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. 2023 Mar 29;93(4):261–271. doi: 10.1097/QAI.0000000000003201

Impact of COVID-19 on HIV Adolescent Programming in 16 Countries With USAID-Supported PEPFAR Programs

Tishina Okegbe a,✉, Jessica Williams b, Kate F Plourde c, Kelsey Oliver d, Barbara Ddamulira e, Kristina Caparrelli f, USAID/PEPFAR Adolescent Group
PMCID: PMC10287048  PMID: 36989134

Introduction:

The COVID-19 pandemic has disrupted access to critical health services, resulting in diminished gains in HIV epidemic control. This review assesses the magnitude of the impact that the COVID-19 pandemic has had on HIV services for adolescents.

Methods:

PEPFAR Monitoring, Evaluation, and Reporting programmatic data were analyzed from across 16 USAID-supported adolescent care and treatment programs for fiscal year 2020 (FY20; October 2019–September 2020). Descriptive statistics were used to calculate absolute number and percent change between the pre-COVID-19 (Quarters 1–2; October 2019–March 2020) and COVID-19 periods (Quarters 3–4; April 2020–September 2020) for clinical cascade indicators. All analyses were conducted in Microsoft Excel.

Results:

The number of HIV tests conducted during COVID-19 decreased by 21.4% compared with pre-COVID-19, with a subsequent 28% decrease in adolescents identified living with HIV. The rate of proxy linkage to antiretroviral therapy increased between periods, from 86.9% to 90.4%. There was a 25.9% decrease in treatment initiations among adolescents during COVID-19. During FY20, viral load coverage rates for adolescents dropped from 81.6% in FY20Q1 to 76.5% in FY20Q4, whereas the rates of viral load suppression for adolescents increased from 76.1% in FY20Q1 to 80.5% in FY20Q4.

Conclusion:

There was a substantial decrease in case-finding, treatment initiations, and viral load coverage rates for adolescents supported in USAID/PEPFAR programs during the COVID-19 pandemic. Additional health systems adaptations and strategies are required to ensure adolescents have continued access to HIV services during pandemic disruptions.

Key Words: adolescents, HIV, COVID-19, care and treatment

BACKGROUND

Globally, adolescents account for a growing proportion of the total number of people living with HIV. In 2019, an estimated 1.7 million adolescents were living with HIV (ALHIV), and approximately 84% of all ALHIV (10–19 year old) were living in sub-Saharan Africa.1,2 Compared with adults living with HIV, ALHIV have significantly lower rates of linkage to treatment, retention, adherence, and viral suppression; higher rates of interruptions in treatment; and a greater need for psychosocial and sexual reproductive health services.2–4 In 2020, an estimated 54% of children (0–14 years old) and ALHIV received antiretroviral therapy (ART) compared with 74% of adults living with HIV (15 years and older)—and this percentage may be declining.1 Furthermore, AIDS-related deaths among ALHIV have declined more slowly over the last decade (45%) when compared with the declines seen among children living with HIV (55%) but on par with adults living with HIV (44%%).1

The COVID-19 pandemic and associated control measures have resulted in the disruption of critical health services and increased social and structural barriers to health globally, threatening to reverse gains in HIV epidemic control for all age groups. Evidence suggests that the impact of COVID-19 may further exacerbate the barriers to prevention and treatment among adolescents, an already marginalized population.5–8 Recorded impacts of the COVID-19 pandemic on the lives of adolescents include prolonged school closure, increased economic hardship, social isolation, reduced food intake, increased gender-based violence, and an uptick in teenage pregnancy.9–12 Furthermore, many adolescents have experienced negative mental health outcomes as a result of COVID-19, with decreased access to psychosocial support.13–15 In addition, findings from South Africa and the United States demonstrate that ALHIV on treatment experienced increased vulnerabilities during the pandemic, including economic loss, food insecurity, and treatment interruptions.16,17 A greater understanding of the magnitude of the COVID-19 pandemic's impact on HIV services for adolescents globally is needed.

The President's Emergency Plan for AIDS Relief (PEPFAR) supports country-led efforts to combat the complex challenges of HIV/AIDS through HIV testing, care, and treatment in 28 country/regional programs, reaching millions of individuals.18 The availability of age-disaggregated and sex-disaggregated USAID/PEPFAR program data provides a unique opportunity to examine the impact of the COVID-19 pandemic on adolescent access to and utilization of HIV services. This analysis aimed to compare HIV case-finding, linkage to treatment, and viral load coverage (VLC) and suppression (VLS) for adolescents in USAID/PEPFAR programs between the periods before and during the COVID-19 pandemic.

METHODS

Routinely reported PEPFAR Monitoring, Evaluation, and Reporting programmatic data were analyzed from across all USAID-supported countries for fiscal year 2020 (FY20; October 2019–September 2020). Quarters 1 and 2 (October 2019–March 2020) constitute the pre-COVID-19 time period, and Quarters 3 and 4 (April 2020–September 2020) constitute the during COVID-19 period. The 16 countries include Burundi, Dominican Republic (DR), Democratic Republic of the Congo (DRC), Eswatini, Haiti, Kenya, Lesotho, Malawi, Mozambique, Nigeria, South Africa, South Sudan, Tanzania, Uganda, Zambia, and Zimbabwe.

Descriptive statistics were used to calculate absolute number and percent change between the pre-COVID-19 and COVID-19 periods for the following indicators for adolescents: number of HIV tests, number of HIV-positive tests, number newly initiated on ART, total number on ART, number with a viral load (VL) test conducted, and number with a suppressed VL (<1000 copies/mL). The following indicators were calculated: positivity (percent of tests that were positive), number needed to test to find 1 positive (NNT) (number of tests/number of positive tests), proxy ART linkage (percent of positives newly initiated on ART), proxy VLC (percent of patients eligible for VL testing who have received a test), and VLS (percent of VL tests with less than 1000 copies/mL). HIV testing data by testing modality were also analyzed, including proportion of HIV tests, HIV-positive results, positivity, and NNT for each modality.

