<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">WJA</journal-id><journal-title-group><journal-title>World Journal of AIDS</journal-title></journal-title-group><issn pub-type="epub">2160-8814</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/wja.2021.114015</article-id><article-id pub-id-type="publisher-id">WJA-114406</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Medicine&amp;Healthcare</subject></subj-group></article-categories><title-group><article-title>
 
 
  COVID-19 and HIV Treatment Interruption: A Case Study of the AIDS Support Organization (TASO) Mbale Clinic
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Bonniface</surname><given-names>Oryokot</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Andrew</surname><given-names>Kazibwe</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Abraham</surname><given-names>Ignatius Oluka</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Yunus</surname><given-names>Miya</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Michael</surname><given-names>Bernard Etukoit</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>University of Suffolk, Ipswich, UK</addr-line></aff><aff id="aff3"><addr-line>Directorate of Program Management and Capacity Development, The AIDS Support Organization (TASO), Kampala, Uganda</addr-line></aff><aff id="aff2"><addr-line>Makerere University College of Health Sciences, Kampala, Uganda</addr-line></aff><pub-date pub-type="epub"><day>07</day><month>12</month><year>2021</year></pub-date><volume>11</volume><issue>04</issue><fpage>199</fpage><lpage>215</lpage><history><date date-type="received"><day>8,</day>	<month>November</month>	<year>2021</year></date><date date-type="rev-recd"><day>28,</day>	<month>December</month>	<year>2021</year>	</date><date date-type="accepted"><day>31,</day>	<month>December</month>	<year>2021</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  Introduction: COVID-19 pandemic caught many HIV programs completely unprepared, leading to massive interruptions in HIV treatment. Fear and anxiety caused by another infectious and potentially deadly virus kept many PLHIV away from accessing ART services. Besides, the COVID-19 control measures imposed by the Government of Uganda, such as restrictions on movement due to the ban on both private and public transport, shortened travel hours due to the curfew imposed from 7 p.m. local time and limited resources at The AIDS Support Organization (TASO) Mbale clinic further frustrated access to ART services. The actual burden of treatment interruption in Uganda remains unclear. As such, this paper provides the magnitude of treatment interruption in TASO Mbale clinic during the April-June 2020 quarter—the COVID-19 pandemic peak period in Uganda. 
  Methodology: We analyzed secondary and routine program data for all PLHIV on scheduled appointment in the quarters of January-March 2020 and April 2020-June 2020. We abstracted data from Uganda Electronic Medical Records (EMR) and linked with that from TASO Management Information system to make one dataset. This was then exported for final analysis in STATA version 15.
   Results: Out of 6744 PLHIV scheduled on appointment during April-June 2020 quarter, 1710 (25.3%) individuals missed their appointments, with the facility-based clients more affected than community-based (56.1% vs 43.9%) (p &lt; 0.001), individuals with up-to-date viral load (VL) status were less likely to miss their appointment (p &lt; 0.001) while sex was not associated with missed appointment (p-value = 0.269). Overall, there was a 356% increase in rate of missed appointment compared with that of January-March 2020 quarter (25.3% vs 7.1%) before COVID-19 pandemic hit Uganda. Moreover, PLHIV who received six-month’s drug refills were less likely to miss their appointment (p &lt; 0.001) compared to those who received less. 
  Conclusions: The COVID-19 pandemic significantly disrupted provision of ART services, leading to increased rate of missed appointment from 7.1% in the pre-COVID-19 quarter to 25.3%.
 
</p></abstract><kwd-group><kwd>HIV</kwd><kwd> Treatment Interruption</kwd><kwd> COVID-19</kwd><kwd> TASO</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>The novel coronavirus, SARS-CoV-2, and the associated Corona Virus Disease (COVID-19), described in Wuhan, China in December 2019, resulted in a global health emergency [<xref ref-type="bibr" rid="scirp.114406-ref1">1</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref2">2</xref>]. Many countries in sub-Saharan Africa (SSA) including Uganda, in compliance with World Health Organization (WHO) recommendations [<xref ref-type="bibr" rid="scirp.114406-ref1">1</xref>], first instituted strict lockdown measures on 18<sup>th</sup> March 2020, as part of the COVID-19 containment measures [<xref ref-type="bibr" rid="scirp.114406-ref3">3</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref4">4</xref>]. These measures included closure of all educational institutions, transport restrictions with total ban on public means of transport and closure of all places that encourage crowding [<xref ref-type="bibr" rid="scirp.114406-ref1">1</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref5">5</xref>]. While the lockdowns aimed at limiting community spread of COVID-19, it also resulted in untold consequences, such as reduced access to medical services including those of HIV, which could negatively influence treatment outcomes [<xref ref-type="bibr" rid="scirp.114406-ref4">4</xref>]. With a fragile healthcare system often constrained by inadequate human resources and logistics, COVID-19 was feared to undermine progress in ending the HIV epidemic in many developing countries such as those in SSA [<xref ref-type="bibr" rid="scirp.114406-ref6">6</xref>]. Moreover, the diversion of healthcare resources to manage COVID-19 patients [<xref ref-type="bibr" rid="scirp.114406-ref7">7</xref>] and the lockdown measures were predicted to further negatively impact HIV service access and utilization. Furthermore, the adverse psychosocial and socioeconomic situations caused by loss of employment and direct impact of COVID-19 [<xref ref-type="bibr" rid="scirp.114406-ref8">8</xref>] could further increase chances of PLHIV missing their scheduled clinic appointments; hence, interrupting treatment. Home to about 66.7% of global population of people living with HIV (PLHIV) [<xref ref-type="bibr" rid="scirp.114406-ref9">9</xref>], SSA was expected to suffer worst, from the direct and indirect effects of COVID-19 [<xref ref-type="bibr" rid="scirp.114406-ref3">3</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref4">4</xref>]. The effect of HIV care and treatment disruption could lead to increased adverse service outcomes, such as morbidity and mortality among the PLHIV.</p><p>Indeed, modeling studies have predicted increased morbidity and death from AIDS-related illnesses in the region [<xref ref-type="bibr" rid="scirp.114406-ref6">6</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref10">10</xref>]. For example, a five-year effect of HIV treatment interruption is predicted to cause 10% increment in AIDS-related deaths [<xref ref-type="bibr" rid="scirp.114406-ref10">10</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref11">11</xref>]. Similarly, a separate study indicated that a six-month interruption in HIV treatment could cause 1.63 times increase in death in one year [<xref ref-type="bibr" rid="scirp.114406-ref6">6</xref>]. The realization of this chilling prediction could stifle great gains in the HIV fight that have been achieved in SSA, including Uganda. In the case of Uganda, AIDS related mortality had reduced by 58% by the end of 2019 compared to the 2010 figures [<xref ref-type="bibr" rid="scirp.114406-ref12">12</xref>]. Besides, 87% of PLHIV in Uganda knew their status, with 84% on treatment and 75% achieving viral suppression by the end of December 2019, which was in line with the global targets of 95-95-95 [<xref ref-type="bibr" rid="scirp.114406-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref13">13</xref>]. It is critical for these gains to be sustained and propelled forwards to realize the global targets of epidemic control. However, for the country to sustain this momentum, PLHIV need to remain in care and on ART without substantial interruptions which may ensure optimal adherence with subsequent viral load suppression [<xref ref-type="bibr" rid="scirp.114406-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref14">14</xref>]. Unfortunately, the COVID-19 pandemic has directly or indirectly caused massive disruptions in HIV services in the country, leading to limited access to antiretroviral therapy (ART) to PLHIV [<xref ref-type="bibr" rid="scirp.114406-ref8">8</xref>]. This may peg back the national and sub-national progress in the race to attain the AIDS epidemic control by 2030 [<xref ref-type="bibr" rid="scirp.114406-ref15">15</xref>].