Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
PLoS Negl Trop Dis. 2021 May 13;15(5):e0009351. doi: 10.1371/journal.pntd.0009351. eCollection 2021 May.
Locally tailored interventions for neglected tropical diseases (NTDs) are becoming increasingly important for ensuring that the World Health Organization (WHO) goals for control and elimination are reached. Mathematical models, such as those developed by the NTD Modelling Consortium, are able to offer recommendations on interventions but remain constrained by the data currently available. Data collection for NTDs needs to be strengthened as better data are required to indirectly inform transmission in an area. Addressing specific data needs will improve our modelling recommendations, enabling more accurate tailoring of interventions and assessment of their progress. In this collection, we discuss the data needs for several NTDs, specifically gambiense human African trypanosomiasis, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminths (STH), trachoma, and visceral leishmaniasis. Similarities in the data needs for these NTDs highlight the potential for integration across these diseases and where possible, a wider spectrum of diseases.
针对被忽视的热带病（NTDs）的本地化干预措施对于确保世界卫生组织（WHO）控制和消除目标的实现变得越来越重要。数学模型，如 NTD 建模联盟开发的模型，能够提供干预措施的建议，但仍然受到当前可用数据的限制。需要加强 NTD 数据收集，因为需要更好的数据来间接了解一个地区的传播情况。解决具体的数据需求将改进我们的建模建议，使干预措施的定制更加准确，并评估其进展。在本集中，我们讨论了几种 NTD 的数据需求，特别是冈比亚人体锥虫病、淋巴丝虫病、盘尾丝虫病、血吸虫病、土壤传播性蠕虫（STH）、沙眼和内脏利什曼病。这些 NTD 的数据需求的相似之处突出了这些疾病之间潜在的整合，以及在可能的情况下，更广泛的疾病范围。
