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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">An investigation of the disparity in estimates of microfilaraemia and antigenaemia in lymphatic filariasis surveys</title>
<author><name sortKey="Cano, Jorge" sort="Cano, Jorge" uniqKey="Cano J" first="Jorge" last="Cano">Jorge Cano</name>
<affiliation><nlm:aff id="af1"><addr-line>Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Moraga, Paula" sort="Moraga, Paula" uniqKey="Moraga P" first="Paula" last="Moraga">Paula Moraga</name>
<affiliation><nlm:aff id="af1"><addr-line>Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Nikolay, Birgit" sort="Nikolay, Birgit" uniqKey="Nikolay B" first="Birgit" last="Nikolay">Birgit Nikolay</name>
<affiliation><nlm:aff id="af1"><addr-line>Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Rebollo, Maria P" sort="Rebollo, Maria P" uniqKey="Rebollo M" first="Maria P." last="Rebollo">Maria P. Rebollo</name>
<affiliation><nlm:aff id="af2"><addr-line>NTD Support Center, Task Force for Global Health, Decatur, Atlanta, USA</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Okorie, Patricia N" sort="Okorie, Patricia N" uniqKey="Okorie P" first="Patricia N." last="Okorie">Patricia N. Okorie</name>
<affiliation><nlm:aff id="af3"><addr-line>Institute for Advanced Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Nigeria</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Davies, Emmanuel" sort="Davies, Emmanuel" uniqKey="Davies E" first="Emmanuel" last="Davies">Emmanuel Davies</name>
<affiliation><nlm:aff id="af4"><addr-line>Ministry of Health, Nigeria</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Njenga, Sammy M" sort="Njenga, Sammy M" uniqKey="Njenga S" first="Sammy M." last="Njenga">Sammy M. Njenga</name>
<affiliation><nlm:aff id="af5"><addr-line>Eastern and Southern Africa Centre of International Parasite Control, Kenya Medical Research Institute (KEMRI), Nairobi, Kenya</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Bockarie, Moses J" sort="Bockarie, Moses J" uniqKey="Bockarie M" first="Moses J." last="Bockarie">Moses J. Bockarie</name>
<affiliation><nlm:aff id="af6"><addr-line>Centre for Neglected Tropical Diseases, Liverpool School of Tropical Medicine, Liverpool, UK</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Brooker, Simon J" sort="Brooker, Simon J" uniqKey="Brooker S" first="Simon J." last="Brooker">Simon J. Brooker</name>
<affiliation><nlm:aff id="af1"><addr-line>Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK</addr-line>
</nlm:aff>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">PMC</idno>
<idno type="pmid">26101292</idno>
<idno type="pmc">4542699</idno>
<idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4542699</idno>
<idno type="RBID">PMC:4542699</idno>
<idno type="doi">10.1093/trstmh/trv048</idno>
<date when="2015">2015</date>
<idno type="wicri:Area/Pmc/Corpus">000139</idno>
<idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000139</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">An investigation of the disparity in estimates of microfilaraemia and antigenaemia in lymphatic filariasis surveys</title>
<author><name sortKey="Cano, Jorge" sort="Cano, Jorge" uniqKey="Cano J" first="Jorge" last="Cano">Jorge Cano</name>
<affiliation><nlm:aff id="af1"><addr-line>Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Moraga, Paula" sort="Moraga, Paula" uniqKey="Moraga P" first="Paula" last="Moraga">Paula Moraga</name>
<affiliation><nlm:aff id="af1"><addr-line>Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Nikolay, Birgit" sort="Nikolay, Birgit" uniqKey="Nikolay B" first="Birgit" last="Nikolay">Birgit Nikolay</name>
<affiliation><nlm:aff id="af1"><addr-line>Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Rebollo, Maria P" sort="Rebollo, Maria P" uniqKey="Rebollo M" first="Maria P." last="Rebollo">Maria P. Rebollo</name>
<affiliation><nlm:aff id="af2"><addr-line>NTD Support Center, Task Force for Global Health, Decatur, Atlanta, USA</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Okorie, Patricia N" sort="Okorie, Patricia N" uniqKey="Okorie P" first="Patricia N." last="Okorie">Patricia N. Okorie</name>