</p><p>The international community acknowledges this disturbing fact and has encouraged different countries to innovate strategies that may mitigate its effects [<xref ref-type="bibr" rid="scirp.114406-ref16">16</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref17">17</xref>]. However, for Uganda to effectively circumvent the potential catastrophe posed by the disruptions in HIV services, there is need to appreciate the actual burden of HIV treatment interruptions in the country. To date, there is only a paucity of data indicating the actual burden of HIV treatment interruptions in Uganda following the COVID-19 pandemic, which may frustrate development of appropriate policies to respond to the COVID-19 devastation in HIV services. In consequence, our paper provides evidence on the burden of disengagement of PLHIV in care at The AIDS Support Organization (TASO) Mbale clinic in Eastern Uganda during the April-June 2020 quarter, the COVID-19 Pandemic peak period in Uganda. This will contribute to the existing body of knowledge to guide policy in the implementation of client-centered HIV care services in response to calls by UNAIDS and WHO for governments to develop context specific COVID-19 counter measures.</p></sec><sec id="s2"><title>2. Methodology</title><sec id="s2_1"><title>2.1. Study Design</title><p>A retrospective cohort study design was used and routine program data from April 2020 to June 2020 was analyzed. In addition, program data of PLHIV clients who were on scheduled appointment in that period were analyzed to identify the magnitude of missed appointment, and re-engagement of PLHIV after disengagement. Similarly, data for the January 2020-March 2020 quarter for purposes of comparisons were analyzed.</p></sec><sec id="s2_2"><title>2.2. Study Site</title><p>The AIDS Support Organization (TASO) Mbale is a Center of Excellence (CoE) providing comprehensive HIV prevention, care and treatment services [<xref ref-type="bibr" rid="scirp.114406-ref18">18</xref>]. TASO Mbale is a specialized HIV clinic located inside Mbale Regional Referral Hospital approximately 230 kilometers east of Kampala Capital City. The CoE operates in the districts of Mbale, Sironko, Bududa, Namisindwa, Manafwa, Bukedea, Kibuku, Budaka, Pallisa and Butebo, covering a diameter of 75 kilometers [<xref ref-type="bibr" rid="scirp.114406-ref9">9</xref>]. The services are provided through a differentiated service delivery model (DSDM)s, with about 70% of the PLHIV served in the community and about 30% from the facility. DSDMs included facility-based individual management (FBIM), Fast-track drug refills (FTDR), Facility-based groups (FBG), Community-client-led ART delivery (CCLAD), Community drug delivery points (CDDPs) [<xref ref-type="bibr" rid="scirp.114406-ref19">19</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref20">20</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref21">21</xref>]. Both CCLAD and CDDPs are based in the community and all PLHIV receive their drugs from designated locations within their localities. The clinic operates normally from Monday to Friday, 08:00-17:30 hours East African Standard time. Finally, individuals received ART in a multi-month approach, with drugs dispensed for one month, two months, three months, four months, five months and six months respectively, depending on the clinical status of a client [<xref ref-type="bibr" rid="scirp.114406-ref17">17</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref22">22</xref>].</p></sec><sec id="s2_3"><title>2.3. Study Population</title><p>All the PLHIV on ART, registered at TASO Mbale clinic and scheduled to receive services from the 1<sup>st</sup> April, 2020 to 30<sup>th</sup> June, 2020, and those scheduled on appointment from the 1<sup>st</sup> January, 2020 to 31<sup>st</sup> March, 2020 for purposes of comparison. These individuals were expected to receive HIV services from both the facility and community.</p></sec><sec id="s2_4"><title>2.4. Data Management</title><p>Routine patient monitoring raw data were extracted from Uganda Electronic Medical Records (EMR) version 3.0.4 using inbuilt cohort builder module capabilities. Clients with any return visit dates between April 2020 and June 2020 were extracted from Uganda EMR with basic patient characteristics like age, sex and service point. Specifically, up to date viral load data was generated and extracted from TASO Management Information Systems with restrictions to only viral load (VL) done in the last 12 months. Data from Uganda EMR and TASO MIS were then linked and merged into one dataset. Preliminary data cleaning was done in MS-Excel and MS-Access interchangeably and the final cleaned dataset was exported to STATA CORP version 15 for analysis.</p><p>Descriptive statistics were conducted in order to determine basic patient characteristics. At bivariate level, Pearson chi-square tests were performed to test for relationships between missed appointments and different independent variables such as sex, age group and service point. Statistically, significant independent variables were also tested for the same using simple logistic regression model where unadjusted odds ratios were reported. Furthermore, a multivariate logistic regression model was conducted to identify factors associated with missed appointments adjusted for confounding and multicollinearity. To estimate the maximum likely influence of the different independent factors on the dependent variable, logistic regression model was preferred because of a binary outcome variable. The statistical level of significance was set at 0.05.</p></sec><sec id="s2_5"><title>2.5. Measurements</title><p>The outcome variable was the missed appointment defined as any PLHIV who did not turn up on their scheduled appointment. It was measured on a binary scale of yes or no. Therefore, individuals who kept their appointments were considered as active while those who missed appointment were considered as disengaged. However, those individuals who came back to care after missing their appointment were considered as re-engaged. The independent variables were age group, service point (described as the point where a PLHIV receives ART services either from the facility or community), multi-month dispensing (MMD), sex and viral load status.</p></sec></sec><sec id="s3"><title>3. Results</title><p>As demonstrated in <xref ref-type="table" rid="table1">Table 1</xref>, a total of 6744 patients scheduled for clinical services at TASO Mbale CoE during the quarter of April to June 2020, 4647 (68.9%) were females and 2097 (31.1%) males. In terms of service point, 4220 (62.6%) were scheduled to access their comprehensive HIV services from the community while 2524 (37.4%) were supposed to be reviewed at the facility. The vast majority of our patients were adults (5982, 88.7%) aged 25 years or older while the children, adolescents and the youths constituted 2%, 5.9% and 3.4% respectively.</p><p>Out of the 6744 patients on scheduled appointment during the quarter, 1710 (25.3%) patients missed their appointment including 1160 (67.8%) females and 550 (32.2%) males. Importantly, more patients 960 (56.1%) missed at the facility than in the community (750, 43.9%). Comparatively, in the quarter of January to March 2020, out of 7279 patients on scheduled appointment, only 519 missed their appointments, translating to 7.1%. Multi-month drug refills were strongly associated with missed appointment (P-value &lt; 0.001).</p><p>From <xref ref-type="table" rid="table2">Table 2</xref>, 337 (19.7%) patients were followed and provided with services while 18 (1.1%) deaths were recorded and 7 clients were transferred out to other facilities during this period. Majority of the patients (1348, 78.8%) were yet to be followed up and statuses determined.</p><p>From <xref ref-type="table" rid="table3">Table 3</xref>, it can be seen that age group is associated with missed appointment (P-value &lt; 0.001) and service point (P-value &lt; 0.001) while sex was not associated with missed appointment (P-value = 0.269). Moreover, it was found that individuals with an up-to-date viral load result (within 12 months before study period) were less likely to miss their appointment compared to those without (P &lt; 0.001).