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“The Cango Lyec Project - Healing the Elephant”: HIV related vulnerabilities of post-conflict affected… Malamba, Samuel S; Muyinda, Herbert; Spittal, Patricia M; Ekwaru, John P; Kiwanuka, Noah; Ogwang, Martin D; Odong, Patrick; Kitandwe, Paul K; Katamba, Achilles; Jongbloed, Kate; Sewankambo, Nelson K; Kinyanda, Eugene; Blair, Alden; Schechter, Martin T Nov 21, 2016

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RESEARCH ARTICLE Open Access“The Cango Lyec Project - Healing theElephant”: HIV related vulnerabilities ofpost-conflict affected populations aged13–49 years living in three Mid-NorthernUganda districtsSamuel S. Malamba1,11*, Herbert Muyinda2, Patricia M. Spittal3, John P. Ekwaru4, Noah Kiwanuka5,8,Martin D. Ogwang6,7, Patrick Odong7, Paul K. Kitandwe5, Achilles Katamba8, Kate Jongbloed3,Nelson K. Sewankambo8, Eugene Kinyanda9,10, Alden Blair3 and Martin T. Schechter3AbstractBackground: The protracted war between the Government of Uganda and the Lord’s Resistance Army in NorthernUganda (1996–2006) resulted in widespread atrocities, destruction of health infrastructure and services, weakening thesocial and economic fabric of the affected populations, internal displacement and death. Despite grave concerns thatincreased spread of HIV/AIDS may be devastating to post conflict Northern Uganda, empirical epidemiological datadescribing the legacy of the war on HIV infection are scarce.Methods: The ‘Cango Lyec’ Project is an open cohort study involving conflict-affected populations living in three districtsof Gulu, Nwoya and Amuru in mid-northern Uganda. Between November 2011 and July 2012, 8 study communitiesrandomly selected out of 32, were mapped and house-to-house census conducted to enumerate the entire communitypopulation. Consenting participants aged 13–49 years were enrolled and interviewer-administered data were collected ontrauma, depression and socio-demographic-behavioural characteristics, in the local Luo language. Venous blood wastaken for HIV and syphilis serology. Multivariable logistic regression was used to determine factors associated with HIVprevalence at baseline.Results: A total of 2954 participants were eligible, of whom 2449 were enrolled. Among 2388 participants with knownHIV status, HIV prevalence was 12.2% (95%CI: 10.8-13.8), higher in females (14.6%) than males (8.5%, p < 0.001), higher inGulu (15.2%) than Nwoya (11.6%, p < 0.001) and Amuru (7.5%, p = 0.006) districts. In this post-conflict period, HIVinfection was significantly associated with war trauma experiences (Adj. OR = 2.50; 95%CI: 1.31–4.79), the psychiatricproblems of PTSD (Adj. OR = 1.44; 95%CI: 1.06–1.96), Major Depressive Disorder (Adj. OR = 1.89; 95%CI: 1.28–2.80) andsuicidal ideation (Adj. OR = 1.87; 95%CI: 1.34–2.61). Other HIV related vulnerabilities included older age, being married,separated, divorced or widowed, residing in an urban district, ulcerative sexually transmitted infections, and staying in afemale headed household. There was no evidence in this study to suggest that people with a history of abductionwere more likely to be HIV positive.(Continued on next page)* Correspondence: malambas@gmail.com1Uganda Virus Research Institute (UVRI) - HIV Reference Laboratory Program,Entebbe, Uganda11Northern Uganda Program on Health Sciences, c/o Uganda Virus ResearchInstitute, HIV Reference Laboratory, P.O. Box 49, Entebbe, Kampala, UgandaFull list of author information is available at the end of the article© The Author(s). 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Malamba et al. BMC Infectious Diseases  (2016) 16:690 DOI 10.1186/s12879-016-2030-0(Continued from previous page)Conclusions: HIV prevalence in this post conflict-affected population is high and is significantly associated with age,trauma, depression, history of ulcerative STIs, and residing in more urban districts. Evidence-based HIV/STI preventionprograms and culturally safe, gender and trauma-informed are urgently needed.Keywords: HIV, Prevalence, Risk factors, Post conflict, Northern UgandaBackgroundIn Northern Uganda, protracted war between the Gov-ernment of Uganda and the Lord’s Resistance Army(LRA) resulted in widespread atrocities, rights violations,displacement and death. Between 2004 and 2006, morethan 1.8 million people – accounting for over 90% of thepopulation – were forcibly displaced into Internally Dis-placed People (IDP) camps where they were entirelydependent upon relief aid and services [1]. Signing ofthe ‘Cessation of Hostilities Agreement’ in 2006 initiatedreturn migration of IDPs to their ancestral homes [2].Currently, the majority of IDP camps have closed and asof December 2010, more than 90% of IDPs who wereencamped at the height of the conflict had returned totheir traditional homesteads.The Uganda AIDS Indicator Survey 2011 estimated anHIV prevalence of 8.3% among people aged 15–49 yearsin the entire mid-Northern region, nearly double the low-est regional HIV prevalence of 4.1% for mid-EasternUganda [3]. Data collected through antenatal care in Guludistrict – one of the most conflict-affected areas in North-ern Uganda – estimated HIV prevalence to be at 10.3% in2006 [4, 5]. However, well-established concerns that ANCdata may significantly underestimate the true prevalenceof HIV remain [6–9]. Further, as available data are limitedto the regional level, detailed HIV prevalence estimates inareas and sub-groups most affected by the conflict are ur-gently required to provide reliable estimates that wouldguide prevention and care programmatic activities. Thenew UNAIDS 90-90-90 targets call for rapid scale-up ofHIV treatment and an end to the epidemic in 2030. Forthese goals to be met, substantial improvements in redu-cing gaps in HIV prevalence data for key populations,including those affected by conflict, are critical.The relationship between HIV/AIDS and conflict iscomplex [10]. On one hand, conflict may decrease HIVrisk by reducing mobility and improving social service inIDP camp settings [6, 11, 12]. On the other hand, it mayincrease vulnerability through increased sexual violence,breakdown of social service, and disrupted health infra-structure [12]. War-related vulnerability may make indi-viduals more susceptible to infection (i.e. due to changesin biological and environmental factors), while