<affiliation><nlm:aff id="af3"><addr-line>Institute for Advanced Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Nigeria</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Davies, Emmanuel" sort="Davies, Emmanuel" uniqKey="Davies E" first="Emmanuel" last="Davies">Emmanuel Davies</name>
<affiliation><nlm:aff id="af4"><addr-line>Ministry of Health, Nigeria</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Njenga, Sammy M" sort="Njenga, Sammy M" uniqKey="Njenga S" first="Sammy M." last="Njenga">Sammy M. Njenga</name>
<affiliation><nlm:aff id="af5"><addr-line>Eastern and Southern Africa Centre of International Parasite Control, Kenya Medical Research Institute (KEMRI), Nairobi, Kenya</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Bockarie, Moses J" sort="Bockarie, Moses J" uniqKey="Bockarie M" first="Moses J." last="Bockarie">Moses J. Bockarie</name>
<affiliation><nlm:aff id="af6"><addr-line>Centre for Neglected Tropical Diseases, Liverpool School of Tropical Medicine, Liverpool, UK</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Brooker, Simon J" sort="Brooker, Simon J" uniqKey="Brooker S" first="Simon J." last="Brooker">Simon J. Brooker</name>
<affiliation><nlm:aff id="af1"><addr-line>Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK</addr-line>
</nlm:aff>
</affiliation>
</author>
</analytic>
<series><title level="j">Transactions of the Royal Society of Tropical Medicine and Hygiene</title>
<idno type="ISSN">0035-9203</idno>
<idno type="eISSN">1878-3503</idno>
<imprint><date when="2015">2015</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass></textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p>The diagnosis of lymphatic filariasis (LF) is based typically on either microfilaraemia as assessed by microscopy or filarial antigenaemia using an immuno-chromatographic test. While it is known that estimates of antigenaemia are generally higher than estimates of microfilaraemia, the extent of the difference is not known.</p>
</sec>
<sec><title>Methods</title>
<p>This paper presents the results of an extensive literature search for surveys that estimated both microfilaraemia and antigenaemia in order to better understand the disparity between the two measures.</p>
</sec>
<sec><title>Results and Conclusions</title>
<p>In some settings there was a very large disparity, up to 40–70%, between estimates of microfilaraemia and antigenaemia. Regression analysis was unable to identify any predictable relationship between the two measures. The implications of findings for risk mapping and surveillance of LF are discussed.</p>
</sec>
</div>
</front>
<back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Rebollo, Mp" uniqKey="Rebollo M">MP Rebollo</name>
</author>
<author><name sortKey="Bockarie, Mj" uniqKey="Bockarie M">MJ Bockarie</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Rebollo, Mp" uniqKey="Rebollo M">MP Rebollo</name>
</author>
<author><name sortKey="Bockarie, Mj" uniqKey="Bockarie M">MJ Bockarie</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Weil, Gj" uniqKey="Weil G">GJ Weil</name>
</author>
<author><name sortKey="Lammie, Pj" uniqKey="Lammie P">PJ Lammie</name>
</author>
<author><name sortKey="Weiss, N" uniqKey="Weiss N">N Weiss</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Weil, Gj" uniqKey="Weil G">GJ Weil</name>
</author>
<author><name sortKey="Ramzy, Rm" uniqKey="Ramzy R">RM Ramzy</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Cano, J" uniqKey="Cano J">J Cano</name>
</author>
<author><name sortKey="Rebollo, Mp" uniqKey="Rebollo M">MP Rebollo</name>
</author>
<author><name sortKey="Golding, N" uniqKey="Golding N">N Golding</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Witt, C" uniqKey="Witt C">C Witt</name>
</author>
<author><name sortKey="Ottesen, Ea" uniqKey="Ottesen E">EA Ottesen</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Dreyer, G" uniqKey="Dreyer G">G Dreyer</name>
</author>
