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Review
. 2021 Jun 14;72(Suppl 3):S152-S157.
doi: 10.1093/cid/ciab191.

Modelling the Impact of Vector Control on Lymphatic Filariasis Programs: Current Approaches and Limitations

E L Davis  1 , J Prada  2 , L J Reimer  3 , T D Hollingsworth  1
Affiliations
Review

Modelling the Impact of Vector Control on Lymphatic Filariasis Programs: Current Approaches and Limitations

E L Davis et al. Clin Infect Dis. .

Abstract

Vector control is widely considered an important tool for lymphatic filariasis (LF) elimination but is not usually included in program budgets and has often been secondary to other policy questions in modelling studies. Evidence from the field demonstrates that vector control can have a large impact on program outcomes and even halt transmission entirely, but implementation is expensive. Models of LF have the potential to inform where and when resources should be focused, but often simplify vector dynamics and focus on capturing human prevalence trends, making them comparatively ill-designed for direct analysis of vector control measures. We review the recent modelling literature and present additional results using a well-established model, highlighting areas of agreement between model predictions and field evidence, and discussing the possible determinants of existing disagreements. We conclude that there are likely to be long-term benefits of vector control, both on accelerating programs and preventing resurgence.

Keywords: elimination; lymphatic filariasis; modelling; resurgence; vector control.

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Figures

Figure 1.
Figure 1.
Modelled impact of vector control on MDA rounds to EPHP. The number of rounds of MDA (65% IA, Anopheles settings) required to reach EPHP (1% mf prevalence) from a baseline prevalence of 9%–11% (aggregation k from 0.01 to 0.1 and ABR from 0 to 1200). MDA only (red) and MDA with 50% vector control coverage (orange) and a range of assumptions around systematic nonadherence: (A) No systematic nonadherence; (B) moderate systematic nonadherence (correlation 0.35); (C) high systematic nonadherence (correlation 0.7).
Figure 2.
Figure 2.
Modelled impact of vector control on elimination and resurgence trajectories. Mean mf prevalence for scenarios with 65% coverage of IA and 50% coverage vector control during MDA (Anopheles settings, 9%–11% baseline mf prevalence) that reach EPHP in 10 rounds. Following MDA cessation, 3 scenarios are considered: waning vector control efficacy due to poor or no maintenance (red, solid); vector control maintained consistently at 50% coverage (orange, dashed); enhanced 80% coverage vector control (green, dotted).
Figure 3.
Figure 3.
Modelled impact of vector control on probabilities of elimination and resurgence. Probability of resurgence (left), low-level maintenance (center), and true elimination (right) following EPHP validation and MDA cessation for Anopheles settings with a 9%–11% baseline prevalence. Following MDA cessation, 3 scenarios are considered: waning vector control efficacy due to poor or no maintenance (red, left); vector control maintained consistently at 50% coverage (orange, center); enhanced 80% coverage vector control (green, right).
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