</p><p>From <xref ref-type="table" rid="table4">Table 4</xref>, the columns of results of the unadjusted ratios show that age group, service point, viral load status and multi-months drug dispensing respectively were statistically significant (P &lt; 0.05) in influencing missed appointments. Specifically, the youths (20 - 24 years) were 2.13 times more likely to miss appointments as compared to children (0 - 9 years) (OR = 2.13; 95% C. I [1.3111 - 3.4636]; P &lt; 0.001). Relatedly, PLHIV receiving ART services from facility arm</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Showing basic patient characteristics</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="2"  >Variable</th><th align="center" valign="middle"  colspan="2"  >Scheduled Appointments</th><th align="center" valign="middle"  colspan="2"  >Missed Appointments</th></tr></thead><tr><td align="center" valign="middle" >Frequency (n = 6744)</td><td align="center" valign="middle" >Percent (%)</td><td align="center" valign="middle" >Frequency (n = 1710)</td><td align="center" valign="middle" >Percent (%)</td></tr><tr><td align="center" valign="middle"  colspan="5"  >Period</td></tr><tr><td align="center" valign="middle" >April_20</td><td align="center" valign="middle" >2872</td><td align="center" valign="middle" >42.6</td><td align="center" valign="middle" >704</td><td align="center" valign="middle" >41.2</td></tr><tr><td align="center" valign="middle" >June_20</td><td align="center" valign="middle" >2137</td><td align="center" valign="middle" >31.7</td><td align="center" valign="middle" >346</td><td align="center" valign="middle" >20.2</td></tr><tr><td align="center" valign="middle" >May_20</td><td align="center" valign="middle" >1735</td><td align="center" valign="middle" >25.7</td><td align="center" valign="middle" >660</td><td align="center" valign="middle" >38.6</td></tr><tr><td align="center" valign="middle" >Jan_20-March_20</td><td align="center" valign="middle" >7279</td><td align="center" valign="middle" >100</td><td align="center" valign="middle" >519</td><td align="center" valign="middle" >7.1</td></tr><tr><td align="center" valign="middle"  colspan="5"  >Age group (Years)</td></tr><tr><td align="center" valign="middle" >Children (0 - 9)</td><td align="center" valign="middle" >132</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >30</td><td align="center" valign="middle" >1.8</td></tr><tr><td align="center" valign="middle" >Adolescents (10 - 19)</td><td align="center" valign="middle" >399</td><td align="center" valign="middle" >5.9</td><td align="center" valign="middle" >73</td><td align="center" valign="middle" >4.3</td></tr><tr><td align="center" valign="middle" >Youths (20 - 24)</td><td align="center" valign="middle" >231</td><td align="center" valign="middle" >3.4</td><td align="center" valign="middle" >89</td><td align="center" valign="middle" >5.2</td></tr><tr><td align="center" valign="middle" >Adults (≥25)</td><td align="center" valign="middle" >5982</td><td align="center" valign="middle" >88.7</td><td align="center" valign="middle" >1518</td><td align="center" valign="middle" >88.8</td></tr><tr><td align="center" valign="middle"  colspan="5"  >Sex</td></tr><tr><td align="center" valign="middle" >Female</td><td align="center" valign="middle" >4647</td><td align="center" valign="middle" >68.9</td><td align="center" valign="middle" >1160</td><td align="center" valign="middle" >67.8</td></tr><tr><td align="center" valign="middle" >Male</td><td align="center" valign="middle" >2097</td><td align="center" valign="middle" >31.1</td><td align="center" valign="middle" >550</td><td align="center" valign="middle" >32.2</td></tr><tr><td align="center" valign="middle"  colspan="5"  >Service point</td></tr><tr><td align="center" valign="middle" >Community</td><td align="center" valign="middle" >4220</td><td align="center" valign="middle" >62.6</td><td align="center" valign="middle" >750</td><td align="center" valign="middle" >43.9</td></tr><tr><td align="center" valign="middle" >Facility</td><td align="center" valign="middle" >2524</td><td align="center" valign="middle" >37.4</td><td align="center" valign="middle" >960</td><td align="center" valign="middle" >56.1</td></tr><tr><td align="center" valign="middle"  colspan="5"  >Viral load status</td></tr><tr><td align="center" valign="middle" >No VL result</td><td align="center" valign="middle" >880</td><td align="center" valign="middle" >13.1</td><td align="center" valign="middle" >437</td><td align="center" valign="middle" >25.6</td></tr><tr><td align="center" valign="middle" >Suppressed</td><td align="center" valign="middle" >5515</td><td align="center" valign="middle" >81.8</td><td align="center" valign="middle" >1159</td><td align="center" valign="middle" >67.8</td></tr><tr><td align="center" valign="middle" >Non-suppressed</td><td align="center" valign="middle" >349</td><td align="center" valign="middle" >5.2</td><td align="center" valign="middle" >114</td><td align="center" valign="middle" >6.7</td></tr><tr><td align="center" valign="middle"  colspan="5"  >Multi Month Dispensation of drugs</td></tr><tr><td align="center" valign="middle" >1 Month</td><td align="center" valign="middle" >236</td><td align="center" valign="middle" >3.5</td><td align="center" valign="middle" >119</td><td align="center" valign="middle" >7.0</td></tr><tr><td align="center" valign="middle" >2 Months</td><td align="center" valign="middle" >251</td><td align="center" valign="middle" >3.7</td><td align="center" valign="middle" >115</td><td align="center" valign="middle" >6.7</td></tr><tr><td align="center" valign="middle" >3 Months</td><td align="center" valign="middle" >2794</td><td align="center" valign="middle" >41.4</td><td align="center" valign="middle" >992</td><td align="center" valign="middle" >58.0</td></tr><tr><td align="center" valign="middle" >4 Months</td><td align="center" valign="middle" >62</td><td align="center" valign="middle" >0.9</td><td align="center" valign="middle" >13</td><td align="center" valign="middle" >0.8</td></tr><tr><td align="center" valign="middle" >5 Months</td><td align="center" valign="middle" >20</td><td align="center" valign="middle" >0.3</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >0.3</td></tr><tr><td align="center" valign="middle" >≥6 Months</td><td align="center" valign="middle" >3381</td><td align="center" valign="middle" >50.1</td><td align="center" valign="middle" >466</td><td align="center" valign="middle" >27.3</td></tr></tbody></table></table-wrap><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Showing patients followed up and status determined</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Variable</th><th align="center" valign="middle" >Frequency (n = 1710)</th><th align="center" valign="middle" >Percent (%)</th></tr></thead><tr><td align="center" valign="middle"  colspan="3"  >Follow-up status</td></tr><tr><td align="center" valign="middle" >Returned to care</td><td align="center" valign="middle" >337</td><td align="center" valign="middle" >19.7</td></tr><tr><td align="center" valign="middle" >Died</td><td align="center" valign="middle" >18</td><td align="center" valign="middle" >1.1</td></tr><tr><td align="center" valign="middle" >Lost</td><td align="center" valign="middle" >1348</td><td align="center" valign="middle" >78.8</td></tr><tr><td align="center" valign="middle" >Transferred out</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >0.4</td></tr></tbody></table></table-wrap><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Showing some factors associated with missed appointment during the peak of COVID-19 control measures at TASO Mbale (chi-square tests)</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="2"  >Variable</th><th align="center" valign="middle"  colspan="2"  >Missed appointment</th><th align="center" valign="middle" ></th></tr></thead><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >P-Value</td></tr><tr><td align="center" valign="middle"  colspan="4"  >Age group (Years)</td></tr><tr><td align="center" valign="middle" >Children (0 - 9)</td><td align="center" valign="middle" >102</td><td align="center" valign="middle" >30</td><td align="center" valign="middle"  rowspan="4"  >&lt;0.001*</td></tr><tr><td align="center" valign="middle" >Adolescents (10 - 19)</td><td align="center" valign="middle" >326</td><td align="center" valign="middle" >73</td></tr><tr><td align="center" valign="middle" >Youths (20 - 24)</td><td align="center" valign="middle" >142</td><td align="center" valign="middle" >89</td></tr><tr><td align="center" valign="middle" >Adults (≥25)</td><td align="center" valign="middle" >4464</td><td align="center" valign="middle" >1518</td></tr><tr><td align="center" valign="middle"  colspan="4"  >Sex</td></tr><tr><td align="center" valign="middle" >Female</td><td align="center" valign="middle" >3487</td><td align="center" valign="middle" >1160</td><td align="center" valign="middle"  rowspan="2"  >0.269</td></tr><tr><td align="center" valign="middle" >Male</td><td align="center" valign="middle" >1547</td><td align="center" valign="middle" >550</td></tr><tr><td align="center" valign="middle"  colspan="4"  >Service point</td></tr><tr><td align="center" valign="middle" >Community</td><td align="center" valign="middle" >3470</td><td align="center" valign="middle" >750</td><td align="center" valign="middle"  rowspan="2"  >&lt;0.001*</td></tr><tr><td align="center" valign="middle" >Facility</td><td align="center" valign="middle" >1564</td><td align="center" valign="middle" >960</td></tr><tr><td align="center" valign="middle"  colspan="4"  >Viral load status</td></tr><tr><td align="center" valign="middle" >No VL result</td><td align="center" valign="middle" >443</td><td align="center" valign="middle" >437</td><td align="center" valign="middle"  rowspan="3"  >&lt;0.001*</td></tr><tr><td align="center" valign="middle" >Suppressed</td><td align="center" valign="middle" >4356</td><td align="center" valign="middle" >1159</td></tr><tr><td align="center" valign="middle" >Unsuppressed</td><td align="center" valign="middle" >235</td><td align="center" valign="middle" >114</td></tr></tbody></table></table-wrap><p>*Significant (P &lt; 0.05).