Serologic Evidence of the Geographic Distribution of Bacterial Zoonotic Agents in Kenya, 2007
Identifieur interne : 000493 ( Pmc/Checkpoint ); précédent : 000492; suivant : 000494Serologic Evidence of the Geographic Distribution of Bacterial Zoonotic Agents in Kenya, 2007
Auteurs : Victor O. Omballa ; Raymond N. Musyoka ; Amy Y. Vittor ; Kabura B. Wamburu ; Cyrus M. Wachira ; Lilian W. Waiboci ; Mamo U. Abudo ; Bonventure W. Juma ; Andrea A. Kim ; Joel M. Montgomery ; Robert F. Breiman ; Barry S. FieldsSource :
- The American Journal of Tropical Medicine and Hygiene [ 0002-9637 ] ; 2016.
Abstract
Diseases of zoonotic origin contribute to the burden of febrile illnesses in developing countries. We evaluated serologic evidence of exposure to
Url:
DOI: 10.4269/ajtmh.15-0320
PubMed: 26598574
PubMed Central: 4710443
Affiliations:
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<author><name sortKey="Musyoka, Raymond N" sort="Musyoka, Raymond N" uniqKey="Musyoka R" first="Raymond N." last="Musyoka">Raymond N. Musyoka</name>
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<author><name sortKey="Vittor, Amy Y" sort="Vittor, Amy Y" uniqKey="Vittor A" first="Amy Y." last="Vittor">Amy Y. Vittor</name>
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<author><name sortKey="Wamburu, Kabura B" sort="Wamburu, Kabura B" uniqKey="Wamburu K" first="Kabura B." last="Wamburu">Kabura B. Wamburu</name>
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<author><name sortKey="Wachira, Cyrus M" sort="Wachira, Cyrus M" uniqKey="Wachira C" first="Cyrus M." last="Wachira">Cyrus M. Wachira</name>
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<author><name sortKey="Waiboci, Lilian W" sort="Waiboci, Lilian W" uniqKey="Waiboci L" first="Lilian W." last="Waiboci">Lilian W. Waiboci</name>
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<author><name sortKey="Abudo, Mamo U" sort="Abudo, Mamo U" uniqKey="Abudo M" first="Mamo U." last="Abudo">Mamo U. Abudo</name>
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<author><name sortKey="Juma, Bonventure W" sort="Juma, Bonventure W" uniqKey="Juma B" first="Bonventure W." last="Juma">Bonventure W. Juma</name>
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<author><name sortKey="Kim, Andrea A" sort="Kim, Andrea A" uniqKey="Kim A" first="Andrea A." last="Kim">Andrea A. Kim</name>
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<author><name sortKey="Montgomery, Joel M" sort="Montgomery, Joel M" uniqKey="Montgomery J" first="Joel M." last="Montgomery">Joel M. Montgomery</name>
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<author><name sortKey="Breiman, Robert F" sort="Breiman, Robert F" uniqKey="Breiman R" first="Robert F." last="Breiman">Robert F. Breiman</name>
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<author><name sortKey="Fields, Barry S" sort="Fields, Barry S" uniqKey="Fields B" first="Barry S." last="Fields">Barry S. Fields</name>
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Serologic Evidence of the Geographic Distribution of Bacterial Zoonotic Agents in Kenya, 2007</title>
<author><name sortKey="Omballa, Victor O" sort="Omballa, Victor O" uniqKey="Omballa V" first="Victor O." last="Omballa">Victor O. Omballa</name>
</author>
<author><name sortKey="Musyoka, Raymond N" sort="Musyoka, Raymond N" uniqKey="Musyoka R" first="Raymond N." last="Musyoka">Raymond N. Musyoka</name>
</author>
<author><name sortKey="Vittor, Amy Y" sort="Vittor, Amy Y" uniqKey="Vittor A" first="Amy Y." last="Vittor">Amy Y. Vittor</name>
</author>
<author><name sortKey="Wamburu, Kabura B" sort="Wamburu, Kabura B" uniqKey="Wamburu K" first="Kabura B." last="Wamburu">Kabura B. Wamburu</name>
</author>
<author><name sortKey="Wachira, Cyrus M" sort="Wachira, Cyrus M" uniqKey="Wachira C" first="Cyrus M." last="Wachira">Cyrus M. Wachira</name>
</author>
<author><name sortKey="Waiboci, Lilian W" sort="Waiboci, Lilian W" uniqKey="Waiboci L" first="Lilian W." last="Waiboci">Lilian W. Waiboci</name>
</author>
<author><name sortKey="Abudo, Mamo U" sort="Abudo, Mamo U" uniqKey="Abudo M" first="Mamo U." last="Abudo">Mamo U. Abudo</name>
</author>
<author><name sortKey="Juma, Bonventure W" sort="Juma, Bonventure W" uniqKey="Juma B" first="Bonventure W." last="Juma">Bonventure W. Juma</name>
</author>
<author><name sortKey="Kim, Andrea A" sort="Kim, Andrea A" uniqKey="Kim A" first="Andrea A." last="Kim">Andrea A. Kim</name>
</author>
<author><name sortKey="Montgomery, Joel M" sort="Montgomery, Joel M" uniqKey="Montgomery J" first="Joel M." last="Montgomery">Joel M. Montgomery</name>
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<author><name sortKey="Breiman, Robert F" sort="Breiman, Robert F" uniqKey="Breiman R" first="Robert F." last="Breiman">Robert F. Breiman</name>
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<author><name sortKey="Fields, Barry S" sort="Fields, Barry S" uniqKey="Fields B" first="Barry S." last="Fields">Barry S. Fields</name>
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<series><title level="j">The American Journal of Tropical Medicine and Hygiene</title>
<idno type="ISSN">0002-9637</idno>
<idno type="eISSN">1476-1645</idno>
<imprint><date when="2016">2016</date>
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<front><div type="abstract" xml:lang="en"><p>Diseases of zoonotic origin contribute to the burden of febrile illnesses in developing countries. We evaluated serologic evidence of exposure to <italic>Bacillus anthracis</italic>
, <italic>Brucella</italic>
spp., spotted fever group rickettsioses (SFGR), and typhus group rickettsioses (TGR) from samples of persons aged 15–64 years collected during a nationwide human immunodeficiency virus (HIV) serosurvey conducted in 2007 in Kenya. The seropositivity observed for pathogens was <italic>B. anthracis</italic>
11.3%, <italic>Brucella</italic>
spp. 3.0%, SFGR 23.3%, and TGR 0.6%. On univariate analysis, seropositivity for each pathogen was significantly associated with the following risk factors: <italic>B. anthracis</italic>
with province of residence; <italic>Brucella</italic>
spp. with sex, education level, and wealth; SFGR with age, education level, wealth, and province of residence; and TGR with province of residence. On multivariate analysis, seropositivity remained significantly associated with wealth and province for <italic>B. anthracis</italic>
; with sex and age for <italic>Brucella</italic>
spp; and with sex, education level, and province of residence for SFGR whereas TGR had no significance. High IgG seropositivity to these zoonotic pathogens (especially, <italic>B. anthracis</italic>
and SFGR) suggests substantial exposure. These pathogens should be considered in the differential diagnosis of febrile illness in Kenya.</p>
</div>
</front>
<back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Kahsay, Ag" uniqKey="Kahsay A">AG Kahsay</name>
</author>
<author><name sortKey="Abebew, D" uniqKey="Abebew D">D Abebew</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Richards, Al" uniqKey="Richards A">AL Richards</name>
</author>
<author><name sortKey="Jiang, J" uniqKey="Jiang J">J Jiang</name>
</author>
<author><name sortKey="Omulo, S" uniqKey="Omulo S">S Omulo</name>
</author>
<author><name sortKey="Dare, R" uniqKey="Dare R">R Dare</name>
</author>
<author><name sortKey="Abdirahman, K" uniqKey="Abdirahman K">K Abdirahman</name>
</author>
<author><name sortKey="Ali, A" uniqKey="Ali A">A Ali</name>
</author>
<author><name sortKey="Sharif, Sk" uniqKey="Sharif S">SK Sharif</name>
</author>
<author><name sortKey="Feikin, Dr" uniqKey="Feikin D">DR Feikin</name>
</author>
<author><name sortKey="Breiman, Rf" uniqKey="Breiman R">RF Breiman</name>
</author>
<author><name sortKey="Njenga, Mk" uniqKey="Njenga M">MK Njenga</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Taylor, Lh" uniqKey="Taylor L">LH Taylor</name>
</author>
<author><name sortKey="Lathan, Sm" uniqKey="Lathan S">SM Lathan</name>
</author>
<author><name sortKey="Woolhouse, Me" uniqKey="Woolhouse M">ME Woolhouse</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Ari, Md" uniqKey="Ari M">MD Ari</name>
