The lymphatic filariasis treatment study landscape: A systematic review of study characteristics and the case for an individual participant data platform

16 Jan 2024
Luzia T. Freitas, Mashroor Ahmad Khan, Azhar Uddin, Julia B. Halder, Sauman Singh-Phulgenda, Jeyapal Dinesh Raja, Vijayakumar Balakrishnan, Eli Harriss, Manju Rahi, Matthew Brack, Philippe J. Guérin, Maria-Gloria Basáñez, Ashwani Kumar, Martin Walker, Adi



Lymphatic filariasis (LF) is a neglected tropical disease (NTD) targeted by the World Health Organization for elimination as a public health problem (EPHP). Since 2000, more than 9 billion treatments of antifilarial medicines have been distributed through mass drug administration (MDA) programmes in 72 endemic countries and 17 countries have reached EPHP. Yet in 2021, nearly 900 million people still required MDA with combinations of albendazole, diethylcarbamazine and/or ivermectin. Despite the reliance on these drugs, there remain gaps in understanding of variation in responses to treatment. As demonstrated for other infectious diseases, some urgent questions could be addressed by conducting individual participant data (IPD) meta-analyses. Here, we present the results of a systematic literature review to estimate the abundance of IPD on pre- and post-intervention indicators of infection and/or morbidity and assess the feasibility of building a global data repository.


We searched literature published between 1st January 2000 and 5th May 2023 in 15 databases to identify prospective studies assessing LF treatment and/or morbidity management and disease prevention (MMDP) approaches. We considered only studies where individual participants were diagnosed with LF infection or disease and were followed up on at least one occasion after receiving an intervention/treatment.

Principle findings

We identified 138 eligible studies from 23 countries, having followed up an estimated 29,842 participants after intervention. We estimate 14,800 (49.6%) IPD on pre- and post-intervention infection indicators including microfilaraemia, circulating filarial antigen and/or ultrasound indicators measured before and after intervention using 8 drugs administered in various combinations. We identified 33 studies on MMDP, estimating 6,102 (20.4%) IPD on pre- and post-intervention clinical morbidity indicators only. A further 8,940 IPD cover a mixture of infection and morbidity outcomes measured with other diagnostics, from participants followed for adverse event outcomes only or recruited after initial intervention.


The LF treatment study landscape is heterogeneous, but the abundance of studies and related IPD suggest that establishing a global data repository to facilitate IPD meta-analyses would be feasible and useful to address unresolved questions on variation in treatment outcomes across geographies, demographics and in underrepresented groups. New studies using more standardized approaches should be initiated to address the scarcity and inconsistency of data on morbidity management.

Author summary

Lymphatic filariasis (LF) is a debilitating parasitic disease that the World Health Organization (WHO) has earmarked for elimination by 2030 through a combination of mass distribution of anti-parasitic medicines and disease management approaches. Great strides have been made towards the elimination of LF as a public health problem, but nearly 900 million people still require treatment every year. In recent years, new combinations of medicines have been shown to improve the treatment of LF, yet there remain substantial gaps in understanding of apparent variability in treatment success and on the best treatment and management approaches to alleviate chronic morbidity. Some of these questions could be addressed through the development of a LF global data platform, which would enable pooled analyses of all available individual participant data. Here, we present the results of a systematic literature review of the LF treatment study landscape. We estimate the abundance of individual data on treatment of infection and morbidity and describe the characteristics of the studies and participants that have generated these data. We argue that collating and curating these data into a data LF platform could help to fill gaps in understanding of the best ways to treat infection and disease and enhance prospects of eliminating LF by 2030.