Combining different diagnostic studies of lymphatic filariasis for risk mapping in Papua New Guinea: A predictive model from microfilaraemia and antigenaemia prevalence surveys Peter Wood

被引：5

作者：

Berg Soto A. ^{[1
]}

Xu Z. ^{[2
]}

Wood P. ^{[3
]}

Sanuku N. ^{[4
]}

Robinson L.J. ^{[4
,5
]}

King C.L. ^{[6
]}

Tisch D. ^{[7
]}

Susapu M. ^{[8
]}

Graves P.M. ^{[3
]}

机构：

[1] Information Resources, James Cook University, Townsville, 4811, QLD

[2] Research School of Population Health, Australian National University, Canberra, 2601, ACT

[3] College of Public Health, Medical and Veterinary Sciences, James Cook University, Cairns, 4870, QLD

[4] Vector Borne Diseases Unit, PNG Institute of Medical Research, Goroka

[5] Disease Elimination Program, Burnet Institute, Melbourne, 3004, VIC

[6] School of Medicine and Veterans Affairs Administration, Case Western Reserve University, Cleveland, 44106, OH

[7] Department of Population and Quantitative Health Science, Case Western Reserve University, Cleveland, 44106, OH

[8] Malaria and Vector Borne Diseases, Public Health, Department of Health, Port Moresby

来源：

Tropical Medicine and Health | / 46卷 / 1期

基金：

美国国家卫生研究院;

关键词：

Diagnostic tests; Lymphatic filariasis; Papua New Guinea; Predictive model; Prevalence; Risk map;

D O I：

10.1186/s41182-018-0123-8

中图分类号：

学科分类号：

摘要：

Background: The Global Programme to Eliminate Lymphatic Filariasis has encouraged countries to follow a set of guidelines to help them assess the need for mass drug administration and evaluate its progress. Papua New Guinea (PNG) is one of the highest priority countries in the Western Pacific for lymphatic filariasis and the site of extensive research on lymphatic filariasis and surveys of its prevalence. However, different diagnostic tests have been used and thresholds for each test are unclear. Methods: We reviewed the prevalence of lymphatic filariasis reported in 295 surveys conducted in PNG between 1990 and 2014, of which 65 used more than one test. Results from different diagnostics were standardised using a set of criteria that included a model to predict antigen prevalence from microfilariae prevalence. We mapped the point location of each of these surveys and categorised their standardised prevalence estimates. Results: Several predictive models were produced and investigated, including the effect of any mass drug administration and number of rounds prior to the surveys. One model was chosen based on goodness of fit parameters and used to predict antigen prevalence for surveys that tested only for microfilariae. Standardised prevalence values show that 72% of all surveys reported a prevalence above 0.05. High prevalence was situated on the coastal north, south and island regions, while the central highland area of Papua New Guinea shows low levels of prevalence. Conclusions: Our study is the first to provide an explicit predictive relationship between the prevalence values based on empirical results from antigen and microfilaria tests, taking into account the occurrence of mass drug administration. This is a crucial step to combine studies to develop risk maps of lymphatic filariasis for programme planning and evaluation, as shown in the case of Papua New Guinea. © 2018 The Author(s).

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