also in-creasing the risk of exposure (i.e. population movement,poverty, increased sexual and physical violence) [6].However, risks and protective factors influencing HIVvulnerability in post-conflict settings are not well under-stood, particularly the impact of psychological conse-quences of war and relocation.Exposure to war-related sexual violence in NorthernUganda has been well documented [13–17], yet the ex-tent to which it has heightened HIV vulnerability in theregion is unknown [14]. Estimates suggest that between25000 and 66000 children aged 6–13 were abducted duringthe conflict, profoundly impacting the physical and socialwellbeing of young people in the post-conflict era [18].Abductees were forced to serve as child soldiers, labourers,and sex slaves [18]. Premenstrual girls in particular are be-lieved to have been at increased risk of abduction, as theywere considered less likely to be living with HIV [19].Sexual violence has also been documented in and near IDPcamp settings, including alarming levels of sexual violenceand mass rape by armed forces on the outskirts of camps[13, 16, 20]. Of note, a significant percentage of boysand men were also victims of war-related sexual vio-lence [21–24]. A recent study among young peopleaged 15–29 living in post-emergency phase transitcamps in Gulu district found that the strongest pre-dictor of HIV infection was non-consensual sexual de-but, and that this risk factor was reported by over 25%of young women and nearly 8% of young men [25].With prevailing peace in Northern Uganda, trade be-tween the South Sudan and Northern Uganda is booming.A consequence of this new post-war economy involvescross-border movement of truckers, agricultural traders,and cattle-loaders. Simultaneously, withdrawal of food pro-grams that were central to relief efforts in camps and a re-cent drought and crop failure raised concerns about highlevels of food insecurity reportedly worse than at the heightof insurgency [26–30]. There is growing recognition thatpoverty and food insecurity may be key drivers of the HIVepidemic by increasing sex-related vulnerabilities includingsubsistence, intergenerational, and coerced sex [6, 31–34].Further, young people disconnected from traditional liveli-hoods after prolonged displacement must now find theirway in the post-conflict setting. Consequently, increasedlevels of transactional and subsistence sex have been re-ported all along the Kampala-Juba highway, including inGulu, Atiak and Bibia [35]. While sex work was certainlypart of life before the war, it is now a source of growingdiscussion, disquiet, and even tension within some commu-nities due to its relationship to HIV infection.Malamba et al. BMC Infectious Diseases  (2016) 16:690 Page 2 of 13Concerns of a growing HIV epidemic led Ugandanand Canadian investigators to initiate the ‘Cango Lyec’Project study involving Acholi people in NorthernUganda at risk of HIV in the aftermath of a long rebel-led civil war. The longitudinal 5-year cohort sought todetermine population-wide HIV prevalence and risk fac-tors to inform the development of prevention programs.This paper reports baseline HIV prevalence and corre-lates of HIV infection from Amuru, Gulu and NwoyaDistricts, Northern Uganda.MethodsStudy design and settingThis paper reports baseline findings of a 5-year prospectiveopen cohort study involving a representative sample ofconflict-affected people living in the former Gulu district,which was later sub-divided to create Amuru, Gulu, andNwoya Districts, Northern Uganda. Baseline field activitieswere conducted between November 2011 and July 2012.Sample size calculationThe required sample was calculated using the formula: n¼ zm 2p^ 1−p^ð Þ  deffR [36]. This gave a total sample size ad-justed to 2400 to take care of possible non-response (R)and sampling design effect (deff), assuming a design effect(deff) of 2 and a response rate (R) of 98.7% based on previ-ous studies that were conducted in rural South WestUganda, ‘m’ being the level of precision desired. This sam-ple size would produce a two-sided 95% confidence interval(Alpha = 0.05) with a width ranging from 2.0 to 2.3%around the point estimate when the overall prevalence ofHIV infection ranges between 6.4 and 9.1% in all communi-ties combined.Selection of study communities and populationA two-stage stratified sampling method was used to ran-domly select three study communities in each district, onefrom each settlement category. All communities in thethree districts were listed; all major settlements weremapped and categorized as either permanent, transient ordisplaced. Settlements created to accommodate IDP duringthe war were categorized as displaced communities; Settle-ments created to accommodate IDP returning to their over-grown gardens and destroyed houses were categorized astransient communities and settlements which were therebefore the war and residents were never displaced were cat-egorized to as Permanent. Amuru district had 10 commu-nities (6 permanent, 2 transient, 2 displaced); Gulu districthad 16 communities (10 permanent, 2 transient, 3 dis-placed, 1 pilot community) and Nwoya district had sevencommunities (4 permanent, 3 transient, 0 displaced). Atotal of eight study communities were selected from 32listed communities excluding the pilot community. Onecommunity was purposively selected for the purposes ofpiloting questionnaires and survey tools. Information ob-tained from residents of this pilot community were not in-cluded in the study analyses but was used to identifysensitivities individuals or communities had to some ques-tions and to inform changes to the final survey tools. Com-munities with large population sizes (>250 adults) likeAwach and Layibi were sub-divided by villages\divisionswhich were randomly selected to represent these commu-nities and contributed household numbers proportional tosize of the communities they represent as compared to thepopulations of other selected communities to fit within theestimated study sample size of 2400 individuals. Only twocommunities were selected in Nwoya district because it didnot have any categorized as ‘displaced’. All households inthe selected communities were mapped and a householdcensus was completed to establish the number and thedemographic characteristics of all individuals (N = 6375). A“take all” approach was used to survey all consenting indi-viduals aged 13–49 years who had been residents in the se-lected communities for the last month. We used the 13–49year age-group for two main reasons. 