<author><name sortKey="Noroes, J" uniqKey="Noroes J">J Noroes</name>
</author>
<author><name sortKey="Amaral, F" uniqKey="Amaral F">F Amaral</name>
</author>
</analytic>
</biblStruct>
</listBibl>
</div1>
</back>
</TEI>
<pmc article-type="brief-report"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Trans R Soc Trop Med Hyg</journal-id>
<journal-id journal-id-type="iso-abbrev">Trans. R. Soc. Trop. Med. Hyg</journal-id>
<journal-id journal-id-type="publisher-id">trstmh</journal-id>
<journal-id journal-id-type="hwp">trstmh</journal-id>
<journal-title-group><journal-title>Transactions of the Royal Society of Tropical Medicine and Hygiene</journal-title>
</journal-title-group>
<issn pub-type="ppub">0035-9203</issn>
<issn pub-type="epub">1878-3503</issn>
<publisher><publisher-name>Oxford University Press</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">26101292</article-id>
<article-id pub-id-type="pmc">4542699</article-id>
<article-id pub-id-type="doi">10.1093/trstmh/trv048</article-id>
<article-id pub-id-type="publisher-id">trv048</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Short Communications</subject>
</subj-group>
</article-categories>
<title-group><article-title>An investigation of the disparity in estimates of microfilaraemia and antigenaemia in lymphatic filariasis surveys</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Cano</surname>
<given-names>Jorge</given-names>
</name>
<xref ref-type="aff" rid="af1">a</xref>
<xref ref-type="corresp" rid="cor1">*</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Moraga</surname>
<given-names>Paula</given-names>
</name>
<xref ref-type="aff" rid="af1">a</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Nikolay</surname>
<given-names>Birgit</given-names>
</name>
<xref ref-type="aff" rid="af1">a</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Rebollo</surname>
<given-names>Maria P.</given-names>
</name>
<xref ref-type="aff" rid="af2">b</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Okorie</surname>
<given-names>Patricia N.</given-names>
</name>
<xref ref-type="aff" rid="af3">c</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Davies</surname>
<given-names>Emmanuel</given-names>
</name>
<xref ref-type="aff" rid="af4">d</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Njenga</surname>
<given-names>Sammy M.</given-names>
</name>
<xref ref-type="aff" rid="af5">e</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Bockarie</surname>
<given-names>Moses J.</given-names>
</name>
<xref ref-type="aff" rid="af6">f</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Brooker</surname>
<given-names>Simon J.</given-names>
</name>
<xref ref-type="aff" rid="af1">a</xref>
</contrib>
<aff id="af1"><label>a</label>
<addr-line>Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK</addr-line>
</aff>
<aff id="af2"><label>b</label>
<addr-line>NTD Support Center, Task Force for Global Health, Decatur, Atlanta, USA</addr-line>
</aff>
<aff id="af3"><label>c</label>
<addr-line>Institute for Advanced Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Nigeria</addr-line>
</aff>
<aff id="af4"><label>d</label>
<addr-line>Ministry of Health, Nigeria</addr-line>
</aff>
<aff id="af5"><label>e</label>
<addr-line>Eastern and Southern Africa Centre of International Parasite Control, Kenya Medical Research Institute (KEMRI), Nairobi, Kenya</addr-line>
</aff>
<aff id="af6"><label>f</label>
<addr-line>Centre for Neglected Tropical Diseases, Liverpool School of Tropical Medicine, Liverpool, UK</addr-line>
</aff>
</contrib-group>
<author-notes><corresp id="cor1"><label>*</label>
Corresponding author: Tel: +44 (0) 207927 2584; E-mail: <email>jcano.ortega@lshtm.ac.uk</email>
</corresp>
</author-notes>
<pub-date pub-type="ppub"><month>8</month>
<year>2015</year>
</pub-date>
<pub-date pub-type="epub"><day>21</day>
<month>6</month>
<year>2015</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>21</day>
<month>6</month>
<year>2015</year>
</pub-date>
<pmc-comment> PMC Release delay is 0 months and 0 days and was based on the
. </pmc-comment>
<volume>109</volume>
<issue>8</issue>