Analyses were conducted for the entire 10–19-year-old age band as well as disaggregated by younger adolescents (10–14-year-old), older adolescents (15–19-year-old) and sex (males and females). All analyses were conducted in Microsoft Excel Version 16.62.

RESULTS

HIV Testing

Overall, the number of HIV tests conducted in adolescents during COVID-19 decreased by 21.4% (FY20Q3 & FY20Q4; 1,230,165) compared with the number of tests conducted pre-COVID-19 (FY20Q1 & FY20Q2; 1,564,323; Fig. 1). The largest quarterly decline in testing was observed between FY20Q2 and FY20Q3 (−33.5%). A large rebound occurred in FY20Q4, with 708,760 HIV tests conducted; a 35.9% increase over the number of tests conducted in FY20Q3 but still below the pre-COVID quarterly volume.

FIGURE 1.

FIGURE 1.

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First 95, adolescent testing, positivity yield and NNT by sex and age in USAID/PEPFAR programs, FY20. (A) Testing and yield by sex. (B) Testing and yield by age. (C) Number needed to test and yield by sex. (D) Number needed to test and yield by age.

Pre-COVID-19, 67.3% of tests were conducted among female adolescents, increasing to 73.8% during COVID-19. Most tests (78.4%) were conducted among older adolescents (15–19 years) pre-COVID-19, encompassing an even larger percentage (85.5%) during COVID-19. Younger adolescents (10–14 years) experienced a sharp decline in testing during COVID-19 compared with pre-COVID-19 (−47.1%; Fig. 1). Most countries experienced drops in testing during COVID-19 with the steepest declines occurring in Haiti (−71.5%; Table 1), Zimbabwe (−58.9%), and DRC (−45%). Four countries experienced testing increases during COVID-19 included Kenya (5.5%), Nigeria (5.5%), Tanzania (3.8%), and Burundi (1.1%). The number of tests decreased for multiple testing modalities, with the steepest declines observed in emergency (−74.4%; Table 1), voluntary male medical circumcision (−59.5%), and both community voluntary counseling and testing (VCT) and facility VCT (−28.4%). Testing increases were observed in the following 3 modalities: sexually transmitted infection clinics (19.3%), index facility (9.8%), and postantenatal care visit 1 (5.4%).

TABLE 1.

HIV Testing, Case-Finding, Testing Yield, and NNT in Adolescents in USAID/PEPFAR Programs, FY20