</author>
<author><name sortKey="Guracha, A" uniqKey="Guracha A">A Guracha</name>
</author>
<author><name sortKey="Fadeel, Ma" uniqKey="Fadeel M">MA Fadeel</name>
</author>
<author><name sortKey="Njuguna, C" uniqKey="Njuguna C">C Njuguna</name>
</author>
<author><name sortKey="Njenga, Mk" uniqKey="Njenga M">MK Njenga</name>
</author>
<author><name sortKey="Kalani, R" uniqKey="Kalani R">R Kalani</name>
</author>
<author><name sortKey="Abdi, H" uniqKey="Abdi H">H Abdi</name>
</author>
<author><name sortKey="Warfu, O" uniqKey="Warfu O">O Warfu</name>
</author>
<author><name sortKey="Omballa, V" uniqKey="Omballa V">V Omballa</name>
</author>
<author><name sortKey="Tetteh, C" uniqKey="Tetteh C">C Tetteh</name>
</author>
<author><name sortKey="Breiman, Rf" uniqKey="Breiman R">RF Breiman</name>
</author>
<author><name sortKey="Pimentel, G" uniqKey="Pimentel G">G Pimentel</name>
</author>
<author><name sortKey="Feikin, Dr" uniqKey="Feikin D">DR Feikin</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Woyessa, Ab" uniqKey="Woyessa A">AB Woyessa</name>
</author>
<author><name sortKey="Omballa, V" uniqKey="Omballa V">V Omballa</name>
</author>
<author><name sortKey="Wang, D" uniqKey="Wang D">D Wang</name>
</author>
<author><name sortKey="Lambert, A" uniqKey="Lambert A">A Lambert</name>
</author>
<author><name sortKey="Waiboci, L" uniqKey="Waiboci L">L Waiboci</name>
</author>
<author><name sortKey="Ayele, W" uniqKey="Ayele W">W Ayele</name>
</author>
<author><name sortKey="Ahmed, A" uniqKey="Ahmed A">A Ahmed</name>
</author>
<author><name sortKey="Abera, Na" uniqKey="Abera N">NA Abera</name>
</author>
<author><name sortKey="Cao, S" uniqKey="Cao S">S Cao</name>
</author>
<author><name sortKey="Ochieng, M" uniqKey="Ochieng M">M Ochieng</name>
</author>
<author><name sortKey="Montgomery, Jm" uniqKey="Montgomery J">JM Montgomery</name>
</author>
<author><name sortKey="Jima, D" uniqKey="Jima D">D Jima</name>
</author>
<author><name sortKey="Fields, B" uniqKey="Fields B">B Fields</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Heisch, Rb" uniqKey="Heisch R">RB Heisch</name>
</author>
<author><name sortKey="Grainger, We" uniqKey="Grainger W">WE Grainger</name>
</author>
<author><name sortKey="Harvey, Aec" uniqKey="Harvey A">AEC Harvey</name>
</author>
<author><name sortKey="Lister, G" uniqKey="Lister G">G Lister</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="John, K" uniqKey="John K">K John</name>
</author>
<author><name sortKey="Kazwala, R" uniqKey="Kazwala R">R Kazwala</name>
</author>
<author><name sortKey="Mfinanga, Gs" uniqKey="Mfinanga G">GS Mfinanga</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Muriuki, Sm" uniqKey="Muriuki S">SM Muriuki</name>
</author>
<author><name sortKey="Mcdermott, Jj" uniqKey="Mcdermott J">JJ McDermott</name>
</author>
<author><name sortKey="Arimi, Sm" uniqKey="Arimi S">SM Arimi</name>
</author>
<author><name sortKey="Mugambi, Jt" uniqKey="Mugambi J">JT Mugambi</name>
</author>
<author><name sortKey="Wamola, Ia" uniqKey="Wamola I">IA Wamola</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Maina, An" uniqKey="Maina A">AN Maina</name>
</author>
<author><name sortKey="Knobel, Dl" uniqKey="Knobel D">DL Knobel</name>
</author>
<author><name sortKey="Jiang, J" uniqKey="Jiang J">J Jiang</name>
</author>
<author><name sortKey="Halliday, J" uniqKey="Halliday J">J Halliday</name>
</author>
<author><name sortKey="Feikin, Dr" uniqKey="Feikin D">DR Feikin</name>
</author>
<author><name sortKey="Cleaveland, S" uniqKey="Cleaveland S">S Cleaveland</name>
</author>
<author><name sortKey="Ng Ang A, Z" uniqKey="Ng Ang A Z">Z Ng'ang'a</name>
</author>
<author><name sortKey="Junghae, M" uniqKey="Junghae M">M Junghae</name>
</author>
<author><name sortKey="Breiman, Rf" uniqKey="Breiman R">RF Breiman</name>
</author>
<author><name sortKey="Richards, Al" uniqKey="Richards A">AL Richards</name>
</author>
<author><name sortKey="Njenga, Mk" uniqKey="Njenga M">MK Njenga</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Maina, Wk" uniqKey="Maina W">WK Maina</name>
</author>
<author><name sortKey="Kim, Aa" uniqKey="Kim A">AA Kim</name>
</author>
<author><name sortKey="Rutherford, Gw" uniqKey="Rutherford G">GW Rutherford</name>
</author>
<author><name sortKey="Harper, M" uniqKey="Harper M">M Harper</name>
</author>
<author><name sortKey="K Oyugi, Bo" uniqKey="K Oyugi B">BO K'Oyugi</name>
</author>
<author><name sortKey="Sharif, S" uniqKey="Sharif S">S Sharif</name>
</author>
<author><name sortKey="Kichamu, G" uniqKey="Kichamu G">G Kichamu</name>
</author>
<author><name sortKey="Muraguri, Nm" uniqKey="Muraguri N">NM Muraguri</name>
</author>
<author><name sortKey="Akhwale, W" uniqKey="Akhwale W">W Akhwale</name>
</author>
<author><name sortKey="Decock, Km" uniqKey="Decock K">KM DeCock</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Bennett, S" uniqKey="Bennett S">S Bennett</name>
</author>
<author><name sortKey="Woods, T" uniqKey="Woods T">T Woods</name>
</author>
<author><name sortKey="Liyanage, Wm" uniqKey="Liyanage W">WM Liyanage</name>
</author>
<author><name sortKey="Smith, Dl" uniqKey="Smith D">DL Smith</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Mcdermott, Jj" uniqKey="Mcdermott J">JJ McDermott</name>
</author>
<author><name sortKey="Arimi, Sm" uniqKey="Arimi S">SM Arimi</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Kaabia, N" uniqKey="Kaabia N">N Kaabia</name>
</author>
<author><name sortKey="Rolain, Jm" uniqKey="Rolain J">JM Rolain</name>
</author>
<author><name sortKey="Khalifa, M" uniqKey="Khalifa M">M Khalifa</name>
</author>
<author><name sortKey="Jazia, Eb" uniqKey="Jazia E">EB Jazia</name>
</author>
<author><name sortKey="Bahri, F" uniqKey="Bahri F">F Bahri</name>
</author>
<author><name sortKey="Raoult, D" uniqKey="Raoult D">D Raoult</name>
</author>
<author><name sortKey="Letaief, A" uniqKey="Letaief A">A Letaief</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Anyangu, As" uniqKey="Anyangu A">AS Anyangu</name>
</author>
<author><name sortKey="Gould, Lh" uniqKey="Gould L">LH Gould</name>
</author>
<author><name sortKey="Sharif, Sk" uniqKey="Sharif S">SK Sharif</name>
</author>
<author><name sortKey="Nguku, Pm" uniqKey="Nguku P">PM Nguku</name>
</author>
<author><name sortKey="Omolo, Jo" uniqKey="Omolo J">JO Omolo</name>
</author>
<author><name sortKey="Mutonga, D" uniqKey="Mutonga D">D Mutonga</name>
</author>
<author><name sortKey="Rao, Cy" uniqKey="Rao C">CY Rao</name>
</author>
<author><name sortKey="Lederman, Er" uniqKey="Lederman E">ER Lederman</name>
</author>
<author><name sortKey="Schnabel, D" uniqKey="Schnabel D">D Schnabel</name>
</author>
<author><name sortKey="Paweska, Jt" uniqKey="Paweska J">JT Paweska</name>
</author>
<author><name sortKey="Katz, M" uniqKey="Katz M">M Katz</name>
</author>
<author><name sortKey="Hightower, A" uniqKey="Hightower A">A Hightower</name>
</author>
<author><name sortKey="Njenga, Mk" uniqKey="Njenga M">MK Njenga</name>
</author>
<author><name sortKey="Feikin, Dr" uniqKey="Feikin D">DR Feikin</name>
</author>
<author><name sortKey="Breiman, Rf" uniqKey="Breiman R">RF Breiman</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Arimi, Sm" uniqKey="Arimi S">SM Arimi</name>
</author>
<author><name sortKey="Koroti, E" uniqKey="Koroti E">E Koroti</name>
</author>
<author><name sortKey="Kang Ethe, Ek" uniqKey="Kang Ethe E">EK Kang'ethe</name>
</author>
<author><name sortKey="Omore, Ao" uniqKey="Omore A">AO Omore</name>
</author>
<author><name sortKey="Mcdermott, Jj" uniqKey="Mcdermott J">JJ McDermott</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Jones, Ke" uniqKey="Jones K">KE Jones</name>
</author>
<author><name sortKey="Patel, Ng" uniqKey="Patel N">NG Patel</name>
</author>
<author><name sortKey="Levy, Ma" uniqKey="Levy M">MA Levy</name>
</author>
<author><name sortKey="Storeygard, A" uniqKey="Storeygard A">A Storeygard</name>
</author>
<author><name sortKey="Balk, Dd" uniqKey="Balk D">DD Balk</name>
</author>
<author><name sortKey="Gittleman, Jl" uniqKey="Gittleman J">JL Gittleman</name>