<fpage>529</fpage>
<lpage>531</lpage>
<history><date date-type="received"><day>12</day>
<month>5</month>
<year>2015</year>
</date>
<date date-type="rev-recd"><day>5</day>
<month>6</month>
<year>2015</year>
</date>
<date date-type="accepted"><day>5</day>
<month>6</month>
<year>2015</year>
</date>
</history>
<permissions><copyright-statement>© The Author 2015. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.</copyright-statement>
<copyright-year>2015</copyright-year>
<license license-type="creative-commons" xlink:href="http://creativecommons.org/licenses/by/4.0/"><license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>
), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
</license>
</permissions>
<self-uri content-type="pdf" xlink:href="trv048.pdf"></self-uri>
<abstract><sec><title>Background</title>
<p>The diagnosis of lymphatic filariasis (LF) is based typically on either microfilaraemia as assessed by microscopy or filarial antigenaemia using an immuno-chromatographic test. While it is known that estimates of antigenaemia are generally higher than estimates of microfilaraemia, the extent of the difference is not known.</p>
</sec>
<sec><title>Methods</title>
<p>This paper presents the results of an extensive literature search for surveys that estimated both microfilaraemia and antigenaemia in order to better understand the disparity between the two measures.</p>
</sec>
<sec><title>Results and Conclusions</title>
<p>In some settings there was a very large disparity, up to 40–70%, between estimates of microfilaraemia and antigenaemia. Regression analysis was unable to identify any predictable relationship between the two measures. The implications of findings for risk mapping and surveillance of LF are discussed.</p>
</sec>
</abstract>
<kwd-group><kwd>Antigenaemia</kwd>
<kwd>Logistic regression</kwd>
<kwd>Lymphatic filariasis</kwd>
<kwd>Microfilaraemia</kwd>
<kwd>Prevalence surveys</kwd>
</kwd-group>
<funding-group><award-group id="funding-1"><funding-source>Wellcome Trust <named-content content-type="funder-id">http://dx.doi.org/10.13039/100004440</named-content>
</funding-source>
</award-group>
</funding-group>
</article-meta>
</front>
<body><sec sec-type="intro" id="s1"><title>Introduction</title>
<p>The control and elimination of lymphatic filariasis (LF), a disfiguring and disabling mosquito-borne disease,<sup><xref rid="TRV048C1" ref-type="bibr">1</xref>
</sup>
necessitates a detailed understanding of the geographical distribution of infection. Mapping of LF has been completed in nearly all endemic countries and many countries are now undertaking transmission assessment surveys (TAS) in order to determine whether mass drug administration (MDA) can be stopped. Reliable diagnosis is an essential prerequisite for mapping, TAS and post-MDA surveillance. In the past, diagnosis was principally based on the use of blood films collected during night blood surveys to detect the presence of microfilariae (mf) by expert microscopy.<sup><xref rid="TRV048C2" ref-type="bibr">2</xref>
</sup>
The development, in the 1990s, of a simple and rapid antigen detection test for <italic>Wuchereria bancrofti</italic>
antigenaemia, based on the immuno-chromatographic test (ICT), revolutionized LF surveys since it avoided the need for night blood surveys and time-consuming microscopy.<sup><xref rid="TRV048C3" ref-type="bibr">3</xref>
</sup>
It is well-known that estimates of antigenaemia are typically higher than estimates of microfilariae for a number of biological and practical reasons, including the fact that antifilarial drugs are highly effective against microfilariae but have minimal effect on adult worms.<sup><xref rid="TRV048C4" ref-type="bibr">4</xref>
</sup>
What is less clear is the extent of the disparity in estimates and whether prevalence of antigenaemia can be used to predict the mf prevalence, and vice versa. To investigate these issues, we analyzed the relationship between prevalence of LF based on antigenaemia using ICT and microfilaraemia using microscopy. The implications for risk mapping and surveillance of LF are discussed.</p>