1) To be able to com-pare our prevalence estimates with the Uganda AIDS Indi-cator Survey 2011 and 2) to increase our power ofestimating HIV incidence since HIV-infections mostlyoccur in this age range.Data collection proceduresThe study team was trained on the key components of thestudy protocol including the study objectives, consentingprocedures, administration of the study questionnaire,counselling and the referral process for those respondentsfound to have HIV, syphilis, PTSD or depression.Laboratory testingTwo ELISA tests, Vironostika HIV Uni-Form II plus O(Biomerieux SA, Marcy l’Etoile, France) and Murex HIV-1.2.O (Diasorin S.P.A, Dartford, United Kingdom) wereused in parallel to test for HIV infection at the UgandaVirus Research Institute IAVI-laboratory. The WesternBlot (Genetic Systems, Bio-Rad Laboratories) was used asa tiebreaker if the ELISA results were discordant. Indeter-minate Western Blot results not resolved by the time ofthis analysis were excluded. Samples screening positive forsyphilis using the rapid plasma regain (RPR) test weresubjected to a confirmatory treponema pallidum haem-agglutination test (TPHA).Data collection toolsBlood specimen collection was used to determine HIVprevalence and was linked with a questionnaire assessingsocio-demographic characteristics, conflict-related experi-ences and sexual behaviours. Questionnaires were trans-lated into local language (Luo) through a process ofMalamba et al. BMC Infectious Diseases  (2016) 16:690 Page 3 of 13forward and backward translation by an experienced teamof health professionals working independently. Where therewas a wide disparity, translations were discussed and re-vised to bring out the intended meaning. Given that somequestions may elicit memories of significant trauma andvictimization, participants who requested care were referredto Trauma Clinics in the study area. Part I and IV of theHarvard Trauma Questionnaire (HTQ) were used to meas-ure post-traumatic stress disorder (PTSD). PTSD scoreswere calculated using the sum of all answered items in PartIV divided by the number of answered items. Scores ≥2.0were classified as meeting the criteria for screening positivefor PTSD [37–39]. The Hopkins Symptom Check List-25(HSCL-25) was used to measure major depressive disorder(MDD). Participants with a mean score of ≥1.75 on Part IIwere classified as meeting the criteria for screening positivefor MDD [37–39]. Luo versions of the HTQ and HSCL-25,as developed and validated by Roberts et al. for use in Guludistrict, Uganda, were adopted [37, 38]. Calculation ofscores on the HTQ and the HSCL was carried out usingpublished guidelines for these instruments. Experiences ofwar events in Northern Uganda were collected using a 15-item War Trauma Experience Check-list (WETC-15) in-strument. Scores on the WTEC-15 were dichotomized; ≤12vs. >12 severe traumatic events based on a previous studyby Roberts [21].Statistical analysisData were entered in duplicate using Microsoft Access soft-ware and analysed using SAS 9.4 software (SAS Institute,Cary, NC, USA). Unadjusted and multivariable logisticregression models were used to determine variables inde-pendently associated with HIV infection. All factors includ-ing socio-demographic, medical, laboratory, psycho-socialand war-related trauma associated with HIV sero-positivityat a ≤0.1 level of significance in the unadjusted models wereentered into a multivariable model that adjusted for differ-ences in age, gender, marital status, religion, education, anddistrict of residence. A stepwise regression procedure thatdropped, at each step, variables that did not reach the <0.1level of significance was used to develop the multivariablemodels excluding factors considered to be on the causalpathway and including factors that were associated withHIV sero-positivity at p < 0.05 in the final model for eachpotential risk factor. A likelihood ratio test was used tocheck for interactions and determine the model that bestfits the data. Unadjusted and adjusted odds ratios of preva-lent HIV infection are reported. To account for the add-itional variance due to the complex two-stage samplingstudy design that included stratification by the three settle-ment types and the three study districts, and the unequalselection probabilities and clustering, survey analysis proce-dures in SAS were used. Communities were the primarysampling units (PSU) and the stratification variables werethe settlement type and the district. The sampling weightswere based on the selection probabilities at each level ofselection and on the proportion of survey participantsconsenting for interview and HIV testing. For independentcategorical variables, we included a missing value categoryto minimize list-wise deletion of observation in the models.All 61 indeterminate HIV test results (Outcome variable)were considered missing, and were excluded from theanalysis.Ethics, consent and permissionsEthical approvals were obtained from the University ofBritish Columbia-Providence Healthcare Research EthicsBoard (Canada), Makerere University College of HealthSciences-School of Public Health Science Ethical Commit-tee, Uganda Virus Research Institute-Science and EthicsCommittee, and Uganda National Council for Science andTechnology. The Office of the President of Uganda issueda letter, which was signed by the Resident District Com-missioner in each district and from all participating dis-trict authorities. Informed written consent was alsoobtained from all eligible study participants aged 13–49years after explaining the objectives and procedures of thestudy. Parental/legal guardian’s written consent for<18 years with minor’s assent were also obtained. Everyparticipant was properly counselled and consented beforebeing asked to sign or put a fingerprint on the consentform if they were not able to write. Study participantswere assured of confidentiality before the start of eachinterview. All data collected was kept under lock and keyonly accessible to the research team.ResultsStudy populationFrom a household census of 6375 residents, 2976 individ-uals were not surveyed because they were less than 13 orgreater