</p><table-wrap id="table4" ><label><xref ref-type="table" rid="table4">Table 4</xref></label><caption><title> Showing unadjusted and adjusted logistic regression (testing for likelihood of missing appointment)</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle"  colspan="4"  >Unadjusted</th><th align="center" valign="middle"  colspan="4"  >Adjusted</th></tr></thead><tr><td align="center" valign="middle" >Variable</td><td align="center" valign="middle" >Odds ratio</td><td align="center" valign="middle" >P-Value</td><td align="center" valign="middle"  colspan="2"  >[95% confid. Interval]</td><td align="center" valign="middle" >Odds ratio</td><td align="center" valign="middle" >P-Value</td><td align="center" valign="middle"  colspan="2"  >[95% confid. Interval]</td></tr><tr><td align="center" valign="middle" >Age group (Years)</td><td align="center" valign="middle"  colspan="4"  ></td><td align="center" valign="middle"  colspan="4"  ></td></tr><tr><td align="center" valign="middle" >Children (0 - 9)</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >1</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Adolescents (10 - 19)</td><td align="center" valign="middle" >0.76</td><td align="center" valign="middle" >0.27</td><td align="center" valign="middle" >0.4712</td><td align="center" valign="middle" >1.23</td><td align="center" valign="middle" >0.84</td><td align="center" valign="middle" >0.49</td><td align="center" valign="middle" >0.5183</td><td align="center" valign="middle" >1.3732</td></tr><tr><td align="center" valign="middle" >Youths (20 - 24)</td><td align="center" valign="middle" >2.13</td><td align="center" valign="middle" >&lt;0.001*</td><td align="center" valign="middle" >1.3111</td><td align="center" valign="middle" >3.4636</td><td align="center" valign="middle" >2.42</td><td align="center" valign="middle" >&lt;0.001*</td><td align="center" valign="middle" >1.4663</td><td align="center" valign="middle" >3.9975</td></tr><tr><td align="center" valign="middle" >Adults (≥25)</td><td align="center" valign="middle" >1.16</td><td align="center" valign="middle" >0.49</td><td align="center" valign="middle" >0.7664</td><td align="center" valign="middle" >1.7443</td><td align="center" valign="middle" >2.79</td><td align="center" valign="middle" >&lt;0.001*</td><td align="center" valign="middle" >1.8181</td><td align="center" valign="middle" >4.2724</td></tr><tr><td align="center" valign="middle" >Sex</td><td align="center" valign="middle"  colspan="4"  ></td><td align="center" valign="middle"  colspan="4"  ></td></tr><tr><td align="center" valign="middle" >Female</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >1</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Male</td><td align="center" valign="middle" >1.07</td><td align="center" valign="middle" >0.27</td><td align="center" valign="middle" >0.9499</td><td align="center" valign="middle" >1.2024</td><td align="center" valign="middle" >1.02</td><td align="center" valign="middle" >0.81</td><td align="center" valign="middle" >0.894</td><td align="center" valign="middle" >1.154</td></tr><tr><td align="center" valign="middle" >Service point</td><td align="center" valign="middle"  colspan="4"  ></td><td align="center" valign="middle"  colspan="4"  ></td></tr><tr><td align="center" valign="middle" >Community</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >1</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Facility</td><td align="center" valign="middle" >2.84</td><td align="center" valign="middle" >&lt;0.001*</td><td align="center" valign="middle" >2.5374</td><td align="center" valign="middle" >3.1785</td><td align="center" valign="middle" >1.82</td><td align="center" valign="middle" >&lt;0.001*</td><td align="center" valign="middle" >1.5872</td><td align="center" valign="middle" >2.0943</td></tr><tr><td align="center" valign="middle" >VL status</td><td align="center" valign="middle"  colspan="4"  ></td><td align="center" valign="middle"  colspan="4"  ></td></tr><tr><td align="center" valign="middle" >No VL result</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >1</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Suppressed</td><td align="center" valign="middle" >0.27</td><td align="center" valign="middle" >&lt;0.001*</td><td align="center" valign="middle" >0.2328</td><td align="center" valign="middle" >0.3125</td><td align="center" valign="middle" >0.42</td><td align="center" valign="middle" >&lt;0.001*</td><td align="center" valign="middle" >0.3593</td><td align="center" valign="middle" >0.4949</td></tr><tr><td align="center" valign="middle" >Unsuppressed</td><td align="center" valign="middle" >0.49</td><td align="center" valign="middle" >&lt;0.001*</td><td align="center" valign="middle" >0.3792</td><td align="center" valign="middle" >0.6377</td><td align="center" valign="middle" >0.54</td><td align="center" valign="middle" >&lt;0.001*</td><td align="center" valign="middle" >0.4105</td><td align="center" valign="middle" >0.7181</td></tr><tr><td align="center" valign="middle" >Multi-month drug dispensed</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >1 Month</td><td align="center" valign="middle" >6.36</td><td align="center" valign="middle" >&lt;0.001*</td><td align="center" valign="middle" >4.841</td><td align="center" valign="middle" >8.3617</td><td align="center" valign="middle" >3.78</td><td align="center" valign="middle" >&lt;0.001*</td><td align="center" valign="middle" >2.7916</td><td align="center" valign="middle" >5.1218</td></tr><tr><td align="center" valign="middle" >2 Months</td><td align="center" valign="middle" >5.29</td><td align="center" valign="middle" >&lt;0.001*</td><td align="center" valign="middle" >4.0506</td><td align="center" valign="middle" >6.9072</td><td align="center" valign="middle" >4.25</td><td align="center" valign="middle" >&lt;0.001*</td><td align="center" valign="middle" >3.1609</td><td align="center" valign="middle" >5.7094</td></tr><tr><td align="center" valign="middle" >3 Months</td><td align="center" valign="middle" >3.44</td><td align="center" valign="middle" >&lt;0.001*</td><td align="center" valign="middle" >3.0397</td><td align="center" valign="middle" >3.9012</td><td align="center" valign="middle" >2.79</td><td align="center" valign="middle" >&lt;0.001*</td><td align="center" valign="middle" >2.4289</td><td align="center" valign="middle" >3.2048</td></tr><tr><td align="center" valign="middle" >4 Months</td><td align="center" valign="middle" >1.66</td><td align="center" valign="middle" >0.109</td><td align="center" valign="middle" >0.8934</td><td align="center" valign="middle" >3.0827</td><td align="center" valign="middle" >1.22</td><td align="center" valign="middle" >0.54</td><td align="center" valign="middle" >0.6477</td><td align="center" valign="middle" >2.2859</td></tr><tr><td align="center" valign="middle" >5 Months</td><td align="center" valign="middle" >2.09</td><td align="center" valign="middle" >0.157</td><td align="center" valign="middle" >0.7543</td><td align="center" valign="middle" >5.7642</td><td align="center" valign="middle" >1.51</td><td align="center" valign="middle" >0.43</td><td align="center" valign="middle" >0.5381</td><td align="center" valign="middle" >4.2438</td></tr><tr><td align="center" valign="middle" >≥6 Months</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr></tbody></table></table-wrap><p>*Significant (P &lt; 0.05).</p><p>were 2.84 times more likely to miss their scheduled appointments compared to their counterparts in the community (OR = 2.84; 95% [2.5374 - 3.1785] P &lt; 0.001). As regards their viral load status in the last 12 months, results also depicted that clients with suppressed viral load in the past 12 months were 73% less likely to miss their appointments as compared to those who had never been bled for viral load (OR = 0.73; 95% C.I [0.2328 - 0.3125]); P &lt; 0.001). Additionally, clients with unsuppressed VL in the past 12 months were 51% less likely to miss their scheduled appointments as compared to their counterparts who have never been monitored for VL in the last 12 months (OR = 0.51; C.I [0.3792 - 0.6377] P &lt; 0.001). In the same vein, clients who received ART for one month, two months and three months, respectively were three or more times more likely to miss their scheduled appointments compared to those who received ART for 6 or more months (OR = 6.36, 5.29, 3.44; 95% C.I [4.8410 - 8.3617]; [4.0506 - 6.9072]; [3.0397 - 3.9012] P &lt; 0.001). On the contrary, sex was found to be insignificant in influencing missed appointments (P &gt; 0.05).