</sec>
<sec sec-type="methods" id="s2"><title>Materials and methods</title>
<p>An exhaustive literature search was made to identify prevalence surveys where microfilaraemia and antigenaemia were assessed among the study population. The search included surveys according to previously defined inclusion and exclusion criteria.<sup><xref rid="TRV048C5" ref-type="bibr">5</xref>
</sup>
Studies were stratified based on whether they were conducted before the initiation of large-scale MDA (pre-intervention) or once MDA had been initiated, as part of monitoring activities (post-intervention). Studies were additionally stratified by continent in order to capture differences in mosquito species distribution and socio-economic conditions, type of ICT test (i.e., AMRAD vs Binax), and type of blood collected (venous blood vs peripheral blood). We assumed that Binax ICT was used in surveys conducted from 2001 when the type of ICT card test was not provided (n=74 surveys). In all identified surveys, mf diagnosis was based on night blood sampling. The relationship between the prevalence of microfilaraemia (p<sub>mf</sub>
) and antigenaemia (p<sub>ICT</sub>
) was fitted with logistic regression as follows:
<disp-formula><tex-math id="M1">\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{upgreek}
\usepackage{mathrsfs}
\setlength{\oddsidemargin}{-69pt}
\begin{document}
}{}$$\hbox{for each survey}\,i = 1, \ldots ,N,$$\end{document}</tex-math>
</disp-formula>
<disp-formula><tex-math id="M2">\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{upgreek}
\usepackage{mathrsfs}
\setlength{\oddsidemargin}{-69pt}
\begin{document}
}{}$${Y_{m{f_i}}}|{p_{m{f_i}}} \sim Binomial\; ({{N_{m{f_i}}},{p_{m{f_i}}}} )$$\end{document}</tex-math>
</disp-formula>
<disp-formula><tex-math id="M3">\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{upgreek}
\usepackage{mathrsfs}
\setlength{\oddsidemargin}{-69pt}
\begin{document}
}{}$$\eqalign{ \hbox{logit} ({p_{Mf_{i}}}{\rm )} = & \; \alpha + {\alpha _1}\hbox{logit}\, ( {p_{IC{T_i}}}) + {\alpha _2}\hbox{logit}\,{ ( {p_{IC{T_i}}} ) ^2} + {\alpha _{{PRE}}} \times PR{E_i} \cr & + {\alpha _{1PRE}}\hbox{logit}\, ({p_{IC{T_i}}}) \times PR{E_i} + {\alpha _{2PRE}}\hbox{logit}\,({p_{IC{T_i}}}) ^2 \times PR{E_i} \cr & + {\alpha _{AMERICAS}} \times AMERICA{S_i} + {\alpha _{ASIA}} \times ASI{A_i} \cr & + {\alpha _{OCEANIA}} \times OCEANI{A_i} + {\alpha _{TYPECIT\_}} \times TYPECI{T_i} \cr & + {\alpha _{VENOUSBLOOD\_}} \times VENOUSBLOO{D_i},} $$\end{document}</tex-math>
</disp-formula>
where <inline-formula><tex-math id="M4">\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{upgreek}
\usepackage{mathrsfs}
\setlength{\oddsidemargin}{-69pt}
\begin{document}
}{}${Y_{m{\,f_i}}}$\end{document}</tex-math>
</inline-formula>
and <inline-formula><tex-math id="M5">\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{upgreek}
\usepackage{mathrsfs}
\setlength{\oddsidemargin}{-69pt}
\begin{document}
}{}${N_{m{\,f_i}}}$\end{document}</tex-math>
</inline-formula>
denote the number of positive individuals and the total number of individuals tested by parasitological techniques (either the thick smear or filtration method), respectively. <inline-formula><tex-math id="M6">\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{upgreek}
\usepackage{mathrsfs}
\setlength{\oddsidemargin}{-69pt}
\begin{document}
}{}${\,p_{IC{T_i}}}$\end{document}</tex-math>
</inline-formula>
is the prevalence estimated using the ICT and <inline-formula><tex-math id="M7">\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{upgreek}
\usepackage{mathrsfs}
\setlength{\oddsidemargin}{-69pt}
\begin{document}
}{}$PR{E_i}\; $\end{document}</tex-math>
</inline-formula>
is a binary variable that is equal to 1 if the observation corresponds to a survey conducted in pre-control settings and 0 to post-control settings. <inline-formula><tex-math id="M8">\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{upgreek}
\usepackage{mathrsfs}
\setlength{\oddsidemargin}{-69pt}
\begin{document}
}{}$AMERICA{S_i}$\end{document}</tex-math>