Number of HIV Tests Number of HIV-Positive Tests Yield %* Number Needed to Test†
Pre-COVID During COVID Pre-COVID During COVID Pre-COVID During COVID Pre-COVID During COVID
FY20Q1 FY20Q2 Total FY20Q3 FY20Q4 Total FY20Q1 FY20Q2 Total FY20Q3 FY20Q4 Total FY20Q1 FY20Q2 Average FY20Q3 FY20Q4 Average FY20Q1 FY20Q2 Average FY20Q3 FY20Q4 Average
Total 10–19 780,342 783,981 1,564,323 521,404 708,760 1,230,165 15,057 14,115 29,171 9888 10,878 20,766 1.9% 1.7% 1.9% 2.0% 1.7% 1.7% 52 56 54 53 65 59
Age
 10–14 yrs 169,651 168,516 338,167 74,899 103,845 178,744 2906 2652 5558 1674 1902 3576 1.7% 1.6% 1.6% 2.2% 1.8% 2.0% 58 64 61 45 55 50
 15–19 yrs 610,691 615,465 1,226,156 446,506 604,915 1,051,421 12,151 11,463 23,614 8214 8976 17,190 2.0% 1.9% 1.9% 1.8% 1.5% 1.6% 50 54 52 54 67 61
Sex
 Female 522,514 530,570 1,053,084 406,757 500,601 907,358 11,660 10,986 22,646 7836 8546 16,382 2.2% 2.1% 2.2% 2.0% 1.8% 1.8% 45 48 47 52 59 56
 Male 257,828 253,411 511,239 114,648 208,159 322,807 3397 3129 6526 2052 2332 4384 1.3% 1.2% 1.3% 2.0% 1.4% 1.4% 76 81 79 56 89 73
Country
 Burundi 10,399 10,144 20,543 10,431 10,346 20,777 200 183 383 165 147 312 1.9% 1.8% 1.9% 1.6% 1.4% 1.5% 52 55 54 63 70 67
 DR 13,440 13,972 27,412 12,665 12,565 25,230 336 371 707 286 361 647 2.5% 2.7% 2.6% 2.3% 2.9% 2.6% 40 38 39 44 35 40
 DRC 3358 3414 6772 1236 2490 3726 29 35 64 12 43 55 0.9% 1.0% 0.9% 1.0% 1.7% 1.5% 116 98 107 103 58 80
 Eswatini 3960 4348 8308 4274 6856 11,130 50 51 101 53 57 110 1.3% 1.2% 1.2% 1.2% 0.8% 1.0% 79 85 82 81 120 100
 Haiti 25,649 20,614 46,263 7327 5866 13,193 197 174 371 101 73 174 0.8% 0.8% 0.8% 1.4% 1.2% 1.3% 130 118 124 73 80 76
 Kenya 6853 9212 16,065 5122 11,820 16,942 178 217 395 81 244 325 2.6% 2.4% 2.5% 1.6% 2.1% 1.9% 39 42 40 63 48 56
 Lesotho 73,148 66,923 140,071 58,187 81,717 139,904 632 659 1291 538 612 1150 0.9% 1.0% 0.9% 0.9% 0.7% 0.8% 116 102 109 108 134 121
 Malawi 65,702 42,312 108,014 22,096 41,643 63,739 726 490 1216 274 526 800 1.1% 1.2% 1.1% 1.2% 1.3% 1.3% 90 86 88 81 79 80
 Mozambique 60,594 62,625 123,219 36,681 41,666 78,347 1106 1267 2373 887 885 1772 1.8% 2.0% 1.9% 2.4% 2.1% 2.3% 55 49 52 41 47 44
 Nigeria 61,921 66,901 128,822 45,739 90,196 135,935 2043 1510 3553 984 1447 2431 3.3% 2.3% 2.8% 2.2% 1.6% 1.8% 30 44 37 46 62 54
 South Africa 220,033 222,760 442,793 138,477 176,864 315,341 5188 5020 10,208 2977 3056 6033 2.4% 2.3% 2.3% 2.1% 1.7% 1.9% 42 44 43 47 58 52
 South Sudan 2472 2676 5148 2339 2208 4547 51 57 108 31 31 62 2.1% 2.1% 2.1% 1.3% 1.4% 1.4% 48 47 48 75 71 73
 Tanzania 37,551 41,920 79,471 41,871 40,594 82,465 844 828 1672 918 713 1631 2.2% 2.0% 2.1% 2.2% 1.8% 2.0% 44 51 48 46 57 51
 Uganda 95,859 110,870 206,729 81,192 122,929 204,121 1011 1111 2122 1067 1081 2148 1.1% 1.0% 1.0% 1.3% 0.9% 1.1% 95 100 97 76 114 95
 Zambia 51,683 44,285 95,968 34,161 35,901 70,062 1409 1076 2485 1001 934 1935 2.7% 2.4% 2.6% 2.9% 2.6% 2.8% 37 41 39 34 38 36
 Zimbabwe 47,720 61,005 108,725 19,607 25,099 44,706 1057 1066 2123 513 668 1181 2.2% 1.7% 2.0% 2.6% 2.7% 2.6% 45 57 51 38 38 38
Modality
 Community mobile 61,804 65,434 127,238 40,233 78,508 118,741 1461 1409 2870 803 1209 2012 2.4% 2.2% 2.3% 2.1% 1.4% 1.7% 42 46 44 50 65 58
 Community VCT 6371 5679 12,050 3528 5102 8630 179 146 325 170 148 318 2.6% 2.4% 2.7% 2.5% 2.5% 3.7% 36 39 37 21 34 28
 Emergency 10,729 2669 13,398 1546 1887 3433 276 82 358 71 51 122 2.6% 3.7% 2.7% 4.7% 2.9% 3.6% 39 33 36 22 37 29
 Index (community) 8223 6390 14,613 4203 6907 11,110 1149 773 1922 450 757 1207 13.3% 13.5% 13.2% 10.7% 11.3% 10.9% 7 8 8 9 9 9
 Index (facility) 16,719 16,201 32,920 14,135 22,020 36,155 1761 1722 3483 1410 1484 2894 11.9% 12.1% 10.6% 11.8% 8.1% 8.0% 9 9 9 10 15 12
 Inpatient 9656 12,044 21,700 10,250 10,164 20,414 179 188 367 153 134 287 1.8% 1.5% 1.7% 1.6% 1.3% 1.4% 54 64 59 67 76 71
 Other communities 9293 8731 18,024 4180 10,005 14,185 217 159 376 89 125 214 2.8% 1.4% 2.1% 1.6% 0.9% 1.5% 43 55 49 47 80 64
 Other PITC 337,818 350,472 688,290 234,024 301,486 535,510 6011 5964 11,975 3864 4146 8010 1.7% 1.6% 1.7% 1.6% 1.3% 1.5% 56 59 57 61 73 67
 PMTCT ANC 129,185 131,291 260,476 120,282 126,800 247,082 1751 1763 3514 1465 1449 2914 1.1% 1.3% 1.3% 1.2% 1.1% 1.2% 74 74 74 82 88 85
 Post ANC1 27,992 31,554 59,546 30,500 32,248 62,748 160 219 379 295 208 503 0.4% 1.3% 0.6% 0.7% 0.6% 0.8% 175 144 160 103 155 129
 STI clinic 454 370 824 596 387 983 9 3 12 8 2 10 2.5% 2.0% 1.5% 0.8% 0.3% 1.0% 45 93 69 75 194 134
 TB clinic 3777 4187 7964 2928 3344 6272 255 204 459 161 121 282 7.1% 4.9% 5.8% 5.7% 3.7% 4.5% 15 21 18 18 28 23
 VCT 68,812 61,701 130,513 41,035 52,363 93,398 1395 1310 2705 889 929 1818 2.1% 2.4% 2.1% 2.5% 1.9% 1.9% 49 47 48 46 56 51
 VMMC 89,509 87,258 176,767 13,965 57,539 71,504 253 172 425 60 115 175 0.3% 0.2% 0.2% 0.3% 0.1% 0.2% 354 507 431 233 500 367
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*

Number of HIV-positive tests/Number of HIV tests.

†

Number needed to test to find 1 positive. Number of HIV tests/Number of HIV-positive tests.

Identifying ALHIV

During COVID-19, 20,766 adolescents were diagnosed with HIV, a decrease of 28.8% compared with the number of adolescents identified pre-COVID-19 (29,172; Table 1). The largest quarterly decline occurred between FY20Q2 and FY20Q3, resulting in a 29.9% drop in the number of adolescents identified with HIV, with younger adolescents driving the decrease (−36.9%) compared with older adolescents (−28.3%). Overall case identification slightly rebounded in FY20Q4, with a 9.1% increase in positive tests over FY20Q3 (10,878 vs 9888). Pre-COVID-19, most positive tests were identified among female adolescents (77.6%), with little change (78.9%) during COVID-19. Males experienced a larger decrease in case finding compared with females between the periods (−32.8% vs −27.7%). Most positive tests were identified among older adolescents both pre-COVID-19 (80.9%) and during COVID-19 (82.8%).