</author>
<author><name sortKey="Daszak, P" uniqKey="Daszak P">P Daszak</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Muendo, En" uniqKey="Muendo E">EN Muendo</name>
</author>
<author><name sortKey="Mbatha, Pm" uniqKey="Mbatha P">PM Mbatha</name>
</author>
<author><name sortKey="Macharia, J" uniqKey="Macharia J">J Macharia</name>
</author>
<author><name sortKey="Abdoel, Th" uniqKey="Abdoel T">TH Abdoel</name>
</author>
<author><name sortKey="Janszen, Pv" uniqKey="Janszen P">PV Janszen</name>
</author>
<author><name sortKey="Pastoor, R" uniqKey="Pastoor R">R Pastoor</name>
</author>
<author><name sortKey="Smits, Hl" uniqKey="Smits H">HL Smits</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Omemo, P" uniqKey="Omemo P">P Omemo</name>
</author>
<author><name sortKey="Ogola, E" uniqKey="Ogola E">E Ogola</name>
</author>
<author><name sortKey="Omondi, G" uniqKey="Omondi G">G Omondi</name>
</author>
<author><name sortKey="Wasonga, J" uniqKey="Wasonga J">J Wasonga</name>
</author>
<author><name sortKey="Knobel, D" uniqKey="Knobel D">D Knobel</name>
</author>
</analytic>
</biblStruct>
</listBibl>
</div1>
</back>
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<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Am J Trop Med Hyg</journal-id>
<journal-id journal-id-type="iso-abbrev">Am. J. Trop. Med. Hyg</journal-id>
<journal-id journal-id-type="publisher-id">tpmd</journal-id>
<journal-title-group><journal-title>The American Journal of Tropical Medicine and Hygiene</journal-title>
</journal-title-group>
<issn pub-type="ppub">0002-9637</issn>
<issn pub-type="epub">1476-1645</issn>
<publisher><publisher-name>The American Society of Tropical Medicine and Hygiene</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">26598574</article-id>
<article-id pub-id-type="pmc">4710443</article-id>
<article-id pub-id-type="doi">10.4269/ajtmh.15-0320</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Articles</subject>
</subj-group>
</article-categories>
<title-group><article-title>Serologic Evidence of the Geographic Distribution of Bacterial Zoonotic Agents in Kenya, 2007</article-title>
<alt-title alt-title-type="left-running-head">OMBALLA AND OTHERS</alt-title>
<alt-title alt-title-type="right-running-head">SEROLOGIC EVIDENCE OF BACTERIAL ZOONOTIC AGENTS IN KENYA, 2007</alt-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Omballa</surname>
<given-names>Victor O.</given-names>
</name>
<xref ref-type="corresp" rid="COR1">*</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Musyoka</surname>
<given-names>Raymond N.</given-names>
</name>
</contrib>
<contrib contrib-type="author"><name><surname>Vittor</surname>
<given-names>Amy Y.</given-names>
</name>
</contrib>
<contrib contrib-type="author"><name><surname>Wamburu</surname>
<given-names>Kabura B.</given-names>
</name>
</contrib>
<contrib contrib-type="author"><name><surname>Wachira</surname>
<given-names>Cyrus M.</given-names>
</name>
</contrib>
<contrib contrib-type="author"><name><surname>Waiboci</surname>
<given-names>Lilian W.</given-names>
</name>
</contrib>
<contrib contrib-type="author"><name><surname>Abudo</surname>
<given-names>Mamo U.</given-names>
</name>
</contrib>
<contrib contrib-type="author"><name><surname>Juma</surname>
<given-names>Bonventure W.</given-names>
</name>
</contrib>
<contrib contrib-type="author"><name><surname>Kim</surname>
<given-names>Andrea A.</given-names>
</name>
</contrib>
<contrib contrib-type="author"><name><surname>Montgomery</surname>
<given-names>Joel M.</given-names>
</name>
</contrib>
<contrib contrib-type="author"><name><surname>Breiman</surname>
<given-names>Robert F.</given-names>
</name>
</contrib>
<contrib contrib-type="author"><name><surname>Fields</surname>
<given-names>Barry S.</given-names>
</name>
</contrib>
</contrib-group>
<aff id="AFF1">Center for Global Health Research, Kenya Medical Research Institute, Nairobi, Kenya; University of Tampere, Tampere, Finland; Africa Refugee Health Program, Division of Global Health Protection, Centers for Disease Control and Prevention, Nairobi, Kenya; Department of Medicine, University of Florida, Gainesville, Florida; University of Nairobi, Nairobi, Kenya; Kenya Ministry of Public Health and Sanitation, Nairobi, Kenya; Diagnostics and Laboratory Systems Program, Division of Global Health Protection, Centers for Disease Control and Prevention, Nairobi, Kenya; Division of Global HIV/AIDS, Surveillance and Epidemiology, Centers for Disease Control and Prevention, Nairobi, Kenya; Global Disease Detection Branch, Division of Global Health Protection, Centers for Disease Control and Prevention, Nairobi, Kenya; Emory University, Atlanta, Georgia</aff>
<author-notes><corresp id="COR1">*Address correspondence to Victor O. Omballa, Center for Global Health Research, Kenya Medical Research Institute, P.O. Box 606-00621, Nairobi, Kenya. E-mail: <email>vomballa@kemricdc.org</email>
</corresp>
</author-notes>
<pub-date pub-type="ppub"><day>06</day>
<month>1</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>06</day>
<month>1</month>
<year>2016</year>
</pub-date>
<pmc-comment> PMC Release delay is 0 months and 0 days and was based on the
. </pmc-comment>
<volume>94</volume>
<issue>1</issue>
<fpage>43</fpage>
<lpage>51</lpage>
<history><date date-type="received"><day>30</day>
<month>4</month>
<year>2015</year>
</date>
<date date-type="accepted"><day>25</day>
<month>9</month>
<year>2015</year>
</date>
</history>
<permissions><copyright-statement>©The American Society of Tropical Medicine and Hygiene</copyright-statement>
<copyright-year>2016</copyright-year>
<license license-type="open-access"><license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>
, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
</license>
</permissions>
<abstract><p>Diseases of zoonotic origin contribute to the burden of febrile illnesses in developing countries. We evaluated serologic evidence of exposure to <italic>Bacillus anthracis</italic>
, <italic>Brucella</italic>
spp., spotted fever group rickettsioses (SFGR), and typhus group rickettsioses (TGR) from samples of persons aged 15–64 years collected during a nationwide human immunodeficiency virus (HIV) serosurvey conducted in 2007 in Kenya. The seropositivity observed for pathogens was <italic>B. anthracis</italic>
11.3%, <italic>Brucella</italic>
spp. 3.0%, SFGR 23.3%, and TGR 0.6%. On univariate analysis, seropositivity for each pathogen was significantly associated with the following risk factors: <italic>B. anthracis</italic>
with province of residence; <italic>Brucella</italic>
spp. with sex, education level, and wealth; SFGR with age, education level, wealth, and province of residence; and TGR with province of residence. On multivariate analysis, seropositivity remained significantly associated with wealth and province for <italic>B. anthracis</italic>
; with sex and age for <italic>Brucella</italic>
spp; and with sex, education level, and province of residence for SFGR whereas TGR had no significance. High IgG seropositivity to these zoonotic pathogens (especially, <italic>B. anthracis</italic>
and SFGR) suggests substantial exposure. These pathogens should be considered in the differential diagnosis of febrile illness in Kenya.</p>
</abstract>
</article-meta>
<notes notes-type="disclaimer"><p>Disclaimer: The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.</p>
</notes>
</front>
<floats-group><table-wrap id="T1" position="float"><label>Table 1</label>
<caption><p>Bivariate and multivariate analysis of factors associated with previous exposure to <italic>Bacillus anthracis</italic>
</p>
</caption>
<table frame="hsides" rules="groups"><thead><tr><th align="center" rowspan="1" colspan="1">Variable</th>
<th align="center" rowspan="1" colspan="1">Positive (<italic>n</italic>
)</th>
<th align="center" rowspan="1" colspan="1">Total (<italic>N</italic>
)</th>
<th align="center" rowspan="1" colspan="1">% Positive (95% CI)</th>
<th align="center" rowspan="1" colspan="1">Unadjusted OR (95% CI)</th>
<th align="center" rowspan="1" colspan="1"><italic>P</italic>
