ opinions and perspective on its value for case detection 97%
- Community health worker knowledge, attitudes and practices towards COVID-19: learnings from an online cross-sectional survey using a digital health platform, UpSCALE, in Mozambique 96%
- Health worker acceptability of an HIV testing mobile health application within a rural Zambian HIV treatment programme 96%
Similar papers in this journal
- Development and validation of a framework to improve neglected tropical diseases surveillance and response at the sub-national level in Kenya 97%
- Stakeholders Perspective of Integrating Female Genital Schistosomiasis into HIV Care: A Qualitative Study in Ghana 97%
- Assessing the knowledge, attitudes, practices, and perspectives of stakeholders of the deworming program in rural Rwanda 96%
Similar papers in this journal
- Understanding Knowledge, Attitudes and Practices on Ebola Virus Disease: A Multi-Site Mixed Methods Survey on Preparedness in Rwanda 96%
- Community Perceptions of Vaccination Among Influential Stakeholders: Qualitative Research in Rural India 95%
- Acceptability and feasibility of strategies to shield the vulnerable during the COVID-19 outbreak: a qualitative study in six Sudanese communities 94%
Similar papers in this journal
- The impact of the COVID-19 pandemic on health service utilisation in Sierra Leone 96%
- Private sector tuberculosis care quality during the COVID-19 pandemic: A repeated cross-sectional standardized patients study of adherence to national TB guidelines in urban Nigeria 95%
- Cholera in Internally Displaced Persons Camps in Borno State--Nigeria, 2017: A qualitative study of the multi-sectorial emergency response to stop the spread of the outbreak 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.