Optimising passive surveillance of a neglected tropical disease in the era of elimination: A modelling study.

Joshua Longbottom,Paul R Bessell,Steve J Torr,Charles Wamboga,Michelle C Stanton,Colleen L Lau

doi:10.1371/journal.pntd.0008599

Joshua Longbottom, Paul R Bessell + Show 4 more

Open Access

https://doi.org/10.1371/journal.pntd.0008599

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Abstract

BackgroundSurveillance is an essential component of global programs to eliminate infectious diseases and avert epidemics of (re-)emerging diseases. As the numbers of cases decline, costs of treatment and control diminish but those for surveillance remain high even after the ‘last’ case. Reducing surveillance may risk missing persistent or (re-)emerging foci of disease. Here, we use a simulation-based approach to determine the minimal number of passive surveillance sites required to ensure maximum coverage of a population at-risk (PAR) of an infectious disease.Methodology and principal findingsFor this study, we use Gambian human African trypanosomiasis (g-HAT) in north-western Uganda, a neglected tropical disease (NTD) which has been reduced to historically low levels (<1000 cases/year globally), as an example. To quantify travel time to diagnostic facilities, a proxy for surveillance coverage, we produced a high spatial-resolution resistance surface and performed cost-distance analyses. We simulated travel time for the PAR with different numbers (1–170) and locations (170,000 total placement combinations) of diagnostic facilities, quantifying the percentage of the PAR within 1h and 5h travel of the facilities, as per in-country targets. Our simulations indicate that a 70% reduction (51/170) in diagnostic centres still exceeded minimal targets of coverage even for remote populations, with >95% of a total PAR of ~3million individuals living ≤1h from a diagnostic centre, and we demonstrate an approach to best place these facilities, informing a minimal impact scale back.ConclusionsOur results highlight that surveillance of g-HAT in north-western Uganda can be scaled back without substantially reducing coverage of the PAR. The methodology described can contribute to cost-effective and equable strategies for the surveillance of NTDs and other infectious diseases approaching elimination or (re-)emergence.

Highlights

Quantifying the spatial and temporal distribution of cases is essential for the development, implementation and monitoring of programmes to control or eliminate infectious diseases [1,2,3]
Our simulations indicate that a 70% reduction (51/170) in diagnostic centres still exceeded minimal targets of coverage even for remote populations, with >95% of a total population at-risk (PAR) of ~3million individuals living 1h from a diagnostic centre, and we demonstrate an approach to best place these facilities, informing a minimal impact scale back
Our results highlight that surveillance of Gambian human African trypanosomiasis (g-HAT) in north-western Uganda can be scaled back without substantially reducing coverage of the PAR

Summary

Introduction

Quantifying the spatial and temporal distribution of cases is essential for the development, implementation and monitoring of programmes to control or eliminate infectious diseases [1,2,3]. Costs for treatment and control of a disease scale with the number of cases, but those for surveillance can be high even when disease incidence is low [4]. Programmes aiming to eliminate or eradicate a disease maintain high levels of surveillance, as illustrated by the global programmes against smallpox and polio [5,6]. Maintaining adequate surveillance for diseases approaching elimination or with potential for emergence can be prohibitively costly for national health systems, for resource-poor countries in the tropics [8,9], and as such, approaches for cost-effective surveillance are required. We use a simulation-based approach to determine the minimal number of passive surveillance sites required to ensure maximum coverage of a population at-risk (PAR) of an infectious disease

Methods

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Conclusion