value</th>
<th align="center" rowspan="1" colspan="1">G <italic>P</italic>
value</th>
<th align="center" rowspan="1" colspan="1">AOR (95% CI)</th>
<th align="center" rowspan="1" colspan="1">M <italic>P</italic>
value</th>
</tr>
</thead>
<tbody><tr><td colspan="9" rowspan="1">Residence</td>
</tr>
<tr><td rowspan="1" colspan="1"> Rural</td>
<td rowspan="1" colspan="1">110</td>
<td rowspan="1" colspan="1">784</td>
<td rowspan="1" colspan="1">11.2 (7.8–14.6)</td>
<td rowspan="1" colspan="1">1.0 (0.5–2.0)</td>
<td rowspan="1" colspan="1">0.902</td>
<td rowspan="1" colspan="1">0.902</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Urban</td>
<td rowspan="1" colspan="1">31</td>
<td rowspan="1" colspan="1">307</td>
<td rowspan="1" colspan="1">11.6 (5.2–18.1)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Sex</td>
</tr>
<tr><td rowspan="1" colspan="1"> Male</td>
<td rowspan="1" colspan="1">61</td>
<td rowspan="1" colspan="1">430</td>
<td rowspan="1" colspan="1">13.6 (7.8–19.4)</td>
<td rowspan="1" colspan="1">1.4 (0.8–2.5)</td>
<td rowspan="1" colspan="1">0.2139</td>
<td rowspan="1" colspan="1">0.2139</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Female</td>
<td rowspan="1" colspan="1">80</td>
<td rowspan="1" colspan="1">661</td>
<td rowspan="1" colspan="1">9.9 (6.8–13.0)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Age (in years)</td>
</tr>
<tr><td rowspan="1" colspan="1"> 15–29</td>
<td rowspan="1" colspan="1">67</td>
<td rowspan="1" colspan="1">529</td>
<td rowspan="1" colspan="1">11.0 (7.5–14.6)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> 30–49</td>
<td rowspan="1" colspan="1">54</td>
<td rowspan="1" colspan="1">395</td>
<td rowspan="1" colspan="1">11.4 (5.4–17.4)</td>
<td rowspan="1" colspan="1">1.0 (0.5–2.0)</td>
<td rowspan="1" colspan="1">0.9228</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> 50–64</td>
<td rowspan="1" colspan="1">20</td>
<td rowspan="1" colspan="1">167</td>
<td rowspan="1" colspan="1">12.2 (5.8–18.5)</td>
<td rowspan="1" colspan="1">1.12 (0.6–2.2)</td>
<td rowspan="1" colspan="1">0.7571</td>
<td rowspan="1" colspan="1">0.9532</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Education level</td>
</tr>
<tr><td rowspan="1" colspan="1"> No primary</td>
<td rowspan="1" colspan="1">22</td>
<td rowspan="1" colspan="1">223</td>
<td rowspan="1" colspan="1">7.0 (2.4–11.6)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Some primary</td>
<td rowspan="1" colspan="1">47</td>
<td rowspan="1" colspan="1">295</td>
<td rowspan="1" colspan="1">14.5 (10.1–18.9)</td>
<td rowspan="1" colspan="1"><bold>2.3</bold>
<bold>(1.07</bold>
–<bold>4.76)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0322</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">0.1007</td>
<td rowspan="1" colspan="1">0.91 (0.5–1.67)</td>
<td rowspan="1" colspan="1">0.7693</td>
</tr>
<tr><td rowspan="1" colspan="1"> Complete primary and secondary+</td>
<td rowspan="1" colspan="1">72</td>
<td rowspan="1" colspan="1">573</td>
<td rowspan="1" colspan="1">11.9 (7.7–16.1)</td>
<td rowspan="1" colspan="1">1.8 (0.9–3.8)</td>
<td rowspan="1" colspan="1">0.1236</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">1.16 (0.56–2.4)</td>
<td rowspan="1" colspan="1">0.6883</td>
</tr>
<tr><td colspan="9" rowspan="1">Wealth quintiles</td>
</tr>
<tr><td rowspan="1" colspan="1"> Lowest</td>
<td rowspan="1" colspan="1">33</td>
<td rowspan="1" colspan="1">234</td>
<td rowspan="1" colspan="1">10.7 (5.9–15.6)</td>
<td rowspan="1" colspan="1">1.99 (0.85–4.66)</td>
<td rowspan="1" colspan="1">0.1145</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1"><bold>4.91 (1.57</bold>
–<bold>15.4)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0063</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> Second</td>
<td rowspan="1" colspan="1">44</td>
<td rowspan="1" colspan="1">189</td>
<td rowspan="1" colspan="1">17.1 (7.0–27.2)</td>
<td rowspan="1" colspan="1"><bold>3.42 (1.26</bold>
–<bold>9.28)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.016</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">0.0622</td>
<td rowspan="1" colspan="1"><bold>5.57 (1.77</bold>
–<bold>17.51)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0033</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> Middle</td>
<td rowspan="1" colspan="1">23</td>
<td rowspan="1" colspan="1">188</td>
<td rowspan="1" colspan="1">9.1 (5.1–13.0)</td>
<td rowspan="1" colspan="1">1.65 (0.71–3.83)</td>
<td rowspan="1" colspan="1">0.2466</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">2.0 (0.64–6.19)</td>
<td rowspan="1" colspan="1">0.2312</td>
</tr>
<tr><td rowspan="1" colspan="1"> Fourth</td>
<td rowspan="1" colspan="1">22</td>
<td rowspan="1" colspan="1">186</td>
<td rowspan="1" colspan="1">18.5 (6.8–30.3)</td>
<td rowspan="1" colspan="1"><bold>3.77 (1.26</bold>
–<bold>11.30)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.018</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1"><bold>4.56 (1.15</bold>
–<bold>18.14)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0313</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> Highest</td>
<td rowspan="1" colspan="1">19</td>
<td rowspan="1" colspan="1">294</td>
<td rowspan="1" colspan="1">5.7 (2.0–9.4)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Province</td>
</tr>
<tr><td rowspan="1" colspan="1"> Nairobi</td>
<td rowspan="1" colspan="1">9</td>
<td rowspan="1" colspan="1">153</td>
<td rowspan="1" colspan="1">9.5 (1.5–17.6)</td>
<td rowspan="1" colspan="1"><bold>5.46 (1.20</bold>
–<bold>24.88)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0281</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1"><bold>18.27 (2.84</bold>
–<bold>117.39)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0022</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> Central</td>
<td rowspan="1" colspan="1">10</td>
<td rowspan="1" colspan="1">150</td>
<td rowspan="1" colspan="1">6.4 (2.5–10.3)</td>
<td rowspan="1" colspan="1">3.55 (0.91–13.86)</td>
<td rowspan="1" colspan="1">0.0679</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1"><bold>6.48 (1.34</bold>
–<bold>31.36)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0203</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> Coast</td>
<td rowspan="1" colspan="1">20</td>
<td rowspan="1" colspan="1">129</td>
<td rowspan="1" colspan="1">12.8 (6.1–19.5)</td>
<td rowspan="1" colspan="1"><bold>7.63 (2.01</bold>
–<bold>29.04)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0029</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1"><bold>13.39 (3.09</bold>
–<bold>57.9)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0005</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> Eastern</td>
<td rowspan="1" colspan="1">11</td>
<td rowspan="1" colspan="1">112</td>
<td rowspan="1" colspan="1">7.3 (2.0–12.7)</td>
<td rowspan="1" colspan="1">4.11 (0.98–17.24)</td>
<td rowspan="1" colspan="1">0.0531</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1"><bold>5.83 (1.24</bold>
–<bold>27.35)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0253</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> North Eastern</td>
<td rowspan="1" colspan="1">7</td>
<td rowspan="1" colspan="1">140</td>
<td rowspan="1" colspan="1">1.9 (0.0–4.1)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Nyanza</td>
<td rowspan="1" colspan="1">35</td>
<td rowspan="1" colspan="1">154</td>
<td rowspan="1" colspan="1">21.4 (13.3–29.4)</td>
<td rowspan="1" colspan="1"><bold>14.09 (3.88</bold>
–<bold>51.14)</bold>
</td>
<td rowspan="1" colspan="1"><bold>< 0.0001</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1"><bold>18.19 (4.41</bold>
–<bold>74.91)</bold>
</td>
<td rowspan="1" colspan="1"><bold>< 0.0001</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> Rift Valley</td>
<td rowspan="1" colspan="1">10</td>
<td rowspan="1" colspan="1">117</td>
<td rowspan="1" colspan="1">11.0 (1.3–20.8)</td>
<td rowspan="1" colspan="1"><bold>6.44 (1.36</bold>
–<bold>30.48)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.019</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1"><bold>10.55 (2.32</bold>