than 49 years old, 434 were non-residents and 11were absent or had out-migrated between the time of con-ducting the household census and the survey. A total of2954 individuals were eligible, of whom 2449 (82.9%) con-sented to participate (Amuru district = 732, Gulu district= 1159 and Nwoya district = 558). A total of 61 recordswith indeterminate HIV Western Blot results wereexcluded from any analysis modelling HIV (Fig. 1).Socio-demographic characteristics of the respondents byHIV sero-statusTable 1 shows the distribution of socio-demographiccharacteristics of all enrolled study participants with de-termined HIV status. The study population was mostlyfemale (59.7%) and the majority (81.4%) were less than35 years old with a median age of 25 years (IQR: 18–32).Of the 857 men who responded to the circumcision sta-tus question, only 72 (8.4%) self-reported that they wereMalamba et al. BMC Infectious Diseases  (2016) 16:690 Page 4 of 13circumcised. Slightly more than two thirds of partici-pants (67.6%) were residing in communities which wereformerly displaced or transient camps. Almost one fifth(21.9%) had ever been abducted and only 11.1% hadconsistently used a condom with their last three sexualpartners in the last 12 months. A substantial proportion(71.9%) was Roman Catholic, 53% were currentlymarried, 13.1% had never received any form of formaleducation, 9.3% reported genital ulcers in the last12 months and 4.2% (95%CI: 3.3–5.2) tested positive foractive syphilis. One in eight participants was staying in afemale-headed household and 8.0% were residing in achild (<25 years) headed household.The prevalence of HIV infection was 12.2% (95%CI:7.6–18.8) overall; 14.6% (95% CI: 9.3–22.2) in femalesand 8.5% (95%CI: 5.6–12.7) in males (p < 0.001). HIVprevalence was higher in females than that in males inall age-groups below 45 years but this difference wasonly significantly higher below the age of 30 years(Table 2).HIV infection and mental healthEight percent (95%CI: 6.4–10.0) of participants had experi-enced rape or sexual abuse, 14.9% (95%CI: 12.6–17.5)screened positive for MDD, 11.9% (95%CI: 8.8–15.9)screened positive for PTSD, 8.8% reported experience of 12or more traumatic events ever and 11.7% (95%CI: 9.7–14.0)reported suicidal ideation. HIV sero-positivity was higheramong individuals who reported ever experiencing trau-matic events like rape or sexual abuse, ill health withoutmedical care, and suicidal ideation within the last 2 weeks.Study participants classified to have MDD (AOR= 1.89;95%CI: 1.28–2.80), PTSD (AOR= 1.44; 95%CI: 1.06–1.96),war trauma experiences (Adj. OR = 2.50; 95%CI: 1.31–4.79)and suicidal ideation (Adj. OR = 1.87; 95%CI: 1.34–2.61)were more likely to be living with HIV than those classifiednot to have these conditions (Table 3).Socio-behavioural, sexual histories and STI related riskfactors for HIVAdditional risk factors significantly associated with HIVinfection in the multivariable analysis were: older age, res-iding in an urban district, being married, being separated,divorced or widowed, staying in a female headed house-hold and consistent condom use in the last 12 months(Table 4.) HIV infection was higher among participantswho consistently used condoms with their last 3 partnerscombined in the past 12 months as compared to thosewho inconstantly used condoms (AOR = 2.10; 95%CI:1.38–3.18). Consistent condom use in the last relationshipwas significantly associated with a higher odds of HIV in-fection (OR = 1.38; 95%CI: 1.22–1.55) but not for the sec-ond and third last relationships. HIV sero-positivityamong those who were married (AOR = 4.69; (95%CI:3.25–6.76), separated/divorced (AOR = 9.17; 95%CI: 5.60–15.00) or widowed (AOR = 20.35; (95%CI: 10.27–40.34)considerably exceeds those who were single (never mar-ried). Staying in female-headed households was associatedwith higher HIV sero-positivity (AOR = 2.30; (95%CI:1.34–3.94). Active syphilis was confirmed among 98(4.2%) participants. In the multivariable models, genital ul-cers in the past 12 months (AOR = 3.33, 95%CI: 2.58,4.28) and active syphilis (AOR = 3.55; 95%CI: 1.59–7.93)remained significantly associated with HIV (Table 4).Fig. 1 Participant enrolment flow diagram and reason for not enrolling. Legend: Study participants’ enrolment flow diagram in the Cango Lyecstudy, mid-northern Uganda districts of Amuru, Gulu and Nwoya, 2011/2012. Approximately 81% of the eligible participants were analysed and98% of those who consented were analysedMalamba et al. BMC Infectious Diseases  (2016) 16:690 Page 5 of 13Table 1 HIV-1 sero-positivity by population socio-demographic characteristics and sexual history at baselinePopulationcharacteristicsTotal Weighted (%) Unadjusted(N = 2388) (%) 95% CI HIV+ (%) OR (95%CI) p-valueAge group13–19 723 29.1 (23.5–35.5) 15 (2.2%) 1.0020–24 443 20.2 (13.1–29.7) 40 (8.5%) 4.24 (1.81,9.93) 0.00525–29 442 19.6 (16.4–23.4) 58 (14.0%) 7.43 (3.62,15.24) <.00130–34 315 12.4 (11.0–14.1) 61 (21.7%) 12.60 (5.98,26.52) <.00135+ 465 18.6 (14.9–23.1) 103 (23.4%) 13.87 (7.79,24.70) <.001SexMale 991 40.3 (34.1–46.8) 77 (8.5%) 1.00Female 1397 59.7 (53.2–65.9) 200 (14.6%) 1.84 (1.50,2.25) <.001Current marital statusNever married 739 31.7 (26.6–37.2) 13 (1.8%) 1.00Married 1248 53.0 (46.6–59.3) 180 (15.0%) 9.51 (7.51,12.05) <.001Separated/divorced 185 8.2 (4.7–14.1) 41 (24.8%) 17.70 (9.90,31.65) <.001Widowed 65 2.5 (1.8–3.3) 31 (49.1%) 51.80 (29.11,92.17) <.001Missing 151 4.6 (0.4–34.4) 12 (7.4%) 4.28 (1.38,13.28) 0.019Highest education attainedNever 350 13.1 (5.2–29.3) 40 (12.6%) 1.00Primary 1333 55.5 (47.4–63.2) 182 (14.6%) 1.19 (0.69,2.02) 0.477Sec/Tertiary/University 638 28.3 (17.7–42.0) 48 (7.7%) 0.58 (0.28,1.18) 0.112Others 67 3.2 (1.4–7.2) 7 (6.6%) 0.49 (0.05,4.42) 0.468ReligionRoman Catholic 1690 71.9 (62.0–80.0) 207 (12.7%) 1.00Protestant 358 14.0 (9.4–20.5) 48 (14.1%) 1.13 (0.48,2.66) 0.748Moslem 28 1.2 (0.5–2.7) 4 (19.6%) 1.67 (0.92,3.04) 0.080Other 178 9.1 (5.0–15.9) 10 (6.5%) 0.48 (0.21,1.10) 0.073Missing 134 3.8 (0.2–40.3) 8 (5.9%) 0.43 (0.22,0.87) 0.025District of residenceAmuru 703 33.7 (4.7–83.9) 53 (7.5%) 1.00Gulu 1139 53.3 (9.0–93.0) 160 (15.2%) 2.21 (1.68,2.91) <.001Nwoya 546 12.9 (1.1–66.8) 64 (11.6%) 1.62 (1.49,1.76) <.001Community displacement statusDisplaced 333 12.9 (5.5–27.3) 28 (8.6%) 1.00Transient 1122 54.7 (20.7–84.8) 148 (14.7%) 