Most countries experienced declines in case identification for adolescents during COVID-19, with the largest decreases occurring in Haiti (−53.1%; Table 1), Zimbabwe (−44.4%), and South Sudan (−42.6%). Two countries experienced increases in case identification during COVID-19: Eswatini (8.9%) and Uganda (1.2%).

Pre-COVID-19, most positive tests in adolescents were identified in the following modalities: other provider-initiated testing and counseling (PITC) (41.0%; Table 1), followed by ANC (12.0%) and facility-based index testing (11.9%). During COVID-19, the modality trend remained the same although there was a slight decrease in the contribution to positive tests from other PITC (38.6%) and slight percent increases in the contributions from PMTCT ANC (14.0%) and facility-based index testing (13.9%).

Overall, the percent of adolescents testing positive across all modalities witnessed only a slight decline of 0.2% from pre-COVID-19 (1.9%) to during COVID-19 (1.7%), with a corresponding small increase in the NNT (54 vs 59; Fig. 1). For younger adolescents, the percent testing positive increased from 1.6% pre-COVID-19%–2.0% during COVID-19 and the NNT decreased (61 vs 50), whereas the positivity decreased slightly for older adolescents during the same time period (1.9% vs 1.6%) and the NNT increased (52 vs 61). For female adolescents, the percent testing positive decreased slightly during COVID-19 (1.8%) compared with pre-COVID-19 (2.2%), with a subsequent increase in NNT (47 vs 55) over the same period (Fig. 1). Male adolescents also experienced a slight increase in percent testing positive during COVID-19 (1.3% vs 1.4%), whereas NNT decreased (79 vs 73).

Proxy Linkage to ART

The overall rate of proxy linkage to ART increased between the pre-COVID-19 and COVID-19 periods (86.9% vs 90.4%; Fig. 2). Quarterly trends demonstrate the largest increase in proxy linkage between FY20Q1 (81.2%) and FY20Q2 (92.9%). Pre-COVID-19, the proxy linkage rate for younger adolescents was 81.3% and 88.2% for older adolescents. During COVID-19, both younger and older adolescents had higher linkage to ART at 90.4% (Fig. 2). Between the pre-COVID-19 and COVID-19 periods, proxy linkage to ART increased for females (89.9% vs 93.3%) and males (76.1% vs 79.7%) (Fig. 2).

FIGURE 2.

FIGURE 2.

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Second 95, number of HIV-positive adolescent tests, new treatment initiations and proxy linkage by sex and age in USAID/PEPFAR programs, FY20. (A) Positive tests, new treatment initiations and proxy linkage by sex. (B) Positive tests, new treatment initiations and proxy linkage by age. (C) Total on ART by sex. (D) Total on ART by age.

Most countries experienced an increase in proxy linkage to ART during COVID-19 (Table 2). The countries with the largest increase include DRC (50% vs 64%), Mozambique (76% vs 87%), Nigeria (88% vs 101%), and South Sudan (58% vs 108%). Countries experiencing declines include Eswatini (95% vs 90%), Tanzania (110% vs 95%) (The calculated metrics are proxies using aggregated totals and noncohort data. As a result, since the denominator and numerators are not based on the same cohort, it is possible for calculated metrics to be more than 100%), and Uganda (79% vs 75%).

TABLE 2.