–<bold>48.03)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0023</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> Western</td>
<td rowspan="1" colspan="1">39</td>
<td rowspan="1" colspan="1">136</td>
<td rowspan="1" colspan="1">27.5 (18.4–36.7)</td>
<td rowspan="1" colspan="1"><bold>19.71 (5.49–70.84)</bold>
</td>
<td rowspan="1" colspan="1"><bold>< 0.0001</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1"><bold>< 0.0001</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1"><bold>25.41 (6.4–100.92)</bold>
</td>
<td rowspan="1" colspan="1"><bold>< 0.0001</bold>
<xref ref-type="table-fn" rid="TFN3"><bold>*</bold>
</xref>
</td>
</tr>
</tbody>
</table>
<table-wrap-foot><fn id="TFN1"><p>AOR = adjusted odds ratio; CI = confidence interval; REF = reference.</p>
</fn>
<fn id="TFN2"><p><italic>P</italic>
value is the category <italic>P</italic>
value, G <italic>P</italic>
value is the global <italic>P</italic>
value for the bivariate variable, M <italic>P</italic>
value is the category multivariate <italic>P</italic>
value.</p>
</fn>
<fn id="TFN3"><label>*</label>
<p>Bold values have significant <italic>P</italic>
values.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T2" position="float"><label>Table 2</label>
<caption><p>Bivariate and multivariate analysis of factors associated with previous exposure to <italic>Brucella</italic>
spp.</p>
</caption>
<table frame="hsides" rules="groups"><thead><tr><th align="center" rowspan="1" colspan="1">Variable</th>
<th align="center" rowspan="1" colspan="1">Positive (<italic>n</italic>
)</th>
<th align="center" rowspan="1" colspan="1">Total (<italic>N</italic>
)</th>
<th align="center" rowspan="1" colspan="1">% Positive (95% CI)</th>
<th align="center" rowspan="1" colspan="1">Unadjusted OR (95% CI)</th>
<th align="center" rowspan="1" colspan="1"><italic>P</italic>
value</th>
<th align="center" rowspan="1" colspan="1">G <italic>P</italic>
value</th>
<th align="center" rowspan="1" colspan="1">AOR (95% CI)</th>
<th align="center" rowspan="1" colspan="1">M <italic>P</italic>
value</th>
</tr>
</thead>
<tbody><tr><td colspan="9" rowspan="1">Residence</td>
</tr>
<tr><td rowspan="1" colspan="1"> Rural</td>
<td rowspan="1" colspan="1">26</td>
<td rowspan="1" colspan="1">694</td>
<td rowspan="1" colspan="1">4.2 (1.2–7.1)</td>
<td rowspan="1" colspan="1"><bold>14.20 (1.74–116.18)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0133</bold>
<xref ref-type="table-fn" rid="TFN6"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1"><bold>0.0133</bold>
<xref ref-type="table-fn" rid="TFN6"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">0.48 (0.0–5.5)</td>
<td rowspan="1" colspan="1">0.5555</td>
</tr>
<tr><td rowspan="1" colspan="1"> Urban</td>
<td rowspan="1" colspan="1">1</td>
<td rowspan="1" colspan="1">269</td>
<td rowspan="1" colspan="1">0.3 (0.0–0.9)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Sex</td>
</tr>
<tr><td rowspan="1" colspan="1"> Male</td>
<td rowspan="1" colspan="1">17</td>
<td rowspan="1" colspan="1">374</td>
<td rowspan="1" colspan="1">5.3 (1.7–8.9)</td>
<td rowspan="1" colspan="1"><bold>3.49 (1.83–6.63)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0001</bold>
<xref ref-type="table-fn" rid="TFN6"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1"><bold>0.0001</bold>
<xref ref-type="table-fn" rid="TFN6"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1"><bold>4.67 (2.37–9.19)</bold>
</td>
<td rowspan="1" colspan="1"><bold>< 0.0001</bold>
<xref ref-type="table-fn" rid="TFN6"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> Female</td>
<td rowspan="1" colspan="1">10</td>
<td rowspan="1" colspan="1">589</td>
<td rowspan="1" colspan="1">1.6 (0.2–2.9)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Age (in years)</td>
</tr>
<tr><td rowspan="1" colspan="1"> 15–29</td>
<td rowspan="1" colspan="1">11</td>
<td rowspan="1" colspan="1">461</td>
<td rowspan="1" colspan="1">2.9 (0.8–5.1)</td>
<td rowspan="1" colspan="1">1.52 (0.7–3.31)</td>
<td rowspan="1" colspan="1">0.2901</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1"><bold>5.09 (1.53–17.00)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0081</bold>
<xref ref-type="table-fn" rid="TFN6"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> 30–49</td>
<td rowspan="1" colspan="1">9</td>
<td rowspan="1" colspan="1">353</td>
<td rowspan="1" colspan="1">2.0 (0.3–3.6)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> 50–64</td>
<td rowspan="1" colspan="1">7</td>
<td rowspan="1" colspan="1">149</td>
<td rowspan="1" colspan="1">6.3 (0.3–12.3)</td>
<td rowspan="1" colspan="1"><bold>3.37 (1.15–9.86)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0265</bold>
<xref ref-type="table-fn" rid="TFN6"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">0.0853</td>
<td rowspan="1" colspan="1"><bold>3.38 (1.08–10.65)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0371</bold>
<xref ref-type="table-fn" rid="TFN6"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td colspan="9" rowspan="1">Education level</td>
</tr>
<tr><td rowspan="1" colspan="1"> No primary</td>
<td rowspan="1" colspan="1">22</td>
<td rowspan="1" colspan="1">202</td>
<td rowspan="1" colspan="1">9.8 (1.4–18.3)</td>
<td rowspan="1" colspan="1"><bold>15.76 (3.91–63.54)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0001</bold>
<xref ref-type="table-fn" rid="TFN6"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1"><bold>0.0001</bold>
<xref ref-type="table-fn" rid="TFN6"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1"><bold>7.29 (1.48–35.94)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0146</bold>
<xref ref-type="table-fn" rid="TFN6"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> Some primary</td>
<td rowspan="1" colspan="1">5</td>
<td rowspan="1" colspan="1">259</td>
<td rowspan="1" colspan="1">0.7 (0. –1.4)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Complete primary and secondary+</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Wealth quintiles</td>
</tr>
<tr><td rowspan="1" colspan="1"> Lowest</td>
<td rowspan="1" colspan="1">18</td>
<td rowspan="1" colspan="1">216</td>
<td rowspan="1" colspan="1">10.0 (2.6–17.3)</td>
<td rowspan="1" colspan="1"><bold>50.1 (5.91–425.07)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0003</bold>
<xref ref-type="table-fn" rid="TFN6"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">12.78 (0.74–219.83)</td>
<td rowspan="1" colspan="1">0.0793</td>
</tr>
<tr><td rowspan="1" colspan="1"> Second</td>
<td rowspan="1" colspan="1">3</td>
<td rowspan="1" colspan="1">166</td>
<td rowspan="1" colspan="1">1.6 (0.0–3.9)</td>
<td rowspan="1" colspan="1">7.52 (0.65–87.22)</td>
<td rowspan="1" colspan="1">0.1067</td>
<td rowspan="1" colspan="1"><bold>< 0.0001</bold>
<xref ref-type="table-fn" rid="TFN6"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">2.34 (0.11–48.15)</td>
<td rowspan="1" colspan="1">0.5807</td>
</tr>
<tr><td rowspan="1" colspan="1"> Middle</td>
<td rowspan="1" colspan="1">5</td>
<td rowspan="1" colspan="1">160</td>
<td rowspan="1" colspan="1">2.8 (0.3–5.3)</td>
<td rowspan="1" colspan="1"><bold>13.1 (1.51–113.51)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0196</bold>
<xref ref-type="table-fn" rid="TFN6"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">8.38 (0.48–147.27)</td>
<td rowspan="1" colspan="1">0.1461</td>
</tr>
<tr><td rowspan="1" colspan="1"> Fourth</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Highest</td>
<td rowspan="1" colspan="1">1</td>
<td rowspan="1" colspan="1">256</td>
<td rowspan="1" colspan="1">0.2 (0.0–0.7)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Province</td>
</tr>
<tr><td rowspan="1" colspan="1"> Nairobi</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Central</td>
<td rowspan="1" colspan="1">2</td>
<td rowspan="1" colspan="1">141</td>
<td rowspan="1" colspan="1">1.1 (0.0–2.7)</td>
<td rowspan="1" colspan="1">2.06 (0.18–23.97)</td>
<td rowspan="1" colspan="1">0.5628</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">5.51 (0.50–61.12)</td>