1.84 (1.12,3.04) 0.023Permanent 933 32.4 (8.8–70.6) 101 (9.3%) 1.09 (0.69,1.72) 0.669Staying in a child (<25) headed householdNo 1658 61.3 (21.7–90.0) 181 (10.7%) 1.00Yes 240 8.0 (4.1–15.2) 11 (5.3%) 0.46 (0.30,0.73) 0.005Missing 490 30.7 (4.8–79.5) 85 (16.8%) 1.69 (1.09,2.61) 0.026Staying in a female headed householdNo 1524 56.9 (22.2–85.9) 124 (8.0%) 1.00Yes 375 12.5 (5.6–25.7) 68 (19.3%) 2.74 (2.21,3.39) <.001Missing 489 30.6 (4.8–79.4) 85 (16.9%) 2.32 (1.55,3.48) 0.002Malamba et al. BMC Infectious Diseases  (2016) 16:690 Page 6 of 13There was no significant difference in HIV infectionbetween participants who had ever been abducted dur-ing the war and those who had never been abducted (p= 0.578). Giving or being given money or gifts inexchange for sex in the past 12 months only attainedborderline significance (p = 0.093); Participants whostayed in a child-headed household (p = 0.274); and menwho were circumcised were less likely to have HIV butthis effect did not attain statistical significance in themultivariable model.Sexual experiences at first sexual debutThe median age at first sexual debut among 1955 studyparticipants who reported ever having sex was similar be-tween those with and those without HIV infection (16 years,IQR: 14, 18) but the number of lifetime sex partners wasTable 1 HIV-1 sero-positivity by population socio-demographic characteristics and sexual history at baseline (Continued)Ever been abductedNo 1798 78.1 (70.6–84.1) 180 (10.8%) 1.00Yes 590 21.9 (15.9–29.4) 97 (17.0%) 1.69 (1.24,2.30) 0.005Circumcised men (Self report)No 785 82.3 (53.6–94.9) 65 (9.1%) 1.00Yes 72 8.4 (2.5–25.0) 4 (5.5%) 0.59 (0.11,3.27) 0.487Missing 134 9.3 (0.5–66.2) 8 (6.0%) 0.63 (0.36,1.13) 0.104Consistent condom use with last 3 partners in past 12 monthsInconsistent 1724 71.4 (67.1–75.4) 241 (14.7%) 1.00Consistent 231 11.1 (6.3–18.8) 33 (14.1%) 0.95 (0.44,2.03) 0.872Never had sex 433 17.5 (12.4–24.1) 3 (0.4%) 0.02 (0.00,0.21) 0.005Genital ulcers in last 12 monthsNo 2184 90.7 (88.4–92.5) 212 (10.0%) 1.00Yes 204 9.3 (7.5–11.6) 65 (33.0%) 4.44 (3.11,6.34) <0.001Active SyphilisNegative 2290 95.8 (94.8–96.7) 250 (11.3%) 1.00Positive 98 4.2 (3.3–5.2) 27 (32.0%) 3.70 (2.33,5.85) <0.001Number of sexual partners ever0 441 17.7 (12.7–24.1) 3 (0.4%) 1.01 453 19.5 (15.8–23.9) 19 (4.3%) 12.73 (1.50, 107.85) 0.0262 424 17.6 (14.1–21.7) 61 (11.7%) 37.80 (5.74, 248.94) 0.0033+ 963 40.8 (30.9–51.4) 193 (21.9%) 79.67 (8.54, 743.23) 0.002Missing 107 4.4 (1.7–11.0) 7 (6.3%) 19.10 (2.21, 165.23) 0.014Legend: logistic regression data from the Cango Lyec study, mid-northern Uganda districts, 2011/2012NB: % weighted using sampling weightsTable 2 Prevalence of HIV-1 infection by age and sex Cango Lyec study, mid-northern Uganda districts, 2011/2012Variable HIV+/Total (Weighted %) HIV+/Total (Weighted %) HIV+/Total (Weighted %) p-valueAge Total Males Females13–19 15/723 (2.2%) 3/343 (0.8%) 12/380 (3.4%) 0.00520–24 40/443 (8.5%) 8/185 (4.0%) 32/258 (11.5%) <0.00125–29 58/442 (14.0%) 11/161 (9.3%) 47/281 (16.5%) 0.04630–34 61/315 (21.7%) 15/118 (15.7%) 46/197 (25.0%) 0.15235–39 46/199 (22.7%) 17/84 (22.6%) 29/115 (22.8%) 0.97240–44 42/155 (30.1%) 16/63 (27.7%) 26/92 (31.4%) 0.07345–49 15/111 (14.6%) 7/37 (17.8%) 8/74 (13.0%) 0.655Total 277/2388 (12.2%) 77/991 (8.5%) 200/1397 (14.6%) 0.0002Legend: HIV prevalence was higher in females compared to males and increased with increasing age with a peak at the 40–44 years in both sexesNB: % weighted using sampling weightsMalamba et al. BMC Infectious Diseases  (2016) 16:690 Page 7 of 13significantly higher in participants with HIV infection (me-dian = 3: IQR: 2–5) than those without HIV infection (Me-dian = 2: IQR: 1–3), p < 0.001.DiscussionHIV vulnerability among people who have survived thewar in Northern Uganda is a critical human rights issuerooted in the length of the war and its atrocities. Our re-sults illustrate that although a majority of the populationhas returned to their traditional homesteads from IDPcamps, Acholi people continue to be severely impactedby a high risk of HIV infection that is significantly asso-ciated with war related psychiatric disorder in this post-conflict setting. These findings underscore the urgentneed for the implementation of HIV prevention andtreatment programs that integrate mental health careand are culturally and gender sensitive.HIV prevalenceFindings from this study highlight the enormity of theproblem of HIV infection among people residing in Gulu,Nwoya, and Amuru districts of Northern Uganda. HIVprevalence overall was alarmingly high at 12.2%. In con-trast, a national AIDS survey conducted in 2011 estimatedHIV prevalence in the whole mid Northern region ofUganda to be just over eight percent [40]. Observedestimates of HIV prevalence in ‘Cango Lyec’ are markedlyhigher than the national averages, particularly amongwomen. High prevalence of HIV infection is deeply con-cerning and demonstrates the continuing crisis of the epi-demic in this post-conflict setting.We observed that district of residence was an importantrisk factor for HIV infection, with participants residing inGulu district at least two times as likely to be living withHIV, compared to those in Amuru district. Those living inNwoya district were also 1.67 times as likely to be livingwith HIV compared to those in Amuru district. Early inthe conflict, the Ugandan government was reluctant to de-clare Northern Uganda an ‘emergency situation’ and HIV/AIDS funding for the conflict-affected districts remainedstagnant. In 2005, the Uganda AIDS Commission and Of-fice of the Prime Minister described the situation in dis-tricts impacted by the war as one of poor access, unevendistribution and poorly linked HIV care, treatment, andreferral services [41]. With cessation of hostilities, theGovernment of Uganda announced an official shift in pol-icy towards development-related activities. As a result,many non-government organizations engaged in relief ef-forts that supported HIV prevention and care closed downoperations, leaving significant gaps [42]. Currently, morethan 90% of the 2 million internally displaced people inthe region have now migrated back to their war-ravagedTable 3 Association between HIV infection, major depressive disorder, post-traumatic stress disorder, trauma experiences andsuicidal ideationVariable Total (N = 2388) HIV+ Weighted (%) Unadjusted OR (95% CI) aAdjusted OR (95%CI) p-valueMajor Depressive Disorder (Mean Depression Scores ≥1.75)No 2027 (85.1%) 193 (10.2%) 1.00 1.00Yes 360 (14.9%) 84 (23.4%) 2.70 (1.95, 3.75) 1.89 (1.28, 2.80) 0.006PTSD (Mean PTSD Scores ≥2.0)No 2109 (88.1%) 227 (11.2%) 1.00 1.00Yes 279 (11.9%) 50 (19.3%) 1.90 (1.30, 2.78) 1.44 (1.06, 1.96) 0.02612 or more Traumatic events everNo 2160 (91.2%) 227 (11.0%) 1,00 1.00Yes 228 (8.8%) 50 (23.7%) 2.52 (1.70, 3.73) 2.50 (1.31, 4.79) 0.012Ever experienced rape or sexual abuseNo 2189 (92.0%) 226 (11.0%) 1.00 1.00Yes 199 (8.0%) 51 (25.6%) 2.80 (1.88, 4.17) 1.80 (0.96, 3.37) 0.063Ill Health without medical care everNo 1639 (69.7%) 162 (10.1%) 1.00 1.00Yes 749 (30.3%) 115 (16.9%) 1.82 (1.36, 2.44) 1.59 (1.00, 2.52) 0.048Suicidal Ideation within last 2 weeksNot at all 2093 (88.4%) 218 (11.2%) 1.00 1.00Yes - A little/Quite a bit/Extremely 293 (11.7%) 59 (19.2%) 1.88 (1.30, 2.72) 1.87 (1.34, 2.61) 0.003Missing 2 (0.1%) 0 (0%) - -Legend: Unadjusted and after adjustinga for differences in age, sex, marital status, religion, and district of residence, several mental health factors were found tobe associated with HIV-infection in three mid-northern Uganda districts population, 2011/2012Malamba et al. BMC Infectious Diseases  (2016) 16:690 Page 8 of 13Table 4 Unadjusted and multivariable analysis for socio-behavioural, sexual histories and STI related risk factors for HIV infection (N= 2388)Parameter HIV Unadjusted *AdjustedN Weighted % OR (95%CI) p-value OR (95%CI) p-valueAge in years 2388 1.08 (1.06,1.10) <0.001 1.05 (1.03,1.08) 0.002SexFemale 1397 14.6 1.00 1.00Male 991 8.5 0.54 (0.44,0.67) <0.001 1.17 (0.95,1.45) 0.114DistrictAmuru 703 7.5 1.00 1.00Gulu 1139 15.2 2.21 (1.68,2.91) <0.001 2.20 (1.37,3.54) 0.006Nwoya 546 11.6 1.62 (1.49,1.76) <0.001 1.67 (1.52,1.85) <0.001Community Displacement statusDisplaced 333 12.9 1.00 1.00Transient 1122 54.7 1.84 (1.12,3.04) 0.023 1.68 (0.64,4.36) 0.243Permanent 933 32.4 1.09 (0.69,1.72) 0.669 1.32 (0.71,2.48) 0.328Marital statusNever married 739 1.8 1.00 1.00Married 1248 15.0 9.51 (7.51,12.05) <0.001 4.69 (3.25,6.76) <0.001Separated/divorced 185 24.8 17.70 (9.90,31.65) <0.001 9.17 (5.60,15.00) <0.001Widowed 65 49.1 51.80 (29.11,92.17) <0.001 20.35 (10.27,40.34) <0.001Missing 151 7.4 4.28 (1.38,13.28) 0.019 5.74 (0.47,70.37) 0.143ReligionRoman Catholic 1690 12.7 1.00 1.00Protestant 358 14.1 1.13 (0.48,2.66) 0.748 0.96 (0.46,2.02) 0.904Moslem 28 19.6 1.67 (0.92,3.04) 0.080 1.99 (0.96,4.12) 0.061Other 178 6.5 0.48 (0.21,1.10) 0.073 0.35 (0.14,0.86) 0.028Missing 134 5.9 0.43 (0.22,0.87) 0.025 0.35 (0.04,2.79) 0.268Staying in a female headed householdNo 1524 8.0 1.00 1.00Yes 375 19.3 2.74 (2.21,3.39) <0.001 2.55 (1.75,3.69) <0.001Missing 489 16.9 2.32 (1.55,3.48) 0.002 1.98 (1.23,3.18) 0.011Staying in a child (<25 years) headed householdNo 1658 10.7 1.00 1.00Yes 240 5.3 0.46 (0.30,0.73) 0.005 0.74 (0.40,1.36) 0.274Missing 490 16.8 1.69 (1.09,2.61) 0.026 - <0.001Given/gave money or gifts in exchange for sex in past 12 monthsNo 1778 14.9 1.00 1.00Yes 21 28.0 2.22 (0.72,6.83) 0.138 2.79 (0.80,9.73) 0.093Never had sex 411 0.4 0.02 (0.00,0.19) 0.004 - <.001Missing 178 5.5 0.33 (0.18,0.62) 0.004 0.38 (0.12,1.19) 0.085Number of sexual partners in last year0 656 6.6 1.00 1.001 1385 13.5 2.21 (1.54,3.19) 0.001 1.19 (0.69,2.04) 0.4792 217 19.1 3.35 (2.10,5.36) <0.001 2.37 (1.13,4.98) 0.0293+ 113 15.6 2.63 (1.19,5.82) 0.024 2.14 (0.64,7.13) 0.179Missing 17 . - <0.001 - <.001Malamba et al. BMC Infectious Diseases  (2016) 16:690 Page 9 of 13ancestral villages. Although the conflict is over, district of-ficials remain concerned that inadequate health-care infra-structure and health worker attrition has alarmingconsequences for HIV prevention as the previouslyencamped resettle [42]. Our findings clearly indicate thepotential for rapid progression of HIV infection inNorthern Uganda requiring an aggressive, evidence-basedresponse to HIV prevention that takes into account post-conflict realities.GenderHIV prevalence was much higher among women (14.6%)compared to men (8.5%) in this study (p = 0.001). In themultivariable analysis, we observed that young women aged18 to 34 are at considerably higher risk than young men ofthe same age, with a 1.64 increase in odds of being HIVpositive, after controlling for marital status, district, religionand age. However, the difference was not statistically signifi-cant among 35+ year olds. The impact of gender-based dis-parities in HIV risk were further illustrated by our findingthat participants who lived in a female-headed householdwere more than two and a half times likely to be living withHIV. As conflict-affected young women navigate newenvironments outside of the bush and IDP camps wherethey have spent large portions of their lives, district officialsare concerned that they face new and undocumentedvulnerabilities [25]. With prevailing peace, trade betweenNorthern Uganda and South Sudan has expanded, leadingto cross border movement of truckers, agricultural traders,and cattle-loaders into the previously isolated region. Thesetrends have been accompanied by increased transactionaland subsistence sex along the Kampala-Juba highway.Young women displaced by war who experienced multipletraumas and never learned agricultural skills may be transi-tioning into sex work along this new corridor and in ruralareas, resulting in the emergence of HIV and STI transmis-sion hotspots. District leaders have raised concerns thatfamilies moving away from trading centres back to their an-cestral homes leave daughters behind to be closer toschools without adequate socioeconomic support, exposingthem to predation. In addition, it has been highlighted thatyoung women have been working in strip/sex clubs and ex-changing sex for essential goods, such as sanitary napkins.It is clear from our current work that with the restorationof relative security in Northern Uganda, young women arejust as vulnerable to HIV infection, predation, and gender-based violence as they were at the height of the conflict[43]. The drivers of risk have changed, but the vulnerabilityremains the same.War trauma, psychiatric disorder and HIVThis study identified powerful associations between HIVprevalence and war trauma experiences and the psychi-atric problems of PTSD, MDD and suicidal