</p><p>Further, the multivariate results from the columns of the adjusted odds ratios suggest that age group, service point and VL status are statistically significant influencers of missed appointments (P &lt; 0.05). Precisely, adults aged 25 years and above were 2.79 times more likely to miss their scheduled appointments as compared to children less than 10 years of age (OR = 2.79, 95% CI [1.8181 - 4.2724]; P &lt; 0.001). The youths were 2.42 times more likely to miss their scheduled appointments as compared to the children less than 10 years of age (OR = 2.42; 95% C.I [1.4663 - 3.9975]; P &lt; 0.001). Moreover, the adjusted ratios consistently suggest that clients receiving their ART care services from the facility were 1.82 times more likely to miss their scheduled visits as compared to their colleagues receiving treatment from the community arm (OR = 1.82; 95% C.I [1.5872 - 2.0943] P &lt; 0.001). As per the VL status, clients with suppressed VL in the last 12 months were 58% less likely to miss their appointments as compared to their counterparts without any VL results in the past 12 months (OR = 0.58; 95% C.I [0.3593 - 0.4949] P &lt; 0.001). Furthermore, those with unsuppressed VL results in the past 12 months were 46% less likely to miss their scheduled appointments when compared to their colleagues who were not bled for VL in the last 12 months (OR = 0.46; 95% C.I [0.4105 - 0.7181] P &lt; 0.001). The results also showed that clients who received ART for one month, two months and three months, respectively were two or more times more likely to miss their scheduled appointments compared to those who received ART for 6 or more months (OR = 2; 95 C.I [2.7916 - 5.1218]; [3.1609 - 5.7094]; [2.4289 - 3.2048] P &lt; 0.001). Therefore, six-month refills could potentially provide for continued engagement of PLHIV in care. At multivariate level, sex was not a significant influencer of missed appointments in the period of study, which is consistent with previous results from chi-square and unadjusted ratios (P &gt; 0.05)</p></sec><sec id="s4"><title>4. Discussions</title><p>In this study, we found that 1710 (25.3%) out of 6744 PLHIV on scheduled appointment during the April-June 2020 quarter missed their clinic encounters at TASO Mbale clinic compared to just 7.1% during the preceding quarter of January-March 2020. The PLHIV most likely to miss their clinic encounters were those without an up-to-date viral load test done in the previous twelve months before the period (P &lt; 0.05), those who were in the facility model of treatment compared to those served through the community arms (P &lt; 0.001), youths aged 20 - 24 years compared to other age groups (P &lt; 0.001), and those who received less than 6 months of drugs at their last clinic visit (P &lt; 0.001). There were no significant gender differences observed. Overall, there was a 356% increment in the missed appointment rate compared with the 7.1% (519/7279) experienced during the January-March 2020 quarter.</p><p>High rate of missed appointment among the PLHIV during this quarter could be attributed to increased clinical, psychological and structural barriers to accessing HIV treatment services, such as increased transport costs and transport lockdown restrictions, and perceived risk of increased COVID-19 exposure from health facilities as was described by Nalubega et al. and Linnemayr et al. [<xref ref-type="bibr" rid="scirp.114406-ref23">23</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref24">24</xref>]. Our finding is supported by a Chinese study that indicated that 32.6% of PLHIV could potentially miss their drugs and 48.6% were unsure of where or how to access the much-needed lifesaving ART during the lockdown [<xref ref-type="bibr" rid="scirp.114406-ref3">3</xref>]. Another study in the United States of America (US) reported rescheduling 30% of the 98 PLHIV on appointment during the first four weeks (March 21-April 17) of the COVID-19 peak in Chicago [<xref ref-type="bibr" rid="scirp.114406-ref25">25</xref>]. Furthermore, many HIV clinics reduced working hours to beat the curfew imposed by the Government of Uganda which further curtailed access to ART related services [<xref ref-type="bibr" rid="scirp.114406-ref7">7</xref>]. In addition, some key health workers were absorbed into the COVID-19 task force while others worked from home; thus, limiting service provision [<xref ref-type="bibr" rid="scirp.114406-ref7">7</xref>]. In TASO Mbale, like other health facilities in Uganda at the time, volunteers and students on academic placement in the facility were all asked to stay home. This resulted in further increased workload on the already limited available workforce. Importantly, domestic violence cases spiked during the lockdown restrictions with women living with HIV disproportionately affected and this further hampered their abilities to access HIV care services. For example, in South Africa, 67000 cases of domestic violence were reported in the first week of the COVID-19 lockdown [<xref ref-type="bibr" rid="scirp.114406-ref26">26</xref>].</p><p>Relatedly, this study revealed that facility-based clients were more likely to miss their appointment than their community-based counterparts; hence, suffering greater treatment interruption. From the study results, it can be concluded that the transport restrictions could have contributed significantly to this situation because TASO Mbale clinic provides services to individuals as far away from the facility as 75 km. In addition, it was perhaps easier to mobilize clients in their community groups using telephone calls directly to individual clients and through their leaders as well. As a result, the use of telemedicine has been highly recommended in the wake of the COVID-19 pandemic and even before, especially in improving retention among the PLHIV in care [<xref ref-type="bibr" rid="scirp.114406-ref27">27</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref28">28</xref>]. Our finding supports the findings by Zakumumpa et al. that the COVID-19 pandemic revived interest in community ART delivery models in Uganda, as part of efforts to sustain treatment services among PLHIV. He describes important modifications to and intensified implementation of traditional community drug delivery models such as home-based ART delivery, drug pick-up at Community Drug Distribution Points (CDDPs) and provision of longer treatment refills [<xref ref-type="bibr" rid="scirp.114406-ref29">29</xref>]. This further emphasizes the effectiveness of differentiated service delivery models of HIV care [<xref ref-type="bibr" rid="scirp.114406-ref30">30</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref31">31</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref32">32</xref>], which includes reduced geographic barriers, access to peer support, flexible services, client-centeredness and increased health systems efficiency [<xref ref-type="bibr" rid="scirp.114406-ref30">30</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref33">33</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref34">34</xref>] that are crucial in ensuring favorable HIV treatment outcomes such as viral load suppression, and less likelihood of PLHIV developing drug resistance, which is highly prevalent in Uganda [<xref ref-type="bibr" rid="scirp.114406-ref35">35</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref36">36</xref>]. Similarly, many HIV programs in Western Kenya adopted community approach to HIV care [<xref ref-type="bibr" rid="scirp.114406-ref7">7</xref>] to relieve pressure on the health system and reduce the waiting time for clients who seek HIV treatment services [<xref ref-type="bibr" rid="scirp.114406-ref21">21</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref37">37</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref38">38</xref>]. This is probably the main reason Lodge and Kuchukhidze recommended the scale up of community-based HIV treatment services to mitigate the immense and anticipated disruptions caused by COVID-19 [<xref ref-type="bibr" rid="scirp.114406-ref14">14</xref>].</p><p>The study found that youths aged 20 - 24 compared to children aged 0 - 9 years, had higher odds of missing their clinic appointments. Although this study could not find any findings that compared retention among the youths and children younger than 10 years, many reported equally lower retention rates among the groups compared to other age groups. For example, studies from Kenya and Thailand reported that the attrition rate was double among the youths compared to young adolescents aged 10 - 14 years old [<xref ref-type="bibr" rid="scirp.114406-ref39">39</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref40">40</xref>]. This is why it is not surprising that a large study involving PLHIV aged 10 years or older in four SSA countries of Kenya, Mozambique, Rwanda and Tanzania found the highest rates of attrition among the youths when compared with young adolescents [<xref ref-type="bibr" rid="scirp.114406-ref41">41</xref>]. Socioeconomic factors have been described as key barriers to continued engagement in care among the youths. These include geographical (urban vs rural) factors, low social support systems, low income status and non-disclosure of HIV status [<xref ref-type="bibr" rid="scirp.114406-ref41">41</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref42">42</xref>]. It is thus, important for HIV programs to design interventions and services that are youth-friendly in order to maintain them in care.