<td rowspan="1" colspan="1">0.1644</td>
</tr>
<tr><td rowspan="1" colspan="1"> Coast</td>
<td rowspan="1" colspan="1">1</td>
<td rowspan="1" colspan="1">113</td>
<td rowspan="1" colspan="1">1.0 (0.0–2.9)</td>
<td rowspan="1" colspan="1">1.79 (0.11–29.77)</td>
<td rowspan="1" colspan="1">0.6853</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">1.37 (0.06–30.47)</td>
<td rowspan="1" colspan="1">0.8438</td>
</tr>
<tr><td rowspan="1" colspan="1"> Eastern</td>
<td rowspan="1" colspan="1">1</td>
<td rowspan="1" colspan="1">96</td>
<td rowspan="1" colspan="1">1.5 (0.0–4.3)</td>
<td rowspan="1" colspan="1">2.72 (0.17–44.68)</td>
<td rowspan="1" colspan="1">0.4833</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">2.57 (0.25–25.96)</td>
<td rowspan="1" colspan="1">0.4249</td>
</tr>
<tr><td rowspan="1" colspan="1"> North Eastern</td>
<td rowspan="1" colspan="1">20</td>
<td rowspan="1" colspan="1">129</td>
<td rowspan="1" colspan="1">10.3 (0.0–21.8)</td>
<td rowspan="1" colspan="1"><bold>20.86 (1.99–218.72)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0113</bold>
<xref ref-type="table-fn" rid="TFN6"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">5.52 (0.50–61.27)</td>
<td rowspan="1" colspan="1">0.1639</td>
</tr>
<tr><td rowspan="1" colspan="1"> Nyanza</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Rift Valley</td>
<td rowspan="1" colspan="1">2</td>
<td rowspan="1" colspan="1">106</td>
<td rowspan="1" colspan="1">2.8 (0.0–7.0)</td>
<td rowspan="1" colspan="1">5.29 (0.43–64.39)</td>
<td rowspan="1" colspan="1">0.1916</td>
<td rowspan="1" colspan="1">0.0679</td>
<td rowspan="1" colspan="1">2.97 (0.27–32.00)</td>
<td rowspan="1" colspan="1">0.3705</td>
</tr>
<tr><td rowspan="1" colspan="1"> Western</td>
<td rowspan="1" colspan="1">1</td>
<td rowspan="1" colspan="1">126</td>
<td rowspan="1" colspan="1">0.5 (0.0–1.6)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
</tbody>
</table>
<table-wrap-foot><fn id="TFN4"><p>AOR = adjusted odds ratio; CI = confidence interval; REF = reference.</p>
</fn>
<fn id="TFN5"><p><italic>P</italic>
value is the category <italic>P</italic>
value, G <italic>P</italic>
value is the global <italic>P</italic>
value for the bivariate variable, M <italic>P</italic>
value is the category multivariate <italic>P</italic>
value.</p>
</fn>
<fn id="TFN6"><label>*</label>
<p>Bold values have significant <italic>P</italic>
values.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T3" position="float"><label>Table 3</label>
<caption><p>Bivariate and multivariate analysis of factors associated with previous exposure to SFGR</p>
</caption>
<table frame="hsides" rules="groups"><thead><tr><th align="center" rowspan="1" colspan="1">Variable</th>
<th align="center" rowspan="1" colspan="1">Positive (<italic>n</italic>
)</th>
<th align="center" rowspan="1" colspan="1">Total (<italic>N</italic>
)</th>
<th align="center" rowspan="1" colspan="1">% Positive (95% CI)</th>
<th align="center" rowspan="1" colspan="1">Unadjusted OR (95% CI)</th>
<th align="center" rowspan="1" colspan="1"><italic>P</italic>
value</th>
<th align="center" rowspan="1" colspan="1">G <italic>P</italic>
value</th>
<th align="center" rowspan="1" colspan="1">Adjusted OR (95% CI)</th>
<th align="center" rowspan="1" colspan="1">M <italic>P</italic>
value</th>
</tr>
</thead>
<tbody><tr><td colspan="9" rowspan="1">Residence</td>
</tr>
<tr><td rowspan="1" colspan="1"> Rural</td>
<td rowspan="1" colspan="1">160</td>
<td rowspan="1" colspan="1">558</td>
<td rowspan="1" colspan="1">26.7 (22.3–31.1)</td>
<td rowspan="1" colspan="1"><bold>2.29 (1.23–4.24)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0088</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1"><bold>0.0088</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">2.33 (0.80–6.77)</td>
<td rowspan="1" colspan="1">0.1211</td>
</tr>
<tr><td rowspan="1" colspan="1"> Urban</td>
<td rowspan="1" colspan="1">31</td>
<td rowspan="1" colspan="1">212</td>
<td rowspan="1" colspan="1">13.8 (6.9–20.6)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Sex</td>
</tr>
<tr><td rowspan="1" colspan="1"> Male</td>
<td rowspan="1" colspan="1">91</td>
<td rowspan="1" colspan="1">317</td>
<td rowspan="1" colspan="1">27.2 (21.5–32.8)</td>
<td rowspan="1" colspan="1">1.45 (0.94–2.23)</td>
<td rowspan="1" colspan="1">0.0937</td>
<td rowspan="1" colspan="1">0.0937</td>
<td rowspan="1" colspan="1">1.80 (1.05–3.06)</td>
<td rowspan="1" colspan="1"><bold>0.0308</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> Female</td>
<td rowspan="1" colspan="1">100</td>
<td rowspan="1" colspan="1">453</td>
<td rowspan="1" colspan="1">20.5 (15.3–25.7)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Age (in years)</td>
</tr>
<tr><td rowspan="1" colspan="1"> 15–29</td>
<td rowspan="1" colspan="1">88</td>
<td rowspan="1" colspan="1">368</td>
<td rowspan="1" colspan="1">22.7 (17.0–28.3)</td>
<td rowspan="1" colspan="1">1.24 (0.85–1.8)</td>
<td rowspan="1" colspan="1">0.2703</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">1.47 (0.93–2.33)</td>
<td rowspan="1" colspan="1">0.1024</td>
</tr>
<tr><td rowspan="1" colspan="1"> 30–49</td>
<td rowspan="1" colspan="1">63</td>
<td rowspan="1" colspan="1">285</td>
<td rowspan="1" colspan="1">19.1 (14.9–23.4)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> 50–64</td>
<td rowspan="1" colspan="1">40</td>
<td rowspan="1" colspan="1">117</td>
<td rowspan="1" colspan="1">37.7 (19.2–56.2)</td>
<td rowspan="1" colspan="1"><bold>2.56 (1.15–5.71)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0217</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1"><bold>0.0361</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">1.97 (0.81–4.80)</td>
<td rowspan="1" colspan="1">0.1364</td>
</tr>
<tr><td colspan="9" rowspan="1">Education level</td>
</tr>
<tr><td rowspan="1" colspan="1"> No primary</td>
<td rowspan="1" colspan="1">59</td>
<td rowspan="1" colspan="1">156</td>
<td rowspan="1" colspan="1">36.5 (28.6–44.4)</td>
<td rowspan="1" colspan="1"><bold>3.56 (2.09–6.08)</bold>
</td>
<td rowspan="1" colspan="1"><bold>< 0.0001</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1"><bold>< 0.0001</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">0.66 (0.15–2.94)</td>
<td rowspan="1" colspan="1">0.5866</td>
</tr>
<tr><td rowspan="1" colspan="1"> Some primary</td>
<td rowspan="1" colspan="1">60</td>
<td rowspan="1" colspan="1">211</td>
<td rowspan="1" colspan="1">27.4 (19.7–35.1)</td>
<td rowspan="1" colspan="1"><bold>2.34 (1.42–3.87)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0009</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">8.40 (0.39–182.39)</td>
<td rowspan="1" colspan="1">0.1753</td>
</tr>
<tr><td rowspan="1" colspan="1"> Complete primary and secondary+</td>
<td rowspan="1" colspan="1">72</td>
<td rowspan="1" colspan="1">403</td>
<td rowspan="1" colspan="1">13.9 (9.6–18.2)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Wealth quintiles</td>
</tr>
<tr><td rowspan="1" colspan="1"> Lowest</td>
<td rowspan="1" colspan="1">53</td>
<td rowspan="1" colspan="1">161</td>
<td rowspan="1" colspan="1">30.9 (23.1–38.8)</td>
<td rowspan="1" colspan="1"><bold>3.24 (1.74–6.03)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0002</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">0.95 (0.27–3.32)</td>
<td rowspan="1" colspan="1">0.9398</td>
</tr>
<tr><td rowspan="1" colspan="1"> Second</td>
<td rowspan="1" colspan="1">52</td>
<td rowspan="1" colspan="1">147</td>
<td rowspan="1" colspan="1">31.4 (23.8–38.9)</td>
<td rowspan="1" colspan="1"><bold>3.31 (1.81–6.07)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0001</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1"><bold>0.0013</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">0.58 (0.16–2.09)</td>
<td rowspan="1" colspan="1">0.4077</td>
</tr>
<tr><td rowspan="1" colspan="1"> Middle</td>
<td rowspan="1" colspan="1">34</td>
<td rowspan="1" colspan="1">130</td>
<td rowspan="1" colspan="1">23.1 (15.1–31.1)</td>