</inline-formula>
, <inline-formula><tex-math id="M9">\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{upgreek}
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\setlength{\oddsidemargin}{-69pt}
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}{}$ASI{A_i}$\end{document}</tex-math>
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and <inline-formula><tex-math id="M10">\documentclass[12pt]{minimal}
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}{}$OCEANI{A_i}$\end{document}</tex-math>
</inline-formula>
e binary variables that are equal to 1 if the observation corresponds to the Americas, Asia or Southwest Pacific regions, respectively and 0 otherwise. <inline-formula><tex-math id="M11">\documentclass[12pt]{minimal}
\usepackage{amsmath}
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}{}$VENOUSBLOO{D_i}$\end{document}</tex-math>
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is equal to 1 if the blood sample was collected on venous blood (n=41) and 0 if collected on peripheral (i.e., finger prick) blood (n=215). Variation in the type of ICT used in surveys was captured through the covariate<inline-formula><tex-math id="M12">\documentclass[12pt]{minimal}
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}{}$\; TYPEIC{T_i}$\end{document}</tex-math>
</inline-formula>
, which is 1 for AMRAD ICT-based surveys (n=37) and 0 for surveys using the Binax test (n=218). We also fitted a model including random effects <inline-formula><tex-math id="M13">\documentclass[12pt]{minimal}
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}{}${u_i}\sim \; N\; ({0,\; {\sigma^2}} )$\end{document}</tex-math>
</inline-formula>
taking into account the variability not explained by the covariates. The deviance information criterion (DIC) was used to compare fitted models and eventually to determine model selection (i.e., model that yields the lowest DIC value was chosen).</p>
</sec>
<sec id="s3"><title>Results and Discussion</title>
<p>The literature search identified 264 surveys, including 86 surveys conducted prior to the implementation of MDA and 178 post-MDA surveys. Details of included studies are shown in <ext-link ext-link-type="uri" xlink:href="http://trstmh.oxfordjournals.org/lookup/suppl/doi:10.1093/trstmh/trv048/-/DC1">Supplementary Table 1</ext-link>
. In the majority (215/264) of studies mf was determined by thick smear using between 20 and 60 µl of blood; 36 studies used filtration techniques (using 1 to 3 ml blood). Four studies used both thick smear and filtration methods, with estimates obtained by filtration considered. None of the included surveys were conducted in areas where loiasis occurs or in areas where mass treatment against onchocerciasis had been implemented.</p>
<p>Figure <xref ref-type="fig" rid="TRV048F1">1</xref>
A presents the relationship between p<sub>mf</sub>
and p<sub>ICT</sub>
, stratified by pre- and post-intervention settings and by continent, and shows that p<sub>ICT</sub>
consistently overestimates prevalence compared to p<sub>mf</sub>
, especially in post-control settings. The correlation between p<sub>mf</sub>
and p<sub>ICT</sub>
is positive, but not very strong (Spearman's correlation coefficient of 0.62 and 0.59 under pre- and post-intervention settings, respectively). Despite these correlations, we were unable to obtain a well-fitting regression model between p<sub>ICT</sub>
and p<sub>mf</sub>
that would enable prediction of p<sub>mf</sub>
from p<sub>ICT</sub>
(Figure <xref ref-type="fig" rid="TRV048F1">1</xref>
B). DIC values for the fitted models were 1163 and 2960 with and without random effects, respectively, indicating that effects of unmeasured characteristics that affect all individuals surveyed contribute to the observed variability. We were unable to account for age group, as surveys typically targeted all age groups (n=229/264). Sensitivity analysis explored separate models for different volumes of blood examined (20 µl or 20–60 µl), but showed that overall model fit did not improve (see results in the Supplementary information).