HIV Treatment in Adolescents in USAID/PEPFAR Programs, FY20

Number of HIV-Positive Tests New Treatment Initiations Proxy Linkage to ART (%)* Total on ART
Pre-COVID During COVID Pre-COVID During COVID Pre-COVID During COVID Pre-COVID During COVID
FY20Q1 FY20Q2 Total FY20Q3 FY20Q4 Total FY20Q1 FY20Q2 Total FY20Q3 FY20Q4 Total FY20Q1 FY20Q2 Average FY20Q3 FY20Q4 Average FY20Q1 FY20Q2 Total FY20Q3 FY20Q4 Total
Total 10–19 15,057 14,115 29,171 9888 10,878 20,766 12,227 13,109 25,336 9067 9706 18,773 78% 92% 87% 93% 88% 90% 262,730 269,573 532,303 265,191 268,478 533,669
Age
 10–14 yrs 2906 2652 5558 1674 1902 3576 2103 2415 4518 1574 1657 3231 72% 91% 81% 94% 87% 90% 117,710 119,327 237,037 118,425 118,661 237,086
 15–19 yrs 12,151 11,463 23,614 8214 8976 17,190 10,124 10,694 20,818 7493 8049 15,542 83% 93% 88% 91% 90% 90% 145,020 150,246 295,266 146,766 149,817 296,583
Sex
 Female 11,660 10,986 22,646 7836 8546 16,382 9848 10,521 20,369 7380 7900 15,280 80% 97% 90% 93% 90% 93% 153,436 159,461 312,897 153,790 155,502 309,292
 Male 3397 3129 6526 2052 2332 4384 2379 2588 4967 1687 1806 3493 70% 83% 76% 86% 80% 80% 109,294 110,112 219,406 111,401 112,976 224,377
Country
 Burundi 200 183 383 165 147 312 146 124 270 124 121 245 73% 68% 70% 75% 82% 79% 3771 3722 7493 3670 3670 7340
 DR 336 371 707 286 361 647 325 340 665 273 342 615 97% 92% 94% 95% 95% 95% 3232 3533 6765 3,803 4082 7885
 DRC 29 35 64 12 43 55 12 20 32 8 27 35 41% 57% 50% 67% 63% 64% 258 274 532 168 514 682
 Eswatini 50 51 101 53 57 110 43 53 96 50 49 99 86% 104% 95% 94% 86% 90% 562 629 1191 623 639 1262
 Haiti 197 174 371 101 73 174 199 175 374 97 88 185 101% 101% 101% 96% 121% 106% 6107 6032 12,139 5,942 6433 12,375
 Kenya 178 217 395 81 244 325 137 177 314 73 179 252 77% 82% 79% 90% 73% 78% 4747 4931 9678 5,008 5257 10,265
 Lesotho 632 659 1291 538 612 1150 543 594 1137 494 540 1034 86% 90% 88% 92% 88% 90% 25,516 25,978 51,494 25,920 25,993 51,913
 Malawi 726 490 1216 274 526 800 825 840 1665 536 535 1071 114% 171% 137% 196% 102% 134% 18,870 19,648 38,518 18,907 19,080 37,987
 Mozambique 1106 1267 2373 887 885 1772 866 933 1799 780 765 1545 78% 74% 76% 88% 86% 87% 9716 9530 19,246 9,920 10,700 20,620
 Nigeria 2043 1510 3553 984 1447 2431 1540 1582 3122 1044 1400 2444 75% 105% 88% 106% 97% 101% 11,228 11,814 23,042 12,216 13,270 25,486
 South Africa 5188 5020 10,208 2977 3056 6033 3910 4502 8412 2567 2701 5268 75% 90% 82% 86% 88% 87% 82,917 87,667 170,584 80,131 79,582 159,713
 South Sudan 51 57 108 31 31 62 29 34 63 32 35 67 57% 60% 58% 103% 113% 108% 192 194 386 203 236 439
 Tanzania 844 828 1672 918 713 1631 870 977 1847 859 687 1546 103% 118% 110% 94% 96% 95% 20,367 21,317 41,684 21,281 21,129 42,410
 Uganda 1011 1111 2122 1067 1081 2148 775 908 1683 792 822 1614 77% 82% 79% 74% 76% 75% 21,591 21,599 43,190 21,415 21,901 43,316
 Zambia 1409 1076 2485 1001 934 1935 1198 970 2168 884 816 1700 85% 90% 87% 88% 87% 88% 22,919 21,309 44,228 20,560 20,358 40,918
 Zimbabwe 1057 1066 2123 513 668 1181 809 880 1689 454 599 1053 77% 83% 80% 88% 90% 89% 30,737 31,396 62,133 35,424 35,634 71,058
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*

New treatment initiations/Number of HIV-positive tests.

New Treatment Initiations

There was an overall decrease of 25.9% in treatment initiations among adolescents during COVID-19 (25,336 vs 18,773; Fig. 2). The largest quarterly decrease in new initiations occurred between FY20Q2 and FY20Q3 (−30.8%). As with testing, there was a decrease (−28.5%) in new treatment initiation among younger adolescents pre-COVID-19 (4518) compared with during COVID-19 (3231; Fig. 2). Older adolescents experienced a 25.3% decline in new treatment initiations between pre-COVID-19 (20,818) and during COVID-19 (15,542) periods.

Consistent with the pattern of testing observed pre-COVID-19, most treatment initiations were in female adolescents (80.4%; Fig. 2), slightly increasing to comprise 81.4% during COVID-19. During COVID-19, treatment initiations among female adolescents decreased by 25%, whereas males experienced a decline of 30%. The volume of declines among females was larger (−3141).

Pre-COVID-19, the countries with the largest volume of treatment initiations included South Africa (8412; Table 2), Nigeria (3,122), and Zambia (2,168). During COVID-19, the same 3 countries reported the largest volume of treatment initiations, however, with declines: South Africa (−37.3%), Nigeria (−21.7%), and Zambia (−21.6%). Countries that experienced the greatest declines in new treatment initiations during COVID-19 include Haiti (−50.5%) and Zimbabwe (−37.7%). Three countries experienced increases in new treatment initiations between the pre-COVID-19 and during COVID-19 periods: DRC (9.4%), Eswatini (3.1%), and South Sudan (6.3%).

Total on ART

Overall, there were similar numbers of adolescents on treatment pre-COVID-19 and during COVID-19 (532,303 and 533,669; Fig. 2). Most countries experienced growth or maintenance in their adolescent treatment cohorts during COVID-19, with a few exceptions, including Burundi (−2.0%; Table 2), Malawi (−1.4%), South Africa (−6.4%), and Zambia (−7.5%). The largest increase in treatment cohort growth between the pre-COVID-19 and during COVID-19 periods occurred in DRC (28.2%) and DR (16.6%).

There was a slight increase in the treatment cohort for younger and older adolescents, increasing by 37 clients and 1317 clients, respectively (Fig. 2). Females on treatment remained relatively consistent during COVID-19, decreasing by −1.2%, whereas the male treatment cohort increased by 2.3%.

Viral Load Coverage

Proxy VLC results cannot be aggregated across quarters, and as such, rates at each quarter were analyzed. Overall, during FY20, VLC rates for adolescents dropped, from 81.6% at FY20Q1 to 76.5% at FY20Q4 (Fig. 3). The largest quarterly decline occurred between FY20Q1 and FY20Q2, which saw a 4.9 percentage point decrease to 76.7%. VLC rates followed a similar declining trend across the fiscal year for older (76.8% at FY20Q1 vs 71.7% at FY20Q4; Fig. 3) and younger (86.5% vs 81.3%) adolescents as well as for males (84.8% vs 81.2%) and females (80.0% vs 73.9%).

FIGURE 3.

FIGURE 3.

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Third 95, adolescent proxy viral load suppression and coverage by sex and age in USAID/PEPFAR programs, FY20. (A) Viral load suppression and proxy viral load coverage by sex. (B) Viral load suppression and proxy viral load coverage by age.