<td rowspan="1" colspan="1"><bold>2.18 (1.16–4.09)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0155</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">0.98 (0.37–2.61)</td>
<td rowspan="1" colspan="1">0.962</td>
</tr>
<tr><td rowspan="1" colspan="1"> Fourth</td>
<td rowspan="1" colspan="1">25</td>
<td rowspan="1" colspan="1">129</td>
<td rowspan="1" colspan="1">18.2 (8.9–27.4)</td>
<td rowspan="1" colspan="1">1.61 (0.79–3.3)</td>
<td rowspan="1" colspan="1">0.1926</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">0.68 (0.30–1.57)</td>
<td rowspan="1" colspan="1">0.3659</td>
</tr>
<tr><td rowspan="1" colspan="1"> Highest</td>
<td rowspan="1" colspan="1">27</td>
<td rowspan="1" colspan="1">203</td>
<td rowspan="1" colspan="1">12.1 (6.8–17.5)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Province</td>
</tr>
<tr><td rowspan="1" colspan="1"> Nairobi</td>
<td rowspan="1" colspan="1">11</td>
<td rowspan="1" colspan="1">110</td>
<td rowspan="1" colspan="1">10.8 (2.1–19.5)</td>
<td rowspan="1" colspan="1">2.82 (0.73–10.88)</td>
<td rowspan="1" colspan="1">0.1325</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1"><bold>6.84 (1.19–39.27)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0309</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> Central</td>
<td rowspan="1" colspan="1">4</td>
<td rowspan="1" colspan="1">106</td>
<td rowspan="1" colspan="1">4.1 (0.2–8.1)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1"><bold>REF</bold>
</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Coast</td>
<td rowspan="1" colspan="1">32</td>
<td rowspan="1" colspan="1">89</td>
<td rowspan="1" colspan="1">39.2 (23.0–55.3)</td>
<td rowspan="1" colspan="1"><bold>15.00 (4.48–50.21)</bold>
</td>
<td rowspan="1" colspan="1"><bold>< 0.0001</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1"><bold>13.75 (3.80–49.65)</bold>
</td>
<td rowspan="1" colspan="1"><bold>< 0.0001</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> Eastern</td>
<td rowspan="1" colspan="1">22</td>
<td rowspan="1" colspan="1">77</td>
<td rowspan="1" colspan="1">29.9 (15.5–44.3)</td>
<td rowspan="1" colspan="1"><bold>9.92 (2.95–33.41)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0002</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1"><bold>10.51 (2.85–38.75)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0004</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> North Eastern</td>
<td rowspan="1" colspan="1">29</td>
<td rowspan="1" colspan="1">100</td>
<td rowspan="1" colspan="1">28.2 (21.8–34.6)</td>
<td rowspan="1" colspan="1"><bold>9.14 (3.20–26.14)</bold>
</td>
<td rowspan="1" colspan="1"><bold>< 0.0001</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1"><bold>5.10 (1.41–18.51)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0131</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> Nyanza</td>
<td rowspan="1" colspan="1">34</td>
<td rowspan="1" colspan="1">106</td>
<td rowspan="1" colspan="1">25.8 (13.0–38.7)</td>
<td rowspan="1" colspan="1"><bold>8.11 (2.42–27.03)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0007</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1"><bold>8.90 (2.46–32.22)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0009</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
</tr>
<tr><td rowspan="1" colspan="1"> Rift Valley</td>
<td rowspan="1" colspan="1">12</td>
<td rowspan="1" colspan="1">83</td>
<td rowspan="1" colspan="1">12.8 (1.3–24.2)</td>
<td rowspan="1" colspan="1">3.41 (0.81–14.33</td>
<td rowspan="1" colspan="1">0.0938</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">2.99 (0.68–13.10)</td>
<td rowspan="1" colspan="1">0.147</td>
</tr>
<tr><td rowspan="1" colspan="1"> Western</td>
<td rowspan="1" colspan="1">47</td>
<td rowspan="1" colspan="1">99</td>
<td rowspan="1" colspan="1">46.1 (34.0–58.2)</td>
<td rowspan="1" colspan="1"><bold>19.9 (6.54–60.58)</bold>
</td>
<td rowspan="1" colspan="1"><bold>< 0.0001</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1"><bold>< 0.0001</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1"><bold>21.13 (6.03–74.00)</bold>
</td>
<td rowspan="1" colspan="1"><bold>< 0.0001</bold>
<xref ref-type="table-fn" rid="TFN9"><bold>*</bold>
</xref>
</td>
</tr>
</tbody>
</table>
<table-wrap-foot><fn id="TFN7"><p>AOR = adjusted odds ratio; CI = confidence interval; SFGR = spotted fever group rickettsioses; REF = reference.</p>
</fn>
<fn id="TFN8"><p><italic>P</italic>
value is the category <italic>P</italic>
value, G <italic>P</italic>
value is the global <italic>P</italic>
value for the bivariate variable, M <italic>P</italic>
value is the category multivariate <italic>P</italic>
value.</p>
</fn>
<fn id="TFN9"><label>*</label>
<p>Bold values have significant <italic>P</italic>
values.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T4" position="float"><label>Table 4</label>
<caption><p>Interaction terms fitted into the SFGR model</p>
</caption>
<table frame="hsides" rules="groups"><thead><tr><th align="center" rowspan="1" colspan="1">Variable</th>
<th align="center" rowspan="1" colspan="1">AOR (95% CI)</th>
<th align="center" rowspan="1" colspan="1">M <italic>P</italic>
value</th>
</tr>
</thead>
<tbody><tr><td colspan="3" rowspan="1">Residence by education level</td>
</tr>
<tr><td rowspan="1" colspan="1"> Rural/no primary</td>
<td rowspan="1" colspan="1">0.35 (0.025–5.01)</td>
<td rowspan="1" colspan="1">0.4399</td>
</tr>
<tr><td rowspan="1" colspan="1"> Urban/complete primary and secondary+</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1">Education level by wealth quintiles</td>
<td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1"></td>
</tr>
<tr><td rowspan="1" colspan="1"> Lowest/incomplete primary</td>
<td rowspan="1" colspan="1">0.63 (0.11–3.67)</td>
<td rowspan="1" colspan="1">0.606</td>
</tr>
<tr><td rowspan="1" colspan="1"> Second/incomplete primary</td>
<td rowspan="1" colspan="1">1.55 (0.29–8.31)</td>
<td rowspan="1" colspan="1">0.6097</td>
</tr>
<tr><td rowspan="1" colspan="1"> Middle/incomplete primary</td>
<td rowspan="1" colspan="1">1.02 (0.20–5.13)</td>
<td rowspan="1" colspan="1">0.9821</td>
</tr>
<tr><td rowspan="1" colspan="1"> Fourth/incomplete primary</td>
<td rowspan="1" colspan="1">1.19 (0.26–5.39)</td>
<td rowspan="1" colspan="1">0.826</td>
</tr>
<tr><td rowspan="1" colspan="1"> Lowest/no primary</td>
<td rowspan="1" colspan="1">0.81 (0.02–27.08)</td>
<td rowspan="1" colspan="1">0.9083</td>
</tr>
<tr><td rowspan="1" colspan="1"> Second/no primary</td>
<td rowspan="1" colspan="1">2.14 (0.06–74.15)</td>
<td rowspan="1" colspan="1">0.6736</td>
</tr>
<tr><td rowspan="1" colspan="1"> Middle/no primary</td>
<td rowspan="1" colspan="1">0.48 (0.01–17.92)</td>
<td rowspan="1" colspan="1">0.6888</td>
</tr>
<tr><td rowspan="1" colspan="1"> Fourth/no primary</td>
<td rowspan="1" colspan="1">1.55 (0.14–17.35)</td>
<td rowspan="1" colspan="1">0.7241</td>
</tr>
<tr><td rowspan="1" colspan="1"> Highest/complete primary and secondary+</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">REF</td>
</tr>
</tbody>
</table>
<table-wrap-foot><fn id="TFN10"><p>AOR = adjusted odds ratio; CI = confidence interval; SFGR = spotted fever group rickettsioses; REF = reference.</p>
</fn>
<fn id="TFN11"><p>M <italic>P</italic>
value is the category multivariate <italic>P</italic>
value.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T5" position="float"><label>Table 5</label>
<caption><p>Bivariate and multivariate analysis of factors associated with previous exposure to TGR</p>
</caption>
<table frame="hsides" rules="groups"><thead><tr><th align="center" rowspan="1" colspan="1">Variable</th>
<th align="center" rowspan="1" colspan="1">Positive (<italic>n</italic>
)</th>
<th align="center" rowspan="1" colspan="1">Total (<italic>N</italic>
)</th>
<th align="center" rowspan="1" colspan="1">% Positive (95% CI)</th>
<th align="center" rowspan="1" colspan="1">Unadjusted OR (95% CI)</th>
<th align="center" rowspan="1" colspan="1"><italic>P</italic>
value</th>
<th align="center" rowspan="1" colspan="1">G <italic>P</italic>
value</th>
<th align="center" rowspan="1" colspan="1">AOR (95% CI)</th>