</p><p>Unlike several reports from previous studies indicating higher attrition rate among men than women [<xref ref-type="bibr" rid="scirp.114406-ref43">43</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref44">44</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref45">45</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref46">46</xref>], we did not find significant gender differences in burden of missed appointments. However, it is important to note that those studies were conducted nearly a decade ago, yet there have been many interventions to close this gender disparity over the same period [<xref ref-type="bibr" rid="scirp.114406-ref22">22</xref>]. For example, TASO has been implementing differentiated service delivery model of HIV care for more than a decade now [<xref ref-type="bibr" rid="scirp.114406-ref19">19</xref>] and this could have provided men with similar treatment experiences in the clinic.</p><p>Furthermore, our study also found that viral load status was associated with the likelihood of attrition. Individuals who had an up-to-date VL status were less likely to miss their appointment compared with those without (P &lt; 0.001). There were no studies found reporting similar findings. However, it could be theorized that PLHIV who attend clinic visits with fidelity are likely to have their VL tests done compared to those who irregularly do so. This position is corroborated by the fact that majority of those without current VL results were in the facility arm (560 vs 320). Hence, this finding concretizes the call for enhanced community interventions for PLHIV.</p><p>Finally, clients who received a three- to a six-month’s ART refills seemed less likely to experience missed appointment. Termed as MMD, many policymakers have recommended its use to counter the rampant missed appointments among the PLHIV [<xref ref-type="bibr" rid="scirp.114406-ref17">17</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref22">22</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref34">34</xref>] and improve overall retention in care of clients. Indeed, PLHIV who received ART refills for three months or less were more likely to miss their scheduled appointments than those who were refilled for six months or more (P &lt; 0.001). It can be theorized that clients who received few drug refills have to visit the clinic more frequently, potentially experiencing greater economic costs, especially in the era of COVID-19 pandemic where transport costs are much higher than before compared with those whose appointments were more spaced. MMD ART refills are considered a key component of PLHIV centered care and the President’s Emergency Plan for AIDS Relief (PEPFAR) has consistently recommended its increased uptake to scale to avert the catastrophic impact of COVID-19 on client retention [<xref ref-type="bibr" rid="scirp.114406-ref17">17</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref47">47</xref>]. Therefore, a six-month’s ART refills appears to provide hope in reducing missed appointment schedules among the PLHIV, which could lead to the betterment of these individuals’ engagements in care. Nevertheless, there is a continued call to different HIV programs to ensure continuity of services as the COVID-19 situation continues to terrorize countries [<xref ref-type="bibr" rid="scirp.114406-ref48">48</xref>].</p></sec><sec id="s5"><title>5. Strengths of the Study</title><p>This study used routine program data, which potentially provides a true reflection of the situation on the ground.</p></sec><sec id="s6"><title>6. Study Limitations</title><p>The use of secondary data denied us the chance to obtain patient perspective on actual reasons for missing their scheduled appointments. This, therefore, presents an opportunity for a future study to consider this element of the study. Furthermore, this study only focused on one facility which means the findings may not necessarily be representative of the national situation. However, we believe the findings fairly represent the general national picture as all HIV service providers were similarly affected across the country. Also, this study does not describe the impact of the pandemic on patient treatment outcomes such as morbidity, mortality and viral load suppression. Further studies are required involving bigger sample sizes and with longitudinal follow up of clients to provide further information on the long-term impacts of the COVID-19 pandemic on chronic HIV care.</p></sec><sec id="s7"><title>7. Conclusion</title><p>1) The COVID-19 pandemic significantly interrupted HIV care as demonstrated by clients missing their scheduled appointment especially during the peak of COVID-19 pandemic in the country.</p><p>2) It was also found that MMD, specifically the six-month’s refills of ART appear to provide better engagement of the PLHIV in care.</p><p>3) Community-based PLHIV were less likely to miss their appointment than their facility-based counter-parts.</p></sec><sec id="s8"><title>Recommendation</title><p>1) Overall, chronic disease programs should adapt flexible service delivery models to ensure resilience in case of emergency of pandemics that restrict patient physical access to health care facilities. Therefore, different programs need to innovate or adapt strategies in order to mitigate HIV treatment interruptions.</p><p>2) There is need to encourage different HIV programs to adopt the MMD because it reduces treatment interruptions. The six-month’s refills particularly sappear to offer more favorable outcomes.</p><p>3) Furthermore, more resources need to be directed to retention. Clearly, the pandemic has and most likely, will continue to cause treatment interruptions. Therefore, it is going to be more costly to retain PLHIV in care than before the pandemic.</p><p>4) Lastly, it is necessary to adopt community-based HIV services across different age groups. This offers less treatment interruptions, so more focus and resources need to be directed towards community HIV programming. This will require more meaningful involvement of HIV peers which have been demonstrated to be effective elsewhere including in Prevention of Mother to Child Transmission of HIV [<xref ref-type="bibr" rid="scirp.114406-ref49">49</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref50">50</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref51">51</xref>] [<xref ref-type="bibr" rid="scirp.114406-ref52">52</xref>].</p></sec><sec id="s9"><title>Acknowledgements</title><p>We appreciate the USAID RHITES-E mechanism, through INTRAHEALTH and Ministry of Health-Uganda for providing financial and technical guidance to TASO Mbale clinic. We also sincerely thank TASO Uganda senior management and Mr. Gordon Karukomain particular for supporting publication of this study. In addition, Mr. Ceaser Godfrey Mafabi and the entire management team of TASO Mbale is appreciated for their unwavering efforts in supporting TASO Mbale clients and making this study a reality. Finally, we appreciate Mr. Sebastian Jalameso of National Curriculum Development Center (Uganda) for editing this work.</p></sec><sec id="s10"><title>Conflicts of Interest</title><p>The authors declare no conflicts of interest regarding the publication of this paper.</p></sec><sec id="s11"><title>Cite this paper</title><p>Oryokot, B., Kazibwe, A., Oluka, A.I., Miya, Y. and Etukoit, M.B. (2021) COVID-19 and HIV Treatment Interruption: A Case Study of the AIDS Support Organization (TASO) Mbale Clinic. World Journal of AIDS, 11, 199-215. https://doi.org/10.4236/wja.2021.114015</p></sec></body><back><ref-list><title>References</title><ref id="scirp.114406-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">WHO (World Health Organization) (2020, March 7) Responding to Community Spread of COVID-19. Interim Guidance, 1-6. https://www.who.int/publications/i/item/responding-to-community-spread-of-covid-19</mixed-citation></ref><ref id="scirp.114406-ref2"><label>2</label><mixed-citation publication-type="other" xlink:type="simple">WHO (World Health Organization) (2020) Infection Prevention and Control Guidance for Long-Term Care Facilities in the Context of COVID-19. Interim Guidance. World Health Organization, 1-5. https://apps.who.int/iris/handle/10665/331508</mixed-citation></ref><ref id="scirp.114406-ref3"><label>3</label><mixed-citation publication-type="other" xlink:type="simple">Nyoni, T. and Okumu, M. (2020) COVID-19-Compliant Strategies for Supporting Treatment Adherence among People Living with HIV in Sub-Saharan Africa. AIDS and Behavior, 24, 1-4. https://doi.org/10.1007/s10461-020-02888-0</mixed-citation></ref><ref id="scirp.114406-ref4"><label>4</label><mixed-citation publication-type="other" xlink:type="simple">Mhango, M., Chitungo, I. and Dzinamarira, T. (2020) COVID-19 Lockdowns: Impact on Facility-Based HIV Testing and the Case for the Scaling Up of Home-Based Testing Services in Sub-Saharan Africa. AIDS and Behavior, 24, 3014-3016. https://doi.org/10.1007/s10461-020-02939-6</mixed-citation></ref><ref id="scirp.114406-ref5"><label>5</label><mixed-citation