| Literature DB >> 35381024 |
Michael Kerzner1, Anindya K De2, Randy Yee2, Ryan Keating2, Gaston Djomand2, Sharon Stash3, Sangeeta Rana4, Allison Kimmel4, Robyn Eakle4, Sara Klucking5, Pragna Patel2.
Abstract
BACKGROUND: Mitigation measures for the first wave of the COVID-19 pandemic and burden on health systems created challenges for pre-exposure prophylaxis (PrEP) service delivery. We examined PrEP uptake in PEPFAR programs before and after the start of the COVID-19 pandemic.Entities:
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Year: 2022 PMID: 35381024 PMCID: PMC8982838 DOI: 10.1371/journal.pone.0266280
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
New and current preexposure prophylaxis (PrEP) users in PEPFAR-supported countries, by pre-COVID-19 and COVID-19 time periods.
| PEPFAR Countries | Time period | Percent change | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Pre-COVID | COVID-19 | ||||||||
| PrEP uptake | PrEP uptake achievement (%) | PrEP uptake | PrEP uptake achievement | PrEP uptake | PrEP uptake achievement§ | ||||
| All countries | 233,250 | 100 | 113,129 | 599,935 | 90 | 221,331 | 157.2 | -12.4 | 95.6 |
| Botswana | 1,732 | 170 | 1,174 | 3,829 | 100 | 174 | 121.1 | -40.0 | -85.2 |
| Cameroon | 433 | 30 | 260 | 2,023 | 50 | 0 | 367.2 | 80.5 | -100.0 |
| Democratic Republic of the Congo | 646 | 70 | 491 | 2,217 | 30 | 1,017 | 243.2 | -49.3 | 107.1 |
| Dominican Republic | 720 | 130 | 993 | 658 | 50 | 725 | -8.6 | -58.8 | -27.0 |
| Eswatini | 6,213 | 160 | 2,681 | 11,344 | 140 | 982 | 82.6 | -12.9 | -63.4 |
| Ethiopia | 801 | 60 | 704 | 8,577 | 100 | 4,801 | 970.8 | 67.3 | 582.0 |
| Kenya | 39,169 | 110 | 31,141 | 59,632 | 90 | 54,219 | 52.2 | -23.8 | 74.1 |
| Lesotho | 12,884 | 80 | 8,109 | 12,219 | 60 | 13,888 | -5.2 | -25.6 | 71.3 |
| Malawi | 721 | 20 | 284 | 440 | 0 | 180 | -39.0 | -79.4 | -36.6 |
| Mozambique | 6,596 | 90 | 1,501 | 21,572 | 70 | 2,341 | 227.0 | -19.7 | 56.0 |
| Namibia | 11,144 | 110 | 1,496 | 15,226 | 80 | 11,649 | 36.6 | -25.5 | 678.7 |
| Nigeria | 3,435 | 50 | 411 | 84,763 | 140 | 29,128 | 2367.6 | 210.5 | 6,987.1 |
| Rwanda | 1,621 | 100 | 353 | 7,548 | 170 | 8,286 | 365.6 | 65.5 | 2,247.3 |
| South Africa | 48,588 | 70 | 13,149 | 146,540 | 80 | 16,385 | 201.6 | 19.7 | 24.6 |
| Tanzania | 6,045 | 30 | 5,460 | 25,694 | 20 | 9,458 | 325.0 | -27.9 | 73.2 |
| Thailand | 5,754 | 150 | 7,294 | 5,106 | 90 | 9,631 | -11.3 | -42.1 | 32.0 |
| Uganda | 28,532 | 120 | 11,208 | 69,228 | 110 | 4,700 | 142.6 | -9.6 | -58.1 |
| Ukraine | 1,626 | 110 | 439 | 1,392 | 70 | 856 | -14.4 | -34.0 | 95.0 |
| Vietnam | 7,684 | 150 | 4,984 | 13,276 | 90 | 14,595 | 72.8 | -38.5 | 192.8 |
| Zambia | 35,580 | 250 | 10,703 | 86,810 | 160 | 20,897 | 144.0 | -33.9 | 95.2 |
| Zimbabwe | 13,326 | 230 | 10,294 | 21,841 | 140 | 17,419 | 63.9 | -39.1 | 69.2 |
* Indicates possible reporting error.
†All changes are significant at 0.05 level except that of Dominican Republic.