<th align="center" rowspan="1" colspan="1">M <italic>P</italic>
value</th>
</tr>
</thead>
<tbody><tr><td colspan="9" rowspan="1">Residence</td>
</tr>
<tr><td rowspan="1" colspan="1"> Rural</td>
<td rowspan="1" colspan="1">8</td>
<td rowspan="1" colspan="1">558</td>
<td rowspan="1" colspan="1">0.5 (0.1–1.0)</td>
<td rowspan="1" colspan="1">0.5541 (0.1256–2.4452)</td>
<td rowspan="1" colspan="1">0.4357</td>
<td rowspan="1" colspan="1">0.4357</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Urban</td>
<td rowspan="1" colspan="1">4</td>
<td rowspan="1" colspan="1">212</td>
<td rowspan="1" colspan="1">1.0 (0.0–2.2)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Sex</td>
</tr>
<tr><td rowspan="1" colspan="1"> Male</td>
<td rowspan="1" colspan="1">3</td>
<td rowspan="1" colspan="1">317</td>
<td rowspan="1" colspan="1">0.5 (0.0–1.1)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Female</td>
<td rowspan="1" colspan="1">9</td>
<td rowspan="1" colspan="1">453</td>
<td rowspan="1" colspan="1">0.8 (0.3–1.4)</td>
<td rowspan="1" colspan="1">1.73 (0.48–6.29)</td>
<td rowspan="1" colspan="1">0.4045</td>
<td rowspan="1" colspan="1">0.4045</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Age (in years)</td>
</tr>
<tr><td rowspan="1" colspan="1"> 15–29</td>
<td rowspan="1" colspan="1">5</td>
<td rowspan="1" colspan="1">368</td>
<td rowspan="1" colspan="1">0.7 (0.2–1.2)</td>
<td rowspan="1" colspan="1">1.93 (0.56–6.72)</td>
<td rowspan="1" colspan="1">0.3002</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> 30–49</td>
<td rowspan="1" colspan="1">3</td>
<td rowspan="1" colspan="1">285</td>
<td rowspan="1" colspan="1">0.4 (0.0–0.8)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> 50–64</td>
<td rowspan="1" colspan="1">4</td>
<td rowspan="1" colspan="1">117</td>
<td rowspan="1" colspan="1">1.5 (0.0–3.4)</td>
<td rowspan="1" colspan="1">4.12 (0.81–20.99)</td>
<td rowspan="1" colspan="1">0.0886</td>
<td rowspan="1" colspan="1">0.229</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Education level</td>
</tr>
<tr><td rowspan="1" colspan="1"> No primary</td>
<td rowspan="1" colspan="1">5</td>
<td rowspan="1" colspan="1">156</td>
<td rowspan="1" colspan="1">0.9 (0.0–2.0)</td>
<td rowspan="1" colspan="1">1.76 (0.34–9.12)</td>
<td rowspan="1" colspan="1">0.5028</td>
<td rowspan="1" colspan="1">0.794</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Some primary</td>
<td rowspan="1" colspan="1">3</td>
<td rowspan="1" colspan="1">211</td>
<td rowspan="1" colspan="1">0.7 (0.0–1.5)</td>
<td rowspan="1" colspan="1">1.38 (0.25–7.57)</td>
<td rowspan="1" colspan="1">0.7132</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Complete primary and secondary+</td>
<td rowspan="1" colspan="1">4</td>
<td rowspan="1" colspan="1">403</td>
<td rowspan="1" colspan="1">0.5 (0.0–1.2)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Wealth quintiles</td>
</tr>
<tr><td rowspan="1" colspan="1"> Lowest</td>
<td rowspan="1" colspan="1">5</td>
<td rowspan="1" colspan="1">161</td>
<td rowspan="1" colspan="1">1.2 (0.1–2.3)</td>
<td rowspan="1" colspan="1"><bold>7.35 (1.09–49.75)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.041</bold>
<xref ref-type="table-fn" rid="TFN14"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Second</td>
<td rowspan="1" colspan="1">1</td>
<td rowspan="1" colspan="1">147</td>
<td rowspan="1" colspan="1">0.2 (0.0–0.5)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Middle</td>
<td rowspan="1" colspan="1">1</td>
<td rowspan="1" colspan="1">130</td>
<td rowspan="1" colspan="1">0.3 (0.0–0.8)</td>
<td rowspan="1" colspan="1">1.54 (0.09–27.19)</td>
<td rowspan="1" colspan="1">0.7663</td>
<td rowspan="1" colspan="1">0.1108</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Fourth</td>
<td rowspan="1" colspan="1">4</td>
<td rowspan="1" colspan="1">129</td>
<td rowspan="1" colspan="1">1.3 (0.0–3.1)</td>
<td rowspan="1" colspan="1">8.21 (0.69–97.30)</td>
<td rowspan="1" colspan="1">0.0952</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Highest</td>
<td rowspan="1" colspan="1">1</td>
<td rowspan="1" colspan="1">203</td>
<td rowspan="1" colspan="1">0.4 (0.0–1.2)</td>
<td rowspan="1" colspan="1">2.46 (0.14–42.98)</td>
<td rowspan="1" colspan="1">0.5382</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td colspan="9" rowspan="1">Province</td>
</tr>
<tr><td rowspan="1" colspan="1"> Nairobi</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Central</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Coast</td>
<td rowspan="1" colspan="1">10</td>
<td rowspan="1" colspan="1">89</td>
<td rowspan="1" colspan="1">7.2 (1.1–13.4)</td>
<td rowspan="1" colspan="1"><bold>23.16 (2.14</bold>
–<bold>250.24)</bold>
</td>
<td rowspan="1" colspan="1"><bold>0.0097</bold>
<xref ref-type="table-fn" rid="TFN14"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Eastern</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> North Eastern</td>
<td rowspan="1" colspan="1">1</td>
<td rowspan="1" colspan="1">100</td>
<td rowspan="1" colspan="1">0.3 (0.0–1.1)</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">REF</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Nyanza</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Rift Valley</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
<tr><td rowspan="1" colspan="1"> Western</td>
<td rowspan="1" colspan="1">1</td>
<td rowspan="1" colspan="1">99</td>
<td rowspan="1" colspan="1">0.7 (0.0–2.0)</td>
<td rowspan="1" colspan="1">1.94 (0.10–37.96)</td>
<td rowspan="1" colspan="1">0.6601</td>
<td rowspan="1" colspan="1"><bold>0.0064</bold>
<xref ref-type="table-fn" rid="TFN14"><bold>*</bold>
</xref>
</td>
<td rowspan="1" colspan="1">–</td>
<td rowspan="1" colspan="1">–</td>
</tr>
</tbody>
</table>
<table-wrap-foot><fn id="TFN12"><p>AOR = adjusted odds ratio; CI = confidence interval; TGR = typhus group rickettsioses; REF = reference.</p>
</fn>
<fn id="TFN13"><p><italic>P</italic>
value is the category <italic>P</italic>
value, G <italic>P</italic>
value is the global <italic>P</italic>
value for the bivariate variable, M <italic>P</italic>
value is the category multivariate <italic>P</italic>
value.</p>
</fn>
<fn id="TFN14"><label>*</label>
<p>Bold values have significant <italic>P</italic>
values.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</floats-group>
</pmc>
<affiliations><list></list>
<tree><noCountry><name sortKey="Abudo, Mamo U" sort="Abudo, Mamo U" uniqKey="Abudo M" first="Mamo U." last="Abudo">Mamo U. Abudo</name>
<name sortKey="Breiman, Robert F" sort="Breiman, Robert F" uniqKey="Breiman R" first="Robert F." last="Breiman">Robert F. Breiman</name>
<name sortKey="Fields, Barry S" sort="Fields, Barry S" uniqKey="Fields B" first="Barry S." last="Fields">Barry S. Fields</name>
<name sortKey="Juma, Bonventure W" sort="Juma, Bonventure W" uniqKey="Juma B" first="Bonventure W." last="Juma">Bonventure W. Juma</name>
<name sortKey="Kim, Andrea A" sort="Kim, Andrea A" uniqKey="Kim A" first="Andrea A." last="Kim">Andrea A. Kim</name>
<name sortKey="Montgomery, Joel M" sort="Montgomery, Joel M" uniqKey="Montgomery J" first="Joel M." last="Montgomery">Joel M. Montgomery</name>
<name sortKey="Musyoka, Raymond N" sort="Musyoka, Raymond N" uniqKey="Musyoka R" first="Raymond N." last="Musyoka">Raymond N. Musyoka</name>
<name sortKey="Omballa, Victor O" sort="Omballa, Victor O" uniqKey="Omballa V" first="Victor O." last="Omballa">Victor O. Omballa</name>
<name sortKey="Vittor, Amy Y" sort="Vittor, Amy Y" uniqKey="Vittor A" first="Amy Y." last="Vittor">Amy Y. Vittor</name>
<name sortKey="Wachira, Cyrus M" sort="Wachira, Cyrus M" uniqKey="Wachira C" first="Cyrus M." last="Wachira">Cyrus M. Wachira</name>
<name sortKey="Waiboci, Lilian W" sort="Waiboci, Lilian W" uniqKey="Waiboci L" first="Lilian W." last="Waiboci">Lilian W. Waiboci</name>
<name sortKey="Wamburu, Kabura B" sort="Wamburu, Kabura B" uniqKey="Wamburu K" first="Kabura B." last="Wamburu">Kabura B. Wamburu</name>
</noCountry>
</tree>
</affiliations>
</record>
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