publication-type="other" xlink:type="simple">Aimua, E.P. and Paul, J. (2021) Covid-19 and the Educational Sector: Challenges and the Need for Inclusive Education in Nigeria. Asian Journal of Economics, Business and Accounting, 21, 15-23. https://doi.org/10.9734/ajeba/2021/v21i530377</mixed-citation></ref><ref id="scirp.114406-ref6"><label>6</label><mixed-citation publication-type="other" xlink:type="simple">Jewell, B.L., Mudimu, E., Stover, J., ten Brink, D., Phillips, A.N., Smith, J.A., et al. (2020) Potential Effects of Disruption to HIV Programmes in Sub-Saharan Africa Caused by COVID-19: Results from Multiple Mathematical Models. Lancet HIV, 7, e629-e640. https://doi.org/10.1016/S2352-3018(20)30211-3</mixed-citation></ref><ref id="scirp.114406-ref7"><label>7</label><mixed-citation publication-type="other" xlink:type="simple">Lagat, H., Sharma, M., Kariithi, E., Otieno, G., Katz, D., Masyuko, S., et al. (2020) Impact of the COVID-19 Pandemic on HIV Testing and Assisted Partner Notification Services, Western Kenya. AIDS and Behavior, 24, 3010-3013. https://doi.org/10.1007/s10461-020-02938-7</mixed-citation></ref><ref id="scirp.114406-ref8"><label>8</label><mixed-citation publication-type="other" xlink:type="simple">Pinto, R.M. and Park, S. (2020) COVID-19 Pandemic Disrupts HIV Continuum of Care and Prevention: Implications for Research and Practice Concerning Community-Based Organizations and Frontline Providers. AIDS and Behavior, 24, 2486-2489. https://doi.org/10.1007/s10461-020-02893-3</mixed-citation></ref><ref id="scirp.114406-ref9"><label>9</label><mixed-citation publication-type="other" xlink:type="simple">Oryokot, B., Miya, Y., Logose, B., Ajambo, E., Oluka, A., Odoi, C., et al. (2020) Interventions to Improve HIV Viral Load Suppression among the Adolescents: Evidence of Improvement Science through a Quality Improvement Approach in Eastern Uganda. World Journal of AIDS, 10, 94-106. https://doi.org/10.4236/wja.2020.102008</mixed-citation></ref><ref id="scirp.114406-ref10"><label>10</label><mixed-citation publication-type="other" xlink:type="simple">Hogan, A.B., Jewell, B.L., Sherrard-Smith, E., Vesga, J.F., Watson, O.J., Whittaker, C., et al. (2020) Potential Impact of the COVID-19 Pandemic on HIV, Tuberculosis, and Malaria in Low-Income and Middle-Income Countries: A Modelling Study. The Lancet Global Health, 8, e1132-e1141. https://doi.org/10.1016/S2214-109X(20)30288-6</mixed-citation></ref><ref id="scirp.114406-ref11"><label>11</label><mixed-citation publication-type="other" xlink:type="simple">The Lancet (2020) Maintaining the HIV Response in a World Shaped by COVID-19. The Lancet, 396, 1703. https://doi.org/10.1016/S0140-6736(20)32526-5https://pubmed.ncbi.nlm.nih.gov/33248482/</mixed-citation></ref><ref id="scirp.114406-ref12"><label>12</label><mixed-citation publication-type="other" xlink:type="simple">UAC (Uganda Aids Commission) (2019) Uganda Aids Commission Facts on HIV and Aids in Uganda 2020.</mixed-citation></ref><ref id="scirp.114406-ref13"><label>13</label><mixed-citation publication-type="other" xlink:type="simple">United Nations Joint Programme on HIV/AIDS (UNAIDS) (2019) Country Factsheets Uganda. 2019 HIV and AIDS Estimates Adults and Children. United Nations Joint Programme on HIV/AIDS (UNAIDS), Geneva, 1-10.</mixed-citation></ref><ref id="scirp.114406-ref14"><label>14</label><mixed-citation publication-type="other" xlink:type="simple">Lodge, W. and Kuchukhidze, S. (2020) COVID-19, HIV, and Migrant Workers: The Double Burden of the Two Viruses. AIDS Patient Care and STDs, 34, 249-250. https://doi.org/10.1089/apc.2020.0092</mixed-citation></ref><ref id="scirp.114406-ref15"><label>15</label><mixed-citation publication-type="other" xlink:type="simple">Walker, J. (2016) Achieving Health SDG 3 in Africa through NGO Capacity Building—Insights from the Gates Foundation Investment in Partnership in Advocacy for Child and Family Health (PACFaH) Project. African Journal of Reproductive Health, 20, 55-61. https://doi.org/10.29063/ajrh2016/v20i3.10</mixed-citation></ref><ref id="scirp.114406-ref16"><label>16</label><mixed-citation publication-type="other" xlink:type="simple">Golin, R., Godfrey, C., Firth, J., Lee, L., Minior, T., et al. (2020) PEPFAR’s Response to the Convergence of the HIV and COVID-19 Pandemics in Sub-Saharan Africa. Journal of the International AIDS Society, 23, Article ID: e25587. https://doi.org/10.1002/jia2.25587</mixed-citation></ref><ref id="scirp.114406-ref17"><label>17</label><mixed-citation publication-type="other" xlink:type="simple">U.S. President’s Emergency Plan for AIDS Relief (PEPFAR) (2020) PEPFAR Technical Guidance in Context of COVID-19 Pandemic. Washington DC, 1-36.</mixed-citation></ref><ref id="scirp.114406-ref18"><label>18</label><mixed-citation publication-type="other" xlink:type="simple">TASO (The AIDS Support Organization) (2017) TASO Strategic Plan 2018-2022. The AIDS Support Organization, Uganda.</mixed-citation></ref><ref id="scirp.114406-ref19"><label>19</label><mixed-citation publication-type="other" xlink:type="simple">The AIDS Support Organization (TASO) (2016) Community Client-Led ART Delivery Model (CCLAD). The AIDS Support Organization, Uganda, 6.</mixed-citation></ref><ref id="scirp.114406-ref20"><label>20</label><mixed-citation publication-type="other" xlink:type="simple">Sarah, K., Julie, R., Julian, H. and Andrew, E. (2011) Cases in Global Health Delivery: The AIDS Support Organization (TASO) of Uganda. No. 44, Harvard Business Publishing, Boston, 1-36.</mixed-citation></ref><ref id="scirp.114406-ref21"><label>21</label><mixed-citation publication-type="other" xlink:type="simple">Ministry of Health of Uganda (2020) National Training Curriculum for Roll Out of the Consolidated Guidelines for the Prevention and Treatment of HIV and Aids in. Ministry of Health of Uganda, Kampala.</mixed-citation></ref><ref id="scirp.114406-ref22"><label>22</label><mixed-citation publication-type="other" xlink:type="simple">U.S. President’s Emergency Plan for AIDS Relief (PEPFAR) (2020) PEPFAR 2020 Country Operational Plan Guidance for All PEPFAR Countries. PEPFAR, Washington DC.</mixed-citation></ref><ref id="scirp.114406-ref23"><label>23</label><mixed-citation publication-type="other" xlink:type="simple">Nalubega, S., Kyenkya, J., Bagaya, I., Nabukenya, S., Ssewankambo, N., Nakanjako, D., et al. (2021) COVID-19 May Exacerbate the Clinical, Structural and Psychological Barriers to Retention in Care among Women Living with HIV in Rural and Peri-Urban Settings in Uganda. BMC Infectious Diseases, 21, Article No. 980. https://doi.org/10.1186/s12879-021-06684-6</mixed-citation></ref><ref id="scirp.114406-ref24"><label>24</label><mixed-citation publication-type="other" xlink:type="simple">Linnemayr, S., Jennings Mayo-Wilson, L., Saya, U., Wagner, Z., MacCarthy, S., Walukaga, S., et al. (2021) HIV Care Experiences during the COVID-19 Pandemic: Mixed-Methods Telephone Interviews with Clinic-Enrolled HIV-Infected Adults in Uganda. AIDS and Behavior, 25, 28-39. https://doi.org/10.1007/s10461-020-03032-8</mixed-citation></ref><ref id="scirp.114406-ref25"><label>25</label><mixed-citation publication-type="other" xlink:type="simple">Ridgway, J.P., Schmitt, J., Friedman, E., Taylor, M., Devlin, S., McNulty, M., et al. (2020) HIV Care Continuum and COVID-19 Outcomes among People Living with HIV during the COVID-19 Pandemic, Chicago, IL. AIDS and Behavior, 24, 2770-2772. https://doi.org/10.1007/s10461-020-02905-2</mixed-citation></ref><ref id="scirp.114406-ref26"><label>26</label><mixed-citation publication-type="other" xlink:type="simple">Joska, J.A., Andersen, L., Rabie, S., Marais, A., Ndwandwa, E.S., Wilson, P., et al. (2020) COVID-19: Increased Risk to the Mental Health and Safety of Women Living with HIV in South Africa. AIDS and Behavior, 24, 2751-2753. https://doi.org/10.1007/s10461-020-02897-z</mixed-citation></ref><ref id="scirp.114406-ref27"><label>27</label><mixed-citation publication-type="other" xlink:type="simple">Mgbako, O., Miller, E.H., Santoro, A.F., Remien, R.H., et al. (2020) COVID-19, Telemedicine, and Patient Empowerment in HIV Care and Research. AIDS and Behavior, 24, 1990-1993. https://doi.org/10.1007/s10461-020-02926-x</mixed-citation></ref><ref id="scirp.114406-ref28"><label>28</label><mixed-citation publication-type="other" xlink:type="simple">Hermans, S.M., Elbireer, S., Tibakabikoba, H., Hoefman, B.J. and Manabe, Y.C. (2017) Text Messaging to Decrease Tuberculosis Treatment Attrition in TB-HIV Coinfection in Uganda. Patient Preference and Adherence, 11, 1479-1487. https://doi.org/10.2147/PPA.S135540</mixed-citation></ref><ref id="scirp.114406-ref29"><label>29</label><mixed-citation publication-type="other" xlink:type="simple">Zakumumpa, H., Tumwine, C., Milliam, K. and Spicer, N. (2021) Dispensing Antiretrovirals during Covid-19 Lockdown: Re-Discovering Community-Based ART Delivery Models in Uganda. BMC Health Services Research, 21, Article No. 692. https://doi.org/10.1186/s12913-021-06607-w</mixed-citation></ref><ref id="scirp.114406-ref30"><label>30</label><mixed-citation