ideationamong conflict-affected populations. We observed thatparticipants living with HIV were two and a half timesas likely to report 12 or more traumatic events. Partici-pants living with HIV were 1.44 times as likely to haveprobable PTSD, nearly two times as likely to have prob-able MDD and nearly two times as likely to reportTable 4 Unadjusted and multivariable analysis for socio-behavioural, sexual histories and STI related risk factors for HIV infection (N= 2388)(Continued)Consistent condom use with the last 3 partners in past 12 monthsInconsistent 1724 14.7 1.00 1.00Consistent 231 14.1 0.95 (0.44,2.03) 0.872 2.10 (1.38,3.18) 0.004Never had sex 433 0.4 0.02 (0.00,0.21) 0.005 0.21 (0.02,1.85) 0.134Ever been abductedNo 1798 10.8 1.00 1.00Yes 590 17.0 1.69 (1.24,2.30) 0.005 1.12 (0.70,1.80) 0.578Genital ulcers in past 12 monthsNo 2184 10.0 1.00 1.00Yes 204 33.0 4.44 (3.11,6.34) <0.001 3.33 (2.58,4.28) <0.001Active SyphilisNegative 2290 11.3 1.00 1.00Positive 98 32.0 3.70 (2.33,5.85) <0.001 3.55 (1.59,7.93) 0.017Legend: Each unit increase in age, district of residence, marital status, residing in a female headed household, condom use, genital ulcers and active syphilis wereidentified as the main socio-behavioural, sexual histories and STI related factors for HIV infection in this study population*Adjusted for age, sex, district of residence, religion and marital status*Note: Sex was forced to remain in the final modelNested models and the resulting fit characteristics and Likelihood ratio testsSocio-demographics, sexual histories, STI and HIV (Log Likelihood = −646.4)Socio-demographics, sexual histories, STI, [sex * age] and HIV (LR Test = 7.13, p = 0.076Socio-demographics, sexual histories, STI, [sex * age * marital status] and HIV (LR Test = 10.63, p = 0.06Malamba et al. BMC Infectious Diseases  (2016) 16:690 Page 10 of 13suicidal ideation within the last 2 weeks. PTSD may en-hance HIV vulnerability by promoting high-risk behav-iour, reducing immune function, and interfering withmedication adherence [44–46]. However, the relation-ship between HIV and MDD is complex and bidirec-tional where persons with MDD are at increased risk forHIV infection, and persons with HIV are at increasedrisk of developing MDD [47]. Delineating which of theseassociations is at play in the post-conflict situation ofNorthern Uganda will be answered by the follow-upcomponent of this study. There is need for more studiesin order to understand the link between mental healthand HIV vulnerability in the context of war and forcedmigration [48–50].Of note, contrary to the speculation that the experienceof abduction and its’ associated experience of sexual abuseexacerbated vulnerability to HIV, there is no evidence tosuggest that people with a history of abduction are morelikely to be HIV positive in this study [48, 51]. However,former abductees in the ‘Cango Lyec’ study were nearlythree times more likely to meet the criteria for probablePTSD which in this study has been associated with HIVinfection. Anecdotal observations from the region indicatethat former abductees experience significant levels ofstigma on returning from the bush including the beliefthat they are HIV infected. Could this stigma and isolationexplain the lack of association between abduction andHIV infection? This and many other questions call for fur-ther studies in order to understand the complex relation-ship between war experiences, war related psychiatricdisorder and vulnerability to HIV infection. The positiveassociation observed in this study between HIV infectionand war related psychiatric disorders calls for the integra-tion of mental health care in HIV prevention and treat-ment programs in conflict and post-conflict communities.Sexually vulnerabilityConsistent with existing research, this study observed in-creased likelihood of HIV among participants with otherSTIs. It is of great concern that among ‘Cango Lyec’ partic-ipants, baseline prevalence of self-reported genital ulcerdisease (GUD) in the last year was nearly 10%. Indeed,participants who reported GUD in the past year weremore than four times as likely to be living with HIV atbaseline. Among participants who tested positive for ac-tive syphilis, risk of HIV increased nearly four-fold. Bothulcerative and non-ulcerative STIs have been shown to in-crease transmission of HIV infection [49, 50, 52, 53]. In astudy of monogamous HIV-discordant couples in Rakai,Uganda, risk of HIV transmission was approximatelydouble if one partner had GUD. When both partners hadGUD, the risk was nearly four-fold higher [54]. Further, astudy of young conflict-affected people aged 15–29 resid-ing in transit camps in Northern Uganda observed thatever having had an STI was associated with a four-fold in-crease in HIV risk among young women, but was not sig-nificantly associated with HIV risk among young men[55]. Active syphilis and other GUD in conjunction withlow prevalence of male circumcision is worrisome andmay be a warning sign for a rise in new HIV infections inthe aftermath of war [56]. These findings highlight the im-portance of post-conflict HIV prevention interventionsthat support access to STI diagnosis and treatment.Compared to those who were single, those who werecurrently or had ever been married were significantlymore likely to be living with HIV in this study. These find-ings are consistent with other research demonstrating thatmany new HIV infections in sub-Saharan Africa occur instable partnerships [57]. However, HIV prevention pro-grams continue to focus on reducing sex and increasingcondom use with casual partners.In addition, participants who reported consistent con-dom use in the last 3 months were two times as likely tobe living with HIV. These findings and the observed ex-tremely low rates (11%) of consistent condom use are con-cerning, as elsewhere in Uganda [58]. More work must bedone to help men and women, including those living withHIV, negotiate condom use with all partners.Strengths and limitationsSignificant strength of this study includes the ability to de-termine the HIV and syphilis status using laboratory tests.Efforts were made to enrol all eligible members of thestudy population. Unfortunately, some individuals were re-peatedly absent or refused to participate in the survey.Some of these individuals were more likely to be