§All changes are significant at 0.05 level.
Fig 1Uptake of pre-exposure prophylaxis in all populations (right) and incidence of COVID-19 (left), by country.
a. Percent change in uptake of pre-exposure prophylaxis in all populations from the pre-COVID to COVID periods, by country (right). B. Cumulative COVID-19 cases by country, March 2020 –July 2021 (left). Data source: https://covid19.who.int/ [16]; Maps were created using Microsoft Excel version 2102.
New and current preexposure prophylaxis (PrEP) users in PEPFAR-supported countries, by pre-COVID-19 and COVID-19 time periods, among adolescent girls and young women aged 15–24 years.
| PEPFAR Countries | Time period | Percent change | ||||
|---|---|---|---|---|---|---|
| Pre-COVID | COVID-19 | |||||
| PrEP uptake | PrEP uptake achievement (%) | PrEP uptake (n) | PrEP uptake achievement | PrEP uptake | PrEP uptake achievement | |
| All countries | 80,452 | 80 | 208,607 | 70 | 159.3 | -17.2 |
| Botswana | 972 | 140 | 1,976 | 80 | 103.3 | -45.4 |
| Cameroon | 46 | 20 | 255 | 50 | 454.3 | 116.4 |
| Democratic Republic of the Congo | 129 | 70 | 337 | 30 | 161.2 | -52.3 |
| Dominican Republic | 88 | 120 | 97 | 70 | 10.2 | -39.4 |
| Eswatini | 1,238 | 160 | 3,349 | 100 | 170.5 | -36.2 |
| Ethiopia | 423 | 130 | 4,367 | 220 | 932.4 | 73.8 |
| Kenya | 11,955 | 120 | 17,357 | 80 | 45.2 | -34.3 |
| Lesotho | 6,068 | 190 | 5,424 | 80 | -10.6 | -56.3 |
| Malawi | 432 | 30 | 168 | 0 | -61.1 | -88.7 |
| Mozambique | 3,001 | 150 | 7,495 | 60 | 149.8 | -57.8 |
| Namibia | 5,169 | 100 | 8,198 | 100 | 58.6 | 0.7 |
| Nigeria | 298 | 20 | 9,877 | 110 | 3,214.4 | 402.0 |
| Rwanda | 289 | 70 | 4,081 | 170 | 1,312.1 | 134.2 |
| South Africa | 28,568 | 50 | 83,266 | 60 | 191.5 | 7.0 |
| Tanzania | 2,038 | 30 | 10,383 | 20 | 409.5 | -32.1 |
| Uganda | 8,519 | 130 | 21,199 | 230 | 148.8 | 81.8 |
| Vietnam | 203 | 60 | 357 | 40 | 75.9 | -23.7 |
| Zambia | 6,381 | 250 | 20,538 | 120 | 221.9 | -53.8 |
| Zimbabwe | 4,635 | 230 | 9,883 | 210 | 113.2 | -7.9 |
*All changes are significant (p<0.05) except that of Dominican Republic.
†All changes are significant except for Namibia.
New and current preexposure prophylaxis (PrEP) users in PEPFAR-supported countries, by pre-COVID-19 and COVID-19 time periods, among key populations*.
| PEPFAR Countries | Time period | Percent change | ||||
|---|---|---|---|---|---|---|
| Pre-COVID (April 1, 2019 –March 31, 2020) | COVID-19 (April 1, 2020 –March 31, 2021) | |||||
| PrEP uptake (n) | PrEP uptake achievement (%) | PrEP uptake (n) | PrEP uptake achievement (%) | PrEP uptake† | ||
| All countries | 77,430 | 100 | 209,114 | 120 | 170.1 | 28.6 |
| Botswana | 901 | 220 | 1,765 | 160 | 95.9 | -27.4 |
| Dominican Republic | 718 | 120 | 602 | 90 | -16.2 | -31.1 |
| Ethiopia | 636 | 60 | 7,011 | 160 | 1,002.4 | 151.4 |
| Kenya | 5,818 | 100 | 15,636 | 80 | 168.8 | -20.7 |
| Lesotho | 1,024 | 40 | 1,662 | 150 | 62.3 | 262.2 |
| Malawi | 366 | 20 | 1,199 | 30 | 227.6 | 22.5 |
| Namibia | 1,239 | 50 | 3,859 | 160 | 211.5 | 186.9 |
| Nigeria | 2,237 | 50 | 49,358 | 250 | 2,106.4 | 399.3 |
| Rwanda | 1,513 | 330 | 4,358 | 170 | 188.0 | -49.3 |
| South Africa | 15,310 | 60 | 21,618 | 70 | 41.2 | 25.0 |
| Tanzania | 4,547 | 100 | 16,035 | 50 | 252.7 | -54.3 |
| Thailand | 5,744 | 150 | 5,017 | 90 | -12.7 | -43.0 |
| Uganda | 15,847 | 110 | 38,891 | 270 | 145.4 | 138.3 |
| Ukraine | 1,108 | 70 | 869 | 60 | -21.6 | -14.3 |
| Vietnam | 6,184 | 130 | 11,780 | 90 | 90.5 | -30.3 |
| Zambia | 5,076 | 130 | 16,529 | 220 | 225.6 | 71.9 |
| Zimbabwe | 9,162 | 300 | 12,925 | 200 | 41.1 | -34.7 |
* Key populations consist of sex workers, men who have sex with men, people who inject drugs, prisoners, and transgender persons.