Between FY20Q1 and FY20Q4, the largest percentage point increases in proxy VLC were observed in the following countries: DR (63.4% vs 85.0%; Table 3), DRC (59.0% vs 83.7%), and Lesotho (84.1% vs 93.5%). The largest decreases across the same time period were observed in the following countries: Burundi (101.8% vs 79.0%) (The calculated metrics are proxies using aggregated totals and noncohort data. As a result, since the denominator and numerators are not based on the same cohort, it is possible for calculated metrics to be more than 100%), Malawi (134.8% vs 68.7%), and South Sudan (80.3% vs 46.4%). The lowest reported VLC rate during the fiscal year was reported in South Sudan during COVID-19 in FY20Q4 (46%).

TABLE 3.

Viral Load Coverage and Suppression in Adolescents in USAID/PEPFAR Programs, FY20

Number of VL Tests With a Result Number of VL Tests With a Result <1000 Copies/mL Proxy VL Coverage (%)* VL Suppression (%)†
Pre‐COVID During COVID Pre‐COVID During COVID Pre‐COVID During COVID Pre‐COVID During COVID
FY20Q1 FY20Q2 Total FY20Q3 FY20Q4 Total FY20Q1 FY20Q2 Total FY20Q3 FY20Q4 Total FY20Q1 FY20Q2 Average FY20Q3 FY20Q4 Average FY20Q1 FY20Q2 Average FY20Q3 FY20Q4 Average
Total 10‐19 202,608 202,096 404,704 198,986 204,749 403,735 154,146 156,806 310,952 156,118 164,805 320,923 82% 77% 79% 76% 77% 76% 76% 78% 77% 78% 80% 79%
Age
 10–14 yrs 98,824 98,040 196,864 96,012 96,987 192,999 73,852 74,377 148,229 74,312 77,295 151,607 86% 82% 84% 82% 81% 81% 75% 76% 75% 77% 80% 79%
 15–19 yrs 103,784 104,056 207,840 102,974 107,762 210,736 80,294 82,429 162,723 81,806 87,510 169,316 77% 72% 74% 71% 72% 71% 77% 79% 78% 79% 81% 80%
Sex
 Female 114,181 115,262 229,443 111,620 115,307 226,927 88,420 90,933 179,353 88,796 94,023 182,819 80% 76% 78% 74% 74% 74% 77% 79% 78% 79% 81% 81%
 Male 88,427 86,834 175,261 87,366 89,442 176,808 65,726 65,873 131,599 67,322 70,782 138,104 85% 79% 82% 80% 81% 81% 74% 76% 75% 77% 79% 78%
Country
 Burundi 2633 3184 5817 3241 2942 6183 1964 2513 4477 2506 2506 5012 102% 121% 111% 86% 79% 82% 75% 79% 77% 77% 85% 81%
 DR 222 192 414 195 233 428 149 139 288 145 168 313 63% 59% 61% 76% 85% 80% 67% 72% 70% 74% 72% 73%
 DRC 1610 2054 3664 2145 2957 5102 1231 1661 2892 1788 2635 4423 59% 69% 64% 66% 84% 75% 76% 81% 79% 83% 89% 87%
 Eswatini 3952 3886 7838 3957 4420 8377 3735 3712 7447 3797 3980 7777 86% 85% 85% 83% 90% 86% 95% 96% 95% 96% 90% 93%
 Haiti 393 434 827 446 484 930 253 319 572 332 371 703 70% 77% 73% 79% 77% 78% 64% 74% 69% 74% 77% 76%
 Kenya 25,238 25,317 50,555 24,913 24,579 49,492 19,367 19,837 39,204 19,804 20,600 40,404 90% 87% 88% 98% 95% 96% 77% 78% 78% 79% 84% 82%
 Lesotho 5172 5459 10,631 5411 5640 11,051 4556 4914 9470 4864 5295 10,159 84% 88% 86% 89% 94% 91% 88% 90% 89% 90% 94% 92%
 Malawi 16,557 15,138 31,695 13,971 13,505 27,476 10,961 10,589 21,550 10,259 10,301 20,560 135% 78% 107% 74% 69% 71% 66% 70% 68% 73% 76% 75%
 Mozambique 5553 4994 10,547 5184 5455 10,639 3247 2972 6219 3260 3656 6916 58% 51% 54% 53% 57% 55% 58% 60% 59% 63% 67% 65%
 Nigeria 7341 7249 14,590 7430 9399 16,829 5186 5389 10,575 5702 7769 13,471 74% 64% 69% 66% 80% 73% 71% 74% 72% 77% 83% 80%
 South Africa 63,806 64,418 128,224 62,051 61,530 123,581 50,826 51,391 102,217 49,209 49,100 98,309 77% 76% 76% 75% 70% 73% 80% 80% 80% 79% 80% 80%
 South Sudan 94 128 222 94 90 184 48 80 128 53 50 103 80% 79% 79% 49% 46% 48% 51% 63% 58% 56% 56% 56%
 Tanzania 17,747 17,226 34,973 17,138 17,300 34,438 13,622 13,845 27,467 14,315 14,785 29,100 90% 84% 87% 84% 81% 83% 77% 80% 79% 84% 85% 84%
 Uganda 20,330 20,726 41,056 20,507 20,779 41,286 14,834 15,199 30,033 15,067 15,865 30,932 97% 97% 97% 95% 96% 96% 73% 73% 73% 73% 76% 75%
 Zambia 14,267 14,153 28,420 14,555 16,217 30,772 10,839 11,175 22,014 11,574 13,359 24,933 73% 69% 71% 64% 76% 70% 76% 79% 77% 80% 82% 81%
 Zimbabwe 17,693 17,538 35,231 17,748 19,219 36,967 13,328 13,071 26,399 13,443 14,365 27,808 60% 58% 59% 58% 61% 59% 75% 75% 75% 76% 75% 75%
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*

Number of VL tests with a result/Number on ART 6 months prior.

