Reactive case detection can improve the efficiency of lymphatic filariasis surveillance compared to random sampling, Samoa 2023
Helen J. Mayfield, Benn Sartorius, Angus McLure, Stephanie J. Curtis, Beatris Mario Martin, Sarah Sheridan, Robert Thomsen, Rossana Tofaeono-Pifeleti, Satupaitea Viali, Patricia M. Graves, Colleen L. Lau

TL;DR
A targeted sampling method found more lymphatic filariasis cases than random sampling in Samoa, especially in areas with medium infection rates.
Contribution
Demonstrates that reactive case detection is more efficient than random sampling for LF surveillance in medium prevalence settings.
Findings
Targeted sampling identified more Ag- and Mf-positive individuals than random sampling.
Efficiency gains were highest in medium Ag prevalence villages.
Reactive case detection improved resource allocation for LF surveillance in Samoa.
Abstract
In Samoa, lymphatic filariasis (LF) remains endemic despite persistent elimination efforts. Targeted sampling based on locations of known infections could be an efficient strategy for locating infected individuals and residual infections to support these efforts. This cross-sectional study assesses the efficiency of reactive case detection versus random sampling for identifying LF antigen (Ag)- and microfilaria (Mf)-positive individuals in Samoa in varying Ag prevalence scenarios. In 2023, six primary sampling units (PSUs) were surveyed using random and targeted sampling strategies. PSUs were selected based on Ag prevalence in 2019; two PSUs each with low (3–5%), medium (6–7%) and high (13–17%) Ag prevalence. The randomly selected group included residents aged ≥5 years in 15 houses per PSU. The targeted group included residents aged ≥5 years in up to eight households within 200 metres…
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Taxonomy
TopicsParasitic Diseases Research and Treatment · Parasite Biology and Host Interactions · Mosquito-borne diseases and control