publication-type="other" xlink:type="simple">ICAP (2017) ICAP Approach to Differentiated Service Delivery. ICAP, New York, p. 7. https://cquin.icap.columbia.edu/wp-content/uploads/2017/07/ICAP_CQUIN_ICAP_Approach_to_DSD_July2017.pdf</mixed-citation></ref><ref id="scirp.114406-ref31"><label>31</label><mixed-citation publication-type="other" xlink:type="simple">Kandasami, S., Shobiye, H., Fakoya, A., Asiimwe, S., Inimah, M., Etukoit, M., et al. (2019) Can Changes in Service Delivery Models Improve Program Quality and Efficiency? A Closer Look at HIV Programs in Kenya and Uganda. JAIDS Journal of Acquired Immune Deficiency Syndromes, 81, 533-539. https://doi.org/10.1097/QAI.0000000000002064</mixed-citation></ref><ref id="scirp.114406-ref32"><label>32</label><mixed-citation publication-type="other" xlink:type="simple">WHO (World Health Organization) (2016) Meeting report Consultation on HIV Differentiated Service Delivery Models for Specific Populations and Settings: Pregnant and Breastfeeding Women, Children, Adolescents and Key Populations. World Health Organization, Geneva, 2-4. http://www.who.int/hiv/pub/meetingreports/DSDmeetingreportJan122017.pdf</mixed-citation></ref><ref id="scirp.114406-ref33"><label>33</label><mixed-citation publication-type="other" xlink:type="simple">Eshun-Wilson. I., Mukumbwa-Mwenechanya, M., Kim, H.Y., Zannolini, A., Mwamba, C.P., Dowdy, D., et al. (2019) Differentiated Care Preferences of Stable Patients on Antiretroviral Therapy in Zambia: A Discrete Choice Experiment. JAIDS Journal of Acquired Immune Deficiency Syndromes, 81, 540-546. https://doi.org/10.1097/QAI.0000000000002070</mixed-citation></ref><ref id="scirp.114406-ref34"><label>34</label><mixed-citation publication-type="other" xlink:type="simple">MOH-Uganda (Ministry of Health of Uganda) (2017) Implementation Guide for Differentiated Service Delivery of HIV Services in Uganda. Ministry of Health of Uganda, Kampala.</mixed-citation></ref><ref id="scirp.114406-ref35"><label>35</label><mixed-citation publication-type="other" xlink:type="simple">Kityo, C., Boerma, R.S., Sigaloff, K.C.E., Kaudha, E., Calis, J.C.J., Musiime, V., et al. (2017) Pretreatment HIV Drug Resistance Results in Virological Failure and Accumulation of Additional Resistance Mutations in Ugandan Children. Journal of Antimicrobial Chemotherapy, 72, 2587-2595. https://doi.org/10.1093/jac/dkx188</mixed-citation></ref><ref id="scirp.114406-ref36"><label>36</label><mixed-citation publication-type="other" xlink:type="simple">WHO (World Health Organization) (2019) Preventing and Responding to HIV Drug Resistance in the African Region: Regional Action Plan 2019-2023. World Health Organization, Brazzaville.</mixed-citation></ref><ref id="scirp.114406-ref37"><label>37</label><mixed-citation publication-type="other" xlink:type="simple">MOH-Uganda (Ministry of Health of Uganda) (2018) Consolidated Guidelines on the Prevention and Treatment of HIV. Ministry of Health of Uganda, Kampala.</mixed-citation></ref><ref id="scirp.114406-ref38"><label>38</label><mixed-citation publication-type="other" xlink:type="simple">World Health Organization (2016) Consolidated Guidelines on the Use of Antiretroviral Drugs for Treating and Preventing HIV Infection. World Health Organization, Geneva.</mixed-citation></ref><ref id="scirp.114406-ref39"><label>39</label><mixed-citation publication-type="other" xlink:type="simple">Emily Koecha, E.J.A., Teasdalea, C.A., Wanga, C., Fayorseya, R., Alwara, T., Mukuic, I.N. and Hawkena, M. (2016) Characteristics and Outcomes of HIV-Infected Youth and Young Adolescents Enrolled in HIV Care in Kenya. AIDS, 28, 2729-2738. https://doi.org/10.1097/QAD.0000000000000473</mixed-citation></ref><ref id="scirp.114406-ref40"><label>40</label><mixed-citation publication-type="other" xlink:type="simple">Teeraananchai, S., Puthanakit, T., Kerr, S.J., Chaivooth, S., Kiertiburanakul, S., Chokephaibulkit, K., et al. (2019) Attrition and Treatment Outcomes among Adolescents and Youths Living with HIV in the Thai National AIDS Program. Journal of Virus Eradication, 5, 33-40. https://doi.org/10.1016/S2055-6640(20)30276-4</mixed-citation></ref><ref id="scirp.114406-ref41"><label>41</label><mixed-citation publication-type="other" xlink:type="simple">Lamb, M.R., Fayorsey, R., Nuwagaba-Biribonwoha, H., Viola, V., Mutabazi, V., Alwar, T., et al. (2014) High Attrition before and after ART Initiation among Youth (15-24 Years of Age) Enrolled in HIV Care. AIDS, 28, 559-568. https://doi.org/10.1097/QAD.0000000000000054</mixed-citation></ref><ref id="scirp.114406-ref42"><label>42</label><mixed-citation publication-type="other" xlink:type="simple">Colasanti, J., Stahl, N., Farber, E.W., Del Rio, C. and Armstrong, W.S. (2017) An Exploratory Study to Assess Individual and Structural Level Barriers Associated with Poor Retention and Re-Engagement in Care among Persons Living with HIV/AIDS. JAIDS Journal of Acquired Immune Deficiency Syndromes, 74, S113-S120. https://doi.org/10.1097/QAI.0000000000001242</mixed-citation></ref><ref id="scirp.114406-ref43"><label>43</label><mixed-citation publication-type="other" xlink:type="simple">Cornell, M., Schomaker, M., Garone, D.B., Giddy, J., Hoffmann, C.J., Lessells, R., et al. (2012) Gender Differences in Survival among Adult Patients Starting Antiretroviral Therapy in South Africa: A Multicentre Cohort Study. PLoS Medicine, 9, e1001304. https://doi.org/10.1371/journal.pmed.1001304</mixed-citation></ref><ref id="scirp.114406-ref44"><label>44</label><mixed-citation publication-type="other" xlink:type="simple">Hawkins, C., Chalamilla, G., Okuma, J., Spiegelman, D., Hertzmark, E., Aris, E., et al. (2011) Sex Differences in Antiretroviral Treatment Outcomes among HIV-Infected Adults in an Urban Tanzanian Setting. AIDS, 25, 1189-1197. https://doi.org/10.1097/QAD.0b013e3283471deb</mixed-citation></ref><ref id="scirp.114406-ref45"><label>45</label><mixed-citation publication-type="other" xlink:type="simple">Ochieng-Ooko, V., Ochieng, D., Sidle, J.E., Holdsworth, M., Wools-Kaloustian, K., Siika, A.M., et al. (2010) Influence du sexe de la personne sur la perte du suivi dans un vaste programme de traitement du VIH dans l’ouest du Kenya. Bulletin of the World Health Organization, 88, 681-688. https://doi.org/10.2471/BLT.09.064329</mixed-citation></ref><ref id="scirp.114406-ref46"><label>46</label><mixed-citation publication-type="other" xlink:type="simple">Kranzer, K., Lewis, J.J., Ford, N., Zeinecker, J., Orrell, C., Lawn, S.D., et al. (2010) Treatment Interruption in a Primary Care Antiretroviral Therapy Program in South Africa: Cohort Analysis of Trends and Risk Factors. Journal of Acquired Immune Deficiency Syndromes, 55, 17-23. https://doi.org/10.1097/QAI.0b013e3181f275fd</mixed-citation></ref><ref id="scirp.114406-ref47"><label>47</label><mixed-citation publication-type="other" xlink:type="simple">PEPFAR (The U.S. President’s Emergency Plan for AIDS Relief) (2020) PEPFAR 2021 Country and Regional Operational Plan (COP/ROP) Guidance for all PEPFAR Countries. PEPFAR, Washington DC, 1-487. https://www.state.gov/wp-content/uploads/2020/12/PEPFAR-COP21-Guidance-Final.pdf</mixed-citation></ref><ref id="scirp.114406-ref48"><label>48</label><mixed-citation publication-type="other" xlink:type="simple">Hightow-Weidman, L., Muessig, K., Claude, K., Roberts, J., Zlotorzynska, M. and Sanchez, T. (2020) Maximizing Digital Interventions for Youth in the Midst of Covid-19: Lessons from the Adolescent Trials Network for HIV Interventions. AIDS and Behavior, 24, 2239-2243. https://doi.org/10.1007/s10461-020-02870-w</mixed-citation></ref><ref id="scirp.114406-ref49"><label>49</label><mixed-citation publication-type="other" xlink:type="simple">Igumbor, J.O., Ouma, J., Otwombe, K., Musenge, E., Anyanwu, F.C., Basera, T., et al. (2019) Effect of a Mentor Mother Programme on Retention of Mother-Baby Pairs in HIV Care: A Secondary Analysis of Programme Data in Uganda. PLoS ONE, 14, e0223332. https://doi.org/10.1371/journal.pone.0223332</mixed-citation></ref><ref id="scirp.114406-ref50"><label>50</label><mixed-citation publication-type="other" xlink:type="simple">Choko, A.T., Nanfuka, M., Birungi, J., Taasi, G., Kisembo, P. and Helleringer, S. (2018) A Pilot Trial of the Peer-Based Distribution of HIV Self-Test Kits among Fishermen in Bulisa, Uganda. PLoS ONE, 13, e0208191. https://doi.org/10.1371/journal.pone.0208191</mixed-citation></ref><ref id="scirp.114406-ref51"><label>51</label><mixed-citation publication-type="other" xlink:type="simple">Inzaule, S.C., Hamers, R.L., Kityo, C., Rinke De Wit, T.F. and Roura, M. (2016) Long-Term Antiretroviral Treatment Adherence in HIV-Infected Adolescents and Adults in Uganda: A Qualitative Study. PLoS ONE, 11, e0167492. https://doi.org/10.1371/journal.pone.0167492</mixed-citation></ref><ref id="scirp.114406-ref52"><label>52</label><mixed-citation publication-type="other" xlink:type="simple">ICAP (2019) Infant HIV Testing Implementation Guide for Programme Managers. ICAP, New York.https://icap.columbia.edu/tools_resources/infant-hiv-testing-guide/</mixed-citation></ref></ref-list></back></article>