†

Number of VL tests with a result <1000 copies/mL / Number of VL tests with a result.

Viral Load Suppression

Similar to VLC, VLS quarterly rates were analyzed. Overall, during FY20, the rates of VLS for adolescents increased, from 76.1% at FY20Q1 to 80.5% at FY20Q4 (Fig. 3). The largest quarterly change was a two-percentage point increase between FY20Q3 (78.5%) and FY20Q4 (80.5%). VLS rates followed a similar trend across the fiscal year for older (77.4% at FY20Q1 vs 81.2% at FY20Q4; Fig. 3) and younger (74.7% vs 79.7%) adolescents as well as for males (74.3% vs 79.1%) and females (77.4% vs 81.5%). VLS remained higher in females compared with males; and among 15–19-year-olds as compared with 10–14-year-olds at every quarter—the inverse of the VLC trends for age and sex.

Between FY20Q1 and FY20Q4, most countries examined experienced increases in adolescent VLS rates (Table 3). The largest percentage point increases in VLS were observed in the following countries: DR (67.1% vs 72.1%), DRC (76.5% vs 89.1%), Malawi (66.2% vs 76.3%), and Nigeria (70.6% vs 82.7%). Only 2 countries experienced decreases in adolescent VLS rates between FY20Q1 and FY20Q4: Eswatini (94.5% vs 90.0%) and Zimbabwe (75.3% vs 74.7%).

DISCUSSION

Overall, there were substantial decreases in testing, case finding, and consequently treatment initiations in ALHIV in USAID/PEPFAR programs that coincide with the COVID-19 pandemic and resultant mitigation measures. The largest quarterly declines for all 3 indicators were reported between FY20Q2 (January–March 2020) and FY20Q3 (April–June 2020), which correlates with when many countries experienced their first wave of COVID-19. Comparatively, in previous fiscal years between Q1–Q2 vs Q3–Q4, there were increases in testing (FY17, 33.0%; FY18, 16.3%) and a small decline (FY19%, −4.9%), suggesting that the large testing decreases observed in FY20, and downstream cascade impacts, are attributable to the pandemic (data not shown). Furthermore, data from a PEPFAR-wide analysis of the impact of COVID-19 on pediatric testing (0–14-year-old) in 22 countries show similar large decreases.19 These large declines are likely a result of lockdowns and travel restrictions, disruptions and strains on health facilities and community-based health programming, and other stringent country COVID-19 mitigation policies.

Interestingly, there was a 35.9% rebound in adolescent testing between FY20Q3 and FY20Q4, which was followed by increases in case-finding and treatment initiations. This jump could be attributable to loosened COVID-19 mitigation policies or to adaptations in national health care systems and USAID/PEPFAR-supported activities designed to continue health service delivery amid the pandemic.20 Although overall testing rebounded by 35.9% in FY20Q4, there was only a 10.0% increase in the number of ALHIV identified and a 7.0% increase in the number of new treatment initiations. This may indicate that initiatives focused on the identification and treatment of adolescents at highest risk of living with HIV, such as community-based testing and outreach, were disproportionately impacted during the pandemic.

Female adolescents and older adolescents represented most tests conducted during both time periods, although there were decreases in the total volume during the pandemic. This may be due to the fact that there are more females living with HIV compared with males and more older adolescents living with HIV compared with younger adolescents.1 This finding is also consistent with recent data from Nigeria and Gambia that shows that among youth aged 15–24 years, females and older youth (20–24-year-old) are more likely to ever have been tested for HIV.21,22 Under normal circumstances, younger adolescents (10–14-year-old) may have less agency and ability to access HIV testing services (HTS) without parental consent, and this was exacerbated during the COVID-19 pandemic. Lowering country age of consent laws for testing will help increase HTS eligibility and access for younger adolescents. In addition, expanding access to HIV self-testing for adolescents can increase HTS accessibility away from health facilities, which may be more appealing for those seeking privacy and reduce potential exposure to COVID-19.

The overall decline in the volume of new treatment initiations among both sexes and age bands pre-COVID-19 vs during COVID-19 (−25.9%) mirrors the overall declines in testing and case finding. Although fewer adolescents were HIV tested and identified during the pandemic, USAID/PEPFAR programs improved in linking those identified to treatment. This may suggest that new or adapted adolescent-responsive strategies were used, such as digital health interventions such as virtual WhatsApp and Facebook groups, to ensure that newly identified adolescents were linked to care. Or perhaps, during COVID-19, despite barriers, adolescents who were symptomatic were more likely to seek care at a health facility and to start ART once diagnosed.23

Although several countries saw a VLC increase between time periods observed, the increases were small, while observed decreases were more dramatic. This may be explained by the fact that many countries repurposed HIV testing platforms for COVID-19 diagnostics and also experienced supply chain disruptions, leading to limited VLC commodities.24 Furthermore, when comparing data by age and sex, the trends observed during both time periods warrant further investigation to better understand why VLC rates are higher for younger (10–14-year-old) and male adolescents. During FY20, there was a 4.4 percentage point increase in VLS rates for adolescents. Although unexpected, this rise may be partially attributable to school closures, mitigating the possible disruptive effects of school attendance on adherence to ART as well as VL sample collection. Furthermore, it is possible that adolescents were more adherent to their regimens due to perceived COVID-19 risks or had recently transitioned to optimized ART regimens and thus achieved VLS. In fact, a cohort study from Malawi found that during the pandemic, VLS rates increased slightly for patients on protease inhibitor–based regimens (eg, lopinavir/ritonavir) and integrase strand transfer inhibitor–based regimens (eg, dolutegravir).25 Observation and comparison of VL data over a longer time period is needed to determine if these differences are consistent and significant and what other factors may contribute.