<fig id="TRV048F1" orientation="portrait" position="float"><label>Figure 1.</label>
<caption><p>(A) The relationship between the prevalence of lymphatic filariasis based on microfilaraemia (p<sub>mf</sub>
) and prevalence estimated from antigenemia (p<sub>ICT</sub>
), grouped by continent and pre- and post-control. (B) Observed and predicted relationship between p<sub>ICT</sub>
and p<sub>mf.</sub>
For each p<sub>ICT</sub>
value, observed and predicted p<sub>mf</sub>
values obtained from the model without random effects grouped by pre- and post-control. Details of included studies are shown in <ext-link ext-link-type="uri" xlink:href="http://trstmh.oxfordjournals.org/lookup/suppl/doi:10.1093/trstmh/trv048/-/DC1">Supplementary Table 1</ext-link>
.</p>
</caption>
<graphic xlink:href="trv04801"></graphic>
</fig>
</p>
<p>Our analysis highlights a disparity in prevalence estimates of microfilaraemia, based on blood smears, and of antigenaemia based on use of an ICT test. This result was to be expected as filarial antigen tests detect circulating antigen of worm adults and in pre-intervention settings, antigenaemia in children can develop up to 2-3 years before the appearance of microfilaraemia.<sup><xref rid="TRV048C6" ref-type="bibr">6</xref>
</sup>
Among treated populations, adult worms retain the capacity to resume production of microfilariae and rates of antigenaemia are known to decline more slowly following treatment.<sup><xref rid="TRV048C4" ref-type="bibr">4</xref>
</sup>
Other factors related to MDA delivery, including treatment coverage, time interval between rounds and number of rounds, may also influence differently observed levels of microfilaraemia and antigenaemia. In addition, the timing of night blood collection may introduce variation in the estimates of mf prevalence since the density of circulating mf fluctuates overnight,<sup><xref rid="TRV048C7" ref-type="bibr">7</xref>
</sup>
but unfortunately few studies report this information. We recognize that our analysis lacked a gold standard of true LF infection and that technical and human factors may have influenced the reliability of both microscopy and ICTs,<sup><xref rid="TRV048C2" ref-type="bibr">2</xref>
</sup>
but the results clearly show that estimates of microfilaraemia and antigenaemia do not correspond in a predictable manner, especially in post-intervention settings. What was particularly surprising in our analysis was the large difference, up to 40–70%, in estimates of microfilaraemia and antigenaemia. This finding has a number of practical and scientific implications. First, WHO recommends that MDA is initiated in settings where the prevalence of LF >1% and whether this is based on p<sub>mf</sub>
(as initially recommended) or p<sub>ICT</sub>
(as currently recommended) may result in different treatment decisions. Second, the lack of a predictable relationship between microfilaraemia and antigenaemia means that they cannot be combined in studies that seek to develop risk maps of LF and future work should give careful consideration to the diagnostic method when predicting the spatial distribution of LF transmission.</p>
</sec>
<sec sec-type="supplementary-material" id="s4"><title>Supplementary data</title>
<p><ext-link ext-link-type="uri" xlink:href="http://trstmh.oxfordjournals.org/lookup/suppl/doi:10.1093/trstmh/trv048/-/DC1">Supplementary data are available at Transactions Online (http://trstmh.oxfordjournals.org/)</ext-link>
.</p>
<supplementary-material id="PMC_1" content-type="local-data"><caption><title>Supplementary Data</title>
</caption>
<media mimetype="text" mime-subtype="html" xlink:href="supp_109_8_529__index.html"></media>
<media xlink:role="associated-file" mimetype="application" mime-subtype="msword" xlink:href="supp_trv048_trv048supp.docx"></media>
</supplementary-material>
</sec>
</body>
<back><ack><p><bold>Authors' contributions:</bold>
JC and SJB conceived and designed the study, and drafted the manuscript; JC, MPR, ED and SMN were responsible for data collection; JC, PM and BN performed data analysis; JC, SJB, MPR, MJB, PNO, ED and SMN participated in interpretation of data and manuscript revision. All authors read and approved the final manuscript. JC and SJB are guarantors of the paper.</p>
<p><bold>Funding:</bold>
This work was supported by the <funding-source>Wellcome Trust</funding-source>
through a Senior Fellowship in Basic Biomedical Science [098045] to SJB and by grants from the United Kingdom Department for International Development to MJB.</p>
<p><bold>Competing interests:</bold>
None declared.</p>
<p><bold>Ethical approval:</bold>
Not required.</p>
</ack>
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</record>
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