Department of Biology, University of Oxford, Oxford OX1 3SZ, UK.
Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.
Philos Trans R Soc Lond B Biol Sci. 2023 Oct 9;378(1887):20220279. doi: 10.1098/rstb.2022.0279. Epub 2023 Aug 21.
Reducing the morbidities caused by neglected tropical diseases (NTDs) is a central aim of ongoing disease control programmes. The broad spectrum of pathogens under the umbrella of NTDs lead to a range of negative health outcomes, from malnutrition and anaemia to organ failure, blindness and carcinogenesis. For some NTDs, the most severe clinical manifestations develop over many years of chronic or repeated infection. For these diseases, the association between infection and risk of long-term pathology is generally complex, and the impact of multiple interacting factors, such as age, co-morbidities and host immune response, is often poorly quantified. Mathematical modelling has been used for many years to gain insights into the complex processes underlying the transmission dynamics of infectious diseases; however, long-term morbidities associated with chronic or cumulative exposure are generally not incorporated into dynamic models for NTDs. Here we consider the complexities and challenges for determining the relationship between cumulative pathogen exposure and morbidity at the individual and population levels, drawing on case studies for trachoma, schistosomiasis and foodborne trematodiasis. We explore potential frameworks for explicitly incorporating long-term morbidity into NTD transmission models, and consider the insights such frameworks may bring in terms of policy-relevant projections for the elimination era. This article is part of the theme issue 'Challenges and opportunities in the fight against neglected tropical diseases: a decade from the London Declaration on NTDs'.
降低被忽视的热带病(NTDs)引起的发病率是正在进行的疾病控制计划的主要目标。NTDs 所涵盖的病原体范围广泛,导致一系列负面健康后果,从营养不良和贫血到器官衰竭、失明和癌变。对于一些 NTDs,最严重的临床表现是在多年的慢性或反复感染后发展而来。对于这些疾病,感染与长期病理学风险之间的关联通常很复杂,并且多个相互作用因素(如年龄、合并症和宿主免疫反应)的影响往往难以量化。数学建模多年来一直被用于深入了解传染病传播动态背后的复杂过程;然而,与慢性或累积暴露相关的长期发病率通常未被纳入 NTD 的动态模型中。在这里,我们考虑了在个体和人群层面确定累积病原体暴露与发病率之间关系的复杂性和挑战,借鉴了沙眼、血吸虫病和食源性吸虫病的案例研究。我们探讨了将长期发病率明确纳入 NTD 传播模型的潜在框架,并考虑了这些框架在消除时代的政策相关预测方面可能带来的见解。本文是“被忽视的热带病防治的挑战与机遇:距离伦敦 NTD 宣言十年”主题特刊的一部分。