During COVID-19, many programs implemented approaches to bring treatment closer to communities and to improve access to differentiated service delivery models, such as multimonth dispensing or decentralized/community-based drug distribution.26 Many countries rapidly modified policies to allow for multimonth dispensing/differentiated service delivery among younger age groups and pregnant girls and women to allow flexibility to obtain ART in a location and timeframe that is more convenient for clients.15 The small changes observed in VLC and VLS between the pre-COVID-19 and during COVID-19 time period may suggest that these approaches contributed to treatment continuation among adolescents during the initial stages of the COVID-19 pandemic; however, further investigation is warranted.27 Preliminary USAID/PEPFAR programmatic data suggest that MMD may be correlated with higher rates of VLS and improved adherence across populations28 and data from cohort studies in Malawi and Italy also show increased rates of VLS during COVID-19 due to introducing patient-centered care models.25,29

Given that the total number of adolescents on ART grew only modestly during FY20, strategies to keep adolescents engaged in treatment should be emphasized. These may include peer support groups, such as Operation Triple Zero and Zvandiri, digital health interventions such as WhatsApp and Facebook support groups, enhanced monitoring and counseling, back to treatment strategies, and comprehensive community-based support and services provided through orphans and vulnerable children programming, for those eligible.30–32 In the future, it would be interesting to further analyze the differences in HIV treatment services access and uptake for younger adolescents vs older adolescents during subsequent waves of the COVID-19 pandemic, with a particular interest in identifying and understanding potential gaps in linkage to ART, VLC, and VLS.

LIMITATIONS

This analysis has several limitations. Because the data were aggregated across countries, the authors were unable to review data completeness or quality in depth by country. This could potentially mask country-specific changes, contexts, and/or data quality issues. In addition, USAID adolescent HIV programming varies across countries and is not implemented at a national scale, and, therefore, the data presented are not intended to be nationally representative. Last, we did not control for the differential burden of the COVID-19 pandemic by country.

It should be noted that calculations, such as linkage and VLC, are proxy indicators because USAID/PEPFAR programs routinely report aggregate-level data and not individual-level beneficiary data. Indicators that provide more data on continuity of treatment, treatment interruption, multi-month dispensation trends, and mortality were excluded given the limited timeframe assessed. Further analysis, including these additional indicators, is needed.

In this paper, data were analyzed within a limited timeframe—4 quarters of 1 fiscal year. Further analysis of data from additional time points is needed to better understand trends and sustained impact of additional waves of COVID-19 and mitigation measures. This future analysis should also take into account the variability of these waves and measures in addition to nuanced changes and fluctuations as a result of programmatic shifts.

CONCLUSIONS

This review describes the magnitude of the COVID-19 pandemic's impact on HIV services in USAID/PEPFAR adolescent programming. Our results, which show decreased rates of HIV testing and the identification of fewer ALHIV during COVID-19 as compared with periods before the pandemic, are consistent with findings from other studies assessing HIV care and treatment programs during COVID-19. These findings coincided with a decrease in treatment initiations and in VLC and an increase in VLS. Against the backdrop of the concurrent and well documented increases in HIV risk factors associated with the pandemic (such as increased orphanhood, increased family and gender-based violence, and school closures), the lower rates of adolescent testing, case finding, and linkage to treatment are cause for concern. As restrictions designed to decrease the spread of COVID-19 ease globally, investments in increased HIV testing, case finding, treatment linkage, psychosocial support for adolescents, and training and mentorship to health care providers will be critical. In addition, research to identify potential approaches to optimize HIV testing, case finding, and treatment linkage strategies during future pandemics is needed.

Authors’ Contributions

The initial concept and outline for this commentary was conceived and developed by TCO, JW, KO, and KP. All authors (TCO, BD, JW, KC, KO, KP, and USAID/PEPFAR Adolescent Group) contributed to the article content and revisions. All authors (TCO, BD, JW, KC, KO, KP, and USAID/PEPFAR Adolescent Group) reviewed and approved the final article before publication.

ACKNOWLEDGMENTS

The authors thank Meena Srivastava, George Siberry, and Matthew Barnhart for reviewing the draft manuscript and providing helpful feedback. The authors also thank Nashiva McDavid for strategic information support.

Footnotes

Funding: This article was made possible by the support of the American people through the United States Agency for International Development (USAID) under the US President's Emergency Plan for AIDS Relief (PEPFAR).

Conflicts of interest: The authors declare no conflicts of interest.

Disclaimer: The contents in this article are those of the authors and do not necessarily reflect the view of the US President's Emergency Plan for AIDS Relief, the US Agency for International Development, or the US Government.

PEPFAR Adolescent Group: Diana Kemunto, MBchB, MPH, Dunstan Achwoka, MBChB, MSC, PhD, Onesimo Maguwu, MPH, MBA, Solomon Mukungunugwa, MD, Nyakallang Moyo, MScIH, Gerald Zomba, MPH, Olbeg Desinor, MD, Esther Karungi Karamagi Nkolo, PhD, Erin Berghammer, MSc, MPH, Godfrey Lingenda, MD, MPH, Nicholas Baabe, MSc, Justine Mirembe, Buyile Buthelezi, PDM, MPhil, MBA, Carolyn Mbelwa, MD, MPH, Jacqueline Kalimunda, BSc, MPH, Igboelina Onyeka Donald, MD, MPH, Armando Cotrina, MD, MPH, Mercia Matsinhe, MD, Argentina Wate, MD.

Contributor Information

Jessica Williams, Email: jesswilliams@usaid.gov.

Kate F. Plourde, Email: kplourde@fhi360.org.

Kelsey Oliver, Email: kelseyoliver@gwmail.gwu.edu.

Barbara Ddamulira, Email: bddamulira@usaid.gov.

Kristina Caparrelli, Email: kcaparrelli@usaid.gov.

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