†All changes are significant (p<0.05).
Fig 2Pre-exposure prophylaxis (PrEP) uptake, by country and by reporting time period, with select COVID-19 mitigation strategies.
Summary of pre-exposure prophylaxis program adaptations by country and by population.
| Country & Program Area | PrEP Program Adaptations | Date of Reported Activity | ||
|---|---|---|---|---|
| Kenya | Adaptations consistent across two-three countries in bold | FY20 Q2 | FY20 | FY21 |
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| Prioritization of cases | ||||
| Public-private sector | ||||
| Rearranged workflow and schedules implemented for COVID-19 | ||||
| Strategic information generation/coordination/implementation and standardized reporting | ||||
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| Individual education and mobilization adhering to COVID-19 prevention practices | ||||
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| New sites identified for PrEP | |||
| Doctor networks identified and contracted for service implementation | ||||
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| Retrained staff for remote call center | ||||
| Community venues identified as alternative to closed/restricted schools w/COVID-19 measures | ||||
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| Scheduling initial PrEP appointments upon request by potential client once lockdown lifted | |||
| Appointment and treatment | ||||
| Extended service hours upon lifting of lockdowns | ||||
| Motivational interviewing & links to services | ||||
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| Reduced group size for program sessions adhering to COVID prevention practices | ||||
| M-groups/Clinicians at M-groups for follow up appointments | ||||
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| Extended Call Centre expansion of staff and services | ||||
| Call center for follow up & obtaining PrEP commitments for uptake upon visits being allowed | ||||
| Key Population (KP) targeted video clips and live interviews over social media | ||||
| Radio coverage | ||||
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| PrEP commodity tracking | |||
| Continuous quality improvement site activities | ||||
| Data reviews to identify implementation gaps (reasons for declining PrEP or missed appointments) | ||||
| PrEP technical working group worked with Ministry of Health to revise national PrEP guidelines to provide a more favorable policy environment for AGYW and pregnant/breast-feeding women | ||||
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| Routine HIV tests at one- and -three-months follow-up | |||
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| Community distribution points & refills at key population (KP)-friendly drop-in centers in KP hotspots | ||||
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| Peer leaders providing door-to-door refills | ||||
| Continuation of risk screening tools, client enrollment, counseling, follow-ups, and retesting | ||||
| Flexible clinic hours for community refills | ||||
| KP Civil Society Organization (CSO) follow-ups for those who missed appointments | ||||
| Peer support meetings | ||||
| KP CSO delivering refills | ||||
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| Demand creation with CSOs such as peer-led dialogues | |||
| Print media used | ||||
| Site outreach and client referrals | ||||
Acronyms = KP: Key population, FY: Fiscal year, MMD: Multi-Month Dispensing, CSO: Civil-society Organization, AGYW: Adolescent girls and young women
IEC: Information, educational and communication.
Color coding = : management and policy; : service delivery; : communication and outreach.
*Some reported adaptations as both implemented and planned without further clarity. Adaptations reported in PrEP_CURR & PrEP_NEW narratives are counted twice here.
Fig 3Pre-exposure prophylaxis (PrEP) need met in PEPFAR-supported countries, by pre-COVID-19 and COVID-19 time periods and by country.