mobileindividuals who have been shown to have higher risks ofinfection. Reasons for refusing to participate in the surveywere not given; some may have refused because of knownHIV sero-positive status, we cannot completely rule outselection bias. In addition, the study relies on self-reportedbehavioural data, there is therefore potential for recall bias,socially desirable reporting, and misclassification of expos-ure. Responses to historical questions may be influencedby the participant’s ability to recall event(s). Social desir-ability may lead to an underestimation of some HIV riskbehaviours. The effect of memory on these study variablesis difficult to assess. Due to the cross-sectional nature ofthis analysis we are unable to identify cause-effect relation-ships and temporal sequences. Finally, while the HTQ andHSCL-25 have been demonstrated to be both reliable andvalid in this setting, they are screening tools and not diag-nostic, which may lead to a conflation in levels of probablePTSD and MDD. On the other hand, ill people might havebeen more inclined to comply in the expectation of receiv-ing treatment. Despite these limitations, we are confidentthat due to our recruitment methods and rigorousMalamba et al. BMC Infectious Diseases  (2016) 16:690 Page 11 of 13eligibility criteria our sample is representative of peopleresiding in study communities.ConclusionEvidence of the extreme HIV vulnerability of conflict-affected populations in Northern Uganda observed in thisstudy is an immediate global concern. It is clear from ourcurrent work that with the restoration of relative security inNorthern Uganda, young women in particular are just asvulnerable to HIV infection, predation, and gender-basedviolence as they were at the height of the conflict. Inaddition, war related psychiatric disorders emerge as keyrisk factors for HIV in this post-conflict community. Thedrivers of risk have changed, but the vulnerability remainsthe same. With HIV vaccines unlikely to be available formany years, Acholi people impacted by Northern Uganda’scivil war represent a critical hotspot where specializedinterventions are required to prevent transmission andsupport engagement in HIV care. Meaningful HIV inter-ventions must address the war trauma experiences of thispopulation, the consequent psychiatric disorder and shouldfoster resilience.AcknowledgementsWe would like to thank the research participants in Uganda who courageouslyshared their stories with us. The Ugandan investigative team and the ‘CangoLyec’ study staff: interviewers, counsellors, drivers, data management andlaboratory teams for their commitment.FundingThis project was funded by the Canadian Institutes for Health Research (CIHR).The funders had no role in the study design, data collection and analysis,decision to publish, or preparation of the manuscript.Availability of data and materialsRaw data will not be available for sharing since we are still analysing someaspects of the baseline and follow-up data and developing several othermanuscripts addressing the four main research objectives in the protocol,especially the HIV incidence results.Authors’ contributionsSSM substantial contributions to conception and design of the study,acquisition of data, carried out the statistical analysis, interpretation of data,drafted and edit the manuscript. HM, NK, EK, MDO and PMS co-conceivedthe study and study design, and helped draft and edit the manuscript. PKKparticipated in the testing and analysis of the samples for HIV and Syphilisinfections. JPE, AB and KJ participated in data analysis and edited themanuscript. AK, PO and NKS supervised protocol implementation, read andedited the manuscript. MTS supervised the study implementation andmanuscript development. All authors read and approved the final submittedversion of the manuscript.Competing interestsThe authors declare that they have no competing interests.Consent for publication“Not applicable” since the manuscript doesn’t contain individual person’sdata.Ethical approval and consent to participateEthical approvals were obtained from the University of British Columbia-Providence Healthcare Research Ethics Board (Canada), Makerere UniversityCollege of Health Sciences-School of Public Health - Science Ethical Committee,Uganda Virus Research Institute-Science and Ethics Committee, and UgandaNational Council for Science and Technology. Informed written consent wasobtained from all eligible study participants aged 13–49 years. Parental\legalguardians written consent for participants <18 years together with their assentwere also obtained. Every participant was properly counselled and consentedbefore being asked to sign or put a fingerprint on the consent form if they werenot able to write.Author details1Uganda Virus Research Institute (UVRI) - HIV Reference Laboratory Program,Entebbe, Uganda. 2Makerere University, Child Health Development Center,Kampala, Uganda. 3University of British Columbia, School of Population &Public Health, Vancouver, Canada. 4School of Public Health, University ofAlberta, Alberta, Canada. 5Uganda Virus Research Institute - International HIV/AIDS Vaccine Initiative (UVRI-IAVI) HIV Vaccine Program, Entebbe, Uganda.6St. Mary’s Hospital-Lacor, Gulu, Uganda. 7Northern Uganda Program onHealth Sciences, Kampala, Uganda. 8Makerere University College of HealthSciences, Kampala, Uganda. 9MRC/UVRI Uganda Research Unit on AIDS,Entebbe, Uganda. 10Butabika National Psychiatric Referral Hospital, Nakawa,Uganda. 11Northern Uganda Program on Health Sciences, c/o Uganda VirusResearch Institute, HIV Reference Laboratory, P.O. 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HIV incidenceand sexually transmitted disease prevalence associated with condom use: apopulation study in Rakai, Uganda. Aids. 2001;15(16):2171–9.•  We accept pre-submission inquiries •  Our selector tool helps you to find the most relevant journal•  We provide round the clock customer support •  Convenient online submission•  Thorough peer review•  Inclusion in PubMed and all major indexing services •  Maximum visibility for your researchSubmit your manuscript atwww.biomedcentral.com/submitSubmit your next manuscript to BioMed Central and we will help you at every step:Malamba et al. BMC Infectious Diseases  (2016) 16:690 Page 13 of 13


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